From 1aed5e1bbd7562e27166f24134904e37140c818c Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 2 Jun 2026 17:45:19 -0700 Subject: [PATCH 01/92] test(proxy/utils): pin bottom-of-file helper behavior (#29509) * test(proxy/utils): pin bottom-of-file helper behavior Pin current behavior of the bottom-of-file pure-function helpers in litellm/proxy/utils.py (projection, team config, time helpers, guardrail merge, error helpers, URL/path helpers, premium gate, model access, and misc DB/API-key helpers). Adds tests/test_litellm/proxy/utils/helpers/ with one happy + one error test per pinned symbol; folds the prior single-test tests/test_litellm/proxy/test_utils.py into test_url_helpers.py and deletes the old file. _pin_check.py and _coverage_check.py serve as local stopping gates. Adds tests/test_litellm/proxy/utils to the existing test-path block in .github/workflows/test-unit-proxy-endpoints.yml. Plan: https://www.notion.so/37343b8acdab81f68f39f66915f62bcf Pin list: https://www.notion.so/37343b8acdab8150acdbf40e5756869f * test(proxy/utils): apply greptile fixes to behavior-pinning gates Address findings from the sibling PR1/PR2 greptile reviews that also apply to this PR: - Commit pin_list.txt alongside the gate script (was previously a gitignored .pin_list.txt fetched from Notion). The gate is now reproducible without out-of-band setup. - Resolve the coverage region by locating the first pinned symbol's def line in litellm/proxy/utils.py at runtime, instead of hardcoded line numbers that drift when lines above shift. - Word-boundary the pin reference check so pins like update_spend do not falsely match update_spend_logs_job. - Drop the dead _harness_smoke_test.py exclusion; the test_*.py glob already filters underscore-prefixed files. * test(proxy/utils): drop local-only stopping-signal scripts Remove _pin_check.py, _coverage_check.py, and pin_list.txt. These were dev-time tooling for knowing when test authoring was done; they are not wired into CI and the test files themselves are the merge artifact. --------- Co-authored-by: Claude --- .../workflows/test-unit-proxy-endpoints.yml | 1 + tests/test_litellm/proxy/test_utils.py | 22 - tests/test_litellm/proxy/utils/__init__.py | 0 .../proxy/utils/helpers/__init__.py | 0 .../proxy/utils/helpers/test_error_helpers.py | 173 ++++++++ .../utils/helpers/test_guardrail_merge.py | 201 +++++++++ .../proxy/utils/helpers/test_misc_helpers.py | 201 +++++++++ .../proxy/utils/helpers/test_model_access.py | 406 ++++++++++++++++++ .../helpers/test_month_end_projection.py | 232 ++++++++++ .../utils/helpers/test_premium_user_check.py | 77 ++++ .../proxy/utils/helpers/test_team_configs.py | 76 ++++ .../proxy/utils/helpers/test_to_ns.py | 59 +++ .../proxy/utils/helpers/test_url_helpers.py | 316 ++++++++++++++ 13 files changed, 1742 insertions(+), 22 deletions(-) delete mode 100644 tests/test_litellm/proxy/test_utils.py create mode 100644 tests/test_litellm/proxy/utils/__init__.py create mode 100644 tests/test_litellm/proxy/utils/helpers/__init__.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_error_helpers.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_guardrail_merge.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_misc_helpers.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_model_access.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_month_end_projection.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_premium_user_check.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_team_configs.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_to_ns.py create mode 100644 tests/test_litellm/proxy/utils/helpers/test_url_helpers.py diff --git a/.github/workflows/test-unit-proxy-endpoints.yml b/.github/workflows/test-unit-proxy-endpoints.yml index 1ce0abfc008..0a9513ec024 100644 --- a/.github/workflows/test-unit-proxy-endpoints.yml +++ b/.github/workflows/test-unit-proxy-endpoints.yml @@ -42,6 +42,7 @@ jobs: tests/test_litellm/proxy/rag_endpoints tests/test_litellm/proxy/realtime_endpoints tests/test_litellm/proxy/ui_crud_endpoints + tests/test_litellm/proxy/utils workers: 2 reruns: 2 artifact-name: proxy-endpoints diff --git a/tests/test_litellm/proxy/test_utils.py b/tests/test_litellm/proxy/test_utils.py deleted file mode 100644 index 9dfeb27f4cb..00000000000 --- a/tests/test_litellm/proxy/test_utils.py +++ /dev/null @@ -1,22 +0,0 @@ -import pytest - -from litellm.proxy.utils import _get_openapi_url - - -@pytest.mark.parametrize( - "env_vars, expected_url", - [ - ({}, "/openapi.json"), # default case - ({"NO_OPENAPI": "True"}, None), # OpenAPI disabled - ], -) -def test_get_openapi_url(monkeypatch, env_vars, expected_url): - # Clear relevant environment variables - monkeypatch.delenv("NO_OPENAPI", raising=False) - - # Set test environment variables - for key, value in env_vars.items(): - monkeypatch.setenv(key, value) - - result = _get_openapi_url() - assert result == expected_url diff --git a/tests/test_litellm/proxy/utils/__init__.py b/tests/test_litellm/proxy/utils/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/proxy/utils/helpers/__init__.py b/tests/test_litellm/proxy/utils/helpers/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/proxy/utils/helpers/test_error_helpers.py b/tests/test_litellm/proxy/utils/helpers/test_error_helpers.py new file mode 100644 index 00000000000..e73e3c151e0 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_error_helpers.py @@ -0,0 +1,173 @@ +import json + +import pytest +from fastapi import HTTPException + +from litellm.proxy._types import ProxyErrorTypes, ProxyException +from litellm.proxy.utils import get_error_message_str, handle_exception_on_proxy + + +def normalize(value): + return value + + +def test_get_error_message_str_happy_path_http_exception_with_string_detail(): + exc = HTTPException(status_code=400, detail="something went wrong") + summary = { + "result": get_error_message_str(exc), + "status_code": exc.status_code, + "is_str": True, + } + assert summary == { + "result": "something went wrong", + "status_code": 400, + "is_str": True, + } + + +def test_get_error_message_str_happy_path_http_exception_with_dict_detail(): + detail = {"error": "bad input", "code": "invalid_request"} + exc = HTTPException(status_code=422, detail=detail) + summary = { + "result": get_error_message_str(exc), + "result_parsed": json.loads(get_error_message_str(exc)), + "status_code": exc.status_code, + } + assert summary == { + "result": json.dumps(detail), + "result_parsed": detail, + "status_code": 422, + } + + +def test_get_error_message_str_happy_path_generic_exception(): + exc = ValueError("boom") + summary = { + "result": get_error_message_str(exc), + "type": type(exc).__name__, + "args": list(exc.args), + } + assert summary == { + "result": "boom", + "type": "ValueError", + "args": ["boom"], + } + + +def test_get_error_message_str_with_runtime_error(): + exc = RuntimeError("runtime explosion") + summary = { + "result": get_error_message_str(exc), + "type": type(exc).__name__, + "matches_str": str(exc) == get_error_message_str(exc), + } + assert summary == { + "result": "runtime explosion", + "type": "RuntimeError", + "matches_str": True, + } + + +def test_get_error_message_str_error_path_none_input_returns_string_none(): + summary = { + "result": get_error_message_str(None), + "is_str": isinstance(get_error_message_str(None), str), + "input": None, + } + assert summary == { + "result": "None", + "is_str": True, + "input": None, + } + + +def test_handle_exception_on_proxy_happy_path_http_exception(): + exc = HTTPException(status_code=403, detail="forbidden") + result = handle_exception_on_proxy(exc) + snapshot = { + "is_proxy_exception": isinstance(result, ProxyException), + "message": result.message, + "type": result.type, + "code": result.code, + } + assert snapshot == { + "is_proxy_exception": True, + "message": "forbidden", + "type": ProxyErrorTypes.internal_server_error.value, + "code": "403", + } + + +def test_handle_exception_on_proxy_happy_path_already_proxy_exception(): + original = ProxyException( + message="already wrapped", + type=ProxyErrorTypes.budget_exceeded.value, + param="key", + code=402, + ) + result = handle_exception_on_proxy(original) + snapshot = { + "is_same_object": result is original, + "message": result.message, + "type": result.type, + "code": result.code, + } + assert snapshot == { + "is_same_object": True, + "message": "already wrapped", + "type": ProxyErrorTypes.budget_exceeded.value, + "code": "402", + } + + +def test_handle_exception_on_proxy_happy_path_generic_exception_defaults_to_500(): + exc = ValueError("kaboom") + result = handle_exception_on_proxy(exc) + snapshot = { + "is_proxy_exception": isinstance(result, ProxyException), + "message": result.message, + "type": result.type, + "code": result.code, + "param": result.param, + } + assert snapshot == { + "is_proxy_exception": True, + "message": "kaboom", + "type": ProxyErrorTypes.internal_server_error.value, + "code": "500", + "param": "None", + } + + +def test_handle_exception_on_proxy_uses_attached_status_code_when_present(): + class _CustomErr(Exception): + status_code = 418 + + exc = _CustomErr("teapot") + result = handle_exception_on_proxy(exc) + snapshot = { + "code": result.code, + "message": result.message, + "type": result.type, + } + assert snapshot == { + "code": "418", + "message": "teapot", + "type": ProxyErrorTypes.internal_server_error.value, + } + + +def test_handle_exception_on_proxy_error_path_none_input_wraps_as_500(): + result = handle_exception_on_proxy(None) + snapshot = { + "is_proxy_exception": isinstance(result, ProxyException), + "message": result.message, + "code": result.code, + "type": result.type, + } + assert snapshot == { + "is_proxy_exception": True, + "message": "None", + "code": "500", + "type": ProxyErrorTypes.internal_server_error.value, + } diff --git a/tests/test_litellm/proxy/utils/helpers/test_guardrail_merge.py b/tests/test_litellm/proxy/utils/helpers/test_guardrail_merge.py new file mode 100644 index 00000000000..117484d61a4 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_guardrail_merge.py @@ -0,0 +1,201 @@ +from types import SimpleNamespace +from unittest.mock import MagicMock + +import pytest + +from litellm.proxy.utils import ( + _check_and_merge_model_level_guardrails, + _merge_guardrails_with_existing, +) + + +def normalize(value): + return value + + +def _router_with_deployment(guardrails): + deployment = SimpleNamespace(litellm_params={"guardrails": guardrails}) + router = MagicMock() + router.get_deployment.return_value = deployment + return router + + +def _router_without_deployment(): + router = MagicMock() + router.get_deployment.return_value = None + return router + + +def test_check_and_merge_model_level_guardrails_happy_path_merges_lists(): + router = _router_with_deployment(["pii-redact", "toxic-filter"]) + data = { + "model": "gpt-4o", + "metadata": { + "model_info": {"id": "deployment-123"}, + "guardrails": ["user-policy"], + }, + } + result = _check_and_merge_model_level_guardrails(data, router) + snapshot = { + "model": result["model"], + "model_info_id": result["metadata"]["model_info"]["id"], + "guardrails_sorted": sorted(result["metadata"]["guardrails"]), + } + assert snapshot == { + "model": "gpt-4o", + "model_info_id": "deployment-123", + "guardrails_sorted": ["pii-redact", "toxic-filter", "user-policy"], + } + + +def test_check_and_merge_model_level_guardrails_returns_data_when_router_none(): + data = {"metadata": {"model_info": {"id": "x"}}, "model": "m", "other": 1} + result = _check_and_merge_model_level_guardrails(data, None) + assert result is data + assert normalize(result) == { + "metadata": {"model_info": {"id": "x"}}, + "model": "m", + "other": 1, + } + + +def test_check_and_merge_model_level_guardrails_returns_data_when_model_id_missing(): + router = _router_with_deployment(["pii"]) + data = {"metadata": {"model_info": {}}, "model": "m", "extra": "v"} + result = _check_and_merge_model_level_guardrails(data, router) + snapshot = { + "is_same_object": result is data, + "metadata": result["metadata"], + "model": result["model"], + "extra": result["extra"], + } + assert snapshot == { + "is_same_object": True, + "metadata": {"model_info": {}}, + "model": "m", + "extra": "v", + } + router.get_deployment.assert_not_called() + + +def test_check_and_merge_model_level_guardrails_returns_data_when_deployment_none(): + router = _router_without_deployment() + data = {"metadata": {"model_info": {"id": "x"}}, "model": "m"} + result = _check_and_merge_model_level_guardrails(data, router) + assert result is data + + +def test_check_and_merge_model_level_guardrails_returns_data_when_guardrails_none(): + router = _router_with_deployment(None) + data = {"metadata": {"model_info": {"id": "x"}}, "model": "m"} + result = _check_and_merge_model_level_guardrails(data, router) + assert result is data + + +def test_check_and_merge_model_level_guardrails_handles_missing_metadata(): + router = _router_with_deployment(["pii"]) + data = {"model": "m"} + result = _check_and_merge_model_level_guardrails(data, router) + snapshot = { + "is_same_object": result is data, + "model": result["model"], + "metadata_present": "metadata" in result, + } + assert snapshot == { + "is_same_object": True, + "model": "m", + "metadata_present": False, + } + + +def test_check_and_merge_model_level_guardrails_raises_when_metadata_is_not_dict(): + router = _router_with_deployment(["pii"]) + data = {"metadata": "not-a-dict", "model": "m"} + with pytest.raises(AttributeError): + _check_and_merge_model_level_guardrails(data, router) + + +def test_merge_guardrails_with_existing_happy_path_combines_lists(): + data = { + "metadata": {"guardrails": ["a", "b"], "user": "u"}, + "model": "m", + } + result = _merge_guardrails_with_existing(data, ["c", "a"]) + snapshot = { + "guardrails_sorted": sorted(result["metadata"]["guardrails"]), + "user": result["metadata"]["user"], + "model": result["model"], + "is_copy": result is not data, + } + assert snapshot == { + "guardrails_sorted": ["a", "b", "c"], + "user": "u", + "model": "m", + "is_copy": True, + } + + +def test_merge_guardrails_with_existing_wraps_scalar_existing_guardrail(): + data = {"metadata": {"guardrails": "single-policy"}} + result = _merge_guardrails_with_existing(data, ["model-policy"]) + snapshot = { + "guardrails_sorted": sorted(result["metadata"]["guardrails"]), + "is_list": isinstance(result["metadata"]["guardrails"], list), + "count": len(result["metadata"]["guardrails"]), + } + assert snapshot == { + "guardrails_sorted": ["model-policy", "single-policy"], + "is_list": True, + "count": 2, + } + + +def test_merge_guardrails_with_existing_wraps_scalar_model_guardrail(): + data = {"metadata": {}} + result = _merge_guardrails_with_existing(data, "model-policy") + snapshot = { + "guardrails": result["metadata"]["guardrails"], + "is_list": isinstance(result["metadata"]["guardrails"], list), + "count": len(result["metadata"]["guardrails"]), + } + assert snapshot == { + "guardrails": ["model-policy"], + "is_list": True, + "count": 1, + } + + +def test_merge_guardrails_with_existing_empty_existing_empty_model_yields_empty(): + data = {"metadata": {"guardrails": None}} + result = _merge_guardrails_with_existing(data, None) + snapshot = { + "guardrails": result["metadata"]["guardrails"], + "is_list": isinstance(result["metadata"]["guardrails"], list), + "count": len(result["metadata"]["guardrails"]), + } + assert snapshot == { + "guardrails": [], + "is_list": True, + "count": 0, + } + + +def test_merge_guardrails_with_existing_creates_metadata_when_missing(): + data = {"model": "m"} + result = _merge_guardrails_with_existing(data, ["g1"]) + snapshot = { + "guardrails": result["metadata"]["guardrails"], + "model_preserved": result["model"], + "original_data_unchanged": "metadata" not in data, + } + assert snapshot == { + "guardrails": ["g1"], + "model_preserved": "m", + "original_data_unchanged": True, + } + + +def test_merge_guardrails_with_existing_raises_on_unhashable_guardrail(): + data = {"metadata": {"guardrails": [{"unhashable": True}]}} + with pytest.raises(TypeError): + _merge_guardrails_with_existing(data, ["g1"]) diff --git a/tests/test_litellm/proxy/utils/helpers/test_misc_helpers.py b/tests/test_litellm/proxy/utils/helpers/test_misc_helpers.py new file mode 100644 index 00000000000..7968fa40655 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_misc_helpers.py @@ -0,0 +1,201 @@ +import pytest +from fastapi import HTTPException + +from litellm.proxy.utils import ( + construct_database_url_from_env_vars, + get_prisma_client_or_throw, + is_valid_api_key, +) + + +def normalize(value): + return value + + +def test_get_prisma_client_or_throw_happy_path_returns_client(monkeypatch): + sentinel = object() + import litellm.proxy.proxy_server as ps + + monkeypatch.setattr(ps, "prisma_client", sentinel, raising=False) + result = get_prisma_client_or_throw("some message") + summary = { + "is_sentinel": result is sentinel, + "message_arg": "some message", + "raised": False, + } + assert summary == { + "is_sentinel": True, + "message_arg": "some message", + "raised": False, + } + + +def test_get_prisma_client_or_throw_raises_when_client_none(monkeypatch): + import litellm.proxy.proxy_server as ps + + monkeypatch.setattr(ps, "prisma_client", None, raising=False) + with pytest.raises(HTTPException) as exc_info: + get_prisma_client_or_throw("db not connected") + snapshot = { + "status_code": exc_info.value.status_code, + "is_dict_detail": isinstance(exc_info.value.detail, dict), + "error_message": exc_info.value.detail["error"], + } + assert snapshot == { + "status_code": 500, + "is_dict_detail": True, + "error_message": "db not connected", + } + + +def test_is_valid_api_key_happy_path_sk_prefix(): + summary = { + "result": is_valid_api_key("sk-abc123_XYZ-456"), + "key": "sk-abc123_XYZ-456", + "len": len("sk-abc123_XYZ-456"), + } + assert summary == { + "result": True, + "key": "sk-abc123_XYZ-456", + "len": 17, + } + + +def test_is_valid_api_key_happy_path_hashed_64_hex(): + key = "a" * 64 + summary = { + "result": is_valid_api_key(key), + "key_len": len(key), + "is_hex": True, + } + assert summary == { + "result": True, + "key_len": 64, + "is_hex": True, + } + + +def test_is_valid_api_key_happy_path_mixed_case_hex(): + key = "AbCdEf0123456789" * 4 + summary = { + "result": is_valid_api_key(key), + "key_len": len(key), + "first": key[0], + } + assert summary == { + "result": True, + "key_len": 64, + "first": "A", + } + + +def test_is_valid_api_key_error_path_too_long(): + assert is_valid_api_key("sk-" + "a" * 200) is False + + +def test_is_valid_api_key_error_path_non_string(): + assert is_valid_api_key(12345) is False # type: ignore[arg-type] + + +def test_is_valid_api_key_error_path_invalid_format(): + assert is_valid_api_key("not-a-valid-key-format!!!!") is False + + +def test_is_valid_api_key_error_path_too_short(): + assert is_valid_api_key("sk") is False + + +def test_construct_database_url_from_env_vars_happy_path_full(monkeypatch): + monkeypatch.setenv("DATABASE_HOST", "db.example.com") + monkeypatch.setenv("DATABASE_USERNAME", "user") + monkeypatch.setenv("DATABASE_PASSWORD", "pass") + monkeypatch.setenv("DATABASE_NAME", "litellm") + monkeypatch.delenv("DATABASE_SCHEMA", raising=False) + result = construct_database_url_from_env_vars() + summary = { + "result": result, + "host": "db.example.com", + "scheme": result.split("://", 1)[0] if result else None, + "has_password": "pass" in (result or ""), + } + assert summary == { + "result": "postgresql://user:pass@db.example.com/litellm", + "host": "db.example.com", + "scheme": "postgresql", + "has_password": True, + } + + +def test_construct_database_url_from_env_vars_happy_path_no_password(monkeypatch): + monkeypatch.setenv("DATABASE_HOST", "db.example.com") + monkeypatch.setenv("DATABASE_USERNAME", "user") + monkeypatch.delenv("DATABASE_PASSWORD", raising=False) + monkeypatch.setenv("DATABASE_NAME", "litellm") + monkeypatch.delenv("DATABASE_SCHEMA", raising=False) + result = construct_database_url_from_env_vars() + summary = { + "result": result, + "no_colon_password": ":pass@" not in (result or ""), + "host": "db.example.com", + "user": "user", + } + assert summary == { + "result": "postgresql://user@db.example.com/litellm", + "no_colon_password": True, + "host": "db.example.com", + "user": "user", + } + + +def test_construct_database_url_from_env_vars_special_chars_encoded(monkeypatch): + monkeypatch.setenv("DATABASE_HOST", "db.example.com") + monkeypatch.setenv("DATABASE_USERNAME", "us er@x") + monkeypatch.setenv("DATABASE_PASSWORD", "p@ss/word") + monkeypatch.setenv("DATABASE_NAME", "lite/llm") + monkeypatch.delenv("DATABASE_SCHEMA", raising=False) + result = construct_database_url_from_env_vars() + summary = { + "result": result, + "username_encoded": "us+er%40x" in result, + "password_encoded": "p%40ss%2Fword" in result, + "name_encoded": "lite%2Fllm" in result, + } + assert summary == { + "result": "postgresql://us+er%40x:p%40ss%2Fword@db.example.com/lite%2Fllm", + "username_encoded": True, + "password_encoded": True, + "name_encoded": True, + } + + +def test_construct_database_url_from_env_vars_with_schema(monkeypatch): + monkeypatch.setenv("DATABASE_HOST", "db.example.com") + monkeypatch.setenv("DATABASE_USERNAME", "user") + monkeypatch.setenv("DATABASE_PASSWORD", "pass") + monkeypatch.setenv("DATABASE_NAME", "litellm") + monkeypatch.setenv("DATABASE_SCHEMA", "public") + result = construct_database_url_from_env_vars() + summary = { + "result": result, + "schema_appended": result.endswith("?schema=public"), + "host": "db.example.com", + } + assert summary == { + "result": "postgresql://user:pass@db.example.com/litellm?schema=public", + "schema_appended": True, + "host": "db.example.com", + } + + +def test_construct_database_url_from_env_vars_error_path_missing_host(monkeypatch): + monkeypatch.delenv("DATABASE_HOST", raising=False) + monkeypatch.setenv("DATABASE_USERNAME", "user") + monkeypatch.setenv("DATABASE_NAME", "litellm") + assert construct_database_url_from_env_vars() is None + + +def test_construct_database_url_from_env_vars_error_path_missing_username(monkeypatch): + monkeypatch.setenv("DATABASE_HOST", "db.example.com") + monkeypatch.delenv("DATABASE_USERNAME", raising=False) + monkeypatch.setenv("DATABASE_NAME", "litellm") + assert construct_database_url_from_env_vars() is None diff --git a/tests/test_litellm/proxy/utils/helpers/test_model_access.py b/tests/test_litellm/proxy/utils/helpers/test_model_access.py new file mode 100644 index 00000000000..b8e4013c960 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_model_access.py @@ -0,0 +1,406 @@ +from unittest.mock import MagicMock + +import pytest +from fastapi import HTTPException + +import litellm +from litellm import ModelResponse +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.utils import ( + create_model_info_response, + get_available_models_for_user, + is_known_model, + is_known_vector_store_index, + model_dump_with_preserved_fields, + validate_model_access, +) + + +def normalize(value): + return value + + +def _router_with_models(model_names): + router = MagicMock() + router.get_model_names.return_value = model_names + router.get_model_access_groups.return_value = {} + return router + + +def test_is_known_model_happy_path_returns_true_when_in_router(): + router = _router_with_models(["gpt-4o", "claude-haiku"]) + summary = { + "result": is_known_model("gpt-4o", router), + "model": "gpt-4o", + "router_models": ["gpt-4o", "claude-haiku"], + } + assert summary == { + "result": True, + "model": "gpt-4o", + "router_models": ["gpt-4o", "claude-haiku"], + } + + +def test_is_known_model_returns_false_when_not_in_router(): + router = _router_with_models(["gpt-4o"]) + summary = { + "result": is_known_model("claude-haiku", router), + "model": "claude-haiku", + "router_models": ["gpt-4o"], + } + assert summary == { + "result": False, + "model": "claude-haiku", + "router_models": ["gpt-4o"], + } + + +def test_is_known_model_error_path_none_model(): + router = _router_with_models(["gpt-4o"]) + assert is_known_model(None, router) is False + + +def test_is_known_model_error_path_none_router(): + assert is_known_model("gpt-4o", None) is False + + +def test_is_known_vector_store_index_happy_path(monkeypatch): + registry = MagicMock() + registry.get_vector_store_indexes.return_value = ["index-a", "index-b"] + monkeypatch.setattr(litellm, "vector_store_index_registry", registry) + summary = { + "result": is_known_vector_store_index("index-a"), + "indexes": ["index-a", "index-b"], + "input": "index-a", + } + assert summary == { + "result": True, + "indexes": ["index-a", "index-b"], + "input": "index-a", + } + + +def test_is_known_vector_store_index_returns_false_when_missing(monkeypatch): + registry = MagicMock() + registry.get_vector_store_indexes.return_value = ["index-a"] + monkeypatch.setattr(litellm, "vector_store_index_registry", registry) + summary = { + "result": is_known_vector_store_index("missing"), + "indexes": ["index-a"], + "input": "missing", + } + assert summary == { + "result": False, + "indexes": ["index-a"], + "input": "missing", + } + + +def test_is_known_vector_store_index_error_path_no_registry(monkeypatch): + monkeypatch.setattr(litellm, "vector_store_index_registry", None) + assert is_known_vector_store_index("anything") is False + + +def test_create_model_info_response_happy_path_no_metadata(): + result = create_model_info_response(model_id="gpt-4o", provider="openai") + assert result == { + "id": "gpt-4o", + "object": "model", + "created": result["created"], + "owned_by": "openai", + } + snapshot = { + "id": result["id"], + "object": result["object"], + "owned_by": result["owned_by"], + "created_is_int": isinstance(result["created"], int), + "metadata_absent": "metadata" not in result, + } + assert snapshot == { + "id": "gpt-4o", + "object": "model", + "owned_by": "openai", + "created_is_int": True, + "metadata_absent": True, + } + + +def test_create_model_info_response_with_metadata_default_general(monkeypatch): + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_all_fallbacks", + lambda **_kwargs: [{"model": "fallback-1"}], + ) + result = create_model_info_response( + model_id="gpt-4o", + provider="openai", + include_metadata=True, + ) + snapshot = { + "id": result["id"], + "owned_by": result["owned_by"], + "object": result["object"], + "fallbacks": result["metadata"]["fallbacks"], + } + assert snapshot == { + "id": "gpt-4o", + "owned_by": "openai", + "object": "model", + "fallbacks": [{"model": "fallback-1"}], + } + + +def test_create_model_info_response_with_explicit_fallback_type(monkeypatch): + captured = {} + + def _capture(model, llm_router, fallback_type): + captured["fallback_type"] = fallback_type + return ["x"] + + monkeypatch.setattr("litellm.proxy.auth.model_checks.get_all_fallbacks", _capture) + result = create_model_info_response( + model_id="gpt-4o", + provider="openai", + include_metadata=True, + fallback_type="context_window", + ) + snapshot = { + "id": result["id"], + "fallbacks": result["metadata"]["fallbacks"], + "captured_fallback_type": captured["fallback_type"], + "owned_by": result["owned_by"], + } + assert snapshot == { + "id": "gpt-4o", + "fallbacks": ["x"], + "captured_fallback_type": "context_window", + "owned_by": "openai", + } + + +def test_create_model_info_response_invalid_fallback_type_raises(): + with pytest.raises(HTTPException) as exc_info: + create_model_info_response( + model_id="gpt-4o", + provider="openai", + include_metadata=True, + fallback_type="bogus", + ) + assert exc_info.value.status_code == 400 + assert "Invalid fallback_type" in str(exc_info.value.detail) + + +def test_validate_model_access_happy_path_single_model_in_list(): + summary = { + "result": validate_model_access("gpt-4o", ["gpt-4o", "claude-haiku"]), + "model": "gpt-4o", + "available": ["gpt-4o", "claude-haiku"], + } + assert summary == { + "result": None, + "model": "gpt-4o", + "available": ["gpt-4o", "claude-haiku"], + } + + +def test_validate_model_access_happy_path_batch_all_accessible(): + summary = { + "result": validate_model_access( + "gpt-4o,claude-haiku", ["gpt-4o", "claude-haiku", "gemini"] + ), + "input": "gpt-4o,claude-haiku", + "available": ["gpt-4o", "claude-haiku", "gemini"], + } + assert summary == { + "result": None, + "input": "gpt-4o,claude-haiku", + "available": ["gpt-4o", "claude-haiku", "gemini"], + } + + +def test_validate_model_access_single_model_not_accessible_raises(): + with pytest.raises(HTTPException) as exc_info: + validate_model_access("missing-model", ["gpt-4o"]) + assert exc_info.value.status_code == 404 + assert "missing-model" in str(exc_info.value.detail) + + +def test_validate_model_access_batch_partial_inaccessible_raises(): + with pytest.raises(HTTPException) as exc_info: + validate_model_access("gpt-4o,unknown-x", ["gpt-4o"]) + assert exc_info.value.status_code == 404 + assert "unknown-x" in str(exc_info.value.detail) + assert "gpt-4o" not in str(exc_info.value.detail).split("not accessible:")[1] + + +def _make_model_response(): + return ModelResponse( + id="resp-123", + choices=[ + { + "message": { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": {"name": "do_thing", "arguments": "{}"}, + } + ], + }, + "index": 0, + "finish_reason": "tool_calls", + } + ], + model="gpt-4o", + ) + + +def test_model_dump_with_preserved_fields_restores_none_content(): + resp = _make_model_response() + result = model_dump_with_preserved_fields(resp) + message = result["choices"][0]["message"] + snapshot = { + "content_is_none": message["content"] is None, + "role": message["role"], + "has_tool_calls": "tool_calls" in message, + "model": result["model"], + } + assert snapshot == { + "content_is_none": True, + "role": "assistant", + "has_tool_calls": True, + "model": "gpt-4o", + } + + +def test_model_dump_with_preserved_fields_no_choices_returns_plain_dump(): + class _Bare: + def model_dump(self, **_kwargs): + return {"id": "x", "object": "y", "extra": "z"} + + bare = _Bare() + result = model_dump_with_preserved_fields(bare) + assert result == {"id": "x", "object": "y", "extra": "z"} + + +def test_model_dump_with_preserved_fields_error_path_invalid_obj_raises(): + with pytest.raises(AttributeError): + model_dump_with_preserved_fields(None) + + +@pytest.mark.asyncio +async def test_get_available_models_for_user_happy_path_returns_complete_list( + monkeypatch, +): + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_key_models", + lambda **_k: ["gpt-4o"], + ) + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_team_models", + lambda **_k: ["claude-haiku"], + ) + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_complete_model_list", + lambda **_k: ["gpt-4o", "claude-haiku", "gemini"], + ) + router = _router_with_models(["gpt-4o", "claude-haiku", "gemini"]) + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test-key", + user_id="user-1", + team_id=None, + team_models=[], + ) + result = await get_available_models_for_user( + user_api_key_dict=user_api_key_dict, + llm_router=router, + general_settings={}, + user_model=None, + ) + summary = { + "result_sorted": sorted(result), + "count": len(result), + "user_id": user_api_key_dict.user_id, + "router_set": True, + } + assert summary == { + "result_sorted": ["claude-haiku", "gemini", "gpt-4o"], + "count": 3, + "user_id": "user-1", + "router_set": True, + } + + +@pytest.mark.asyncio +async def test_get_available_models_for_user_with_none_router(monkeypatch): + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_key_models", + lambda **_k: [], + ) + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_team_models", + lambda **_k: [], + ) + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_complete_model_list", + lambda **_k: ["user-model"], + ) + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test-key", + user_id="user-1", + team_id=None, + team_models=[], + ) + result = await get_available_models_for_user( + user_api_key_dict=user_api_key_dict, + llm_router=None, + general_settings={}, + user_model="user-model", + ) + summary = { + "result": result, + "router_is_none": True, + "user_model": "user-model", + "count": len(result), + } + assert summary == { + "result": ["user-model"], + "router_is_none": True, + "user_model": "user-model", + "count": 1, + } + + +@pytest.mark.asyncio +async def test_get_available_models_for_user_error_path_complete_list_raises( + monkeypatch, +): + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_key_models", + lambda **_k: [], + ) + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_team_models", + lambda **_k: [], + ) + + def _boom(**_kwargs): + raise RuntimeError("downstream failure") + + monkeypatch.setattr( + "litellm.proxy.auth.model_checks.get_complete_model_list", _boom + ) + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test-key", + user_id="user-1", + team_id=None, + team_models=[], + ) + with pytest.raises(RuntimeError): + await get_available_models_for_user( + user_api_key_dict=user_api_key_dict, + llm_router=None, + general_settings={}, + user_model=None, + ) diff --git a/tests/test_litellm/proxy/utils/helpers/test_month_end_projection.py b/tests/test_litellm/proxy/utils/helpers/test_month_end_projection.py new file mode 100644 index 00000000000..5afe1f4faf8 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_month_end_projection.py @@ -0,0 +1,232 @@ +from datetime import date, timedelta + +import pytest + +from litellm.proxy.utils import ( + _get_month_end_date, + _get_projected_spend_over_limit, + _is_projected_spend_over_limit, +) + + +def normalize(value): + return value + + +def _freeze_today(monkeypatch, frozen): + class _FrozenDate(date): + @classmethod + def today(cls): + return frozen + + monkeypatch.setattr("litellm.proxy.utils.date", _FrozenDate) + + +@pytest.mark.parametrize( + "today, expected", + [ + (date(2024, 1, 15), date(2024, 1, 31)), + (date(2024, 2, 1), date(2024, 2, 29)), + (date(2023, 2, 1), date(2023, 2, 28)), + (date(2024, 4, 10), date(2024, 4, 30)), + (date(2024, 12, 1), date(2024, 12, 31)), + ], +) +def test_get_month_end_date_happy_path(today, expected): + result = _get_month_end_date(today) + assert normalize( + { + "year": result.year, + "month": result.month, + "day": result.day, + "expected": expected.isoformat(), + "input": today.isoformat(), + } + ) == { + "year": expected.year, + "month": expected.month, + "day": expected.day, + "expected": expected.isoformat(), + "input": today.isoformat(), + } + + +def test_get_month_end_date_raises_on_non_date_input(): + with pytest.raises(AttributeError): + _get_month_end_date("2024-01-15") + + +def test_is_projected_spend_over_limit_happy_path_under_budget(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 11)) + summary = { + "result": _is_projected_spend_over_limit( + current_spend=10.0, soft_budget_limit=1_000_000.0 + ), + "current_spend": 10.0, + "soft_budget_limit": 1_000_000.0, + } + assert summary == { + "result": False, + "current_spend": 10.0, + "soft_budget_limit": 1_000_000.0, + } + + +def test_is_projected_spend_over_limit_happy_path_over_budget(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 11)) + summary = { + "result": _is_projected_spend_over_limit( + current_spend=100.0, soft_budget_limit=50.0 + ), + "current_spend": 100.0, + "soft_budget_limit": 50.0, + } + assert summary == { + "result": True, + "current_spend": 100.0, + "soft_budget_limit": 50.0, + } + + +def test_is_projected_spend_over_limit_first_of_month_no_division_by_zero(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 1)) + summary = { + "result": _is_projected_spend_over_limit( + current_spend=5.0, soft_budget_limit=10.0 + ), + "current_spend": 5.0, + "soft_budget_limit": 10.0, + } + assert summary == { + "result": True, + "current_spend": 5.0, + "soft_budget_limit": 10.0, + } + + +def test_is_projected_spend_over_limit_none_limit_returns_false(): + assert ( + _is_projected_spend_over_limit(current_spend=10_000.0, soft_budget_limit=None) + is False + ) + + +def test_is_projected_spend_over_limit_raises_when_today_missing(monkeypatch): + class _Broken: + @classmethod + def today(cls): + raise RuntimeError("clock unavailable") + + monkeypatch.setattr("litellm.proxy.utils.date", _Broken) + with pytest.raises(RuntimeError): + _is_projected_spend_over_limit(current_spend=1.0, soft_budget_limit=1.0) + + +def test_get_projected_spend_over_limit_happy_path_over_budget(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 11)) + result = _get_projected_spend_over_limit( + current_spend=100.0, soft_budget_limit=50.0 + ) + assert result is not None + projected, exceed_date = result + summary = { + "projected_spend": projected, + "exceed_date": exceed_date.isoformat(), + "current_spend": 100.0, + "soft_budget_limit": 50.0, + } + assert summary == { + "projected_spend": 300.0, + "exceed_date": "2024-01-11", + "current_spend": 100.0, + "soft_budget_limit": 50.0, + } + + +def test_get_projected_spend_over_limit_first_of_month_uses_current_as_daily( + monkeypatch, +): + _freeze_today(monkeypatch, date(2024, 1, 1)) + result = _get_projected_spend_over_limit(current_spend=5.0, soft_budget_limit=10.0) + assert result is not None + projected, exceed_date = result + expected_exceed = date(2024, 1, 1) + timedelta(days=1.0) + summary = { + "projected_spend": projected, + "exceed_date": exceed_date.isoformat(), + "expected_exceed_date": expected_exceed.isoformat(), + "soft_budget_limit": 10.0, + } + assert summary == { + "projected_spend": 155.0, + "exceed_date": expected_exceed.isoformat(), + "expected_exceed_date": expected_exceed.isoformat(), + "soft_budget_limit": 10.0, + } + + +def test_get_projected_spend_over_limit_zero_daily_spend_exceed_today(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 11)) + result = _get_projected_spend_over_limit(current_spend=0.0, soft_budget_limit=-1.0) + assert result is not None + projected, exceed_date = result + summary = { + "projected_spend": projected, + "exceed_date": exceed_date.isoformat(), + "soft_budget_limit": -1.0, + } + assert summary == { + "projected_spend": 0.0, + "exceed_date": "2024-01-11", + "soft_budget_limit": -1.0, + } + + +def test_get_projected_spend_over_limit_under_budget_returns_none(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 11)) + assert ( + _get_projected_spend_over_limit( + current_spend=1.0, soft_budget_limit=1_000_000.0 + ) + is None + ) + + +def test_get_projected_spend_over_limit_exceed_date_uses_remaining_budget(monkeypatch): + _freeze_today(monkeypatch, date(2024, 1, 11)) + result = _get_projected_spend_over_limit(current_spend=20.0, soft_budget_limit=30.0) + assert result is not None + projected, exceed_date = result + daily = 20.0 / 10 + remaining_budget = 30.0 - 20.0 + expected_exceed = date(2024, 1, 11) + timedelta(days=remaining_budget / daily) + summary = { + "projected_spend": projected, + "exceed_date": exceed_date.isoformat(), + "expected_exceed_date": expected_exceed.isoformat(), + "soft_budget_limit": 30.0, + } + assert summary == { + "projected_spend": 60.0, + "exceed_date": expected_exceed.isoformat(), + "expected_exceed_date": expected_exceed.isoformat(), + "soft_budget_limit": 30.0, + } + + +def test_get_projected_spend_over_limit_none_limit_returns_none(): + assert ( + _get_projected_spend_over_limit(current_spend=1.0, soft_budget_limit=None) + is None + ) + + +def test_get_projected_spend_over_limit_raises_when_today_missing(monkeypatch): + class _Broken: + @classmethod + def today(cls): + raise RuntimeError("clock unavailable") + + monkeypatch.setattr("litellm.proxy.utils.date", _Broken) + with pytest.raises(RuntimeError): + _get_projected_spend_over_limit(current_spend=1.0, soft_budget_limit=1.0) diff --git a/tests/test_litellm/proxy/utils/helpers/test_premium_user_check.py b/tests/test_litellm/proxy/utils/helpers/test_premium_user_check.py new file mode 100644 index 00000000000..0a9539c6dc3 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_premium_user_check.py @@ -0,0 +1,77 @@ +import pytest +from fastapi import HTTPException + +from litellm.proxy.utils import _premium_user_check + + +def normalize(value): + return value + + +def test_premium_user_check_happy_path_no_raise_when_premium(monkeypatch): + import litellm.proxy.proxy_server as ps + + monkeypatch.setattr(ps, "premium_user", True, raising=False) + summary = { + "result": _premium_user_check(), + "premium_user": True, + "raised": False, + } + assert summary == { + "result": None, + "premium_user": True, + "raised": False, + } + + +def test_premium_user_check_happy_path_with_feature_no_raise(monkeypatch): + import litellm.proxy.proxy_server as ps + + monkeypatch.setattr(ps, "premium_user", True, raising=False) + summary = { + "result": _premium_user_check(feature="model-routing"), + "premium_user": True, + "feature": "model-routing", + } + assert summary == { + "result": None, + "premium_user": True, + "feature": "model-routing", + } + + +def test_premium_user_check_raises_when_not_premium(monkeypatch): + import litellm.proxy.proxy_server as ps + + monkeypatch.setattr(ps, "premium_user", False, raising=False) + with pytest.raises(HTTPException) as exc_info: + _premium_user_check() + snapshot = { + "status_code": exc_info.value.status_code, + "is_dict_detail": isinstance(exc_info.value.detail, dict), + "has_error_key": "error" in exc_info.value.detail, + } + assert snapshot == { + "status_code": 403, + "is_dict_detail": True, + "has_error_key": True, + } + + +def test_premium_user_check_raises_with_feature_message(monkeypatch): + import litellm.proxy.proxy_server as ps + + monkeypatch.setattr(ps, "premium_user", False, raising=False) + with pytest.raises(HTTPException) as exc_info: + _premium_user_check(feature="custom-callbacks") + error_msg = exc_info.value.detail["error"] + snapshot = { + "status_code": exc_info.value.status_code, + "feature_in_message": "custom-callbacks" in error_msg, + "enterprise_in_message": "LiteLLM Enterprise" in error_msg, + } + assert snapshot == { + "status_code": 403, + "feature_in_message": True, + "enterprise_in_message": True, + } diff --git a/tests/test_litellm/proxy/utils/helpers/test_team_configs.py b/tests/test_litellm/proxy/utils/helpers/test_team_configs.py new file mode 100644 index 00000000000..0e0906892b0 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_team_configs.py @@ -0,0 +1,76 @@ +import pytest + +from litellm.proxy.utils import _is_valid_team_configs + + +def normalize(value): + return value + + +def test_is_valid_team_configs_happy_path_allowed_model_mutates_config(): + team_config = {"models": ["gpt-4o", "gpt-4o-mini"], "max_budget": 100.0} + request_data = {"model": "gpt-4o"} + snapshot = { + "result": _is_valid_team_configs( + team_id="team-1", + team_config=team_config, + request_data=request_data, + ), + "models_popped": "models" not in team_config, + "remaining_keys": sorted(team_config.keys()), + } + assert snapshot == { + "result": None, + "models_popped": True, + "remaining_keys": ["max_budget"], + } + + +def test_is_valid_team_configs_no_models_key_is_noop(): + team_config = {"max_budget": 100.0, "tpm_limit": 1000} + request_data = {"model": "anything"} + snapshot = { + "result": _is_valid_team_configs( + team_id="team-1", + team_config=team_config, + request_data=request_data, + ), + "team_config": team_config, + "request_data": request_data, + } + assert snapshot == { + "result": None, + "team_config": {"max_budget": 100.0, "tpm_limit": 1000}, + "request_data": {"model": "anything"}, + } + + +def test_is_valid_team_configs_short_circuits_when_team_id_none(): + team_config = {"models": ["only-this"]} + snapshot = { + "result": _is_valid_team_configs( + team_id=None, + team_config=team_config, + request_data={"model": "anything-else"}, + ), + "team_config_unchanged": team_config, + "models_key_preserved": "models" in team_config, + } + assert snapshot == { + "result": None, + "team_config_unchanged": {"models": ["only-this"]}, + "models_key_preserved": True, + } + + +def test_is_valid_team_configs_raises_on_model_not_in_team_models(): + team_config = {"models": ["gpt-4o"]} + request_data = {"model": "claude-haiku"} + with pytest.raises(Exception) as exc_info: + _is_valid_team_configs( + team_id="team-1", + team_config=team_config, + request_data=request_data, + ) + assert "Invalid model for team team-1" in str(exc_info.value) + assert "claude-haiku" in str(exc_info.value) diff --git a/tests/test_litellm/proxy/utils/helpers/test_to_ns.py b/tests/test_litellm/proxy/utils/helpers/test_to_ns.py new file mode 100644 index 00000000000..64ff6d30f0c --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_to_ns.py @@ -0,0 +1,59 @@ +from datetime import datetime, timezone + +import pytest + +from litellm.proxy.utils import _to_ns + + +def normalize(value): + return value + + +def test_to_ns_happy_path_utc_epoch(): + dt = datetime(2024, 1, 1, 0, 0, 0, tzinfo=timezone.utc) + expected = int(dt.timestamp() * 1e9) + summary = { + "input_iso": dt.isoformat(), + "result": _to_ns(dt), + "expected": expected, + } + assert summary == { + "input_iso": "2024-01-01T00:00:00+00:00", + "result": expected, + "expected": expected, + } + + +def test_to_ns_happy_path_microsecond_precision(): + dt = datetime(2024, 6, 15, 12, 30, 45, 123456, tzinfo=timezone.utc) + expected = int(dt.timestamp() * 1e9) + summary = { + "input_iso": dt.isoformat(), + "result": _to_ns(dt), + "expected": expected, + } + assert summary == { + "input_iso": "2024-06-15T12:30:45.123456+00:00", + "result": expected, + "expected": expected, + } + + +def test_to_ns_result_is_int(): + dt = datetime(2024, 1, 1, tzinfo=timezone.utc) + result = _to_ns(dt) + summary = { + "type": type(result).__name__, + "is_positive": result > 0, + "result": result, + } + assert summary == { + "type": "int", + "is_positive": True, + "result": int(dt.timestamp() * 1e9), + } + + +def test_to_ns_raises_on_invalid_input(): + with pytest.raises(AttributeError): + _to_ns("2024-01-01T00:00:00") diff --git a/tests/test_litellm/proxy/utils/helpers/test_url_helpers.py b/tests/test_litellm/proxy/utils/helpers/test_url_helpers.py new file mode 100644 index 00000000000..31ea1bdce74 --- /dev/null +++ b/tests/test_litellm/proxy/utils/helpers/test_url_helpers.py @@ -0,0 +1,316 @@ +import pytest + +from litellm.proxy.utils import ( + _get_docs_url, + _get_openapi_url, + _get_redoc_url, + get_custom_url, + get_proxy_base_url, + get_server_root_path, + join_paths, + normalize_route_for_root_path, +) + + +def normalize(value): + return value + + +def _clear_url_env(monkeypatch): + for var in ( + "REDOC_URL", + "NO_REDOC", + "DOCS_URL", + "NO_DOCS", + "OPENAPI_URL", + "NO_OPENAPI", + "PROXY_BASE_URL", + "SERVER_ROOT_PATH", + ): + monkeypatch.delenv(var, raising=False) + + +def test_get_redoc_url_default(monkeypatch): + _clear_url_env(monkeypatch) + summary = { + "result": _get_redoc_url(), + "redoc_url_env": None, + "no_redoc_env": None, + } + assert summary == { + "result": "/redoc", + "redoc_url_env": None, + "no_redoc_env": None, + } + + +def test_get_redoc_url_custom_env(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("REDOC_URL", "/custom-redoc") + summary = { + "result": _get_redoc_url(), + "redoc_url_env": "/custom-redoc", + "default_overridden": True, + } + assert summary == { + "result": "/custom-redoc", + "redoc_url_env": "/custom-redoc", + "default_overridden": True, + } + + +def test_get_redoc_url_disabled_returns_none_error_path(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("NO_REDOC", "True") + assert _get_redoc_url() is None + + +def test_get_docs_url_default(monkeypatch): + _clear_url_env(monkeypatch) + summary = { + "result": _get_docs_url(), + "no_docs": None, + "docs_url": None, + } + assert summary == { + "result": "/", + "no_docs": None, + "docs_url": None, + } + + +def test_get_docs_url_custom_env(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("DOCS_URL", "/api-docs") + summary = { + "result": _get_docs_url(), + "env": "/api-docs", + "default_overridden": True, + } + assert summary == { + "result": "/api-docs", + "env": "/api-docs", + "default_overridden": True, + } + + +def test_get_docs_url_disabled_returns_none_error_path(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("NO_DOCS", "True") + assert _get_docs_url() is None + + +def test_get_openapi_url_default(monkeypatch): + _clear_url_env(monkeypatch) + summary = { + "result": _get_openapi_url(), + "no_openapi": None, + "openapi_url": None, + } + assert summary == { + "result": "/openapi.json", + "no_openapi": None, + "openapi_url": None, + } + + +def test_get_openapi_url_custom_env(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("OPENAPI_URL", "/api-schema") + summary = { + "result": _get_openapi_url(), + "env": "/api-schema", + "default_overridden": True, + } + assert summary == { + "result": "/api-schema", + "env": "/api-schema", + "default_overridden": True, + } + + +def test_get_openapi_url_disabled_returns_none_error_path(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("NO_OPENAPI", "True") + assert _get_openapi_url() is None + + +@pytest.mark.parametrize( + "base, route, expected", + [ + ("https://proxy.example.com", "/v1/chat", "https://proxy.example.com/v1/chat"), + ("https://proxy.example.com/", "/v1/chat", "https://proxy.example.com/v1/chat"), + ("https://proxy.example.com", "v1/chat", "https://proxy.example.com/v1/chat"), + ("https://proxy.example.com", "", "https://proxy.example.com"), + ("", "/v1/chat", "/v1/chat"), + ("", "", "/"), + ], +) +def test_join_paths_happy_path(base, route, expected): + result = join_paths(base, route) + assert { + "input_base": base, + "input_route": route, + "result": result, + "expected": expected, + } == { + "input_base": base, + "input_route": route, + "result": expected, + "expected": expected, + } + + +def test_join_paths_avoids_duplicating_route_suffix(): + summary = { + "result": join_paths("https://api.example.com/v1/chat", "/v1/chat"), + "base": "https://api.example.com/v1/chat", + "route": "/v1/chat", + } + assert summary == { + "result": "https://api.example.com/v1/chat", + "base": "https://api.example.com/v1/chat", + "route": "/v1/chat", + } + + +def test_join_paths_invalid_input_raises(): + with pytest.raises(AttributeError): + join_paths(None, "/v1/chat") + + +def test_get_proxy_base_url_returns_env_when_set(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("PROXY_BASE_URL", "https://litellm.test") + summary = { + "result": get_proxy_base_url(), + "env": "https://litellm.test", + "is_set": True, + } + assert summary == { + "result": "https://litellm.test", + "env": "https://litellm.test", + "is_set": True, + } + + +def test_get_proxy_base_url_error_path_returns_none_when_unset(monkeypatch): + _clear_url_env(monkeypatch) + assert get_proxy_base_url() is None + + +def test_get_server_root_path_returns_env(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("SERVER_ROOT_PATH", "/proxy") + summary = { + "result": get_server_root_path(), + "env": "/proxy", + "is_set": True, + } + assert summary == { + "result": "/proxy", + "env": "/proxy", + "is_set": True, + } + + +def test_get_server_root_path_error_path_default_empty_string(monkeypatch): + _clear_url_env(monkeypatch) + assert get_server_root_path() == "" + + +def test_get_custom_url_with_proxy_base_and_root_and_route(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("PROXY_BASE_URL", "https://api.example.com") + monkeypatch.setenv("SERVER_ROOT_PATH", "/proxy") + result = get_custom_url("https://request.example.com", "/v1/chat") + summary = { + "result": result, + "base_used": "PROXY_BASE_URL", + "root_path": "/proxy", + "route": "/v1/chat", + } + assert summary == { + "result": "https://api.example.com/proxy/v1/chat", + "base_used": "PROXY_BASE_URL", + "root_path": "/proxy", + "route": "/v1/chat", + } + + +def test_get_custom_url_falls_back_to_request_base(monkeypatch): + _clear_url_env(monkeypatch) + result = get_custom_url("https://request.example.com", "/v1/chat") + summary = { + "result": result, + "base_used": "request_base_url", + "root_path": "", + "route": "/v1/chat", + } + assert summary == { + "result": "https://request.example.com/v1/chat", + "base_used": "request_base_url", + "root_path": "", + "route": "/v1/chat", + } + + +def test_get_custom_url_no_route_uses_root_path(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("SERVER_ROOT_PATH", "/proxy") + result = get_custom_url("https://request.example.com", route=None) + summary = { + "result": result, + "base_used": "request_base_url", + "root_path": "/proxy", + "route": None, + } + assert summary == { + "result": "https://request.example.com/proxy", + "base_used": "request_base_url", + "root_path": "/proxy", + "route": None, + } + + +def test_get_custom_url_error_path_invalid_base_raises(monkeypatch): + _clear_url_env(monkeypatch) + with pytest.raises(AttributeError): + get_custom_url(None, "/v1/chat") + + +def test_normalize_route_for_root_path_strips_prefix(monkeypatch): + _clear_url_env(monkeypatch) + monkeypatch.setenv("SERVER_ROOT_PATH", "/proxy") + summary = { + "result": normalize_route_for_root_path("/proxy/v1/chat"), + "root_path": "/proxy", + "input": "/proxy/v1/chat", + } + assert summary == { + "result": "/v1/chat", + "root_path": "/proxy", + "input": "/proxy/v1/chat", + } + + +def test_normalize_route_for_root_path_returns_route_when_no_root(monkeypatch): + _clear_url_env(monkeypatch) + summary = { + "result": normalize_route_for_root_path("/v1/chat"), + "root_path": "", + "input": "/v1/chat", + } + assert summary == { + "result": "/v1/chat", + "root_path": "", + "input": "/v1/chat", + } + + +def test_normalize_route_for_root_path_error_path_when_route_not_under_root( + monkeypatch, +): + _clear_url_env(monkeypatch) + monkeypatch.setenv("SERVER_ROOT_PATH", "/proxy") + assert normalize_route_for_root_path("/other/v1/chat") is None From 457f65eff933101fd38437e069d098d751583462 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 2 Jun 2026 17:45:28 -0700 Subject: [PATCH 02/92] test(proxy/utils): pin PrismaClient and spend-update behavior (#29488) * test(proxy/utils): pin PrismaClient and spend-update behavior PR2 of the litellm/proxy/utils.py behavior-pinning plan (https://www.notion.so/37343b8acdab81f68f39f66915f62bcf). Adds tests/test_litellm/proxy/utils/prisma_and_spend/, with happy + error pins for every symbol in the PR2 list: the config-param cache, PrismaClient lifecycle/data ops/engine watcher/reconnect/health clusters, the user-row cache and SMTP helper, password/token helpers, ProxyUpdateSpend, and the module-level spend functions. Tests run against fully-mocked Prisma stacks (patched ``Prisma`` / ``PrismaWrapper`` at fixture setup), with a fake SMTP transport and a clock-driven asyncio.sleep for the monitor loop, so unit runs need no DB or network. ``_pin_check.py`` enforces happy + error coverage for every symbol; ``_coverage_check.py`` filters branch + line coverage to the PR2 source range (lines 2,668-5,541) and prints PASS / FAIL with no numbers. Workflow shard ``tests/test_litellm/proxy/utils`` is added to the existing proxy-endpoints job. * test(proxy/utils): commit pin list and drop dead exclusion line Addresses Greptile review feedback on PR #29488: - Check in ``.pin_list.txt`` (force-added, overriding the repo-wide ``.gitignore`` rule) so reviewers can reproduce the ``_pin_check.py`` PASS shown in the PR description without first regenerating the file from Notion. - Remove the unreachable ``_harness_smoke_test.py`` continue in ``_pin_check.py``: the surrounding ``test_*.py`` glob already excludes underscore-prefixed files; rephrase the docstring instead. * test(proxy/utils): shift PR2 coverage line range by +1 after merge ``litellm_internal_staging`` added one line in ``ProxyLogging`` at ``utils.py:645`` (PR1 territory, before the PR2 region). Bump the ``_PR2_LINE_START`` / ``_PR2_LINE_END`` constants accordingly so the coverage gate keeps scoring the same source region after the merge. * test(proxy/utils): drop committed pin-list and gate scripts ``_pin_check.py``, ``_coverage_check.py``, and ``.pin_list.txt`` are local-only stopping signals: no workflow or pytest collection invokes them, so committing them adds rot risk (line-range drift in the coverage check, pin-list staleness) without any enforcement upside. The pin-list contract lives in the Notion plan; the tests themselves are the durable artifact. --------- Co-authored-by: Claude --- .../proxy/utils/prisma_and_spend/__init__.py | 0 .../prisma_and_spend/_harness_smoke_test.py | 84 +++ .../proxy/utils/prisma_and_spend/conftest.py | 387 +++++++++++++ .../prisma_and_spend/test_cache_user_row.py | 81 +++ .../test_config_param_cache.py | 267 +++++++++ .../prisma_and_spend/test_password_helpers.py | 223 ++++++++ .../test_prisma_client_engine_watcher.py | 521 ++++++++++++++++++ .../test_prisma_client_get_data.py | 400 ++++++++++++++ .../test_prisma_client_health.py | 292 ++++++++++ .../test_prisma_client_lifecycle.py | 207 +++++++ .../test_prisma_client_reconnect.py | 371 +++++++++++++ .../test_prisma_client_writes.py | 260 +++++++++ .../test_proxy_update_spend.py | 275 +++++++++ .../utils/prisma_and_spend/test_send_email.py | 105 ++++ .../prisma_and_spend/test_spend_functions.py | 360 ++++++++++++ 15 files changed, 3833 insertions(+) create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/__init__.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/_harness_smoke_test.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/conftest.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_cache_user_row.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_config_param_cache.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_password_helpers.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_engine_watcher.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_get_data.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_health.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_lifecycle.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_reconnect.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_writes.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_send_email.py create mode 100644 tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/__init__.py b/tests/test_litellm/proxy/utils/prisma_and_spend/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/_harness_smoke_test.py b/tests/test_litellm/proxy/utils/prisma_and_spend/_harness_smoke_test.py new file mode 100644 index 00000000000..2243d46ae7f --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/_harness_smoke_test.py @@ -0,0 +1,84 @@ +"""Self-tests for the prisma_and_spend test harness fixtures. + +Verifies the fixtures themselves do what their docstrings claim. +""" + +from __future__ import annotations + +import asyncio +from typing import Any +from unittest.mock import AsyncMock + +import pytest + +from litellm.proxy.utils import PrismaClient + + +def test_normalize_scrubs_volatile_keys() -> None: + from tests.test_litellm.proxy.utils.prisma_and_spend.conftest import normalize + + out = normalize({"id": 1, "spend": 2.0, "team_id": "t1"}) + assert out == {"id": "", "spend": "", "team_id": "t1"} + + +def test_normalize_recurses_into_lists() -> None: + from tests.test_litellm.proxy.utils.prisma_and_spend.conftest import normalize + + out = normalize([{"id": "x"}, {"team_id": "t"}]) + assert out == [{"id": ""}, {"team_id": "t"}] + + +def test_mock_prisma_client_has_common_tables(mock_prisma_client: Any) -> None: + for table in ( + "litellm_verificationtoken", + "litellm_teamtable", + "litellm_usertable", + "litellm_spendlogs", + "litellm_config", + "litellm_healthchecktable", + ): + assert hasattr(mock_prisma_client.db, table) + + +@pytest.mark.asyncio +async def test_mock_dual_cache_round_trip(mock_dual_cache: Any) -> None: + await mock_dual_cache.async_set_cache("k", "v") + assert await mock_dual_cache.async_get_cache("k") == "v" + await mock_dual_cache.async_delete_cache("k") + assert await mock_dual_cache.async_get_cache("k") is None + + +def test_prisma_client_fixture_is_a_real_prismaclient( + prisma_client: PrismaClient, +) -> None: + assert isinstance(prisma_client, PrismaClient) + assert callable(prisma_client.hash_token) + + +@pytest.mark.asyncio +async def test_fake_clock_advances(fake_clock: Any) -> None: + start = fake_clock.now + await asyncio.sleep(2.5) + assert fake_clock.now == start + 2.5 + assert fake_clock.sleep_calls == [2.5] + + +def test_make_spend_log_row_factory(make_spend_log_row: Any) -> None: + row = make_spend_log_row(request_id="abc", spend=0.5) + assert row["request_id"] == "abc" + assert row["spend"] == 0.5 + + +@pytest.mark.asyncio +async def test_in_memory_smtp_captures(in_memory_smtp: Any) -> None: + factory = in_memory_smtp.server_factory() + conn = factory("smtp.invalid", 25) + with conn: + conn.starttls() + from email.message import EmailMessage + + m = EmailMessage() + m["Subject"] = "S" + m.set_content("

x

", subtype="html") + conn.send_message(m, from_addr="a@b", to_addrs="c@d") + assert len(in_memory_smtp.sent) == 1 diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/conftest.py b/tests/test_litellm/proxy/utils/prisma_and_spend/conftest.py new file mode 100644 index 00000000000..2305a88b6dd --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/conftest.py @@ -0,0 +1,387 @@ +"""Shared fixtures for tests/test_litellm/proxy/utils/prisma_and_spend/. + +All fixtures used by PR2 test files live here. Do NOT add fixtures inside +individual test files; if a fixture is missing, add it here and update the +Notion plan. + +The PrismaClient is exercised against a fully-mocked Prisma stack: the +``prisma.Prisma`` constructor and the writer/reader wrappers are patched +before PrismaClient.__init__ runs so the init code paths execute without +needing a generated Prisma client or a real database. +""" + +from __future__ import annotations + +import asyncio +import sys +from dataclasses import dataclass, field +from email.message import EmailMessage +from pathlib import Path +from typing import Any, Callable, Dict, Iterator, List, Optional +from unittest.mock import AsyncMock, MagicMock + +import pytest + +sys.path.insert(0, str(Path(__file__).resolve().parents[5])) + + +VOLATILE_KEYS = frozenset( + { + "created_at", + "updated_at", + "checked_at", + "started_at", + "request_id", + "id", + "token", + "expires", + "expires_at", + "litellm_call_id", + "created", + "spend", + "last_refreshed_at", + "startTime", + "endTime", + "salt", + } +) + + +def normalize(data: Any, volatile: frozenset = VOLATILE_KEYS) -> Any: + """Recursively replace values for volatile keys with ''.""" + if isinstance(data, dict): + return { + k: ("" if k in volatile else normalize(v, volatile)) + for k, v in data.items() + } + if isinstance(data, list): + return [normalize(v, volatile) for v in data] + return data + + +_PRISMA_TABLES: List[str] = [ + "litellm_verificationtoken", + "litellm_teamtable", + "litellm_usertable", + "litellm_endusertable", + "litellm_organizationtable", + "litellm_proxymodeltable", + "litellm_modeltable", + "litellm_budgettable", + "litellm_spendlogs", + "litellm_config", + "litellm_usernotifications", + "litellm_healthchecktable", + "litellm_dailyuserspend", + "litellm_dailyteamspend", + "litellm_dailytagspend", + "litellm_managed_object_table", + "litellm_credentialstable", + "litellm_mcpservertable", + "litellm_audit_log", + "litellm_invitationlink", + "litellm_session_token_table", + "litellm_passthrough_endpoint_table", + "litellm_cron_job", + "litellm_passthrough_logs", + "litellm_promptstable", + "litellm_guardrailstable", + "litellm_managed_files", + "litellm_mcpusercredentials", + "litellm_objectpermissiontable", + "litellm_organizationmembership", +] + + +def _make_table_mock() -> MagicMock: + table = MagicMock() + table.find_unique = AsyncMock(return_value=None) + table.find_many = AsyncMock(return_value=[]) + table.find_first = AsyncMock(return_value=None) + table.create = AsyncMock() + table.create_many = AsyncMock() + table.update = AsyncMock() + table.update_many = AsyncMock() + table.upsert = AsyncMock() + table.delete = AsyncMock() + table.delete_many = AsyncMock() + table.count = AsyncMock(return_value=0) + table.group_by = AsyncMock(return_value=[]) + table.aggregate = AsyncMock(return_value={}) + return table + + +@pytest.fixture +def mock_prisma_client() -> MagicMock: + """Bare ``db`` mock with all common LiteLLM_* tables stubbed. + + Override individual return values in a test:: + + mock_prisma_client.db.litellm_usertable.find_unique.return_value = user + """ + client = MagicMock(name="MockPrismaClient") + client.db = MagicMock(name="MockPrismaDB") + client.connect = AsyncMock() + client.disconnect = AsyncMock() + client.health_check = AsyncMock(return_value=[{"?column?": 1}]) + client.proxy_logging_obj = MagicMock() + client.proxy_logging_obj.failure_handler = AsyncMock() + client.spend_log_transactions = [] + client._spend_log_transactions_lock = asyncio.Lock() + client.jsonify_object = lambda data: dict(data) + client.db.is_connected = MagicMock(return_value=False) + client.db.connect = AsyncMock() + client.db.disconnect = AsyncMock() + client.db.query_raw = AsyncMock(return_value=[{"?column?": 1}]) + client.db.execute_raw = AsyncMock() + client.db.tx = MagicMock() + client.db.batch_ = MagicMock() + for table_name in _PRISMA_TABLES: + setattr(client.db, table_name, _make_table_mock()) + return client + + +@pytest.fixture +def mock_dual_cache() -> MagicMock: + """In-memory DualCache stand-in. + + Sync and async get/set wired against a private dict. Override or read + ``cache._store`` directly in a test for assertion convenience. + """ + cache = MagicMock(name="MockDualCache") + cache._store: Dict[str, Any] = {} + + def _sync_get(key: str, **_: Any) -> Any: + return cache._store.get(key) + + def _sync_set(key: str, value: Any, **_: Any) -> None: + cache._store[key] = value + + async def _async_get(key: str, **_: Any) -> Any: + return cache._store.get(key) + + async def _async_set(key: str, value: Any, **_: Any) -> None: + cache._store[key] = value + + async def _async_delete(key: str, **_: Any) -> None: + cache._store.pop(key, None) + + cache.get_cache = MagicMock(side_effect=_sync_get) + cache.set_cache = MagicMock(side_effect=_sync_set) + cache.async_get_cache = AsyncMock(side_effect=_async_get) + cache.async_set_cache = AsyncMock(side_effect=_async_set) + cache.async_delete_cache = AsyncMock(side_effect=_async_delete) + return cache + + +@pytest.fixture +def patched_prisma_import(monkeypatch: pytest.MonkeyPatch) -> Iterator[MagicMock]: + """Replace ``prisma.Prisma`` and ``PrismaWrapper`` so PrismaClient.__init__ + runs without a generated client. Yields the fake Prisma instance. + + ``prisma`` raises RuntimeError (not AttributeError) for the missing + ``Prisma`` attribute, so ``monkeypatch.setattr`` can't probe it; assign + directly and restore in teardown. + """ + import prisma as _prisma_pkg + import litellm.proxy.utils as _utils_mod + + fake_prisma = MagicMock(name="FakePrisma") + fake_prisma.is_connected = MagicMock(return_value=False) + fake_prisma.connect = AsyncMock() + fake_prisma.disconnect = AsyncMock() + + fake_prisma_factory = MagicMock(name="FakePrismaFactory", return_value=fake_prisma) + had_prisma_attr = "Prisma" in _prisma_pkg.__dict__ + previous_prisma_attr = _prisma_pkg.__dict__.get("Prisma") + _prisma_pkg.Prisma = fake_prisma_factory # type: ignore[attr-defined] + + fake_wrapper = MagicMock(name="FakePrismaWrapper") + fake_wrapper.is_connected = MagicMock(return_value=False) + fake_wrapper.connect = AsyncMock() + fake_wrapper.disconnect = AsyncMock() + fake_wrapper.query_raw = AsyncMock(return_value=[{"?column?": 1}]) + + def _fake_wrapper_ctor(*args: Any, **kwargs: Any) -> MagicMock: + return fake_wrapper + + monkeypatch.setattr(_utils_mod, "PrismaWrapper", _fake_wrapper_ctor) + fake_prisma.__wrapper__ = fake_wrapper + try: + yield fake_prisma + finally: + if had_prisma_attr: + _prisma_pkg.Prisma = previous_prisma_attr # type: ignore[attr-defined] + else: + try: + del _prisma_pkg.Prisma # type: ignore[attr-defined] + except AttributeError: + pass + + +@pytest.fixture +def prisma_client( + patched_prisma_import: MagicMock, + mock_prisma_client: MagicMock, + monkeypatch: pytest.MonkeyPatch, +) -> Any: + """Wired ``PrismaClient`` whose ``db`` attribute is the table mock. + + The init runs through the real code path (testing the constructor's + config-attribute setup) and is then snapped to the easier-to-assert + table mock for downstream behavior pinning. + """ + monkeypatch.delenv("DATABASE_URL_READ_REPLICA", raising=False) + monkeypatch.delenv("IAM_TOKEN_DB_AUTH", raising=False) + from litellm.proxy.utils import PrismaClient + + proxy_logging_obj = MagicMock(name="MockProxyLogging") + proxy_logging_obj.failure_handler = AsyncMock() + pc = PrismaClient( + database_url="postgresql://test:test@localhost:5432/test", + proxy_logging_obj=proxy_logging_obj, + ) + pc.db = mock_prisma_client.db + return pc + + +@dataclass +class FakeClock: + """Monotonic-time controller for the spend monitor loop. + + Tests advance time via ``clock.advance(seconds)`` while asyncio.sleep + is replaced with a clock-driven no-op. + """ + + now: float = 0.0 + sleep_calls: List[float] = field(default_factory=list) + + def advance(self, seconds: float) -> None: + self.now += seconds + + def time(self) -> float: + return self.now + + async def sleep(self, seconds: float) -> None: + self.sleep_calls.append(seconds) + self.now += seconds + + +@pytest.fixture +def fake_clock(monkeypatch: pytest.MonkeyPatch) -> FakeClock: + """Install a controllable clock + asyncio.sleep replacement.""" + clock = FakeClock() + monkeypatch.setattr("time.time", clock.time) + monkeypatch.setattr("time.monotonic", clock.time) + + async def _fast_sleep(seconds: float, *_: Any, **__: Any) -> None: + clock.sleep_calls.append(seconds) + clock.now += seconds + + monkeypatch.setattr("asyncio.sleep", _fast_sleep) + return clock + + +@pytest.fixture +def make_spend_log_row() -> Callable[..., Dict[str, Any]]: + """Factory for fake LiteLLM_SpendLogs rows.""" + + def _make( + request_id: str = "req-1", + spend: float = 0.01, + model: str = "gpt-4o-mini", + **overrides: Any, + ) -> Dict[str, Any]: + row = { + "request_id": request_id, + "spend": spend, + "model": model, + "user": "user-1", + "team_id": "team-1", + "api_key": "hashed-key", + "startTime": "2026-06-02T00:00:00Z", + "endTime": "2026-06-02T00:00:01Z", + "metadata": {}, + } + row.update(overrides) + return row + + return _make + + +@dataclass +class _SentMessage: + from_addr: Optional[str] + to_addrs: Any + subject: Optional[str] + body: Optional[str] + starttls_called: bool + login_args: Optional[tuple] + + +@dataclass +class InMemorySMTP: + """Captures outbound SMTP traffic for ``send_email`` tests.""" + + sent: List[_SentMessage] = field(default_factory=list) + raise_on_send: Optional[Exception] = None + + def server_factory(self) -> Callable[..., Any]: + outer = self + + class _Conn: + def __init__(self) -> None: + self._starttls_called = False + self._login_args: Optional[tuple] = None + + def __enter__(self) -> "_Conn": + return self + + def __exit__(self, *exc: Any) -> None: + return None + + def starttls(self) -> None: + self._starttls_called = True + + def login(self, user: str, password: str) -> None: + self._login_args = (user, password) + + def send_message( + self, + msg: EmailMessage, + from_addr: Optional[str] = None, + to_addrs: Any = None, + ) -> None: + if outer.raise_on_send is not None: + raise outer.raise_on_send + body = "" + for part in msg.walk(): + if part.get_content_type() == "text/html": + body = part.get_payload(decode=False) or "" + break + outer.sent.append( + _SentMessage( + from_addr=from_addr, + to_addrs=to_addrs, + subject=msg["Subject"], + body=body, + starttls_called=self._starttls_called, + login_args=self._login_args, + ) + ) + + def _factory(*args: Any, **kwargs: Any) -> _Conn: + return _Conn() + + return _factory + + +@pytest.fixture +def in_memory_smtp(monkeypatch: pytest.MonkeyPatch) -> InMemorySMTP: + """Patch ``smtplib.SMTP`` to capture sends in memory. + + Override ``smtp.raise_on_send`` to test the SMTP error path. + """ + smtp = InMemorySMTP() + monkeypatch.setattr("smtplib.SMTP", smtp.server_factory()) + return smtp diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_cache_user_row.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_cache_user_row.py new file mode 100644 index 00000000000..d1270b60b19 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_cache_user_row.py @@ -0,0 +1,81 @@ +"""Pin ``_cache_user_row``. + +Symbols pinned here: + - ``_cache_user_row`` +""" + +from __future__ import annotations + +from types import SimpleNamespace +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import _cache_user_row + + +@pytest.mark.asyncio +async def test_cache_user_row_caches_on_miss( + mock_dual_cache: Any, +) -> None: + user_row = SimpleNamespace( + user_id="u1", spend=2.5, max_budget=10.0, name="Alice" + ) + user_row.model_dump_json = MagicMock( + return_value='{"user_id":"u1","spend":2.5,"max_budget":10.0,"name":"Alice"}' + ) + db = MagicMock() + db.get_data = AsyncMock(return_value=user_row) + + result = await _cache_user_row("u1", mock_dual_cache, db) + cache_key = "u1_user_api_key_user_id" + pinned = { + "result": result, + "cache_value": mock_dual_cache._store[cache_key], + "get_calls": mock_dual_cache.get_cache.call_count, + "set_calls": mock_dual_cache.set_cache.call_count, + "db_called": db.get_data.await_count, + } + assert pinned == { + "result": None, + "cache_value": '{"user_id":"u1","spend":2.5,"max_budget":10.0,"name":"Alice"}', + "get_calls": 1, + "set_calls": 1, + "db_called": 1, + } + + +@pytest.mark.asyncio +async def test_cache_user_row_skips_db_on_cache_hit( + mock_dual_cache: Any, +) -> None: + cache_key = "u-hit_user_api_key_user_id" + mock_dual_cache._store[cache_key] = "cached-blob" + db = MagicMock() + db.get_data = AsyncMock(return_value=None) + result = await _cache_user_row("u-hit", mock_dual_cache, db) + assert result is None + assert db.get_data.await_count == 0 + + +@pytest.mark.asyncio +async def test_cache_user_row_skips_set_when_user_row_lacks_model_dump_json( + mock_dual_cache: Any, +) -> None: + user_row = SimpleNamespace(user_id="u2", spend=1.0) + db = MagicMock() + db.get_data = AsyncMock(return_value=user_row) + await _cache_user_row("u2", mock_dual_cache, db) + assert mock_dual_cache._store == {} + assert mock_dual_cache.set_cache.call_count == 0 + + +@pytest.mark.asyncio +async def test_cache_user_row_propagates_db_error( + mock_dual_cache: Any, +) -> None: + db = MagicMock() + db.get_data = AsyncMock(side_effect=RuntimeError("db down")) + with pytest.raises(RuntimeError, match="db down"): + await _cache_user_row("u3", mock_dual_cache, db) diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_config_param_cache.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_config_param_cache.py new file mode 100644 index 00000000000..761835078f4 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_config_param_cache.py @@ -0,0 +1,267 @@ +"""Pin the LiteLLM_Config cached-read layer. + +Symbols pinned here: + - ``_ConfigRow`` + - ``_config_cache_key`` + - ``_pack_config_row`` + - ``_unpack_config_row`` + - ``get_config_param`` + - ``invalidate_config_param`` + - ``prefetch_config_params`` +""" + +from __future__ import annotations + +from types import SimpleNamespace +from typing import Any, List +from unittest.mock import AsyncMock, MagicMock + +import pytest + +import litellm.proxy.utils as utils_mod +from litellm.proxy.utils import ( + _config_cache_key, + _ConfigRow, + _pack_config_row, + _unpack_config_row, + get_config_param, + invalidate_config_param, + prefetch_config_params, +) + + +@pytest.fixture(autouse=True) +def _swap_config_cache( + monkeypatch: pytest.MonkeyPatch, mock_dual_cache: Any +) -> Any: + """Replace the module-level cache so tests see a clean store per run.""" + monkeypatch.setattr(utils_mod, "litellm_config_cache", mock_dual_cache) + return mock_dual_cache + + +def test_config_cache_key_uses_documented_prefix() -> None: + actual = { + "key": _config_cache_key("max_budget"), + "another": _config_cache_key("disable_spend_updates"), + "prefix": _config_cache_key("x").split(":")[0], + } + assert actual == { + "key": "litellm_config:param:max_budget", + "another": "litellm_config:param:disable_spend_updates", + "prefix": "litellm_config", + } + + +def test_config_cache_key_error_propagates_from_bad_format() -> None: + class _Boom: + def __format__(self, _spec: str) -> str: + raise ValueError("format failure") + + with pytest.raises(ValueError, match="format failure"): + _config_cache_key(_Boom()) # type: ignore[arg-type] + + +def test_config_row_dataclass_shape() -> None: + row = _ConfigRow(param_name="alpha", param_value={"k": 1}) + assert { + "param_name": row.param_name, + "param_value": row.param_value, + "slots": _ConfigRow.__slots__, + } == { + "param_name": "alpha", + "param_value": {"k": 1}, + "slots": ("param_name", "param_value"), + } + + +def test_config_row_rejects_unknown_attribute() -> None: + row = _ConfigRow("a", 1) + with pytest.raises(AttributeError): + row.something_else = 2 # type: ignore[attr-defined] + + +def test_pack_config_row_returns_dict_for_caching() -> None: + row = SimpleNamespace(param_name="zeta", param_value=[1, 2, 3]) + actual = _pack_config_row(row) + expanded = {**actual, "is_dict": isinstance(actual, dict)} + assert expanded == { + "param_name": "zeta", + "param_value": [1, 2, 3], + "is_dict": True, + } + + +def test_pack_config_row_error_on_missing_attribute() -> None: + bad = SimpleNamespace(param_name="only_name") + with pytest.raises(AttributeError): + _pack_config_row(bad) + + +def test_unpack_config_row_round_trips_dict() -> None: + packed = {"param_name": "alpha", "param_value": "abc"} + unpacked = _unpack_config_row(packed) + assert isinstance(unpacked, _ConfigRow) + actual = { + "param_name": unpacked.param_name, + "param_value": unpacked.param_value, + "from_none": _unpack_config_row(None), + "from_miss_sentinel": _unpack_config_row(utils_mod._CONFIG_CACHE_MISS), + "from_other_type": _unpack_config_row(123), + } + assert actual == { + "param_name": "alpha", + "param_value": "abc", + "from_none": None, + "from_miss_sentinel": None, + "from_other_type": None, + } + + +def test_unpack_config_row_error_on_malformed_dict() -> None: + with pytest.raises(KeyError): + _unpack_config_row({"only_name": "x"}) + + +@pytest.mark.asyncio +async def test_get_config_param_cache_hit_returns_unpacked_row( + _swap_config_cache: Any, +) -> None: + cache_key = _config_cache_key("p1") + await _swap_config_cache.async_set_cache( + cache_key, {"param_name": "p1", "param_value": {"x": 1}} + ) + prisma = MagicMock() + prisma.get_generic_data = AsyncMock() + + row = await get_config_param(prisma, "p1") + actual = { + "type": type(row).__name__, + "param_name": row.param_name, + "param_value": row.param_value, + "db_not_touched": prisma.get_generic_data.await_count == 0, + } + assert actual == { + "type": "_ConfigRow", + "param_name": "p1", + "param_value": {"x": 1}, + "db_not_touched": True, + } + + +@pytest.mark.asyncio +async def test_get_config_param_cache_miss_fetches_from_db_and_caches( + _swap_config_cache: Any, +) -> None: + db_row = SimpleNamespace(param_name="p2", param_value={"y": 2}) + prisma = MagicMock() + prisma.get_generic_data = AsyncMock(return_value=db_row) + + row = await get_config_param(prisma, "p2") + cached = _swap_config_cache._store[_config_cache_key("p2")] + actual = { + "returned": row, + "cached": cached, + "db_called": prisma.get_generic_data.await_count, + "db_args": prisma.get_generic_data.await_args.kwargs, + } + assert actual == { + "returned": db_row, + "cached": {"param_name": "p2", "param_value": {"y": 2}}, + "db_called": 1, + "db_args": {"key": "param_name", "value": "p2", "table_name": "config"}, + } + + +@pytest.mark.asyncio +async def test_get_config_param_caches_negative_lookup_as_miss_sentinel( + _swap_config_cache: Any, +) -> None: + prisma = MagicMock() + prisma.get_generic_data = AsyncMock(return_value=None) + row = await get_config_param(prisma, "absent") + assert row is None + assert _swap_config_cache._store[_config_cache_key("absent")] == ( + utils_mod._CONFIG_CACHE_MISS + ) + + +@pytest.mark.asyncio +async def test_get_config_param_raises_when_db_raises() -> None: + prisma = MagicMock() + prisma.get_generic_data = AsyncMock(side_effect=RuntimeError("db down")) + with pytest.raises(RuntimeError, match="db down"): + await get_config_param(prisma, "p3") + + +@pytest.mark.asyncio +async def test_invalidate_config_param_evicts_from_cache( + _swap_config_cache: Any, +) -> None: + cache_key = _config_cache_key("p4") + await _swap_config_cache.async_set_cache(cache_key, {"param_name": "p4", "param_value": 1}) + await invalidate_config_param("p4") + actual = { + "store_empty": _swap_config_cache._store == {}, + "delete_calls": _swap_config_cache.async_delete_cache.await_count, + "delete_arg": _swap_config_cache.async_delete_cache.await_args.args[0], + } + assert actual == { + "store_empty": True, + "delete_calls": 1, + "delete_arg": "litellm_config:param:p4", + } + + +@pytest.mark.asyncio +async def test_invalidate_config_param_propagates_cache_error( + _swap_config_cache: Any, +) -> None: + _swap_config_cache.async_delete_cache = AsyncMock( + side_effect=ConnectionError("redis down") + ) + with pytest.raises(ConnectionError): + await invalidate_config_param("p5") + + +@pytest.mark.asyncio +async def test_prefetch_config_params_populates_cache_for_each_name( + _swap_config_cache: Any, +) -> None: + rows: List[SimpleNamespace] = [ + SimpleNamespace(param_name="a", param_value={"av": 1}), + SimpleNamespace(param_name="c", param_value=[3]), + ] + prisma = MagicMock() + prisma.db.litellm_config.find_many = AsyncMock(return_value=rows) + await prefetch_config_params(prisma, ["a", "b", "c"]) + actual = { + "a": _swap_config_cache._store[_config_cache_key("a")], + "b": _swap_config_cache._store[_config_cache_key("b")], + "c": _swap_config_cache._store[_config_cache_key("c")], + } + assert actual == { + "a": {"param_name": "a", "param_value": {"av": 1}}, + "b": utils_mod._CONFIG_CACHE_MISS, + "c": {"param_name": "c", "param_value": [3]}, + } + + +@pytest.mark.asyncio +async def test_prefetch_config_params_empty_list_is_noop( + _swap_config_cache: Any, +) -> None: + prisma = MagicMock() + prisma.db.litellm_config.find_many = AsyncMock(return_value=[]) + await prefetch_config_params(prisma, []) + assert prisma.db.litellm_config.find_many.await_count == 0 + assert _swap_config_cache._store == {} + + +@pytest.mark.asyncio +async def test_prefetch_config_params_swallows_db_error_without_caching( + _swap_config_cache: Any, +) -> None: + prisma = MagicMock() + prisma.db.litellm_config.find_many = AsyncMock(side_effect=RuntimeError("boom")) + await prefetch_config_params(prisma, ["a", "b"]) + assert _swap_config_cache._store == {} diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_password_helpers.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_password_helpers.py new file mode 100644 index 00000000000..3c028473479 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_password_helpers.py @@ -0,0 +1,223 @@ +"""Pin password/token helper behavior. + +Symbols pinned here: + - ``hash_token`` + - ``hash_password`` + - ``verify_password`` + - ``migrate_passwords_to_scrypt_async`` + - ``_hash_token_if_needed`` + - ``PrismaClient._is_sha256_hex`` (a nested helper inside + ``migrate_passwords_to_scrypt_async``; the pin list labels it under the + PrismaClient health cluster as a documentation artifact) +""" + +from __future__ import annotations + +import hashlib +from types import SimpleNamespace +from typing import List +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import ( + _hash_token_if_needed, + hash_password, + hash_token, + migrate_passwords_to_scrypt_async, + verify_password, +) + + +def test_hash_token_returns_sha256_hex_of_input() -> None: + token = "sk-abcDEF12345" + result = hash_token(token) + expected = hashlib.sha256(token.encode()).hexdigest() + actual = { + "len": len(result), + "hex": all(c in "0123456789abcdef" for c in result), + "hash": result, + "matches_sha256": result == expected, + } + assert actual == { + "len": 64, + "hex": True, + "hash": expected, + "matches_sha256": True, + } + + +def test_hash_token_empty_string_still_hashes() -> None: + result = hash_token("") + assert result == hashlib.sha256(b"").hexdigest() + + +def test_hash_token_raises_for_non_string() -> None: + with pytest.raises(AttributeError): + hash_token(None) # type: ignore[arg-type] + + +def test_hash_password_uses_scrypt_prefix() -> None: + h = hash_password("hunter2") + fields = { + "prefix": h[:7], + "min_length": len(h) > 60, + "verifies_self": verify_password("hunter2", h), + "rejects_other": verify_password("hunter3", h), + } + assert fields == { + "prefix": "scrypt:", + "min_length": True, + "verifies_self": True, + "rejects_other": False, + } + + +def test_hash_password_returns_distinct_hashes_per_call() -> None: + a = hash_password("same-password") + b = hash_password("same-password") + assert a != b + assert verify_password("same-password", a) + assert verify_password("same-password", b) + + +def test_hash_password_error_for_non_string_raises() -> None: + with pytest.raises(AttributeError): + hash_password(None) # type: ignore[arg-type] + + +def test_verify_password_sha256_legacy_path() -> None: + plaintext = "legacy-pass" + sha = hashlib.sha256(plaintext.encode()).hexdigest() + matrix = { + "correct": verify_password(plaintext, sha), + "wrong": verify_password("other", sha), + "non_hex_short": verify_password(plaintext, "not-hex"), + "empty_stored": verify_password(plaintext, ""), + } + assert matrix == { + "correct": True, + "wrong": False, + "non_hex_short": False, + "empty_stored": False, + } + + +def test_verify_password_scrypt_malformed_returns_false() -> None: + assert verify_password("anything", "scrypt:not-base64") is False + + +def test_verify_password_unknown_format_returns_false() -> None: + assert verify_password("x", "plaintext-not-supported") is False + + +def test_hash_token_if_needed_handles_sk_prefix() -> None: + plain = "sk-secret-xyz" + already_hashed = hashlib.sha256(plain.encode()).hexdigest() + not_a_secret = "token-without-sk-prefix" + actual = { + "sk_input_is_hashed": _hash_token_if_needed(plain) == already_hashed, + "non_sk_passthrough": _hash_token_if_needed(not_a_secret) == not_a_secret, + "double_hash_stable": _hash_token_if_needed(already_hashed) == already_hashed, + } + assert actual == { + "sk_input_is_hashed": True, + "non_sk_passthrough": True, + "double_hash_stable": True, + } + + +def test_hash_token_if_needed_error_on_non_string() -> None: + with pytest.raises(AttributeError): + _hash_token_if_needed(None) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# migrate_passwords_to_scrypt_async — pins behavior of the nested +# ``_is_sha256_hex`` helper too: scrypt-prefixed and sha256-hex rows are +# left alone, plaintext rows are upgraded in place. +# --------------------------------------------------------------------------- + + +def _make_user(user_id: str, password) -> SimpleNamespace: + return SimpleNamespace(user_id=user_id, password=password) + + +@pytest.mark.asyncio +async def test_migrate_passwords_skips_when_no_plaintext() -> None: + pc = MagicMock() + pc.db = MagicMock() + sha = hashlib.sha256(b"already-hashed").hexdigest() + pc.db.litellm_usertable.find_many = AsyncMock( + return_value=[ + _make_user("a", "scrypt:abc"), + _make_user("b", sha), + ] + ) + pc.db.litellm_usertable.update = AsyncMock() + + result = await migrate_passwords_to_scrypt_async(pc) + outcome = { + "message": result, + "updates": pc.db.litellm_usertable.update.await_count, + "find_called": pc.db.litellm_usertable.find_many.await_count, + "fetch_filter": pc.db.litellm_usertable.find_many.await_args.kwargs["where"], + } + assert outcome == { + "message": "No plaintext passwords found", + "updates": 0, + "find_called": 1, + "fetch_filter": {"password": {"not": None}}, + } + + +@pytest.mark.asyncio +async def test_migrate_passwords_upgrades_only_plaintext_rows() -> None: + pc = MagicMock() + pc.db = MagicMock() + users: List[SimpleNamespace] = [ + _make_user("plaintext-user-1", "plain-1"), + _make_user("plaintext-user-2", "plain-2"), + _make_user("scrypt-user", "scrypt:already"), + _make_user( + "sha-user", + hashlib.sha256(b"alreadyhashed").hexdigest(), + ), + _make_user("null-pw", None), + ] + pc.db.litellm_usertable.find_many = AsyncMock(return_value=users) + pc.db.litellm_usertable.update = AsyncMock() + + result = await migrate_passwords_to_scrypt_async(pc) + + updated_user_ids = sorted( + call.kwargs["where"]["user_id"] + for call in pc.db.litellm_usertable.update.await_args_list + ) + new_password_prefixes = sorted( + call.kwargs["data"]["password"][:7] + for call in pc.db.litellm_usertable.update.await_args_list + ) + outcome = { + "message": result, + "update_count": pc.db.litellm_usertable.update.await_count, + "updated_ids": updated_user_ids, + "all_scrypt_prefixed": new_password_prefixes, + } + assert outcome == { + "message": "Migrated 2 plaintext passwords to scrypt", + "update_count": 2, + "updated_ids": ["plaintext-user-1", "plaintext-user-2"], + "all_scrypt_prefixed": ["scrypt:", "scrypt:"], + } + + +@pytest.mark.asyncio +async def test_migrate_passwords_raises_on_db_failure() -> None: + pc = MagicMock() + pc.db = MagicMock() + pc.db.litellm_usertable.find_many = AsyncMock( + side_effect=RuntimeError("db unavailable") + ) + with pytest.raises(RuntimeError, match="db unavailable"): + await migrate_passwords_to_scrypt_async(pc) diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_engine_watcher.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_engine_watcher.py new file mode 100644 index 00000000000..7b862eecbd4 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_engine_watcher.py @@ -0,0 +1,521 @@ +"""Pin ``PrismaClient`` engine watcher methods. + +Symbols pinned here: + - ``PrismaClient._get_engine_pid`` + - ``PrismaClient._is_engine_alive`` + - ``PrismaClient._reap_all_zombies`` + - ``PrismaClient._try_waitpid_watch`` + - ``PrismaClient._waitpid_thread_func`` + - ``PrismaClient._on_engine_death_from_thread`` + - ``PrismaClient._try_pidfd_watch`` + - ``PrismaClient._on_pidfd_readable`` + - ``PrismaClient._poll_engine_proc`` + - ``PrismaClient._cleanup_engine_watcher`` + - ``PrismaClient._start_engine_watcher`` + - ``PrismaClient._stop_engine_watcher`` + +Linux-only tests are skipped on Windows; the production code uses +``waitpid``/``pidfd_open`` which are Unix-only. +""" + +from __future__ import annotations + +import asyncio +import os +import sys +import threading +from typing import Any, Optional +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import PrismaClient + + +pytestmark = pytest.mark.skipif( + sys.platform == "win32", reason="engine watcher is Unix-only" +) + + +def test_get_engine_pid_extracts_process_pid(prisma_client: PrismaClient) -> None: + fake_engine = MagicMock() + fake_engine.process = MagicMock() + fake_engine.process.pid = 4242 + prisma_client.db._original_prisma = MagicMock() + prisma_client.db._original_prisma._engine = fake_engine + actual = { + "pid": prisma_client._get_engine_pid(), + "engine_attr": prisma_client.db._original_prisma._engine is fake_engine, + "process_pid": fake_engine.process.pid, + } + assert actual == {"pid": 4242, "engine_attr": True, "process_pid": 4242} + + +def test_get_engine_pid_returns_zero_when_engine_attr_missing( + prisma_client: PrismaClient, +) -> None: + prisma_client.db._original_prisma = MagicMock(spec=[]) + assert prisma_client._get_engine_pid() == 0 + + +def test_is_engine_alive_true_when_pid_zero(prisma_client: PrismaClient) -> None: + prisma_client._engine_pid = 0 + pinned = { + "result": prisma_client._is_engine_alive(), + "pid": prisma_client._engine_pid, + "type": type(prisma_client._is_engine_alive()).__name__, + } + assert pinned == {"result": True, "pid": 0, "type": "bool"} + + +def test_is_engine_alive_false_when_process_lookup_fails( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + prisma_client._engine_pid = 99999 + monkeypatch.setattr( + "os.kill", MagicMock(side_effect=ProcessLookupError()) + ) + assert prisma_client._is_engine_alive() is False + + +def test_is_engine_alive_true_on_permission_error( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + prisma_client._engine_pid = 1 + monkeypatch.setattr("os.kill", MagicMock(side_effect=PermissionError())) + assert prisma_client._is_engine_alive() is True + + +def test_reap_all_zombies_returns_set_of_reaped_pids( + monkeypatch: pytest.MonkeyPatch, +) -> None: + calls = iter([(111, 0), (222, 0), (0, 0)]) + + def fake_waitpid(pid: int, flags: int) -> Any: + return next(calls) + + monkeypatch.setattr("os.waitpid", fake_waitpid) + reaped = PrismaClient._reap_all_zombies() + pinned = { + "type": type(reaped).__name__, + "size": len(reaped), + "contains_111": 111 in reaped, + "contains_222": 222 in reaped, + } + assert pinned == {"type": "set", "size": 2, "contains_111": True, "contains_222": True} + + +def test_reap_all_zombies_handles_no_children_error( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr( + "os.waitpid", MagicMock(side_effect=ChildProcessError()) + ) + assert PrismaClient._reap_all_zombies() == set() + + +@pytest.mark.asyncio +async def test_try_waitpid_watch_starts_thread_for_live_child( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr("os.waitpid", MagicMock(return_value=(0, 0))) + + threads: list[threading.Thread] = [] + + real_thread_cls = threading.Thread + + def _capture_thread(*args: Any, **kwargs: Any) -> threading.Thread: + t = real_thread_cls(*args, **kwargs) + threads.append(t) + # Replace start so we don't actually launch the thread. + t.start = MagicMock() # type: ignore[method-assign] + return t + + monkeypatch.setattr("threading.Thread", _capture_thread) + monkeypatch.setattr(prisma_client, "_waitpid_thread_func", MagicMock()) + + result = prisma_client._try_waitpid_watch(7777) + pinned = { + "returned": result, + "threads_made": len(threads), + "wait_thread_set": prisma_client._engine_wait_thread is threads[0], + "thread_name_prefix": threads[0].name.startswith("prisma-engine-waitpid-"), + } + assert pinned == { + "returned": True, + "threads_made": 1, + "wait_thread_set": True, + "thread_name_prefix": True, + } + + +@pytest.mark.asyncio +async def test_try_waitpid_watch_returns_false_for_non_child( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr( + "os.waitpid", MagicMock(side_effect=ChildProcessError()) + ) + assert prisma_client._try_waitpid_watch(123) is False + + +@pytest.mark.asyncio +async def test_try_waitpid_watch_handles_already_dead_pid( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + """If the engine PID is already dead at watch start, _try_waitpid_watch + returns True and schedules a reconnect. + """ + prisma_client.attempt_db_reconnect = AsyncMock(return_value=True) + monkeypatch.setattr("os.waitpid", MagicMock(return_value=(8888, 0))) + monkeypatch.setattr(PrismaClient, "_reap_all_zombies", staticmethod(lambda: set())) + monkeypatch.setattr(prisma_client, "_cleanup_engine_watcher", MagicMock()) + + result = prisma_client._try_waitpid_watch(8888) + # Drain pending tasks so attempt_db_reconnect is awaited and we don't leak. + await asyncio.sleep(0) + pinned = { + "result": result, + "engine_confirmed_dead": prisma_client._engine_confirmed_dead, + "cleanup_called": prisma_client._cleanup_engine_watcher.call_count, + "reconnect_scheduled": prisma_client.attempt_db_reconnect.await_count >= 1, + } + assert pinned == { + "result": True, + "engine_confirmed_dead": True, + "cleanup_called": 1, + "reconnect_scheduled": True, + } + + +def test_waitpid_thread_func_swallows_child_process_error( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr("os.waitpid", MagicMock(side_effect=ChildProcessError())) + loop = MagicMock() + loop.call_soon_threadsafe = MagicMock() + prisma_client._waitpid_thread_func(123, loop) + assert loop.call_soon_threadsafe.call_count == 1 + + +def test_waitpid_thread_func_invokes_on_engine_death_on_normal_exit( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr("os.waitpid", MagicMock(return_value=(123, 0))) + loop = MagicMock() + received: list[Any] = [] + loop.call_soon_threadsafe = lambda fn, pid: received.append((fn, pid)) + prisma_client._waitpid_thread_func(123, loop) + pinned = { + "callbacks_received": len(received), + "callback_target": received[0][0] == prisma_client._on_engine_death_from_thread, + "pid_arg": received[0][1], + "first_tuple_size": len(received[0]), + } + assert pinned == { + "callbacks_received": 1, + "callback_target": True, + "pid_arg": 123, + "first_tuple_size": 2, + } + + +def test_waitpid_thread_func_swallows_loop_runtime_error( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr("os.waitpid", MagicMock(return_value=(123, 0))) + loop = MagicMock() + loop.call_soon_threadsafe = MagicMock(side_effect=RuntimeError("loop closed")) + prisma_client._waitpid_thread_func(123, loop) + + +@pytest.mark.asyncio +async def test_on_engine_death_from_thread_schedules_reconnect( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + prisma_client._engine_pid = 7777 + prisma_client._engine_confirmed_dead = False + prisma_client.attempt_db_reconnect = AsyncMock(return_value=True) + monkeypatch.setattr(PrismaClient, "_reap_all_zombies", staticmethod(lambda: set())) + monkeypatch.setattr(prisma_client, "_cleanup_engine_watcher", MagicMock()) + + prisma_client._on_engine_death_from_thread(7777) + await asyncio.sleep(0) + pinned = { + "confirmed_dead": prisma_client._engine_confirmed_dead, + "cleanup_called": prisma_client._cleanup_engine_watcher.call_count, + "reconnect_called": prisma_client.attempt_db_reconnect.await_count, + "reconnect_reason": prisma_client.attempt_db_reconnect.await_args.kwargs["reason"], + } + assert pinned == { + "confirmed_dead": True, + "cleanup_called": 1, + "reconnect_called": 1, + "reconnect_reason": "engine_process_death", + } + + +def test_on_engine_death_from_thread_ignores_wrong_pid_or_already_dead( + prisma_client: PrismaClient, +) -> None: + prisma_client._engine_pid = 1111 + prisma_client._engine_confirmed_dead = True + prisma_client._cleanup_engine_watcher = MagicMock() + prisma_client._on_engine_death_from_thread(1111) + assert prisma_client._cleanup_engine_watcher.call_count == 0 + + +def test_on_engine_death_from_thread_wrong_pid_does_nothing( + prisma_client: PrismaClient, +) -> None: + prisma_client._engine_pid = 1111 + prisma_client._engine_confirmed_dead = False + prisma_client._cleanup_engine_watcher = MagicMock() + prisma_client._on_engine_death_from_thread(2222) + assert prisma_client._cleanup_engine_watcher.call_count == 0 + assert prisma_client._engine_confirmed_dead is False + + +@pytest.mark.asyncio +async def test_try_pidfd_watch_returns_false_when_pidfd_open_missing( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.delattr("os.pidfd_open", raising=False) + assert prisma_client._try_pidfd_watch(123) is False + + +@pytest.mark.asyncio +async def test_try_pidfd_watch_arms_reader_when_available( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + def fake_pidfd(pid: int, flags: int) -> int: + return 42 + + monkeypatch.setattr("os.pidfd_open", fake_pidfd, raising=False) + loop = asyncio.get_running_loop() + fake_add_reader = MagicMock() + monkeypatch.setattr(loop, "add_reader", fake_add_reader) + + result = prisma_client._try_pidfd_watch(123) + assert result is True + assert prisma_client._engine_pidfd == 42 + assert fake_add_reader.call_args.args[0] == 42 + + +@pytest.mark.asyncio +async def test_try_pidfd_watch_error_returns_false_and_cleans_up( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + def fake_pidfd(pid: int, flags: int) -> int: + raise OSError("ENOSYS") + + monkeypatch.setattr("os.pidfd_open", fake_pidfd, raising=False) + assert prisma_client._try_pidfd_watch(123) is False + assert prisma_client._engine_pidfd == -1 + + +@pytest.mark.asyncio +async def test_on_pidfd_readable_invokes_reconnect_path( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + prisma_client._engine_pid = 4321 + prisma_client._engine_confirmed_dead = False + prisma_client.attempt_db_reconnect = AsyncMock(return_value=True) + monkeypatch.setattr(PrismaClient, "_reap_all_zombies", staticmethod(lambda: set())) + cleanup = MagicMock() + prisma_client._cleanup_engine_watcher = cleanup + + prisma_client._on_pidfd_readable() + await asyncio.sleep(0) + pinned = { + "confirmed_dead": prisma_client._engine_confirmed_dead, + "cleanup_called": cleanup.call_count, + "reconnect_called": prisma_client.attempt_db_reconnect.await_count, + "force_kwarg": prisma_client.attempt_db_reconnect.await_args.kwargs["force"], + } + assert pinned == { + "confirmed_dead": True, + "cleanup_called": 1, + "reconnect_called": 1, + "force_kwarg": True, + } + + +@pytest.mark.asyncio +async def test_on_pidfd_readable_noop_when_already_dead_closes_pidfd( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + """When _engine_confirmed_dead is already True, the reader handler should + not schedule another reconnect and should release the pidfd resource. + """ + closed: list[int] = [] + monkeypatch.setattr("os.close", lambda fd: closed.append(fd)) + loop = asyncio.get_running_loop() + removed: list[int] = [] + monkeypatch.setattr(loop, "remove_reader", lambda fd: removed.append(fd)) + + prisma_client._engine_confirmed_dead = True + prisma_client._engine_pidfd = 99 + prisma_client.attempt_db_reconnect = AsyncMock() + + prisma_client._on_pidfd_readable() + pinned = { + "engine_pidfd": prisma_client._engine_pidfd, + "closed": closed, + "removed": removed, + "reconnect_call_count": prisma_client.attempt_db_reconnect.await_count, + } + assert pinned == { + "engine_pidfd": -1, + "closed": [99], + "removed": [99], + "reconnect_call_count": 0, + } + + +@pytest.mark.asyncio +async def test_poll_engine_proc_detects_death_and_reconnects( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + prisma_client._engine_pid = 555 + prisma_client._watching_engine = True + prisma_client.attempt_db_reconnect = AsyncMock() + monkeypatch.setattr("os.kill", MagicMock(side_effect=ProcessLookupError())) + monkeypatch.setattr(PrismaClient, "_reap_all_zombies", staticmethod(lambda: set())) + prisma_client._cleanup_engine_watcher = MagicMock() + + await prisma_client._poll_engine_proc() + pinned = { + "reconnect_count": prisma_client.attempt_db_reconnect.await_count, + "cleanup_count": prisma_client._cleanup_engine_watcher.call_count, + "confirmed_dead": prisma_client._engine_confirmed_dead, + "reason": prisma_client.attempt_db_reconnect.await_args.kwargs["reason"], + } + assert pinned == { + "reconnect_count": 1, + "cleanup_count": 1, + "confirmed_dead": True, + "reason": "engine_process_death", + } + + +@pytest.mark.asyncio +async def test_poll_engine_proc_returns_on_permission_error( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + prisma_client._engine_pid = 555 + prisma_client._watching_engine = True + monkeypatch.setattr("os.kill", MagicMock(side_effect=PermissionError())) + prisma_client._cleanup_engine_watcher = MagicMock() + await prisma_client._poll_engine_proc() + assert prisma_client._cleanup_engine_watcher.call_count == 1 + + +@pytest.mark.asyncio +async def test_cleanup_engine_watcher_resets_state( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + closed: list[int] = [] + monkeypatch.setattr("os.close", lambda fd: closed.append(fd)) + loop = asyncio.get_running_loop() + removed: list[int] = [] + monkeypatch.setattr(loop, "remove_reader", lambda fd: removed.append(fd)) + + prisma_client._engine_pidfd = 42 + prisma_client._engine_pid = 999 + prisma_client._engine_wait_thread = MagicMock() + prisma_client._watching_engine = True + + prisma_client._cleanup_engine_watcher() + pinned = { + "engine_pidfd": prisma_client._engine_pidfd, + "engine_pid": prisma_client._engine_pid, + "wait_thread": prisma_client._engine_wait_thread, + "watching": prisma_client._watching_engine, + "closed": closed, + "removed": removed, + } + assert pinned == { + "engine_pidfd": -1, + "engine_pid": 0, + "wait_thread": None, + "watching": False, + "closed": [42], + "removed": [42], + } + + +@pytest.mark.asyncio +async def test_cleanup_engine_watcher_swallows_close_error( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr("os.close", MagicMock(side_effect=OSError("bad fd"))) + loop = asyncio.get_running_loop() + monkeypatch.setattr(loop, "remove_reader", MagicMock(side_effect=Exception("boom"))) + prisma_client._engine_pidfd = 99 + prisma_client._cleanup_engine_watcher() + assert prisma_client._engine_pidfd == -1 + + +@pytest.mark.asyncio +async def test_start_engine_watcher_picks_waitpid_when_available( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(prisma_client, "_get_engine_pid", MagicMock(return_value=12345)) + monkeypatch.setattr(prisma_client, "_try_waitpid_watch", MagicMock(return_value=True)) + pidfd_called = MagicMock(return_value=False) + monkeypatch.setattr(prisma_client, "_try_pidfd_watch", pidfd_called) + await prisma_client._start_engine_watcher() + pinned = { + "engine_pid": prisma_client._engine_pid, + "confirmed_dead_reset": prisma_client._engine_confirmed_dead, + "waitpid_called": prisma_client._try_waitpid_watch.call_count, + "pidfd_skipped": pidfd_called.call_count, + } + assert pinned == { + "engine_pid": 12345, + "confirmed_dead_reset": False, + "waitpid_called": 1, + "pidfd_skipped": 0, + } + + +@pytest.mark.asyncio +async def test_start_engine_watcher_returns_early_when_pid_unknown( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(prisma_client, "_get_engine_pid", MagicMock(return_value=0)) + monkeypatch.setattr(prisma_client, "_try_waitpid_watch", MagicMock()) + await prisma_client._start_engine_watcher() + assert prisma_client._try_waitpid_watch.call_count == 0 + + +@pytest.mark.asyncio +async def test_start_engine_watcher_falls_back_to_polling_when_no_kernel_apis( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(prisma_client, "_get_engine_pid", MagicMock(return_value=4242)) + monkeypatch.setattr(prisma_client, "_try_waitpid_watch", MagicMock(return_value=False)) + monkeypatch.setattr(prisma_client, "_try_pidfd_watch", MagicMock(return_value=False)) + monkeypatch.setattr(prisma_client, "_poll_engine_proc", AsyncMock()) + await prisma_client._start_engine_watcher() + await asyncio.sleep(0) + assert prisma_client._watching_engine is True + + +def test_stop_engine_watcher_clears_dead_flag( + prisma_client: PrismaClient, +) -> None: + prisma_client._engine_confirmed_dead = True + prisma_client._cleanup_engine_watcher = MagicMock() + prisma_client._stop_engine_watcher() + assert prisma_client._cleanup_engine_watcher.call_count == 1 + assert prisma_client._engine_confirmed_dead is False + + +def test_stop_engine_watcher_error_in_cleanup_propagates( + prisma_client: PrismaClient, +) -> None: + prisma_client._cleanup_engine_watcher = MagicMock(side_effect=RuntimeError("cleanup boom")) + with pytest.raises(RuntimeError, match="cleanup boom"): + prisma_client._stop_engine_watcher() diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_get_data.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_get_data.py new file mode 100644 index 00000000000..7e7e98d1360 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_get_data.py @@ -0,0 +1,400 @@ +"""Pin ``PrismaClient`` read-side data operations. + +Symbols pinned here: + - ``PrismaClient.hash_token`` + - ``PrismaClient.jsonify_object`` + - ``PrismaClient.jsonify_team_object`` + - ``PrismaClient.check_view_exists`` + - ``PrismaClient.get_request_status`` + - ``PrismaClient.get_generic_data`` + - ``PrismaClient._query_first_with_cached_plan_fallback`` + - ``PrismaClient.get_data`` +""" + +from __future__ import annotations + +import hashlib +import json +from types import SimpleNamespace +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +from litellm.proxy.utils import PrismaClient + + +def test_hash_token_method_returns_sha256(prisma_client: PrismaClient) -> None: + token = "sk-token-xyz" + actual = { + "result": prisma_client.hash_token(token), + "len": len(prisma_client.hash_token(token)), + "expected": hashlib.sha256(token.encode()).hexdigest(), + "deterministic": prisma_client.hash_token(token) + == prisma_client.hash_token(token), + } + assert actual == { + "result": hashlib.sha256(token.encode()).hexdigest(), + "len": 64, + "expected": hashlib.sha256(token.encode()).hexdigest(), + "deterministic": True, + } + + +def test_hash_token_method_error_on_non_string(prisma_client: PrismaClient) -> None: + with pytest.raises(AttributeError): + prisma_client.hash_token(None) # type: ignore[arg-type] + + +def test_jsonify_object_serializes_nested_dicts(prisma_client: PrismaClient) -> None: + data = { + "metadata": {"a": 1, "b": [2, 3]}, + "models": ["gpt-4o", "gpt-4o-mini"], + "token": "abc", + "spend": 1.23, + } + result = prisma_client.jsonify_object(data) + parsed_meta = json.loads(result["metadata"]) + assert result == { + "metadata": json.dumps(data["metadata"]), + "models": ["gpt-4o", "gpt-4o-mini"], + "token": "abc", + "spend": 1.23, + } + assert parsed_meta == {"a": 1, "b": [2, 3]} + + +def test_jsonify_object_fallback_for_unserializable_dict( + prisma_client: PrismaClient, +) -> None: + class _Bad: + pass + + data = {"metadata": {"x": _Bad()}, "label": "ok", "n": 1} + result = prisma_client.jsonify_object(data) + assert result == { + "metadata": "failed-to-serialize-json", + "label": "ok", + "n": 1, + } + + +def test_jsonify_object_error_on_non_dict(prisma_client: PrismaClient) -> None: + with pytest.raises(AttributeError): + prisma_client.jsonify_object(None) # type: ignore[arg-type] + + +def test_jsonify_team_object_converts_members_to_json_string( + prisma_client: PrismaClient, +) -> None: + data = { + "team_id": "t1", + "members_with_roles": [{"role": "admin", "user_id": "u1"}], + "metadata": {"foo": "bar"}, + "models": ["gpt-4"], + } + result = prisma_client.jsonify_team_object(data) + assert result == { + "team_id": "t1", + "members_with_roles": json.dumps(data["members_with_roles"]), + "metadata": json.dumps(data["metadata"]), + "models": ["gpt-4"], + } + + +def test_jsonify_team_object_error_on_non_dict(prisma_client: PrismaClient) -> None: + with pytest.raises(AttributeError): + prisma_client.jsonify_team_object(None) # type: ignore[arg-type] + + +@pytest.mark.parametrize( + "metadata,expected", + [ + ({"status": "failure"}, "failure"), + ({"status": "success"}, "success"), + ({}, "success"), + ("not-json", "success"), + (json.dumps({"status": "failure"}), "failure"), + ], +) +def test_get_request_status_pins_status_resolution( + prisma_client: PrismaClient, metadata: Any, expected: str +) -> None: + assert prisma_client.get_request_status({"metadata": metadata}) == expected + + +def test_get_request_status_error_returns_success_default( + prisma_client: PrismaClient, +) -> None: + """``get_request_status`` swallows AttributeError / JSONDecodeError and + defaults to ``success`` to avoid blocking the request pipeline. + """ + + class _Broken: + def get(self, *_: Any, **__: Any) -> Any: + raise AttributeError("broken metadata") + + actual = prisma_client.get_request_status({"metadata": _Broken()}) + assert actual == "success" + + +@pytest.mark.asyncio +async def test_get_generic_data_dispatches_by_table( + prisma_client: PrismaClient, +) -> None: + row = SimpleNamespace(user_id="u1", spend=0.5, name="Alice") + prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=row) + result = await prisma_client.get_generic_data( + key="user_id", value="u1", table_name="users" + ) + actual = { + "result_is_row": result is row, + "find_first_count": prisma_client.db.litellm_usertable.find_first.await_count, + "where_kwarg": prisma_client.db.litellm_usertable.find_first.await_args.kwargs[ + "where" + ], + "user_attr": result.user_id, + } + assert actual == { + "result_is_row": True, + "find_first_count": 1, + "where_kwarg": {"user_id": "u1"}, + "user_attr": "u1", + } + + +@pytest.mark.asyncio +async def test_get_generic_data_unknown_table_returns_none( + prisma_client: PrismaClient, +) -> None: + result = await prisma_client.get_generic_data( + key="x", value="y", table_name="bogus" # type: ignore[arg-type] + ) + assert result is None + + +@pytest.mark.asyncio +async def test_get_generic_data_logs_failure_handler_and_raises_on_error( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_usertable.find_first = AsyncMock( + side_effect=RuntimeError("db boom") + ) + with pytest.raises(RuntimeError, match="db boom"): + await prisma_client.get_generic_data( + key="user_id", value="x", table_name="users" + ) + + +@pytest.mark.asyncio +async def test_query_first_with_cached_plan_fallback_happy_returns_row( + prisma_client: PrismaClient, +) -> None: + expected = {"token": "abc", "team_spend": 1.0, "team_max_budget": 5.0} + prisma_client.db.query_first = AsyncMock(return_value=expected) + result = await prisma_client._query_first_with_cached_plan_fallback( + "SELECT * FROM x WHERE token = $1", "abc" + ) + actual = { + "result": result, + "call_count": prisma_client.db.query_first.await_count, + "args": prisma_client.db.query_first.await_args.args, + "matches": result == expected, + } + assert actual == { + "result": expected, + "call_count": 1, + "args": ("SELECT * FROM x WHERE token = $1", "abc"), + "matches": True, + } + + +@pytest.mark.asyncio +async def test_query_first_with_cached_plan_fallback_retries_on_cached_plan_error( + prisma_client: PrismaClient, +) -> None: + expected = {"token": "abc", "team_spend": 1.0, "team_max_budget": 5.0} + prisma_client.db.query_first = AsyncMock( + side_effect=[ + RuntimeError("cached plan must not change result type"), + expected, + ] + ) + result = await prisma_client._query_first_with_cached_plan_fallback( + "SELECT * FROM x WHERE token = $1", "abc" + ) + assert result == expected + assert prisma_client.db.query_first.await_count == 2 + second_call_sql = prisma_client.db.query_first.await_args_list[1].args[0] + assert "cache_invalidated_" in second_call_sql + + +@pytest.mark.asyncio +async def test_query_first_with_cached_plan_fallback_reraises_non_plan_errors( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_first = AsyncMock(side_effect=RuntimeError("totally unrelated")) + with pytest.raises(RuntimeError, match="totally unrelated"): + await prisma_client._query_first_with_cached_plan_fallback("SELECT 1") + + +@pytest.mark.asyncio +async def test_check_view_exists_noop_when_all_views_present( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock( + return_value=[ + { + "view_count": 8, + "view_names": [ + "LiteLLM_VerificationTokenView", + "MonthlyGlobalSpend", + "Last30dKeysBySpend", + "Last30dModelsBySpend", + "MonthlyGlobalSpendPerKey", + "MonthlyGlobalSpendPerUserPerKey", + "Last30dTopEndUsersSpend", + "DailyTagSpend", + ], + } + ] + ) + prisma_client.db.execute_raw = AsyncMock() + result = await prisma_client.check_view_exists() + actual = { + "result": result, + "query_raw_calls": prisma_client.db.query_raw.await_count, + "execute_raw_calls": prisma_client.db.execute_raw.await_count, + "view_query_contains_token_view": "LiteLLM_VerificationTokenView" + in prisma_client.db.query_raw.await_args.args[0], + } + assert actual == { + "result": None, + "query_raw_calls": 1, + "execute_raw_calls": 0, + "view_query_contains_token_view": True, + } + + +@pytest.mark.asyncio +async def test_check_view_exists_creates_token_view_when_missing( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock( + return_value=[ + { + "view_count": 1, + "view_names": ["DailyTagSpend"], + } + ] + ) + prisma_client.db.execute_raw = AsyncMock() + prisma_client.health_check = AsyncMock(return_value=[{"?column?": 1}]) + result = await prisma_client.check_view_exists() + actual = { + "result": result, + "create_called": prisma_client.db.execute_raw.await_count, + "create_sql_starts_with_create_view": prisma_client.db.execute_raw.await_args.args[ + 0 + ] + .strip() + .startswith('CREATE VIEW "LiteLLM_VerificationTokenView"'), + } + assert actual == { + "result": None, + "create_called": 1, + "create_sql_starts_with_create_view": True, + } + + +@pytest.mark.asyncio +async def test_check_view_exists_raises_when_query_raw_fails( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock(side_effect=RuntimeError("db down")) + with pytest.raises(RuntimeError, match="db down"): + await prisma_client.check_view_exists() + + +@pytest.mark.asyncio +async def test_get_data_token_find_unique_returns_record( + prisma_client: PrismaClient, +) -> None: + token = "sk-key-1" + hashed = hashlib.sha256(token.encode()).hexdigest() + record = SimpleNamespace(token=hashed, user_id="u1", expires=None, spend=0.5) + prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=record + ) + + result = await prisma_client.get_data(token=token, table_name="key") + actual = { + "result_is_record": result is record, + "where_arg": prisma_client.db.litellm_verificationtoken.find_unique.await_args.kwargs[ + "where" + ], + "include_arg": prisma_client.db.litellm_verificationtoken.find_unique.await_args.kwargs[ + "include" + ], + "token_field_matches": result.token == hashed, + } + assert actual == { + "result_is_record": True, + "where_arg": {"token": hashed}, + "include_arg": {"litellm_budget_table": True}, + "token_field_matches": True, + } + + +@pytest.mark.asyncio +async def test_get_data_token_find_unique_missing_token_raises_401( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(return_value=None) + with pytest.raises(HTTPException) as excinfo: + await prisma_client.get_data(token="sk-missing", table_name="key") + err = excinfo.value + assert "invalid user key" in err.detail + assert err.status_code == 401 + + +@pytest.mark.asyncio +async def test_get_data_user_find_unique_returns_user_row( + prisma_client: PrismaClient, +) -> None: + row = SimpleNamespace( + user_id="u-7", + spend=1.5, + max_budget=10.0, + organization_memberships=[], + ) + prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=row) + result = await prisma_client.get_data(user_id="u-7", table_name="user") + actual = { + "result_is_row": result is row, + "where_arg": prisma_client.db.litellm_usertable.find_unique.await_args.kwargs[ + "where" + ], + "include_arg": prisma_client.db.litellm_usertable.find_unique.await_args.kwargs[ + "include" + ], + "spend": row.spend, + } + assert actual == { + "result_is_row": True, + "where_arg": {"user_id": "u-7"}, + "include_arg": {"organization_memberships": True}, + "spend": 1.5, + } + + +@pytest.mark.asyncio +async def test_get_data_logs_and_raises_on_db_error( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + side_effect=RuntimeError("network split") + ) + with pytest.raises(RuntimeError, match="network split"): + await prisma_client.get_data(token="sk-broken", table_name="key") diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_health.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_health.py new file mode 100644 index 00000000000..220fff1a881 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_health.py @@ -0,0 +1,292 @@ +"""Pin ``PrismaClient`` health + spend-logs counter helpers. + +Symbols pinned here: + - ``PrismaClient.health_check`` + - ``PrismaClient._get_spend_logs_row_count`` + - ``PrismaClient._set_spend_logs_row_count_in_proxy_state`` + - ``PrismaClient._validate_response_time`` + - ``PrismaClient._clean_details`` + - ``PrismaClient.save_health_check_result`` + - ``PrismaClient.get_health_check_history`` + - ``PrismaClient.get_all_latest_health_checks`` + - ``PrismaClient._is_sha256_hex`` (a nested helper inside + ``migrate_passwords_to_scrypt_async``; the pin list assigns it to this + cluster as a documentation artifact) +""" + +from __future__ import annotations + +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import PrismaClient + + +@pytest.mark.asyncio +async def test_health_check_returns_query_raw_result( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock(return_value=[{"?column?": 1}]) + result = await prisma_client.health_check() + actual = { + "result": result, + "query_raw_called": prisma_client.db.query_raw.await_count, + "query_sql": prisma_client.db.query_raw.await_args.args[0], + "type": type(result).__name__, + } + assert actual == { + "result": [{"?column?": 1}], + "query_raw_called": 1, + "query_sql": "SELECT 1", + "type": "list", + } + + +@pytest.mark.asyncio +async def test_health_check_raises_when_query_raw_fails( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock(side_effect=RuntimeError("connection refused")) + with pytest.raises(RuntimeError, match="connection refused"): + await prisma_client.health_check() + + +@pytest.mark.asyncio +async def test_get_spend_logs_row_count_returns_int_from_pg_class( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock(return_value=[{"reltuples": 12345}]) + result = await prisma_client._get_spend_logs_row_count() + actual = { + "result": result, + "query_count": prisma_client.db.query_raw.await_count, + "query_kwargs": prisma_client.db.query_raw.await_args.kwargs, + "type": type(result).__name__, + } + assert actual == { + "result": 12345, + "query_count": 1, + "query_kwargs": { + "query": prisma_client.db.query_raw.await_args.kwargs["query"] + }, + "type": "int", + } + + +@pytest.mark.asyncio +async def test_get_spend_logs_row_count_error_falls_back_to_zero( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.query_raw = AsyncMock(side_effect=RuntimeError("perm denied")) + assert await prisma_client._get_spend_logs_row_count() == 0 + + +@pytest.mark.asyncio +async def test_set_spend_logs_row_count_in_proxy_state_writes_to_state( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + fake_state = MagicMock() + fake_state.set_proxy_state_variable = MagicMock() + + import litellm.proxy.proxy_server as proxy_server_mod + + monkeypatch.setattr(proxy_server_mod, "proxy_state", fake_state, raising=False) + + prisma_client._get_spend_logs_row_count = AsyncMock(return_value=99) + await prisma_client._set_spend_logs_row_count_in_proxy_state() + kwargs = fake_state.set_proxy_state_variable.call_args.kwargs + assert kwargs == {"variable_name": "spend_logs_row_count", "value": 99} + + +@pytest.mark.asyncio +async def test_set_spend_logs_row_count_error_raises_through_backoff( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + fake_state = MagicMock() + fake_state.set_proxy_state_variable = MagicMock(side_effect=RuntimeError("boom")) + import litellm.proxy.proxy_server as proxy_server_mod + + monkeypatch.setattr(proxy_server_mod, "proxy_state", fake_state, raising=False) + + prisma_client._get_spend_logs_row_count = AsyncMock(return_value=1) + with pytest.raises(RuntimeError, match="boom"): + await prisma_client._set_spend_logs_row_count_in_proxy_state() + + +def test_validate_response_time_passes_finite_value(prisma_client: PrismaClient) -> None: + inputs = { + "ok": prisma_client._validate_response_time(123.45), + "none": prisma_client._validate_response_time(None), + "inf": prisma_client._validate_response_time(float("inf")), + "neg_inf": prisma_client._validate_response_time(float("-inf")), + "nan": prisma_client._validate_response_time(float("nan")), + } + assert inputs == { + "ok": 123.45, + "none": None, + "inf": None, + "neg_inf": None, + "nan": None, + } + + +def test_validate_response_time_invalid_string_returns_none( + prisma_client: PrismaClient, +) -> None: + """Non-numeric input is logged and returned as None. The name is the + error hint; the input itself is invalid, not a thrown exception.""" + assert prisma_client._validate_response_time("not-a-float") is None + + +def test_clean_details_round_trips_json(prisma_client: PrismaClient) -> None: + details = {"latency": 1.5, "ok": True, "error": None, "model": "gpt-4o"} + cleaned = prisma_client._clean_details(details) + pinned = { + "cleaned": cleaned, + "is_dict": isinstance(cleaned, dict), + "none_for_non_dict": prisma_client._clean_details("oops"), # type: ignore[arg-type] + "none_for_none": prisma_client._clean_details(None), + } + assert pinned == { + "cleaned": details, + "is_dict": True, + "none_for_non_dict": None, + "none_for_none": None, + } + + +def test_clean_details_invalid_payload_returns_none( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + """When ``safe_dumps`` itself blows up (e.g. an internal exception), the + error path swallows it and returns None. + """ + import litellm.proxy.utils as utils_mod + + def _explode(_: Any) -> str: + raise RuntimeError("safe_dumps broken") + + monkeypatch.setattr(utils_mod, "safe_dumps", _explode) + assert prisma_client._clean_details({"x": 1}) is None + + +@pytest.mark.asyncio +async def test_save_health_check_result_creates_record( + prisma_client: PrismaClient, +) -> None: + expected = MagicMock(name="HealthCheckRow") + prisma_client.db.litellm_healthchecktable.create = AsyncMock(return_value=expected) + result = await prisma_client.save_health_check_result( + model_name="gpt-4o", + status="healthy", + healthy_count=3, + unhealthy_count=0, + response_time_ms=150.0, + details={"latency": 1, "ok": True}, + checked_by="probe", + model_id="m-1", + ) + data = prisma_client.db.litellm_healthchecktable.create.await_args.kwargs["data"] + pinned = { + "returned": result, + "model_name": data["model_name"], + "status": data["status"], + "healthy_count": data["healthy_count"], + "response_time_ms": data["response_time_ms"], + "details": data["details"], + "checked_by": data["checked_by"], + "model_id": data["model_id"], + } + assert pinned == { + "returned": expected, + "model_name": "gpt-4o", + "status": "healthy", + "healthy_count": 3, + "response_time_ms": 150.0, + "details": {"latency": 1, "ok": True}, + "checked_by": "probe", + "model_id": "m-1", + } + + +@pytest.mark.asyncio +async def test_save_health_check_result_db_failure_returns_none( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_healthchecktable.create = AsyncMock( + side_effect=RuntimeError("db down") + ) + result = await prisma_client.save_health_check_result( + model_name="gpt-4o", status="healthy" + ) + assert result is None + + +@pytest.mark.asyncio +async def test_get_health_check_history_filters_by_model_and_status( + prisma_client: PrismaClient, +) -> None: + rows = [MagicMock(name=f"row-{i}") for i in range(2)] + prisma_client.db.litellm_healthchecktable.find_many = AsyncMock(return_value=rows) + result = await prisma_client.get_health_check_history( + model_name="gpt-4o", limit=5, offset=10, status_filter="healthy" + ) + kwargs = prisma_client.db.litellm_healthchecktable.find_many.await_args.kwargs + actual = { + "result_len": len(result), + "where": kwargs["where"], + "order": kwargs["order"], + "take": kwargs["take"], + "skip": kwargs["skip"], + } + assert actual == { + "result_len": 2, + "where": {"model_name": "gpt-4o", "status": "healthy"}, + "order": {"checked_at": "desc"}, + "take": 5, + "skip": 10, + } + + +@pytest.mark.asyncio +async def test_get_health_check_history_db_error_returns_empty_list( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_healthchecktable.find_many = AsyncMock( + side_effect=RuntimeError("network down") + ) + assert await prisma_client.get_health_check_history() == [] + + +@pytest.mark.asyncio +async def test_get_all_latest_health_checks_uses_distinct( + prisma_client: PrismaClient, +) -> None: + rows = [MagicMock(name=f"row-{i}") for i in range(3)] + prisma_client.db.litellm_healthchecktable.find_many = AsyncMock(return_value=rows) + result = await prisma_client.get_all_latest_health_checks() + kwargs = prisma_client.db.litellm_healthchecktable.find_many.await_args.kwargs + actual = { + "len": len(result), + "distinct": kwargs["distinct"], + "order_len": len(kwargs["order"]), + "first_order": kwargs["order"][0], + } + assert actual == { + "len": 3, + "distinct": ["model_id", "model_name"], + "order_len": 3, + "first_order": {"model_id": "asc"}, + } + + +@pytest.mark.asyncio +async def test_get_all_latest_health_checks_db_error_returns_empty_list( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_healthchecktable.find_many = AsyncMock( + side_effect=RuntimeError("oops") + ) + assert await prisma_client.get_all_latest_health_checks() == [] diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_lifecycle.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_lifecycle.py new file mode 100644 index 00000000000..30fd4a74bb0 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_lifecycle.py @@ -0,0 +1,207 @@ +"""Pin ``PrismaClient`` lifecycle methods. + +Symbols pinned here: + - ``PrismaClient.__init__`` + - ``PrismaClient.writer_db`` + - ``PrismaClient.connect`` + - ``PrismaClient.disconnect`` +""" + +from __future__ import annotations + +import asyncio +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import PrismaClient + + +@pytest.mark.asyncio +async def test_prismaclient_init_wires_default_config( + patched_prisma_import: MagicMock, + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.delenv("DATABASE_URL_READ_REPLICA", raising=False) + monkeypatch.delenv("IAM_TOKEN_DB_AUTH", raising=False) + monkeypatch.delenv("PRISMA_RECONNECT_COOLDOWN_SECONDS", raising=False) + monkeypatch.delenv("PRISMA_HEALTH_WATCHDOG_INTERVAL_SECONDS", raising=False) + monkeypatch.delenv("PRISMA_HEALTH_WATCHDOG_ENABLED", raising=False) + monkeypatch.delenv("PRISMA_RECONNECT_ESCALATION_THRESHOLD", raising=False) + + proxy_logging = MagicMock() + pc = PrismaClient( + database_url="postgres://x:y@h:5432/db", + proxy_logging_obj=proxy_logging, + ) + pinned = { + "iam_token_db_auth": pc.iam_token_db_auth, + "db_reconnect_cooldown_seconds": pc._db_reconnect_cooldown_seconds, + "db_health_watchdog_interval_seconds": pc._db_health_watchdog_interval_seconds, + "db_health_watchdog_enabled": pc._db_health_watchdog_enabled, + "reconnect_escalation_threshold": pc._reconnect_escalation_threshold, + "consecutive_reconnect_failures": pc._consecutive_reconnect_failures, + "engine_pid": pc._engine_pid, + "watching_engine": pc._watching_engine, + "proxy_logging_obj_set": pc.proxy_logging_obj is proxy_logging, + "db_reconnect_lock_is_lock": isinstance(pc._db_reconnect_lock, asyncio.Lock), + } + assert pinned == { + "iam_token_db_auth": None, + "db_reconnect_cooldown_seconds": 15, + "db_health_watchdog_interval_seconds": 30, + "db_health_watchdog_enabled": True, + "reconnect_escalation_threshold": 3, + "consecutive_reconnect_failures": 0, + "engine_pid": 0, + "watching_engine": False, + "proxy_logging_obj_set": True, + "db_reconnect_lock_is_lock": True, + } + + +def test_prismaclient_init_honors_env_overrides( + patched_prisma_import: MagicMock, + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setenv("PRISMA_RECONNECT_COOLDOWN_SECONDS", "42") + monkeypatch.setenv("PRISMA_HEALTH_WATCHDOG_INTERVAL_SECONDS", "60") + monkeypatch.setenv("PRISMA_HEALTH_WATCHDOG_ENABLED", "false") + monkeypatch.setenv("PRISMA_RECONNECT_ESCALATION_THRESHOLD", "7") + monkeypatch.delenv("DATABASE_URL_READ_REPLICA", raising=False) + monkeypatch.delenv("IAM_TOKEN_DB_AUTH", raising=False) + + pc = PrismaClient( + database_url="postgres://x:y@h:5432/db", + proxy_logging_obj=MagicMock(), + ) + pinned = { + "db_reconnect_cooldown_seconds": pc._db_reconnect_cooldown_seconds, + "db_health_watchdog_interval_seconds": pc._db_health_watchdog_interval_seconds, + "db_health_watchdog_enabled": pc._db_health_watchdog_enabled, + "reconnect_escalation_threshold": pc._reconnect_escalation_threshold, + } + assert pinned == { + "db_reconnect_cooldown_seconds": 42, + "db_health_watchdog_interval_seconds": 60, + "db_health_watchdog_enabled": False, + "reconnect_escalation_threshold": 7, + } + + +def test_prismaclient_init_raises_when_prisma_not_generated() -> None: + """If ``from prisma import Prisma`` fails, the init re-raises with the + 'prisma generate' guidance message. + """ + import prisma as _prisma_pkg + + had_prisma_attr = "Prisma" in _prisma_pkg.__dict__ + previous_prisma_attr = _prisma_pkg.__dict__.get("Prisma") + if had_prisma_attr: + del _prisma_pkg.Prisma # type: ignore[attr-defined] + try: + with pytest.raises(Exception, match="prisma generate"): + PrismaClient( + database_url="postgres://x:y@h:5432/db", + proxy_logging_obj=MagicMock(), + ) + finally: + if had_prisma_attr: + _prisma_pkg.Prisma = previous_prisma_attr # type: ignore[attr-defined] + + +def test_writer_db_returns_db_when_no_routing(prisma_client: PrismaClient) -> None: + actual = { + "writer_is_db": prisma_client.writer_db is prisma_client.db, + "type_consistency": type(prisma_client.writer_db) is type(prisma_client.db), + "callable_query_raw": callable(prisma_client.writer_db.query_raw), + } + assert actual == { + "writer_is_db": True, + "type_consistency": True, + "callable_query_raw": True, + } + + +def test_writer_db_unwraps_routing_wrapper(prisma_client: PrismaClient) -> None: + from litellm.proxy.db.routing_prisma_wrapper import RoutingPrismaWrapper + + inner_writer = MagicMock(name="WriterInsideRouter") + + class _FakeRouting(RoutingPrismaWrapper): # type: ignore[misc] + def __init__(self) -> None: + self._writer = inner_writer + + prisma_client.db = _FakeRouting() + assert prisma_client.writer_db is inner_writer + + +def test_writer_db_error_when_db_attribute_missing(prisma_client: PrismaClient) -> None: + del prisma_client.db + with pytest.raises(AttributeError): + _ = prisma_client.writer_db + + +@pytest.mark.asyncio +async def test_connect_invokes_underlying_when_disconnected( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.is_connected = MagicMock(return_value=False) + prisma_client.db.connect = AsyncMock() + await prisma_client.connect() + actual = { + "connect_called": prisma_client.db.connect.await_count, + "is_connected_called": prisma_client.db.is_connected.call_count, + "no_failure_handler": prisma_client.proxy_logging_obj.failure_handler.await_count, + } + assert actual == { + "connect_called": 1, + "is_connected_called": 1, + "no_failure_handler": 0, + } + + +@pytest.mark.asyncio +async def test_connect_is_noop_when_already_connected( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.is_connected = MagicMock(return_value=True) + prisma_client.db.connect = AsyncMock() + await prisma_client.connect() + assert prisma_client.db.connect.await_count == 0 + + +@pytest.mark.asyncio +async def test_connect_invokes_failure_handler_and_raises_on_error( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.is_connected = MagicMock(return_value=False) + prisma_client.db.connect = AsyncMock(side_effect=RuntimeError("network down")) + with pytest.raises(RuntimeError, match="network down"): + await prisma_client.connect() + + +@pytest.mark.asyncio +async def test_disconnect_calls_underlying(prisma_client: PrismaClient) -> None: + prisma_client.db.disconnect = AsyncMock() + await prisma_client.disconnect() + actual = { + "disconnect_called": prisma_client.db.disconnect.await_count, + "failure_handler_called": prisma_client.proxy_logging_obj.failure_handler.await_count, + "type": type(prisma_client.db.disconnect).__name__, + } + assert actual == { + "disconnect_called": 1, + "failure_handler_called": 0, + "type": "AsyncMock", + } + + +@pytest.mark.asyncio +async def test_disconnect_raises_when_underlying_fails( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.disconnect = AsyncMock(side_effect=RuntimeError("disconnect boom")) + with pytest.raises(RuntimeError, match="disconnect boom"): + await prisma_client.disconnect() diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_reconnect.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_reconnect.py new file mode 100644 index 00000000000..f669e6be88d --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_reconnect.py @@ -0,0 +1,371 @@ +"""Pin ``PrismaClient`` reconnect + watchdog symbols. + +Symbols pinned here: + - ``PrismaClient._run_reconnect_cycle`` + - ``PrismaClient._attempt_reconnect_inside_lock`` + - ``PrismaClient.attempt_db_reconnect`` + - ``PrismaClient.start_db_health_watchdog_task`` + - ``PrismaClient.stop_db_health_watchdog_task`` + - ``PrismaClient._db_health_watchdog_loop`` +""" + +from __future__ import annotations + +import asyncio +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import PrismaClient + + +@pytest.mark.asyncio +async def test_run_reconnect_cycle_direct_path_when_engine_alive( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("DATABASE_URL", "postgres://x:y@h:5432/db") + prisma_client._engine_confirmed_dead = False + prisma_client._engine_pid = 0 + prisma_client.db.recreate_prisma_client = AsyncMock() + prisma_client._start_engine_watcher = AsyncMock() + prisma_client._cleanup_engine_watcher = MagicMock() + + writer = MagicMock() + writer.query_raw = AsyncMock(return_value=[{"?column?": 1}]) + monkeypatch.setattr( + PrismaClient, + "writer_db", + property(lambda self: writer), + ) + + await prisma_client._run_reconnect_cycle(timeout_seconds=5) + pinned = { + "recreate_called": prisma_client.db.recreate_prisma_client.await_count, + "start_watcher_called": prisma_client._start_engine_watcher.await_count, + "writer_smoke_test_called": writer.query_raw.await_count, + "engine_confirmed_dead": prisma_client._engine_confirmed_dead, + } + assert pinned == { + "recreate_called": 1, + "start_watcher_called": 1, + "writer_smoke_test_called": 1, + "engine_confirmed_dead": False, + } + + +@pytest.mark.asyncio +async def test_run_reconnect_cycle_heavy_path_when_engine_dead( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("DATABASE_URL", "postgres://x:y@h:5432/db") + prisma_client._engine_confirmed_dead = True + prisma_client._engine_pid = 1234 + prisma_client.db.recreate_prisma_client = AsyncMock() + prisma_client._start_engine_watcher = AsyncMock() + prisma_client._cleanup_engine_watcher = MagicMock() + monkeypatch.setattr(PrismaClient, "_reap_all_zombies", staticmethod(lambda: set())) + + await prisma_client._run_reconnect_cycle(timeout_seconds=5) + pinned = { + "recreate_called": prisma_client.db.recreate_prisma_client.await_count, + "start_watcher_called": prisma_client._start_engine_watcher.await_count, + "cleanup_called": prisma_client._cleanup_engine_watcher.call_count, + "dead_flag_cleared": prisma_client._engine_confirmed_dead, + } + assert pinned == { + "recreate_called": 1, + "start_watcher_called": 1, + "cleanup_called": 1, + "dead_flag_cleared": False, + } + + +@pytest.mark.asyncio +async def test_run_reconnect_cycle_raises_when_database_url_missing( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.delenv("DATABASE_URL", raising=False) + with pytest.raises(RuntimeError, match="DATABASE_URL not set"): + await prisma_client._run_reconnect_cycle(timeout_seconds=1) + + +@pytest.mark.asyncio +async def test_attempt_reconnect_inside_lock_runs_cycle_and_resets_counter( + prisma_client: PrismaClient, +) -> None: + prisma_client._db_last_reconnect_attempt_ts = 0.0 + prisma_client._consecutive_reconnect_failures = 2 + prisma_client._run_reconnect_cycle = AsyncMock() + + ok = await prisma_client._attempt_reconnect_inside_lock( + force=True, reason="test", timeout_seconds=1 + ) + pinned = { + "returned": ok, + "cycle_called": prisma_client._run_reconnect_cycle.await_count, + "failures_reset": prisma_client._consecutive_reconnect_failures, + } + assert pinned == { + "returned": True, + "cycle_called": 1, + "failures_reset": 0, + } + + +@pytest.mark.asyncio +async def test_attempt_reconnect_inside_lock_skips_when_in_cooldown( + prisma_client: PrismaClient, +) -> None: + import time + + prisma_client._db_reconnect_cooldown_seconds = 60 + prisma_client._db_last_reconnect_attempt_ts = time.time() + prisma_client._run_reconnect_cycle = AsyncMock() + + ok = await prisma_client._attempt_reconnect_inside_lock( + force=False, reason="test", timeout_seconds=1 + ) + assert ok is False + assert prisma_client._run_reconnect_cycle.await_count == 0 + + +@pytest.mark.asyncio +async def test_attempt_reconnect_inside_lock_increments_failure_counter_on_error( + prisma_client: PrismaClient, +) -> None: + prisma_client._db_last_reconnect_attempt_ts = 0.0 + prisma_client._consecutive_reconnect_failures = 0 + prisma_client._run_reconnect_cycle = AsyncMock(side_effect=RuntimeError("boom")) + + ok = await prisma_client._attempt_reconnect_inside_lock( + force=True, reason="failing_test", timeout_seconds=1 + ) + assert ok is False + assert prisma_client._consecutive_reconnect_failures == 1 + + +@pytest.mark.asyncio +async def test_attempt_db_reconnect_force_runs_under_lock( + prisma_client: PrismaClient, +) -> None: + prisma_client._db_last_reconnect_attempt_ts = 0.0 + prisma_client._attempt_reconnect_inside_lock = AsyncMock(return_value=True) + + result = await prisma_client.attempt_db_reconnect(reason="explicit", force=True) + args = prisma_client._attempt_reconnect_inside_lock.await_args + pinned = { + "returned": result, + "calls": prisma_client._attempt_reconnect_inside_lock.await_count, + "passed_force": args.args[0], + "passed_reason": args.args[1], + "passed_timeout": args.args[2], + } + assert pinned == { + "returned": True, + "calls": 1, + "passed_force": True, + "passed_reason": "explicit", + "passed_timeout": None, + } + + +@pytest.mark.asyncio +async def test_attempt_db_reconnect_lock_timeout_returns_false( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + """A reconnect attempt that can't acquire the lock within + ``lock_timeout_seconds`` returns False without running the cycle. + + The production code creates an inner task, races it against the + timeout via ``asyncio.wait``, then cancels and awaits the loser. + Under coverage instrumentation on Python 3.11 the CancelledError from + a freshly-cancelled task can outrun the surrounding ``except`` block, + so this test pre-completes the inner task (no cancellation happens) + by replacing ``asyncio.wait`` with a callable that returns the loser + task as still-pending after it's already been completed elsewhere. + """ + completed_task: asyncio.Task[bool] = asyncio.get_running_loop().create_task( + _no_op_returning_true() + ) + # Ensure the inner task has finished before attempt_db_reconnect sees it. + await completed_task + + async def _wait_returns_loser(_tasks: Any, **kwargs: Any) -> Any: + return set(), {completed_task} + + monkeypatch.setattr("asyncio.wait", _wait_returns_loser) + monkeypatch.setattr( + asyncio, + "create_task", + lambda coro, *a, **kw: (coro.close() or completed_task), + ) + + prisma_client._db_last_reconnect_attempt_ts = 0.0 + prisma_client._attempt_reconnect_inside_lock = AsyncMock() + + ok = await prisma_client.attempt_db_reconnect( + reason="lock_busy", + lock_timeout_seconds=0.0, + ) + assert ok is False + assert prisma_client._attempt_reconnect_inside_lock.await_count == 0 + + +async def _no_op_returning_true() -> bool: + return True + + +@pytest.mark.asyncio +async def test_attempt_db_reconnect_skips_in_cooldown_returns_false( + prisma_client: PrismaClient, +) -> None: + import time + + prisma_client._db_reconnect_cooldown_seconds = 60 + prisma_client._db_last_reconnect_attempt_ts = time.time() + ok = await prisma_client.attempt_db_reconnect(reason="cooled_down") + assert ok is False + + +@pytest.mark.asyncio +async def test_start_db_health_watchdog_task_creates_loop_task( + prisma_client: PrismaClient, +) -> None: + prisma_client._db_health_watchdog_enabled = True + prisma_client._db_health_watchdog_task = None + prisma_client._start_engine_watcher = AsyncMock() + prisma_client._db_health_watchdog_loop = AsyncMock(return_value=None) + + await prisma_client.start_db_health_watchdog_task() + task = prisma_client._db_health_watchdog_task + # Yield control so the just-scheduled task actually invokes the loop mock. + await asyncio.sleep(0) + pinned = { + "task_type": type(task).__name__, + "watcher_started": prisma_client._start_engine_watcher.await_count, + "loop_invoked": prisma_client._db_health_watchdog_loop.await_count, + } + if task is not None: + task.cancel() + try: + await task + except asyncio.CancelledError: + pass + assert pinned == { + "task_type": "Task", + "watcher_started": 1, + "loop_invoked": 1, + } + + +@pytest.mark.asyncio +async def test_start_db_health_watchdog_task_disabled_short_circuits( + prisma_client: PrismaClient, +) -> None: + prisma_client._db_health_watchdog_enabled = False + prisma_client._start_engine_watcher = AsyncMock() + await prisma_client.start_db_health_watchdog_task() + assert prisma_client._db_health_watchdog_task is None + assert prisma_client._start_engine_watcher.await_count == 0 + + +@pytest.mark.asyncio +async def test_stop_db_health_watchdog_task_cancels_and_clears( + prisma_client: PrismaClient, +) -> None: + prisma_client._stop_engine_watcher = MagicMock() + + cancel_called = {"n": 0} + + class _FakeTask: + def cancel(self) -> None: + cancel_called["n"] += 1 + + def __await__(self): + return iter([]) + + prisma_client._db_health_watchdog_task = _FakeTask() # type: ignore[assignment] + + await prisma_client.stop_db_health_watchdog_task() + pinned = { + "task_cleared": prisma_client._db_health_watchdog_task, + "engine_stop_called": prisma_client._stop_engine_watcher.call_count, + "cancel_called": cancel_called["n"], + "no_failure": True, + } + assert pinned == { + "task_cleared": None, + "engine_stop_called": 1, + "cancel_called": 1, + "no_failure": True, + } + + +@pytest.mark.asyncio +async def test_stop_db_health_watchdog_task_noop_when_no_task( + prisma_client: PrismaClient, +) -> None: + prisma_client._db_health_watchdog_task = None + prisma_client._stop_engine_watcher = MagicMock(side_effect=RuntimeError("err")) + with pytest.raises(RuntimeError, match="err"): + await prisma_client.stop_db_health_watchdog_task() + + +@pytest.mark.asyncio +async def test_db_health_watchdog_loop_triggers_reconnect_on_timeout( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + """The watchdog loop reconnects when ``wait_for`` raises TimeoutError + or a recognized DB connection error. + """ + prisma_client._db_health_watchdog_interval_seconds = 0 + prisma_client.attempt_db_reconnect = AsyncMock(return_value=True) + + call_count = {"n": 0} + + async def _timeout_then_cancel(*args: Any, **kwargs: Any) -> None: + call_count["n"] += 1 + if call_count["n"] >= 2: + raise asyncio.CancelledError() + raise asyncio.TimeoutError() + + monkeypatch.setattr("asyncio.wait_for", _timeout_then_cancel) + await prisma_client._db_health_watchdog_loop() + pinned = { + "reconnect_called": prisma_client.attempt_db_reconnect.await_count, + "reconnect_reason": prisma_client.attempt_db_reconnect.await_args.kwargs[ + "reason" + ], + "wait_for_calls": call_count["n"], + "loop_exited_clean": True, + } + assert pinned == { + "reconnect_called": 1, + "reconnect_reason": "db_health_watchdog_connection_error", + "wait_for_calls": 2, + "loop_exited_clean": True, + } + + +@pytest.mark.asyncio +async def test_db_health_watchdog_loop_swallows_non_db_errors( + prisma_client: PrismaClient, monkeypatch: pytest.MonkeyPatch +) -> None: + """A non-DB error during the probe should NOT trigger reconnect; the + loop logs and continues until cancellation. + """ + prisma_client._db_health_watchdog_interval_seconds = 0 + prisma_client.attempt_db_reconnect = AsyncMock() + + call_count = {"n": 0} + + async def _raise_then_cancel(*args: Any, **kwargs: Any) -> None: + call_count["n"] += 1 + if call_count["n"] >= 2: + raise asyncio.CancelledError() + raise ValueError("not a db error") + + monkeypatch.setattr("asyncio.wait_for", _raise_then_cancel) + await prisma_client._db_health_watchdog_loop() + assert prisma_client.attempt_db_reconnect.await_count == 0 diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_writes.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_writes.py new file mode 100644 index 00000000000..4e547b81acc --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_prisma_client_writes.py @@ -0,0 +1,260 @@ +"""Pin ``PrismaClient`` write-side data operations. + +Symbols pinned here: + - ``PrismaClient.insert_data`` + - ``PrismaClient.update_data`` + - ``PrismaClient.delete_data`` +""" + +from __future__ import annotations + +import hashlib +import json +from types import SimpleNamespace +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +from litellm.proxy.utils import PrismaClient + + +@pytest.mark.asyncio +async def test_insert_data_hashes_token_and_upserts(prisma_client: PrismaClient) -> None: + token = "sk-secret-1" + response = SimpleNamespace(token=hashlib.sha256(token.encode()).hexdigest(), + key_alias="alias", user_id="u1") + prisma_client.db.litellm_verificationtoken.upsert = AsyncMock(return_value=response) + data = { + "token": token, + "user_id": "u1", + "team_id": "t1", + "metadata": {"a": 1}, + } + result = await prisma_client.insert_data(data=data, table_name="key") + upsert_kwargs = prisma_client.db.litellm_verificationtoken.upsert.await_args.kwargs + actual = { + "returned": result, + "where": upsert_kwargs["where"], + "include": upsert_kwargs["include"], + "create_token": upsert_kwargs["data"]["create"]["token"], + "create_metadata_serialized": isinstance( + upsert_kwargs["data"]["create"]["metadata"], str + ), + "update_empty": upsert_kwargs["data"]["update"], + } + expected_hash = hashlib.sha256(token.encode()).hexdigest() + assert actual == { + "returned": response, + "where": {"token": expected_hash}, + "include": {"litellm_budget_table": True}, + "create_token": expected_hash, + "create_metadata_serialized": True, + "update_empty": {}, + } + + +@pytest.mark.asyncio +async def test_insert_data_strips_null_budget_limits(prisma_client: PrismaClient) -> None: + prisma_client.db.litellm_verificationtoken.upsert = AsyncMock(return_value=None) + await prisma_client.insert_data( + data={"token": "sk-1", "budget_limits": None}, table_name="key" + ) + create_payload = prisma_client.db.litellm_verificationtoken.upsert.await_args.kwargs[ + "data" + ]["create"] + assert "budget_limits" not in create_payload + + +@pytest.mark.asyncio +async def test_insert_data_team_serializes_members(prisma_client: PrismaClient) -> None: + prisma_client.db.litellm_teamtable.upsert = AsyncMock( + return_value=SimpleNamespace(team_id="t1", team_alias="x", spend=0) + ) + data = { + "team_id": "t1", + "team_alias": "x", + "members_with_roles": [{"role": "admin", "user_id": "u1"}], + } + result = await prisma_client.insert_data(data=data, table_name="team") + create_payload = prisma_client.db.litellm_teamtable.upsert.await_args.kwargs["data"][ + "create" + ] + assert result.team_id == "t1" + assert create_payload["members_with_roles"] == json.dumps(data["members_with_roles"]) + assert create_payload["team_id"] == "t1" + + +@pytest.mark.asyncio +async def test_insert_data_user_organization_fk_raises_400( + prisma_client: PrismaClient, +) -> None: + err = RuntimeError( + "Foreign key constraint failed on the field: `LiteLLM_UserTable_organization_id_fkey (index)`" + ) + prisma_client.db.litellm_usertable.upsert = AsyncMock(side_effect=err) + with pytest.raises(HTTPException) as excinfo: + await prisma_client.insert_data( + data={"user_id": "u1", "organization_id": "org-bad"}, table_name="user" + ) + raised = excinfo.value + assert "Foreign Key Constraint failed" in raised.detail["error"] + assert raised.status_code == 400 + + +@pytest.mark.asyncio +async def test_insert_data_logs_and_raises_generic_error( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_verificationtoken.upsert = AsyncMock( + side_effect=RuntimeError("write boom") + ) + with pytest.raises(RuntimeError, match="write boom"): + await prisma_client.insert_data(data={"token": "sk-1"}, table_name="key") + + +@pytest.mark.asyncio +async def test_update_data_token_hashes_and_updates( + prisma_client: PrismaClient, +) -> None: + token = "sk-update-1" + response = SimpleNamespace( + token=hashlib.sha256(token.encode()).hexdigest(), + model_dump=lambda: { + "token": hashlib.sha256(token.encode()).hexdigest(), + "spend": 1.0, + "user_id": "u1", + }, + ) + prisma_client.db.litellm_verificationtoken.update = AsyncMock(return_value=response) + result = await prisma_client.update_data( + token=token, + data={"spend": 1.0}, + ) + update_kwargs = prisma_client.db.litellm_verificationtoken.update.await_args.kwargs + hashed = hashlib.sha256(token.encode()).hexdigest() + actual = { + "result": result, + "where": update_kwargs["where"], + "data_token": update_kwargs["data"]["token"], + "data_spend": update_kwargs["data"]["spend"], + } + assert actual == { + "result": { + "token": hashed, + "data": {"token": hashed, "spend": 1.0, "user_id": "u1"}, + }, + "where": {"token": hashed}, + "data_token": hashed, + "data_spend": 1.0, + } + + +@pytest.mark.asyncio +async def test_update_data_user_upsert_returns_user_envelope( + prisma_client: PrismaClient, +) -> None: + row = SimpleNamespace(user_id="u2", spend=2.0) + prisma_client.db.litellm_usertable.upsert = AsyncMock(return_value=row) + result = await prisma_client.update_data( + data={"user_id": "u2", "spend": 2.0}, + table_name="user", + ) + assert result == {"user_id": "u2", "data": row} + + +@pytest.mark.asyncio +async def test_update_data_team_serializes_members_when_list( + prisma_client: PrismaClient, +) -> None: + row = SimpleNamespace(team_id="t9", team_alias="x") + prisma_client.db.litellm_teamtable.upsert = AsyncMock(return_value=row) + members = [{"role": "admin", "user_id": "u1"}] + result = await prisma_client.update_data( + data={"team_id": "t9", "members_with_roles": members}, + update_key_values={"members_with_roles": members}, + table_name="team", + ) + upsert_kwargs = prisma_client.db.litellm_teamtable.upsert.await_args.kwargs + actual = { + "result_team_id": result["team_id"], + "result_data": result["data"], + "create_members": upsert_kwargs["data"]["create"]["members_with_roles"], + "update_members": upsert_kwargs["data"]["update"]["members_with_roles"], + } + assert actual == { + "result_team_id": "t9", + "result_data": row, + "create_members": json.dumps(members), + "update_members": json.dumps(members), + } + + +@pytest.mark.asyncio +async def test_update_data_logs_and_raises_on_error( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_verificationtoken.update = AsyncMock( + side_effect=RuntimeError("update fail") + ) + with pytest.raises(RuntimeError, match="update fail"): + await prisma_client.update_data(token="sk-x", data={"spend": 1.0}) + + +@pytest.mark.asyncio +async def test_delete_data_hashes_sk_tokens_and_calls_delete_many( + prisma_client: PrismaClient, +) -> None: + deleted = SimpleNamespace(count=2) + prisma_client.db.litellm_verificationtoken.delete_many = AsyncMock( + return_value=deleted + ) + tokens = ["sk-one", "sk-two", "raw-hashed-token"] + result = await prisma_client.delete_data(tokens=tokens) + where = prisma_client.db.litellm_verificationtoken.delete_many.await_args.kwargs[ + "where" + ] + expected_hashes = sorted( + [ + hashlib.sha256(b"sk-one").hexdigest(), + hashlib.sha256(b"sk-two").hexdigest(), + "raw-hashed-token", + ] + ) + actual = { + "deleted_keys_attr": result["deleted_keys"], + "where_keys": list(where.keys()), + "filter_in_sorted": sorted(where["token"]["in"]), + "delete_call_count": prisma_client.db.litellm_verificationtoken.delete_many.await_count, + } + assert actual == { + "deleted_keys_attr": deleted, + "where_keys": ["token"], + "filter_in_sorted": expected_hashes, + "delete_call_count": 1, + } + + +@pytest.mark.asyncio +async def test_delete_data_team_calls_team_delete_many( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_teamtable.delete_many = AsyncMock() + result = await prisma_client.delete_data( + team_id_list=["t1", "t2"], table_name="team" + ) + where = prisma_client.db.litellm_teamtable.delete_many.await_args.kwargs["where"] + assert result == {"deleted_teams": ["t1", "t2"]} + assert where == {"team_id": {"in": ["t1", "t2"]}} + + +@pytest.mark.asyncio +async def test_delete_data_logs_and_raises_on_error( + prisma_client: PrismaClient, +) -> None: + prisma_client.db.litellm_verificationtoken.delete_many = AsyncMock( + side_effect=RuntimeError("delete fail") + ) + with pytest.raises(RuntimeError, match="delete fail"): + await prisma_client.delete_data(tokens=["sk-x"]) diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py new file mode 100644 index 00000000000..6a4fd516c9b --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py @@ -0,0 +1,275 @@ +"""Pin ``ProxyUpdateSpend`` behavior. + +Symbols pinned here: + - ``ProxyUpdateSpend.update_end_user_spend`` + - ``ProxyUpdateSpend.update_spend_logs`` + - ``ProxyUpdateSpend.disable_spend_updates`` +""" + +from __future__ import annotations + +import asyncio +from typing import Any, Dict, List +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import ProxyUpdateSpend + + +class _AsyncCM: + def __init__(self, target: Any) -> None: + self.target = target + + async def __aenter__(self) -> Any: + return self.target + + async def __aexit__(self, *exc: Any) -> None: + return None + + +@pytest.mark.asyncio +async def test_update_end_user_spend_upserts_each_end_user( + mock_prisma_client: Any, +) -> None: + batcher = MagicMock() + batcher.litellm_endusertable.upsert = MagicMock() + transaction = MagicMock() + transaction.batch_ = lambda: _AsyncCM(batcher) + mock_prisma_client.db.tx = lambda timeout: _AsyncCM(transaction) + + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + + end_user_costs: Dict[str, float] = {"u_b": 1.0, "u_a": 0.5} + await ProxyUpdateSpend.update_end_user_spend( + n_retry_times=0, + prisma_client=mock_prisma_client, + proxy_logging_obj=proxy_logging, + end_user_list_transactions=end_user_costs, + ) + calls = batcher.litellm_endusertable.upsert.call_args_list + ordered_ids = [c.kwargs["where"]["user_id"] for c in calls] + creates = [c.kwargs["data"]["create"] for c in calls] + pinned = { + "upsert_count": len(calls), + "ordered_ids": ordered_ids, + "first_create_keys": sorted(creates[0].keys()), + "first_create_user_id": creates[0]["user_id"], + "first_create_spend": creates[0]["spend"], + } + assert pinned == { + "upsert_count": 2, + "ordered_ids": ["u_a", "u_b"], + "first_create_keys": sorted(["user_id", "spend", "blocked"]), + "first_create_user_id": "u_a", + "first_create_spend": 0.5, + } + + +@pytest.mark.asyncio +async def test_update_end_user_spend_retries_on_connection_error( + mock_prisma_client: Any, monkeypatch: pytest.MonkeyPatch +) -> None: + """``DB_CONNECTION_ERROR_TYPES`` failures should be retried with backoff; + once retries are exhausted, ``_raise_failed_update_spend_exception`` is + invoked and the original exception bubbles up. + """ + import httpx + import litellm.proxy.utils as utils_mod + + sleeps: list[float] = [] + + async def _fake_sleep(seconds: float) -> None: + sleeps.append(seconds) + + monkeypatch.setattr(utils_mod.asyncio, "sleep", _fake_sleep) + + err = httpx.ReadError("conn reset") + mock_prisma_client.db.tx = MagicMock(side_effect=err) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + with pytest.raises(httpx.ReadError): + await ProxyUpdateSpend.update_end_user_spend( + n_retry_times=1, + prisma_client=mock_prisma_client, + proxy_logging_obj=proxy_logging, + end_user_list_transactions={"u": 1.0}, + ) + assert sleeps == [1.0] + + +@pytest.mark.asyncio +async def test_update_end_user_spend_non_connection_error_raises_immediately( + mock_prisma_client: Any, +) -> None: + mock_prisma_client.db.tx = MagicMock(side_effect=RuntimeError("unknown")) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + with pytest.raises(RuntimeError, match="unknown"): + await ProxyUpdateSpend.update_end_user_spend( + n_retry_times=3, + prisma_client=mock_prisma_client, + proxy_logging_obj=proxy_logging, + end_user_list_transactions={"u": 1.0}, + ) + + +@pytest.mark.asyncio +async def test_update_spend_logs_writes_batches_via_create_many( + mock_prisma_client: Any, make_spend_log_row: Any +) -> None: + logs = [make_spend_log_row(request_id=f"r{i}", spend=float(i)) for i in range(3)] + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock() + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=0, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + logs_to_process=logs, + ) + kwargs = mock_prisma_client.db.litellm_spendlogs.create_many.await_args.kwargs + pinned = { + "calls": mock_prisma_client.db.litellm_spendlogs.create_many.await_count, + "data_len": len(kwargs["data"]), + "skip_duplicates": kwargs["skip_duplicates"], + "first_request_id": kwargs["data"][0]["request_id"], + } + assert pinned == { + "calls": 1, + "data_len": 3, + "skip_duplicates": True, + "first_request_id": "r0", + } + + +@pytest.mark.asyncio +async def test_update_spend_logs_uses_spend_logs_url_when_set( + mock_prisma_client: Any, + make_spend_log_row: Any, + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setenv("SPEND_LOGS_URL", "http://writer.invalid") + writer = MagicMock() + writer.post = AsyncMock(return_value=MagicMock(status_code=200)) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + logs = [make_spend_log_row(request_id="r1")] + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=0, + prisma_client=mock_prisma_client, + db_writer_client=writer, + proxy_logging_obj=proxy_logging, + logs_to_process=logs, + ) + pinned = { + "post_calls": writer.post.await_count, + "url": writer.post.await_args.kwargs["url"], + "headers": writer.post.await_args.kwargs["headers"], + "create_many_calls": mock_prisma_client.db.litellm_spendlogs.create_many.await_count, + } + assert pinned == { + "post_calls": 1, + "url": "http://writer.invalid/spend/update", + "headers": {"Content-Type": "application/json"}, + "create_many_calls": 0, + } + + +@pytest.mark.asyncio +async def test_update_spend_logs_pops_logs_when_logs_to_process_is_none( + mock_prisma_client: Any, make_spend_log_row: Any +) -> None: + mock_prisma_client.spend_log_transactions = [ + make_spend_log_row(request_id="a"), + make_spend_log_row(request_id="b"), + ] + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock() + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=0, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + assert mock_prisma_client.spend_log_transactions == [] + assert mock_prisma_client.db.litellm_spendlogs.create_many.await_count == 1 + + +@pytest.mark.asyncio +async def test_update_spend_logs_failure_raises_after_retries( + mock_prisma_client: Any, + make_spend_log_row: Any, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """When all retries exhaust the underlying DB error, the helper raises + via ``_raise_failed_update_spend_exception``. + """ + import httpx + import litellm.proxy.utils as utils_mod + + async def _fake_sleep(_: float) -> None: + return None + + monkeypatch.setattr(utils_mod.asyncio, "sleep", _fake_sleep) + + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock( + side_effect=httpx.ReadError("network blip") + ) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + with pytest.raises(httpx.ReadError): + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=1, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + logs_to_process=[make_spend_log_row(request_id="r1")], + ) + + +def test_disable_spend_updates_reflects_general_settings( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """The static method delegates to ``general_settings['disable_spend_updates']``; + flipping that value toggles the helper's return. + """ + import litellm.proxy.proxy_server as proxy_server_mod + + monkeypatch.setattr( + proxy_server_mod, "general_settings", {"disable_spend_updates": True} + ) + pinned = { + "with_flag_true": ProxyUpdateSpend.disable_spend_updates(), + "type_is_bool": isinstance(ProxyUpdateSpend.disable_spend_updates(), bool), + "method_is_static": isinstance( + ProxyUpdateSpend.__dict__["disable_spend_updates"], staticmethod + ), + } + assert pinned == { + "with_flag_true": True, + "type_is_bool": True, + "method_is_static": True, + } + + +def test_disable_spend_updates_default_false_without_flag( + monkeypatch: pytest.MonkeyPatch, +) -> None: + import litellm.proxy.proxy_server as proxy_server_mod + + monkeypatch.setattr(proxy_server_mod, "general_settings", {}) + assert ProxyUpdateSpend.disable_spend_updates() is False + + +def test_disable_spend_updates_error_when_general_settings_unavailable( + monkeypatch: pytest.MonkeyPatch, +) -> None: + import litellm.proxy.proxy_server as proxy_server_mod + + monkeypatch.delattr(proxy_server_mod, "general_settings", raising=False) + with pytest.raises(ImportError): + ProxyUpdateSpend.disable_spend_updates() diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_send_email.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_send_email.py new file mode 100644 index 00000000000..5028b65705f --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_send_email.py @@ -0,0 +1,105 @@ +"""Pin ``send_email``. + +Symbols pinned here: + - ``send_email`` +""" + +from __future__ import annotations + +from typing import Any + +import pytest + +from litellm.proxy.utils import send_email + + +@pytest.fixture(autouse=True) +def _smtp_env(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("SMTP_HOST", "smtp.invalid") + monkeypatch.setenv("SMTP_PORT", "2525") + monkeypatch.setenv("SMTP_USERNAME", "u") + monkeypatch.setenv("SMTP_PASSWORD", "p") + monkeypatch.setenv("SMTP_SENDER_EMAIL", "from@invalid") + monkeypatch.setenv("SMTP_TLS", "True") + + +@pytest.mark.asyncio +async def test_send_email_dispatches_via_smtp(in_memory_smtp: Any) -> None: + await send_email( + receiver_email="to@invalid", + subject="Hello", + html="

body

", + ) + assert len(in_memory_smtp.sent) == 1 + sent = in_memory_smtp.sent[0] + pinned = { + "from_addr": sent.from_addr, + "to_addrs": sent.to_addrs, + "subject": sent.subject, + "starttls": sent.starttls_called, + "login": sent.login_args, + } + assert pinned == { + "from_addr": "from@invalid", + "to_addrs": "to@invalid", + "subject": "Hello", + "starttls": True, + "login": ("u", "p"), + } + assert "

body

" in sent.body + + +@pytest.mark.asyncio +async def test_send_email_skips_starttls_when_disabled( + in_memory_smtp: Any, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("SMTP_TLS", "False") + await send_email( + receiver_email="to@invalid", + subject="Hi", + html="

x

", + ) + assert in_memory_smtp.sent[0].starttls_called is False + + +@pytest.mark.asyncio +async def test_send_email_error_missing_sender_email( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.delenv("SMTP_SENDER_EMAIL", raising=False) + with pytest.raises(ValueError, match="SMTP_SENDER_EMAIL"): + await send_email( + receiver_email="x@y", subject="s", html="

h

" + ) + + +@pytest.mark.asyncio +async def test_send_email_error_missing_receiver() -> None: + with pytest.raises(ValueError, match="receiver email"): + await send_email(receiver_email=None, subject="s", html="

h

") + + +@pytest.mark.asyncio +async def test_send_email_error_missing_subject() -> None: + with pytest.raises(ValueError, match="subject"): + await send_email(receiver_email="x@y", subject=None, html="

h

") + + +@pytest.mark.asyncio +async def test_send_email_error_missing_html() -> None: + with pytest.raises(ValueError, match="HTML"): + await send_email(receiver_email="x@y", subject="s", html=None) + + +@pytest.mark.asyncio +async def test_send_email_smtp_failure_is_swallowed( + in_memory_smtp: Any, +) -> None: + """SMTP send_message errors are caught and logged; ``send_email`` itself + does not raise so a failing email never blocks the proxy. + """ + in_memory_smtp.raise_on_send = RuntimeError("smtp boom") + await send_email( + receiver_email="to@invalid", subject="Hi", html="

x

" + ) + assert in_memory_smtp.sent == [] diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py new file mode 100644 index 00000000000..a0b3af54750 --- /dev/null +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_spend_functions.py @@ -0,0 +1,360 @@ +"""Pin module-level spend functions. + +Symbols pinned here: + - ``update_spend`` + - ``update_daily_tag_spend`` + - ``update_spend_logs_job`` + - ``_monitor_spend_logs_queue`` + - ``_raise_failed_update_spend_exception`` +""" + +from __future__ import annotations + +import asyncio +from typing import Any, Dict, List +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.proxy.utils import ( + _monitor_spend_logs_queue, + _raise_failed_update_spend_exception, + update_daily_tag_spend, + update_spend, + update_spend_logs_job, +) + + +@pytest.mark.asyncio +async def test_update_spend_invokes_writer_and_skips_empty_queue( + mock_prisma_client: Any, +) -> None: + proxy_logging = MagicMock() + proxy_logging.db_spend_update_writer = MagicMock() + proxy_logging.db_spend_update_writer.db_update_spend_transaction_handler = AsyncMock() + mock_prisma_client.spend_log_transactions = [] + + await update_spend( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + handler = proxy_logging.db_spend_update_writer.db_update_spend_transaction_handler + pinned = { + "handler_called": handler.await_count, + "handler_kwargs": handler.await_args.kwargs, + "queue_empty": mock_prisma_client.spend_log_transactions, + } + assert pinned == { + "handler_called": 1, + "handler_kwargs": { + "prisma_client": mock_prisma_client, + "n_retry_times": 3, + "proxy_logging_obj": proxy_logging, + }, + "queue_empty": [], + } + + +@pytest.mark.asyncio +async def test_update_spend_processes_logs_when_queue_nonempty( + mock_prisma_client: Any, make_spend_log_row: Any, monkeypatch: pytest.MonkeyPatch +) -> None: + proxy_logging = MagicMock() + proxy_logging.db_spend_update_writer = MagicMock() + proxy_logging.db_spend_update_writer.db_update_spend_transaction_handler = AsyncMock() + mock_prisma_client.spend_log_transactions = [make_spend_log_row(request_id="r1")] + + import litellm.proxy.utils as utils_mod + + job_mock = AsyncMock() + monkeypatch.setattr(utils_mod, "update_spend_logs_job", job_mock) + + await update_spend( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + assert job_mock.await_count == 1 + + +@pytest.mark.asyncio +async def test_update_spend_handler_failure_propagates( + mock_prisma_client: Any, +) -> None: + proxy_logging = MagicMock() + proxy_logging.db_spend_update_writer = MagicMock() + proxy_logging.db_spend_update_writer.db_update_spend_transaction_handler = AsyncMock( + side_effect=RuntimeError("handler down") + ) + with pytest.raises(RuntimeError, match="handler down"): + await update_spend( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + + +@pytest.mark.asyncio +async def test_update_daily_tag_spend_redis_path_when_buffered( + mock_prisma_client: Any, +) -> None: + proxy_logging = MagicMock() + writer = MagicMock() + proxy_logging.db_spend_update_writer = writer + writer.redis_update_buffer = MagicMock() + writer.redis_update_buffer._should_commit_spend_updates_to_redis = MagicMock( + return_value=True + ) + writer._commit_daily_tag_spend_to_db_with_redis = AsyncMock() + writer._commit_daily_tag_spend_to_db = AsyncMock() + + await update_daily_tag_spend( + prisma_client=mock_prisma_client, proxy_logging_obj=proxy_logging + ) + redis_kwargs = writer._commit_daily_tag_spend_to_db_with_redis.await_args.kwargs + pinned = { + "redis_calls": writer._commit_daily_tag_spend_to_db_with_redis.await_count, + "direct_calls": writer._commit_daily_tag_spend_to_db.await_count, + "redis_kwargs_keys": sorted(redis_kwargs.keys()), + "redis_n_retries": redis_kwargs["n_retry_times"], + } + assert pinned == { + "redis_calls": 1, + "direct_calls": 0, + "redis_kwargs_keys": sorted( + ["prisma_client", "n_retry_times", "proxy_logging_obj"] + ), + "redis_n_retries": 3, + } + + +@pytest.mark.asyncio +async def test_update_daily_tag_spend_direct_path_when_no_redis( + mock_prisma_client: Any, +) -> None: + proxy_logging = MagicMock() + writer = MagicMock() + proxy_logging.db_spend_update_writer = writer + writer.redis_update_buffer = MagicMock() + writer.redis_update_buffer._should_commit_spend_updates_to_redis = MagicMock( + return_value=False + ) + writer._commit_daily_tag_spend_to_db_with_redis = AsyncMock() + writer._commit_daily_tag_spend_to_db = AsyncMock() + + await update_daily_tag_spend( + prisma_client=mock_prisma_client, proxy_logging_obj=proxy_logging + ) + assert writer._commit_daily_tag_spend_to_db.await_count == 1 + assert writer._commit_daily_tag_spend_to_db_with_redis.await_count == 0 + + +@pytest.mark.asyncio +async def test_update_daily_tag_spend_logs_and_swallows_errors( + mock_prisma_client: Any, +) -> None: + """A failure in the commit path is logged but not re-raised; this matches + the historical behavior of this site (see plain ``logger.error`` rather + than ``spend_log_error``). + """ + proxy_logging = MagicMock() + proxy_logging.db_spend_update_writer = MagicMock() + proxy_logging.db_spend_update_writer.redis_update_buffer = MagicMock() + proxy_logging.db_spend_update_writer.redis_update_buffer._should_commit_spend_updates_to_redis = MagicMock( + return_value=False + ) + proxy_logging.db_spend_update_writer._commit_daily_tag_spend_to_db = AsyncMock( + side_effect=RuntimeError("commit boom") + ) + await update_daily_tag_spend( + prisma_client=mock_prisma_client, proxy_logging_obj=proxy_logging + ) + + +@pytest.mark.asyncio +async def test_update_spend_logs_job_skips_when_queue_empty( + mock_prisma_client: Any, +) -> None: + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + mock_prisma_client.spend_log_transactions = [] + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock() + await update_spend_logs_job( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + assert mock_prisma_client.db.litellm_spendlogs.create_many.await_count == 0 + + +@pytest.mark.asyncio +async def test_update_spend_logs_job_processes_and_clears_queue( + mock_prisma_client: Any, make_spend_log_row: Any, monkeypatch: pytest.MonkeyPatch +) -> None: + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + mock_prisma_client.spend_log_transactions = [ + make_spend_log_row(request_id="r1"), + make_spend_log_row(request_id="r2"), + ] + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock() + + # Stub auxiliary imports so the test focuses on the spend-logs write path. + import litellm.proxy.guardrails.usage_tracking as guard_mod + import litellm.proxy.db.spend_log_tool_index as tool_mod + + monkeypatch.setattr( + guard_mod, "process_spend_logs_guardrail_usage", AsyncMock(), raising=False + ) + monkeypatch.setattr( + tool_mod, "process_spend_logs_tool_usage", AsyncMock(), raising=False + ) + + await update_spend_logs_job( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + pinned = { + "create_many_calls": mock_prisma_client.db.litellm_spendlogs.create_many.await_count, + "queue_after": mock_prisma_client.spend_log_transactions, + "first_data_request_id": mock_prisma_client.db.litellm_spendlogs.create_many.await_args.kwargs[ + "data" + ][0]["request_id"], + "skip_duplicates_set": mock_prisma_client.db.litellm_spendlogs.create_many.await_args.kwargs[ + "skip_duplicates" + ], + } + assert pinned == { + "create_many_calls": 1, + "queue_after": [], + "first_data_request_id": "r1", + "skip_duplicates_set": True, + } + + +@pytest.mark.asyncio +async def test_monitor_spend_logs_queue_invokes_job_when_queue_nonempty( + mock_prisma_client: Any, + make_spend_log_row: Any, + monkeypatch: pytest.MonkeyPatch, +) -> None: + import litellm.proxy.utils as utils_mod + import litellm.constants as constants_mod + + monkeypatch.setattr(constants_mod, "SPEND_LOG_QUEUE_POLL_INTERVAL", 0.0, raising=False) + monkeypatch.setattr(constants_mod, "SPEND_LOG_QUEUE_SIZE_THRESHOLD", 1, raising=False) + proxy_logging = MagicMock() + mock_prisma_client.spend_log_transactions = [make_spend_log_row(request_id="r1")] + + cancel_after = {"n": 0} + + async def _fake_job(*args: Any, **kwargs: Any) -> None: + cancel_after["n"] += 1 + if cancel_after["n"] >= 1: + raise asyncio.CancelledError() + + monkeypatch.setattr(utils_mod, "update_spend_logs_job", _fake_job) + + with pytest.raises(asyncio.CancelledError): + await _monitor_spend_logs_queue( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + assert cancel_after["n"] == 1 + + +@pytest.mark.asyncio +async def test_monitor_spend_logs_queue_swallows_errors_and_backs_off( + mock_prisma_client: Any, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """An exception inside the loop is logged with backoff and the loop + continues running rather than crashing the monitor task. + """ + import litellm.proxy.utils as utils_mod + import litellm.constants as constants_mod + + monkeypatch.setattr(constants_mod, "SPEND_LOG_QUEUE_POLL_INTERVAL", 0.0, raising=False) + + sleep_count = {"n": 0} + + async def _short_sleep(_: float, *args: Any, **kwargs: Any) -> None: + sleep_count["n"] += 1 + if sleep_count["n"] >= 3: + raise asyncio.CancelledError() + + monkeypatch.setattr(utils_mod.asyncio, "sleep", _short_sleep) + proxy_logging = MagicMock() + + bad_lock = MagicMock() + bad_lock.__aenter__ = AsyncMock(side_effect=RuntimeError("lock broken")) + bad_lock.__aexit__ = AsyncMock(return_value=False) + mock_prisma_client._spend_log_transactions_lock = bad_lock + + with pytest.raises(asyncio.CancelledError): + await _monitor_spend_logs_queue( + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + ) + assert sleep_count["n"] == 3 + + +def test_raise_failed_update_spend_exception_emits_failure_handler() -> None: + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + + async def _runner() -> Any: + try: + _raise_failed_update_spend_exception( + e=RuntimeError("boom"), + start_time=0.0, + proxy_logging_obj=proxy_logging, + ) + except RuntimeError as e: + return e + return None + + err = asyncio.run(_runner()) + pinned = { + "raised": str(err), + "failure_handler_called": proxy_logging.failure_handler.call_count, + "call_type": ( + proxy_logging.failure_handler.call_args.kwargs.get("call_type") + if proxy_logging.failure_handler.call_args + else None + ), + "non_blocking_in_traceback": ( + "Non-Blocking" + in proxy_logging.failure_handler.call_args.kwargs["traceback_str"] + if proxy_logging.failure_handler.call_args + else False + ), + } + assert pinned == { + "raised": "boom", + "failure_handler_called": 1, + "call_type": "update_spend", + "non_blocking_in_traceback": True, + } + + +def test_raise_failed_update_spend_exception_raises_original_error() -> None: + """Error path: the function always re-raises the original exception so + the caller can observe the failure. + """ + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + + async def _runner() -> None: + _raise_failed_update_spend_exception( + e=ValueError("specific"), + start_time=0.0, + proxy_logging_obj=proxy_logging, + ) + + with pytest.raises(ValueError, match="specific"): + asyncio.run(_runner()) From b175990b4ac211bd363751d6b9135b31cf529d8f Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 2 Jun 2026 17:45:39 -0700 Subject: [PATCH 03/92] test(proxy/utils): pin ProxyLogging behavior (#29485) * test(proxy/utils): pin ProxyLogging behavior Add behavior-pinning tests for the ProxyLogging cluster in litellm/proxy/utils.py under tests/test_litellm/proxy/utils/proxy_logging/. Covers InternalUsageCache, _CallbackCapabilities, top-of-file helpers (print_verbose, _get_email_logger_class, _accepts_litellm_call_info, _enrich_http_exception_with_guardrail_context), the full ProxyLogging class (lifecycle, MCP-LLM bridging, capability probes, guardrail pipeline, pre/during/post/streaming hooks, alerting), plus the bottom-of-region helpers (on_backoff, jsonify_object, _lookup_deprecated_key). Each pinned symbol has happy-path and error-path coverage; happy paths use direct dict-equality with three or more keys (or HiddenParams / Pydantic model_validate where the surface is a Pydantic shape). The subdirectory carries a local _pin_check.py and _coverage_check.py that enforce the gate without surfacing numeric thresholds in CI logs. Wires tests/test_litellm/proxy/utils into the existing test-path block in .github/workflows/test-unit-proxy-endpoints.yml. * test(proxy/utils): drop unused mock_httpx_client fixture Declared in conftest.py but never referenced by any test. Removing the dead fixture per Greptile P2 feedback. * test(proxy/utils): drop local-only gate scripts from PR _pin_check.py and _coverage_check.py are local stopping signals (not wired into CI, consume a gitignored .pin_list.txt). They served their purpose telling the engineer when to stop writing tests; the pytest suite is the artifact that belongs in the repo. --------- Co-authored-by: Claude --- .../proxy/utils/proxy_logging/__init__.py | 0 .../proxy_logging/_harness_smoke_test.py | 56 ++ .../proxy/utils/proxy_logging/conftest.py | 136 +++++ .../utils/proxy_logging/test_alerting.py | 262 ++++++++ .../test_callback_capabilities_class.py | 338 +++++++++++ .../test_callback_capabilities_dataclass.py | 59 ++ .../proxy_logging/test_during_call_hook.py | 86 +++ .../proxy_logging/test_guardrail_pipeline.py | 559 ++++++++++++++++++ .../test_internal_usage_cache.py | 186 ++++++ .../utils/proxy_logging/test_lifecycle.py | 403 +++++++++++++ .../utils/proxy_logging/test_mcp_bridging.py | 426 +++++++++++++ .../proxy_logging/test_module_helpers.py | 353 +++++++++++ .../test_post_call_failure_hook.py | 269 +++++++++ .../test_post_call_success_hook.py | 97 +++ .../utils/proxy_logging/test_pre_call_hook.py | 168 ++++++ .../proxy_logging/test_streaming_hooks.py | 432 ++++++++++++++ 16 files changed, 3830 insertions(+) create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/__init__.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/_harness_smoke_test.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/conftest.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_class.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_dataclass.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_during_call_hook.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_guardrail_pipeline.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_internal_usage_cache.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_lifecycle.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_mcp_bridging.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_module_helpers.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_post_call_success_hook.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_pre_call_hook.py create mode 100644 tests/test_litellm/proxy/utils/proxy_logging/test_streaming_hooks.py diff --git a/tests/test_litellm/proxy/utils/proxy_logging/__init__.py b/tests/test_litellm/proxy/utils/proxy_logging/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/proxy/utils/proxy_logging/_harness_smoke_test.py b/tests/test_litellm/proxy/utils/proxy_logging/_harness_smoke_test.py new file mode 100644 index 00000000000..1ec01f8c563 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/_harness_smoke_test.py @@ -0,0 +1,56 @@ +"""Sanity tests for the proxy_logging conftest fixtures. + +Excluded from the pin-check by name. +""" + +from __future__ import annotations + +import pytest + + +def test_normalize_replaces_volatile_keys(normalize_fn): + raw = {"id": 7, "name": "x", "nested": {"created_at": 1, "value": 2}} + expected = {"id": "", "name": "x", "nested": {"created_at": "", "value": 2}} + assert normalize_fn(raw) == expected + + +def test_normalize_handles_lists(normalize_fn): + raw = [{"id": 1}, {"id": 2}] + assert normalize_fn(raw) == [{"id": ""}, {"id": ""}] + + +def test_mock_dual_cache_is_dual_cache(mock_dual_cache): + from litellm.caching.caching import DualCache + + assert isinstance(mock_dual_cache, DualCache) + + +def test_make_user_api_key_auth_returns_correct_type(make_user_api_key_auth): + from litellm.proxy._types import UserAPIKeyAuth + + auth = make_user_api_key_auth() + assert isinstance(auth, UserAPIKeyAuth) + assert auth.user_id == "test-user" + + +def test_make_user_api_key_auth_overrides_apply(make_user_api_key_auth): + auth = make_user_api_key_auth(user_id="custom-id") + assert auth.user_id == "custom-id" + + +def test_proxy_logging_fixture_is_initialized(proxy_logging): + from litellm.proxy.utils import InternalUsageCache, ProxyLogging + + assert isinstance(proxy_logging, ProxyLogging) + assert isinstance(proxy_logging.internal_usage_cache, InternalUsageCache) + assert proxy_logging.proxy_hook_mapping == {} + + +def test_make_mcp_request_obj_default(make_mcp_request_obj): + obj = make_mcp_request_obj() + assert obj.tool_name == "calculator" + assert obj.arguments == {"x": 1, "y": 2} + + +def test_mock_router_has_guardrail_list(mock_router): + assert mock_router.guardrail_list == [] diff --git a/tests/test_litellm/proxy/utils/proxy_logging/conftest.py b/tests/test_litellm/proxy/utils/proxy_logging/conftest.py new file mode 100644 index 00000000000..74508a74e3b --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/conftest.py @@ -0,0 +1,136 @@ +"""Shared fixtures for tests/test_litellm/proxy/utils/proxy_logging/. + +All fixtures used by PR1 of the proxy/utils.py behavior-pinning project +live here. Tests should not declare fixtures inline. +""" + +from __future__ import annotations + +import sys +from pathlib import Path +from typing import Any, Dict, Optional +from unittest.mock import MagicMock + +import pytest + +sys.path.insert(0, str(Path(__file__).resolve().parents[5])) + + +VOLATILE_KEYS = frozenset( + { + "created_at", + "updated_at", + "id", + "request_id", + "token", + "expires", + "expires_at", + "litellm_call_id", + "key_alias", + "created", + "start_time", + "end_time", + "duration", + "guardrail_start_time", + "guardrail_end_time", + "guardrail_duration", + } +) + + +def normalize(data: Any, volatile: frozenset = VOLATILE_KEYS) -> Any: + if isinstance(data, dict): + return { + k: ("" if k in volatile else normalize(v, volatile)) + for k, v in data.items() + } + if isinstance(data, list): + return [normalize(v, volatile) for v in data] + return data + + +@pytest.fixture +def mock_dual_cache(): + from litellm.caching.caching import DualCache + + cache = DualCache(default_in_memory_ttl=1) + return cache + + +@pytest.fixture +def mock_router(): + router = MagicMock() + router.guardrail_list = [] + router.get_available_guardrail = MagicMock(return_value={"callback": None}) + return router + + +@pytest.fixture +def mock_callbacks_disabled(monkeypatch): + """Disable all litellm callbacks for the duration of a test.""" + import litellm + + monkeypatch.setattr(litellm, "callbacks", []) + monkeypatch.setattr(litellm, "success_callback", []) + monkeypatch.setattr(litellm, "failure_callback", []) + monkeypatch.setattr(litellm, "_async_success_callback", []) + monkeypatch.setattr(litellm, "_async_failure_callback", []) + yield + + +@pytest.fixture +def make_user_api_key_auth(): + from litellm.proxy._types import UserAPIKeyAuth + + def _make(**overrides) -> UserAPIKeyAuth: + defaults: Dict[str, Any] = { + "api_key": "sk-test-1234", + "user_id": "test-user", + "team_id": "test-team", + "user_role": None, + "max_budget": None, + "spend": 0.0, + } + defaults.update(overrides) + return UserAPIKeyAuth(**defaults) + + return _make + + +@pytest.fixture +def proxy_logging(mock_callbacks_disabled): + """A wired-up ProxyLogging instance backed by a fresh DualCache. + + The fixture leaves it un-started; tests that need ``startup_event`` + should call it explicitly with the deps they want to control. + """ + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.utils import ProxyLogging + + return ProxyLogging(user_api_key_cache=UserApiKeyCache()) + + +@pytest.fixture +def normalize_fn(): + return normalize + + +@pytest.fixture +def make_mcp_request_obj(): + from litellm.types.llms.base import HiddenParams + from litellm.types.mcp import MCPPreCallRequestObject + + def _make( + tool_name: str = "calculator", + arguments: Optional[dict] = None, + server_name: Optional[str] = "math-server", + ) -> MCPPreCallRequestObject: + return MCPPreCallRequestObject( + tool_name=tool_name, + arguments=arguments if arguments is not None else {"x": 1, "y": 2}, + server_name=server_name, + user_api_key_auth={}, + hidden_params=HiddenParams(), + ) + + return _make diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py b/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py new file mode 100644 index 00000000000..cede859cb38 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py @@ -0,0 +1,262 @@ +"""Pin alerting helpers on ``ProxyLogging``. + +Covers ``failed_tracking_alert``, ``budget_alerts``, ``alerting_handler``, +``failure_handler``. +""" + +from __future__ import annotations + +from datetime import datetime +from typing import Any, Dict +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +import litellm +from litellm.proxy._types import AlertType, CallInfo + + +# --------------------------------------------------------------------------- +# failed_tracking_alert +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_failed_tracking_alert_no_op_when_alerting_none(proxy_logging): + proxy_logging.alerting = None + proxy_logging.slack_alerting_instance = MagicMock(failed_tracking_alert=AsyncMock()) + await proxy_logging.failed_tracking_alert(error_message="x", failing_model="m") + proxy_logging.slack_alerting_instance.failed_tracking_alert.assert_not_called() + + +@pytest.mark.asyncio +async def test_failed_tracking_alert_forwards_to_slack(proxy_logging): + proxy_logging.alerting = ["slack"] + captured: Dict[str, Any] = {} + + async def fake_alert(**kwargs): + captured.update(kwargs) + + proxy_logging.slack_alerting_instance = MagicMock(failed_tracking_alert=fake_alert) + await proxy_logging.failed_tracking_alert(error_message="db down", failing_model="gpt-4") + snapshot = { + "error_message": captured["error_message"], + "failing_model": captured["failing_model"], + "captured_keys": sorted(captured.keys()), + } + assert snapshot == { + "error_message": "db down", + "failing_model": "gpt-4", + "captured_keys": ["error_message", "failing_model"], + } + + +@pytest.mark.asyncio +async def test_failed_tracking_alert_slack_error_raises(proxy_logging): + proxy_logging.alerting = ["slack"] + proxy_logging.slack_alerting_instance = MagicMock( + failed_tracking_alert=AsyncMock(side_effect=RuntimeError("slack down")) + ) + with pytest.raises(RuntimeError): + await proxy_logging.failed_tracking_alert(error_message="x", failing_model="m") + + +# --------------------------------------------------------------------------- +# budget_alerts +# --------------------------------------------------------------------------- + + +def _user_info(alert_emails=None): + return CallInfo( + spend=0.0, + max_budget=1.0, + token="tok", + user_id="u1", + team_id="t1", + team_alias=None, + user_email=None, + key_alias=None, + projected_exceeded_date=None, + projected_spend=None, + event_group="user", + event="threshold_crossed", + alert_emails=alert_emails, + ) + + +@pytest.mark.asyncio +async def test_budget_alerts_no_op_when_alerting_off_and_no_emails(proxy_logging): + proxy_logging.alerting = None + proxy_logging.slack_alerting_instance = MagicMock(budget_alerts=AsyncMock()) + proxy_logging.email_logging_instance = MagicMock(budget_alerts=AsyncMock()) + await proxy_logging.budget_alerts(type="user_budget", user_info=_user_info()) + proxy_logging.slack_alerting_instance.budget_alerts.assert_not_called() + proxy_logging.email_logging_instance.budget_alerts.assert_not_called() + + +@pytest.mark.asyncio +async def test_budget_alerts_slack_when_slack_alerting(proxy_logging): + proxy_logging.alerting = ["slack"] + captured: Dict[str, Any] = {} + + async def fake_alert(**kwargs): + captured.update(kwargs) + + proxy_logging.slack_alerting_instance = MagicMock(budget_alerts=fake_alert) + proxy_logging.email_logging_instance = None + user_info = _user_info() + await proxy_logging.budget_alerts(type="user_budget", user_info=user_info) + snapshot = { + "type": captured["type"], + "user_info_is_callinfo": isinstance(captured["user_info"], CallInfo), + "user_id": captured["user_info"].user_id, + } + assert snapshot == {"type": "user_budget", "user_info_is_callinfo": True, "user_id": "u1"} + + +@pytest.mark.asyncio +async def test_budget_alerts_soft_budget_with_alert_emails_bypasses_global(proxy_logging): + proxy_logging.alerting = None + proxy_logging.slack_alerting_instance = MagicMock(budget_alerts=AsyncMock()) + proxy_logging.email_logging_instance = MagicMock(budget_alerts=AsyncMock()) + info = _user_info(alert_emails=["a@b.c"]) + await proxy_logging.budget_alerts(type="soft_budget", user_info=info) + proxy_logging.email_logging_instance.budget_alerts.assert_called_once() + proxy_logging.slack_alerting_instance.budget_alerts.assert_not_called() + + +@pytest.mark.asyncio +async def test_budget_alerts_slack_failure_raises(proxy_logging): + proxy_logging.alerting = ["slack"] + proxy_logging.slack_alerting_instance = MagicMock( + budget_alerts=AsyncMock(side_effect=ConnectionError("slack")) + ) + proxy_logging.email_logging_instance = None + with pytest.raises(ConnectionError): + await proxy_logging.budget_alerts(type="user_budget", user_info=_user_info()) + + +# --------------------------------------------------------------------------- +# alerting_handler +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_alerting_handler_no_op_when_alerting_is_none(proxy_logging): + proxy_logging.alerting = None + proxy_logging.slack_alerting_instance = MagicMock(send_alert=AsyncMock()) + await proxy_logging.alerting_handler(message="x", level="High", alert_type=AlertType.db_exceptions) + proxy_logging.slack_alerting_instance.send_alert.assert_not_called() + + +@pytest.mark.asyncio +async def test_alerting_handler_sends_to_slack(proxy_logging): + proxy_logging.alerting = ["slack"] + captured: Dict[str, Any] = {} + + async def fake_send(**kwargs): + captured.update(kwargs) + + proxy_logging.slack_alerting_instance = MagicMock(send_alert=fake_send) + await proxy_logging.alerting_handler( + message="hi", level="High", alert_type=AlertType.db_exceptions, request_data={"metadata": {}} + ) + snapshot = { + "message": captured["message"], + "level": captured["level"], + "alert_type": captured["alert_type"], + "user_info": captured["user_info"], + } + assert snapshot == { + "message": "hi", + "level": "High", + "alert_type": AlertType.db_exceptions, + "user_info": None, + } + + +@pytest.mark.asyncio +async def test_alerting_handler_sentry_without_sdk_error_raises(proxy_logging, monkeypatch): + proxy_logging.alerting = ["sentry"] + monkeypatch.setattr(litellm.utils, "sentry_sdk_instance", None) + with pytest.raises(Exception, match="SENTRY_DSN"): + await proxy_logging.alerting_handler(message="x", level="Low", alert_type=AlertType.db_exceptions) + + +# --------------------------------------------------------------------------- +# failure_handler +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_failure_handler_skips_when_db_exceptions_not_in_alert_types(proxy_logging): + proxy_logging.alert_types = ["llm_too_slow"] # type: ignore[list-item] + proxy_logging.alerting_handler = AsyncMock() + proxy_logging.service_logging_obj = MagicMock(async_service_failure_hook=AsyncMock()) + await proxy_logging.failure_handler(original_exception=Exception("x"), duration=1.0, call_type="db_read") + proxy_logging.alerting_handler.assert_not_called() + proxy_logging.service_logging_obj.async_service_failure_hook.assert_not_called() + + +@pytest.mark.asyncio +async def test_failure_handler_logs_db_error_and_calls_service_logging(proxy_logging, monkeypatch): + proxy_logging.alert_types = [AlertType.db_exceptions] + proxy_logging.alerting_handler = AsyncMock() + proxy_logging.service_logging_obj = MagicMock(async_service_failure_hook=AsyncMock()) + monkeypatch.setattr(litellm.utils, "capture_exception", None) + await proxy_logging.failure_handler( + original_exception=HTTPException(status_code=500, detail="boom"), + duration=1.5, + call_type="db_write", + ) + call_kwargs = proxy_logging.service_logging_obj.async_service_failure_hook.call_args.kwargs + snapshot = { + "service": call_kwargs["service"].value if hasattr(call_kwargs["service"], "value") else call_kwargs["service"], + "duration": call_kwargs["duration"], + "call_type": call_kwargs["call_type"], + } + assert snapshot == { + "service": "postgres", + "duration": 1.5, + "call_type": "db_write", + } + + +@pytest.mark.asyncio +async def test_failure_handler_with_capture_exception_invoked(proxy_logging, monkeypatch): + proxy_logging.alert_types = [AlertType.db_exceptions] + proxy_logging.alerting_handler = AsyncMock() + proxy_logging.service_logging_obj = MagicMock(async_service_failure_hook=AsyncMock()) + captured: Dict[str, Any] = {} + + def fake_capture(error): + captured["error"] = error + + monkeypatch.setattr(litellm.utils, "capture_exception", fake_capture) + err = RuntimeError("real") + await proxy_logging.failure_handler(original_exception=err, duration=1.0, call_type="db_read") + snapshot = { + "captured_is_input": captured["error"] is err, + "service_failure_called": proxy_logging.service_logging_obj.async_service_failure_hook.called, + "alerting_handler_scheduled": proxy_logging.alerting_handler.called, + } + assert snapshot == { + "captured_is_input": True, + "service_failure_called": True, + "alerting_handler_scheduled": True, + } + + +@pytest.mark.asyncio +async def test_failure_handler_propagates_service_logging_error_raises(proxy_logging, monkeypatch): + proxy_logging.alert_types = [AlertType.db_exceptions] + proxy_logging.alerting_handler = AsyncMock() + proxy_logging.service_logging_obj = MagicMock( + async_service_failure_hook=AsyncMock(side_effect=RuntimeError("svc")) + ) + monkeypatch.setattr(litellm.utils, "capture_exception", None) + with pytest.raises(RuntimeError): + await proxy_logging.failure_handler( + original_exception=Exception("x"), duration=0.0, call_type="db_read" + ) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_class.py b/tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_class.py new file mode 100644 index 00000000000..45b81acbce1 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_class.py @@ -0,0 +1,338 @@ +"""Pin the ``ProxyLogging`` capability-probe family. + +Covers ``_callback_capabilities`` (the cached deriver), +``has_post_call_response_headers_callbacks``, ``has_streaming_callbacks``, +``has_streaming_chunk_hook_overrides``, ``needs_iterator_wrap``, +``needs_per_chunk_streaming_hook``, ``has_during_call_guardrails``, and +``get_combined_callback_list``. +""" + +from __future__ import annotations + +from typing import Any + +import pytest + +import litellm +from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy.utils import ProxyLogging, _CallbackCapabilities + + +class _PlainLogger(CustomLogger): + pass + + +class _OverridesResponseHeaders(CustomLogger): + async def async_post_call_response_headers_hook(self, *args, **kwargs): # type: ignore[override] + return None + + +class _OverridesIterator(CustomLogger): + async def async_post_call_streaming_iterator_hook(self, *args, **kwargs): # type: ignore[override] + return None + + +class _OverridesPerChunk(CustomLogger): + async def async_post_call_streaming_hook(self, *args, **kwargs): # type: ignore[override] + return None + + +class _OverridesPreCall(CustomLogger): + async def async_pre_call_hook(self, *args, **kwargs): # type: ignore[override] + return None + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +def test_callback_capabilities_with_no_callbacks_returns_defaults(mock_callbacks_disabled): + caps = ProxyLogging._callback_capabilities() + snapshot = { + "headers": caps.has_post_call_response_headers, + "iterator": caps.has_iterator_override, + "chunk": caps.has_streaming_chunk_override, + "guardrail": caps.has_guardrail, + "pre_call": caps.has_pre_call_override, + "callbacks": caps.resolved_callbacks, + "overrides": caps.iterator_overrides, + } + assert snapshot == { + "headers": False, + "iterator": False, + "chunk": False, + "guardrail": False, + "pre_call": False, + "callbacks": (), + "overrides": (), + } + + +def test_callback_capabilities_detects_overrides(monkeypatch): + cb1 = _OverridesResponseHeaders() + cb2 = _OverridesIterator() + cb3 = _OverridesPerChunk() + cb4 = _OverridesPreCall() + monkeypatch.setattr(litellm, "callbacks", [cb1, cb2, cb3, cb4]) + + caps = ProxyLogging._callback_capabilities() + snapshot = { + "headers": caps.has_post_call_response_headers, + "iterator": caps.has_iterator_override, + "chunk": caps.has_streaming_chunk_override, + "pre_call": caps.has_pre_call_override, + } + assert snapshot == { + "headers": True, + "iterator": True, + "chunk": True, + "pre_call": True, + } + + +def test_callback_capabilities_caches_result(monkeypatch): + cb = _OverridesResponseHeaders() + monkeypatch.setattr(litellm, "callbacks", [cb]) + first = ProxyLogging._callback_capabilities() + second = ProxyLogging._callback_capabilities() + assert first is second + + +def test_callback_capabilities_invalidates_on_change(monkeypatch): + monkeypatch.setattr(litellm, "callbacks", [_OverridesResponseHeaders()]) + first = ProxyLogging._callback_capabilities() + monkeypatch.setattr(litellm, "callbacks", [_OverridesIterator()]) + second = ProxyLogging._callback_capabilities() + assert first is not second + assert first.has_post_call_response_headers is True + assert second.has_post_call_response_headers is False + assert second.has_iterator_override is True + + +def test_callback_capabilities_callback_resolution_error_raises(monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["unknown-string"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(RuntimeError("bad")), + ) + with pytest.raises(RuntimeError): + ProxyLogging._callback_capabilities() + + +# --------------------------------------------------------------------------- +# Individual capability probes +# --------------------------------------------------------------------------- + + +def test_has_post_call_response_headers_callbacks_truth_table(monkeypatch, mock_callbacks_disabled): + """One snapshot covering true + false + cache invalidation.""" + snapshot = { + "empty_returns_false": ProxyLogging.has_post_call_response_headers_callbacks(), + } + monkeypatch.setattr(litellm, "callbacks", [_OverridesResponseHeaders()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["override_returns_true"] = ProxyLogging.has_post_call_response_headers_callbacks() + monkeypatch.setattr(litellm, "callbacks", [_PlainLogger()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["plain_logger_false"] = ProxyLogging.has_post_call_response_headers_callbacks() + assert snapshot == { + "empty_returns_false": False, + "override_returns_true": True, + "plain_logger_false": False, + } + + +def test_has_post_call_response_headers_callbacks_error_when_bad_callback(monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["x"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(RuntimeError("kaboom")), + ) + with pytest.raises(RuntimeError): + ProxyLogging.has_post_call_response_headers_callbacks() + + +def test_has_streaming_callbacks_truth_table(monkeypatch, mock_callbacks_disabled): + snapshot = { + "empty_false": ProxyLogging.has_streaming_callbacks(), + } + monkeypatch.setattr(litellm, "callbacks", [_OverridesIterator()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["iterator_override_true"] = ProxyLogging.has_streaming_callbacks() + monkeypatch.setattr(litellm, "callbacks", [_OverridesPerChunk()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["per_chunk_override_true"] = ProxyLogging.has_streaming_callbacks() + assert snapshot == { + "empty_false": False, + "iterator_override_true": True, + "per_chunk_override_true": True, + } + + +def test_has_streaming_callbacks_error_when_resolution_fails(monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["x"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(ValueError("nope")), + ) + with pytest.raises(ValueError): + ProxyLogging.has_streaming_callbacks() + + +def test_has_streaming_chunk_hook_overrides_truth_table(monkeypatch, mock_callbacks_disabled): + snapshot = { + "empty_false": ProxyLogging.has_streaming_chunk_hook_overrides(), + } + monkeypatch.setattr(litellm, "callbacks", [_OverridesPerChunk()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["per_chunk_override_true"] = ProxyLogging.has_streaming_chunk_hook_overrides() + monkeypatch.setattr(litellm, "callbacks", [_OverridesIterator()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["only_iterator_false"] = ProxyLogging.has_streaming_chunk_hook_overrides() + assert snapshot == { + "empty_false": False, + "per_chunk_override_true": True, + "only_iterator_false": False, + } + + +def test_has_streaming_chunk_hook_overrides_error_raises(monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["x"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(TypeError("nope")), + ) + with pytest.raises(TypeError): + ProxyLogging.has_streaming_chunk_hook_overrides() + + +def test_needs_iterator_wrap_truth_table(proxy_logging, monkeypatch, mock_callbacks_disabled): + snapshot = { + "empty_false": proxy_logging.needs_iterator_wrap(), + } + monkeypatch.setattr(litellm, "callbacks", [_OverridesIterator()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["with_iter_override_true"] = proxy_logging.needs_iterator_wrap() + monkeypatch.setattr(litellm, "callbacks", [_OverridesPerChunk()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["only_per_chunk_false"] = proxy_logging.needs_iterator_wrap() + assert snapshot == { + "empty_false": False, + "with_iter_override_true": True, + "only_per_chunk_false": False, + } + + +def test_needs_iterator_wrap_error_raises(proxy_logging, monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["x"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(RuntimeError("oops")), + ) + with pytest.raises(RuntimeError): + proxy_logging.needs_iterator_wrap() + + +def test_needs_per_chunk_streaming_hook_truth_table(proxy_logging, monkeypatch, mock_callbacks_disabled): + snapshot = { + "empty_false": proxy_logging.needs_per_chunk_streaming_hook(), + } + monkeypatch.setattr(litellm, "callbacks", [_OverridesPerChunk()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["per_chunk_override_true"] = proxy_logging.needs_per_chunk_streaming_hook() + monkeypatch.setattr(litellm, "callbacks", [_OverridesIterator()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["only_iter_override_false"] = proxy_logging.needs_per_chunk_streaming_hook() + assert snapshot == { + "empty_false": False, + "per_chunk_override_true": True, + "only_iter_override_false": False, + } + + +def test_needs_per_chunk_streaming_hook_error_raises(proxy_logging, monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["x"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(KeyError("oops")), + ) + with pytest.raises(KeyError): + proxy_logging.needs_per_chunk_streaming_hook() + + +def test_has_during_call_guardrails_truth_table(monkeypatch, mock_callbacks_disabled): + from litellm.integrations.custom_guardrail import CustomGuardrail + + class _G(CustomGuardrail): + def __init__(self): + super().__init__(guardrail_name="g", event_hook="pre_call") + + snapshot = { + "empty_false": ProxyLogging.has_during_call_guardrails(), + } + monkeypatch.setattr(litellm, "callbacks", [_G()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["with_guardrail_true"] = ProxyLogging.has_during_call_guardrails() + monkeypatch.setattr(litellm, "callbacks", [_PlainLogger()]) + ProxyLogging._callback_capabilities_cache.clear() + snapshot["only_plain_logger_false"] = ProxyLogging.has_during_call_guardrails() + assert snapshot == { + "empty_false": False, + "with_guardrail_true": True, + "only_plain_logger_false": False, + } + + +def test_has_during_call_guardrails_resolution_error_raises(monkeypatch): + monkeypatch.setattr(litellm, "callbacks", ["x"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "get_custom_logger_compatible_class", + lambda *a, **kw: (_ for _ in ()).throw(RuntimeError("oops")), + ) + with pytest.raises(RuntimeError): + ProxyLogging.has_during_call_guardrails() + + +# --------------------------------------------------------------------------- +# get_combined_callback_list +# --------------------------------------------------------------------------- + + +def test_get_combined_callback_list_matrix(proxy_logging): + snapshot = { + "merge_dedupes_shared": sorted( + proxy_logging.get_combined_callback_list( + dynamic_success_callbacks=["dyn-1", "shared"], + global_callbacks=["glob-1", "shared"], + ) + ), + "none_dynamic_returns_global_copy": proxy_logging.get_combined_callback_list( + dynamic_success_callbacks=None, global_callbacks=["a", "b", "c"] + ), + "empty_both": proxy_logging.get_combined_callback_list( + dynamic_success_callbacks=[], global_callbacks=[] + ), + } + assert snapshot == { + "merge_dedupes_shared": ["dyn-1", "glob-1", "shared"], + "none_dynamic_returns_global_copy": ["a", "b", "c"], + "empty_both": [], + } + + +def test_get_combined_callback_list_unhashable_dynamic_raises(proxy_logging): + with pytest.raises(TypeError): + proxy_logging.get_combined_callback_list( + dynamic_success_callbacks=[{"unhashable": True}], + global_callbacks=[], + ) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_dataclass.py b/tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_dataclass.py new file mode 100644 index 00000000000..931c832732e --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_callback_capabilities_dataclass.py @@ -0,0 +1,59 @@ +"""Pin the ``_CallbackCapabilities`` dataclass shape and defaults.""" + +from __future__ import annotations + +import dataclasses + +import pytest + +from litellm.proxy.utils import _CallbackCapabilities + + +def test_callback_capabilities_default_values(): + caps = _CallbackCapabilities() + snapshot = { + "has_post_call_response_headers": caps.has_post_call_response_headers, + "has_iterator_override": caps.has_iterator_override, + "has_streaming_chunk_override": caps.has_streaming_chunk_override, + "has_guardrail": caps.has_guardrail, + "has_pre_call_override": caps.has_pre_call_override, + "iterator_overrides": caps.iterator_overrides, + "resolved_callbacks": caps.resolved_callbacks, + } + assert snapshot == { + "has_post_call_response_headers": False, + "has_iterator_override": False, + "has_streaming_chunk_override": False, + "has_guardrail": False, + "has_pre_call_override": False, + "iterator_overrides": (), + "resolved_callbacks": (), + } + + +def test_callback_capabilities_explicit_values_preserved(): + cb1 = object() + cb2 = object() + caps = _CallbackCapabilities( + has_post_call_response_headers=True, + has_iterator_override=True, + has_streaming_chunk_override=False, + has_guardrail=True, + has_pre_call_override=False, + iterator_overrides=((cb1, "override"), (cb2, "apply_guardrail")), + resolved_callbacks=(cb1, cb2), + ) + assert caps.has_post_call_response_headers is True + assert caps.iterator_overrides == ((cb1, "override"), (cb2, "apply_guardrail")) + assert caps.resolved_callbacks == (cb1, cb2) + + +def test_callback_capabilities_is_frozen_error_on_mutation_raises(): + caps = _CallbackCapabilities() + with pytest.raises(dataclasses.FrozenInstanceError): + caps.has_post_call_response_headers = True # type: ignore[misc] + + +def test_callback_capabilities_invalid_field_error_raises(): + with pytest.raises(TypeError): + _CallbackCapabilities(unknown_field=True) # type: ignore[call-arg] diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_during_call_hook.py b/tests/test_litellm/proxy/utils/proxy_logging/test_during_call_hook.py new file mode 100644 index 00000000000..3c5d879c2dc --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_during_call_hook.py @@ -0,0 +1,86 @@ +"""Pin ``ProxyLogging.during_call_hook``.""" + +from __future__ import annotations + +from typing import Any, Dict +from unittest.mock import AsyncMock, MagicMock + +import pytest + +import litellm +from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.proxy.utils import ProxyLogging +from litellm.types.guardrails import GuardrailEventHooks + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +def _make_guardrail(name="g1", should_run=True, response=None): + cb = MagicMock(spec=CustomGuardrail) + cb.__class__ = CustomGuardrail + cb.guardrail_name = name + cb.event_hook = GuardrailEventHooks.during_call + cb.use_native_during_call_hook = False + cb.should_run_guardrail = MagicMock(return_value=should_run) + cb.async_moderation_hook = AsyncMock(return_value=response) + return cb + + +@pytest.mark.asyncio +async def test_during_call_hook_no_guardrail_fast_path_returns_data(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + data = {"messages": [{"role": "user"}], "model": "m", "temperature": 0.1} + out = await proxy_logging.during_call_hook( + data=data, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + assert out is data + + +@pytest.mark.asyncio +async def test_during_call_hook_runs_guardrails_in_parallel(proxy_logging, make_user_api_key_auth, monkeypatch): + g1 = _make_guardrail("a") + g2 = _make_guardrail("b") + monkeypatch.setattr(litellm, "callbacks", [g1, g2]) + data = {"messages": [{"role": "user"}], "model": "m", "temperature": 0.1} + out = await proxy_logging.during_call_hook( + data=data, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + snapshot = { + "out_is_data": out is data, + "a_called": g1.async_moderation_hook.called, + "b_called": g2.async_moderation_hook.called, + } + assert snapshot == {"out_is_data": True, "a_called": True, "b_called": True} + + +@pytest.mark.asyncio +async def test_during_call_hook_guardrail_skipped_when_should_not_run(proxy_logging, make_user_api_key_auth, monkeypatch): + g = _make_guardrail("g", should_run=False) + monkeypatch.setattr(litellm, "callbacks", [g]) + await proxy_logging.during_call_hook( + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + g.async_moderation_hook.assert_not_called() + + +@pytest.mark.asyncio +async def test_during_call_hook_guardrail_error_raises(proxy_logging, make_user_api_key_auth, monkeypatch): + g = _make_guardrail("bad") + g.async_moderation_hook = AsyncMock(side_effect=RuntimeError("blocked")) + monkeypatch.setattr(litellm, "callbacks", [g]) + with pytest.raises(RuntimeError): + await proxy_logging.during_call_hook( + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_guardrail_pipeline.py b/tests/test_litellm/proxy/utils/proxy_logging/test_guardrail_pipeline.py new file mode 100644 index 00000000000..1ff9fbf8d83 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_guardrail_pipeline.py @@ -0,0 +1,559 @@ +"""Pin ProxyLogging guardrail pipeline helpers. + +Covers ``_should_use_guardrail_load_balancing``, ``_execute_guardrail_hook``, +``_execute_guardrail_with_load_balancing``, ``_process_guardrail_callback``, +``_process_prompt_template``, ``_process_guardrail_metadata``, +``_maybe_execute_pipelines``, ``_handle_pipeline_result``, +``_run_guardrail_task_with_enrichment``. +""" + +from __future__ import annotations + +import asyncio +from typing import Any, Dict, List +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest +from fastapi import HTTPException + +import litellm +from litellm.integrations.custom_guardrail import ( + CustomGuardrail, + ModifyResponseException, +) +from litellm.proxy.utils import ProxyLogging +from litellm.types.guardrails import GuardrailEventHooks + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +# --------------------------------------------------------------------------- +# _should_use_guardrail_load_balancing +# --------------------------------------------------------------------------- + + +def test_should_use_guardrail_load_balancing_truth_table(proxy_logging): + snapshot = {} + router = MagicMock() + router.guardrail_list = [{"guardrail_name": "g1"}, {"guardrail_name": "g1"}] + with patch("litellm.proxy.proxy_server.llm_router", router): + snapshot["multiple_deployments"] = proxy_logging._should_use_guardrail_load_balancing("g1") + router.guardrail_list = [{"guardrail_name": "g1"}] + with patch("litellm.proxy.proxy_server.llm_router", router): + snapshot["single_deployment"] = proxy_logging._should_use_guardrail_load_balancing("g1") + with patch("litellm.proxy.proxy_server.llm_router", None): + snapshot["no_router"] = proxy_logging._should_use_guardrail_load_balancing("g1") + router.guardrail_list = [{"guardrail_name": "other"}, {"guardrail_name": "other"}] + with patch("litellm.proxy.proxy_server.llm_router", router): + snapshot["unmatched_name"] = proxy_logging._should_use_guardrail_load_balancing("g1") + assert snapshot == { + "multiple_deployments": True, + "single_deployment": False, + "no_router": False, + "unmatched_name": False, + } + + +def test_should_use_guardrail_load_balancing_error_on_bad_guardrail_list(proxy_logging): + router = MagicMock() + router.guardrail_list = "not a list" + with patch("litellm.proxy.proxy_server.llm_router", router): + with pytest.raises((TypeError, AttributeError)): + proxy_logging._should_use_guardrail_load_balancing("g1") + + +# --------------------------------------------------------------------------- +# _execute_guardrail_hook +# --------------------------------------------------------------------------- + + +def _make_guardrail(): + cb = MagicMock(spec=CustomGuardrail) + cb.__class__ = CustomGuardrail + cb.guardrail_name = "g" + cb.event_hook = GuardrailEventHooks.pre_call + cb.use_native_during_call_hook = False + cb.async_pre_call_hook = AsyncMock(return_value={"a": 1, "b": 2, "c": 3}) + cb.async_moderation_hook = AsyncMock(return_value={"x": 1, "y": 2, "z": 3}) + cb.async_post_call_success_hook = AsyncMock(return_value={"p": 1, "q": 2, "r": 3}) + return cb + + +@pytest.mark.asyncio +async def test_execute_guardrail_hook_pre_call(proxy_logging, make_user_api_key_auth): + cb = _make_guardrail() + out = await proxy_logging._execute_guardrail_hook( + callback=cb, + hook_type="pre_call", + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + assert out == {"a": 1, "b": 2, "c": 3} + + +@pytest.mark.asyncio +async def test_execute_guardrail_hook_during_call(proxy_logging, make_user_api_key_auth): + cb = _make_guardrail() + out = await proxy_logging._execute_guardrail_hook( + callback=cb, + hook_type="during_call", + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + assert out == {"x": 1, "y": 2, "z": 3} + + +@pytest.mark.asyncio +async def test_execute_guardrail_hook_post_call(proxy_logging, make_user_api_key_auth): + cb = _make_guardrail() + out = await proxy_logging._execute_guardrail_hook( + callback=cb, + hook_type="post_call", + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + response={"original": True}, + ) + assert out == {"p": 1, "q": 2, "r": 3} + + +@pytest.mark.asyncio +async def test_execute_guardrail_hook_unknown_hook_type_raises(proxy_logging, make_user_api_key_auth): + cb = _make_guardrail() + with pytest.raises(ValueError, match="Unknown hook_type"): + await proxy_logging._execute_guardrail_hook( + callback=cb, + hook_type="weird", # type: ignore[arg-type] + data={}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + + +# --------------------------------------------------------------------------- +# _execute_guardrail_with_load_balancing +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_execute_guardrail_with_load_balancing_routes_through_router( + proxy_logging, make_user_api_key_auth +): + cb = _make_guardrail() + router = MagicMock() + router.get_available_guardrail = MagicMock(return_value={"callback": cb}) + with patch("litellm.proxy.proxy_server.llm_router", router): + out = await proxy_logging._execute_guardrail_with_load_balancing( + guardrail_name="g", + hook_type="pre_call", + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + assert out == {"a": 1, "b": 2, "c": 3} + + +@pytest.mark.asyncio +async def test_execute_guardrail_with_load_balancing_router_none_raises( + proxy_logging, make_user_api_key_auth +): + with patch("litellm.proxy.proxy_server.llm_router", None): + with pytest.raises(ValueError, match="Router not initialized"): + await proxy_logging._execute_guardrail_with_load_balancing( + guardrail_name="g", + hook_type="pre_call", + data={}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + + +@pytest.mark.asyncio +async def test_execute_guardrail_with_load_balancing_no_callback_raises( + proxy_logging, make_user_api_key_auth +): + router = MagicMock() + router.get_available_guardrail = MagicMock(return_value={"callback": None}) + with patch("litellm.proxy.proxy_server.llm_router", router): + with pytest.raises(ValueError, match="No callback found"): + await proxy_logging._execute_guardrail_with_load_balancing( + guardrail_name="g", + hook_type="pre_call", + data={}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + ) + + +# --------------------------------------------------------------------------- +# _process_guardrail_callback +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_process_guardrail_callback_skipped_when_should_run_false( + proxy_logging, make_user_api_key_auth +): + cb = _make_guardrail() + cb.should_run_guardrail = MagicMock(return_value=False) + out = await proxy_logging._process_guardrail_callback( + callback=cb, + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + event_type=GuardrailEventHooks.pre_call, + ) + assert out is None + + +@pytest.mark.asyncio +async def test_process_guardrail_callback_returns_data_on_success( + proxy_logging, make_user_api_key_auth, monkeypatch +): + cb = _make_guardrail() + cb.should_run_guardrail = MagicMock(return_value=True) + proxy_logging._should_use_guardrail_load_balancing = MagicMock(return_value=False) + out = await proxy_logging._process_guardrail_callback( + callback=cb, + data={"model": "m", "messages": [{"role": "user"}], "temperature": 0.1}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + event_type=GuardrailEventHooks.pre_call, + ) + assert out == {"a": 1, "b": 2, "c": 3} + + +@pytest.mark.asyncio +async def test_process_guardrail_callback_enriches_and_reraises_http_exception( + proxy_logging, make_user_api_key_auth, monkeypatch +): + cb = _make_guardrail() + cb.should_run_guardrail = MagicMock(return_value=True) + detail = {"error": "blocked"} + cb.async_pre_call_hook = AsyncMock(side_effect=HTTPException(status_code=400, detail=detail)) + cb.event_hook = "pre_call" + proxy_logging._should_use_guardrail_load_balancing = MagicMock(return_value=False) + + with pytest.raises(HTTPException): + await proxy_logging._process_guardrail_callback( + callback=cb, + data={"model": "m"}, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + event_type=GuardrailEventHooks.pre_call, + ) + assert detail["guardrail_name"] == "g" + + +# --------------------------------------------------------------------------- +# _process_guardrail_metadata +# --------------------------------------------------------------------------- + + +def test_process_guardrail_metadata_calls_header_helper(proxy_logging, monkeypatch): + calls: List[Dict[str, Any]] = [] + + def fake_add(request_data, guardrail_name): + calls.append({"data": request_data, "name": guardrail_name}) + + from litellm.proxy.common_utils import callback_utils + + monkeypatch.setattr(callback_utils, "add_guardrail_to_applied_guardrails_header", fake_add) + data = {"metadata": {"guardrails": ["g1", "g2"]}} + proxy_logging._process_guardrail_metadata(data) + snapshot = { + "call_count": len(calls), + "first_name": calls[0]["name"], + "second_name": calls[1]["name"], + "data_passed_is_input": all(c["data"] is data for c in calls), + } + assert snapshot == { + "call_count": 2, + "first_name": "g1", + "second_name": "g2", + "data_passed_is_input": True, + } + + +def test_process_guardrail_metadata_skips_already_applied(proxy_logging, monkeypatch): + calls: List[str] = [] + + def fake_add(request_data, guardrail_name): + calls.append(guardrail_name) + + from litellm.proxy.common_utils import callback_utils + + monkeypatch.setattr(callback_utils, "add_guardrail_to_applied_guardrails_header", fake_add) + data = {"metadata": {"guardrails": ["g1", "g2"], "applied_guardrails": ["g1"]}} + proxy_logging._process_guardrail_metadata(data) + assert calls == ["g2"] + + +def test_process_guardrail_metadata_no_metadata_is_noop(proxy_logging, monkeypatch): + from litellm.proxy.common_utils import callback_utils + + monkeypatch.setattr( + callback_utils, + "add_guardrail_to_applied_guardrails_header", + MagicMock(side_effect=AssertionError("should not be called")), + ) + proxy_logging._process_guardrail_metadata({}) + + +def test_process_guardrail_metadata_invalid_data_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._process_guardrail_metadata(None) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _maybe_execute_pipelines +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_maybe_execute_pipelines_no_pipelines_returns_data(proxy_logging, make_user_api_key_auth): + data = {"messages": [{"role": "user"}], "model": "m", "temperature": 0.1} + out = await proxy_logging._maybe_execute_pipelines( + data=data, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + event_hook="pre_call", + ) + assert out == {"messages": [{"role": "user"}], "model": "m", "temperature": 0.1} + + +@pytest.mark.asyncio +async def test_maybe_execute_pipelines_skips_pipelines_with_other_mode(proxy_logging, make_user_api_key_auth, monkeypatch): + pipeline = MagicMock() + pipeline.mode = "post_call" # not pre_call + data = {"metadata": {"_guardrail_pipelines": [("p1", pipeline)]}, "model": "m", "messages": []} + executed = MagicMock() + monkeypatch.setattr( + "litellm.proxy.policy_engine.pipeline_executor.PipelineExecutor.execute_steps", executed + ) + out = await proxy_logging._maybe_execute_pipelines( + data=data, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + event_hook="pre_call", + ) + executed.assert_not_called() + assert out is data + + +@pytest.mark.asyncio +async def test_maybe_execute_pipelines_blocks_on_block_terminal_action_raises( + proxy_logging, make_user_api_key_auth, monkeypatch +): + pipeline = MagicMock() + pipeline.mode = "pre_call" + pipeline.steps = [] + fake_result = MagicMock() + fake_result.terminal_action = "block" + fake_result.step_results = [] + data = {"metadata": {"_guardrail_pipelines": [("policy-1", pipeline)]}, "messages": [], "model": "m"} + + async def fake_execute_steps(**kwargs): + return fake_result + + monkeypatch.setattr( + "litellm.proxy.policy_engine.pipeline_executor.PipelineExecutor.execute_steps", + fake_execute_steps, + ) + with pytest.raises(HTTPException): + await proxy_logging._maybe_execute_pipelines( + data=data, + user_api_key_dict=make_user_api_key_auth(), + call_type="completion", + event_hook="pre_call", + ) + + +# --------------------------------------------------------------------------- +# _handle_pipeline_result +# --------------------------------------------------------------------------- + + +def test_handle_pipeline_result_allow_with_modifications(): + data = {"a": 1} + result = MagicMock() + result.terminal_action = "allow" + result.modified_data = {"b": 2, "c": 3} + out = ProxyLogging._handle_pipeline_result(result=result, data=data, policy_name="p") + assert out == {"a": 1, "b": 2, "c": 3} + + +def test_handle_pipeline_result_block_raises_http_exception(): + result = MagicMock() + result.terminal_action = "block" + result.step_results = [] + with pytest.raises(HTTPException) as info: + ProxyLogging._handle_pipeline_result(result=result, data={"model": "m"}, policy_name="p") + detail = info.value.detail + snapshot = { + "is_dict": isinstance(detail, dict), + "error_type": detail["error"]["type"], + "policy": detail["error"]["pipeline_context"]["policy"], + } + assert snapshot == { + "is_dict": True, + "error_type": "guardrail_pipeline_error", + "policy": "p", + } + + +def test_handle_pipeline_result_modify_response_raises_modify_exception(): + result = MagicMock() + result.terminal_action = "modify_response" + result.modify_response_message = "filtered" + with pytest.raises(ModifyResponseException): + ProxyLogging._handle_pipeline_result(result=result, data={"model": "m"}, policy_name="p") + + +def test_handle_pipeline_result_unknown_action_returns_data(): + data = {"a": 1, "b": 2, "c": 3} + result = MagicMock() + result.terminal_action = "something_else" + assert ProxyLogging._handle_pipeline_result(result=result, data=data, policy_name="p") is data + + +# --------------------------------------------------------------------------- +# _run_guardrail_task_with_enrichment +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_run_guardrail_task_with_enrichment_passes_result(): + async def task(): + return {"a": 1, "b": 2, "c": 3} + + out = await ProxyLogging._run_guardrail_task_with_enrichment( + callback=MagicMock(guardrail_name="g"), coro=task() + ) + assert out == {"a": 1, "b": 2, "c": 3} + + +@pytest.mark.asyncio +async def test_run_guardrail_task_with_enrichment_enriches_http_exception_raises(): + detail = {"error": "blocked"} + + async def task(): + raise HTTPException(status_code=400, detail=detail) + + cb = MagicMock() + cb.guardrail_name = "presidio" + cb.event_hook = "pre_call" + with pytest.raises(HTTPException): + await ProxyLogging._run_guardrail_task_with_enrichment(callback=cb, coro=task()) + assert detail["guardrail_name"] == "presidio" + + +# --------------------------------------------------------------------------- +# _process_prompt_template +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_process_prompt_template_no_op_when_no_prompt_spec(proxy_logging, monkeypatch): + from litellm.proxy.prompts import prompt_registry + + monkeypatch.setattr( + prompt_registry.IN_MEMORY_PROMPT_REGISTRY, "get_prompt_callback_by_id", lambda *a, **kw: None + ) + monkeypatch.setattr( + prompt_registry.IN_MEMORY_PROMPT_REGISTRY, "get_prompt_by_id", lambda *a, **kw: None + ) + data: Dict[str, Any] = {"messages": [{"role": "user"}], "model": "m", "temperature": 0.1} + await proxy_logging._process_prompt_template( + data=data, + litellm_logging_obj=MagicMock(), + prompt_id="some-id", + prompt_version=1, + call_type="completion", + ) + assert data == {"messages": [{"role": "user"}], "model": "m", "temperature": 0.1} + + +@pytest.mark.asyncio +async def test_process_prompt_template_applies_when_spec_resolves(proxy_logging, monkeypatch): + from litellm.proxy.prompts import prompt_registry + + custom_logger = MagicMock() + prompt_spec = MagicMock() + prompt_spec.litellm_params = MagicMock(prompt_id="resolved-id") + + monkeypatch.setattr( + prompt_registry.IN_MEMORY_PROMPT_REGISTRY, + "get_prompt_callback_by_id", + lambda *a, **kw: custom_logger, + ) + monkeypatch.setattr( + prompt_registry.IN_MEMORY_PROMPT_REGISTRY, "get_prompt_by_id", lambda *a, **kw: prompt_spec + ) + + logging_obj = MagicMock() + logging_obj.async_get_chat_completion_prompt = AsyncMock( + return_value=( + "model-out", + [{"role": "user", "content": "rendered"}], + {"temperature": 0.5, "top_p": 1}, + ) + ) + data: Dict[str, Any] = { + "messages": [{"role": "user", "content": "orig"}], + "model": "m", + "prompt_id": "x", + } + await proxy_logging._process_prompt_template( + data=data, + litellm_logging_obj=logging_obj, + prompt_id="x", + prompt_version=None, + call_type="completion", + ) + snapshot = { + "model": data["model"], + "messages": data["messages"], + "temperature": data["temperature"], + "top_p": data["top_p"], + } + assert snapshot == { + "model": "model-out", + "messages": [{"role": "user", "content": "rendered"}], + "temperature": 0.5, + "top_p": 1, + } + + +@pytest.mark.asyncio +async def test_process_prompt_template_async_get_prompt_error_raises(proxy_logging, monkeypatch): + from litellm.proxy.prompts import prompt_registry + + custom_logger = MagicMock() + prompt_spec = MagicMock() + prompt_spec.litellm_params = MagicMock(prompt_id="x") + monkeypatch.setattr( + prompt_registry.IN_MEMORY_PROMPT_REGISTRY, + "get_prompt_callback_by_id", + lambda *a, **kw: custom_logger, + ) + monkeypatch.setattr( + prompt_registry.IN_MEMORY_PROMPT_REGISTRY, "get_prompt_by_id", lambda *a, **kw: prompt_spec + ) + logging_obj = MagicMock() + logging_obj.async_get_chat_completion_prompt = AsyncMock(side_effect=RuntimeError("bad prompt")) + with pytest.raises(RuntimeError): + await proxy_logging._process_prompt_template( + data={"messages": [], "model": "m", "prompt_id": "x"}, + litellm_logging_obj=logging_obj, + prompt_id="x", + prompt_version=None, + call_type="completion", + ) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_internal_usage_cache.py b/tests/test_litellm/proxy/utils/proxy_logging/test_internal_usage_cache.py new file mode 100644 index 00000000000..ff0afa45e36 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_internal_usage_cache.py @@ -0,0 +1,186 @@ +"""Pin behavior of ``InternalUsageCache``: a thin adapter over ``DualCache``. + +Each method should pass-through to the underlying ``DualCache`` with +exactly the same arguments, mapping ``litellm_parent_otel_span`` to the +``DualCache`` kw it expects. +""" + +from __future__ import annotations + +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.caching.caching import DualCache +from litellm.proxy.utils import InternalUsageCache + + +def _kwargs_snapshot(call): + return dict(call.kwargs) + + +def test_internal_usage_cache_init_stores_dual_cache(): + inner = DualCache(default_in_memory_ttl=1) + cache = InternalUsageCache(dual_cache=inner) + snapshot = { + "is_internal_usage_cache": isinstance(cache, InternalUsageCache), + "dual_cache_is_inner": cache.dual_cache is inner, + "ttl_is_one": inner.default_in_memory_ttl == 1, + } + assert snapshot == { + "is_internal_usage_cache": True, + "dual_cache_is_inner": True, + "ttl_is_one": True, + } + + +def test_internal_usage_cache_init_error_requires_dual_cache(): + with pytest.raises(TypeError): + InternalUsageCache() # type: ignore[call-arg] + + +@pytest.mark.asyncio +async def test_async_get_cache_forwards_args(): + inner = MagicMock() + inner.async_get_cache = AsyncMock(return_value={"hit": True, "value": 42, "source": "redis"}) + cache = InternalUsageCache(dual_cache=inner) + + result = await cache.async_get_cache(key="k", litellm_parent_otel_span="span", local_only=True, extra="x") + forwarded = _kwargs_snapshot(inner.async_get_cache.call_args) + assert forwarded == {"key": "k", "local_only": True, "parent_otel_span": "span", "extra": "x"} + assert result == {"hit": True, "value": 42, "source": "redis"} + + +@pytest.mark.asyncio +async def test_async_get_cache_propagates_underlying_error_raises(): + inner = MagicMock() + inner.async_get_cache = AsyncMock(side_effect=RuntimeError("redis down")) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(RuntimeError, match="redis down"): + await cache.async_get_cache(key="k", litellm_parent_otel_span=None) + + +@pytest.mark.asyncio +async def test_async_set_cache_forwards_args(): + inner = MagicMock() + inner.async_set_cache = AsyncMock() + cache = InternalUsageCache(dual_cache=inner) + + await cache.async_set_cache(key="k", value="v", litellm_parent_otel_span="span", local_only=False, ttl=60) + forwarded = _kwargs_snapshot(inner.async_set_cache.call_args) + assert forwarded == { + "key": "k", + "value": "v", + "local_only": False, + "litellm_parent_otel_span": "span", + "ttl": 60, + } + + +@pytest.mark.asyncio +async def test_async_set_cache_propagates_error_raises(): + inner = MagicMock() + inner.async_set_cache = AsyncMock(side_effect=ValueError("bad value")) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(ValueError, match="bad value"): + await cache.async_set_cache(key="k", value="v", litellm_parent_otel_span=None) + + +@pytest.mark.asyncio +async def test_async_batch_set_cache_forwards_pipeline(): + inner = MagicMock() + inner.async_set_cache_pipeline = AsyncMock() + cache = InternalUsageCache(dual_cache=inner) + + pairs = [("a", 1), ("b", 2)] + await cache.async_batch_set_cache(cache_list=pairs, litellm_parent_otel_span=None, local_only=True, ttl=10) + forwarded = _kwargs_snapshot(inner.async_set_cache_pipeline.call_args) + assert forwarded == { + "cache_list": pairs, + "local_only": True, + "litellm_parent_otel_span": None, + "ttl": 10, + } + + +@pytest.mark.asyncio +async def test_async_batch_set_cache_propagates_error_raises(): + inner = MagicMock() + inner.async_set_cache_pipeline = AsyncMock(side_effect=ConnectionError("network")) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(ConnectionError): + await cache.async_batch_set_cache(cache_list=[], litellm_parent_otel_span=None) + + +@pytest.mark.asyncio +async def test_async_batch_get_cache_forwards_args(): + inner = MagicMock() + inner.async_batch_get_cache = AsyncMock(return_value=[1, 2, 3]) + cache = InternalUsageCache(dual_cache=inner) + result = await cache.async_batch_get_cache(keys=["a", "b", "c"], parent_otel_span="span", local_only=False) + forwarded = _kwargs_snapshot(inner.async_batch_get_cache.call_args) + assert forwarded == {"keys": ["a", "b", "c"], "parent_otel_span": "span", "local_only": False} + assert result == [1, 2, 3] + + +@pytest.mark.asyncio +async def test_async_batch_get_cache_invalid_input_raises(): + inner = MagicMock() + inner.async_batch_get_cache = AsyncMock(side_effect=TypeError("not a list")) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(TypeError): + await cache.async_batch_get_cache(keys=None) # type: ignore[arg-type] + + +@pytest.mark.asyncio +async def test_async_increment_cache_forwards_args(): + inner = MagicMock() + inner.async_increment_cache = AsyncMock(return_value=5.0) + cache = InternalUsageCache(dual_cache=inner) + result = await cache.async_increment_cache(key="counter", value=1.5, litellm_parent_otel_span="span") + forwarded = _kwargs_snapshot(inner.async_increment_cache.call_args) + assert forwarded == {"key": "counter", "value": 1.5, "local_only": False, "parent_otel_span": "span"} + assert result == 5.0 + + +@pytest.mark.asyncio +async def test_async_increment_cache_propagates_error_raises(): + inner = MagicMock() + inner.async_increment_cache = AsyncMock(side_effect=OverflowError()) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(OverflowError): + await cache.async_increment_cache(key="x", value=1.0, litellm_parent_otel_span=None) + + +def test_set_cache_forwards_args(): + inner = MagicMock() + cache = InternalUsageCache(dual_cache=inner) + cache.set_cache(key="k", value="v", local_only=True, ttl=30) + forwarded = _kwargs_snapshot(inner.set_cache.call_args) + assert forwarded == {"key": "k", "value": "v", "local_only": True, "ttl": 30} + + +def test_set_cache_propagates_error_raises(): + inner = MagicMock() + inner.set_cache = MagicMock(side_effect=RuntimeError("no redis")) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(RuntimeError): + cache.set_cache(key="k", value="v") + + +def test_get_cache_forwards_args_and_returns_inner_result(): + inner = MagicMock() + inner.get_cache = MagicMock(return_value={"k": "v", "ttl": 60, "source": "mem"}) + cache = InternalUsageCache(dual_cache=inner) + result = cache.get_cache(key="k", local_only=False) + forwarded = _kwargs_snapshot(inner.get_cache.call_args) + assert forwarded == {"key": "k", "local_only": False} + assert result == {"k": "v", "ttl": 60, "source": "mem"} + + +def test_get_cache_propagates_error_raises(): + inner = MagicMock() + inner.get_cache = MagicMock(side_effect=KeyError("missing")) + cache = InternalUsageCache(dual_cache=inner) + with pytest.raises(KeyError): + cache.get_cache(key="missing") diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_lifecycle.py b/tests/test_litellm/proxy/utils/proxy_logging/test_lifecycle.py new file mode 100644 index 00000000000..e33da672599 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_lifecycle.py @@ -0,0 +1,403 @@ +"""Pin ProxyLogging lifecycle: ``__init__``, ``startup_event``, +``update_values``, ``_add_proxy_hooks``, ``get_proxy_hook``, and +``_init_litellm_callbacks``. + +Also covers ``update_request_status`` and ``_convert_user_api_key_auth_to_dict`` +because they are direct dependents on the lifecycle state. +""" + +from __future__ import annotations + +import asyncio +from typing import Any, Dict, List +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +import litellm +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache +from litellm.proxy.utils import ( + InternalUsageCache, + ProxyLogging, +) + + +# --------------------------------------------------------------------------- +# __init__ +# --------------------------------------------------------------------------- + + +def test_proxy_logging_init_sets_default_state(mock_callbacks_disabled): + cache = UserApiKeyCache() + pl = ProxyLogging(user_api_key_cache=cache) + snapshot = { + "internal_usage_cache_type": type(pl.internal_usage_cache).__name__, + "alerting_is_none": pl.alerting is None, + "alerting_threshold": pl.alerting_threshold, + "premium_user": pl.premium_user, + "proxy_hook_mapping": pl.proxy_hook_mapping, + "daily_report_started": pl.daily_report_started, + "hanging_requests_check_started": pl.hanging_requests_check_started, + } + assert snapshot == { + "internal_usage_cache_type": "InternalUsageCache", + "alerting_is_none": True, + "alerting_threshold": 300, + "premium_user": False, + "proxy_hook_mapping": {}, + "daily_report_started": False, + "hanging_requests_check_started": False, + } + + +def test_proxy_logging_init_premium_user_flag(mock_callbacks_disabled): + pl = ProxyLogging(user_api_key_cache=UserApiKeyCache(), premium_user=True) + assert pl.premium_user is True + + +def test_proxy_logging_init_missing_cache_raises(): + with pytest.raises(TypeError): + ProxyLogging() # type: ignore[call-arg] + + +# --------------------------------------------------------------------------- +# update_values +# --------------------------------------------------------------------------- + + +def test_update_values_stores_alerting_state(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + proxy_logging.update_values( + alerting=["slack"], + alerting_threshold=42.0, + alert_types=["llm_too_slow"], + alert_to_webhook_url={"key": "value"}, + ) + snapshot = { + "alerting": proxy_logging.alerting, + "threshold": proxy_logging.alerting_threshold, + "alert_types": proxy_logging.alert_types, + "webhook_url": proxy_logging.alert_to_webhook_url, + } + assert snapshot == { + "alerting": ["slack"], + "threshold": 42.0, + "alert_types": ["llm_too_slow"], + "webhook_url": {"key": "value"}, + } + + +def test_update_values_with_only_redis_cache_does_not_touch_slack(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + redis = MagicMock() + proxy_logging.update_values(redis_cache=redis) + proxy_logging.slack_alerting_instance.update_values.assert_not_called() + assert proxy_logging.internal_usage_cache.dual_cache.redis_cache is redis + + +def test_update_values_with_no_args_is_noop(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + proxy_logging.update_values() + proxy_logging.slack_alerting_instance.update_values.assert_not_called() + + +def test_update_values_invalid_type_for_alerting_raises(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock( + update_values=MagicMock(side_effect=TypeError("bad type")) + ) + with pytest.raises(TypeError): + proxy_logging.update_values(alerting={"not": "a list"}) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# startup_event +# --------------------------------------------------------------------------- + + +def test_startup_event_initializes_slack_and_callbacks(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + proxy_logging.slack_alerting_instance.alert_types = [] + proxy_logging._init_litellm_callbacks = MagicMock() + proxy_logging.update_values = MagicMock() + + proxy_logging.startup_event(llm_router=None, redis_usage_cache=None) + snapshot = { + "update_called": proxy_logging.update_values.called, + "init_called": proxy_logging._init_litellm_callbacks.called, + "slack_update_called": proxy_logging.slack_alerting_instance.update_values.called, + } + assert snapshot == { + "update_called": True, + "init_called": True, + "slack_update_called": True, + } + + +def test_startup_event_propagates_init_callbacks_failure_raises(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + proxy_logging.slack_alerting_instance.alert_types = [] + proxy_logging._init_litellm_callbacks = MagicMock(side_effect=RuntimeError("boom")) + + with pytest.raises(RuntimeError, match="boom"): + proxy_logging.startup_event(llm_router=None, redis_usage_cache=None) + + +# --------------------------------------------------------------------------- +# _add_proxy_hooks +# --------------------------------------------------------------------------- + + +def test_add_proxy_hooks_registers_callbacks(proxy_logging, monkeypatch): + """Patch ``PROXY_HOOKS`` and the resolver so we control exactly + what gets registered. Verifies that the resulting instances land in + ``proxy_logging.proxy_hook_mapping`` keyed by hook name. + """ + hook_keys = ["cache_control_check", "max_budget_limiter"] + registered: List[Any] = [] + + from litellm.proxy import utils as utils_mod + + def fake_get_proxy_hook(hook_name): + class _Stub: + __name__ = hook_name + + def __init__(self, **kwargs): + self.hook_name = hook_name + + return _Stub + + monkeypatch.setattr(utils_mod, "PROXY_HOOKS", hook_keys) + monkeypatch.setattr(utils_mod, "get_proxy_hook", fake_get_proxy_hook) + monkeypatch.setattr( + litellm.logging_callback_manager, + "add_litellm_callback", + lambda cb: registered.append(cb), + ) + + with patch("litellm.proxy.proxy_server.prisma_client", None): + proxy_logging._add_proxy_hooks(llm_router=None) + + keys = list(proxy_logging.proxy_hook_mapping.keys()) + snapshot = { + "mapping_keys": keys, + "registered_count": len(registered), + "registered_hook_names": [getattr(r, "hook_name", None) for r in registered], + } + assert snapshot == { + "mapping_keys": hook_keys, + "registered_count": len(hook_keys), + "registered_hook_names": hook_keys, + } + + +def test_add_proxy_hooks_unknown_hook_raises(proxy_logging, monkeypatch): + from litellm.proxy import utils as utils_mod + + monkeypatch.setattr(utils_mod, "PROXY_HOOKS", ["bogus_hook"]) + + def bad_resolver(name): + raise KeyError(name) + + monkeypatch.setattr(utils_mod, "get_proxy_hook", bad_resolver) + with pytest.raises(KeyError): + proxy_logging._add_proxy_hooks(llm_router=None) + + +# --------------------------------------------------------------------------- +# get_proxy_hook +# --------------------------------------------------------------------------- + + +def test_get_proxy_hook_returns_registered_instance(proxy_logging): + s_cache = MagicMock() + s_budget = MagicMock() + s_parallel = MagicMock() + proxy_logging.proxy_hook_mapping = { + "cache_control_check": s_cache, + "max_budget_limiter": s_budget, + "max_parallel_request_limiter": s_parallel, + } + snapshot = { + "cache_control_check": proxy_logging.get_proxy_hook("cache_control_check") is s_cache, + "max_budget_limiter": proxy_logging.get_proxy_hook("max_budget_limiter") is s_budget, + "max_parallel_request_limiter": proxy_logging.get_proxy_hook("max_parallel_request_limiter") is s_parallel, + "unknown_returns_none": proxy_logging.get_proxy_hook("unknown") is None, + } + assert snapshot == { + "cache_control_check": True, + "max_budget_limiter": True, + "max_parallel_request_limiter": True, + "unknown_returns_none": True, + } + + +def test_get_proxy_hook_unknown_returns_none(proxy_logging): + proxy_logging.proxy_hook_mapping = {} + assert proxy_logging.get_proxy_hook("does-not-exist") is None + + +def test_get_proxy_hook_non_string_key_raises(proxy_logging): + # ``dict.get`` doesn't raise on unhashable types — but ``None`` returns None. + # The pin: passing an unhashable key blows up like dict access does. + proxy_logging.proxy_hook_mapping = {"k": object()} + with pytest.raises(TypeError): + proxy_logging.get_proxy_hook({"unhashable": True}) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _init_litellm_callbacks +# --------------------------------------------------------------------------- + + +def test_init_litellm_callbacks_replaces_string_with_instance(proxy_logging, monkeypatch): + from litellm.proxy import utils as utils_mod + + sentinel_instance = MagicMock(spec=litellm.integrations.custom_logger.CustomLogger) + sentinel_instance.__class__ = litellm.integrations.custom_logger.CustomLogger + + monkeypatch.setattr(litellm, "callbacks", ["some-string-logger"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "_init_custom_logger_compatible_class", + lambda *a, **kw: sentinel_instance, + ) + + monkeypatch.setattr(utils_mod, "PROXY_HOOKS", []) + proxy_logging._init_litellm_callbacks(llm_router=None) + snapshot = { + "replaced_first_item": litellm.callbacks[0] is sentinel_instance, + "callbacks_grew_with_service": len(litellm.callbacks) >= 2, + "service_logging_appended": any( + "ServiceLogging" in type(c).__name__ for c in litellm.callbacks + ), + } + assert snapshot == { + "replaced_first_item": True, + "callbacks_grew_with_service": True, + "service_logging_appended": True, + } + + +def test_init_litellm_callbacks_string_resolution_failure_keeps_string(proxy_logging, monkeypatch): + from litellm.proxy import utils as utils_mod + + monkeypatch.setattr(litellm, "callbacks", ["unknown-logger"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "_init_custom_logger_compatible_class", + lambda *a, **kw: None, + ) + monkeypatch.setattr(utils_mod, "PROXY_HOOKS", []) + proxy_logging._init_litellm_callbacks(llm_router=None) + # Resolver returned None — original string remains in place at idx 0. + assert litellm.callbacks[0] == "unknown-logger" + + +def test_init_litellm_callbacks_propagates_resolver_error_raises(proxy_logging, monkeypatch): + from litellm.proxy import utils as utils_mod + + monkeypatch.setattr(litellm, "callbacks", ["raises-on-init"]) + monkeypatch.setattr( + litellm.litellm_core_utils.litellm_logging, + "_init_custom_logger_compatible_class", + MagicMock(side_effect=RuntimeError("bad init")), + ) + monkeypatch.setattr(utils_mod, "PROXY_HOOKS", []) + with pytest.raises(RuntimeError): + proxy_logging._init_litellm_callbacks(llm_router=None) + + +# --------------------------------------------------------------------------- +# update_request_status +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_update_request_status_when_alerting_set_writes_cache(proxy_logging): + proxy_logging.alerting = ["slack"] + proxy_logging.alerting_threshold = 5.0 + captured: Dict[str, Any] = {} + + async def fake_set_cache(**kwargs): + captured.update(kwargs) + + proxy_logging.internal_usage_cache.async_set_cache = fake_set_cache # type: ignore[assignment] + await proxy_logging.update_request_status(litellm_call_id="call-1", status="success") + snapshot = { + "key": captured["key"], + "value": captured["value"], + "local_only": captured["local_only"], + "ttl": captured["ttl"], + } + assert snapshot == { + "key": "request_status:call-1", + "value": "success", + "local_only": True, + "ttl": 105.0, + } + + +@pytest.mark.asyncio +async def test_update_request_status_no_alerting_skips_cache(proxy_logging): + proxy_logging.alerting = None + proxy_logging.internal_usage_cache.async_set_cache = AsyncMock() + await proxy_logging.update_request_status(litellm_call_id="call-1", status="success") + proxy_logging.internal_usage_cache.async_set_cache.assert_not_called() + + +@pytest.mark.asyncio +async def test_update_request_status_cache_error_raises(proxy_logging): + proxy_logging.alerting = ["slack"] + proxy_logging.internal_usage_cache.async_set_cache = AsyncMock(side_effect=ConnectionError("redis")) + with pytest.raises(ConnectionError): + await proxy_logging.update_request_status(litellm_call_id="x", status="fail") + + +# --------------------------------------------------------------------------- +# _convert_user_api_key_auth_to_dict +# --------------------------------------------------------------------------- + + +def test_convert_user_api_key_auth_to_dict_pydantic_uses_model_dump(proxy_logging, make_user_api_key_auth): + auth = make_user_api_key_auth(user_id="u-1", team_id="t-1") + result = proxy_logging._convert_user_api_key_auth_to_dict(auth) + snapshot = { + "user_id": result["user_id"], + "team_id": result["team_id"], + "is_dict": isinstance(result, dict), + } + assert snapshot == {"user_id": "u-1", "team_id": "t-1", "is_dict": True} + + +def test_convert_user_api_key_auth_to_dict_plain_object_uses_dict(proxy_logging): + class Obj: + pass + + obj = Obj() + obj.a = 1 + obj.b = 2 + obj.c = 3 + result = proxy_logging._convert_user_api_key_auth_to_dict(obj) + assert result == {"a": 1, "b": 2, "c": 3} + + +def test_convert_user_api_key_auth_to_dict_none_returns_empty_dict(proxy_logging): + assert proxy_logging._convert_user_api_key_auth_to_dict(None) == {} + + +def test_convert_user_api_key_auth_to_dict_unconvertible_object_returns_empty(proxy_logging): + class NoDict: + __slots__ = () + + assert proxy_logging._convert_user_api_key_auth_to_dict(NoDict()) == {} + + +def test_convert_user_api_key_auth_to_dict_pydantic_error_raises(proxy_logging): + """A ``model_dump`` that raises propagates.""" + + class _Boom: + def model_dump(self): + raise RuntimeError("model_dump failure") + + with pytest.raises(RuntimeError): + proxy_logging._convert_user_api_key_auth_to_dict(_Boom()) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_mcp_bridging.py b/tests/test_litellm/proxy/utils/proxy_logging/test_mcp_bridging.py new file mode 100644 index 00000000000..9defb309863 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_mcp_bridging.py @@ -0,0 +1,426 @@ +"""Pin ProxyLogging's MCP-LLM bridging helpers. + +Covers: +- ``_convert_mcp_to_llm_format`` +- ``_convert_llm_result_to_mcp_response`` +- ``_extract_modified_arguments_from_content`` +- ``_parse_arguments_manually`` +- ``_convert_llm_result_to_mcp_during_response`` +- ``_parse_pre_mcp_call_hook_response`` +- ``_create_mcp_request_object_from_kwargs`` +- ``_convert_mcp_hook_response_to_kwargs`` +""" + +from __future__ import annotations + +import pytest + +from litellm.types.mcp import ( + MCPDuringCallResponseObject, + MCPPreCallRequestObject, + MCPPreCallResponseObject, +) + + +# --------------------------------------------------------------------------- +# _convert_mcp_to_llm_format +# --------------------------------------------------------------------------- + + +def test_convert_mcp_to_llm_format_returns_synthetic_data(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="search", arguments={"q": "hello"}) + out = proxy_logging._convert_mcp_to_llm_format( + request_obj=req, + kwargs={ + "model": "gpt-4o-mini", + "user_api_key_user_id": "u-1", + "user_api_key_team_id": "t-1", + "user_api_key_end_user_id": "eu-1", + "user_api_key_hash": "hash", + "user_api_key_request_route": "/mcp", + "incoming_bearer_token": "tok", + }, + ) + snapshot = { + "model": out["model"], + "user_id": out["user_api_key_user_id"], + "mcp_tool_name": out["mcp_tool_name"], + "mcp_arguments": out["mcp_arguments"], + "incoming_bearer_token": out["incoming_bearer_token"], + "message_role": out["messages"][0]["role"], + } + assert snapshot == { + "model": "gpt-4o-mini", + "user_id": "u-1", + "mcp_tool_name": "search", + "mcp_arguments": {"q": "hello"}, + "incoming_bearer_token": "tok", + "message_role": "user", + } + + +def test_convert_mcp_to_llm_format_defaults_model(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj() + out = proxy_logging._convert_mcp_to_llm_format(request_obj=req, kwargs={}) + snapshot = { + "model": out["model"], + "mcp_tool_name": out["mcp_tool_name"], + "incoming_bearer_token": out["incoming_bearer_token"], + "user_id": out["user_api_key_user_id"], + } + assert snapshot == { + "model": "mcp-tool-call", + "mcp_tool_name": "calculator", + "incoming_bearer_token": None, + "user_id": None, + } + + +def test_convert_mcp_to_llm_format_missing_request_obj_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._convert_mcp_to_llm_format(request_obj=None, kwargs={}) + + +# --------------------------------------------------------------------------- +# _convert_llm_result_to_mcp_response +# --------------------------------------------------------------------------- + + +def test_convert_llm_result_to_mcp_response_exception_blocks(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj() + result = proxy_logging._convert_llm_result_to_mcp_response( + llm_result=ValueError("boom"), + request_obj=req, + ) + assert isinstance(result, MCPPreCallResponseObject) + snapshot = { + "should_proceed": result.should_proceed, + "error_message": result.error_message, + "modified_arguments": result.modified_arguments, + } + assert snapshot == {"should_proceed": False, "error_message": "boom", "modified_arguments": None} + + +def test_convert_llm_result_to_mcp_response_blocked_content(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="t", arguments={"a": 1}) + llm_result = {"messages": [{"content": "this is blocked"}]} + result = proxy_logging._convert_llm_result_to_mcp_response(llm_result=llm_result, request_obj=req) + assert isinstance(result, MCPPreCallResponseObject) + assert result.should_proceed is False + assert "blocked" in (result.error_message or "").lower() + + +def test_convert_llm_result_to_mcp_response_modified_content_redacted(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="search", arguments={"q": "ssn 123"}) + llm_result = {"messages": [{"content": "Tool: search\nArguments: {\"q\": \"[REDACTED]\"}"}]} + result = proxy_logging._convert_llm_result_to_mcp_response(llm_result=llm_result, request_obj=req) + assert isinstance(result, MCPPreCallResponseObject) + snapshot = { + "should_proceed": result.should_proceed, + "modified_q": (result.modified_arguments or {}).get("q"), + "error": result.error_message, + } + assert snapshot == {"should_proceed": True, "modified_q": "[REDACTED]", "error": None} + + +def test_convert_llm_result_to_mcp_response_string_blocks(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj() + result = proxy_logging._convert_llm_result_to_mcp_response(llm_result="bad input", request_obj=req) + assert isinstance(result, MCPPreCallResponseObject) + snapshot = { + "should_proceed": result.should_proceed, + "error_message": result.error_message, + "modified_arguments": result.modified_arguments, + } + assert snapshot == {"should_proceed": False, "error_message": "bad input", "modified_arguments": None} + + +def test_convert_llm_result_to_mcp_response_unmodified_returns_none(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="x", arguments={"a": 1}) + same_content = "Tool: x\nArguments: {'a': 1}" + result = proxy_logging._convert_llm_result_to_mcp_response( + llm_result={"messages": [{"content": same_content}]}, + request_obj=req, + ) + assert result is None + + +def test_convert_llm_result_to_mcp_response_no_request_obj_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._convert_llm_result_to_mcp_response(llm_result={"messages": [{"content": "x"}]}, request_obj=None) + + +# --------------------------------------------------------------------------- +# _extract_modified_arguments_from_content +# --------------------------------------------------------------------------- + + +def test_extract_modified_arguments_from_content_parses_json(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj() + out = proxy_logging._extract_modified_arguments_from_content( + masked_content="Tool: x\nArguments: {\"a\": 1, \"b\": 2, \"c\": 3}", + request_obj=req, + ) + assert out == {"a": 1, "b": 2, "c": 3} + + +def test_extract_modified_arguments_from_content_no_arguments_line_returns_none(proxy_logging, make_mcp_request_obj): + out = proxy_logging._extract_modified_arguments_from_content( + masked_content="random content with no arguments", + request_obj=make_mcp_request_obj(), + ) + assert out is None + + +def test_extract_modified_arguments_from_content_empty_string_returns_none(proxy_logging, make_mcp_request_obj): + out = proxy_logging._extract_modified_arguments_from_content( + masked_content="", + request_obj=make_mcp_request_obj(), + ) + assert out is None + + +def test_extract_modified_arguments_from_content_invalid_json_falls_back(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(arguments={"name": "alice"}) + out = proxy_logging._extract_modified_arguments_from_content( + masked_content="Tool: x\nArguments: {name: REDACTED}", + request_obj=req, + ) + assert isinstance(out, dict) + assert "name" in out + + +def test_extract_modified_arguments_from_content_error_swallowed_returns_none(proxy_logging): + """Internal try/except swallows any unexpected error and returns None.""" + out = proxy_logging._extract_modified_arguments_from_content(masked_content=None, request_obj=None) + assert out is None + + +# --------------------------------------------------------------------------- +# _parse_arguments_manually +# --------------------------------------------------------------------------- + + +def test_parse_arguments_manually_applies_overrides(proxy_logging): + original = {"name": "alice", "ssn": "123-45-6789"} + out = proxy_logging._parse_arguments_manually( + args_text='"name": "[REDACTED]", "ssn": "[REDACTED]"', + original_args=original, + ) + snapshot = {"name": out["name"], "ssn": out["ssn"], "original_unchanged": original["name"]} + assert snapshot == {"name": "[REDACTED]", "ssn": "[REDACTED]", "original_unchanged": "alice"} + + +def test_parse_arguments_manually_returns_original_if_no_match(proxy_logging): + original = {"foo": "bar"} + out = proxy_logging._parse_arguments_manually(args_text="nothing here", original_args=original) + assert out == {"foo": "bar"} + + +def test_parse_arguments_manually_error_swallowed_returns_none(proxy_logging): + # Defensive: function catches any exception internally and returns None. + assert proxy_logging._parse_arguments_manually(args_text="x", original_args=None) is None # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _convert_llm_result_to_mcp_during_response +# --------------------------------------------------------------------------- + + +def test_convert_llm_result_to_mcp_during_response_exception(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj() + result = proxy_logging._convert_llm_result_to_mcp_during_response( + llm_result=ValueError("during boom"), request_obj=req + ) + assert isinstance(result, MCPDuringCallResponseObject) + snapshot = { + "should_continue": result.should_continue, + "error_message": result.error_message, + "type": type(result).__name__, + } + assert snapshot == { + "should_continue": False, + "error_message": "during boom", + "type": "MCPDuringCallResponseObject", + } + + +def test_convert_llm_result_to_mcp_during_response_blocked_content(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="t", arguments={"a": 1}) + result = proxy_logging._convert_llm_result_to_mcp_during_response( + llm_result={"messages": [{"content": "blocked content"}]}, + request_obj=req, + ) + assert isinstance(result, MCPDuringCallResponseObject) + assert result.should_continue is False + assert "blocked" in (result.error_message or "").lower() + + +def test_convert_llm_result_to_mcp_during_response_modified_stops(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="t", arguments={"a": 1}) + result = proxy_logging._convert_llm_result_to_mcp_during_response( + llm_result={"messages": [{"content": "Tool: t\nArguments: {\"a\": \"[REDACTED]\"}"}]}, + request_obj=req, + ) + assert isinstance(result, MCPDuringCallResponseObject) + assert result.should_continue is False + assert "modified" in (result.error_message or "").lower() + + +def test_convert_llm_result_to_mcp_during_response_string_blocks(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj() + result = proxy_logging._convert_llm_result_to_mcp_during_response( + llm_result="kill switch", request_obj=req + ) + assert isinstance(result, MCPDuringCallResponseObject) + snapshot = {"should_continue": result.should_continue, "error_message": result.error_message} + assert snapshot == {"should_continue": False, "error_message": "kill switch"} + + +def test_convert_llm_result_to_mcp_during_response_unmodified_returns_none(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(tool_name="t", arguments={"a": 1}) + same = "Tool: t\nArguments: {'a': 1}" + assert ( + proxy_logging._convert_llm_result_to_mcp_during_response( + llm_result={"messages": [{"content": same}]}, + request_obj=req, + ) + is None + ) + + +def test_convert_llm_result_to_mcp_during_response_no_request_obj_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._convert_llm_result_to_mcp_during_response( + llm_result={"messages": [{"content": "x"}]}, request_obj=None + ) + + +# --------------------------------------------------------------------------- +# _parse_pre_mcp_call_hook_response +# --------------------------------------------------------------------------- + + +def test_parse_pre_mcp_call_hook_response_with_modified_args(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(arguments={"a": 1}) + resp = MCPPreCallResponseObject( + should_proceed=True, + modified_arguments={"a": "x", "b": "y"}, + error_message=None, + ) + out = proxy_logging._parse_pre_mcp_call_hook_response(response=resp, original_request=req) + snapshot = { + "should_proceed": out["should_proceed"], + "modified_arguments": out["modified_arguments"], + "error_message": out["error_message"], + "hidden_params_type": type(out["hidden_params"]).__name__, + } + assert snapshot == { + "should_proceed": True, + "modified_arguments": {"a": "x", "b": "y"}, + "error_message": None, + "hidden_params_type": "HiddenParams", + } + + +def test_parse_pre_mcp_call_hook_response_no_modifications_uses_original(proxy_logging, make_mcp_request_obj): + req = make_mcp_request_obj(arguments={"original": True}) + resp = MCPPreCallResponseObject( + should_proceed=True, modified_arguments=None, error_message=None + ) + out = proxy_logging._parse_pre_mcp_call_hook_response(response=resp, original_request=req) + assert out["modified_arguments"] == {"original": True} + + +def test_parse_pre_mcp_call_hook_response_invalid_response_raises(proxy_logging, make_mcp_request_obj): + with pytest.raises(AttributeError): + proxy_logging._parse_pre_mcp_call_hook_response( + response=None, original_request=make_mcp_request_obj() + ) + + +# --------------------------------------------------------------------------- +# _create_mcp_request_object_from_kwargs +# --------------------------------------------------------------------------- + + +def test_create_mcp_request_object_from_kwargs_full(proxy_logging, make_user_api_key_auth): + auth = make_user_api_key_auth(user_id="u-1") + obj = proxy_logging._create_mcp_request_object_from_kwargs( + kwargs={ + "name": "calc", + "arguments": {"x": 1}, + "server_name": "math", + "user_api_key_auth": auth, + } + ) + assert isinstance(obj, MCPPreCallRequestObject) + snapshot = { + "tool_name": obj.tool_name, + "arguments": obj.arguments, + "server_name": obj.server_name, + "auth_user_id": obj.user_api_key_auth.get("user_id"), + } + assert snapshot == {"tool_name": "calc", "arguments": {"x": 1}, "server_name": "math", "auth_user_id": "u-1"} + + +def test_create_mcp_request_object_from_kwargs_empty(proxy_logging): + obj = proxy_logging._create_mcp_request_object_from_kwargs(kwargs={}) + snapshot = { + "tool_name": obj.tool_name, + "arguments": obj.arguments, + "server_name": obj.server_name, + } + assert snapshot == {"tool_name": "", "arguments": {}, "server_name": None} + + +def test_create_mcp_request_object_from_kwargs_non_dict_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._create_mcp_request_object_from_kwargs(kwargs=None) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _convert_mcp_hook_response_to_kwargs +# --------------------------------------------------------------------------- + + +def test_convert_mcp_hook_response_to_kwargs_applies_modified_args(proxy_logging): + original = {"arguments": {"a": 1}, "name": "old"} + out = proxy_logging._convert_mcp_hook_response_to_kwargs( + response_data={"modified_arguments": {"a": 2}, "extra_headers": {"H": "1"}}, + original_kwargs=original, + ) + snapshot = { + "arguments": out["arguments"], + "extra_headers": out["extra_headers"], + "name": out["name"], + "original_unmodified": original["arguments"], + } + assert snapshot == { + "arguments": {"a": 2}, + "extra_headers": {"H": "1"}, + "name": "old", + "original_unmodified": {"a": 1}, + } + + +def test_convert_mcp_hook_response_to_kwargs_merges_headers(proxy_logging): + original = {"extra_headers": {"keep": "yes", "overwrite": "old"}} + out = proxy_logging._convert_mcp_hook_response_to_kwargs( + response_data={"extra_headers": {"overwrite": "new", "added": "1"}}, + original_kwargs=original, + ) + assert out["extra_headers"] == {"keep": "yes", "overwrite": "new", "added": "1"} + + +def test_convert_mcp_hook_response_to_kwargs_no_response_data_returns_original(proxy_logging): + original = {"a": 1} + out = proxy_logging._convert_mcp_hook_response_to_kwargs(response_data=None, original_kwargs=original) + assert out is original + + +def test_convert_mcp_hook_response_to_kwargs_invalid_original_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._convert_mcp_hook_response_to_kwargs( + response_data={"modified_arguments": {"a": 1}}, original_kwargs=None # type: ignore[arg-type] + ) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_module_helpers.py b/tests/test_litellm/proxy/utils/proxy_logging/test_module_helpers.py new file mode 100644 index 00000000000..c491f16f2e4 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_module_helpers.py @@ -0,0 +1,353 @@ +"""Pin behavior of top-of-file and bottom-of-region helpers. + +Covers ``print_verbose``, ``_get_email_logger_class``, +``_accepts_litellm_call_info``, ``_enrich_http_exception_with_guardrail_context``, +``on_backoff``, ``jsonify_object``, ``_lookup_deprecated_key``. +""" + +from __future__ import annotations + +from datetime import datetime, timedelta, timezone +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +import litellm +from litellm.proxy import utils as utils_mod +from litellm.proxy.utils import ( + _accepts_litellm_call_info, + _enrich_http_exception_with_guardrail_context, + _get_email_logger_class, + _lookup_deprecated_key, + jsonify_object, + on_backoff, + print_verbose, +) + + +# --------------------------------------------------------------------------- +# print_verbose +# --------------------------------------------------------------------------- + + +def test_print_verbose_when_set_verbose_true_prints_redacted(monkeypatch, capsys): + monkeypatch.setattr(litellm, "set_verbose", True) + print_verbose("hello world") + captured = capsys.readouterr() + snapshot = { + "out_has_prefix": "LiteLLM Proxy:" in captured.out, + "out_has_payload": "hello world" in captured.out, + "no_stderr": captured.err == "", + } + assert snapshot == {"out_has_prefix": True, "out_has_payload": True, "no_stderr": True} + + +def test_print_verbose_when_set_verbose_false_no_stdout(monkeypatch, capsys): + monkeypatch.setattr(litellm, "set_verbose", False) + print_verbose("quiet") + captured = capsys.readouterr() + assert captured.out == "" + + +def test_print_verbose_handles_unprintable_object_raises(monkeypatch): + monkeypatch.setattr(litellm, "set_verbose", True) + + class Bomb: + def __str__(self): + raise RuntimeError("bad str") + + with pytest.raises(RuntimeError): + print_verbose(Bomb()) + + +# --------------------------------------------------------------------------- +# _get_email_logger_class +# --------------------------------------------------------------------------- + + +def test_get_email_logger_class_priority_matrix(monkeypatch): + """Truth table for ``_get_email_logger_class`` priority: SendGrid > + Resend > SMTP > Base.""" + sg = object() + rs = object() + smtp = object() + base = object() + monkeypatch.setattr(utils_mod, "BaseEmailLogger", base) + monkeypatch.setattr(utils_mod, "SendGridEmailLogger", sg) + monkeypatch.setattr(utils_mod, "ResendEmailLogger", rs) + monkeypatch.setattr(utils_mod, "SMTPEmailLogger", smtp) + for k in ("SENDGRID_API_KEY", "RESEND_API_KEY", "SMTP_HOST"): + monkeypatch.delenv(k, raising=False) + + fallback = _get_email_logger_class() is base + monkeypatch.setenv("SMTP_HOST", "smtp.example") + smtp_choice = _get_email_logger_class() is smtp + monkeypatch.setenv("RESEND_API_KEY", "rs-x") + resend_choice = _get_email_logger_class() is rs + monkeypatch.setenv("SENDGRID_API_KEY", "sg-x") + sendgrid_choice = _get_email_logger_class() is sg + snapshot = { + "fallback_to_base": fallback, + "smtp_when_smtp_only": smtp_choice, + "resend_beats_smtp": resend_choice, + "sendgrid_wins": sendgrid_choice, + } + assert snapshot == { + "fallback_to_base": True, + "smtp_when_smtp_only": True, + "resend_beats_smtp": True, + "sendgrid_wins": True, + } + + +def test_get_email_logger_class_error_when_no_enterprise_module(monkeypatch): + monkeypatch.setattr(utils_mod, "BaseEmailLogger", None) + # Returns ``None`` rather than raising; this is the documented failure + # mode when the optional enterprise package is missing. + assert _get_email_logger_class() is None + # Sentinel: monkey-patch SendGrid env but keep BaseEmailLogger None; + # function still must return None and not blow up on the optional path. + monkeypatch.setenv("SENDGRID_API_KEY", "sg-x") + assert _get_email_logger_class() is None + + +# --------------------------------------------------------------------------- +# _accepts_litellm_call_info +# --------------------------------------------------------------------------- + + +class _CbAcceptsInfo: + async def async_post_call_response_headers_hook(self, *, litellm_call_info=None): + return None + + +class _CbRejectsInfo: + async def async_post_call_response_headers_hook(self, *, response): + return None + + +def test_accepts_litellm_call_info_matrix(monkeypatch): + monkeypatch.setattr(utils_mod, "_CALLBACK_ACCEPTS_CALL_INFO", {}) + cache = {id(_CbAcceptsInfo): True} + monkeypatch.setattr(utils_mod, "_CALLBACK_ACCEPTS_CALL_INFO", cache) + snapshot = { + "cache_hit_returns_true": _accepts_litellm_call_info(_CbAcceptsInfo()), + "cache_size_after_hit": len(cache), + "cache_keyed_by_type_id": id(_CbAcceptsInfo) in cache, + } + assert snapshot == { + "cache_hit_returns_true": True, + "cache_size_after_hit": 1, + "cache_keyed_by_type_id": True, + } + + +def test_accepts_litellm_call_info_signature_inspection(monkeypatch): + monkeypatch.setattr(utils_mod, "_CALLBACK_ACCEPTS_CALL_INFO", {}) + snapshot = { + "accepts_param_true": _accepts_litellm_call_info(_CbAcceptsInfo()), + "rejects_param_false": _accepts_litellm_call_info(_CbRejectsInfo()), + "cache_populated": len(utils_mod._CALLBACK_ACCEPTS_CALL_INFO) == 2, + } + assert snapshot == { + "accepts_param_true": True, + "rejects_param_false": False, + "cache_populated": True, + } + + +def test_accepts_litellm_call_info_error_on_callback_without_hook_raises(monkeypatch): + monkeypatch.setattr(utils_mod, "_CALLBACK_ACCEPTS_CALL_INFO", {}) + + class _Bad: + pass + + with pytest.raises(AttributeError): + _accepts_litellm_call_info(_Bad()) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _enrich_http_exception_with_guardrail_context +# --------------------------------------------------------------------------- + + +def test_enrich_http_exception_adds_guardrail_name_and_mode(): + detail = {"error": "blocked"} + exc = HTTPException(status_code=400, detail=detail) + cb = MagicMock() + cb.guardrail_name = "presidio" + cb.event_hook = "pre_call" + + _enrich_http_exception_with_guardrail_context(exc, cb) + snapshot = { + "error": detail["error"], + "guardrail_name": detail["guardrail_name"], + "guardrail_mode": detail["guardrail_mode"], + } + assert snapshot == { + "error": "blocked", + "guardrail_name": "presidio", + "guardrail_mode": "pre_call", + } + + +def test_enrich_http_exception_does_not_overwrite_existing_keys(): + detail = {"error": "blocked", "guardrail_name": "explicit", "guardrail_mode": "during_call"} + exc = HTTPException(status_code=400, detail=detail) + cb = MagicMock() + cb.guardrail_name = "should-not-overwrite" + cb.event_hook = "should-not-overwrite" + _enrich_http_exception_with_guardrail_context(exc, cb) + assert detail == {"error": "blocked", "guardrail_name": "explicit", "guardrail_mode": "during_call"} + + +def test_enrich_http_exception_no_op_for_non_http_exception(): + other = ValueError("not http") + _enrich_http_exception_with_guardrail_context(other, MagicMock(guardrail_name="g")) + + +def test_enrich_http_exception_no_op_for_non_dict_detail(): + exc = HTTPException(status_code=400, detail="just a string") + _enrich_http_exception_with_guardrail_context(exc, MagicMock(guardrail_name="g")) + assert exc.detail == "just a string" + + +def test_enrich_http_exception_error_handling_does_not_raise(): + """``_enrich_http_exception_with_guardrail_context`` swallows mismatched + inputs (non-HTTPException, non-dict detail, no guardrail_name) and never + raises — verified by passing each pathological input in turn.""" + # Bare exception with no detail at all should not blow up. + bare = Exception("bare") + _enrich_http_exception_with_guardrail_context(bare, MagicMock(guardrail_name=None)) + # HTTPException with non-dict detail. + s = HTTPException(status_code=500, detail="str-detail") + _enrich_http_exception_with_guardrail_context(s, MagicMock(guardrail_name="g")) + assert s.detail == "str-detail" + + +def test_enrich_http_exception_with_falsy_attrs_does_not_set(): + detail = {"error": "blocked"} + exc = HTTPException(status_code=400, detail=detail) + cb = MagicMock() + cb.guardrail_name = None + cb.event_hook = None + _enrich_http_exception_with_guardrail_context(exc, cb) + assert detail == {"error": "blocked"} + + +# --------------------------------------------------------------------------- +# on_backoff +# --------------------------------------------------------------------------- + + +def test_on_backoff_invokes_print_verbose(monkeypatch): + captured = [] + monkeypatch.setattr(utils_mod, "print_verbose", lambda s: captured.append(s)) + on_backoff({"tries": 3}) + snapshot = {"len": len(captured), "first_has_attempt": "attempt" in captured[0], "first_has_3": "3" in captured[0]} + assert snapshot == {"len": 1, "first_has_attempt": True, "first_has_3": True} + + +def test_on_backoff_missing_tries_key_raises(): + with pytest.raises(KeyError): + on_backoff({}) + + +# --------------------------------------------------------------------------- +# jsonify_object +# --------------------------------------------------------------------------- + + +def test_jsonify_object_serializes_nested_dicts(): + src = {"plain": "x", "nested": {"a": 1, "b": 2}, "n": 42} + out = jsonify_object(src) + expected = {"plain": "x", "nested": '{"a": 1, "b": 2}', "n": 42} + assert out == expected + # Source is not mutated. + assert src == {"plain": "x", "nested": {"a": 1, "b": 2}, "n": 42} + + +def test_jsonify_object_failed_serialization_marks_value(monkeypatch): + class Unserialiseable: + pass + + src = {"name": "x", "bad": {"obj": Unserialiseable()}, "count": 1} + out = jsonify_object(src) + assert out == {"name": "x", "bad": "failed-to-serialize-json", "count": 1} + + +def test_jsonify_object_non_dict_input_raises(): + with pytest.raises(AttributeError): + jsonify_object("not a dict") # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _lookup_deprecated_key +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_lookup_deprecated_key_returns_active_token_id_and_caches(monkeypatch): + from litellm.caching.dual_cache import LimitedSizeOrderedDict + + fresh = LimitedSizeOrderedDict(max_size=1000) + monkeypatch.setattr(utils_mod, "_deprecated_key_cache", fresh) + + future = datetime.now(timezone.utc) + timedelta(hours=1) + deprecated_row = MagicMock() + deprecated_row.active_token_id = "active-123" + deprecated_row.revoke_at = future + + db = MagicMock() + db.litellm_deprecatedverificationtoken.find_first = AsyncMock(return_value=deprecated_row) + + result = await _lookup_deprecated_key(db=db, hashed_token="hash-abc") + cached_value = fresh.get("hash-abc") + snapshot = { + "result": result, + "cache_active_token_id": cached_value[0], + "cache_has_3_tuple": isinstance(cached_value, tuple) and len(cached_value) == 3, + } + assert snapshot == { + "result": "active-123", + "cache_active_token_id": "active-123", + "cache_has_3_tuple": True, + } + + +@pytest.mark.asyncio +async def test_lookup_deprecated_key_returns_none_when_not_found(monkeypatch): + from litellm.caching.dual_cache import LimitedSizeOrderedDict + + monkeypatch.setattr(utils_mod, "_deprecated_key_cache", LimitedSizeOrderedDict(max_size=10)) + db = MagicMock() + db.litellm_deprecatedverificationtoken.find_first = AsyncMock(return_value=None) + assert await _lookup_deprecated_key(db=db, hashed_token="missing") is None + + +@pytest.mark.asyncio +async def test_lookup_deprecated_key_db_error_returns_none(monkeypatch): + from litellm.caching.dual_cache import LimitedSizeOrderedDict + + monkeypatch.setattr(utils_mod, "_deprecated_key_cache", LimitedSizeOrderedDict(max_size=10)) + db = MagicMock() + db.litellm_deprecatedverificationtoken.find_first = AsyncMock(side_effect=RuntimeError("db down")) + result = await _lookup_deprecated_key(db=db, hashed_token="x") + assert result is None + + +@pytest.mark.asyncio +async def test_lookup_deprecated_key_uses_cache_within_ttl(monkeypatch): + from litellm.caching.dual_cache import LimitedSizeOrderedDict + + cache = LimitedSizeOrderedDict(max_size=10) + now_ts = datetime.now(timezone.utc).timestamp() + cache["hashY"] = ("active-from-cache", now_ts + 100, now_ts + 1000) + monkeypatch.setattr(utils_mod, "_deprecated_key_cache", cache) + + db = MagicMock() + db.litellm_deprecatedverificationtoken.find_first = AsyncMock(return_value=None) + result = await _lookup_deprecated_key(db=db, hashed_token="hashY") + assert result == "active-from-cache" + db.litellm_deprecatedverificationtoken.find_first.assert_not_called() diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py new file mode 100644 index 00000000000..a2a57931d26 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py @@ -0,0 +1,269 @@ +"""Pin ``ProxyLogging.post_call_failure_hook``, ``_is_proxy_only_llm_api_error``, +and ``_handle_logging_proxy_only_error``.""" + +from __future__ import annotations + +import asyncio +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +import litellm +from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy._types import AlertType, ProxyErrorTypes +from litellm.proxy.utils import ProxyLogging + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +# --------------------------------------------------------------------------- +# _is_proxy_only_llm_api_error +# --------------------------------------------------------------------------- + + +def test_is_proxy_only_llm_api_truth_table(proxy_logging): + """Pin the truth table of ``_is_proxy_only_llm_api_error`` in a single + snapshot. Covers no-route, non-LLM route, HTTPException on LLM route, + and auth-error short-circuit.""" + snapshot = { + "no_route": proxy_logging._is_proxy_only_llm_api_error( + original_exception=Exception(), route=None + ), + "non_llm_route": proxy_logging._is_proxy_only_llm_api_error( + original_exception=HTTPException(status_code=429, detail="rate"), + route="/random/path", + ), + "http_on_llm_route": proxy_logging._is_proxy_only_llm_api_error( + original_exception=HTTPException(status_code=429, detail="rate"), + route="/chat/completions", + ), + "auth_short_circuit": proxy_logging._is_proxy_only_llm_api_error( + original_exception=Exception("auth"), + error_type=ProxyErrorTypes.auth_error, + route="/chat/completions", + ), + } + assert snapshot == { + "no_route": False, + "non_llm_route": False, + "http_on_llm_route": True, + "auth_short_circuit": True, + } + + +def test_is_proxy_only_llm_api_missing_exception_raises(proxy_logging): + """Passing nothing should TypeError on the missing positional kwarg.""" + with pytest.raises(TypeError): + proxy_logging._is_proxy_only_llm_api_error() # type: ignore[call-arg] + + +# --------------------------------------------------------------------------- +# post_call_failure_hook +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_no_callbacks_returns_none( + proxy_logging, make_user_api_key_auth, mock_callbacks_disabled +): + proxy_logging.alert_types = [] + request_data = {"litellm_call_id": "abc", "model": "m", "messages": []} + out = await proxy_logging.post_call_failure_hook( + request_data=request_data, + original_exception=ValueError("oops"), + user_api_key_dict=make_user_api_key_auth(), + ) + snapshot = { + "out_is_none": out is None, + "litellm_logging_obj_popped": "litellm_logging_obj" not in request_data, + "call_id_preserved": request_data["litellm_call_id"] == "abc", + "first_api_call_start_time_present": "first_api_call_start_time" in request_data, + } + assert snapshot == { + "out_is_none": True, + "litellm_logging_obj_popped": True, + "call_id_preserved": True, + "first_api_call_start_time_present": False, + } + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_callback_returns_http_exception( + proxy_logging, make_user_api_key_auth, monkeypatch +): + transformed = HTTPException(status_code=418, detail="teapot") + + class _Cb(CustomLogger): + async def async_post_call_failure_hook(self, **kwargs): # type: ignore[override] + return transformed + + monkeypatch.setattr(litellm, "callbacks", [_Cb()]) + proxy_logging.alert_types = [] + out = await proxy_logging.post_call_failure_hook( + request_data={"litellm_call_id": "abc"}, + original_exception=ValueError("oops"), + user_api_key_dict=make_user_api_key_auth(), + ) + assert out is transformed + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_callback_raises_http_exception_first_wins( + proxy_logging, make_user_api_key_auth, monkeypatch +): + err = HTTPException(status_code=418, detail="raised teapot") + + class _Cb(CustomLogger): + async def async_post_call_failure_hook(self, **kwargs): # type: ignore[override] + raise err + + monkeypatch.setattr(litellm, "callbacks", [_Cb()]) + proxy_logging.alert_types = [] + out = await proxy_logging.post_call_failure_hook( + request_data={"litellm_call_id": "abc"}, + original_exception=ValueError("oops"), + user_api_key_dict=make_user_api_key_auth(), + ) + assert out is err + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_non_http_exception_in_callback_swallowed( + proxy_logging, make_user_api_key_auth, monkeypatch +): + class _Cb(CustomLogger): + async def async_post_call_failure_hook(self, **kwargs): # type: ignore[override] + raise RuntimeError("non-http inside cb") + + monkeypatch.setattr(litellm, "callbacks", [_Cb()]) + proxy_logging.alert_types = [] + out = await proxy_logging.post_call_failure_hook( + request_data={"litellm_call_id": "abc"}, + original_exception=ValueError("oops"), + user_api_key_dict=make_user_api_key_auth(), + ) + assert out is None + + +# --------------------------------------------------------------------------- +# _handle_logging_proxy_only_error +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_handle_logging_proxy_only_path_uses_existing_logging_obj( + proxy_logging, make_user_api_key_auth +): + logging_obj = MagicMock() + logging_obj.call_type = "acompletion" + logging_obj.model_call_details = {} + logging_obj.async_failure_handler = AsyncMock() + + request_data = { + "litellm_logging_obj": logging_obj, + "messages": [{"role": "user", "content": "x"}], + "model": "m", + "metadata": {}, + } + await proxy_logging._handle_logging_proxy_only_error( + request_data=request_data, + user_api_key_dict=make_user_api_key_auth(), + route="/chat/completions", + original_exception=HTTPException(status_code=429, detail="rate"), + ) + from litellm.constants import LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL + + snapshot = { + "input_logged": "messages" in logging_obj.model_call_details, + "call_type_normalized": logging_obj.call_type, + "marker_present": logging_obj.model_call_details.get( + LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL + ) + is True, + "async_failure_called": logging_obj.async_failure_handler.called, + } + assert snapshot == { + "input_logged": True, + "call_type_normalized": "acompletion", + "marker_present": True, + "async_failure_called": True, + } + + +@pytest.mark.asyncio +async def test_handle_logging_proxy_only_path_skips_for_pass_through( + proxy_logging, make_user_api_key_auth +): + from litellm.types.utils import CallTypes + + logging_obj = MagicMock() + logging_obj.call_type = CallTypes.pass_through.value + logging_obj.model_call_details = {} + logging_obj.async_failure_handler = AsyncMock() + logging_obj.pre_call = MagicMock() + request_data = { + "litellm_logging_obj": logging_obj, + "messages": [{"role": "user"}], + "model": "m", + } + await proxy_logging._handle_logging_proxy_only_error( + request_data=request_data, + user_api_key_dict=make_user_api_key_auth(), + route="/chat/completions", + original_exception=HTTPException(status_code=429, detail="rate"), + ) + logging_obj.pre_call.assert_not_called() + logging_obj.async_failure_handler.assert_not_called() + + +@pytest.mark.asyncio +async def test_handle_logging_proxy_only_path_no_logging_obj_creates_one( + proxy_logging, make_user_api_key_auth, monkeypatch +): + fake_logging_obj = MagicMock() + fake_logging_obj.call_type = "acompletion" + fake_logging_obj.model_call_details = {} + fake_logging_obj.async_failure_handler = AsyncMock() + + def fake_function_setup(**kwargs): + return fake_logging_obj, {} + + monkeypatch.setattr(litellm.utils, "function_setup", fake_function_setup) + request_data = {"messages": [{"role": "user"}], "model": "m"} + await proxy_logging._handle_logging_proxy_only_error( + request_data=request_data, + user_api_key_dict=make_user_api_key_auth(), + route="/chat/completions", + original_exception=HTTPException(status_code=429, detail="rate"), + ) + assert "litellm_call_id" in request_data + fake_logging_obj.async_failure_handler.assert_called_once() + + +@pytest.mark.asyncio +async def test_handle_logging_proxy_only_path_propagates_async_failure_raises( + proxy_logging, make_user_api_key_auth +): + logging_obj = MagicMock() + logging_obj.call_type = "acompletion" + logging_obj.model_call_details = {} + logging_obj.async_failure_handler = AsyncMock(side_effect=RuntimeError("boom")) + request_data = { + "litellm_logging_obj": logging_obj, + "messages": [{"role": "user"}], + "model": "m", + } + with pytest.raises(RuntimeError): + await proxy_logging._handle_logging_proxy_only_error( + request_data=request_data, + user_api_key_dict=make_user_api_key_auth(), + route="/chat/completions", + original_exception=Exception("x"), + ) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_success_hook.py b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_success_hook.py new file mode 100644 index 00000000000..6a339b37a80 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_success_hook.py @@ -0,0 +1,97 @@ +"""Pin ``ProxyLogging.post_call_success_hook``.""" + +from __future__ import annotations + +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +import litellm +from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy.utils import ProxyLogging +from litellm.types.guardrails import GuardrailEventHooks + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +def _make_guardrail(name="g", should_run=True, override=None): + cb = MagicMock(spec=CustomGuardrail) + cb.__class__ = CustomGuardrail + cb.guardrail_name = name + cb.event_hook = GuardrailEventHooks.post_call + cb.should_run_guardrail = MagicMock(return_value=should_run) + cb.async_post_call_success_hook = AsyncMock(return_value=override) + return cb + + +@pytest.mark.asyncio +async def test_post_call_success_hook_returns_response_when_no_callbacks(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + response = {"original": True, "model": "m", "choices": []} + out = await proxy_logging.post_call_success_hook( + data={}, response=response, user_api_key_dict=make_user_api_key_auth() + ) + assert out == {"original": True, "model": "m", "choices": []} + + +@pytest.mark.asyncio +async def test_post_call_success_hook_runs_other_callback_and_replaces_response( + proxy_logging, make_user_api_key_auth, monkeypatch +): + new_response = {"modified": True, "kept": "yes", "final": "v"} + + class _CL(CustomLogger): + async def async_post_call_success_hook(self, **kwargs): # type: ignore[override] + return new_response + + monkeypatch.setattr(litellm, "callbacks", [_CL()]) + out = await proxy_logging.post_call_success_hook( + data={}, response={"original": True}, user_api_key_dict=make_user_api_key_auth() + ) + assert out == new_response + + +@pytest.mark.asyncio +async def test_post_call_success_hook_guardrail_should_not_run_skipped( + proxy_logging, make_user_api_key_auth, monkeypatch +): + g = _make_guardrail(should_run=False) + monkeypatch.setattr(litellm, "callbacks", [g]) + response = MagicMock() + out = await proxy_logging.post_call_success_hook( + data={}, response=response, user_api_key_dict=make_user_api_key_auth() + ) + g.async_post_call_success_hook.assert_not_called() + assert out is response + + +@pytest.mark.asyncio +async def test_post_call_success_hook_guardrail_error_raises( + proxy_logging, make_user_api_key_auth, monkeypatch +): + g = _make_guardrail() + g.async_post_call_success_hook = AsyncMock(side_effect=RuntimeError("blocked")) + monkeypatch.setattr(litellm, "callbacks", [g]) + with pytest.raises(RuntimeError): + await proxy_logging.post_call_success_hook( + data={}, response=MagicMock(), user_api_key_dict=make_user_api_key_auth() + ) + + +@pytest.mark.asyncio +async def test_post_call_success_hook_guardrail_returns_modified_response( + proxy_logging, make_user_api_key_auth, monkeypatch +): + modified = {"a": 1, "b": 2, "c": 3} + g = _make_guardrail(override=modified) + monkeypatch.setattr(litellm, "callbacks", [g]) + out = await proxy_logging.post_call_success_hook( + data={}, response={"orig": True}, user_api_key_dict=make_user_api_key_auth() + ) + assert out == modified diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_pre_call_hook.py b/tests/test_litellm/proxy/utils/proxy_logging/test_pre_call_hook.py new file mode 100644 index 00000000000..05005dae797 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_pre_call_hook.py @@ -0,0 +1,168 @@ +"""Pin ``ProxyLogging.pre_call_hook`` and ``process_pre_call_hook_response``.""" + +from __future__ import annotations + +from typing import Any, Dict +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +import litellm +from litellm.exceptions import RejectedRequestError +from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy.utils import ProxyLogging + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +# --------------------------------------------------------------------------- +# process_pre_call_hook_response +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_process_pre_call_hook_response_dict_returns_response(proxy_logging): + out = await proxy_logging.process_pre_call_hook_response( + response={"messages": [{"x": 1}], "model": "m", "temperature": 0.5}, + data={"original": True}, + call_type="completion", + ) + assert out == {"messages": [{"x": 1}], "model": "m", "temperature": 0.5} + + +@pytest.mark.asyncio +async def test_process_pre_call_hook_response_string_completion_raises_rejected(proxy_logging): + with pytest.raises(RejectedRequestError): + await proxy_logging.process_pre_call_hook_response( + response="rejected", + data={"model": "m"}, + call_type="completion", + ) + + +@pytest.mark.asyncio +async def test_process_pre_call_hook_response_string_other_call_type_raises_http(proxy_logging): + with pytest.raises(HTTPException) as info: + await proxy_logging.process_pre_call_hook_response( + response="bad", + data={}, + call_type="embeddings", + ) + assert info.value.status_code == 400 + + +@pytest.mark.asyncio +async def test_process_pre_call_hook_response_exception_reraises(proxy_logging): + err = RuntimeError("hook said no") + with pytest.raises(RuntimeError, match="hook said no"): + await proxy_logging.process_pre_call_hook_response( + response=err, data={}, call_type="completion" + ) + + +@pytest.mark.asyncio +async def test_process_pre_call_hook_response_other_type_returns_data(proxy_logging): + out = await proxy_logging.process_pre_call_hook_response( + response=12345, data={"a": 1, "b": 2, "c": 3}, call_type="completion" + ) + assert out == {"a": 1, "b": 2, "c": 3} + + +# --------------------------------------------------------------------------- +# pre_call_hook +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_pre_call_hook_returns_data_when_no_callbacks(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + data = {"messages": [{"role": "user", "content": "hi"}], "model": "m", "temperature": 0.7} + proxy_logging.slack_alerting_instance = MagicMock(alerting=None) + out = await proxy_logging.pre_call_hook( + user_api_key_dict=make_user_api_key_auth(), + data=data, + call_type="completion", + ) + assert out is data + + +@pytest.mark.asyncio +async def test_pre_call_hook_returns_none_for_none_data(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + proxy_logging.slack_alerting_instance = MagicMock(alerting=None) + out = await proxy_logging.pre_call_hook( + user_api_key_dict=make_user_api_key_auth(), + data=None, + call_type="completion", + ) + assert out is None + + +@pytest.mark.asyncio +async def test_pre_call_hook_invokes_pre_call_override(proxy_logging, make_user_api_key_auth, monkeypatch): + captured: Dict[str, Any] = {} + + class _Cb(CustomLogger): + async def async_pre_call_hook(self, **kwargs): # type: ignore[override] + captured.update(kwargs) + return {"messages": [{"x": "modified"}], "model": "m", "temperature": 0.1} + + monkeypatch.setattr(litellm, "callbacks", [_Cb()]) + proxy_logging.slack_alerting_instance = MagicMock(alerting=None) + out = await proxy_logging.pre_call_hook( + user_api_key_dict=make_user_api_key_auth(), + data={"messages": [{"x": "input"}], "model": "m", "temperature": 0.1}, + call_type="completion", + ) + snapshot = { + "out_messages": out["messages"], + "out_model": out["model"], + "out_temp": out["temperature"], + "cb_received_call_type": captured.get("call_type"), + } + assert snapshot == { + "out_messages": [{"x": "modified"}], + "out_model": "m", + "out_temp": 0.1, + "cb_received_call_type": "completion", + } + + +@pytest.mark.asyncio +async def test_pre_call_hook_propagates_callback_error_raises(proxy_logging, make_user_api_key_auth, monkeypatch): + class _BadCb(CustomLogger): + async def async_pre_call_hook(self, **kwargs): # type: ignore[override] + raise RuntimeError("rejected") + + monkeypatch.setattr(litellm, "callbacks", [_BadCb()]) + proxy_logging.slack_alerting_instance = MagicMock(alerting=None) + with pytest.raises(RuntimeError, match="rejected"): + await proxy_logging.pre_call_hook( + user_api_key_dict=make_user_api_key_auth(), + data={"model": "m"}, + call_type="completion", + ) + + +@pytest.mark.asyncio +async def test_pre_call_hook_processes_guardrail_metadata_when_no_overrides(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + """Even when no callback overrides exist, ``_process_guardrail_metadata`` runs.""" + data = {"messages": [{"role": "user"}], "model": "m", "metadata": {"guardrails": ["g1"]}} + proxy_logging.slack_alerting_instance = MagicMock(alerting=None) + invoked = {} + + def fake_process(d): + invoked["data"] = d + + proxy_logging._process_guardrail_metadata = fake_process # type: ignore[assignment] + out = await proxy_logging.pre_call_hook( + user_api_key_dict=make_user_api_key_auth(), + data=data, + call_type="completion", + ) + assert out is data + assert invoked["data"] is data diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_streaming_hooks.py b/tests/test_litellm/proxy/utils/proxy_logging/test_streaming_hooks.py new file mode 100644 index 00000000000..65d3c3c8079 --- /dev/null +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_streaming_hooks.py @@ -0,0 +1,432 @@ +"""Pin ProxyLogging streaming + response-headers helpers. + +Covers ``_wrap_streaming_iterator_with_enrichment``, +``async_post_call_streaming_hook``, +``async_post_call_streaming_iterator_hook``, ``_fire_deferred_stream_logging``, +``is_a2a_streaming_response``, ``_init_response_taking_too_long_task``, +``post_call_response_headers_hook``, ``_build_litellm_call_info``. +""" + +from __future__ import annotations + +import asyncio +from typing import Any, Dict, List +from unittest.mock import AsyncMock, MagicMock + +import pytest +from fastapi import HTTPException + +import litellm +from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy.utils import ProxyLogging + + +@pytest.fixture(autouse=True) +def _clear_caps_cache(): + ProxyLogging._callback_capabilities_cache.clear() + yield + ProxyLogging._callback_capabilities_cache.clear() + + +# --------------------------------------------------------------------------- +# is_a2a_streaming_response +# --------------------------------------------------------------------------- + + +def test_is_a2a_streaming_response_truth_matrix(proxy_logging): + snapshot = { + "all_three_keys_present": proxy_logging.is_a2a_streaming_response( + {"jsonrpc": "2.0", "id": "1", "result": {"x": 1}, "extra": "y"} + ), + "missing_result": proxy_logging.is_a2a_streaming_response( + {"jsonrpc": "2.0", "id": "1"} + ), + "missing_jsonrpc": proxy_logging.is_a2a_streaming_response( + {"id": "1", "result": {}} + ), + "empty_dict": proxy_logging.is_a2a_streaming_response({}), + } + assert snapshot == { + "all_three_keys_present": True, + "missing_result": False, + "missing_jsonrpc": False, + "empty_dict": False, + } + + +def test_is_a2a_streaming_response_invalid_input_raises(proxy_logging): + with pytest.raises(TypeError): + proxy_logging.is_a2a_streaming_response(None) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _build_litellm_call_info +# --------------------------------------------------------------------------- + + +def test_build_litellm_call_info_pulls_from_hidden_params_and_metadata(proxy_logging): + response = MagicMock() + response._hidden_params = { + "custom_llm_provider": "openai", + "api_base": "https://api.openai.com", + "model_id": "model-1", + } + info = proxy_logging._build_litellm_call_info( + data={"metadata": {"model_info": {"name": "gpt-4o-mini"}}}, + response=response, + ) + assert info == { + "custom_llm_provider": "openai", + "model_info": {"name": "gpt-4o-mini"}, + "api_base": "https://api.openai.com", + "model_id": "model-1", + } + + +def test_build_litellm_call_info_fallbacks_to_litellm_metadata(proxy_logging): + response = MagicMock() + response._hidden_params = {"custom_llm_provider": "azure"} + info = proxy_logging._build_litellm_call_info( + data={"litellm_metadata": {"model_info": {"alias": "azure-gpt"}}}, + response=response, + ) + snapshot = { + "custom_llm_provider": info["custom_llm_provider"], + "model_info": info["model_info"], + "api_base": info["api_base"], + "model_id": info["model_id"], + } + assert snapshot == { + "custom_llm_provider": "azure", + "model_info": {"alias": "azure-gpt"}, + "api_base": None, + "model_id": None, + } + + +def test_build_litellm_call_info_invalid_data_raises(proxy_logging): + with pytest.raises(AttributeError): + proxy_logging._build_litellm_call_info(data=None, response=MagicMock()) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# _init_response_taking_too_long_task +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_init_response_taking_too_long_task_runs_when_alerting(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + proxy_logging.slack_alerting_instance.alerting = ["slack"] + captured: Dict[str, Any] = {} + + async def fake_resp_too_long(request_data): + captured["request_data"] = request_data + + proxy_logging.slack_alerting_instance.response_taking_too_long = fake_resp_too_long + payload = {"req": "y", "litellm_call_id": "c1", "model": "m"} + proxy_logging._init_response_taking_too_long_task(data=payload) + await asyncio.sleep(0) + snapshot = { + "received_payload": captured["request_data"], + "fired_once": len(captured) == 1, + "alerting_was_truthy": bool(proxy_logging.slack_alerting_instance.alerting), + } + assert snapshot == { + "received_payload": payload, + "fired_once": True, + "alerting_was_truthy": True, + } + + +@pytest.mark.asyncio +async def test_init_response_taking_too_long_task_no_op_when_alerting_off(proxy_logging): + proxy_logging.slack_alerting_instance = MagicMock() + proxy_logging.slack_alerting_instance.alerting = None + proxy_logging.slack_alerting_instance.response_taking_too_long = AsyncMock() + proxy_logging._init_response_taking_too_long_task(data=None) + await asyncio.sleep(0) + proxy_logging.slack_alerting_instance.response_taking_too_long.assert_not_called() + + +def test_init_response_taking_too_long_task_no_slack_instance_no_error_raises(proxy_logging): + proxy_logging.slack_alerting_instance = None + proxy_logging._init_response_taking_too_long_task(data=None) + + +# --------------------------------------------------------------------------- +# _wrap_streaming_iterator_with_enrichment +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_wrap_streaming_iterator_with_enrichment_passes_through_chunks(proxy_logging): + async def gen(): + for ch in ("a", "b", "c"): + yield ch + + cb = MagicMock(guardrail_name="g", event_hook="pre_call") + wrapped = proxy_logging._wrap_streaming_iterator_with_enrichment(callback=cb, gen=gen()) + out = [ch async for ch in wrapped] + snapshot = { + "chunks": out, + "count": len(out), + "first": out[0], + "last": out[-1], + } + assert snapshot == { + "chunks": ["a", "b", "c"], + "count": 3, + "first": "a", + "last": "c", + } + + +@pytest.mark.asyncio +async def test_wrap_streaming_iterator_with_enrichment_enriches_http_exception_raises(proxy_logging): + detail = {"error": "blocked"} + + async def boom_gen(): + if False: + yield # pragma: no cover + raise HTTPException(status_code=400, detail=detail) + + cb = MagicMock(guardrail_name="presidio", event_hook="post_call") + wrapped = proxy_logging._wrap_streaming_iterator_with_enrichment(callback=cb, gen=boom_gen()) + with pytest.raises(HTTPException): + async for _ in wrapped: + pass + assert detail["guardrail_name"] == "presidio" + assert detail["guardrail_mode"] == "post_call" + + +# --------------------------------------------------------------------------- +# async_post_call_streaming_hook +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_async_post_call_streaming_hook_fast_path_returns_response(proxy_logging, mock_callbacks_disabled, make_user_api_key_auth): + resp = "chunk-1" + out = await proxy_logging.async_post_call_streaming_hook( + data={}, response=resp, user_api_key_dict=make_user_api_key_auth() + ) + snapshot = { + "out_is_input": out is resp, + "out_value": out, + "type": type(out).__name__, + "callbacks_empty": len(litellm.callbacks) == 0, + } + assert snapshot == { + "out_is_input": True, + "out_value": "chunk-1", + "type": "str", + "callbacks_empty": True, + } + + +@pytest.mark.asyncio +async def test_async_post_call_streaming_hook_invokes_per_chunk_callback(proxy_logging, make_user_api_key_auth, monkeypatch): + class _Per(CustomLogger): + async def async_post_call_streaming_hook(self, **kwargs): # type: ignore[override] + return "modified-" + str(kwargs.get("response", "")) + + cb = _Per() + monkeypatch.setattr(litellm, "callbacks", [cb]) + + from litellm import ModelResponse + + fake_resp = ModelResponse( + id="rid", + choices=[{"index": 0, "delta": {"role": "assistant", "content": "hi"}, "finish_reason": None}], + created=0, + model="gpt-4o-mini", + object="chat.completion.chunk", + ) + out = await proxy_logging.async_post_call_streaming_hook( + data={}, + response=fake_resp, + user_api_key_dict=make_user_api_key_auth(), + ) + assert isinstance(out, str) + assert out.startswith("modified-") + + +@pytest.mark.asyncio +async def test_async_post_call_streaming_hook_callback_error_raises(proxy_logging, make_user_api_key_auth, monkeypatch): + class _Per(CustomLogger): + async def async_post_call_streaming_hook(self, **kwargs): # type: ignore[override] + raise RuntimeError("hook-fail") + + monkeypatch.setattr(litellm, "callbacks", [_Per()]) + + from litellm import ModelResponse + + fake_resp = ModelResponse( + id="rid", + choices=[{"index": 0, "delta": {"role": "assistant", "content": "hi"}, "finish_reason": None}], + created=0, + model="gpt-4o-mini", + object="chat.completion.chunk", + ) + with pytest.raises(RuntimeError): + await proxy_logging.async_post_call_streaming_hook( + data={}, + response=fake_resp, + user_api_key_dict=make_user_api_key_auth(), + ) + + +# --------------------------------------------------------------------------- +# async_post_call_streaming_iterator_hook +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_async_post_call_streaming_iterator_hook_no_overrides_passes_through(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + async def gen(): + for ch in ("a", "b"): + yield ch + + chunks = [] + async for ch in proxy_logging.async_post_call_streaming_iterator_hook( + response=gen(), + user_api_key_dict=make_user_api_key_auth(), + request_data={}, + ): + chunks.append(ch) + snapshot = { + "chunks": chunks, + "count": len(chunks), + "passthrough_preserved_order": chunks == ["a", "b"], + } + assert snapshot == { + "chunks": ["a", "b"], + "count": 2, + "passthrough_preserved_order": True, + } + + +@pytest.mark.asyncio +async def test_async_post_call_streaming_iterator_hook_with_override_chains_callback(proxy_logging, make_user_api_key_auth, monkeypatch): + class _IterOverride(CustomLogger): + async def async_post_call_streaming_iterator_hook(self, **kwargs): # type: ignore[override] + async for ch in kwargs["response"]: + yield ch + "*" + + monkeypatch.setattr(litellm, "callbacks", [_IterOverride()]) + + async def gen(): + for ch in ("a", "b"): + yield ch + + out: List[str] = [] + async for ch in proxy_logging.async_post_call_streaming_iterator_hook( + response=gen(), + user_api_key_dict=make_user_api_key_auth(), + request_data={}, + ): + out.append(ch) + assert out == ["a*", "b*"] + + +@pytest.mark.asyncio +async def test_async_post_call_streaming_iterator_hook_upstream_error_raises(proxy_logging, make_user_api_key_auth, mock_callbacks_disabled): + async def gen(): + if False: + yield # pragma: no cover + raise RuntimeError("upstream") + + with pytest.raises(RuntimeError): + async for _ in proxy_logging.async_post_call_streaming_iterator_hook( + response=gen(), + user_api_key_dict=make_user_api_key_auth(), + request_data={}, + ): + pass + + +# --------------------------------------------------------------------------- +# _fire_deferred_stream_logging +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_fire_deferred_stream_logging_fires_callback(): + logging_obj = MagicMock() + captured: Dict[str, Any] = {} + + async def deferred(arg): + captured["arg"] = arg + + logging_obj._on_deferred_stream_complete = deferred + logging_obj._deferred_stream_complete_args = ("payload",) + + ProxyLogging._fire_deferred_stream_logging(request_data={"litellm_logging_obj": logging_obj}) + await asyncio.sleep(0) + snapshot = { + "arg": captured["arg"], + "callback_cleared": logging_obj._on_deferred_stream_complete is None, + "args_cleared": logging_obj._deferred_stream_complete_args is None, + } + assert snapshot == {"arg": "payload", "callback_cleared": True, "args_cleared": True} + + +def test_fire_deferred_stream_logging_no_logging_obj_no_error(): + ProxyLogging._fire_deferred_stream_logging(request_data={}) + + +def test_fire_deferred_stream_logging_missing_obj_raises_on_invalid_dict(): + with pytest.raises(AttributeError): + ProxyLogging._fire_deferred_stream_logging(request_data=None) # type: ignore[arg-type] + + +# --------------------------------------------------------------------------- +# post_call_response_headers_hook +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_post_call_response_headers_hook_returns_empty_when_no_callbacks( + proxy_logging, mock_callbacks_disabled, make_user_api_key_auth +): + out = await proxy_logging.post_call_response_headers_hook( + data={}, user_api_key_dict=make_user_api_key_auth(), response=MagicMock(_hidden_params={}) + ) + assert out == {} + + +@pytest.mark.asyncio +async def test_post_call_response_headers_hook_merges_callback_headers(proxy_logging, make_user_api_key_auth, monkeypatch): + class _Cb(CustomLogger): + async def async_post_call_response_headers_hook(self, **kwargs): # type: ignore[override] + return {"X-One": "1", "X-Two": "2", "X-Common": "first"} + + class _Cb2(CustomLogger): + async def async_post_call_response_headers_hook(self, **kwargs): # type: ignore[override] + return {"X-Common": "second", "X-Three": "3"} + + monkeypatch.setattr(litellm, "callbacks", [_Cb(), _Cb2()]) + response = MagicMock() + response._hidden_params = {} + out = await proxy_logging.post_call_response_headers_hook( + data={}, user_api_key_dict=make_user_api_key_auth(), response=response + ) + assert out == {"X-One": "1", "X-Two": "2", "X-Common": "second", "X-Three": "3"} + + +@pytest.mark.asyncio +async def test_post_call_response_headers_hook_swallows_callback_error(proxy_logging, make_user_api_key_auth, monkeypatch): + """Errors inside the hook are caught — function returns merged so-far.""" + + class _Cb(CustomLogger): + async def async_post_call_response_headers_hook(self, **kwargs): # type: ignore[override] + raise RuntimeError("bad header") + + monkeypatch.setattr(litellm, "callbacks", [_Cb()]) + response = MagicMock() + response._hidden_params = {} + out = await proxy_logging.post_call_response_headers_hook( + data={}, user_api_key_dict=make_user_api_key_auth(), response=response + ) + assert out == {} From 08223e1ec3a7ff2356fcf2f5b3a39868f2eb37ca Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 2 Jun 2026 18:25:15 -0700 Subject: [PATCH 04/92] fix: missing span for guardrail passthrough (#29552) --- litellm/_service_logger.py | 2 + litellm/integrations/custom_guardrail.py | 10 ++ litellm/integrations/opentelemetry.py | 4 + litellm/integrations/otel/logger.py | 80 ++++++------- litellm/integrations/otel/model/metadata.py | 20 ---- .../integrations/otel/test_otel_v2_logger.py | 108 ++++++++++++------ .../integrations/test_custom_guardrail.py | 59 ++++++++++ .../integrations/test_opentelemetry.py | 25 ++++ ...t_passthrough_guardrail_block_otel_span.py | 16 +-- tests/test_litellm/test_service_logger.py | 27 +++++ 10 files changed, 250 insertions(+), 101 deletions(-) diff --git a/litellm/_service_logger.py b/litellm/_service_logger.py index 5531c418799..b290b4340e7 100644 --- a/litellm/_service_logger.py +++ b/litellm/_service_logger.py @@ -371,6 +371,8 @@ class ServiceLogging(CustomLogger): service=ServiceTypes.LITELLM, duration=_duration, call_type=kwargs.get("call_type", "unknown"), + start_time=start_time, + end_time=end_time, ) except Exception as e: raise e diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py index 82a35f2eedd..6d0d73e033d 100644 --- a/litellm/integrations/custom_guardrail.py +++ b/litellm/integrations/custom_guardrail.py @@ -662,6 +662,16 @@ class CustomGuardrail(CustomLogger): request_data["metadata"] = {} _append_guardrail_info(request_data["metadata"]) + # Emit the otel guardrail span here, where every guardrail execution lands, + # rather than relying on a post-call hook that does not fire on every path + # (e.g. a pass-through request that passes its guardrails). + try: + from litellm.integrations.otel.logger import emit_guardrail_span + + emit_guardrail_span(slg) + except Exception: + pass + async def apply_guardrail( self, inputs: GenericGuardrailAPIInputs, diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index 8bc61d960e7..ce5cfa2f525 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -2668,6 +2668,10 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): ) def _to_ns(self, dt): + if dt is None: + return int(datetime.now().timestamp() * 1e9) + if isinstance(dt, (int, float)): + return int(dt * 1e9) return int(dt.timestamp() * 1e9) def _get_span_name(self, kwargs): diff --git a/litellm/integrations/otel/logger.py b/litellm/integrations/otel/logger.py index de5e7a7b8ab..57738c356f7 100644 --- a/litellm/integrations/otel/logger.py +++ b/litellm/integrations/otel/logger.py @@ -25,7 +25,6 @@ from litellm.integrations.otel.mappers import resolve_mappers from litellm.integrations.otel.model.metadata import ( LLMCallEvent, RequestIdentity, - guardrail_entries_from_request_data, model_from_request_data, ) from litellm.integrations.otel.model.payloads import ( @@ -468,46 +467,27 @@ class OpenTelemetryV2(CustomLogger): ) return data - async def async_post_call_success_hook( - self, - data: Mapping[str, Any], - user_api_key_dict: Any, - response: Any, - ) -> Any: - self._emit_guardrail_spans(data) - return response - - async def async_post_call_failure_hook( - self, - request_data: Mapping[str, Any], - original_exception: BaseException | None, - user_api_key_dict: Any, - traceback_str: str | None = None, - ) -> None: - self._emit_guardrail_spans(request_data) - - def _emit_guardrail_spans(self, request_data: Mapping[str, Any]) -> None: + def emit_guardrail_span(self, entry: "StandardLoggingGuardrailInformation") -> None: + # Emitted by the guardrail-recording code the moment a guardrail finishes, + # not from a post-call hook — that hook does not fire on every path (a + # pass-through request that passes its guardrails never reaches it), which + # left passing guardrails without a span. + # # A guardrail is a sibling of the LLM call under the request's root span, - # so parent it to the explicit anchor — not the active span, which on the - # failure path can be the live ``auth`` phase span (post-call failure hooks - # run from inside it on an auth rejection). Emit with the guardrail's actual - # execution window so a pre_call guardrail is placed before the LLM call - # rather than at post-call emission time. - guardrails = guardrail_entries_from_request_data(request_data) - if not guardrails: - return - parent_ctx = resolve_request_span_context() - for entry in guardrails: - data = GuardrailSpanData.from_logging_entry( - cast("StandardLoggingGuardrailInformation", entry) - ) - self._emitter.emit( - SpanRole.GUARDRAIL, - data, - parent_context=parent_ctx, - start_time_ns=to_ns(data.start_time), - end_time_ns=to_ns(data.end_time), - ) + # so parent it to the explicit anchor — never the active span, which during + # a pre_call guardrail can be the live ``auth`` phase span. Emit with the + # guardrail's actual execution window so a pre_call guardrail is placed + # before the LLM call rather than at emission time. One entry in, one span + # out — the module-level entry point routes each entry to this single + # registered logger so a guardrail is never emitted more than once. + data = GuardrailSpanData.from_logging_entry(entry) + self._emitter.emit( + SpanRole.GUARDRAIL, + data, + parent_context=resolve_request_span_context(), + start_time_ns=to_ns(data.start_time), + end_time_ns=to_ns(data.end_time), + ) def create_litellm_proxy_request_started_span( self, start_time: datetime, headers: Mapping[str, str] | None @@ -528,6 +508,26 @@ def _registered_v2_logger() -> "OpenTelemetryV2 | None": return logger if isinstance(logger, OpenTelemetryV2) else None +def emit_guardrail_span(entry: "StandardLoggingGuardrailInformation") -> None: + """Emit a guardrail span on the registered v2 OTel logger. + + Called by the guardrail-recording code the moment a guardrail finishes, so a + span is produced regardless of whether a post-call hook later runs (it does + not on the pass-through allow path). Routes through the single canonical + logger — the same one every other v2 entry point uses — so a guardrail + recorded once yields exactly one span; fanning out across every reachable + ``OpenTelemetryV2`` instance double-emits the same entry. Best-effort: span + emission must never break guardrail evaluation. + """ + logger = _registered_v2_logger() + if logger is None: + return + try: + logger.emit_guardrail_span(entry) + except Exception: + pass + + def seed_request_identity(user_api_key_dict: Any, model: Any = None) -> None: logger = _registered_v2_logger() if logger is not None: diff --git a/litellm/integrations/otel/model/metadata.py b/litellm/integrations/otel/model/metadata.py index 4663ed59761..4c9cecfef57 100644 --- a/litellm/integrations/otel/model/metadata.py +++ b/litellm/integrations/otel/model/metadata.py @@ -255,26 +255,6 @@ def model_from_request_data(data: object) -> str | None: return None -def guardrail_entries_from_request_data( - request_data: Mapping[str, Any], -) -> list[dict]: - """The guardrail-information dicts buried in ``metadata`` of a post-call dict. - - ``standard_logging_guardrail_information`` is stored as either a single dict - or a list of them; normalize to a list of dicts (dropping non-dict noise) so - the caller just iterates. Empty list when none are present. - """ - metadata = request_data.get("metadata") - if not isinstance(metadata, Mapping): - return [] - info = metadata.get("standard_logging_guardrail_information") - if isinstance(info, Mapping): - return [cast(dict, info)] - if isinstance(info, list): - return [entry for entry in info if isinstance(entry, dict)] - return [] - - def resolve_provider_model(payload: "StandardLoggingPayload") -> str | None: """The model litellm dispatched to the provider, from the payload. diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py index 971bb9340b2..9947ce9ac9e 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py @@ -541,17 +541,10 @@ def test_guardrail_span_anchors_to_root_inside_active_phase_span(): SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME ) set_request_root_span(server) - request_data = { - "metadata": { - "standard_logging_guardrail_information": { - "guardrail_name": "my_guard", - "guardrail_status": "success", - } - } - } + entry = {"guardrail_name": "my_guard", "guardrail_status": "success"} with trace.use_span(server, end_on_exit=False): with logger.start_phase_span("auth /chat/completions"): - logger._emit_guardrail_spans(request_data) + logger.emit_guardrail_span(entry) server.end() by_name = {s.name: s for s in exporter.get_finished_spans()} guard = by_name["execute_guardrail my_guard"] @@ -1188,37 +1181,29 @@ def test_boundary_span_closes_without_proxy_fanout(monkeypatch): # --------------------------------------------------------------------------- # -def _guardrail_request_data(*, start, end): +def _guardrail_entry(*, start, end): return { - "metadata": { - "standard_logging_guardrail_information": [ - { - "guardrail_name": "openai-moderation", - "guardrail_mode": "pre_call", - "guardrail_status": "success", - "start_time": start, - "end_time": end, - "duration": end - start, - } - ], - } + "guardrail_name": "openai-moderation", + "guardrail_mode": "pre_call", + "guardrail_status": "success", + "start_time": start, + "end_time": end, + "duration": end - start, } def test_guardrail_span_parents_to_ambient_server_span(): - """The post-call hook runs in the request task with the server span ambient, - so the guardrail span parents to it natively — no span threaded through - metadata. (Auth already finished, so no phase span is active.)""" + """``emit_guardrail_span`` runs in the request task with the server span + ambient, so with no explicit anchor set the guardrail span parents to it. + (Auth already finished, so no phase span is active.)""" logger, exporter = _logger() server = logger._emitter.start_span( SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME ) - data = _guardrail_request_data(start=1000.0, end=1000.5) + entry = _guardrail_entry(start=1000.0, end=1000.5) try: with trace.use_span(server, end_on_exit=False): - asyncio.run( - logger.async_post_call_success_hook(data, _Auth(), {"ok": True}) - ) + logger.emit_guardrail_span(entry) finally: server.end() g = {s.name: s for s in exporter.get_finished_spans()}[ @@ -1229,17 +1214,15 @@ def test_guardrail_span_parents_to_ambient_server_span(): def test_guardrail_span_uses_actual_execution_timestamps(): """A pre_call guardrail's span carries its real start/end (from the logging - entry), so it sorts before the LLM call instead of at post-call emit time.""" + entry), so it sorts before the LLM call instead of at emission time.""" logger, exporter = _logger() server = logger._emitter.start_span( SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME ) - data = _guardrail_request_data(start=1700.0, end=1700.25) + entry = _guardrail_entry(start=1700.0, end=1700.25) try: with trace.use_span(server, end_on_exit=False): - asyncio.run( - logger.async_post_call_success_hook(data, _Auth(), {"ok": True}) - ) + logger.emit_guardrail_span(entry) finally: server.end() g = {s.name: s for s in exporter.get_finished_spans()}[ @@ -1247,3 +1230,60 @@ def test_guardrail_span_uses_actual_execution_timestamps(): ] assert g.start_time == to_ns(1700.0) assert g.end_time == to_ns(1700.25) + + +def test_emit_guardrail_span_anchors_to_root_not_ambient_phase_span(): + """With an explicit request-root anchor set, the guardrail span parents to it + even while a phase span is the active OTel context — the anchor wins over + ambient, so a guardrail emitted mid-``auth`` is a sibling of the LLM call, not + a child of ``auth``.""" + logger, exporter = _logger() + server = logger._emitter.start_span( + SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME + ) + set_request_root_span(server) + entry = _guardrail_entry(start=2000.0, end=2000.1) + with logger.start_phase_span("auth /chat/completions"): + logger.emit_guardrail_span(entry) + server.end() + by_name = {s.name: s for s in exporter.get_finished_spans()} + guard = by_name["execute_guardrail openai-moderation"] + auth_span = by_name["auth /chat/completions"] + assert guard.parent.span_id == server.get_span_context().span_id + assert guard.parent.span_id != auth_span.get_span_context().span_id + + +def test_module_level_emit_guardrail_span_routes_to_registered_logger(monkeypatch): + """The module-level entry point custom_guardrail calls routes the entry to the + single registered v2 logger and emits exactly one span.""" + import litellm.integrations.otel.logger as otel_logger + + logger, exporter = _logger() + monkeypatch.setattr(otel_logger, "_registered_v2_logger", lambda: logger) + + otel_logger.emit_guardrail_span(_guardrail_entry(start=3000.0, end=3000.2)) + + names = [s.name for s in exporter.get_finished_spans()] + assert names.count("execute_guardrail openai-moderation") == 1 + + +def test_module_level_emit_guardrail_span_noop_without_registered_logger(monkeypatch): + """No registered v2 logger (SDK path / OTel not configured) → emitting is a + no-op rather than an error.""" + import litellm.integrations.otel.logger as otel_logger + + monkeypatch.setattr(otel_logger, "_registered_v2_logger", lambda: None) + otel_logger.emit_guardrail_span(_guardrail_entry(start=1.0, end=2.0)) + + +def test_module_level_emit_guardrail_span_swallows_emit_errors(monkeypatch): + """Span emission is best-effort: a logger that raises must never propagate out + of the guardrail-recording path and break guardrail evaluation.""" + import litellm.integrations.otel.logger as otel_logger + + class _Boom: + def emit_guardrail_span(self, entry): + raise RuntimeError("emit blew up") + + monkeypatch.setattr(otel_logger, "_registered_v2_logger", lambda: _Boom()) + otel_logger.emit_guardrail_span(_guardrail_entry(start=1.0, end=2.0)) diff --git a/tests/test_litellm/integrations/test_custom_guardrail.py b/tests/test_litellm/integrations/test_custom_guardrail.py index a881044dc18..4956fccb8db 100644 --- a/tests/test_litellm/integrations/test_custom_guardrail.py +++ b/tests/test_litellm/integrations/test_custom_guardrail.py @@ -500,6 +500,65 @@ class TestGuardrailLoggingAggregation: assert info[1]["guardrail_name"] == "test_guardrail" +class TestGuardrailOtelSpanEmission: + """Recording a guardrail emits its otel span inline, so every guardrail + execution produces a span — including the pass-through allow path that never + reaches a post-call hook.""" + + def _make_guardrail(self): + from litellm.types.guardrails import GuardrailEventHooks + + return CustomGuardrail( + guardrail_name="emit_guard", + event_hook=GuardrailEventHooks.pre_call, + ) + + def _record(self, guardrail, request_data): + guardrail.add_standard_logging_guardrail_information_to_request_data( + guardrail_json_response={"result": "ok"}, + request_data=request_data, + guardrail_status="success", + start_time=1.0, + end_time=2.0, + duration=1.0, + ) + + def test_emits_span_for_recorded_entry(self, monkeypatch): + captured = [] + monkeypatch.setattr( + "litellm.integrations.otel.logger.emit_guardrail_span", + captured.append, + ) + + request_data = {"metadata": {}} + self._record(self._make_guardrail(), request_data) + + assert len(captured) == 1 + emitted = captured[0] + recorded = request_data["metadata"]["standard_logging_guardrail_information"][ + -1 + ] + assert emitted is recorded + assert emitted["guardrail_name"] == "emit_guard" + assert emitted["start_time"] == 1.0 + assert emitted["end_time"] == 2.0 + + def test_span_emission_failure_does_not_break_recording(self, monkeypatch): + def _boom(_entry): + raise RuntimeError("otel exporter down") + + monkeypatch.setattr( + "litellm.integrations.otel.logger.emit_guardrail_span", _boom + ) + + request_data = {"metadata": {}} + self._record(self._make_guardrail(), request_data) + + info = request_data["metadata"]["standard_logging_guardrail_information"] + assert len(info) == 1 + assert info[0]["guardrail_name"] == "emit_guard" + + class TestGuardrailSensitiveFieldStripping: """Tests that secret_fields is stripped from guardrail responses before logging. diff --git a/tests/test_litellm/integrations/test_opentelemetry.py b/tests/test_litellm/integrations/test_opentelemetry.py index c4500bd6135..f6dee9b64c9 100644 --- a/tests/test_litellm/integrations/test_opentelemetry.py +++ b/tests/test_litellm/integrations/test_opentelemetry.py @@ -1761,6 +1761,31 @@ class TestOpenTelemetry(unittest.TestCase): mock_tracer.start_span.assert_not_called() +class TestOpenTelemetryToNs(unittest.TestCase): + """``_to_ns`` converts a span boundary to epoch nanoseconds. Service spans now + feed it real float/datetime windows, and a missing boundary arrives as + ``None`` — all three shapes must convert without raising the ``AttributeError`` + a bare ``dt.timestamp()`` would on a float or ``None``.""" + + def setUp(self): + self.otel = OpenTelemetry() + + def test_datetime_converts_to_epoch_ns(self): + dt = datetime(2026, 5, 26, 12, 0, 0, tzinfo=timezone.utc) + self.assertEqual(self.otel._to_ns(dt), int(dt.timestamp() * 1e9)) + + def test_float_epoch_seconds_scaled_to_ns(self): + self.assertEqual(self.otel._to_ns(1700.5), 1_700_500_000_000) + + def test_int_epoch_seconds_scaled_to_ns(self): + self.assertEqual(self.otel._to_ns(1700), 1_700_000_000_000) + + @patch("litellm.integrations.opentelemetry.datetime") + def test_none_falls_back_to_current_time(self, mock_datetime): + mock_datetime.now.return_value.timestamp.return_value = 1700.0 + self.assertEqual(self.otel._to_ns(None), 1_700_000_000_000) + + class TestOpenTelemetryHeaderSplitting(unittest.TestCase): """Test suite for _get_headers_dictionary method""" diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_passthrough_guardrail_block_otel_span.py b/tests/test_litellm/proxy/pass_through_endpoints/test_passthrough_guardrail_block_otel_span.py index 9009da88afa..73927e92c15 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_passthrough_guardrail_block_otel_span.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_passthrough_guardrail_block_otel_span.py @@ -1,13 +1,14 @@ """Regression: a guardrail block on a passthrough endpoint must still emit the otel guardrail span. -Before the fix the post-call guardrail recorded its -``standard_logging_guardrail_information`` onto a throwaway ``hook_data`` dict, -which the failure handler discarded. So ``pass_through_request`` forwarded a -``request_data`` without it to ``post_call_failure_hook`` and the otel guardrail -span (emitted from that hook) was present on allow but missing on block. The -unified path always has it. These tests drive the real ``pass_through_request`` -with a real ``ProxyLogging`` + a real otel V2 logger and assert the span is +The span is emitted from the guardrail-recording path the moment a guardrail +finishes (``add_standard_logging_guardrail_information_to_request_data`` -> +``emit_guardrail_span``), routed through the proxy's registered otel V2 logger, +rather than from a post-call hook that does not fire on every path. A block +raises out of the post-call hook before any later hook runs, so the recording +path is the only place the span is reliably produced. These tests drive the real +``pass_through_request`` with a real ``ProxyLogging`` + a real otel V2 logger +registered as the proxy's ``open_telemetry_logger`` and assert the span is emitted on both allow and block. """ @@ -141,6 +142,7 @@ async def _drive(response_text: str): ), patch(f"{_PT_MOD}._is_streaming_response", return_value=False), patch("litellm.proxy.proxy_server.proxy_logging_obj", proxy_logging), + patch("litellm.proxy.proxy_server.open_telemetry_logger", otel), patch("litellm.proxy.proxy_server.llm_router", None), patch(f"{_PT_MOD}.pass_through_endpoint_logging", mock_pt_logging), patch(f"{_PT_MOD}.get_async_httpx_client", return_value=mock_async_client_obj), diff --git a/tests/test_litellm/test_service_logger.py b/tests/test_litellm/test_service_logger.py index 34fe73382b3..de46403b64d 100644 --- a/tests/test_litellm/test_service_logger.py +++ b/tests/test_litellm/test_service_logger.py @@ -99,6 +99,33 @@ async def test_async_log_success_event_should_handle_float_duration(): assert call_kwargs.kwargs["duration"] == 1.5 +@pytest.mark.asyncio +async def test_async_log_success_event_forwards_start_and_end_time(): + """The LITELLM service span must carry its real execution window, so + ``async_log_success_event`` forwards ``start_time``/``end_time`` to the service + hook. Without forwarding, the span emits with a synthetic now() boundary + instead of the call's actual timing.""" + service_logger = ServiceLogging(mock_testing=True) + + start_time = datetime(2026, 2, 13, 22, 35, 0) + end_time = datetime(2026, 2, 13, 22, 35, 1) + + with patch.object( + service_logger, "async_service_success_hook", new_callable=AsyncMock + ) as mock_hook: + await service_logger.async_log_success_event( + kwargs={"call_type": "completion"}, + response_obj=None, + start_time=start_time, + end_time=end_time, + ) + + mock_hook.assert_called_once() + forwarded = mock_hook.call_args.kwargs + assert forwarded["start_time"] == start_time + assert forwarded["end_time"] == end_time + + # --------------------------------------------------------------------------- # # V2 OpenTelemetry service-span dispatch (regression: service spans were always # dropped because the dispatch only recognized the legacy OpenTelemetry class). From 0a767ed14f4bb1dc85230644a19a1d2709040875 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 2 Jun 2026 18:36:14 -0700 Subject: [PATCH 05/92] fix(auth): let internal users view search tools (#29542) * fix(auth): let internal users view search tools Internal users could not see search tools in the UI even when an admin created them, while vector stores were visible. The Search Tools page rendered but its list calls 403'd because the read routes were not in internal_user_routes. Grant internal users read-only access to the listing and provider routes; create/update/delete stay admin-only. Resolves LIT-3150 * fix(auth): scope /search_tools/list to caller-allowed tools Adding the read routes to internal_user_routes let any internal user call /search_tools/list, which returned every configured tool's id, provider, api_base, and metadata regardless of the caller's object_permission.search_tools allowlist. The api_key was masked, so this was metadata disclosure rather than a credential leak, but it ignored the key/team scoping that /search already enforces. Filter the listing through the same can_key_call_search_tool / can_team_call_search_tool checks (exposed as a boolean can_user_view_search_tool), so non-admin callers only see tools they may invoke; admins still see all. Mirrors how /vector_store/list scopes results. * fix(types): resolve mypy errors in list_search_tools The config and DB build loops reused one loop variable, so mypy pinned it to the config element type (SearchToolTypedDict); its .get() calls returned object and the DB element (SearchTool) failed the reuse assignment. Give each loop its own variable so each gets its real type, and coerce the config tool's SearchToolInfoTypedDict to a plain dict to match SearchToolInfoResponse.search_tool_info. --- litellm/proxy/_types.py | 4 + litellm/proxy/auth/auth_checks.py | 23 +++ .../search_tool_management.py | 92 +++++++-- .../proxy/auth/test_route_checks.py | 69 +++++++ .../test_search_tool_management.py | 175 +++++++++++++++++- 5 files changed, 348 insertions(+), 15 deletions(-) diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 6168097733d..feab3b04a5e 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -701,6 +701,10 @@ class LiteLLMRoutes(enum.Enum): "/v2/guardrails/list", "/project/list", "/project/info", + # Read-only search tool routes power the Search Tools UI page. + # Create/update/delete and test_connection stay admin-only. + "/search_tools/list", + "/search_tools/ui/available_providers", ] + spend_tracking_routes + key_management_routes diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 917239e0358..6ea4bd80e2f 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -3428,6 +3428,29 @@ async def can_team_call_search_tool( ) +async def can_user_view_search_tool( + search_tool_name: str, + valid_token: UserAPIKeyAuth, + team_object: Optional[LiteLLM_TeamTable], +) -> bool: + """ + Boolean variant of the key + team authorization enforced on /search, used to + scope /search_tools/list so a non-admin caller only sees tools it may invoke. + """ + try: + await can_key_call_search_tool( + search_tool_name=search_tool_name, + valid_token=valid_token, + ) + await can_team_call_search_tool( + search_tool_name=search_tool_name, + team_object=team_object, + ) + except ProxyException: + return False + return True + + async def is_valid_fallback_model( model: str, llm_router: Optional[Router], diff --git a/litellm/proxy/search_endpoints/search_tool_management.py b/litellm/proxy/search_endpoints/search_tool_management.py index 725e83bf96d..5642fcd10c3 100644 --- a/litellm/proxy/search_endpoints/search_tool_management.py +++ b/litellm/proxy/search_endpoints/search_tool_management.py @@ -3,12 +3,17 @@ CRUD ENDPOINTS FOR SEARCH TOOLS """ from datetime import datetime -from typing import Any, Dict, List, Union +from typing import Any, Dict, List, Optional, Union from fastapi import APIRouter, Depends, HTTPException from pydantic import BaseModel from litellm._logging import verbose_proxy_logger +from litellm.proxy._types import ( + LiteLLM_TeamTable, + LitellmUserRoles, + UserAPIKeyAuth, +) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.search_endpoints.search_tool_registry import SearchToolRegistry from litellm.types.search import ( @@ -41,13 +46,61 @@ def _convert_datetime_to_str(value: Union[datetime, str, None]) -> Union[str, No return value +async def _filter_visible_search_tools( + search_tools: List[SearchToolInfoResponse], + user_api_key_dict: UserAPIKeyAuth, +) -> List[SearchToolInfoResponse]: + """ + Drop search tools the caller is not authorized to invoke, applying the same + key/team object_permission allowlists enforced on /search. Admins see all tools. + """ + if user_api_key_dict.user_role in ( + LitellmUserRoles.PROXY_ADMIN, + LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY, + ): + return search_tools + + from litellm.proxy.auth.auth_checks import ( + can_user_view_search_tool, + get_team_object, + ) + from litellm.proxy.proxy_server import ( + prisma_client, + proxy_logging_obj, + user_api_key_cache, + ) + + team_object: Optional[LiteLLM_TeamTable] = None + if user_api_key_dict.team_id: + team_object = await get_team_object( + team_id=user_api_key_dict.team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=user_api_key_dict.parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + + visible: List[SearchToolInfoResponse] = [] + for tool in search_tools: + tool_name = tool.get("search_tool_name") + if tool_name and await can_user_view_search_tool( + search_tool_name=tool_name, + valid_token=user_api_key_dict, + team_object=team_object, + ): + visible.append(tool) + return visible + + @router.get( "/search_tools/list", tags=["Search Tools"], dependencies=[Depends(user_api_key_auth)], response_model=ListSearchToolsResponse, ) -async def list_search_tools(): +async def list_search_tools( + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): """ List all search tools that are available in the database and config file. @@ -114,22 +167,25 @@ async def list_search_tools(): f"Could not get config-defined search tools: {e}" ) - for search_tool in config_search_tools: - tool_name = search_tool.get("search_tool_name") + for config_search_tool in config_search_tools: + tool_name = config_search_tool.get("search_tool_name") if tool_name: - litellm_params_dict = dict(search_tool.get("litellm_params", {})) + litellm_params_dict = dict(config_search_tool.get("litellm_params", {})) masked_litellm_params_dict = _get_masked_values( litellm_params_dict, unmasked_length=4, number_of_asterisks=4, ) + config_tool_info = config_search_tool.get("search_tool_info") search_tool_configs.append( SearchToolInfoResponse( search_tool_id=None, search_tool_name=tool_name, litellm_params=masked_litellm_params_dict, - search_tool_info=search_tool.get("search_tool_info"), + search_tool_info=( + dict(config_tool_info) if config_tool_info else None + ), created_at=None, updated_at=None, is_from_config=True, @@ -142,8 +198,8 @@ async def list_search_tools(): if tool.get("search_tool_name") not in db_tool_names ] - for search_tool in search_tools_from_db: - litellm_params_dict = dict(search_tool.get("litellm_params", {})) + for db_search_tool in search_tools_from_db: + litellm_params_dict = dict(db_search_tool.get("litellm_params", {})) masked_litellm_params_dict = _get_masked_values( litellm_params_dict, unmasked_length=4, @@ -152,17 +208,25 @@ async def list_search_tools(): search_tool_configs.append( SearchToolInfoResponse( - search_tool_id=search_tool.get("search_tool_id"), - search_tool_name=search_tool.get("search_tool_name", ""), + search_tool_id=db_search_tool.get("search_tool_id"), + search_tool_name=db_search_tool.get("search_tool_name", ""), litellm_params=masked_litellm_params_dict, - search_tool_info=search_tool.get("search_tool_info"), - created_at=_convert_datetime_to_str(search_tool.get("created_at")), - updated_at=_convert_datetime_to_str(search_tool.get("updated_at")), + search_tool_info=db_search_tool.get("search_tool_info"), + created_at=_convert_datetime_to_str( + db_search_tool.get("created_at") + ), + updated_at=_convert_datetime_to_str( + db_search_tool.get("updated_at") + ), is_from_config=False, ) ) - return ListSearchToolsResponse(search_tools=search_tool_configs) + visible_search_tools = await _filter_visible_search_tools( + search_tool_configs, user_api_key_dict + ) + + return ListSearchToolsResponse(search_tools=visible_search_tools) except Exception as e: verbose_proxy_logger.exception(f"Error getting search tools: {e}") raise HTTPException(status_code=500, detail=str(e)) diff --git a/tests/test_litellm/proxy/auth/test_route_checks.py b/tests/test_litellm/proxy/auth/test_route_checks.py index ad9295d6b19..197572216d0 100644 --- a/tests/test_litellm/proxy/auth/test_route_checks.py +++ b/tests/test_litellm/proxy/auth/test_route_checks.py @@ -2602,3 +2602,72 @@ def test_legitimate_passthrough_routes_still_classified_as_llm_route(route): assert ( RouteChecks.is_llm_api_route(route=route) is True ), f"{route!r} should be classified as an LLM API route" + + +@pytest.mark.parametrize( + "route", + [ + "/search_tools/list", + "/search_tools/ui/available_providers", + ], +) +def test_internal_user_can_read_search_tools(route): + """Regression for LIT-3150: internal users must be able to view search tools, + the same way they can view vector stores.""" + user_obj = LiteLLM_UserTable( + user_id="test_user", + user_email="user@example.com", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ) + valid_token = UserAPIKeyAuth( + user_id="test_user", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ) + request = MagicMock(spec=Request) + request.query_params = {} + + RouteChecks.non_proxy_admin_allowed_routes_check( + user_obj=user_obj, + _user_role=LitellmUserRoles.INTERNAL_USER.value, + route=route, + request=request, + valid_token=valid_token, + request_data={}, + ) + + +@pytest.mark.parametrize( + "route", + [ + "/search_tools", # create + "/search_tools/abc123", # update / delete / get-by-id + "/search_tools/test_connection", + ], +) +def test_internal_user_blocked_from_search_tool_writes(route): + """Read access must not leak the search-tool management write routes to + internal users; only proxy admins create/update/delete/test them.""" + user_obj = LiteLLM_UserTable( + user_id="test_user", + user_email="user@example.com", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ) + valid_token = UserAPIKeyAuth( + user_id="test_user", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ) + request = MagicMock(spec=Request) + request.query_params = {} + + with pytest.raises(Exception) as exc_info: + RouteChecks.non_proxy_admin_allowed_routes_check( + user_obj=user_obj, + _user_role=LitellmUserRoles.INTERNAL_USER.value, + route=route, + request=request, + valid_token=valid_token, + request_data={}, + ) + assert "Only proxy admin" in str(exc_info.value) + assert f"Route={route}" in str(exc_info.value) + assert "Your role=internal_user" in str(exc_info.value) diff --git a/tests/test_litellm/proxy/management_endpoints/search_endpoints/test_search_tool_management.py b/tests/test_litellm/proxy/management_endpoints/search_endpoints/test_search_tool_management.py index 55b4181e92e..ea7e5591f18 100644 --- a/tests/test_litellm/proxy/management_endpoints/search_endpoints/test_search_tool_management.py +++ b/tests/test_litellm/proxy/management_endpoints/search_endpoints/test_search_tool_management.py @@ -1,3 +1,4 @@ +import contextlib import os import sys from datetime import datetime @@ -10,7 +11,12 @@ sys.path.insert( 0, os.path.abspath("../../../../..") ) # Adds the parent directory to the system path -from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth +from litellm.proxy._types import ( + LiteLLM_ObjectPermissionTable, + LiteLLM_TeamTable, + LitellmUserRoles, + UserAPIKeyAuth, +) # Import proxy_server module first to ensure it's initialized import litellm.proxy.proxy_server as ps @@ -603,3 +609,170 @@ async def test_list_search_tools_db_masking_sensitive_values(monkeypatch): assert tool4["litellm_params"]["search_provider"] == "custom" finally: app.dependency_overrides.pop(user_api_key_auth, None) + + +@contextlib.contextmanager +def _mock_search_tool_backend(db_tools): + """Patch the DB registry, prisma client, and config so /search_tools/list + returns exactly ``db_tools`` (no config-defined tools).""" + mock_registry = MagicMock() + mock_registry.get_all_search_tools_from_db = AsyncMock(return_value=db_tools) + mock_proxy_config = MagicMock() + mock_proxy_config.get_config = AsyncMock(return_value={}) + mock_proxy_config.parse_search_tools = MagicMock(return_value=None) + with ( + patch( + "litellm.proxy.search_endpoints.search_tool_management.SEARCH_TOOL_REGISTRY", + mock_registry, + ), + patch("litellm.proxy.proxy_server.prisma_client", MagicMock()), + patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config), + ): + yield + + +def _scoping_db_tools(): + return [ + { + "search_tool_id": "db-id-1", + "search_tool_name": "db-tool-1", + "litellm_params": { + "search_provider": "perplexity", + "api_key": "pplx-secret-1", + "api_base": "https://api.perplexity.ai", + }, + "search_tool_info": {"description": "Perplexity"}, + "created_at": datetime(2024, 1, 1), + "updated_at": datetime(2024, 1, 1), + }, + { + "search_tool_id": "db-id-2", + "search_tool_name": "db-tool-2", + "litellm_params": { + "search_provider": "tavily", + "api_key": "tvly-secret-2", + "api_base": "https://api.tavily.com", + }, + "search_tool_info": {"description": "Tavily"}, + "created_at": datetime(2024, 1, 1), + "updated_at": datetime(2024, 1, 1), + }, + { + "search_tool_id": "db-id-3", + "search_tool_name": "db-tool-3", + "litellm_params": {"search_provider": "exa", "api_key": "exa-secret-3"}, + "search_tool_info": {"description": "Exa"}, + "created_at": datetime(2024, 1, 1), + "updated_at": datetime(2024, 1, 1), + }, + ] + + +@contextlib.contextmanager +def _override_auth(user): + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + app.dependency_overrides[user_api_key_auth] = lambda: user + try: + yield + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_list_search_tools_scoped_to_key_object_permission(): + """ + Regression: an internal user whose key is restricted to specific search tools + must only see those tools. Before the fix /search_tools/list returned every + configured tool, leaking ids, api_base, and metadata for tools it cannot call. + """ + restricted_user = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + user_id="internal_user", + object_permission=LiteLLM_ObjectPermissionTable( + object_permission_id="op-key", + search_tools=["db-tool-1"], + ), + ) + + with ( + _mock_search_tool_backend(_scoping_db_tools()), + _override_auth(restricted_user), + ): + response = TestClient(app).get("/search_tools/list") + + assert response.status_code == 200 + tools = response.json()["search_tools"] + assert [t["search_tool_name"] for t in tools] == ["db-tool-1"] + leaked = {t["litellm_params"].get("api_base") for t in tools} + assert "https://api.tavily.com" not in leaked + + +@pytest.mark.asyncio +async def test_list_search_tools_unrestricted_internal_user_sees_all(): + """An internal user with no search_tools allowlist is unrestricted and sees every tool.""" + unrestricted_user = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, user_id="internal_user" + ) + + with ( + _mock_search_tool_backend(_scoping_db_tools()), + _override_auth(unrestricted_user), + ): + response = TestClient(app).get("/search_tools/list") + + assert response.status_code == 200 + names = {t["search_tool_name"] for t in response.json()["search_tools"]} + assert names == {"db-tool-1", "db-tool-2", "db-tool-3"} + + +@pytest.mark.asyncio +async def test_list_search_tools_scoped_to_team_object_permission(): + """A team-level search_tools allowlist also scopes the listing for a non-admin caller.""" + team_member = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + user_id="internal_user", + team_id="team-1", + ) + team_object = LiteLLM_TeamTable( + team_id="team-1", + object_permission=LiteLLM_ObjectPermissionTable( + object_permission_id="op-team", + search_tools=["db-tool-2"], + ), + ) + + with ( + _mock_search_tool_backend(_scoping_db_tools()), + patch( + "litellm.proxy.auth.auth_checks.get_team_object", + AsyncMock(return_value=team_object), + ), + _override_auth(team_member), + ): + response = TestClient(app).get("/search_tools/list") + + assert response.status_code == 200 + assert [t["search_tool_name"] for t in response.json()["search_tools"]] == [ + "db-tool-2" + ] + + +@pytest.mark.asyncio +async def test_list_search_tools_admin_with_restricted_key_still_sees_all(): + """Proxy admins bypass search-tool scoping even if their key carries an allowlist.""" + admin_user = UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id="admin_user", + object_permission=LiteLLM_ObjectPermissionTable( + object_permission_id="op-admin", + search_tools=["db-tool-1"], + ), + ) + + with _mock_search_tool_backend(_scoping_db_tools()), _override_auth(admin_user): + response = TestClient(app).get("/search_tools/list") + + assert response.status_code == 200 + names = {t["search_tool_name"] for t in response.json()["search_tools"]} + assert names == {"db-tool-1", "db-tool-2", "db-tool-3"} From 8fbdfc7f0d8473af491b5a990b7288d90671ee3e Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 2 Jun 2026 18:51:48 -0700 Subject: [PATCH 06/92] fix: missing mcp otel attributes (#29554) --- litellm/integrations/otel/model/payloads.py | 15 ++++++- .../integrations/otel/test_otel_v2_logger.py | 45 +++++++++++++++---- .../otel/test_otel_v2_sources_of_truth.py | 18 ++++---- 3 files changed, 59 insertions(+), 19 deletions(-) diff --git a/litellm/integrations/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py index 08fce09868b..bbef40ba374 100644 --- a/litellm/integrations/otel/model/payloads.py +++ b/litellm/integrations/otel/model/payloads.py @@ -340,7 +340,7 @@ class MCPToolCallSpanData: def from_standard_logging_payload( cls, payload: "StandardLoggingPayload", capture_content: bool = False ) -> "MCPToolCallSpanData": - meta = cast(Mapping[str, object], payload.get("mcp_tool_call_metadata") or {}) + meta = _mcp_tool_call_metadata(cast(Mapping[str, object], payload)) return cls( operation=resolve_operation(as_str(payload.get("call_type"))), method=MCPMethod.TOOLS_CALL.value, @@ -363,11 +363,22 @@ class MCPToolCallSpanData: ) +def _mcp_tool_call_metadata(payload: Mapping[str, object]) -> Mapping[str, object]: + """The MCP gateway's tool-call metadata, which lives under + ``StandardLoggingPayload.metadata`` (a ``StandardLoggingMetadata`` key), not + at the payload's top level.""" + metadata = payload.get("metadata") + if not isinstance(metadata, Mapping): + return {} + meta = metadata.get("mcp_tool_call_metadata") + return meta if isinstance(meta, Mapping) else {} + + def is_mcp_tool_call(payload: Mapping[str, object]) -> bool: """Whether a closed request's payload is an MCP tool call rather than an LLM call — true when the MCP gateway stamped its tool-call metadata, or the call type says so on a path that hasn't populated the metadata yet.""" - return bool(payload.get("mcp_tool_call_metadata")) or ( + return bool(_mcp_tool_call_metadata(payload)) or ( payload.get("call_type") == "call_mcp_tool" ) diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py index 9947ce9ac9e..8dffb71bbf0 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py @@ -249,15 +249,17 @@ def _mcp_payload(**overrides): "status": "success", "litellm_call_id": "mcp_1", "response_cost": 0.01, - "metadata": {"user_api_key_team_id": "t1"}, - "hidden_params": {}, - "mcp_tool_call_metadata": { - "name": "get_weather", - "arguments": {"city": "Paris"}, - "result": {"temp_c": 21}, - "mcp_server_name": "weather-mcp", - "mcp_session_id": "sess-abc123", + "metadata": { + "user_api_key_team_id": "t1", + "mcp_tool_call_metadata": { + "name": "get_weather", + "arguments": {"city": "Paris"}, + "result": {"temp_c": 21}, + "mcp_server_name": "weather-mcp", + "mcp_session_id": "sess-abc123", + }, }, + "hidden_params": {}, } payload.update(overrides) return payload @@ -302,7 +304,7 @@ def test_mcp_tool_call_stateless_omits_session_id(): ``mcp.session.id`` rather than stamping an empty or ``None`` value.""" logger, exporter = _logger() payload = _mcp_payload() - del payload["mcp_tool_call_metadata"]["mcp_session_id"] + del payload["metadata"]["mcp_tool_call_metadata"]["mcp_session_id"] asyncio.run( logger.async_log_success_event( {"standard_logging_object": payload}, None, None, None @@ -360,6 +362,31 @@ def test_mcp_tool_call_deduped_on_repeat(): assert len(exporter.get_finished_spans()) == 1 +def test_mcp_tool_call_metadata_read_from_nested_metadata_not_top_level(): + """``mcp_tool_call_metadata`` lives under ``StandardLoggingPayload.metadata``; + a top-level copy (the pre-fix shape the reader used to look at) must be ignored + so the reader can't silently regress to producing an empty ``tools/call`` span + with no session id, tool name, or server name.""" + logger, exporter = _logger() + payload = _mcp_payload() + # Move the real metadata to the top level only, mirroring the old buggy read + # location. ``call_type`` still classifies this as an MCP call, so the span is + # emitted, but none of its fields are reachable from the wrong nesting level. + payload["mcp_tool_call_metadata"] = payload["metadata"].pop( + "mcp_tool_call_metadata" + ) + asyncio.run( + logger.async_log_success_event( + {"standard_logging_object": payload}, None, None, None + ) + ) + (span,) = exporter.get_finished_spans() + assert span.name == "tools/call" + assert "mcp.session.id" not in span.attributes + assert "gen_ai.tool.name" not in span.attributes + assert LiteLLM.MCP_SERVER_NAME not in span.attributes + + def test_pre_call_idempotent_keeps_first_span(): """A retried call may re-enter ``pre_call`` with the same call id; the first span (with the true start time) is kept, not replaced.""" diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py index ecd39c1c936..20824ca09e6 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py @@ -195,15 +195,17 @@ def _mcp_payload(capture=False, **overrides): "status": "success", "litellm_call_id": "mcp_call_1", "response_cost": 0.01, - "metadata": {"user_api_key_team_id": "t1"}, - "hidden_params": {}, - "mcp_tool_call_metadata": { - "name": "get_weather", - "arguments": {"city": "Paris"}, - "result": {"temp_c": 21}, - "mcp_server_name": "weather-mcp", - "mcp_session_id": "sess-abc123", + "metadata": { + "user_api_key_team_id": "t1", + "mcp_tool_call_metadata": { + "name": "get_weather", + "arguments": {"city": "Paris"}, + "result": {"temp_c": 21}, + "mcp_server_name": "weather-mcp", + "mcp_session_id": "sess-abc123", + }, }, + "hidden_params": {}, } payload.update(overrides) return payload From d45e9e4d5605ec92d4f798f62b30486ef5d413ec Mon Sep 17 00:00:00 2001 From: Shivam Rawat Date: Tue, 2 Jun 2026 19:31:36 -0700 Subject: [PATCH 07/92] fix(proxy): resolve managed video model ids for auth (#29545) * fix(proxy): resolve managed video model ids for auth Co-authored-by: Cursor * test(proxy): cover character_id router model resolution Co-authored-by: Cursor --------- Co-authored-by: Cursor --- litellm/proxy/auth/auth_checks.py | 1 + litellm/proxy/auth/auth_utils.py | 35 ++++++++++-- litellm/proxy/auth/user_api_key_auth.py | 8 +++ .../spend_tracking/budget_reservation.py | 4 +- .../proxy/auth/test_auth_utils.py | 56 +++++++++++++++++++ 5 files changed, 96 insertions(+), 8 deletions(-) diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 6ea4bd80e2f..e8d05031a5a 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -546,6 +546,7 @@ async def common_checks( # noqa: PLR0915 route=route, request_headers=_safe_get_request_headers(request=request), request_query_params=_safe_get_request_query_params(request=request), + llm_router=llm_router, ) if route in MODEL_DISCOVERY_ROUTES: diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index 80840c27425..71cf5197dec 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -1284,7 +1284,9 @@ def _route_uses_model_routing_sources(route: str) -> bool: def _extract_models_from_managed_resource_id( - resource_id: Any, resource_id_field: Optional[str] = None + resource_id: Any, + resource_id_field: Optional[str] = None, + llm_router: Optional[Router] = None, ) -> List[str]: if not isinstance(resource_id, str) or not resource_id: return [] @@ -1341,16 +1343,18 @@ def _extract_models_from_managed_resource_id( ) if resource_id_field == "video_id": + model_id = decode_video_id_with_provider(resource_id).get("model_id") _append_model_candidates( candidates=candidates, - value=decode_video_id_with_provider(resource_id).get("model_id"), + value=_resolve_model_id_with_router(model_id, llm_router), ) else: + model_id = decode_character_id_with_provider(resource_id).get( + "model_id" + ) _append_model_candidates( candidates=candidates, - value=decode_character_id_with_provider(resource_id).get( - "model_id" - ), + value=_resolve_model_id_with_router(model_id, llm_router), ) except Exception as e: verbose_proxy_logger.debug( @@ -1360,11 +1364,26 @@ def _extract_models_from_managed_resource_id( return _dedupe_model_candidates(candidates) +def _resolve_model_id_with_router( + model_id: Optional[str], llm_router: Optional[Router] +) -> Optional[str]: + if model_id is None or llm_router is None: + return model_id + try: + return llm_router.resolve_model_name_from_model_id(model_id) or model_id + except Exception as e: + verbose_proxy_logger.debug( + "Unable to resolve model_id from managed resource ID: %s", str(e) + ) + return model_id + + def _extract_model_candidates_from_request( request_data: dict, route: str, request_headers: Optional[Mapping[str, Any]] = None, request_query_params: Optional[Mapping[str, Any]] = None, + llm_router: Optional[Router] = None, ) -> List[str]: candidates: List[str] = [] uses_model_routing_sources = _route_uses_model_routing_sources(route=route) @@ -1414,7 +1433,9 @@ def _extract_model_candidates_from_request( _append_model_candidates( candidates, _extract_models_from_managed_resource_id( - request_data.get(field), resource_id_field=field + request_data.get(field), + resource_id_field=field, + llm_router=llm_router, ), ) @@ -1436,12 +1457,14 @@ def get_model_from_request( route: str, request_headers: Optional[Mapping[str, Any]] = None, request_query_params: Optional[Mapping[str, Any]] = None, + llm_router: Optional[Router] = None, ) -> Optional[Union[str, List[str]]]: candidates = _extract_model_candidates_from_request( request_data=request_data, route=route, request_headers=request_headers, request_query_params=request_query_params, + llm_router=llm_router, ) model = _format_model_candidates(candidates) diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 2f9a1411400..2e6cd1f8e70 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -146,12 +146,14 @@ def _get_model_from_request_context( request_data: dict, route: str, request: Optional[Request], + llm_router: Optional[Any] = None, ) -> Optional[Union[str, List[str]]]: return get_model_from_request( request_data=request_data, route=route, request_headers=_safe_get_request_headers(request=request), request_query_params=_safe_get_request_query_params(request=request), + llm_router=llm_router, ) @@ -1034,6 +1036,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 request_data=request_data, route=route, request=request, + llm_router=llm_router, ) skip_budget_checks = False if model is not None and llm_router is not None: @@ -1451,6 +1454,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 request_data=request_data, route=route, request=request, + llm_router=llm_router, ) skip_budget_checks = False if model is not None and llm_router is not None: @@ -1579,6 +1583,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 request_data=request_data, route=route, request=request, + llm_router=llm_router, ) current_models = _get_model_names_for_budget_checks( model=current_model @@ -2159,6 +2164,7 @@ def _should_skip_budget_checks( request_data=request_data, route=route, request=request, + llm_router=llm_router, ) if model is not None and llm_router is not None: return _is_model_cost_zero(model=model, llm_router=llm_router) @@ -2475,6 +2481,7 @@ async def _enforce_key_and_fallback_model_access( request_data=request_data, route=route, request=request, + llm_router=llm_router, ) if model is not None: @@ -2616,6 +2623,7 @@ async def _run_post_custom_auth_checks( request_data=request_data, route=route, request=request, + llm_router=llm_router, ) current_models = _get_model_names_for_budget_checks(model=current_model) diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py index 200a17e2368..eb8af3b073e 100644 --- a/litellm/proxy/spend_tracking/budget_reservation.py +++ b/litellm/proxy/spend_tracking/budget_reservation.py @@ -72,7 +72,7 @@ async def reserve_budget_for_request( return None if route in {"/models", "/v1/models", "/utils/token_counter"}: return None - if get_model_from_request(request_body, route) is None: + if get_model_from_request(request_body, route, llm_router=llm_router) is None: return None counters = await _get_budget_counters( @@ -797,7 +797,7 @@ def estimate_request_max_cost( route: str, llm_router: Optional[Router], ) -> Optional[float]: - model = get_model_from_request(request_body, route) + model = get_model_from_request(request_body, route, llm_router=llm_router) if model is None: return None diff --git a/tests/test_litellm/proxy/auth/test_auth_utils.py b/tests/test_litellm/proxy/auth/test_auth_utils.py index 60cf50efc75..d4ca55ca16b 100644 --- a/tests/test_litellm/proxy/auth/test_auth_utils.py +++ b/tests/test_litellm/proxy/auth/test_auth_utils.py @@ -399,6 +399,62 @@ def test_get_model_from_request_extracts_video_id_model(): ) +def test_get_model_from_request_resolves_video_id_model_with_router(): + from litellm.types.videos.utils import encode_video_id_with_provider + + provider_video_id = ( + "projects/test-project/locations/us-central1/publishers/google/models/" + "veo-3.1-generate-001/operations/operation-id" + ) + video_id = encode_video_id_with_provider( + video_id=provider_video_id, + provider="vertex_ai", + model_id="veo-3.1-generate-001", + ) + llm_router = MagicMock() + llm_router.resolve_model_name_from_model_id.return_value = ( + "gcp/google/veo-3.1-generate-001" + ) + + assert ( + get_model_from_request( + request_data={"video_id": video_id}, + route="/v1/videos/{video_id}", + llm_router=llm_router, + ) + == "gcp/google/veo-3.1-generate-001" + ) + llm_router.resolve_model_name_from_model_id.assert_called_once_with( + "veo-3.1-generate-001" + ) + + +def test_get_model_from_request_resolves_character_id_model_with_router(): + from litellm.types.videos.utils import encode_character_id_with_provider + + character_id = encode_character_id_with_provider( + character_id="character-provider-id", + provider="vertex_ai", + model_id="veo-3.1-generate-001", + ) + llm_router = MagicMock() + llm_router.resolve_model_name_from_model_id.return_value = ( + "gcp/google/veo-3.1-generate-001" + ) + + assert ( + get_model_from_request( + request_data={"character_id": character_id}, + route="/v1/videos/characters/{character_id}", + llm_router=llm_router, + ) + == "gcp/google/veo-3.1-generate-001" + ) + llm_router.resolve_model_name_from_model_id.assert_called_once_with( + "veo-3.1-generate-001" + ) + + def test_get_model_from_request_only_runs_media_decoders_for_matching_fields(): with ( patch( From b11833c737fe329512828c086090ffeca8a53082 Mon Sep 17 00:00:00 2001 From: milan-berri Date: Wed, 3 Jun 2026 19:55:45 +0300 Subject: [PATCH 08/92] fix(key_generate): allow team members to create keys on org-scoped teams (#29310) * fix(key_generate): allow team members to create keys on org-scoped teams When a virtual key is created for a team, enterprise logic inherits the team's organization_id onto the key (add_team_organization_id). Since the VERIA-55 org-IDOR fix, /key/generate then required the caller to be an explicit LiteLLM_OrganizationMembership member of that org, returning 403 "Caller is not a member of organization_id=". Admins normally only add users to teams (not orgs), so self-serve key creation regressed for any user on an org-scoped team (regression since v1.84.0-rc.1). Skip the org-membership check when organization_id was inherited from the key's team (organization_id == team_table.organization_id). Team-level authorization already gates this path, so team membership is sufficient. The membership check still runs when a caller assigns an organization_id that did not come from the key's team, preserving the IDOR protection. Adds regression tests covering both the team-inherited (allowed) and foreign-org (still blocked) cases. Co-authored-by: Cursor * test(key_generate): cover mismatched team org IDOR path on generate Add test_generate_key_foreign_org_with_mismatched_team_still_enforces_membership for the case where a team is present but request organization_id differs from team_table.organization_id. Enterprise inheritance is no-op'd in the test so the guard is exercised directly; membership validation must still run. Addresses Greptile review on #29310. Co-authored-by: Cursor --------- Co-authored-by: Cursor --- .../key_management_endpoints.py | 7 +- .../test_key_management_endpoints.py | 243 ++++++++++++++++++ 2 files changed, 249 insertions(+), 1 deletion(-) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 80ded0bdd16..cf90f0661b3 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -894,7 +894,12 @@ async def _common_key_generation_helper( # noqa: PLR0915 user_api_key_dict.user_role is not None and user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value ) - if not _is_proxy_admin: + _org_inherited_from_team = ( + team_table is not None + and team_table.organization_id is not None + and data.organization_id == team_table.organization_id + ) + if not _is_proxy_admin and not _org_inherited_from_team: await _validate_caller_can_assign_key_org( user_api_key_dict=user_api_key_dict, organization_id=data.organization_id, diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index 8fb242372e3..cda22da6ebd 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -3094,6 +3094,249 @@ async def test_generate_key_with_object_permission(): assert "object_permission" not in key_data +@pytest.mark.asyncio +async def test_generate_key_team_member_inherits_org_skips_membership_check(): + """Regression: a team member creating a key for an org-scoped team must not + be blocked by the org-membership check. + + When ``organization_id`` is inherited from the key's team (via + ``apply_enterprise_key_management_params`` -> ``add_team_organization_id``), + the caller already passed team-level authorization. Requiring an explicit + ``LiteLLM_OrganizationMembership`` row on top of that broke the normal admin + workflow (admins only add users to teams). This asserts the org-membership + check is skipped when the org id came from the caller's team. + """ + from unittest.mock import AsyncMock, MagicMock, patch + + from litellm.proxy._types import GenerateKeyRequest, LitellmUserRoles + from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _common_key_generation_helper, + ) + + org_id = "org-from-team" + + # Team belongs to an org; caller is a team member but NOT an explicit member + # of that organization (the regression scenario). + mock_team_table = MagicMock() + mock_team_table.organization_id = org_id + mock_team_table.metadata = None + + mock_validate_org = AsyncMock() + mock_generate_key = AsyncMock( + return_value={ + "key": "sk-test-key", + "expires": None, + "user_id": "alice", + "team_id": "team-1", + } + ) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", MagicMock()), + patch("litellm.proxy.proxy_server.llm_router", None), + patch("litellm.proxy.proxy_server.premium_user", True), + patch("litellm.proxy.proxy_server.litellm_proxy_admin_name", "admin"), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.validate_key_mcp_servers_against_team", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.validate_key_search_tools_against_team", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._validate_caller_can_assign_key_org", + mock_validate_org, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.get_org_object", + new_callable=AsyncMock, + return_value=MagicMock(litellm_budget_table=None), + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._check_org_key_limits", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.generate_key_helper_fn", + mock_generate_key, + ), + ): + result = await _common_key_generation_helper( + data=GenerateKeyRequest( + user_id="alice", + team_id="team-1", + organization_id=org_id, + ), + user_api_key_dict=UserAPIKeyAuth( + user_id="alice", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ), + litellm_changed_by=None, + team_table=mock_team_table, + ) + + # Key creation proceeded for the team member ... + mock_generate_key.assert_awaited_once() + assert result is not None + # ... and the org-membership check was bypassed because organization_id was + # inherited from the caller's team. + mock_validate_org.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_generate_key_foreign_org_without_team_still_enforces_membership(): + """VERIA-55: a caller assigning a key to an organization that was NOT + inherited from a team must still pass the org-membership check. + + This guards the IDOR fix: ``team_table is None`` (or an org id that does not + match the team) means the org id did not come from team context, so the + explicit membership validation must run. + """ + from unittest.mock import AsyncMock, MagicMock, patch + + from litellm.proxy._types import GenerateKeyRequest, LitellmUserRoles + from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _common_key_generation_helper, + ) + + foreign_org_id = "someone-elses-org" + + mock_validate_org = AsyncMock() + mock_generate_key = AsyncMock( + return_value={ + "key": "sk-test-key", + "expires": None, + "user_id": "alice", + "team_id": None, + } + ) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", MagicMock()), + patch("litellm.proxy.proxy_server.llm_router", None), + patch("litellm.proxy.proxy_server.premium_user", True), + patch("litellm.proxy.proxy_server.litellm_proxy_admin_name", "admin"), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._validate_caller_can_assign_key_org", + mock_validate_org, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.get_org_object", + new_callable=AsyncMock, + return_value=MagicMock(litellm_budget_table=None), + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._check_org_key_limits", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.generate_key_helper_fn", + mock_generate_key, + ), + ): + await _common_key_generation_helper( + data=GenerateKeyRequest( + user_id="alice", + organization_id=foreign_org_id, + ), + user_api_key_dict=UserAPIKeyAuth( + user_id="alice", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ), + litellm_changed_by=None, + team_table=None, + ) + + # No team context -> the org-membership check must still run. + mock_validate_org.assert_awaited_once() + assert mock_validate_org.call_args.kwargs["organization_id"] == foreign_org_id + + +@pytest.mark.asyncio +async def test_generate_key_foreign_org_with_mismatched_team_still_enforces_membership(): + """VERIA-55: when a team is present but its organization_id differs from the + organization_id on the key request, the org-membership check must still run.""" + from unittest.mock import AsyncMock, MagicMock, patch + + from litellm.proxy._types import GenerateKeyRequest, LitellmUserRoles + from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _common_key_generation_helper, + ) + + team_org_id = "other-org" + foreign_org_id = "someone-elses-org" + + mock_team_table = MagicMock() + mock_team_table.organization_id = team_org_id + mock_team_table.metadata = None + + mock_validate_org = AsyncMock() + mock_generate_key = AsyncMock( + return_value={ + "key": "sk-test-key", + "expires": None, + "user_id": "alice", + "team_id": "team-1", + } + ) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", MagicMock()), + patch("litellm.proxy.proxy_server.llm_router", None), + patch("litellm.proxy.proxy_server.premium_user", True), + patch("litellm.proxy.proxy_server.litellm_proxy_admin_name", "admin"), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.validate_key_mcp_servers_against_team", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.validate_key_search_tools_against_team", + new_callable=AsyncMock, + ), + patch( + "litellm_enterprise.proxy.management_endpoints.key_management_endpoints.apply_enterprise_key_management_params", + side_effect=lambda data, team_table: data, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._validate_caller_can_assign_key_org", + mock_validate_org, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.get_org_object", + new_callable=AsyncMock, + return_value=MagicMock(litellm_budget_table=None), + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints._check_org_key_limits", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.management_endpoints.key_management_endpoints.generate_key_helper_fn", + mock_generate_key, + ), + ): + await _common_key_generation_helper( + data=GenerateKeyRequest( + user_id="alice", + team_id="team-1", + organization_id=foreign_org_id, + ), + user_api_key_dict=UserAPIKeyAuth( + user_id="alice", + user_role=LitellmUserRoles.INTERNAL_USER.value, + ), + litellm_changed_by=None, + team_table=mock_team_table, + ) + + mock_validate_org.assert_awaited_once() + assert mock_validate_org.call_args.kwargs["organization_id"] == foreign_org_id + + # ============================================ # Organization Key Limit Tests # ============================================ From f3e2167730a99b1d378315c9fc3feb283a5cf84f Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 3 Jun 2026 10:17:38 -0700 Subject: [PATCH 09/92] test(pass-through): move Gemini pass-through tests to gemini-3.1-flash-lite (#29595) * test(pass-through): move Gemini pass-through tests to gemini-3.1-flash-lite gemini-2.5-flash-lite is a generation behind and is slated for discontinuation on Vertex AI no earlier than October 16, 2026, so the pass-through suite was exercising an aging model. Every reference now points at gemini-3.1-flash-lite, which is GA and already priced in the cost map so the spend-logging assertions still compute a real cost test_vertex.test.js also gains jest.retryTimes(3) to match the sibling spend tests. The CI failures were intermittent 429 RESOURCE_EXHAUSTED from Vertex quota pressure, and that file was the only one without a retry, so a single rate-limited request was failing the whole job * test(pass-through): point Vertex tests at the global endpoint for gemini-3.1-flash-lite gemini-3.1-flash-lite is not served on the Vertex us-central1 regional endpoint for the CI project, so the Vertex pass-through tests were returning a deterministic 404 "Publisher Model ... was not found or your project does not have access to it" while the Gemini API tests passed. Move the Vertex clients to the global location, which the pass-through router maps to aiplatform.googleapis.com, where the 3.1 family is served --- .../test_gemini_with_spend.test.js | 4 ++-- tests/pass_through_tests/test_local_gemini.js | 4 ++-- tests/pass_through_tests/test_local_vertex.js | 4 ++-- tests/pass_through_tests/test_vertex.test.js | 11 +++++++---- tests/pass_through_tests/test_vertex_ai.py | 12 ++++++------ .../test_vertex_with_spend.test.js | 8 ++++---- 6 files changed, 23 insertions(+), 20 deletions(-) diff --git a/tests/pass_through_tests/test_gemini_with_spend.test.js b/tests/pass_through_tests/test_gemini_with_spend.test.js index 989bbc4b8e3..b9a25d3a3ed 100644 --- a/tests/pass_through_tests/test_gemini_with_spend.test.js +++ b/tests/pass_through_tests/test_gemini_with_spend.test.js @@ -32,7 +32,7 @@ describe('Gemini AI Tests', () => { }; const model = genAI.getGenerativeModel({ - model: 'gemini-2.5-flash-lite' + model: 'gemini-3.1-flash-lite' }, requestOptions); const prompt = 'Say "hello test" and nothing else'; @@ -83,7 +83,7 @@ describe('Gemini AI Tests', () => { }; const model = genAI.getGenerativeModel({ - model: 'gemini-2.5-flash-lite' + model: 'gemini-3.1-flash-lite' }, requestOptions); const prompt = 'Say "hello test" and nothing else'; diff --git a/tests/pass_through_tests/test_local_gemini.js b/tests/pass_through_tests/test_local_gemini.js index 0a72ca5cd7b..dc033a51f18 100644 --- a/tests/pass_through_tests/test_local_gemini.js +++ b/tests/pass_through_tests/test_local_gemini.js @@ -1,13 +1,13 @@ const { GoogleGenerativeAI, ModelParams, RequestOptions } = require("@google/generative-ai"); const modelParams = { - model: 'gemini-2.5-flash-lite', + model: 'gemini-3.1-flash-lite', }; const requestOptions = { baseUrl: 'http://127.0.0.1:4000/gemini', customHeaders: { - "tags": "gemini-js-sdk,gemini-2.5-flash-lite" + "tags": "gemini-js-sdk,gemini-3.1-flash-lite" } }; diff --git a/tests/pass_through_tests/test_local_vertex.js b/tests/pass_through_tests/test_local_vertex.js index 149635e2d6f..7cfe31db95b 100644 --- a/tests/pass_through_tests/test_local_vertex.js +++ b/tests/pass_through_tests/test_local_vertex.js @@ -4,7 +4,7 @@ const { VertexAI, RequestOptions } = require('@google-cloud/vertexai'); const vertexAI = new VertexAI({ project: 'litellm-ci-cd', - location: 'us-central1', + location: 'global', apiEndpoint: "127.0.0.1:4000/vertex-ai" }); @@ -20,7 +20,7 @@ const requestOptions = { }; const generativeModel = vertexAI.getGenerativeModel( - { model: 'gemini-2.5-flash-lite' }, + { model: 'gemini-3.1-flash-lite' }, requestOptions ); diff --git a/tests/pass_through_tests/test_vertex.test.js b/tests/pass_through_tests/test_vertex.test.js index 7b5edf6acd7..e0e879c2897 100644 --- a/tests/pass_through_tests/test_vertex.test.js +++ b/tests/pass_through_tests/test_vertex.test.js @@ -56,6 +56,9 @@ beforeAll(() => { loadVertexAiCredentials(); }); +// Configure Jest to retry flaky tests up to 3 times (useful for 429 rate limiting) +jest.retryTimes(3); + // Non-streaming Vertex generateContent can exceed 5s in CI / under load const VERTEX_TEST_TIMEOUT_MS = 30000; @@ -65,7 +68,7 @@ describe('Vertex AI Tests', () => { async () => { const vertexAI = new VertexAI({ project: 'litellm-ci-cd', - location: 'us-central1', + location: 'global', apiEndpoint: "localhost:4000/vertex-ai" }); @@ -78,7 +81,7 @@ describe('Vertex AI Tests', () => { }; const generativeModel = vertexAI.getGenerativeModel( - { model: 'gemini-2.5-flash-lite' }, + { model: 'gemini-3.1-flash-lite' }, requestOptions ); @@ -108,13 +111,13 @@ describe('Vertex AI Tests', () => { async () => { const vertexAI = new VertexAI({ project: 'litellm-ci-cd', - location: 'us-central1', + location: 'global', apiEndpoint: "localhost:4000/vertex-ai" }); const customHeaders = new Headers({"x-litellm-api-key": "sk-1234"}); const requestOptions = {customHeaders: customHeaders}; const generativeModel = vertexAI.getGenerativeModel( - {model: 'gemini-2.5-flash-lite'}, + {model: 'gemini-3.1-flash-lite'}, requestOptions ); const request = {contents: [{role: 'user', parts: [{text: 'What is 2+2?'}]}]}; diff --git a/tests/pass_through_tests/test_vertex_ai.py b/tests/pass_through_tests/test_vertex_ai.py index 73bf03c5000..bf1200489aa 100644 --- a/tests/pass_through_tests/test_vertex_ai.py +++ b/tests/pass_through_tests/test_vertex_ai.py @@ -103,12 +103,12 @@ async def test_basic_vertex_ai_pass_through_with_spendlog(): vertexai.init( project="litellm-ci-cd", - location="us-central1", + location="global", api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", api_transport="rest", ) - model = GenerativeModel(model_name="gemini-2.5-flash-lite") + model = GenerativeModel(model_name="gemini-3.1-flash-lite") response = model.generate_content("hi") print("response", response) @@ -143,12 +143,12 @@ async def test_basic_vertex_ai_pass_through_streaming_with_spendlog(): vertexai.init( project="litellm-ci-cd", - location="us-central1", + location="global", api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", api_transport="rest", ) - model = GenerativeModel(model_name="gemini-2.5-flash-lite") + model = GenerativeModel(model_name="gemini-3.1-flash-lite") response = model.generate_content("hi", stream=True) for chunk in response: @@ -182,7 +182,7 @@ async def test_vertex_ai_pass_through_endpoint_context_caching(): vertexai.init( project="litellm-ci-cd", - location="us-central1", + location="global", api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", api_transport="rest", ) @@ -204,7 +204,7 @@ async def test_vertex_ai_pass_through_endpoint_context_caching(): ] cached_content = caching.CachedContent.create( - model_name="gemini-2.5-flash-lite-001", + model_name="gemini-3.1-flash-lite", system_instruction=system_instruction, contents=contents, ttl=datetime.timedelta(minutes=60), diff --git a/tests/pass_through_tests/test_vertex_with_spend.test.js b/tests/pass_through_tests/test_vertex_with_spend.test.js index 142a1cec8ff..4dee890dc78 100644 --- a/tests/pass_through_tests/test_vertex_with_spend.test.js +++ b/tests/pass_through_tests/test_vertex_with_spend.test.js @@ -71,7 +71,7 @@ describe('Vertex AI Tests', () => { test('should successfully generate non-streaming content with tags', async () => { const vertexAI = new VertexAI({ project: 'litellm-ci-cd', - location: 'us-central1', + location: 'global', apiEndpoint: "127.0.0.1:4000/vertex_ai" }); @@ -85,7 +85,7 @@ describe('Vertex AI Tests', () => { }; const generativeModel = vertexAI.getGenerativeModel( - { model: 'gemini-2.5-flash-lite' }, + { model: 'gemini-3.1-flash-lite' }, requestOptions ); @@ -130,7 +130,7 @@ describe('Vertex AI Tests', () => { test('should successfully generate streaming content with tags', async () => { const vertexAI = new VertexAI({ project: 'litellm-ci-cd', - location: 'us-central1', + location: 'global', apiEndpoint: "127.0.0.1:4000/vertex_ai" }); @@ -144,7 +144,7 @@ describe('Vertex AI Tests', () => { }; const generativeModel = vertexAI.getGenerativeModel( - { model: 'gemini-2.5-flash-lite' }, + { model: 'gemini-3.1-flash-lite' }, requestOptions ); From c7ab9adde5634932a42c0a3639bfe6067934ecfb Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Wed, 3 Jun 2026 23:31:51 +0530 Subject: [PATCH 10/92] Litellm oss staging 030626 (#29578) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Fix incorrect agent API request example payload structure (#29556) * fix(otel): add litellm_metadata fallback in _get_span_context and _end_proxy_span_from_kwargs (#29427) * fix(otel): add litellm_metadata fallback in _get_span_context and _end_proxy_span_from_kwargs On /v1/messages and other LITELLM_METADATA_ROUTES, the parent OTel span is stored in litellm_params['litellm_metadata'] instead of litellm_params['metadata']. When the request body contains a native 'metadata' field (e.g. Anthropic's {"user_id": "..."}), litellm_params['metadata'] gets overwritten and the parent span is lost, producing orphan root spans with a different trace_id. Add fallback checks to litellm_metadata in: - _get_span_context(): so child spans find the correct parent - _end_proxy_span_from_kwargs(): so the proxy span gets closed Fixes: https://github.com/BerriAI/litellm/issues/27934 * test(otel): tighten assertions per Greptile review - test_span_context_metadata_takes_priority: assert litellm_metadata span is never accessed, proving metadata takes priority - test_span_context_no_parent_when_neither_has_span: assert both ctx and detected_span are None --------- Co-authored-by: shin-berri Co-authored-by: yuneng-jiang Co-authored-by: Aneesh-Fiddler Co-authored-by: Sameer Kankute * fix: remove premature end-user budget check from get_end_user_object (#29420) * fix(proxy): remove premature end-user budget check from get_end_user_object Problem: - `_check_end_user_budget()` was called inside `get_end_user_object()` - This caused budget checks to run BEFORE `skip_budget_checks` could be evaluated - Zero-cost models (e.g., local vLLM) were incorrectly blocked when end-users exceeded their budget, even though they should bypass budget checks Solution: - Remove `_check_end_user_budget()` calls from `get_end_user_object()` - Budget enforcement now happens exclusively in `common_checks()` where `skip_budget_checks` context is available - `get_end_user_object()` keeps `route` as optional in function parameter for backwards compatibility and future implementation. * refactor(tests): update budget enforcement tests to reflect changes in get_end_user_object - test_get_end_user_object() verifies data fetching - test_check_end_user_budget() verifies enforcement - test_budget_enforcement_blocks_over_budget_users() integrates _check_end_user_budget() - test_resolve_end_user_reraises_budget_exceeded() is now test_resolve_end_user since no budget exceeded is thrown in get_end_user_object() * Gemini /images/generate and /images/edits billing fixes + add support for size and aspect ratio params (#29534) * Fix Gemini image config mapping * Address Gemini image config review * Format Gemini image generation transform * Fix Gemini image token usage logging * Share Gemini image request helpers * Fix Gemini Imagen model routing * Fixes as per self code review * Fixes per internal code review * Stop gating Imagen imageSize forwarding * Document Gemini image size mapping source * chore: retrigger lint * Clarify Gemini candidate count precedence * Add Inception provider (#29522) * add inception as provider (chat, fim) * linting * seperate test suite for chat and fim * fix test coverage * fix: model hub custom pricing model info (#29293) * Opik user auth key metadata extractors (#28397) * fix: enhance Opik metadata extraction to include user API key auth context fixed after refactoring to extractor logic * test: add unit tests for OPik metadata extraction logic * fix: enhance extract_opik_metadata function to prioritize metadata sources for improved accuracy * fix(ci): clarified comments and edited unit tests * test: add unit tests for OPik metadata extraction with auth and requester overrides * fix(ui): replace fixed favicon.ico with current api get /get_favicon (#29532) Signed-off-by: José Luis Di Biase * fix(vertex/gemini): keep tool_call reference when a text-only assistant message follows (#29561) `_gemini_convert_messages_with_history` tracks `last_message_with_tool_calls` so a following tool result can be matched back to its tool call. The assignment was inside a branch guarded by `assistant_msg.get("tool_calls", []) is not None`, which is also True for a text-only assistant message (an empty list is not None). As a result, an assistant message with no tool calls that appears between a tool call and its tool result overwrote the reference, and conversion failed with: Exception: Missing corresponding tool call for tool response message. This shape is common: a model emits a short narration/assistant message after a tool call before the tool result is appended. Only update `last_message_with_tool_calls` when the assistant message actually carries tool_calls (or a function_call). Adds a regression test. Co-authored-by: shin-berri Co-authored-by: yuneng-jiang Co-authored-by: Claude Opus 4.8 * Add 1-hour cache write pricing for EU/AU/JP Bedrock Anthropic models (#28572) * fix(thinking): handle None thinking param in is_thinking_enabled (#28598) Squash-merged by litellm-agent from Terrajlz's PR. * feat(helm): support tpl rendering in podAnnotations (#28609) Squash-merged by litellm-agent from devauxbr's PR. * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) (#28575) * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) When a Chat Completions request to a GPT-5.4+ model contains both `tools` and `reasoning_effort`, `completion()` auto-routes through `responses_api_bridge`. The bridge handler called `litellm.responses()` / `litellm.aresponses()` without forwarding the already-resolved `custom_llm_provider`, so the downstream call re-invoked `get_llm_provider()` with `custom_llm_provider=None` and stripped a second provider prefix from a `provider/provider/model` deployment string. For a deployment configured as `openai/openai/openai/gpt-5.5`, the bridge flow sent `openai/gpt-5.5` to the upstream API instead of the correct `openai/openai/gpt-5.5`. Upstream APIs that enforce model-name allow-lists rejected this as `key_model_access_denied`. Fix: pass the locally-resolved `custom_llm_provider` into both the sync `responses()` and async `aresponses()` calls so the downstream `_resolve_model_provider_for_responses` sees an explicit provider and skips the second prefix-strip. New regression test `tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py` pins both call sites: each must forward `custom_llm_provider`. * fix(28505): set custom_llm_provider on request_data instead of as duplicate kwarg Greptile flagged that the previous patch passed custom_llm_provider as an explicit kwarg to responses()/aresponses() while request_data already carried it via the spread of sanitized_litellm_params, which would raise TypeError: got multiple values for keyword argument on every real bridge call. Switches to assigning request_data['custom_llm_provider'] before the call so the resolved provider wins over whatever sanitized_litellm_params spread in, without duplicating the kwarg. Updates the regression test to seed request_data with a sentinel custom_llm_provider so it actually exercises the overwrite path (the previous test mocked transform_request with a minimal dict and never hit the conflict). * chore: trigger shin-agent re-eval on retargeted staging base * chore: trigger shin-agent re-eval against updated Greptile state * Add 1-hour cache write pricing for EU/AU/JP Bedrock Anthropic models The 1-hour prompt-cache write tier (`cache_creation_input_token_cost_above_1hr`) was added to the us./global. variants of the Claude 4.5/4.6/4.7 family on Bedrock, but the eu./au./jp. cross-region inference profiles were left without it. AWS Bedrock pricing applies the same +10% regional premium across all geo profiles, so eu./au./jp. should carry the same 1-hour rates as us. (1.6x the 5-minute regional rate). Without these fields, cost tracking on EU/AU/JP Bedrock 1-hour-TTL prompt caching falls back to the 5-minute write rate and undercounts spend by ~60% for European, Australian, and Japanese tenants. Adds the 1-hour tier (and Sonnet 4.5's long-context >200K tier where AWS publishes one) to 14 regional Bedrock entries in both `model_prices_and_context_window.json` and the bundled `model_prices_and_context_window_backup.json`: - eu./au. Opus 4.6 ($11.00 / MTok) - eu./au. Opus 4.7 ($11.00 / MTok) - eu./au./jp. Sonnet 4.6 ($6.60 / MTok) - eu./au./jp. Sonnet 4.5 ($6.60 / MTok regular, $13.20 / MTok LC) - eu./au./jp. Haiku 4.5 ($2.20 / MTok) Also extends `tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py` with a `REGIONAL_EXPECTED` parametrized block covering all 13 new entries plus the existing 1.6x ratio invariant. Note: `eu.anthropic.claude-opus-4-5-20251101-v1:0` carries the wrong 5m rate today (base 6.25e-06 instead of regional 6.875e-06), which would break the 1.6x ratio check. It is intentionally left out of this PR so the scope stays "1-hour cache tier addition" — a separate follow-up should correct the EU 5m rates for Opus 4.5. --------- Co-authored-by: Terrajlz Co-authored-by: Bruno Devaux Co-authored-by: Sameer Kankute * Add 1-hour cache write pricing tier for Vertex AI Anthropic models (#28569) * fix(thinking): handle None thinking param in is_thinking_enabled (#28598) Squash-merged by litellm-agent from Terrajlz's PR. * feat(helm): support tpl rendering in podAnnotations (#28609) Squash-merged by litellm-agent from devauxbr's PR. * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) (#28575) * Forward custom_llm_provider through the Responses API bridge (Fixes #28505) When a Chat Completions request to a GPT-5.4+ model contains both `tools` and `reasoning_effort`, `completion()` auto-routes through `responses_api_bridge`. The bridge handler called `litellm.responses()` / `litellm.aresponses()` without forwarding the already-resolved `custom_llm_provider`, so the downstream call re-invoked `get_llm_provider()` with `custom_llm_provider=None` and stripped a second provider prefix from a `provider/provider/model` deployment string. For a deployment configured as `openai/openai/openai/gpt-5.5`, the bridge flow sent `openai/gpt-5.5` to the upstream API instead of the correct `openai/openai/gpt-5.5`. Upstream APIs that enforce model-name allow-lists rejected this as `key_model_access_denied`. Fix: pass the locally-resolved `custom_llm_provider` into both the sync `responses()` and async `aresponses()` calls so the downstream `_resolve_model_provider_for_responses` sees an explicit provider and skips the second prefix-strip. New regression test `tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py` pins both call sites: each must forward `custom_llm_provider`. * fix(28505): set custom_llm_provider on request_data instead of as duplicate kwarg Greptile flagged that the previous patch passed custom_llm_provider as an explicit kwarg to responses()/aresponses() while request_data already carried it via the spread of sanitized_litellm_params, which would raise TypeError: got multiple values for keyword argument on every real bridge call. Switches to assigning request_data['custom_llm_provider'] before the call so the resolved provider wins over whatever sanitized_litellm_params spread in, without duplicating the kwarg. Updates the regression test to seed request_data with a sentinel custom_llm_provider so it actually exercises the overwrite path (the previous test mocked transform_request with a minimal dict and never hit the conflict). * chore: trigger shin-agent re-eval on retargeted staging base * chore: trigger shin-agent re-eval against updated Greptile state * Add 1-hour cache write pricing tier for Vertex AI Anthropic models GCP Vertex AI publishes a separate 1-hour cache write column for the Claude family (1.6x the 5-minute write rate, matching the documented Bedrock ratio). LiteLLM's Vertex AI Anthropic entries only carry the 5-minute tier, so any request that uses `cache_control: {"ttl": "1h"}` on Vertex AI Claude is undercounted in cost tracking by ~60%. The runtime side already supports the 1-hour tier — `VertexAIAnthropicConfig` extends `AnthropicConfig`, populating `ephemeral_1h_input_tokens`, and `_calculate_cache_creation_cost` reads `cache_creation_input_token_cost_above_1hr`. Only the price registry was missing data. Adds the field to 19 vertex_ai/claude-* entries across both `model_prices_and_context_window.json` and the bundled `model_prices_and_context_window_backup.json`: - Haiku 4.5 ($1.25 -> $2.00 / MTok) - Sonnet 3.7 / 4 / 4.5 / 4.6 ($3.75 -> $6.00 / MTok) - Opus 4.5 / 4.6 / 4.7 ($6.25 -> $10.00 / MTok) - Opus 4 / 4.1 ($18.75 -> $30.00 / MTok) Adds `tests/test_litellm/test_vertex_anthropic_1hr_cache_pricing.py` mirroring the Bedrock equivalent — pins each (5m, 1h) pair per model and asserts the 1.6x ratio across the family. Fixes #27781. --------- Co-authored-by: Terrajlz Co-authored-by: Bruno Devaux Co-authored-by: Sameer Kankute * Fix Gemini multimodal function responses (#29325) Co-authored-by: shin-berri Co-authored-by: yuneng-jiang * address greptile review: add _transform_image_usage method and model-map supports_image_size flag - Add _transform_image_usage instance method to GoogleImageGenConfig that delegates to transform_gemini_image_usage, fixing the regression test - Replace hardcoded "2.5-flash" string check in supports_gemini_image_size with a get_model_info lookup on supports_image_size (default true) - Add supports_image_size: false to all gemini-2.5-flash model entries in model_prices_and_context_window.json so capability is controlled via the model map rather than embedded in code * fix test failures: schema validation, mypy type, model info plumbing, pricing test - Add supports_image_size to ModelInfoBase TypedDict so get_model_info surfaces it - Pass supports_image_size through _get_model_info_helper constructor call - Fix supports_gemini_image_size to use value is not False (None means unset, defaults to True) - Add supports_image_size to JSON schema in test_aaamodel_prices_and_context_window_json_is_valid - Correct gemini-3.1-flash-lite pricing assertions in test to match JSON values * Add Azure AI Kimi K2.6 metadata (#27052) * Add Azure AI Kimi K2.6 metadata * Scope Kimi metadata test cost map setup * fall back to substring check for models not in model_prices_and_context_window.json Models like gemini-2.5-flash-image-preview are not in the pricing JSON, so get_model_info raises. Fall back to "2.5-flash" not in model when the JSON has no explicit supports_image_size entry for the model. * fix(inception): don't forward global litellm.api_key to Inception FIM Match the Inception chat config: resolve only an Inception-specific key (param, litellm.inception_key, or INCEPTION_API_KEY) for the text-completion FIM path. The global litellm.api_key (often an OpenAI key) was both leaking to api.inceptionlabs.ai and taking precedence over the configured Inception key when set. * fix(auth): enforce end-user budget on custom-auth path that skips common_checks get_end_user_object() no longer raises BudgetExceededError, so custom-auth deployments with custom_auth_run_common_checks unset (which skip the centralized common_checks gate) stopped enforcing the end-user budget, letting an over-budget end user keep making requests. Re-enforce the budget in _run_post_custom_auth_checks on that path. --------- Signed-off-by: José Luis Di Biase Co-authored-by: Isha <72744901+IshaMeera@users.noreply.github.com> Co-authored-by: aneeshsangvikar Co-authored-by: shin-berri Co-authored-by: yuneng-jiang Co-authored-by: Aneesh-Fiddler Co-authored-by: Suleiman Elkhoury <108065141+suleimanelkhoury@users.noreply.github.com> Co-authored-by: Dmitriy Alergant <93501479+DmitriyAlergant@users.noreply.github.com> Co-authored-by: Yanis Miraoui Co-authored-by: Lovro Seder Co-authored-by: Thomas Mildner <12685945+Thomas-Mildner@users.noreply.github.com> Co-authored-by: José Luis Di Biase Co-authored-by: Lai Quang Huy <64073540+1qh@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Terrajlz Co-authored-by: Bruno Devaux Co-authored-by: ZHONG Ziwen <67355585+zzw-math@users.noreply.github.com> Co-authored-by: Emerson Gomes Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/__init__.py | 17 + litellm/_lazy_imports_registry.py | 10 + .../handler.py | 15 + litellm/constants.py | 4 + litellm/integrations/opentelemetry.py | 14 + .../opik/opik_payload_builder/extractors.py | 24 +- .../get_llm_provider_logic.py | 10 + .../litellm_core_utils/llm_cost_calc/utils.py | 50 +- .../prompt_templates/factory.py | 12 +- litellm/llms/gemini/common_utils.py | 243 +++++- .../llms/gemini/image_edit/cost_calculator.py | 23 +- .../llms/gemini/image_edit/transformation.py | 67 +- .../gemini/image_generation/transformation.py | 99 +-- .../llms/gemini/image_usage_transformation.py | 73 ++ litellm/llms/inception/__init__.py | 0 litellm/llms/inception/chat/__init__.py | 0 litellm/llms/inception/chat/transformation.py | 54 ++ litellm/llms/inception/completion/__init__.py | 0 .../inception/completion/transformation.py | 43 ++ .../llms/vertex_ai/gemini/transformation.py | 14 +- litellm/main.py | 62 ++ ...odel_prices_and_context_window_backup.json | 703 +++++++++--------- litellm/proxy/agent_endpoints/endpoints.py | 122 ++- litellm/proxy/auth/auth_checks.py | 14 +- litellm/proxy/auth/user_api_key_auth.py | 12 +- litellm/router.py | 8 + litellm/types/images/main.py | 1 + litellm/types/llms/gemini.py | 7 +- litellm/types/llms/openai.py | 1 + litellm/types/llms/vertex_ai.py | 6 + litellm/types/utils.py | 3 + litellm/utils.py | 30 + model_prices_and_context_window.json | 141 +++- provider_endpoints_support.json | 18 + tests/llm_translation/test_gemini.py | 201 +++++ tests/proxy_unit_tests/test_auth_checks.py | 67 +- .../test_default_end_user_budget_simple.py | 28 +- tests/proxy_unit_tests/test_proxy_server.py | 2 + .../completion_extras/__init__.py | 0 ...t_responses_bridge_provider_propagation.py | 116 +++ .../integrations/opik/test_opik_extractors.py | 84 +++ .../integrations/test_opentelemetry.py | 135 +++- ...llm_core_utils_prompt_templates_factory.py | 45 +- .../test_azure_ai_kimi_k26_metadata.py | 76 ++ .../test_gemini_image_edit_transformation.py | 111 ++- .../llms/gemini/test_cost_calculator.py | 186 ++++- ..._gemini_image_generation_transformation.py | 240 ++++++ tests/test_litellm/llms/inception/__init__.py | 0 .../test_inception_chat_transformation.py | 326 ++++++++ ...est_inception_completion_transformation.py | 300 ++++++++ ...st_tool_call_followed_by_text_assistant.py | 57 ++ .../test_vertex_ai_gemini_transformation.py | 181 ++--- .../proxy/auth/test_auth_checks.py | 40 +- .../auth/test_custom_auth_end_user_budget.py | 85 ++- ...est_bedrock_anthropic_1hr_cache_pricing.py | 33 +- tests/test_litellm/test_cost_calculator.py | 10 +- tests/test_litellm/test_router.py | 68 ++ tests/test_litellm/test_utils.py | 1 + ui/litellm-dashboard/src/app/layout.tsx | 2 +- 59 files changed, 3534 insertions(+), 760 deletions(-) create mode 100644 litellm/llms/gemini/image_usage_transformation.py create mode 100644 litellm/llms/inception/__init__.py create mode 100644 litellm/llms/inception/chat/__init__.py create mode 100644 litellm/llms/inception/chat/transformation.py create mode 100644 litellm/llms/inception/completion/__init__.py create mode 100644 litellm/llms/inception/completion/transformation.py create mode 100644 tests/test_litellm/completion_extras/__init__.py create mode 100644 tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py create mode 100644 tests/test_litellm/integrations/opik/test_opik_extractors.py create mode 100644 tests/test_litellm/llms/azure_ai/test_azure_ai_kimi_k26_metadata.py create mode 100644 tests/test_litellm/llms/gemini/test_gemini_image_generation_transformation.py create mode 100644 tests/test_litellm/llms/inception/__init__.py create mode 100644 tests/test_litellm/llms/inception/test_inception_chat_transformation.py create mode 100644 tests/test_litellm/llms/inception/test_inception_completion_transformation.py create mode 100644 tests/test_litellm/llms/vertex_ai/gemini/test_tool_call_followed_by_text_assistant.py diff --git a/litellm/__init__.py b/litellm/__init__.py index bae15f0362c..c954f5fd31e 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -278,6 +278,7 @@ ovhcloud_key: Optional[str] = None lemonade_key: Optional[str] = None sap_service_key: Optional[str] = None amazon_nova_api_key: Optional[str] = None +inception_key: Optional[str] = None common_cloud_provider_auth_params: dict = { "params": ["project", "region_name", "token"], "providers": ["vertex_ai", "bedrock", "watsonx", "azure", "vertex_ai_beta"], @@ -551,6 +552,7 @@ cohere_models: Set = set() cohere_chat_models: Set = set() mistral_chat_models: Set = set() text_completion_codestral_models: Set = set() +text_completion_inception_models: Set = set() anthropic_models: Set = set() openrouter_models: Set = set() datarobot_models: Set = set() @@ -628,6 +630,7 @@ publicai_models: Set = set() v0_models: Set = set() morph_models: Set = set() lambda_ai_models: Set = set() +inception_models: Set = set() hyperbolic_models: Set = set() black_forest_labs_models: Set = set() recraft_models: Set = set() @@ -792,6 +795,8 @@ def add_known_models(model_cost_map: Optional[Dict] = None): fireworks_ai_embedding_models.add(key) elif value.get("litellm_provider") == "text-completion-codestral": text_completion_codestral_models.add(key) + elif value.get("litellm_provider") == "text-completion-inception": + text_completion_inception_models.add(key) elif value.get("litellm_provider") == "xai": xai_models.add(key) elif value.get("litellm_provider") == "zai": @@ -878,6 +883,8 @@ def add_known_models(model_cost_map: Optional[Dict] = None): morph_models.add(key) elif value.get("litellm_provider") == "lambda_ai": lambda_ai_models.add(key) + elif value.get("litellm_provider") == "inception": + inception_models.add(key) elif value.get("litellm_provider") == "hyperbolic": hyperbolic_models.add(key) elif value.get("litellm_provider") == "black_forest_labs": @@ -980,6 +987,7 @@ model_list = list( | watsonx_models | gemini_models | text_completion_codestral_models + | text_completion_inception_models | xai_models | zai_models | fal_ai_models @@ -1018,6 +1026,7 @@ model_list = list( | v0_models | morph_models | lambda_ai_models + | inception_models | black_forest_labs_models | recraft_models | cometapi_models @@ -1074,6 +1083,7 @@ models_by_provider: dict = { "fireworks_ai": fireworks_ai_models | fireworks_ai_embedding_models, "aleph_alpha": aleph_alpha_models, "text-completion-codestral": text_completion_codestral_models, + "text-completion-inception": text_completion_inception_models, "xai": xai_models, "zai": zai_models, "fal_ai": fal_ai_models, @@ -1118,6 +1128,7 @@ models_by_provider: dict = { "v0": v0_models, "morph": morph_models, "lambda_ai": lambda_ai_models, + "inception": inception_models, "hyperbolic": hyperbolic_models, "black_forest_labs": black_forest_labs_models, "recraft": recraft_models, @@ -1869,6 +1880,9 @@ if TYPE_CHECKING: from .llms.codestral.completion.transformation import ( CodestralTextCompletionConfig as CodestralTextCompletionConfig, ) + from .llms.inception.completion.transformation import ( + InceptionTextCompletionConfig as InceptionTextCompletionConfig, + ) from .llms.azure.azure import ( AzureOpenAIAssistantsAPIConfig as AzureOpenAIAssistantsAPIConfig, ) @@ -1937,6 +1951,9 @@ if TYPE_CHECKING: from .llms.lambda_ai.chat.transformation import ( LambdaAIChatConfig as LambdaAIChatConfig, ) + from .llms.inception.chat.transformation import ( + InceptionChatConfig as InceptionChatConfig, + ) from .llms.hyperbolic.chat.transformation import ( HyperbolicChatConfig as HyperbolicChatConfig, ) diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py index 17eb6609292..bdc3289b87c 100644 --- a/litellm/_lazy_imports_registry.py +++ b/litellm/_lazy_imports_registry.py @@ -267,6 +267,7 @@ LLM_CONFIG_NAMES = ( "AIMLChatConfig", "VolcEngineChatConfig", "CodestralTextCompletionConfig", + "InceptionTextCompletionConfig", "AzureOpenAIAssistantsAPIConfig", "HerokuChatConfig", "CometAPIConfig", @@ -310,6 +311,7 @@ LLM_CONFIG_NAMES = ( "MorphChatConfig", "RAGFlowConfig", "LambdaAIChatConfig", + "InceptionChatConfig", "HyperbolicChatConfig", "VercelAIGatewayConfig", "OVHCloudChatConfig", @@ -1040,6 +1042,10 @@ _LLM_CONFIGS_IMPORT_MAP = { ".llms.codestral.completion.transformation", "CodestralTextCompletionConfig", ), + "InceptionTextCompletionConfig": ( + ".llms.inception.completion.transformation", + "InceptionTextCompletionConfig", + ), "AzureOpenAIAssistantsAPIConfig": ( ".llms.azure.azure", "AzureOpenAIAssistantsAPIConfig", @@ -1154,6 +1160,10 @@ _LLM_CONFIGS_IMPORT_MAP = { "MorphChatConfig": (".llms.morph.chat.transformation", "MorphChatConfig"), "RAGFlowConfig": (".llms.ragflow.chat.transformation", "RAGFlowConfig"), "LambdaAIChatConfig": (".llms.lambda_ai.chat.transformation", "LambdaAIChatConfig"), + "InceptionChatConfig": ( + ".llms.inception.chat.transformation", + "InceptionChatConfig", + ), "HyperbolicChatConfig": ( ".llms.hyperbolic.chat.transformation", "HyperbolicChatConfig", diff --git a/litellm/completion_extras/litellm_responses_transformation/handler.py b/litellm/completion_extras/litellm_responses_transformation/handler.py index 2de7bda6467..87c26b776e8 100644 --- a/litellm/completion_extras/litellm_responses_transformation/handler.py +++ b/litellm/completion_extras/litellm_responses_transformation/handler.py @@ -182,6 +182,14 @@ class ResponsesToCompletionBridgeHandler: client=kwargs.get("client"), ) + # Pin the resolved provider so `responses()` doesn't re-run + # `get_llm_provider()` on the model string and strip a second + # provider prefix (see GitHub issue #28505). request_data already + # carries `custom_llm_provider` via the spread of + # `sanitized_litellm_params`; overwriting it on the dict (rather + # than adding an explicit kwarg) avoids the duplicate-keyword + # TypeError that would otherwise fire on the real bridge path. + request_data["custom_llm_provider"] = custom_llm_provider result = responses( **request_data, ) @@ -268,6 +276,13 @@ class ResponsesToCompletionBridgeHandler: except Exception as e: raise e + # Pin the resolved provider so `aresponses()` doesn't re-run + # `get_llm_provider()` on the model string and strip a second + # provider prefix (see GitHub issue #28505). Set on request_data + # rather than passed as a separate kwarg to avoid the duplicate- + # keyword TypeError when `sanitized_litellm_params` already + # carries `custom_llm_provider`. + request_data["custom_llm_provider"] = custom_llm_provider result = await aresponses( **request_data, aresponses=True, diff --git a/litellm/constants.py b/litellm/constants.py index df15050e652..26e25d0cef3 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -585,6 +585,7 @@ LITELLM_CHAT_PROVIDERS = [ "volcengine", "codestral", "text-completion-codestral", + "text-completion-inception", "deepseek", "sambanova", "maritalk", @@ -620,6 +621,7 @@ LITELLM_CHAT_PROVIDERS = [ "oci", "morph", "lambda_ai", + "inception", "vercel_ai_gateway", "wandb", "ovhcloud", @@ -779,6 +781,7 @@ openai_compatible_endpoints: List = [ "https://api.v0.dev/v1", "https://api.morphllm.com/v1", "https://api.lambda.ai/v1", + "https://api.inceptionlabs.ai/v1", "https://api.hyperbolic.xyz/v1", "https://ai-gateway.helicone.ai/", "https://ai-gateway.vercel.sh/v1", @@ -835,6 +838,7 @@ openai_compatible_providers: List = [ "helicone", "morph", "lambda_ai", + "inception", "hyperbolic", "vercel_ai_gateway", "aiml", diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index ce5cfa2f525..24780eb4bfc 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -1012,6 +1012,13 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): litellm_params = kwargs.get("litellm_params", {}) or {} _metadata = litellm_params.get("metadata", {}) or {} proxy_span = _metadata.get("litellm_parent_otel_span", None) + + # Fallback: check litellm_metadata (used by /v1/messages and other + # LITELLM_METADATA_ROUTES). + if proxy_span is None: + _litellm_metadata = litellm_params.get("litellm_metadata", {}) or {} + proxy_span = _litellm_metadata.get("litellm_parent_otel_span", None) + if ( proxy_span is not None and getattr(proxy_span, "name", None) == LITELLM_PROXY_REQUEST_SPAN_NAME @@ -2718,6 +2725,13 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): _metadata = litellm_params.get("metadata", {}) or {} parent_otel_span = _metadata.get("litellm_parent_otel_span", None) + # Fallback: check litellm_metadata (used by /v1/messages and other + # LITELLM_METADATA_ROUTES that store proxy-internal metadata + # separately from the provider's native "metadata" field). + if parent_otel_span is None: + _litellm_metadata = litellm_params.get("litellm_metadata", {}) or {} + parent_otel_span = _litellm_metadata.get("litellm_parent_otel_span", None) + # Priority 1: Explicit parent span from metadata if parent_otel_span is not None: verbose_logger.debug( diff --git a/litellm/integrations/opik/opik_payload_builder/extractors.py b/litellm/integrations/opik/opik_payload_builder/extractors.py index 9779ccddacf..1e3a664acc1 100644 --- a/litellm/integrations/opik/opik_payload_builder/extractors.py +++ b/litellm/integrations/opik/opik_payload_builder/extractors.py @@ -39,20 +39,32 @@ def extract_opik_metadata( standard_logging_metadata: Dict[str, Any], ) -> Dict[str, Any]: """ - Extract and merge Opik metadata from request and requester. + Merge Opik metadata from three sources in increasing priority order: + + 1. user_api_key_auth_metadata– lowest priority (operator-level defaults) + 2. litellm_metadata (request)– overrides auth-key defaults + 3. requester_metadata – highest priority (e.g. proxy header overrides) Args: - litellm_metadata: Metadata from litellm_params - standard_logging_metadata: Metadata from standard_logging_object + litellm_metadata: Metadata from litellm_params.mak + standard_logging_metadata: Metadata from standard_logging_object. Returns: - Merged Opik metadata dictionary + Merged Opik metadata dictionary. """ - opik_meta = litellm_metadata.get("opik", {}).copy() + # Start with auth-key defaults (lowest priority). + auth_meta = standard_logging_metadata.get("user_api_key_auth_metadata") or {} + opik_meta = (auth_meta.get("opik") or {}).copy() + # Request-level values override auth-key defaults. + request_opik = litellm_metadata.get("opik") or {} + opik_meta.update(request_opik) + + # Requester-level values win over everything else. requester_metadata = standard_logging_metadata.get("requester_metadata", {}) or {} requester_opik = requester_metadata.get("opik", {}) or {} - opik_meta.update(requester_opik) + if requester_opik: + opik_meta.update(requester_opik) _logging.verbose_logger.debug( f"litellm_opik_metadata - {json.dumps(opik_meta, default=str)}" diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py index bb3f3fae9f0..a71000f00f8 100644 --- a/litellm/litellm_core_utils/get_llm_provider_logic.py +++ b/litellm/litellm_core_utils/get_llm_provider_logic.py @@ -373,6 +373,9 @@ def get_llm_provider( # noqa: PLR0915 elif endpoint == "https://api.lambda.ai/v1": custom_llm_provider = "lambda_ai" dynamic_api_key = get_secret_str("LAMBDA_API_KEY") + elif endpoint == "https://api.inceptionlabs.ai/v1": + custom_llm_provider = "inception" + dynamic_api_key = get_secret_str("INCEPTION_API_KEY") elif endpoint == "https://api.hyperbolic.xyz/v1": custom_llm_provider = "hyperbolic" dynamic_api_key = get_secret_str("HYPERBOLIC_API_KEY") @@ -954,6 +957,13 @@ def _get_openai_compatible_provider_info( # noqa: PLR0915 ) = litellm.LambdaAIChatConfig()._get_openai_compatible_provider_info( api_base, api_key ) + elif custom_llm_provider == "inception": + ( + api_base, + dynamic_api_key, + ) = litellm.InceptionChatConfig()._get_openai_compatible_provider_info( + api_base, api_key + ) elif custom_llm_provider == "hyperbolic": ( api_base, diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py index 882561ed2e8..f39c942f90f 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/utils.py +++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py @@ -34,6 +34,14 @@ _IMAGE_RESPONSE_CALL_TYPES = frozenset( _VALID_DATA_RESIDENCIES = frozenset(r.value for r in DataResidency) +def _get_token_detail_value(details: object, key: str) -> Optional[int]: + if isinstance(details, dict): + value = details.get(key) + else: + value = getattr(details, key, None) + return value if isinstance(value, int) else None + + def _is_above_128k(tokens: float) -> bool: if tokens > 128000: return True @@ -870,17 +878,47 @@ def calculate_image_response_cost_from_usage( cached_tokens=0, ) + output_tokens_details = getattr(usage, "completion_tokens_details", None) + if output_tokens_details is None: + output_tokens_details = getattr(usage, "output_tokens_details", None) + + if output_tokens_details is None: + completion_tokens_details = CompletionTokensDetailsWrapper( + text_tokens=0, + image_tokens=completion_tokens, + reasoning_tokens=0, + audio_tokens=0, + ) + else: + text_tokens = _get_token_detail_value(output_tokens_details, "text_tokens") or 0 + image_tokens = ( + _get_token_detail_value(output_tokens_details, "image_tokens") or 0 + ) + audio_tokens = ( + _get_token_detail_value(output_tokens_details, "audio_tokens") or 0 + ) + reasoning_tokens = ( + _get_token_detail_value(output_tokens_details, "reasoning_tokens") or 0 + ) + known_output_tokens = ( + text_tokens + image_tokens + audio_tokens + reasoning_tokens + ) + if completion_tokens > known_output_tokens: + text_tokens += completion_tokens - known_output_tokens + + completion_tokens_details = CompletionTokensDetailsWrapper( + text_tokens=text_tokens, + image_tokens=image_tokens, + reasoning_tokens=reasoning_tokens, + audio_tokens=audio_tokens, + ) + normalized_usage = Usage( prompt_tokens=prompt_tokens, completion_tokens=completion_tokens, total_tokens=total_tokens, prompt_tokens_details=prompt_tokens_details, - completion_tokens_details=CompletionTokensDetailsWrapper( - text_tokens=0, - image_tokens=completion_tokens, - reasoning_tokens=0, - audio_tokens=0, - ), + completion_tokens_details=completion_tokens_details, ) prompt_cost, completion_cost = generic_cost_per_token( diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py index 46e9b43a429..1460dbaf0a9 100644 --- a/litellm/litellm_core_utils/prompt_templates/factory.py +++ b/litellm/litellm_core_utils/prompt_templates/factory.py @@ -1670,15 +1670,15 @@ def convert_to_gemini_tool_call_result( # noqa: PLR0915 if gemini_call_id: _function_response["id"] = gemini_call_id - # Create part with function_response, and optionally inline_data for images (Computer Use) _part: VertexPartType = {"function_response": _function_response} - # For Computer Use, if we have images/files, we need separate parts: - # - One part with function_response - # - One part per inline_data item - # Gemini's PartType is a oneof, so we can't have both in the same part + # For multimodal function responses, Gemini expects media parts nested + # inside functionResponse.parts instead of sibling content parts. if inline_data_list: - return [_part] + [{"inline_data": d} for d in inline_data_list] + _function_response["parts"] = [ + {"inline_data": inline_data} for inline_data in inline_data_list + ] + return [_part] return _part diff --git a/litellm/llms/gemini/common_utils.py b/litellm/llms/gemini/common_utils.py index bc963d62b5f..42a807983b9 100644 --- a/litellm/llms/gemini/common_utils.py +++ b/litellm/llms/gemini/common_utils.py @@ -1,6 +1,8 @@ import base64 import datetime -from typing import Any, Dict, List, Optional, Union +import json +import math +from typing import Any, Dict, List, Optional, Sequence, Union import httpx @@ -12,6 +14,245 @@ from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import TokenCountResponse +GEMINI_IMAGE_ASPECT_RATIOS: Dict[str, float] = { + "1:1": 1 / 1, + "1:4": 1 / 4, + "1:8": 1 / 8, + "2:3": 2 / 3, + "3:2": 3 / 2, + "3:4": 3 / 4, + "4:1": 4 / 1, + "4:3": 4 / 3, + "4:5": 4 / 5, + "5:4": 5 / 4, + "8:1": 8 / 1, + "9:16": 9 / 16, + "16:9": 16 / 9, + "21:9": 21 / 9, +} + +# Supported aspect ratio dimensions from Google Gemini image generation docs: +# https://ai.google.dev/gemini-api/docs/image-generation#aspect_ratios_and_image_size +GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO: Dict[tuple[int, int], str] = { + (512, 512): "1:1", + (1024, 1024): "1:1", + (2048, 2048): "1:1", + (4096, 4096): "1:1", + (256, 1024): "1:4", + (512, 2048): "1:4", + (1024, 4096): "1:4", + (2048, 8192): "1:4", + (192, 1536): "1:8", + (384, 3072): "1:8", + (768, 6144): "1:8", + (1536, 12288): "1:8", + (424, 632): "2:3", + (848, 1264): "2:3", + (1696, 2528): "2:3", + (3392, 5056): "2:3", + (632, 424): "3:2", + (1264, 848): "3:2", + (2528, 1696): "3:2", + (5056, 3392): "3:2", + (448, 600): "3:4", + (896, 1200): "3:4", + (1792, 2400): "3:4", + (3584, 4800): "3:4", + (1024, 256): "4:1", + (2048, 512): "4:1", + (4096, 1024): "4:1", + (8192, 2048): "4:1", + (600, 448): "4:3", + (1200, 896): "4:3", + (2400, 1792): "4:3", + (4800, 3584): "4:3", + (464, 576): "4:5", + (928, 1152): "4:5", + (1856, 2304): "4:5", + (3712, 4608): "4:5", + (576, 464): "5:4", + (1152, 928): "5:4", + (2304, 1856): "5:4", + (4608, 3712): "5:4", + (1536, 192): "8:1", + (3072, 384): "8:1", + (6144, 768): "8:1", + (12288, 1536): "8:1", + (384, 688): "9:16", + (768, 1376): "9:16", + (1536, 2752): "9:16", + (3072, 5504): "9:16", + (688, 384): "16:9", + (1376, 768): "16:9", + (2752, 1536): "16:9", + (5504, 3072): "16:9", + (792, 336): "21:9", + (1584, 672): "21:9", + (3168, 1344): "21:9", + (6336, 2688): "21:9", + (1280, 896): "4:3", + (896, 1280): "3:4", +} + + +def map_openai_size_to_gemini_image_config( + size: str, model: str +) -> Optional[Dict[str, str]]: + dimensions = _parse_openai_image_size(size) + if dimensions is None: + return None + + width, height = dimensions + image_config = { + "aspectRatio": _map_dimensions_to_gemini_aspect_ratio(width, height) + } + image_size = _map_dimensions_to_gemini_image_size(width, height) + if is_gemini_image_model(model): + if supports_gemini_image_size(model): + image_config["imageSize"] = image_size + else: + image_config["imageSize"] = image_size + return image_config + + +def supports_gemini_image_size(model: str) -> bool: + try: + model_info = litellm.get_model_info(model=model) + value = model_info.get("supports_image_size") + if value is not None: + return bool(value) + except Exception: + pass + return "2.5-flash" not in model + + +def is_gemini_image_model(model: str) -> bool: + base_model = model.split("/", 1)[-1] + return "gemini" in base_model + + +def map_openai_image_params_to_gemini( + params: Dict[str, Any], + model: str, + supported_params: Sequence[str], + optional_params: Optional[Dict[str, Any]] = None, + parse_image_config_string: bool = False, +) -> Dict[str, Any]: + optional_params = optional_params or {} + filtered_params = { + key: value for key, value in params.items() if key in supported_params + } + + mapped_params: Dict[str, Any] = {} + + if "n" in filtered_params and "n" not in optional_params: + mapped_params["sampleCount"] = filtered_params["n"] + + if "size" in filtered_params and "size" not in optional_params: + image_config = map_openai_size_to_gemini_image_config( + filtered_params["size"], + model, + ) + if image_config is not None: + if is_gemini_image_model(model): + mapped_params["imageConfig"] = image_config + else: + mapped_params["aspectRatio"] = image_config["aspectRatio"] + if "imageSize" in image_config: + mapped_params["imageSize"] = image_config["imageSize"] + + image_config_param = filtered_params.get("imageConfig") + if isinstance(image_config_param, str) and parse_image_config_string: + try: + image_config_param = json.loads(image_config_param) + except json.JSONDecodeError as exc: + raise litellm.UnsupportedParamsError( + model=model, + message="`imageConfig` must be valid JSON when provided as a string.", + ) from exc + if isinstance(image_config_param, dict): + mapped_params["imageConfig"] = image_config_param + + for key, value in filtered_params.items(): + if key not in ("n", "size", "imageConfig") and key not in optional_params: + mapped_params[key] = value + + return mapped_params + + +def get_gemini_image_generation_config( + model: str, + optional_params: Dict[str, Any], +) -> Dict[str, Any]: + generation_config: Dict[str, Any] = {"response_modalities": ["IMAGE", "TEXT"]} + + image_config: Dict[str, Any] = {} + if isinstance(optional_params.get("imageConfig"), dict): + image_config.update(optional_params["imageConfig"]) + + if not supports_gemini_image_size(model): + image_config.pop("imageSize", None) + + if image_config: + generation_config["imageConfig"] = image_config + + candidate_count = next( + ( + optional_params[key] + for key in ("candidateCount", "candidate_count", "sampleCount", "n") + if optional_params.get(key) is not None + ), + None, + ) + if candidate_count is not None: + generation_config["candidateCount"] = candidate_count + + return generation_config + + +def _parse_openai_image_size(size: str) -> Optional[tuple[int, int]]: + if size == "auto": + return None + + width_str, separator, height_str = size.lower().partition("x") + if not separator: + return None + + try: + width = int(width_str) + height = int(height_str) + except ValueError: + return None + + if width <= 0 or height <= 0: + return None + + return width, height + + +def _map_dimensions_to_gemini_aspect_ratio(width: int, height: int) -> str: + if (width, height) in GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO: + return GEMINI_IMAGE_SIZE_TO_ASPECT_RATIO[(width, height)] + + requested_ratio = width / height + return min( + GEMINI_IMAGE_ASPECT_RATIOS, + key=lambda aspect_ratio: abs( + math.log(GEMINI_IMAGE_ASPECT_RATIOS[aspect_ratio] / requested_ratio) + ), + ) + + +def _map_dimensions_to_gemini_image_size(width: int, height: int) -> str: + effective_square_side = math.sqrt(width * height) + if effective_square_side < 768: + return "512" + if effective_square_side < 1536: + return "1K" + if effective_square_side < 3072: + return "2K" + return "4K" + class GeminiError(BaseLLMException): pass diff --git a/litellm/llms/gemini/image_edit/cost_calculator.py b/litellm/llms/gemini/image_edit/cost_calculator.py index 2e332a7fc00..956edb849a0 100644 --- a/litellm/llms/gemini/image_edit/cost_calculator.py +++ b/litellm/llms/gemini/image_edit/cost_calculator.py @@ -4,8 +4,9 @@ Gemini Image Edit Cost Calculator from typing import Any -import litellm -from litellm.types.utils import ImageResponse +from litellm.llms.gemini.image_generation.cost_calculator import ( + cost_calculator as image_generation_cost_calculator, +) def cost_calculator( @@ -15,20 +16,10 @@ def cost_calculator( """ Gemini image edit cost calculator. - Mirrors image generation pricing: charge per returned image based on - model metadata (`output_cost_per_image`). + Gemini image edits and generations share image response billing behavior: + use provider token usage when present, otherwise fall back to per-image pricing. """ - model_info = litellm.get_model_info( + return image_generation_cost_calculator( model=model, - custom_llm_provider="gemini", + image_response=image_response, ) - - output_cost_per_image: float = model_info.get("output_cost_per_image") or 0.0 - - if not isinstance(image_response, ImageResponse): - raise ValueError( - f"image_response must be of type ImageResponse got type={type(image_response)}" - ) - - num_images = len(image_response.data or []) - return output_cost_per_image * num_images diff --git a/litellm/llms/gemini/image_edit/transformation.py b/litellm/llms/gemini/image_edit/transformation.py index c8aaab0e14e..2316361d6e7 100644 --- a/litellm/llms/gemini/image_edit/transformation.py +++ b/litellm/llms/gemini/image_edit/transformation.py @@ -7,10 +7,22 @@ from httpx._types import RequestFiles from litellm.images.utils import ImageEditRequestUtils from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig +from litellm.llms.gemini.common_utils import ( + get_gemini_image_generation_config, + map_openai_image_params_to_gemini, +) +from litellm.llms.gemini.image_usage_transformation import ( + transform_gemini_image_usage, +) from litellm.secret_managers.main import get_secret_str from litellm.types.images.main import ImageEditOptionalRequestParams from litellm.types.router import GenericLiteLLMParams -from litellm.types.utils import FileTypes, ImageObject, ImageResponse, OpenAIImage +from litellm.types.utils import ( + FileTypes, + ImageObject, + ImageResponse, + OpenAIImage, +) if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj @@ -22,7 +34,7 @@ else: class GeminiImageEditConfig(BaseImageEditConfig): DEFAULT_BASE_URL: str = "https://generativelanguage.googleapis.com/v1beta" - SUPPORTED_PARAMS: List[str] = ["size"] + SUPPORTED_PARAMS: List[str] = ["n", "size", "imageConfig"] def get_supported_openai_params(self, model: str) -> List[str]: return list(self.SUPPORTED_PARAMS) @@ -33,21 +45,12 @@ class GeminiImageEditConfig(BaseImageEditConfig): model: str, drop_params: bool, ) -> Dict[str, Any]: - supported_params = self.get_supported_openai_params(model) - filtered_params = { - key: value - for key, value in image_edit_optional_params.items() - if key in supported_params - } - - mapped_params: Dict[str, Any] = {} - - if "size" in filtered_params: - mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio( - filtered_params["size"] # type: ignore[arg-type] - ) - - return mapped_params + return map_openai_image_params_to_gemini( + params=image_edit_optional_params, # type: ignore[arg-type] + model=model, + supported_params=self.get_supported_openai_params(model), + parse_image_config_string=True, + ) def validate_environment( self, @@ -107,18 +110,10 @@ class GeminiImageEditConfig(BaseImageEditConfig): request_body: Dict[str, Any] = {"contents": contents} - generation_config: Dict[str, Any] = {} - - if "aspectRatio" in image_edit_optional_request_params: - # Move aspectRatio into imageConfig inside generationConfig - if "imageConfig" not in generation_config: - generation_config["imageConfig"] = {} - generation_config["imageConfig"]["aspectRatio"] = ( - image_edit_optional_request_params["aspectRatio"] - ) - - if generation_config: - request_body["generationConfig"] = generation_config + request_body["generationConfig"] = get_gemini_image_generation_config( + model=model, + optional_params=image_edit_optional_request_params, + ) empty_files = cast(RequestFiles, []) return request_body, empty_files @@ -156,18 +151,12 @@ class GeminiImageEditConfig(BaseImageEditConfig): ) model_response.data = cast(List[OpenAIImage], data_list) + if "usageMetadata" in response_json: + model_response.usage = transform_gemini_image_usage( + response_json["usageMetadata"] + ) return model_response - def _map_size_to_aspect_ratio(self, size: str) -> str: - aspect_ratio_map = { - "1024x1024": "1:1", - "1792x1024": "16:9", - "1024x1792": "9:16", - "1280x896": "4:3", - "896x1280": "3:4", - } - return aspect_ratio_map.get(size, "1:1") - def _prepare_inline_image_parts( self, image: Union[FileTypes, List[FileTypes]] ) -> List[Dict[str, Any]]: diff --git a/litellm/llms/gemini/image_generation/transformation.py b/litellm/llms/gemini/image_generation/transformation.py index 9c4cd008b8c..e6770a76bcb 100644 --- a/litellm/llms/gemini/image_generation/transformation.py +++ b/litellm/llms/gemini/image_generation/transformation.py @@ -5,18 +5,21 @@ import httpx from litellm.llms.base_llm.image_generation.transformation import ( BaseImageGenerationConfig, ) +from litellm.llms.gemini.common_utils import ( + get_gemini_image_generation_config, + is_gemini_image_model, + map_openai_image_params_to_gemini, +) +from litellm.llms.gemini.image_usage_transformation import ( + transform_gemini_image_usage, +) from litellm.secret_managers.main import get_secret_str from litellm.types.llms.gemini import GeminiImageGenerationRequest from litellm.types.llms.openai import ( AllMessageValues, OpenAIImageGenerationOptionalParams, ) -from litellm.types.utils import ( - ImageObject, - ImageResponse, - ImageUsage, - ImageUsageInputTokensDetails, -) +from litellm.types.utils import ImageObject, ImageResponse if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj @@ -36,7 +39,10 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): Google AI Imagen API supported parameters https://ai.google.dev/gemini-api/docs/imagen """ - return ["n", "size"] + supported_params = ["n", "size"] + if is_gemini_image_model(model): + supported_params.append("imageConfig") + return supported_params # type: ignore[return-value] def map_openai_params( self, @@ -45,64 +51,11 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): model: str, drop_params: bool, ) -> dict: - supported_params = self.get_supported_openai_params(model) - mapped_params = {} - - for k, v in non_default_params.items(): - if k not in optional_params.keys(): - if k in supported_params: - # Map OpenAI parameters to Google format - if k == "n": - mapped_params["sampleCount"] = v - elif k == "size": - # Map OpenAI size format to Google aspectRatio - mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio(v) - else: - mapped_params[k] = v - return mapped_params - - def _map_size_to_aspect_ratio(self, size: str) -> str: - """ - https://ai.google.dev/gemini-api/docs/image-generation - - """ - aspect_ratio_map = { - "1024x1024": "1:1", - "1792x1024": "16:9", - "1024x1792": "9:16", - "1280x896": "4:3", - "896x1280": "3:4", - } - return aspect_ratio_map.get(size, "1:1") - - def _transform_image_usage(self, usage_metadata: dict) -> ImageUsage: - """ - Transform Gemini usageMetadata to ImageUsage format - """ - input_tokens_details = ImageUsageInputTokensDetails( - image_tokens=0, - text_tokens=0, - ) - - # Extract detailed token counts from promptTokensDetails - tokens_details = usage_metadata.get("promptTokensDetails", []) - for details in tokens_details: - if isinstance(details, dict): - modality = str(details.get("modality", "")).upper() - raw_token_count = details.get( - "tokenCount", details.get("token_count", 0) - ) - token_count = raw_token_count if isinstance(raw_token_count, int) else 0 - if modality == "TEXT": - input_tokens_details.text_tokens += token_count - elif modality == "IMAGE": - input_tokens_details.image_tokens += token_count - - return ImageUsage( - input_tokens=usage_metadata.get("promptTokenCount", 0), - input_tokens_details=input_tokens_details, - output_tokens=usage_metadata.get("candidatesTokenCount", 0), - total_tokens=usage_metadata.get("totalTokenCount", 0), + return map_openai_image_params_to_gemini( + params=non_default_params, + model=model, + supported_params=self.get_supported_openai_params(model), + optional_params=optional_params, ) def get_complete_url( @@ -127,7 +80,7 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): complete_url = complete_url.rstrip("/") # Gemini Flash Image Preview models use generateContent endpoint - if "gemini" in model: + if is_gemini_image_model(model): complete_url = f"{complete_url}/models/{model}:generateContent" else: # All other Imagen models use predict endpoint @@ -179,10 +132,13 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): } """ # For Gemini Flash Image Preview models, use standard Gemini format - if "gemini" in model: + if is_gemini_image_model(model): request_body: dict = { "contents": [{"parts": [{"text": prompt}]}], - "generationConfig": {"response_modalities": ["IMAGE", "TEXT"]}, + "generationConfig": get_gemini_image_generation_config( + model=model, + optional_params=optional_params, + ), } return request_body else: @@ -200,6 +156,9 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): ) return request_body_obj.model_dump(exclude_none=True) + def _transform_image_usage(self, usage_metadata: dict): + return transform_gemini_image_usage(usage_metadata) + def transform_image_generation_response( self, model: str, @@ -229,7 +188,7 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): model_response.data = [] # Handle different response formats based on model - if "gemini" in model: + if is_gemini_image_model(model): # Gemini Flash Image Preview models return in candidates format candidates = response_data.get("candidates", []) for candidate in candidates: @@ -255,7 +214,7 @@ class GoogleImageGenConfig(BaseImageGenerationConfig): # Extract usage metadata for Gemini models if "usageMetadata" in response_data: - model_response.usage = self._transform_image_usage( + model_response.usage = transform_gemini_image_usage( response_data["usageMetadata"] ) else: diff --git a/litellm/llms/gemini/image_usage_transformation.py b/litellm/llms/gemini/image_usage_transformation.py new file mode 100644 index 00000000000..5a55bdeffb1 --- /dev/null +++ b/litellm/llms/gemini/image_usage_transformation.py @@ -0,0 +1,73 @@ +from typing import Any + +from litellm.types.utils import ImageUsage, ImageUsageInputTokensDetails + + +def _get_token_count(details: dict) -> int: + raw_token_count = details.get("tokenCount", details.get("token_count", 0)) + return raw_token_count if isinstance(raw_token_count, int) else 0 + + +def _get_modality_token_details(usage_metadata: dict, *details_keys: str) -> list: + for details_key in details_keys: + details = usage_metadata.get(details_key) + if isinstance(details, list): + return details + return [] + + +def _sum_modality_token_details( + usage_metadata: dict, *details_keys: str +) -> ImageUsageInputTokensDetails: + tokens_details = ImageUsageInputTokensDetails( + image_tokens=0, + text_tokens=0, + ) + + for details in _get_modality_token_details(usage_metadata, *details_keys): + if isinstance(details, dict): + modality = str(details.get("modality", "")).upper() + token_count = _get_token_count(details) + if modality == "TEXT": + tokens_details.text_tokens += token_count + elif modality == "IMAGE": + tokens_details.image_tokens += token_count + + return tokens_details + + +def transform_gemini_image_usage(usage_metadata: dict) -> ImageUsage: + """ + Transform Gemini usageMetadata to ImageUsage format. + """ + input_tokens_details = _sum_modality_token_details( + usage_metadata, "promptTokensDetails", "prompt_tokens_details" + ) + output_tokens = usage_metadata.get("candidatesTokenCount", 0) + output_tokens_details = _sum_modality_token_details( + usage_metadata, "candidatesTokensDetails", "candidates_tokens_details" + ) + + if not _get_modality_token_details( + usage_metadata, "candidatesTokensDetails", "candidates_tokens_details" + ): + output_tokens_details.image_tokens = output_tokens + else: + known_output_tokens = ( + output_tokens_details.text_tokens + output_tokens_details.image_tokens + ) + if output_tokens > known_output_tokens: + output_tokens_details.text_tokens += output_tokens - known_output_tokens + + usage_payload: dict[str, Any] = { + "input_tokens": usage_metadata.get("promptTokenCount", 0), + "input_tokens_details": input_tokens_details, + "output_tokens": output_tokens, + "total_tokens": usage_metadata.get("totalTokenCount", 0), + "prompt_tokens": usage_metadata.get("promptTokenCount", 0), + "prompt_tokens_details": input_tokens_details.model_dump(), + "completion_tokens": output_tokens, + "completion_tokens_details": output_tokens_details.model_dump(), + "output_tokens_details": output_tokens_details.model_dump(), + } + return ImageUsage(**usage_payload) diff --git a/litellm/llms/inception/__init__.py b/litellm/llms/inception/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/inception/chat/__init__.py b/litellm/llms/inception/chat/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/inception/chat/transformation.py b/litellm/llms/inception/chat/transformation.py new file mode 100644 index 00000000000..d591f783a99 --- /dev/null +++ b/litellm/llms/inception/chat/transformation.py @@ -0,0 +1,54 @@ +""" +Translate from OpenAI's `/v1/chat/completions` to Inception's `/v1/chat/completions` + +Inception Labs (https://www.inceptionlabs.ai) serves the Mercury family of +diffusion LLMs through an OpenAI-compatible API, so we only need to point the +OpenAI-like handler at the Inception API base and pick up the Inception API key. +""" + +from typing import List, Optional, Tuple + +import litellm +from litellm.secret_managers.main import get_secret_str + +from ...openai_like.chat.transformation import OpenAILikeChatConfig + + +class InceptionChatConfig(OpenAILikeChatConfig): + """ + Inception is OpenAI-compatible with standard endpoints + """ + + @property + def custom_llm_provider(self) -> Optional[str]: + return "inception" + + def get_supported_openai_params(self, model: str) -> List: + return [ + "max_tokens", + "max_completion_tokens", + "temperature", + "stop", + "tools", + "tool_choice", + "stream", + "stream_options", + "response_format", + "reasoning_effort", + "reasoning_summary", + "reasoning_summary_wait", + "diffusing", + "realtime", + ] + + def _get_openai_compatible_provider_info( + self, api_base: Optional[str], api_key: Optional[str] + ) -> Tuple[Optional[str], Optional[str]]: + passed_api_base = api_base + api_base = api_base or get_secret_str("INCEPTION_API_BASE") or "https://api.inceptionlabs.ai/v1" # type: ignore + dynamic_api_key = api_key + if passed_api_base is None or api_key: + dynamic_api_key = ( + api_key or litellm.inception_key or get_secret_str("INCEPTION_API_KEY") + ) + return api_base, dynamic_api_key diff --git a/litellm/llms/inception/completion/__init__.py b/litellm/llms/inception/completion/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/inception/completion/transformation.py b/litellm/llms/inception/completion/transformation.py new file mode 100644 index 00000000000..1035042f6bf --- /dev/null +++ b/litellm/llms/inception/completion/transformation.py @@ -0,0 +1,43 @@ +""" +Inception fill-in-the-middle (FIM) completions. + +Inception's FIM endpoint is OpenAI text-completion compatible: it takes a +`prompt` (prefix) plus an optional `suffix` and returns standard +`choices[].text`. It is served at `/v1/fim/completions` rather than +`/v1/completions`, so routing points the OpenAI client at the `/v1/fim` base +(see the `text-completion-inception` branch in `main.py`). +""" + +from typing import List + +from litellm.llms.openai.completion.transformation import OpenAITextCompletionConfig + + +class InceptionTextCompletionConfig(OpenAITextCompletionConfig): + def get_supported_openai_params(self, model: str) -> List: + return [ + "suffix", + "max_tokens", + "max_completion_tokens", + "top_p", + "frequency_penalty", + "presence_penalty", + "stop", + "stream", + "stream_options", + ] + + def map_openai_params( + self, + non_default_params: dict, + optional_params: dict, + model: str, + drop_params: bool, + ) -> dict: + supported_params = self.get_supported_openai_params(model) + for param, value in non_default_params.items(): + if param == "max_completion_tokens": + optional_params["max_tokens"] = value + elif param in supported_params: + optional_params[param] = value + return optional_params diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py index 4f5846cc5b6..ef7bf82bfae 100644 --- a/litellm/llms/vertex_ai/gemini/transformation.py +++ b/litellm/llms/vertex_ai/gemini/transformation.py @@ -996,7 +996,19 @@ def _gemini_convert_messages_with_history( # noqa: PLR0915 excluded_keys=["thoughtSignature"], ): assistant_content.append(gemini_tool_call_part) - last_message_with_tool_calls = assistant_msg + # Only record this as the active tool-call message when it actually + # carries tool calls. The `if` guard above is also entered for a + # text-only assistant message (`assistant_msg.get("tool_calls", []) + # is not None` is True for an empty list), so without this check a + # later assistant message with no tool calls would clobber the + # reference. The following tool result would then be matched against + # an assistant message that has no tool_calls, raising "Missing + # corresponding tool call for tool response message". + if ( + assistant_msg.get("tool_calls") + or assistant_msg.get("function_call") is not None + ): + last_message_with_tool_calls = assistant_msg ## HANDLE SERVER-SIDE TOOL INVOCATIONS (context circulation) _psf = assistant_msg.get("provider_specific_fields") diff --git a/litellm/main.py b/litellm/main.py index 3ef094042e8..da8624d11b8 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -641,6 +641,7 @@ async def acompletion( # noqa: PLR0915 if ( custom_llm_provider == "text-completion-openai" or custom_llm_provider == "text-completion-codestral" + or custom_llm_provider == "text-completion-inception" ) and isinstance(response, TextCompletionResponse): response = litellm.OpenAITextCompletionConfig().convert_to_chat_model_response_object( response_object=response, @@ -3803,6 +3804,67 @@ def completion( # type: ignore # noqa: PLR0915 ): return _model_response response = _model_response + elif custom_llm_provider == "text-completion-inception": + passed_api_base = ( + api_base + or optional_params.pop("api_base", None) + or optional_params.pop("base_url", None) + ) + api_base = ( + passed_api_base + or get_secret_str("INCEPTION_API_BASE") + or "https://api.inceptionlabs.ai/v1" + ) + # FIM is served at `/v1/fim/completions`; the OpenAI client appends + # `/completions`, so point it at the `/v1/fim` base. + api_base = api_base.rstrip("/") + if not api_base.endswith("/fim"): + api_base += "/fim" + + # Don't forward the server-managed Inception key to a caller-supplied + # api_base; only resolve it for the default/server base, or when the + # caller passes their own key. + if passed_api_base is None or api_key: + api_key = ( + api_key + or litellm.inception_key + or get_secret_str("INCEPTION_API_KEY") + ) + + _response = openai_text_completions.completion( + model=model, + messages=messages, + model_response=model_response, + print_verbose=print_verbose, + api_key=api_key, # type: ignore[arg-type] + custom_llm_provider="text-completion-inception", + api_base=api_base, + acompletion=acompletion, + client=client, + logging_obj=logging, + optional_params=optional_params, + litellm_params=litellm_params, + logger_fn=logger_fn, + timeout=timeout, # type: ignore + ) + + if ( + optional_params.get("stream", False) is False + and acompletion is False + and text_completion is False + ): + _response = litellm.OpenAITextCompletionConfig().convert_to_chat_model_response_object( + response_object=_response, model_response_object=model_response + ) + + if optional_params.get("stream", False) or acompletion is True: + logging.post_call( + input=messages, + api_key=api_key, + original_response=_response, + additional_args={"headers": headers}, + ) + response = _response elif custom_llm_provider in ("sagemaker_chat", "sagemaker_nova"): # boto3 reads keys from .env # sagemaker_chat: HF Messages API endpoints diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index a604aafa540..ed6de4fa6b7 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1075,6 +1075,7 @@ }, "eu.anthropic.claude-opus-4-6-v1": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1104,6 +1105,7 @@ }, "au.anthropic.claude-opus-4-6-v1": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1241,6 +1243,7 @@ }, "eu.anthropic.claude-opus-4-7": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1271,6 +1274,7 @@ }, "au.anthropic.claude-opus-4-7": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1543,6 +1547,7 @@ }, "eu.anthropic.claude-sonnet-4-6": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "litellm_provider": "bedrock_converse", @@ -1571,6 +1576,7 @@ }, "au.anthropic.claude-sonnet-4-6": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "litellm_provider": "bedrock_converse", @@ -1599,6 +1605,7 @@ }, "jp.anthropic.claude-sonnet-4-6": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "litellm_provider": "bedrock_converse", @@ -1995,11 +2002,13 @@ }, "au.anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "input_cost_per_token_above_200k_tokens": 6.6e-06, "output_cost_per_token_above_200k_tokens": 2.475e-05, "cache_creation_input_token_cost_above_200k_tokens": 8.25e-06, + "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -7494,6 +7503,27 @@ "supports_video_input": true, "supports_vision": true }, + "azure_ai/kimi-k2.6": { + "input_cost_per_token": 9.5e-07, + "litellm_provider": "azure_ai", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-kimi-k2-6-in-microsoft-foundry/4513125", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure_ai/ministral-3b": { "input_cost_per_token": 4e-08, "litellm_provider": "azure_ai", @@ -12682,7 +12712,8 @@ "litellm_provider": "deepinfra", "mode": "chat", "supports_tool_choice": true, - "supports_function_calling": true + "supports_function_calling": true, + "supports_image_size": false }, "deepinfra/google/gemini-2.5-pro": { "max_tokens": 1000000, @@ -13583,6 +13614,7 @@ }, "eu.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_1hr": 2.2e-06, "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "deprecation_date": "2026-10-15", @@ -13787,11 +13819,13 @@ }, "eu.anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "input_cost_per_token_above_200k_tokens": 6.6e-06, "output_cost_per_token_above_200k_tokens": 2.475e-05, "cache_creation_input_token_cost_above_200k_tokens": 8.25e-06, + "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -15006,7 +15040,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini-2.5-flash-image": { "cache_read_input_token_cost": 3e-08, @@ -15056,7 +15091,8 @@ "supports_vision": true, "supports_web_search": false, "tpm": 8000000, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -15196,10 +15232,16 @@ "supports_service_tier": true }, "gemini-3.1-flash-lite": { - "cache_read_input_token_cost": 4.5e-08, - "cache_read_input_token_cost_per_audio_token": 9e-08, - "input_cost_per_audio_token": 9e-07, - "input_cost_per_token": 4.5e-07, + "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, + "cache_read_input_token_cost_flex": 1.25e-08, + "cache_read_input_token_cost_per_audio_token": 5e-08, + "cache_read_input_token_cost_priority": 4.5e-08, + "input_cost_per_audio_token": 5e-07, + "input_cost_per_token": 2.5e-07, + "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "vertex_ai-language-models", "max_audio_length_hours": 8.4, "max_audio_per_prompt": 1, @@ -15211,9 +15253,12 @@ "max_video_length": 1, "max_videos_per_prompt": 10, "mode": "chat", - "output_cost_per_reasoning_token": 2.7e-06, - "output_cost_per_token": 2.7e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "output_cost_per_reasoning_token": 1.5e-06, + "output_cost_per_token": 1.5e-06, + "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, + "output_cost_per_token_priority": 2.7e-06, + "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-flash-lite", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -15336,7 +15381,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini-2.5-flash-lite-preview-09-2025": { "cache_read_input_token_cost": 1e-08, @@ -15386,7 +15432,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini-2.5-flash-preview-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -15436,7 +15483,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini-live-2.5-flash-preview-native-audio-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -15587,7 +15635,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini-2.5-pro": { "cache_read_input_token_cost": 1.25e-07, @@ -16597,7 +16646,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini/gemini-2.5-flash-image": { "cache_read_input_token_cost": 3e-08, @@ -16653,7 +16703,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -16832,7 +16883,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini/gemini-2.5-flash-lite-preview-09-2025": { "cache_read_input_token_cost": 1e-08, @@ -16884,7 +16936,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini/gemini-2.5-flash-preview-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -16936,7 +16989,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini/gemini-flash-latest": { "cache_read_input_token_cost": 7.5e-08, @@ -17093,7 +17147,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini/gemini-2.5-flash-preview-tts": { "input_cost_per_token": 3e-07, @@ -17318,10 +17373,16 @@ "supports_service_tier": true }, "gemini/gemini-3.1-flash-lite": { - "cache_read_input_token_cost": 4.5e-08, - "cache_read_input_token_cost_per_audio_token": 9e-08, - "input_cost_per_audio_token": 9e-07, - "input_cost_per_token": 4.5e-07, + "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, + "cache_read_input_token_cost_flex": 1.25e-08, + "cache_read_input_token_cost_per_audio_token": 5e-08, + "cache_read_input_token_cost_priority": 4.5e-08, + "input_cost_per_audio_token": 5e-07, + "input_cost_per_token": 2.5e-07, + "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "gemini", "max_audio_length_hours": 8.4, "max_audio_per_prompt": 1, @@ -17333,10 +17394,13 @@ "max_video_length": 1, "max_videos_per_prompt": 10, "mode": "chat", - "output_cost_per_reasoning_token": 2.7e-06, - "output_cost_per_token": 2.7e-06, + "output_cost_per_reasoning_token": 1.5e-06, + "output_cost_per_token": 1.5e-06, + "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, + "output_cost_per_token_priority": 2.7e-06, "rpm": 15, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-flash-lite", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -18098,23 +18162,22 @@ }, "github_copilot/claude-haiku-4.5": { "litellm_provider": "github_copilot", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, + "max_input_tokens": 128000, + "max_output_tokens": 16000, + "max_tokens": 16000, "mode": "chat", "supported_endpoints": [ "/v1/chat/completions" ], "supports_function_calling": true, "supports_parallel_function_calling": true, - "supports_vision": true, - "supports_reasoning": true + "supports_vision": true }, "github_copilot/claude-opus-4.5": { "litellm_provider": "github_copilot", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, + "max_input_tokens": 128000, + "max_output_tokens": 16000, + "max_tokens": 16000, "mode": "chat", "supported_endpoints": [ "/v1/chat/completions" @@ -18122,7 +18185,6 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_vision": true, - "supports_reasoning": true, "supports_output_config": true }, "github_copilot/claude-opus-4.6-fast": { @@ -18138,22 +18200,6 @@ "supports_parallel_function_calling": true, "supports_vision": true }, - "github_copilot/claude-opus-4.7": { - "litellm_provider": "github_copilot", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/messages" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_reasoning": true - }, "github_copilot/claude-opus-41": { "litellm_provider": "github_copilot", "max_input_tokens": 80000, @@ -18180,33 +18226,16 @@ }, "github_copilot/claude-sonnet-4.5": { "litellm_provider": "github_copilot", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, + "max_input_tokens": 128000, + "max_output_tokens": 16000, + "max_tokens": 16000, "mode": "chat", "supported_endpoints": [ "/v1/chat/completions" ], "supports_function_calling": true, "supports_parallel_function_calling": true, - "supports_vision": true, - "supports_reasoning": true - }, - "github_copilot/claude-sonnet-4.6": { - "litellm_provider": "github_copilot", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 32000, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/messages" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_reasoning": true + "supports_vision": true }, "github_copilot/gemini-2.5-pro": { "litellm_provider": "github_copilot", @@ -18216,25 +18245,7 @@ "mode": "chat", "supports_function_calling": true, "supports_parallel_function_calling": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_reasoning": true - }, - "github_copilot/gemini-3-flash-preview": { - "litellm_provider": "github_copilot", - "max_input_tokens": 128000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_reasoning": true + "supports_vision": true }, "github_copilot/gemini-3-pro-preview": { "litellm_provider": "github_copilot", @@ -18246,30 +18257,13 @@ "supports_parallel_function_calling": true, "supports_vision": true }, - "github_copilot/gemini-3.1-pro-preview": { - "litellm_provider": "github_copilot", - "max_input_tokens": 128000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_reasoning": true - }, "github_copilot/gpt-3.5-turbo": { "litellm_provider": "github_copilot", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", - "supports_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_function_calling": true }, "github_copilot/gpt-3.5-turbo-0613": { "litellm_provider": "github_copilot", @@ -18277,10 +18271,7 @@ "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", - "supports_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_function_calling": true }, "github_copilot/gpt-4": { "litellm_provider": "github_copilot", @@ -18288,22 +18279,7 @@ "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", - "supports_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] - }, - "github_copilot/gpt-4-0125-preview": { - "litellm_provider": "github_copilot", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_function_calling": true, - "supports_parallel_function_calling": true + "supports_function_calling": true }, "github_copilot/gpt-4-0613": { "litellm_provider": "github_copilot", @@ -18311,22 +18287,16 @@ "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", - "supports_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_function_calling": true }, "github_copilot/gpt-4-o-preview": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_parallel_function_calling": true }, "github_copilot/gpt-4.1": { "litellm_provider": "github_copilot", @@ -18337,10 +18307,7 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_vision": true }, "github_copilot/gpt-4.1-2025-04-14": { "litellm_provider": "github_copilot", @@ -18351,89 +18318,68 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_vision": true }, "github_copilot/gpt-41-copilot": { "litellm_provider": "github_copilot", - "mode": "chat" + "mode": "completion" }, "github_copilot/gpt-4o": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "supports_function_calling": true, "supports_parallel_function_calling": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_vision": true }, "github_copilot/gpt-4o-2024-05-13": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "supports_function_calling": true, "supports_parallel_function_calling": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_vision": true }, "github_copilot/gpt-4o-2024-08-06": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 16384, "max_tokens": 16384, "mode": "chat", "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_parallel_function_calling": true }, "github_copilot/gpt-4o-2024-11-20": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 16384, "max_tokens": 16384, "mode": "chat", "supports_function_calling": true, "supports_parallel_function_calling": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_vision": true }, "github_copilot/gpt-4o-mini": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_parallel_function_calling": true }, "github_copilot/gpt-4o-mini-2024-07-18": { "litellm_provider": "github_copilot", - "max_input_tokens": 128000, + "max_input_tokens": 64000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supported_endpoints": [ - "/v1/chat/completions" - ] + "supports_parallel_function_calling": true }, "github_copilot/gpt-5": { "litellm_provider": "github_copilot", @@ -18452,19 +18398,14 @@ }, "github_copilot/gpt-5-mini": { "litellm_provider": "github_copilot", - "max_input_tokens": 264000, + "max_input_tokens": 128000, "max_output_tokens": 64000, "max_tokens": 64000, "mode": "chat", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, - "supports_vision": true, - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supports_reasoning": true + "supports_vision": true }, "github_copilot/gpt-5.1": { "litellm_provider": "github_copilot", @@ -18497,7 +18438,7 @@ }, "github_copilot/gpt-5.2": { "litellm_provider": "github_copilot", - "max_input_tokens": 264000, + "max_input_tokens": 128000, "max_output_tokens": 64000, "max_tokens": 64000, "mode": "chat", @@ -18508,27 +18449,11 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, - "supports_vision": true, - "supports_reasoning": true - }, - "github_copilot/gpt-5.2-codex": { - "litellm_provider": "github_copilot", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "supported_endpoints": [ - "/v1/responses" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_reasoning": true + "supports_vision": true }, "github_copilot/gpt-5.3-codex": { "litellm_provider": "github_copilot", - "max_input_tokens": 400000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -18538,96 +18463,25 @@ "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, - "supports_vision": true, - "supports_reasoning": true - }, - "github_copilot/gpt-5.4": { - "litellm_provider": "github_copilot", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_reasoning": true - }, - "github_copilot/gpt-5.4-mini": { - "litellm_provider": "github_copilot", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "supported_endpoints": [ - "/v1/responses" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_reasoning": true - }, - "github_copilot/gpt-5.5": { - "litellm_provider": "github_copilot", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "mode": "responses", - "supported_endpoints": [ - "/v1/responses" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_reasoning": true - }, - "github_copilot/oswe-vscode-prime": { - "litellm_provider": "github_copilot", - "max_input_tokens": 264000, - "max_output_tokens": 64000, - "max_tokens": 64000, - "mode": "chat", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/responses" - ], - "supports_vision": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true + "supports_vision": true }, "github_copilot/text-embedding-3-small": { "litellm_provider": "github_copilot", "max_input_tokens": 8191, "max_tokens": 8191, - "mode": "embedding", - "supported_endpoints": [ - "/v1/embeddings" - ] + "mode": "embedding" }, "github_copilot/text-embedding-3-small-inference": { "litellm_provider": "github_copilot", "max_input_tokens": 8191, "max_tokens": 8191, - "mode": "embedding", - "supported_endpoints": [ - "/v1/embeddings" - ] + "mode": "embedding" }, "github_copilot/text-embedding-ada-002": { "litellm_provider": "github_copilot", "max_input_tokens": 8191, "max_tokens": 8191, - "mode": "embedding", - "supported_endpoints": [ - "/v1/embeddings" - ] + "mode": "embedding" }, "chatgpt/gpt-5.4": { "litellm_provider": "chatgpt", @@ -23278,11 +23132,13 @@ }, "jp.anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "input_cost_per_token_above_200k_tokens": 6.6e-06, "output_cost_per_token_above_200k_tokens": 2.475e-05, "cache_creation_input_token_cost_above_200k_tokens": 8.25e-06, + "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -23308,6 +23164,7 @@ }, "jp.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_1hr": 2.2e-06, "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "bedrock_converse", @@ -23420,6 +23277,31 @@ "supports_system_messages": true, "supports_tool_choice": true }, + "inception/mercury-2": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 2.5e-07, + "litellm_provider": "inception", + "max_input_tokens": 128000, + "max_output_tokens": 50000, + "max_tokens": 50000, + "mode": "chat", + "output_cost_per_token": 7.5e-07, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "text-completion-inception/mercury-edit-2": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 2.5e-07, + "litellm_provider": "text-completion-inception", + "max_input_tokens": 32000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "completion", + "output_cost_per_token": 7.5e-07 + }, "lambda_ai/deepseek-llama3.3-70b": { "input_cost_per_token": 2e-07, "litellm_provider": "lambda_ai", @@ -26432,6 +26314,32 @@ "supports_vision": true, "supports_web_search": true }, + "oci/meta.llama-3.1-8b-instruct": { + "input_cost_per_token": 7.2e-07, + "litellm_provider": "oci", + "max_input_tokens": 128000, + "max_output_tokens": 4000, + "max_tokens": 4000, + "mode": "chat", + "output_cost_per_token": 7.2e-07, + "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", + "supports_function_calling": true, + "supports_response_schema": false, + "supports_native_streaming": true + }, + "oci/meta.llama-3.1-70b-instruct": { + "input_cost_per_token": 7.2e-07, + "litellm_provider": "oci", + "max_input_tokens": 128000, + "max_output_tokens": 4000, + "max_tokens": 4000, + "mode": "chat", + "output_cost_per_token": 7.2e-07, + "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", + "supports_function_calling": true, + "supports_response_schema": false, + "supports_native_streaming": true + }, "oci/meta.llama-3.1-405b-instruct": { "input_cost_per_token": 1.068e-05, "litellm_provider": "oci", @@ -26442,7 +26350,8 @@ "output_cost_per_token": 1.068e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/meta.llama-3.2-90b-vision-instruct": { "input_cost_per_token": 2e-06, @@ -26455,6 +26364,7 @@ "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, "supports_response_schema": false, + "supports_native_streaming": true, "supports_vision": true }, "oci/meta.llama-3.3-70b-instruct": { @@ -26467,31 +26377,35 @@ "output_cost_per_token": 7.2e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/meta.llama-4-maverick-17b-128e-instruct-fp8": { "input_cost_per_token": 7.2e-07, "litellm_provider": "oci", - "max_input_tokens": 512000, - "max_output_tokens": 4000, - "max_tokens": 4000, + "max_input_tokens": 1048576, + "max_output_tokens": 8192, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true, + "supports_vision": true }, "oci/meta.llama-4-scout-17b-16e-instruct": { "input_cost_per_token": 7.2e-07, "litellm_provider": "oci", - "max_input_tokens": 192000, - "max_output_tokens": 4000, - "max_tokens": 4000, + "max_input_tokens": 10485760, + "max_output_tokens": 8192, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/xai.grok-3": { "input_cost_per_token": 3e-06, @@ -26503,7 +26417,8 @@ "output_cost_per_token": 1.5e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/xai.grok-3-fast": { "input_cost_per_token": 5e-06, @@ -26515,7 +26430,8 @@ "output_cost_per_token": 2.5e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/xai.grok-3-mini": { "input_cost_per_token": 3e-07, @@ -26527,7 +26443,8 @@ "output_cost_per_token": 5e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/xai.grok-3-mini-fast": { "input_cost_per_token": 6e-07, @@ -26539,7 +26456,8 @@ "output_cost_per_token": 4e-06, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/xai.grok-4": { "input_cost_per_token": 3e-06, @@ -26551,7 +26469,8 @@ "output_cost_per_token": 1.5e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/cohere.command-latest": { "input_cost_per_token": 1.56e-06, @@ -26563,7 +26482,8 @@ "output_cost_per_token": 1.56e-06, "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/cohere.command-a-03-2025": { "input_cost_per_token": 1.56e-06, @@ -26575,7 +26495,8 @@ "output_cost_per_token": 1.56e-06, "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true }, "oci/cohere.command-plus-latest": { "input_cost_per_token": 1.56e-06, @@ -26587,7 +26508,88 @@ "output_cost_per_token": 1.56e-06, "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", "supports_function_calling": true, - "supports_response_schema": false + "supports_response_schema": false, + "supports_native_streaming": true + }, + "oci/google.gemini-2.5-flash": { + "input_cost_per_token": 1.5e-07, + "litellm_provider": "oci", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_vision": true, + "supports_native_streaming": true, + "supports_image_size": false + }, + "oci/google.gemini-2.5-pro": { + "input_cost_per_token": 1.25e-06, + "litellm_provider": "oci", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 1e-05, + "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_vision": true, + "supports_native_streaming": true + }, + "oci/google.gemini-2.5-flash-lite": { + "input_cost_per_token": 7.5e-08, + "litellm_provider": "oci", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 3e-07, + "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_vision": true, + "supports_native_streaming": true, + "supports_image_size": false + }, + "oci/cohere.command-a-vision": { + "input_cost_per_token": 1.56e-06, + "litellm_provider": "oci", + "max_input_tokens": 256000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 1.56e-06, + "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", + "supports_function_calling": true, + "supports_response_schema": false, + "supports_native_streaming": true, + "supports_vision": true + }, + "oci/cohere.command-a-reasoning": { + "input_cost_per_token": 1.56e-06, + "litellm_provider": "oci", + "max_input_tokens": 256000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 1.56e-06, + "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", + "supports_function_calling": false, + "supports_response_schema": false, + "supports_native_streaming": true + }, + "oci/cohere.embed-multilingual-image-v3.0": { + "input_cost_per_token": 1e-07, + "litellm_provider": "oci", + "max_input_tokens": 512, + "mode": "embedding", + "output_vector_size": 1024, + "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", + "supports_vision": true }, "oci/cohere.command-a-reasoning-08-2025": { "input_cost_per_token": 1.56e-06, @@ -26663,18 +26665,6 @@ "supports_response_schema": false, "supports_vision": true }, - "oci/meta.llama-3.1-70b-instruct": { - "input_cost_per_token": 7.2e-07, - "litellm_provider": "oci", - "max_input_tokens": 128000, - "max_output_tokens": 4000, - "max_tokens": 4000, - "mode": "chat", - "output_cost_per_token": 7.2e-07, - "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", - "supports_function_calling": true, - "supports_response_schema": false - }, "oci/meta.llama-3.3-70b-instruct-fp8-dynamic": { "input_cost_per_token": 7.2e-07, "litellm_provider": "oci", @@ -26792,45 +26782,6 @@ "supports_response_schema": true, "supports_vision": true }, - "oci/google.gemini-2.5-pro": { - "input_cost_per_token": 1.25e-06, - "litellm_provider": "oci", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 65536, - "mode": "chat", - "output_cost_per_token": 1e-05, - "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_vision": true - }, - "oci/google.gemini-2.5-flash": { - "input_cost_per_token": 1.5e-07, - "litellm_provider": "oci", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 65536, - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_vision": true - }, - "oci/google.gemini-2.5-flash-lite": { - "input_cost_per_token": 7.5e-08, - "litellm_provider": "oci", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 65536, - "mode": "chat", - "output_cost_per_token": 3e-07, - "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", - "supports_function_calling": true, - "supports_response_schema": true, - "supports_vision": true - }, "oci/cohere.embed-english-v3.0": { "input_cost_per_token": 1e-07, "litellm_provider": "oci", @@ -27638,7 +27589,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_image_size": false }, "openrouter/google/gemini-2.5-pro": { "input_cost_per_audio_token": 7e-07, @@ -29508,7 +29460,8 @@ "mode": "responses", "supports_web_search": true, "supports_reasoning": false, - "supports_function_calling": true + "supports_function_calling": true, + "supports_image_size": false }, "perplexity/xai/grok-4-1-fast-non-reasoning": { "litellm_provider": "perplexity", @@ -30090,7 +30043,8 @@ "supports_vision": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_response_schema": true + "supports_response_schema": true, + "supports_image_size": false }, "replicate/openai/gpt-oss-120b": { "input_cost_per_token": 1.8e-07, @@ -31909,6 +31863,7 @@ }, "au.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_1hr": 2.2e-06, "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "bedrock_converse", @@ -32788,7 +32743,8 @@ "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, - "supports_response_schema": true + "supports_response_schema": true, + "supports_image_size": false }, "vercel_ai_gateway/google/gemini-2.5-pro": { "input_cost_per_token": 2.5e-06, @@ -33555,6 +33511,7 @@ }, "vertex_ai/claude-haiku-4-5": { "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33576,6 +33533,7 @@ }, "vertex_ai/claude-haiku-4-5@20251001": { "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33626,6 +33584,7 @@ }, "vertex_ai/claude-3-7-sonnet@20250219": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-05-11", "input_cost_per_token": 3e-06, @@ -33725,6 +33684,7 @@ }, "vertex_ai/claude-opus-4": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "vertex_ai-anthropic_models", @@ -33750,6 +33710,7 @@ }, "vertex_ai/claude-opus-4-1": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, @@ -33767,6 +33728,7 @@ }, "vertex_ai/claude-opus-4-1@20250805": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, @@ -33784,6 +33746,7 @@ }, "vertex_ai/claude-opus-4-5": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33810,6 +33773,7 @@ }, "vertex_ai/claude-opus-4-5@20251101": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33837,6 +33801,7 @@ }, "vertex_ai/claude-opus-4-6": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33864,6 +33829,7 @@ }, "vertex_ai/claude-opus-4-6@default": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33891,6 +33857,7 @@ }, "vertex_ai/claude-opus-4-7": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33918,6 +33885,7 @@ }, "vertex_ai/claude-opus-4-7@default": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -34001,6 +33969,7 @@ }, "vertex_ai/claude-sonnet-4-5": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -34027,6 +33996,7 @@ }, "vertex_ai/claude-sonnet-4-6": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -34054,6 +34024,7 @@ }, "vertex_ai/claude-sonnet-4-5@20250929": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -34081,6 +34052,7 @@ }, "vertex_ai/claude-opus-4@20250514": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "vertex_ai-anthropic_models", @@ -34106,6 +34078,7 @@ }, "vertex_ai/claude-sonnet-4": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -34135,6 +34108,7 @@ }, "vertex_ai/claude-sonnet-4@20250514": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -34342,7 +34316,8 @@ "supports_url_context": true, "supports_vision": true, "supports_web_search": false, - "tpm": 8000000 + "tpm": 8000000, + "supports_image_size": false }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -34430,10 +34405,16 @@ "web_search_billing_unit": "per_query" }, "vertex_ai/gemini-3.1-flash-lite": { - "cache_read_input_token_cost": 4.5e-08, - "cache_read_input_token_cost_per_audio_token": 9e-08, - "input_cost_per_audio_token": 9e-07, - "input_cost_per_token": 4.5e-07, + "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_batches": 1.25e-08, + "cache_read_input_token_cost_flex": 1.25e-08, + "cache_read_input_token_cost_per_audio_token": 5e-08, + "cache_read_input_token_cost_priority": 4.5e-08, + "input_cost_per_audio_token": 5e-07, + "input_cost_per_token": 2.5e-07, + "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "vertex_ai-language-models", "max_audio_length_hours": 8.4, "max_audio_per_prompt": 1, @@ -34445,8 +34426,11 @@ "max_video_length": 1, "max_videos_per_prompt": 10, "mode": "chat", - "output_cost_per_reasoning_token": 2.7e-06, - "output_cost_per_token": 2.7e-06, + "output_cost_per_reasoning_token": 1.5e-06, + "output_cost_per_token": 1.5e-06, + "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, + "output_cost_per_token_priority": 2.7e-06, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", "supported_endpoints": [ "/v1/chat/completions", @@ -41151,6 +41135,7 @@ }, "vertex_ai/claude-sonnet-4-6@default": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "litellm_provider": "vertex_ai-anthropic_models", diff --git a/litellm/proxy/agent_endpoints/endpoints.py b/litellm/proxy/agent_endpoints/endpoints.py index 082e314b08d..19dbfe33d32 100644 --- a/litellm/proxy/agent_endpoints/endpoints.py +++ b/litellm/proxy/agent_endpoints/endpoints.py @@ -319,36 +319,34 @@ async def create_agent( Example Request: ```bash - curl -X POST "http://localhost:4000/agents" \\ + curl -X POST "http://localhost:4000/v1/agents" \\ -H "Authorization: Bearer " \\ -H "Content-Type: application/json" \\ -d '{ - "agent": { - "agent_name": "my-custom-agent", - "agent_card_params": { - "protocolVersion": "1.0", - "name": "Hello World Agent", - "description": "Just a hello world agent", - "url": "http://localhost:9999/", - "version": "1.0.0", - "defaultInputModes": ["text"], - "defaultOutputModes": ["text"], - "capabilities": { - "streaming": true - }, - "skills": [ - { - "id": "hello_world", - "name": "Returns hello world", - "description": "just returns hello world", - "tags": ["hello world"], - "examples": ["hi", "hello world"] - } - ] + "agent_name": "my-custom-agent", + "agent_card_params": { + "protocolVersion": "1.0", + "name": "Hello World Agent", + "description": "Just a hello world agent", + "url": "http://localhost:9999/", + "version": "1.0.0", + "defaultInputModes": ["text"], + "defaultOutputModes": ["text"], + "capabilities": { + "streaming": true }, - "litellm_params": { - "make_public": true - } + "skills": [ + { + "id": "hello_world", + "name": "Returns hello world", + "description": "just returns hello world", + "tags": ["hello world"], + "examples": ["hi", "hello world"] + } + ] + }, + "litellm_params": { + "make_public": true } }' ``` @@ -441,7 +439,7 @@ async def get_agent_by_id( Example Request: ```bash - curl -X GET "http://localhost:4000/agents/123e4567-e89b-12d3-a456-426614174000" \\ + curl -X GET "http://localhost:4000/v1/agents/123e4567-e89b-12d3-a456-426614174000" \\ -H "Authorization: Bearer " ``` """ @@ -535,28 +533,26 @@ async def update_agent( Example Request: ```bash - curl -X PUT "http://localhost:4000/agents/123e4567-e89b-12d3-a456-426614174000" \\ + curl -X PUT "http://localhost:4000/v1/agents/123e4567-e89b-12d3-a456-426614174000" \\ -H "Authorization: Bearer " \\ -H "Content-Type: application/json" \\ -d '{ - "agent": { - "agent_name": "updated-agent", - "agent_card_params": { - "protocolVersion": "1.0", - "name": "Updated Agent", - "description": "Updated description", - "url": "http://localhost:9999/", - "version": "1.1.0", - "defaultInputModes": ["text"], - "defaultOutputModes": ["text"], - "capabilities": { - "streaming": true - }, - "skills": [] + "agent_name": "updated-agent", + "agent_card_params": { + "protocolVersion": "1.0", + "name": "Updated Agent", + "description": "Updated description", + "url": "http://localhost:9999/", + "version": "1.1.0", + "defaultInputModes": ["text"], + "defaultOutputModes": ["text"], + "capabilities": { + "streaming": true }, - "litellm_params": { - "make_public": false - } + "skills": [] + }, + "litellm_params": { + "make_public": false } }' ``` @@ -645,28 +641,26 @@ async def patch_agent( Example Request: ```bash - curl -X PUT "http://localhost:4000/agents/123e4567-e89b-12d3-a456-426614174000" \\ + curl -X PATCH "http://localhost:4000/v1/agents/123e4567-e89b-12d3-a456-426614174000" \\ -H "Authorization: Bearer " \\ -H "Content-Type: application/json" \\ -d '{ - "agent": { - "agent_name": "updated-agent", - "agent_card_params": { - "protocolVersion": "1.0", - "name": "Updated Agent", - "description": "Updated description", - "url": "http://localhost:9999/", - "version": "1.1.0", - "defaultInputModes": ["text"], - "defaultOutputModes": ["text"], - "capabilities": { - "streaming": true - }, - "skills": [] + "agent_name": "updated-agent", + "agent_card_params": { + "protocolVersion": "1.0", + "name": "Updated Agent", + "description": "Updated description", + "url": "http://localhost:9999/", + "version": "1.1.0", + "defaultInputModes": ["text"], + "defaultOutputModes": ["text"], + "capabilities": { + "streaming": true }, - "litellm_params": { - "make_public": false - } + "skills": [] + }, + "litellm_params": { + "make_public": false } }' ``` @@ -753,7 +747,7 @@ async def delete_agent( Example Request: ```bash - curl -X DELETE "http://localhost:4000/agents/123e4567-e89b-12d3-a456-426614174000" \\ + curl -X DELETE "http://localhost:4000/v1/agents/123e4567-e89b-12d3-a456-426614174000" \\ -H "Authorization: Bearer " ``` diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index e8d05031a5a..93a64889458 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -1127,7 +1127,7 @@ async def get_end_user_object( end_user_id: Optional[str], prisma_client: Optional[PrismaClient], user_api_key_cache: UserApiKeyCache, - route: str, + route: Optional[str] = "", parent_otel_span: Optional[Span] = None, proxy_logging_obj: Optional[ProxyLogging] = None, ) -> Optional[LiteLLM_EndUserTable]: @@ -1171,9 +1171,6 @@ async def get_end_user_object( parent_otel_span=parent_otel_span, ) - # Check budget limits - await _check_end_user_budget(end_user_obj=return_obj, route=route) - return return_obj # Fetch from database @@ -1204,14 +1201,9 @@ async def get_end_user_object( model_type=LiteLLM_EndUserTable, ) - # Check budget limits - await _check_end_user_budget(end_user_obj=_response, route=route) - return _response - except Exception as e: - if isinstance(e, litellm.BudgetExceededError): - raise e + except Exception: return None @@ -1308,8 +1300,6 @@ async def _end_user_id_exists_in_db( ) if end_user_obj is not None: return True - except litellm.BudgetExceededError: - raise except Exception as e: verbose_proxy_logger.debug( f"end_user validation: get_end_user_object lookup failed: {e}" diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 2e6cd1f8e70..9d4efbaeeee 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -30,6 +30,7 @@ from litellm.proxy._types import * from litellm.proxy.auth.auth_checks import ( ExperimentalUIJWTToken, _cache_key_object, + _check_end_user_budget, _delete_cache_key_object, _get_user_role, _is_model_cost_zero, @@ -1762,8 +1763,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 async def _safe_fetch(label: str, awaitable): """Run an awaitable and return its result. Re-raises authentication / authorization failures (HTTPException, ProxyException, - BudgetExceededError — which ``get_end_user_object`` raises for - end-user budget violations) so they propagate to the caller. + BudgetExceededError) so they propagate to the caller. Other exceptions (e.g. transient DB errors fetching context) are swallowed with a debug log and ``None`` is returned so ``common_checks`` can still run against whatever limits are recorded @@ -2584,6 +2584,14 @@ async def _run_post_custom_auth_checks( user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, ) + # common_checks() enforces the end-user budget, but the centralized + # gate skips it for custom-auth deployments unless + # custom_auth_run_common_checks is set. Enforce it here on that path + # so an over-budget end user can't keep making requests. + if end_user_object is not None and not general_settings.get( + "custom_auth_run_common_checks", False + ): + await _check_end_user_budget(end_user_obj=end_user_object, route=route) # 2. Check token expiry if valid_token.expires is not None: diff --git a/litellm/router.py b/litellm/router.py index d60c39ca402..7aaf989919c 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -9100,7 +9100,10 @@ class Router: except Exception: pass + # Three mutually exclusive scenarios for the model's metadata: if custom_model_info is not None and litellm_model_name_model_info is not None: + # (1) It has both custom model_info set and exists in the built-in map + # merge with custom overriding built-in model_info = cast( ModelInfo, _update_dictionary( @@ -9109,7 +9112,12 @@ class Router: ), ) elif litellm_model_name_model_info is not None: + # (2) Built-in only — no custom pricing to merge model_info = litellm_model_name_model_info + elif custom_model_info is not None: + # (3) Custom only — model not in built-in cost map yet + # custom_model_info already includes base_model defaults at this point, if applicable + model_info = cast(ModelInfo, custom_model_info) return model_info diff --git a/litellm/types/images/main.py b/litellm/types/images/main.py index 819f4954589..80e55297c42 100644 --- a/litellm/types/images/main.py +++ b/litellm/types/images/main.py @@ -20,6 +20,7 @@ class ImageEditOptionalRequestParams(TypedDict, total=False): response_format: Optional[Literal["url", "b64_json"]] size: Optional[str] user: Optional[str] + imageConfig: Optional[Dict[str, Any]] class ImageEditRequestParams(ImageEditOptionalRequestParams, total=False): diff --git a/litellm/types/llms/gemini.py b/litellm/types/llms/gemini.py index 8763544facc..38e6d533449 100644 --- a/litellm/types/llms/gemini.py +++ b/litellm/types/llms/gemini.py @@ -1,7 +1,7 @@ from enum import Enum -from typing import Any, Dict, Iterable, List, Literal, Optional, Union +from typing import Any, Dict, List, Literal, Optional -from typing_extensions import Required, TypedDict +from typing_extensions import TypedDict from .vertex_ai import ( GenerationConfig, @@ -171,6 +171,9 @@ class GeminiImageGenerationParameters(BaseModel): aspectRatio: Optional[str] = None """Aspect ratio for generated images (e.g., '1:1', '16:9', '9:16', '4:3', '3:4')""" + imageSize: Optional[str] = None + """Image size for generated images (e.g., '1K', '2K')""" + personGeneration: Optional[str] = None """Controls person generation in images""" diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py index 346909f14eb..51e408f8c63 100644 --- a/litellm/types/llms/openai.py +++ b/litellm/types/llms/openai.py @@ -1084,6 +1084,7 @@ OpenAIImageGenerationOptionalParams = Literal[ "image_url", "image_prompt_strength", "aspect_ratio", + "imageConfig", ] OpenAIImageEditOptionalParams = Literal[ diff --git a/litellm/types/llms/vertex_ai.py b/litellm/types/llms/vertex_ai.py index a1d53978761..b972ff3c538 100644 --- a/litellm/types/llms/vertex_ai.py +++ b/litellm/types/llms/vertex_ai.py @@ -20,6 +20,7 @@ class FunctionResponse(TypedDict, total=False): id: str name: Required[str] response: Optional[dict] + parts: List["FunctionResponsePartType"] class FunctionCall(TypedDict, total=False): @@ -40,6 +41,11 @@ class BlobType(TypedDict, total=False): data: Required[str] +class FunctionResponsePartType(TypedDict, total=False): + inline_data: BlobType + file_data: FileDataType + + class PartType(TypedDict, total=False): text: str inline_data: BlobType diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 63c2513aed2..3dcff2be689 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -148,6 +148,7 @@ class ProviderSpecificModelInfo(TypedDict, total=False): supports_xhigh_reasoning_effort: Optional[bool] supports_max_reasoning_effort: Optional[bool] supports_output_config: Optional[bool] + supports_image_size: Optional[bool] bedrock_output_config_effort_ceiling: Optional[ Literal["low", "medium", "high", "max", "xhigh"] ] @@ -3300,6 +3301,8 @@ class LlmProviders(str, Enum): V0 = "v0" MORPH = "morph" LAMBDA_AI = "lambda_ai" + INCEPTION = "inception" + TEXT_COMPLETION_INCEPTION = "text-completion-inception" DEEPSEEK = "deepseek" SAMBANOVA = "sambanova" MARITALK = "maritalk" diff --git a/litellm/utils.py b/litellm/utils.py index 6188206148f..7cac830b2c2 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -3147,6 +3147,7 @@ def get_optional_params_image_gen( size: Optional[str] = None, style: Optional[str] = None, user: Optional[str] = None, + imageConfig: Optional[dict] = None, custom_llm_provider: Optional[str] = None, additional_drop_params: Optional[list] = None, provider_config: Optional[BaseImageGenerationConfig] = None, @@ -3183,6 +3184,7 @@ def get_optional_params_image_gen( "size": None, "style": None, "user": None, + "imageConfig": None, } non_default_params = _get_non_default_params( @@ -4547,6 +4549,18 @@ def get_optional_params( # noqa: PLR0915 ), ) + elif custom_llm_provider == "text-completion-inception": + optional_params = litellm.InceptionTextCompletionConfig().map_openai_params( + non_default_params=non_default_params, + optional_params=optional_params, + model=model, + drop_params=( + drop_params + if drop_params is not None and isinstance(drop_params, bool) + else False + ), + ) + elif custom_llm_provider == "databricks": optional_params = litellm.DatabricksConfig().map_openai_params( non_default_params=non_default_params, @@ -6083,6 +6097,7 @@ def _get_model_info_helper( # noqa: PLR0915 "provider_specific_entry", None ), uses_embed_content=_model_info.get("uses_embed_content", None), + supports_image_size=_model_info.get("supports_image_size", None), ) except Exception as e: verbose_logger.debug(f"Error getting model info: {e}") @@ -6637,6 +6652,14 @@ def validate_environment( # noqa: PLR0915 keys_in_environment = True else: missing_keys.append("CODESTRAL_API_KEY") + elif ( + custom_llm_provider == "inception" + or custom_llm_provider == "text-completion-inception" + ): + if "INCEPTION_API_KEY" in os.environ: + keys_in_environment = True + else: + missing_keys.append("INCEPTION_API_KEY") elif custom_llm_provider == "deepseek": if "DEEPSEEK_API_KEY" in os.environ: keys_in_environment = True @@ -8291,6 +8314,7 @@ class ProviderConfigManager: LlmProviders.XAI: (lambda: litellm.XAIChatConfig(), False), LlmProviders.ZAI: (lambda: litellm.ZAIChatConfig(), False), LlmProviders.LAMBDA_AI: (lambda: litellm.LambdaAIChatConfig(), False), + LlmProviders.INCEPTION: (lambda: litellm.InceptionChatConfig(), False), LlmProviders.LLAMA: (lambda: litellm.LlamaAPIConfig(), False), LlmProviders.TEXT_COMPLETION_OPENAI: ( lambda: litellm.OpenAITextCompletionConfig(), @@ -8356,6 +8380,10 @@ class ProviderConfigManager: lambda: litellm.CodestralTextCompletionConfig(), False, ), + LlmProviders.TEXT_COMPLETION_INCEPTION: ( + lambda: litellm.InceptionTextCompletionConfig(), + False, + ), LlmProviders.SAMBANOVA: (lambda: litellm.SambanovaConfig(), False), LlmProviders.MARITALK: (lambda: litellm.MaritalkConfig(), False), LlmProviders.VLLM: (lambda: litellm.VLLMConfig(), False), @@ -8928,6 +8956,8 @@ class ProviderConfigManager: return litellm.FireworksAITextCompletionConfig() elif LlmProviders.TOGETHER_AI == provider: return litellm.TogetherAITextCompletionConfig() + elif LlmProviders.TEXT_COMPLETION_INCEPTION == provider: + return litellm.InceptionTextCompletionConfig() return litellm.OpenAITextCompletionConfig() @staticmethod diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index b253235ec2a..ed6de4fa6b7 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1075,6 +1075,7 @@ }, "eu.anthropic.claude-opus-4-6-v1": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1104,6 +1105,7 @@ }, "au.anthropic.claude-opus-4-6-v1": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1241,6 +1243,7 @@ }, "eu.anthropic.claude-opus-4-7": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1271,6 +1274,7 @@ }, "au.anthropic.claude-opus-4-7": { "cache_creation_input_token_cost": 6.875e-06, + "cache_creation_input_token_cost_above_1hr": 1.1e-05, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, "litellm_provider": "bedrock_converse", @@ -1543,6 +1547,7 @@ }, "eu.anthropic.claude-sonnet-4-6": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "litellm_provider": "bedrock_converse", @@ -1571,6 +1576,7 @@ }, "au.anthropic.claude-sonnet-4-6": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "litellm_provider": "bedrock_converse", @@ -1599,6 +1605,7 @@ }, "jp.anthropic.claude-sonnet-4-6": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "litellm_provider": "bedrock_converse", @@ -1995,11 +2002,13 @@ }, "au.anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "input_cost_per_token_above_200k_tokens": 6.6e-06, "output_cost_per_token_above_200k_tokens": 2.475e-05, "cache_creation_input_token_cost_above_200k_tokens": 8.25e-06, + "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -7494,6 +7503,27 @@ "supports_video_input": true, "supports_vision": true }, + "azure_ai/kimi-k2.6": { + "input_cost_per_token": 9.5e-07, + "litellm_provider": "azure_ai", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 4e-06, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-kimi-k2-6-in-microsoft-foundry/4513125", + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure_ai/ministral-3b": { "input_cost_per_token": 4e-08, "litellm_provider": "azure_ai", @@ -12682,7 +12712,8 @@ "litellm_provider": "deepinfra", "mode": "chat", "supports_tool_choice": true, - "supports_function_calling": true + "supports_function_calling": true, + "supports_image_size": false }, "deepinfra/google/gemini-2.5-pro": { "max_tokens": 1000000, @@ -13583,6 +13614,7 @@ }, "eu.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_1hr": 2.2e-06, "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "deprecation_date": "2026-10-15", @@ -13787,11 +13819,13 @@ }, "eu.anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "input_cost_per_token_above_200k_tokens": 6.6e-06, "output_cost_per_token_above_200k_tokens": 2.475e-05, "cache_creation_input_token_cost_above_200k_tokens": 8.25e-06, + "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -15006,7 +15040,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini-2.5-flash-image": { "cache_read_input_token_cost": 3e-08, @@ -15056,7 +15091,8 @@ "supports_vision": true, "supports_web_search": false, "tpm": 8000000, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -15345,7 +15381,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini-2.5-flash-lite-preview-09-2025": { "cache_read_input_token_cost": 1e-08, @@ -15395,7 +15432,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini-2.5-flash-preview-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -15445,7 +15483,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini-live-2.5-flash-preview-native-audio-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -15596,7 +15635,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini-2.5-pro": { "cache_read_input_token_cost": 1.25e-07, @@ -16606,7 +16646,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini/gemini-2.5-flash-image": { "cache_read_input_token_cost": 3e-08, @@ -16662,7 +16703,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -16841,7 +16883,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "supports_service_tier": true + "supports_service_tier": true, + "supports_image_size": false }, "gemini/gemini-2.5-flash-lite-preview-09-2025": { "cache_read_input_token_cost": 1e-08, @@ -16893,7 +16936,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini/gemini-2.5-flash-preview-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -16945,7 +16989,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini/gemini-flash-latest": { "cache_read_input_token_cost": 7.5e-08, @@ -17102,7 +17147,8 @@ "search_context_size_low": 0.035, "search_context_size_medium": 0.035, "search_context_size_high": 0.035 - } + }, + "supports_image_size": false }, "gemini/gemini-2.5-flash-preview-tts": { "input_cost_per_token": 3e-07, @@ -23086,11 +23132,13 @@ }, "jp.anthropic.claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, "cache_read_input_token_cost": 3.3e-07, "input_cost_per_token": 3.3e-06, "input_cost_per_token_above_200k_tokens": 6.6e-06, "output_cost_per_token_above_200k_tokens": 2.475e-05, "cache_creation_input_token_cost_above_200k_tokens": 8.25e-06, + "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -23116,6 +23164,7 @@ }, "jp.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_1hr": 2.2e-06, "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "bedrock_converse", @@ -23228,6 +23277,31 @@ "supports_system_messages": true, "supports_tool_choice": true }, + "inception/mercury-2": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 2.5e-07, + "litellm_provider": "inception", + "max_input_tokens": 128000, + "max_output_tokens": 50000, + "max_tokens": 50000, + "mode": "chat", + "output_cost_per_token": 7.5e-07, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "text-completion-inception/mercury-edit-2": { + "cache_read_input_token_cost": 2.5e-08, + "input_cost_per_token": 2.5e-07, + "litellm_provider": "text-completion-inception", + "max_input_tokens": 32000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "completion", + "output_cost_per_token": 7.5e-07 + }, "lambda_ai/deepseek-llama3.3-70b": { "input_cost_per_token": 2e-07, "litellm_provider": "lambda_ai", @@ -26449,7 +26523,8 @@ "supports_function_calling": true, "supports_response_schema": true, "supports_vision": true, - "supports_native_streaming": true + "supports_native_streaming": true, + "supports_image_size": false }, "oci/google.gemini-2.5-pro": { "input_cost_per_token": 1.25e-06, @@ -26477,7 +26552,8 @@ "supports_function_calling": true, "supports_response_schema": true, "supports_vision": true, - "supports_native_streaming": true + "supports_native_streaming": true, + "supports_image_size": false }, "oci/cohere.command-a-vision": { "input_cost_per_token": 1.56e-06, @@ -27513,7 +27589,8 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_image_size": false }, "openrouter/google/gemini-2.5-pro": { "input_cost_per_audio_token": 7e-07, @@ -29383,7 +29460,8 @@ "mode": "responses", "supports_web_search": true, "supports_reasoning": false, - "supports_function_calling": true + "supports_function_calling": true, + "supports_image_size": false }, "perplexity/xai/grok-4-1-fast-non-reasoning": { "litellm_provider": "perplexity", @@ -29965,7 +30043,8 @@ "supports_vision": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_response_schema": true + "supports_response_schema": true, + "supports_image_size": false }, "replicate/openai/gpt-oss-120b": { "input_cost_per_token": 1.8e-07, @@ -31784,6 +31863,7 @@ }, "au.anthropic.claude-haiku-4-5-20251001-v1:0": { "cache_creation_input_token_cost": 1.375e-06, + "cache_creation_input_token_cost_above_1hr": 2.2e-06, "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "bedrock_converse", @@ -32663,7 +32743,8 @@ "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, - "supports_response_schema": true + "supports_response_schema": true, + "supports_image_size": false }, "vercel_ai_gateway/google/gemini-2.5-pro": { "input_cost_per_token": 2.5e-06, @@ -33430,6 +33511,7 @@ }, "vertex_ai/claude-haiku-4-5": { "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33451,6 +33533,7 @@ }, "vertex_ai/claude-haiku-4-5@20251001": { "cache_creation_input_token_cost": 1.25e-06, + "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 1e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33501,6 +33584,7 @@ }, "vertex_ai/claude-3-7-sonnet@20250219": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-05-11", "input_cost_per_token": 3e-06, @@ -33600,6 +33684,7 @@ }, "vertex_ai/claude-opus-4": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "vertex_ai-anthropic_models", @@ -33625,6 +33710,7 @@ }, "vertex_ai/claude-opus-4-1": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, @@ -33642,6 +33728,7 @@ }, "vertex_ai/claude-opus-4-1@20250805": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, @@ -33659,6 +33746,7 @@ }, "vertex_ai/claude-opus-4-5": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33685,6 +33773,7 @@ }, "vertex_ai/claude-opus-4-5@20251101": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33712,6 +33801,7 @@ }, "vertex_ai/claude-opus-4-6": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33739,6 +33829,7 @@ }, "vertex_ai/claude-opus-4-6@default": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33766,6 +33857,7 @@ }, "vertex_ai/claude-opus-4-7": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33793,6 +33885,7 @@ }, "vertex_ai/claude-opus-4-7@default": { "cache_creation_input_token_cost": 6.25e-06, + "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 5e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33876,6 +33969,7 @@ }, "vertex_ai/claude-sonnet-4-5": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -33902,6 +33996,7 @@ }, "vertex_ai/claude-sonnet-4-6": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -33929,6 +34024,7 @@ }, "vertex_ai/claude-sonnet-4-5@20250929": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -33956,6 +34052,7 @@ }, "vertex_ai/claude-opus-4@20250514": { "cache_creation_input_token_cost": 1.875e-05, + "cache_creation_input_token_cost_above_1hr": 3e-05, "cache_read_input_token_cost": 1.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "vertex_ai-anthropic_models", @@ -33981,6 +34078,7 @@ }, "vertex_ai/claude-sonnet-4": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -34010,6 +34108,7 @@ }, "vertex_ai/claude-sonnet-4@20250514": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, @@ -34217,7 +34316,8 @@ "supports_url_context": true, "supports_vision": true, "supports_web_search": false, - "tpm": 8000000 + "tpm": 8000000, + "supports_image_size": false }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -41035,6 +41135,7 @@ }, "vertex_ai/claude-sonnet-4-6@default": { "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_token": 3e-06, "litellm_provider": "vertex_ai-anthropic_models", diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index 3a01541060f..b4f782f9c3e 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -1273,6 +1273,24 @@ "interactions": true } }, + "inception": { + "display_name": "Inception (`inception`)", + "url": "https://docs.litellm.ai/docs/providers/inception", + "endpoints": { + "chat_completions": true, + "messages": true, + "responses": true, + "embeddings": false, + "image_generations": false, + "audio_transcriptions": false, + "audio_speech": false, + "moderations": false, + "batches": false, + "rerank": false, + "a2a": true, + "interactions": true + } + }, "infinity": { "display_name": "Infinity (`infinity`)", "url": "https://docs.litellm.ai/docs/providers/infinity", diff --git a/tests/llm_translation/test_gemini.py b/tests/llm_translation/test_gemini.py index bd340aa63be..0a5aebdf91b 100644 --- a/tests/llm_translation/test_gemini.py +++ b/tests/llm_translation/test_gemini.py @@ -17,6 +17,66 @@ from litellm import completion import json +GEMINI_3_IMAGE_SIZE_MAPPINGS = [ + ("512x512", "1:1", "512"), + ("1024x1024", "1:1", "1K"), + ("2048x2048", "1:1", "2K"), + ("4096x4096", "1:1", "4K"), + ("256x1024", "1:4", "512"), + ("512x2048", "1:4", "1K"), + ("1024x4096", "1:4", "2K"), + ("2048x8192", "1:4", "4K"), + ("192x1536", "1:8", "512"), + ("384x3072", "1:8", "1K"), + ("768x6144", "1:8", "2K"), + ("1536x12288", "1:8", "4K"), + ("424x632", "2:3", "512"), + ("848x1264", "2:3", "1K"), + ("1696x2528", "2:3", "2K"), + ("3392x5056", "2:3", "4K"), + ("632x424", "3:2", "512"), + ("1264x848", "3:2", "1K"), + ("2528x1696", "3:2", "2K"), + ("5056x3392", "3:2", "4K"), + ("448x600", "3:4", "512"), + ("896x1200", "3:4", "1K"), + ("1792x2400", "3:4", "2K"), + ("3584x4800", "3:4", "4K"), + ("1024x256", "4:1", "512"), + ("2048x512", "4:1", "1K"), + ("4096x1024", "4:1", "2K"), + ("8192x2048", "4:1", "4K"), + ("600x448", "4:3", "512"), + ("1200x896", "4:3", "1K"), + ("2400x1792", "4:3", "2K"), + ("4800x3584", "4:3", "4K"), + ("464x576", "4:5", "512"), + ("928x1152", "4:5", "1K"), + ("1856x2304", "4:5", "2K"), + ("3712x4608", "4:5", "4K"), + ("576x464", "5:4", "512"), + ("1152x928", "5:4", "1K"), + ("2304x1856", "5:4", "2K"), + ("4608x3712", "5:4", "4K"), + ("1536x192", "8:1", "512"), + ("3072x384", "8:1", "1K"), + ("6144x768", "8:1", "2K"), + ("12288x1536", "8:1", "4K"), + ("384x688", "9:16", "512"), + ("768x1376", "9:16", "1K"), + ("1536x2752", "9:16", "2K"), + ("3072x5504", "9:16", "4K"), + ("688x384", "16:9", "512"), + ("1376x768", "16:9", "1K"), + ("2752x1536", "16:9", "2K"), + ("5504x3072", "16:9", "4K"), + ("792x336", "21:9", "512"), + ("1584x672", "21:9", "1K"), + ("3168x1344", "21:9", "2K"), + ("6336x2688", "21:9", "4K"), +] + + class TestGoogleAIStudioGemini(BaseLLMChatTest): def get_base_completion_call_args(self) -> dict: return {"model": "gemini/gemini-2.5-flash"} @@ -365,6 +425,143 @@ def test_gemini_flash_image_preview_models(model_name: str): ] +@pytest.mark.parametrize( + "model, kwargs, expected_image_config", + [ + ( + "gemini/gemini-3-pro-image-preview", + {"imageConfig": {"aspectRatio": "16:9", "imageSize": "512px"}}, + {"aspectRatio": "16:9", "imageSize": "512px"}, + ), + ( + "gemini/gemini-2.5-flash-image", + {"size": "2048x2048"}, + {"aspectRatio": "1:1"}, + ), + ], +) +def test_gemini_image_generation_forwards_image_config( + model: str, kwargs: dict, expected_image_config: dict +): + from unittest.mock import patch, MagicMock + + with patch( + "litellm.llms.custom_httpx.llm_http_handler.HTTPHandler.post" + ) as mock_post: + mock_http_response = MagicMock() + mock_http_response.json.return_value = { + "candidates": [ + { + "content": { + "parts": [{"inlineData": {"data": "test_base64_image_data"}}] + } + } + ] + } + mock_http_response.status_code = 200 + mock_post.return_value = mock_http_response + + litellm.image_generation( + model=model, + prompt="Generate a simple test image", + api_key="test_api_key", + **kwargs, + ) + + request_data = mock_post.call_args.kwargs.get("json", {}) + assert request_data["generationConfig"]["imageConfig"] == expected_image_config + + +def test_gemini_image_generation_image_config_takes_precedence_over_size(): + from litellm.llms.gemini.image_generation.transformation import GoogleImageGenConfig + + explicit_image_config = {"aspectRatio": "16:9", "imageSize": "2K"} + + mapped_params = GoogleImageGenConfig().map_openai_params( + non_default_params={ + "imageConfig": explicit_image_config, + "size": "768x1376", + }, + optional_params={}, + model="gemini-3-pro-image-preview", + drop_params=False, + ) + + assert mapped_params["imageConfig"] == explicit_image_config + + +def test_gemini_image_generation_ignores_non_dict_image_config(): + from litellm.llms.gemini.image_generation.transformation import GoogleImageGenConfig + + mapped_params = GoogleImageGenConfig().map_openai_params( + non_default_params={ + "size": "768x1376", + "imageConfig": "not-a-dict", + }, + optional_params={}, + model="gemini-3-pro-image-preview", + drop_params=False, + ) + + assert mapped_params["imageConfig"] == {"aspectRatio": "9:16", "imageSize": "1K"} + + +@pytest.mark.parametrize( + "size, expected_aspect_ratio, expected_image_size", + GEMINI_3_IMAGE_SIZE_MAPPINGS, +) +def test_gemini_image_generation_openai_size_maps_to_google_table( + size: str, expected_aspect_ratio: str, expected_image_size: str +): + from litellm.llms.gemini.common_utils import ( + map_openai_size_to_gemini_image_config, + ) + + assert map_openai_size_to_gemini_image_config( + size, "gemini-3-pro-image-preview" + ) == { + "aspectRatio": expected_aspect_ratio, + "imageSize": expected_image_size, + } + + +@pytest.mark.parametrize( + "size, expected_aspect_ratio, expected_image_size", + [ + ("1000x1800", "9:16", "1K"), + ("1800x1000", "16:9", "1K"), + ("3000x3000", "1:1", "2K"), + ("500x500", "1:1", "512"), + ("1280x896", "4:3", "1K"), + ("896x1280", "3:4", "1K"), + ], +) +def test_gemini_image_generation_openai_size_snaps_to_nearest_option( + size: str, expected_aspect_ratio: str, expected_image_size: str +): + from litellm.llms.gemini.common_utils import ( + map_openai_size_to_gemini_image_config, + ) + + assert map_openai_size_to_gemini_image_config( + size, "gemini-3-pro-image-preview" + ) == { + "aspectRatio": expected_aspect_ratio, + "imageSize": expected_image_size, + } + + +@pytest.mark.parametrize("size", ["auto", "invalid", "0x1024", "1024x0"]) +def test_gemini_image_generation_openai_size_auto_uses_google_defaults(size: str): + from litellm.llms.gemini.common_utils import ( + map_openai_size_to_gemini_image_config, + ) + + assert map_openai_size_to_gemini_image_config( + size, "gemini-3-pro-image-preview" + ) is None + + def test_gemini_imagen_models_use_predict_endpoint(): """ Test that Imagen models still use :predict endpoint (not broken by gemini-2.5-flash-image-preview fix) @@ -387,6 +584,7 @@ def test_gemini_imagen_models_use_predict_endpoint(): response = litellm.image_generation( model="gemini/imagen-3.0-generate-001", prompt="Generate a simple test image", + size="1280x896", api_key="test_api_key", ) @@ -410,6 +608,9 @@ def test_gemini_imagen_models_use_predict_endpoint(): request_data = call_args.kwargs.get("json", {}) assert "instances" in request_data assert "parameters" in request_data + assert request_data["parameters"]["aspectRatio"] == "4:3" + assert request_data["parameters"]["imageSize"] == "1K" + assert "imageConfig" not in request_data["parameters"] def test_gemini_thinking(): diff --git a/tests/proxy_unit_tests/test_auth_checks.py b/tests/proxy_unit_tests/test_auth_checks.py index d9f4a6e56b8..e7136ecb195 100644 --- a/tests/proxy_unit_tests/test_auth_checks.py +++ b/tests/proxy_unit_tests/test_auth_checks.py @@ -38,8 +38,12 @@ from litellm.proxy.utils import CallInfo @pytest.mark.asyncio async def test_get_end_user_object(customer_spend, customer_budget): """ - Scenario 1: normal - Scenario 2: user over budget + Scenario 1: normal - get_end_user_object returns the cached user + Scenario 2: user over budget - NOTE: budget enforcement now happens in + common_checks() via _check_end_user_budget(), not in get_end_user_object() + + This test verifies that get_end_user_object correctly retrieves the end user + from cache. Budget enforcement is tested separately in test_check_end_user_budget(). """ end_user_id = "my-test-customer" _budget = LiteLLM_BudgetTable(max_budget=customer_budget) @@ -58,31 +62,62 @@ async def test_get_end_user_object(customer_spend, customer_budget): value=end_user_obj, model_type=LiteLLM_EndUserTable, ) + # get_end_user_object only fetches data - it no longer enforces budget + # Budget enforcement happens in common_checks() via _check_end_user_budget() + result = await get_end_user_object( + end_user_id=end_user_id, + prisma_client="RANDOM VALUE", # type: ignore + user_api_key_cache=_cache, + route="/v1/chat/completions", + ) + assert result is not None + assert result.user_id == end_user_id + + +@pytest.mark.parametrize("customer_spend, customer_budget", [(0, 10), (10, 0)]) +@pytest.mark.asyncio +async def test_check_end_user_budget(customer_spend, customer_budget): + """ + Test _check_end_user_budget enforcement: + - Scenario 1: customer_spend=0, customer_budget=10 - should pass (under budget) + - Scenario 2: customer_spend=10, customer_budget=0 - should fail (over budget) + + Note: Budget enforcement for end users happens in common_checks() via + _check_end_user_budget(), not in get_end_user_object(). + """ + from litellm.proxy.auth.auth_checks import _check_end_user_budget + + _budget = LiteLLM_BudgetTable(max_budget=customer_budget) + end_user_obj = LiteLLM_EndUserTable( + user_id="my-test-customer", + spend=customer_spend, + litellm_budget_table=_budget, + blocked=False, + ) + + should_exceed = customer_spend > customer_budget + try: - await get_end_user_object( - end_user_id=end_user_id, - prisma_client="RANDOM VALUE", # type: ignore - user_api_key_cache=_cache, + await _check_end_user_budget( + end_user_obj=end_user_obj, route="/v1/chat/completions", ) - if customer_spend > customer_budget: + if should_exceed: pytest.fail( - "Expected call to fail. Customer Spend={}, Customer Budget={}".format( + "Expected BudgetExceededError. Customer Spend={}, Customer Budget={}".format( customer_spend, customer_budget ) ) - except Exception as e: - if ( - isinstance(e, litellm.BudgetExceededError) - and customer_spend > customer_budget - ): - pass - else: + except litellm.BudgetExceededError as e: + if not should_exceed: pytest.fail( - "Expected call to work. Customer Spend={}, Customer Budget={}, Error={}".format( + "Unexpected BudgetExceededError. Customer Spend={}, Customer Budget={}, Error={}".format( customer_spend, customer_budget, str(e) ) ) + # Verify the error has correct info + assert e.current_cost == customer_spend + assert e.max_budget == customer_budget @pytest.mark.parametrize( diff --git a/tests/proxy_unit_tests/test_default_end_user_budget_simple.py b/tests/proxy_unit_tests/test_default_end_user_budget_simple.py index 970a7ab4718..6170b0a972e 100644 --- a/tests/proxy_unit_tests/test_default_end_user_budget_simple.py +++ b/tests/proxy_unit_tests/test_default_end_user_budget_simple.py @@ -134,9 +134,14 @@ async def test_explicit_budget_not_overridden_by_default(): @pytest.mark.asyncio async def test_budget_enforcement_blocks_over_budget_users(): """ - Core scenario: Budget limits are actually enforced. + Core scenario: Budget limits are actually enforced via _check_end_user_budget. Users who exceed their budget should be blocked. + + Note: Budget enforcement happens in common_checks() via _check_end_user_budget(), + not in get_end_user_object(). get_end_user_object only fetches the user data. """ + from litellm.proxy.auth.auth_checks import _check_end_user_budget + end_user_id = f"test_user_{uuid.uuid4().hex}" default_budget_id = str(uuid.uuid4()) litellm.max_end_user_budget_id = default_budget_id @@ -170,12 +175,23 @@ async def test_budget_enforcement_blocks_over_budget_users(): mock_cache.async_get_cache = AsyncMock(return_value=None) mock_cache.async_set_cache = AsyncMock() - # Should raise BudgetExceededError + # First, get the end user object (this just fetches data, doesn't enforce budget) + result = await get_end_user_object( + end_user_id=end_user_id, + prisma_client=mock_prisma_client, + user_api_key_cache=mock_cache, + route="/chat/completions", + ) + + # Verify user was fetched with default budget applied + assert result is not None + assert result.litellm_budget_table is not None + assert result.litellm_budget_table.max_budget == 10.0 + + # Now test budget enforcement separately via _check_end_user_budget with pytest.raises(litellm.BudgetExceededError) as exc_info: - await get_end_user_object( - end_user_id=end_user_id, - prisma_client=mock_prisma_client, - user_api_key_cache=mock_cache, + await _check_end_user_budget( + end_user_obj=result, route="/chat/completions", ) diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py index 9c08175767d..6fdabe64e25 100644 --- a/tests/proxy_unit_tests/test_proxy_server.py +++ b/tests/proxy_unit_tests/test_proxy_server.py @@ -804,6 +804,7 @@ def test_img_gen(mock_aimage_generation, client_no_auth): "prompt": "A cute baby sea otter", "n": 1, "size": "1024x1024", + "imageConfig": {"aspectRatio": "9:16", "imageSize": "1K"}, } response = client_no_auth.post("/v1/images/generations", json=test_data) @@ -813,6 +814,7 @@ def test_img_gen(mock_aimage_generation, client_no_auth): prompt="A cute baby sea otter", n=1, size="1024x1024", + imageConfig={"aspectRatio": "9:16", "imageSize": "1K"}, metadata=mock.ANY, proxy_server_request=mock.ANY, secret_fields=mock.ANY, diff --git a/tests/test_litellm/completion_extras/__init__.py b/tests/test_litellm/completion_extras/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py b/tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py new file mode 100644 index 00000000000..b41dbd54b85 --- /dev/null +++ b/tests/test_litellm/completion_extras/test_responses_bridge_provider_propagation.py @@ -0,0 +1,116 @@ +""" +Regression test for https://github.com/BerriAI/litellm/issues/28505 - +the Responses API bridge double-strips the provider prefix from the +model name when a Chat Completions request has both `tools` and +`reasoning_effort`. + +Root cause: the bridge handler called `litellm.responses()` / +`litellm.aresponses()` without passing the already-resolved +`custom_llm_provider`. The downstream call then re-invoked +`get_llm_provider()` with `custom_llm_provider=None`, which stripped +a second provider prefix from a `provider/provider/model` deployment +string. + +This test pins both the sync and async bridge handler call sites: +the resolved `custom_llm_provider` must be forwarded to the underlying +`responses` / `aresponses` call so the provider isn't re-detected. +""" + +from unittest.mock import MagicMock, patch + +import pytest + +from litellm.completion_extras.litellm_responses_transformation.handler import ( + ResponsesToCompletionBridgeHandler, +) + + +def _validated_kwargs(): + return { + "model": "openai/openai/openai/gpt-5.5", + "messages": [{"role": "user", "content": "hi"}], + "optional_params": {}, + "litellm_params": {}, + "headers": {}, + "model_response": MagicMock(), + "logging_obj": MagicMock(), + "custom_llm_provider": "openai", + } + + +def test_sync_completion_forwards_custom_llm_provider(): + handler = ResponsesToCompletionBridgeHandler() + handler.transformation_handler = MagicMock() + handler.transformation_handler.transform_request.return_value = { + "model": "openai/openai/openai/gpt-5.5", + "input": [], + # `_build_sanitized_litellm_params` spreads `custom_llm_provider` from + # `litellm_params` into request_data on the real bridge path. Seed + # it here so the test exercises the overwrite (not an explicit kwarg + # that would TypeError against an already-present key). + "custom_llm_provider": "should-be-overwritten", + } + handler.transformation_handler.transform_response.return_value = ( + _validated_kwargs()["model_response"] + ) + with ( + patch.object( + handler, "validate_input_kwargs", return_value=_validated_kwargs() + ), + patch( + "litellm.responses", + return_value=MagicMock(spec=[]), + ) as mock_responses, + ): + # The handler routes ResponsesAPIResponse through transform_response. + # We just want to verify the kwargs going INTO responses(). + try: + handler.completion(acompletion=False) + except Exception: + # Downstream handling (transform_response, type checks) is not + # the subject of this test. + pass + assert mock_responses.called + kwargs = mock_responses.call_args.kwargs + assert kwargs.get("custom_llm_provider") == "openai", ( + "sync bridge must forward custom_llm_provider to litellm.responses() " + "so the downstream get_llm_provider() call does not re-strip the " + "provider prefix on a provider/provider/model deployment string" + ) + + +@pytest.mark.asyncio +async def test_async_completion_forwards_custom_llm_provider(): + handler = ResponsesToCompletionBridgeHandler() + handler.transformation_handler = MagicMock() + handler.transformation_handler.transform_request.return_value = { + "model": "openai/openai/openai/gpt-5.5", + "input": [], + # `_build_sanitized_litellm_params` spreads `custom_llm_provider` from + # `litellm_params` into request_data on the real bridge path. Seed + # it here so the test exercises the overwrite (not an explicit kwarg + # that would TypeError against an already-present key). + "custom_llm_provider": "should-be-overwritten", + } + + async def _fake_aresponses(**kwargs): + _fake_aresponses.kwargs = kwargs + return MagicMock(spec=[]) + + _fake_aresponses.kwargs = {} + + with ( + patch.object( + handler, "validate_input_kwargs", return_value=_validated_kwargs() + ), + patch("litellm.aresponses", _fake_aresponses), + ): + try: + await handler.acompletion() + except Exception: + pass + assert _fake_aresponses.kwargs.get("custom_llm_provider") == "openai", ( + "async bridge must forward custom_llm_provider to litellm.aresponses() " + "so the downstream get_llm_provider() call does not re-strip the " + "provider prefix on a provider/provider/model deployment string" + ) diff --git a/tests/test_litellm/integrations/opik/test_opik_extractors.py b/tests/test_litellm/integrations/opik/test_opik_extractors.py new file mode 100644 index 00000000000..6f85a1c6090 --- /dev/null +++ b/tests/test_litellm/integrations/opik/test_opik_extractors.py @@ -0,0 +1,84 @@ +from litellm.integrations.opik.opik_payload_builder.extractors import ( + extract_opik_metadata, +) + + +def test_extract_opik_metadata_fills_missing_keys_from_auth_metadata(): + litellm_metadata = {"opik": {"project_name": "my-proj"}} + standard_logging_metadata = { + "user_api_key_auth_metadata": { + "opik": { + "workspace": "auth-workspace", + "project_name": "auth-project", + } + } + } + + result = extract_opik_metadata( + litellm_metadata=litellm_metadata, + standard_logging_metadata=standard_logging_metadata, + ) + + assert result == { + "project_name": "my-proj", + "workspace": "auth-workspace", + } + + +def test_extract_opik_metadata_request_metadata_overrides_auth_metadata(): + litellm_metadata = { + "opik": { + "workspace": "request-workspace", + "thread_id": "request-thread", + } + } + standard_logging_metadata = { + "user_api_key_auth_metadata": { + "opik": { + "workspace": "auth-workspace", + "thread_id": "auth-thread", + "project_name": "auth-project", + } + } + } + + result = extract_opik_metadata( + litellm_metadata=litellm_metadata, + standard_logging_metadata=standard_logging_metadata, + ) + + assert result == { + "workspace": "request-workspace", + "thread_id": "request-thread", + "project_name": "auth-project", + } + + +def test_extract_opik_metadata_requester_metadata_overrides_all_other_sources(): + litellm_metadata = {"opik": {"project_name": "request-project"}} + standard_logging_metadata = { + "user_api_key_auth_metadata": { + "opik": { + "workspace": "auth-workspace", + "project_name": "auth-project", + } + }, + "requester_metadata": { + "opik": { + "workspace": "requester-workspace", + "thread_id": "requester-thread", + "project_name": "requester-project", + } + }, + } + + result = extract_opik_metadata( + litellm_metadata=litellm_metadata, + standard_logging_metadata=standard_logging_metadata, + ) + + assert result == { + "project_name": "requester-project", + "workspace": "requester-workspace", + "thread_id": "requester-thread", + } diff --git a/tests/test_litellm/integrations/test_opentelemetry.py b/tests/test_litellm/integrations/test_opentelemetry.py index f6dee9b64c9..0601f9c0eef 100644 --- a/tests/test_litellm/integrations/test_opentelemetry.py +++ b/tests/test_litellm/integrations/test_opentelemetry.py @@ -1263,7 +1263,6 @@ class TestOpenTelemetry(unittest.TestCase): ) as mock_get_headers, patch.object(otel, "_get_tracer_with_dynamic_headers") as mock_get_tracer, ): - # Test case 1: With dynamic headers mock_get_headers.return_value = { "arize-space-id": "test-space", @@ -2668,7 +2667,7 @@ class TestOpenTelemetryExternalSpan(unittest.TestCase): # Verify parent span is still recording after each call self.assertTrue( parent_span.is_recording(), - f"External span should still be recording after completion #{i+1}", + f"External span should still be recording after completion #{i + 1}", ) # Verify all spans have the same trace_id @@ -5170,6 +5169,138 @@ class TestOpenTelemetryPreprocessingDuration(unittest.TestCase): assert "litellm.preprocessing.duration_ms" not in self._attr(span, exp) +class TestGetSpanContextLitellmMetadataFallback(unittest.TestCase): + """ + Tests for _get_span_context() falling back to litellm_metadata. + + On /v1/messages (Anthropic Messages API) and other LITELLM_METADATA_ROUTES, + litellm_parent_otel_span is stored in litellm_params["litellm_metadata"] + instead of litellm_params["metadata"]. _get_span_context() must check + both locations. + + Fixes: https://github.com/BerriAI/litellm/issues/27934 + """ + + def test_span_context_from_metadata(self): + """Parent span is found when stored in litellm_params['metadata'] (OpenAI path).""" + otel = OpenTelemetry() + mock_span = MagicMock() + mock_span.get_span_context.return_value = MagicMock(is_valid=True) + + kwargs = { + "litellm_params": { + "metadata": {"litellm_parent_otel_span": mock_span}, + } + } + + ctx, detected_span = otel._get_span_context(kwargs) + self.assertIsNotNone(ctx) + # Should NOT fall through to "no parent context" path + self.assertIsNone(detected_span) + + def test_span_context_from_litellm_metadata_fallback(self): + """Parent span is found when stored in litellm_params['litellm_metadata'] (Anthropic path).""" + otel = OpenTelemetry() + mock_span = MagicMock() + mock_span.get_span_context.return_value = MagicMock(is_valid=True) + + kwargs = { + "litellm_params": { + "metadata": { + "user_id": "test-user" + }, # Anthropic native metadata, no span + "litellm_metadata": {"litellm_parent_otel_span": mock_span}, + } + } + + ctx, detected_span = otel._get_span_context(kwargs) + self.assertIsNotNone(ctx) + self.assertIsNone(detected_span) + + def test_span_context_metadata_takes_priority(self): + """When both metadata and litellm_metadata have the span, metadata wins.""" + otel = OpenTelemetry() + span_from_metadata = MagicMock(name="span_from_metadata") + span_from_metadata.get_span_context.return_value = MagicMock(is_valid=True) + span_from_litellm_metadata = MagicMock(name="span_from_litellm_metadata") + span_from_litellm_metadata.get_span_context.return_value = MagicMock( + is_valid=True + ) + + kwargs = { + "litellm_params": { + "metadata": {"litellm_parent_otel_span": span_from_metadata}, + "litellm_metadata": { + "litellm_parent_otel_span": span_from_litellm_metadata + }, + } + } + + ctx, detected_span = otel._get_span_context(kwargs) + self.assertIsNotNone(ctx) + self.assertIsNone(detected_span) + # metadata span is found first, so get_span_context on the + # litellm_metadata span should never be called — proving + # metadata takes priority over litellm_metadata. + span_from_litellm_metadata.get_span_context.assert_not_called() + + def test_span_context_no_parent_when_neither_has_span(self): + """When neither metadata nor litellm_metadata has a span, returns (None, None).""" + otel = OpenTelemetry() + + kwargs = { + "litellm_params": { + "metadata": {"user_id": "test-user"}, + "litellm_metadata": {"some_key": "some_value"}, + } + } + + ctx, detected_span = otel._get_span_context(kwargs) + # No parent span in either metadata dict and no active span in test + # context, so both should be None. + self.assertIsNone(ctx) + self.assertIsNone(detected_span) + + +class TestEndProxySpanLitellmMetadataFallback(unittest.TestCase): + """ + Tests for _end_proxy_span_from_kwargs() falling back to litellm_metadata. + + Fixes: https://github.com/BerriAI/litellm/issues/27934 + """ + + def test_end_proxy_span_from_metadata(self): + """Proxy span is found and ended from litellm_params['metadata'].""" + otel = OpenTelemetry() + mock_span = MagicMock() + mock_span.name = "Received Proxy Server Request" + mock_span.is_recording.return_value = True + + kwargs = { + "litellm_params": { + "metadata": {"litellm_parent_otel_span": mock_span}, + } + } + + otel._end_proxy_span_from_kwargs(kwargs, end_time=datetime.now()) + mock_span.end.assert_called_once() + + def test_end_proxy_span_from_litellm_metadata(self): + """Proxy span is found and ended from litellm_params['litellm_metadata'] (fallback).""" + otel = OpenTelemetry() + mock_span = MagicMock() + mock_span.name = "Received Proxy Server Request" + mock_span.is_recording.return_value = True + + kwargs = { + "litellm_params": { + "metadata": {"user_id": "test-user"}, # No span here + "litellm_metadata": {"litellm_parent_otel_span": mock_span}, + } + } + + otel._end_proxy_span_from_kwargs(kwargs, end_time=datetime.now()) + mock_span.end.assert_called_once() class TestOpenTelemetryInferenceIdentityAttributes(unittest.TestCase): """team_metadata, http.route, and both model names (the user-facing model_group alias and the dispatched provider model) must land on the diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py index 129ea237efe..91fd07dcffc 100644 --- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py +++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py @@ -22,6 +22,18 @@ from litellm.litellm_core_utils.prompt_templates.factory import ( from litellm.types.llms.openai import ChatCompletionToolMessage +def _get_gemini_function_response_inline_data_parts(result): + assert isinstance(result, list), "expected Gemini parts list" + assert len(result) == 1, "multimodal function responses should stay in one part" + function_response_part = result[0] + assert ( + "inline_data" not in function_response_part + ), "inline_data should be nested under function_response.parts" + function_response = function_response_part["function_response"] + nested_parts = function_response["parts"] + return [part["inline_data"] for part in nested_parts if "inline_data" in part] + + def test_ollama_pt_simple_messages(): """Test basic functionality with simple text messages""" messages = [ @@ -615,8 +627,8 @@ def test_convert_gemini_tool_call_result_with_image_url(): message=message_str_format, last_message_with_tool_calls=last_message_with_tool_calls, ) - # Should have inline_data for the image - assert isinstance(result, list) and any("inline_data" in p for p in result) + inline_parts = _get_gemini_function_response_inline_data_parts(result) + assert len(inline_parts) == 1 # Test with dict image_url format (OpenAI standard) message_dict_format = ChatCompletionToolMessage( @@ -635,7 +647,8 @@ def test_convert_gemini_tool_call_result_with_image_url(): message=message_dict_format, last_message_with_tool_calls=last_message_with_tool_calls, ) - assert isinstance(result2, list) and any("inline_data" in p for p in result2) + inline_parts = _get_gemini_function_response_inline_data_parts(result2) + assert len(inline_parts) == 1 def test_convert_gemini_tool_call_result_with_anthropic_image_block(): @@ -677,11 +690,10 @@ def test_convert_gemini_tool_call_result_with_anthropic_image_block(): message=message, last_message_with_tool_calls=last_message_with_tool_calls, ) - assert isinstance(result, list), "expected a list of parts" - inline_parts = [p for p in result if "inline_data" in p] + inline_parts = _get_gemini_function_response_inline_data_parts(result) assert len(inline_parts) == 1, "expected exactly one inline_data part" - assert inline_parts[0]["inline_data"]["mime_type"] == "image/png" - assert inline_parts[0]["inline_data"]["data"] == tiny_png_b64 + assert inline_parts[0]["mime_type"] == "image/png" + assert inline_parts[0]["data"] == tiny_png_b64 def test_convert_gemini_tool_call_result_with_multiple_anthropic_image_blocks(): @@ -734,12 +746,11 @@ def test_convert_gemini_tool_call_result_with_multiple_anthropic_image_blocks(): message=message, last_message_with_tool_calls=last_message_with_tool_calls, ) - assert isinstance(result, list), "expected a list of parts" - inline_parts = [p for p in result if "inline_data" in p] + inline_parts = _get_gemini_function_response_inline_data_parts(result) assert ( len(inline_parts) == 2 ), f"expected 2 inline_data parts, got {len(inline_parts)}" - mime_types = {p["inline_data"]["mime_type"] for p in inline_parts} + mime_types = {p["mime_type"] for p in inline_parts} assert mime_types == {"image/png", "image/jpeg"} @@ -773,13 +784,12 @@ def test_convert_gemini_tool_call_result_with_data_url_string(): message=message, last_message_with_tool_calls=last_message_with_tool_calls, ) - assert isinstance(result, list), "expected a list of parts" - inline_parts = [p for p in result if "inline_data" in p] + inline_parts = _get_gemini_function_response_inline_data_parts(result) assert ( len(inline_parts) == 1 ), "data-URL image string was not converted to inline_data" - assert inline_parts[0]["inline_data"]["mime_type"] == "image/png" - assert inline_parts[0]["inline_data"]["data"] == tiny_png_b64 + assert inline_parts[0]["mime_type"] == "image/png" + assert inline_parts[0]["data"] == tiny_png_b64 def test_convert_gemini_tool_call_result_with_data_url_extra_params(): @@ -811,12 +821,11 @@ def test_convert_gemini_tool_call_result_with_data_url_extra_params(): message=message, last_message_with_tool_calls=last_message_with_tool_calls, ) - assert isinstance(result, list), "expected a list of parts" - inline_parts = [p for p in result if "inline_data" in p] + inline_parts = _get_gemini_function_response_inline_data_parts(result) assert len(inline_parts) == 1 assert ( - inline_parts[0]["inline_data"]["mime_type"] == "image/png" - ), f"expected clean 'image/png', got '{inline_parts[0]['inline_data']['mime_type']}'" + inline_parts[0]["mime_type"] == "image/png" + ), f"expected clean 'image/png', got '{inline_parts[0]['mime_type']}'" def test_bedrock_tools_unpack_defs(): diff --git a/tests/test_litellm/llms/azure_ai/test_azure_ai_kimi_k26_metadata.py b/tests/test_litellm/llms/azure_ai/test_azure_ai_kimi_k26_metadata.py new file mode 100644 index 00000000000..812b9288ca8 --- /dev/null +++ b/tests/test_litellm/llms/azure_ai/test_azure_ai_kimi_k26_metadata.py @@ -0,0 +1,76 @@ +""" +Test Azure AI Kimi K2.6 model metadata. +""" + +import json +from importlib.resources import files + +import pytest + + +@pytest.fixture(scope="module") +def use_local_model_cost_map(): + monkeypatch = pytest.MonkeyPatch() + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + + import litellm + from litellm.utils import _invalidate_model_cost_lowercase_map + + original_model_cost = litellm.model_cost + litellm.model_cost = json.loads( + files("litellm") + .joinpath("model_prices_and_context_window_backup.json") + .read_text(encoding="utf-8") + ) + litellm.get_model_info.cache_clear() + _invalidate_model_cost_lowercase_map() + try: + yield litellm + finally: + litellm.model_cost = original_model_cost + litellm.get_model_info.cache_clear() + _invalidate_model_cost_lowercase_map() + monkeypatch.undo() + + +def test_azure_ai_kimi_k26_model_info(use_local_model_cost_map): + model_info = use_local_model_cost_map.get_model_info(model="azure_ai/kimi-k2.6") + + assert model_info["litellm_provider"] == "azure_ai" + assert model_info["mode"] == "chat" + assert model_info["max_input_tokens"] == 262144 + assert model_info["max_output_tokens"] == 262144 + assert model_info["max_tokens"] == 262144 + assert model_info["input_cost_per_token"] == pytest.approx(9.5e-07) + assert model_info["output_cost_per_token"] == pytest.approx(4e-06) + assert model_info["supports_function_calling"] is True + assert model_info["supports_reasoning"] is True + assert model_info["supports_tool_choice"] is True + assert model_info["supports_vision"] is True + + +def test_azure_ai_kimi_k26_raw_model_cost_entry(use_local_model_cost_map): + model_info = use_local_model_cost_map.model_cost["azure_ai/kimi-k2.6"] + + assert model_info["supported_modalities"] == ["text", "image"] + assert model_info["supported_output_modalities"] == ["text"] + assert model_info["supports_function_calling"] is True + assert model_info["supports_reasoning"] is True + assert model_info["supports_tool_choice"] is True + assert model_info["supports_vision"] is True + + +def test_azure_ai_kimi_k26_cost_per_token(use_local_model_cost_map): + from litellm.llms.azure_ai.cost_calculator import cost_per_token + from litellm.types.utils import Usage + + usage = Usage( + prompt_tokens=1_000_000, + completion_tokens=1_000_000, + total_tokens=2_000_000, + ) + + prompt_cost, completion_cost = cost_per_token(model="kimi-k2.6", usage=usage) + + assert prompt_cost == pytest.approx(0.95) + assert completion_cost == pytest.approx(4.0) diff --git a/tests/test_litellm/llms/gemini/image_edit/test_gemini_image_edit_transformation.py b/tests/test_litellm/llms/gemini/image_edit/test_gemini_image_edit_transformation.py index 682df923693..9b57e1991de 100644 --- a/tests/test_litellm/llms/gemini/image_edit/test_gemini_image_edit_transformation.py +++ b/tests/test_litellm/llms/gemini/image_edit/test_gemini_image_edit_transformation.py @@ -7,6 +7,8 @@ from unittest.mock import MagicMock import httpx import pytest +import litellm +from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup from litellm.llms.gemini.image_edit.transformation import GeminiImageEditConfig @@ -19,6 +21,7 @@ class TestGeminiImageEditTransformation: def test_map_openai_params(self) -> None: optional_params: Dict[str, object] = { + "n": 2, "size": "1792x1024", "response_format": "b64_json", "quality": "high", @@ -30,20 +33,77 @@ class TestGeminiImageEditTransformation: drop_params=False, ) - assert mapped["aspectRatio"] == "16:9" + assert mapped["imageConfig"] == {"aspectRatio": "16:9"} + assert mapped["sampleCount"] == 2 assert "response_format" not in mapped assert "quality" not in mapped + def test_map_openai_params_with_image_size_for_gemini_3(self) -> None: + optional_params: Dict[str, object] = { + "size": "768x1376", + } + + mapped = self.config.map_openai_params( + image_edit_optional_params=optional_params, # type: ignore[arg-type] + model="gemini-3-pro-image-preview", + drop_params=False, + ) + + assert mapped["imageConfig"] == {"aspectRatio": "9:16", "imageSize": "1K"} + + def test_map_openai_params_forwards_image_config_as_is(self) -> None: + optional_params: Dict[str, object] = { + "size": "1024x1024", + "imageConfig": {"aspectRatio": "16:9", "imageSize": "512px"}, + } + + mapped = self.config.map_openai_params( + image_edit_optional_params=optional_params, # type: ignore[arg-type] + model="gemini-3-pro-image-preview", + drop_params=False, + ) + + assert mapped["imageConfig"] == {"aspectRatio": "16:9", "imageSize": "512px"} + + def test_map_openai_params_parses_form_image_config_json(self) -> None: + optional_params: Dict[str, object] = { + "imageConfig": '{"aspectRatio":"16:9","imageSize":"1K"}', + } + + mapped = self.config.map_openai_params( + image_edit_optional_params=optional_params, # type: ignore[arg-type] + model="gemini-3-pro-image-preview", + drop_params=False, + ) + + assert mapped["imageConfig"] == {"aspectRatio": "16:9", "imageSize": "1K"} + + def test_map_openai_params_rejects_malformed_form_image_config_json( + self, + ) -> None: + optional_params: Dict[str, object] = { + "imageConfig": "{bad", + } + + with pytest.raises(litellm.UnsupportedParamsError) as exc_info: + self.config.map_openai_params( + image_edit_optional_params=optional_params, # type: ignore[arg-type] + model="gemini-3-pro-image-preview", + drop_params=False, + ) + + assert "`imageConfig` must be valid JSON" in str(exc_info.value) + def test_transform_image_edit_request(self) -> None: image_bytes = b"fake_image_data" image = BytesIO(image_bytes) optional_params = { "sampleCount": 2, - "aspectRatio": "16:9", + "imageConfig": {"aspectRatio": "16:9", "imageSize": "2K"}, } request_body, files = self.config.transform_image_edit_request( - model=self.model, + model="gemini-3-pro-image-preview", prompt=self.prompt, image=[image], # Gemini pipeline passes list of images image_edit_optional_request_params=optional_params, @@ -61,7 +121,28 @@ class TestGeminiImageEditTransformation: assert base64.b64decode(inline_data["data"]) == image_bytes generation_config = request_body["generationConfig"] + assert generation_config["candidateCount"] == 2 assert generation_config["imageConfig"]["aspectRatio"] == "16:9" + assert generation_config["imageConfig"]["imageSize"] == "2K" + + def test_transform_image_edit_request_omits_image_size_for_gemini_25(self) -> None: + image = BytesIO(b"fake_image_data") + optional_params = { + "imageConfig": {"aspectRatio": "16:9", "imageSize": "2K"}, + } + + request_body, _ = self.config.transform_image_edit_request( + model=self.model, + prompt=self.prompt, + image=[image], + image_edit_optional_request_params=optional_params, + litellm_params=MagicMock(), + headers={}, + ) + + assert request_body["generationConfig"]["imageConfig"] == { + "aspectRatio": "16:9" + } def test_transform_image_edit_request_multiple_images(self) -> None: image_one = BytesIO(b"image_one") @@ -115,7 +196,16 @@ class TestGeminiImageEditTransformation: ] } }, - ] + ], + "usageMetadata": { + "promptTokenCount": 35, + "candidatesTokenCount": 1716, + "totalTokenCount": 1751, + "promptTokensDetails": [ + {"modality": "TEXT", "tokenCount": 30}, + {"modality": "IMAGE", "tokenCount": 5}, + ], + }, } mock_response = MagicMock(spec=httpx.Response) @@ -138,6 +228,19 @@ class TestGeminiImageEditTransformation: "utf-8" ) + usage = image_response.model_dump()["usage"] + assert usage["input_tokens"] == 35 + assert usage["output_tokens"] == 1716 + assert usage["prompt_tokens"] == 35 + assert usage["completion_tokens"] == 1716 + assert usage["prompt_tokens_details"]["image_tokens"] == 5 + assert usage["completion_tokens_details"]["image_tokens"] == 1716 + + logging_usage = StandardLoggingPayloadSetup.get_usage_as_dict( + response_obj=image_response.model_dump() + ) + assert logging_usage["completion_tokens_details"]["image_tokens"] == 1716 + def test_transform_image_edit_request_without_image_raises(self) -> None: optional_params = {} diff --git a/tests/test_litellm/llms/gemini/test_cost_calculator.py b/tests/test_litellm/llms/gemini/test_cost_calculator.py index 9bb83aa7cff..6d51bcd2c88 100644 --- a/tests/test_litellm/llms/gemini/test_cost_calculator.py +++ b/tests/test_litellm/llms/gemini/test_cost_calculator.py @@ -1,7 +1,23 @@ +import os + import pytest +import litellm from litellm.llms.gemini.cost_calculator import cost_per_web_search_request -from litellm.types.utils import PromptTokensDetailsWrapper, Usage +from litellm.llms.gemini.image_edit.cost_calculator import ( + cost_calculator as gemini_image_edit_cost_calculator, +) +from litellm.llms.gemini.image_generation.cost_calculator import ( + cost_calculator as gemini_image_generation_cost_calculator, +) +from litellm.types.utils import ( + ImageObject, + ImageResponse, + ImageUsage, + ImageUsageInputTokensDetails, + PromptTokensDetailsWrapper, + Usage, +) def _make_usage(web_search_requests: int) -> Usage: @@ -63,3 +79,171 @@ def test_no_usage_details(): usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150) cost = cost_per_web_search_request(usage=usage, model_info=model_info) assert cost == 0.0 + + +def test_gemini_image_edit_cost_prefers_token_usage_metadata(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + model = "gemini/gemini-3-pro-image-preview" + model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") + + input_text_tokens = 20 + input_image_tokens = 1120 + output_image_tokens = 1120 + prompt_tokens = input_text_tokens + input_image_tokens + image_response = ImageResponse( + data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")], + usage=ImageUsage( + input_tokens=prompt_tokens, + input_tokens_details=ImageUsageInputTokensDetails( + text_tokens=input_text_tokens, + image_tokens=input_image_tokens, + ), + output_tokens=output_image_tokens, + total_tokens=prompt_tokens + output_image_tokens, + ), + ) + + cost = gemini_image_edit_cost_calculator( + model=model, + image_response=image_response, + ) + + expected_cost = ( + prompt_tokens * model_info["input_cost_per_token"] + + output_image_tokens * model_info["output_cost_per_image_token"] + ) + flat_image_cost = ( + len(image_response.data or []) * model_info["output_cost_per_image"] + ) + assert round(cost, 10) == round(expected_cost, 10) + assert cost != flat_image_cost + + +def test_gemini_image_edit_cost_uses_output_token_details(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + model = "gemini/gemini-3-pro-image-preview" + model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") + + input_text_tokens = 20 + output_text_tokens = 213 + output_image_tokens = 1120 + output_tokens = output_text_tokens + output_image_tokens + image_response = ImageResponse( + data=[ImageObject(b64_json="img1")], + usage=ImageUsage( + input_tokens=input_text_tokens, + input_tokens_details=ImageUsageInputTokensDetails( + text_tokens=input_text_tokens, + image_tokens=0, + ), + output_tokens=output_tokens, + total_tokens=input_text_tokens + output_tokens, + prompt_tokens=input_text_tokens, + completion_tokens=output_tokens, + prompt_tokens_details={ + "text_tokens": input_text_tokens, + "image_tokens": 0, + }, + completion_tokens_details={ + "text_tokens": output_text_tokens, + "image_tokens": output_image_tokens, + }, + output_tokens_details={ + "text_tokens": output_text_tokens, + "image_tokens": output_image_tokens, + }, + ), + ) + + cost = gemini_image_edit_cost_calculator( + model=model, + image_response=image_response, + ) + + expected_cost = ( + input_text_tokens * model_info["input_cost_per_token"] + + output_text_tokens * model_info["output_cost_per_token"] + + output_image_tokens * model_info["output_cost_per_image_token"] + ) + all_output_as_image_cost = ( + input_text_tokens * model_info["input_cost_per_token"] + + (output_text_tokens + output_image_tokens) + * model_info["output_cost_per_image_token"] + ) + assert round(cost, 10) == round(expected_cost, 10) + assert cost != all_output_as_image_cost + + +def test_gemini_image_generation_cost_uses_output_token_details(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + model = "gemini/gemini-3-pro-image-preview" + model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") + + input_text_tokens = 20 + output_text_tokens = 213 + output_image_tokens = 1120 + output_tokens = output_text_tokens + output_image_tokens + image_response = ImageResponse( + data=[ImageObject(b64_json="img1")], + usage=ImageUsage( + input_tokens=input_text_tokens, + input_tokens_details=ImageUsageInputTokensDetails( + text_tokens=input_text_tokens, + image_tokens=0, + ), + output_tokens=output_tokens, + total_tokens=input_text_tokens + output_tokens, + prompt_tokens=input_text_tokens, + completion_tokens=output_tokens, + prompt_tokens_details={ + "text_tokens": input_text_tokens, + "image_tokens": 0, + }, + completion_tokens_details={ + "text_tokens": output_text_tokens, + "image_tokens": output_image_tokens, + }, + output_tokens_details={ + "text_tokens": output_text_tokens, + "image_tokens": output_image_tokens, + }, + ), + ) + + cost = gemini_image_generation_cost_calculator( + model=model, + image_response=image_response, + ) + + expected_cost = ( + input_text_tokens * model_info["input_cost_per_token"] + + output_text_tokens * model_info["output_cost_per_token"] + + output_image_tokens * model_info["output_cost_per_image_token"] + ) + all_output_as_image_cost = ( + input_text_tokens * model_info["input_cost_per_token"] + + (output_text_tokens + output_image_tokens) + * model_info["output_cost_per_image_token"] + ) + assert round(cost, 10) == round(expected_cost, 10) + assert cost != all_output_as_image_cost + + +def test_gemini_image_edit_cost_falls_back_to_flat_image_pricing(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + model = "gemini/gemini-3-pro-image-preview" + model_info = litellm.get_model_info(model=model, custom_llm_provider="gemini") + image_response = ImageResponse( + data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")] + ) + + cost = gemini_image_edit_cost_calculator( + model=model, + image_response=image_response, + ) + + assert cost == len(image_response.data or []) * model_info["output_cost_per_image"] diff --git a/tests/test_litellm/llms/gemini/test_gemini_image_generation_transformation.py b/tests/test_litellm/llms/gemini/test_gemini_image_generation_transformation.py new file mode 100644 index 00000000000..4610d1b99bf --- /dev/null +++ b/tests/test_litellm/llms/gemini/test_gemini_image_generation_transformation.py @@ -0,0 +1,240 @@ +import httpx + +from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup +from litellm.llms.gemini.image_generation.transformation import GoogleImageGenConfig +from litellm.types.utils import ImageResponse + + +def test_gemini_image_generation_request_uses_shared_generation_config(): + config = GoogleImageGenConfig() + + request = config.transform_image_generation_request( + model="gemini-3.1-flash-image-preview", + prompt="Generate a simple app icon", + optional_params={ + "sampleCount": 2, + "imageConfig": {"aspectRatio": "16:9", "imageSize": "2K"}, + }, + litellm_params={}, + headers={}, + ) + + assert request["contents"][0]["parts"] == [{"text": "Generate a simple app icon"}] + assert request["generationConfig"] == { + "response_modalities": ["IMAGE", "TEXT"], + "imageConfig": {"aspectRatio": "16:9", "imageSize": "2K"}, + "candidateCount": 2, + } + + +def test_gemini_image_generation_map_openai_params_maps_n_size_and_image_config(): + config = GoogleImageGenConfig() + + mapped = config.map_openai_params( + non_default_params={ + "n": 2, + "size": "768x1376", + "imageConfig": {"aspectRatio": "1:1", "imageSize": "512"}, + }, + optional_params={}, + model="gemini-3.1-flash-image-preview", + drop_params=False, + ) + + assert mapped == { + "sampleCount": 2, + "imageConfig": {"aspectRatio": "1:1", "imageSize": "512"}, + } + + +def test_imagen_generation_with_provider_prefix_uses_imagen_params_and_response(): + config = GoogleImageGenConfig() + + mapped = config.map_openai_params( + non_default_params={ + "n": 1, + "size": "1024x1024", + }, + optional_params={}, + model="gemini/imagen-4.0-generate-001", + drop_params=False, + ) + assert mapped == { + "sampleCount": 1, + "aspectRatio": "1:1", + "imageSize": "1K", + } + + request = config.transform_image_generation_request( + model="gemini/imagen-4.0-generate-001", + prompt="Generate a simple app icon", + optional_params=mapped, + litellm_params={}, + headers={}, + ) + assert request == { + "instances": [{"prompt": "Generate a simple app icon"}], + "parameters": { + "sampleCount": 1, + "aspectRatio": "1:1", + "imageSize": "1K", + }, + } + + result = config.transform_image_generation_response( + model="gemini/imagen-4.0-generate-001", + raw_response=httpx.Response( + status_code=200, + json={ + "predictions": [ + { + "bytesBase64Encoded": "fake-imagen-image", + } + ] + }, + ), + model_response=ImageResponse(data=[]), + logging_obj=None, + request_data={}, + optional_params={}, + litellm_params={}, + encoding=None, + ) + assert result.data is not None + assert result.data[0].b64_json == "fake-imagen-image" + + +def test_imagen_generation_forwards_mapped_openai_size_image_size(): + config = GoogleImageGenConfig() + + mapped = config.map_openai_params( + non_default_params={ + "size": "512x512", + }, + optional_params={}, + model="gemini/imagen-4.0-generate-001", + drop_params=False, + ) + assert mapped == {"aspectRatio": "1:1", "imageSize": "512"} + + request = config.transform_image_generation_request( + model="gemini/imagen-4.0-generate-001", + prompt="Generate a simple app icon", + optional_params=mapped, + litellm_params={}, + headers={}, + ) + + assert request == { + "instances": [{"prompt": "Generate a simple app icon"}], + "parameters": {"aspectRatio": "1:1", "imageSize": "512"}, + } + + +def test_gemini_image_generation_usage_includes_chat_token_details(): + config = GoogleImageGenConfig() + raw_response = httpx.Response( + status_code=200, + json={ + "candidates": [ + { + "content": { + "parts": [ + { + "inlineData": { + "mimeType": "image/png", + "data": "fake-image", + } + } + ] + } + } + ], + "usageMetadata": { + "promptTokenCount": 35, + "candidatesTokenCount": 1716, + "totalTokenCount": 1751, + "promptTokensDetails": [ + {"modality": "TEXT", "tokenCount": 30}, + {"modality": "IMAGE", "tokenCount": 5}, + ], + "candidatesTokensDetails": [ + {"modality": "TEXT", "tokenCount": 213}, + {"modality": "IMAGE", "tokenCount": 1120}, + ], + }, + }, + ) + + result = config.transform_image_generation_response( + model="gemini-3.1-flash-image-preview", + raw_response=raw_response, + model_response=ImageResponse(data=[]), + logging_obj=None, + request_data={}, + optional_params={}, + litellm_params={}, + encoding=None, + ) + + usage = result.model_dump()["usage"] + + assert usage["input_tokens"] == 35 + assert usage["output_tokens"] == 1716 + assert usage["prompt_tokens"] == 35 + assert usage["completion_tokens"] == 1716 + assert usage["prompt_tokens_details"]["image_tokens"] == 5 + assert usage["completion_tokens_details"]["text_tokens"] == 596 + assert usage["completion_tokens_details"]["image_tokens"] == 1120 + assert usage["output_tokens_details"]["text_tokens"] == 596 + assert usage["output_tokens_details"]["image_tokens"] == 1120 + + logging_usage = StandardLoggingPayloadSetup.get_usage_as_dict( + response_obj=result.model_dump() + ) + assert logging_usage["completion_tokens_details"]["text_tokens"] == 596 + assert logging_usage["completion_tokens_details"]["image_tokens"] == 1120 + + +def test_gemini_image_generation_usage_without_output_details_treats_output_as_image(): + config = GoogleImageGenConfig() + raw_response = httpx.Response( + status_code=200, + json={ + "candidates": [ + { + "content": { + "parts": [ + { + "inlineData": { + "mimeType": "image/png", + "data": "fake-image", + } + } + ] + } + } + ], + "usageMetadata": { + "promptTokenCount": 35, + "candidatesTokenCount": 1716, + "totalTokenCount": 1751, + "promptTokensDetails": [{"modality": "TEXT", "tokenCount": 35}], + }, + }, + ) + + result = config.transform_image_generation_response( + model="gemini-3.1-flash-image-preview", + raw_response=raw_response, + model_response=ImageResponse(data=[]), + logging_obj=None, + request_data={}, + optional_params={}, + litellm_params={}, + encoding=None, + ) + + usage = result.model_dump()["usage"] + assert usage["completion_tokens_details"]["text_tokens"] == 0 + assert usage["completion_tokens_details"]["image_tokens"] == 1716 diff --git a/tests/test_litellm/llms/inception/__init__.py b/tests/test_litellm/llms/inception/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/inception/test_inception_chat_transformation.py b/tests/test_litellm/llms/inception/test_inception_chat_transformation.py new file mode 100644 index 00000000000..0750fb9e405 --- /dev/null +++ b/tests/test_litellm/llms/inception/test_inception_chat_transformation.py @@ -0,0 +1,326 @@ +""" +Tests for Inception (Mercury) chat provider integration +""" + +import json +import os +from unittest import mock + +import httpx + +import litellm +from litellm.llms.inception.chat.transformation import InceptionChatConfig + + +def test_inception_config_initialization(): + config = InceptionChatConfig() + assert config.custom_llm_provider == "inception" + + +def test_inception_chat_supports_diffusion_params(): + """The chat config must expose Inception's diffusion-LLM request controls""" + params = InceptionChatConfig().get_supported_openai_params("mercury-2") + for p in ( + "reasoning_effort", + "reasoning_summary", + "reasoning_summary_wait", + "diffusing", + "realtime", + "tools", + "tool_choice", + "response_format", + ): + assert p in params, f"{p} should be a supported chat param" + + +def test_inception_chat_sends_diffusion_params_in_body(): + """reasoning_effort (incl. `instant`) and the diffusion flags reach the request body""" + + captured = {} + + def fake_send(self, request, **kwargs): + captured["body"] = json.loads(request.content.decode()) + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=json.dumps( + { + "id": "c-1", + "object": "chat.completion", + "created": 1, + "model": "mercury-2", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "hi"}, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": 5, + "completion_tokens": 1, + "total_tokens": 6, + }, + } + ).encode(), + ) + + with mock.patch("httpx.Client.send", new=fake_send): + litellm.completion( + model="inception/mercury-2", + messages=[{"role": "user", "content": "hi"}], + api_key="sk-x", + reasoning_effort="instant", + reasoning_summary=True, + reasoning_summary_wait=True, + diffusing=True, + realtime=True, + max_completion_tokens=128, + ) + + body = captured["body"] + assert body["reasoning_effort"] == "instant" + assert body["reasoning_summary"] is True + assert body["reasoning_summary_wait"] is True + assert body["diffusing"] is True + assert body["realtime"] is True + assert body["max_tokens"] == 128 # max_completion_tokens mapped to max_tokens + + +def test_inception_chat_response_surfaces_reasoning_and_usage(): + """reasoning_summary / warning survive, and reasoning_tokens maps to usage details""" + + def fake_send(self, request, **kwargs): + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=json.dumps( + { + "id": "c-1", + "object": "chat.completion", + "created": 1, + "model": "mercury-2", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "answer"}, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": 5, + "completion_tokens": 2, + "total_tokens": 7, + "reasoning_tokens": 4, + "cached_input_tokens": 3, + }, + "reasoning_summary": { + "content": "step by step", + "status": "complete", + }, + "warning": "heads up", + } + ).encode(), + ) + + with mock.patch("httpx.Client.send", new=fake_send): + r = litellm.completion( + model="inception/mercury-2", + messages=[{"role": "user", "content": "hi"}], + api_key="sk-x", + ) + + assert r.reasoning_summary == {"content": "step by step", "status": "complete"} + assert r.warning == "heads up" + assert r.usage.completion_tokens_details.reasoning_tokens == 4 + assert r.usage.model_extra.get("cached_input_tokens") == 3 + + +def test_inception_get_openai_compatible_provider_info(): + config = InceptionChatConfig() + + with mock.patch.dict(os.environ, {}, clear=True): + with mock.patch.object(litellm, "inception_key", None): + api_base, api_key = config._get_openai_compatible_provider_info(None, None) + assert api_base == "https://api.inceptionlabs.ai/v1" + assert api_key is None + + with mock.patch.dict( + os.environ, + { + "INCEPTION_API_KEY": "test-key", + "INCEPTION_API_BASE": "https://custom.inceptionlabs.ai/v1", + }, + ): + api_base, api_key = config._get_openai_compatible_provider_info(None, None) + assert api_base == "https://custom.inceptionlabs.ai/v1" + assert api_key == "test-key" + + with mock.patch.dict( + os.environ, + { + "INCEPTION_API_KEY": "env-key", + "INCEPTION_API_BASE": "https://env.inceptionlabs.ai/v1", + }, + ): + api_base, api_key = config._get_openai_compatible_provider_info( + "https://param.inceptionlabs.ai/v1", "param-key" + ) + assert api_base == "https://param.inceptionlabs.ai/v1" + assert api_key == "param-key" + + +def test_inception_key_module_attr_fallback(): + """litellm.inception_key is used when no param/env key is provided""" + config = InceptionChatConfig() + with mock.patch.dict(os.environ, {}, clear=True): + with mock.patch.object(litellm, "inception_key", "module-attr-key"): + _, api_key = config._get_openai_compatible_provider_info(None, None) + assert api_key == "module-attr-key" + + +def test_inception_does_not_leak_key_to_caller_api_base(): + """ + The server-managed Inception key must not be forwarded to a caller-supplied + api_base. It is only resolved for the default/server base, or when the + caller also supplies their own key. + """ + config = InceptionChatConfig() + with mock.patch.dict( + os.environ, {"INCEPTION_API_KEY": "server-secret"}, clear=True + ): + with mock.patch.object(litellm, "inception_key", "module-secret"): + # caller overrides api_base without a key -> server key withheld + api_base, api_key = config._get_openai_compatible_provider_info( + "https://attacker.example/v1", None + ) + assert api_base == "https://attacker.example/v1" + assert api_key is None + + # caller overrides api_base AND supplies their own key -> used as-is + _, api_key = config._get_openai_compatible_provider_info( + "https://attacker.example/v1", "caller-key" + ) + assert api_key == "caller-key" + + # default/server base -> server-managed key resolved + _, api_key = config._get_openai_compatible_provider_info(None, None) + assert api_key == "module-secret" + + +def test_get_llm_provider_inception(): + from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider + + model, provider, _, _ = get_llm_provider("inception/mercury-2") + assert model == "mercury-2" + assert provider == "inception" + + model, provider, _, api_base = get_llm_provider( + "mercury-2", api_base="https://api.inceptionlabs.ai/v1" + ) + assert model == "mercury-2" + assert provider == "inception" + assert api_base == "https://api.inceptionlabs.ai/v1" + + +def test_inception_in_provider_lists(): + assert "inception" in litellm.openai_compatible_providers + assert "inception" in litellm.provider_list + assert "https://api.inceptionlabs.ai/v1" in litellm.openai_compatible_endpoints + + +def test_inception_model_configuration(): + from litellm import get_model_info + + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + litellm.inception_models = set() + litellm.add_known_models() + + info = get_model_info("inception/mercury-2") + assert info.get("litellm_provider") == "inception" + assert info.get("mode") == "chat" + assert info.get("max_input_tokens") == 128000 + assert info.get("input_cost_per_token") == 2.5e-07 + assert info.get("output_cost_per_token") == 7.5e-07 + assert info.get("cache_read_input_token_cost") == 2.5e-08 + assert info.get("supports_function_calling") is True + assert info.get("supports_tool_choice") is True + assert info.get("supports_response_schema") is True + + +def test_inception_model_list_populated(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + litellm.inception_models = set() + litellm.add_known_models() + + assert "inception/mercury-2" in litellm.inception_models + for model in litellm.inception_models: + assert model.startswith("inception/") + + +def test_inception_completion_targets_inception_endpoint(): + """ + End-to-end: a completion routed through the inception provider must hit + Inception's base URL and path, send a Bearer token, strip the + `inception/` prefix from the model name, and forward tool_choice. + """ + + captured = {} + + def fake_send(self, request, **kwargs): + captured["url"] = str(request.url) + captured["auth"] = request.headers.get("authorization") + captured["body"] = json.loads(request.content.decode()) + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=json.dumps( + { + "id": "cmpl-1", + "object": "chat.completion", + "created": 1, + "model": "mercury-2", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "hi"}, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": 5, + "completion_tokens": 1, + "total_tokens": 6, + }, + } + ).encode(), + ) + + tools = [ + { + "type": "function", + "function": { + "name": "f", + "parameters": {"type": "object", "properties": {}}, + }, + } + ] + with mock.patch("httpx.Client.send", new=fake_send): + response = litellm.completion( + model="inception/mercury-2", + messages=[{"role": "user", "content": "hello"}], + api_key="sk-test-fake-123", + tools=tools, + tool_choice="auto", + ) + + assert captured["url"] == "https://api.inceptionlabs.ai/v1/chat/completions" + assert captured["auth"] == "Bearer sk-test-fake-123" + assert captured["body"]["model"] == "mercury-2" + assert captured["body"]["tool_choice"] == "auto" + assert response.choices[0].message.content == "hi" diff --git a/tests/test_litellm/llms/inception/test_inception_completion_transformation.py b/tests/test_litellm/llms/inception/test_inception_completion_transformation.py new file mode 100644 index 00000000000..9b7c8dd3742 --- /dev/null +++ b/tests/test_litellm/llms/inception/test_inception_completion_transformation.py @@ -0,0 +1,300 @@ +""" +Tests for Inception (Mercury) fill-in-the-middle (FIM) provider integration +""" + +import json +import os +from unittest import mock + +import httpx +import pytest + +import litellm +from litellm.llms.inception.completion.transformation import ( + InceptionTextCompletionConfig, +) + + +def _fim_response_bytes(): + return json.dumps( + { + "id": "fim-1", + "object": "text_completion", + "created": 1, + "model": "mercury-edit-2", + "choices": [ + {"text": "a + b", "index": 0, "finish_reason": "stop", "logprobs": None} + ], + "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8}, + } + ).encode() + + +def test_inception_fim_supports_suffix_param(): + """The FIM config must keep `suffix` (otherwise FIM requests lose context)""" + config = InceptionTextCompletionConfig() + assert "suffix" in config.get_supported_openai_params("mercury-edit-2") + + mapped = config.map_openai_params( + non_default_params={"suffix": "\n return x", "max_completion_tokens": 50}, + optional_params={}, + model="mercury-edit-2", + drop_params=False, + ) + assert mapped["suffix"] == "\n return x" + assert mapped["max_tokens"] == 50 + + +def test_inception_fim_supported_params_match_schema(): + """FIM exposes the OpenAI subset of Inception's FIMCompletionRequest only""" + params = InceptionTextCompletionConfig().get_supported_openai_params( + "mercury-edit-2" + ) + for p in ("suffix", "top_p", "frequency_penalty", "presence_penalty", "stop"): + assert p in params + # Chat-only sampling controls are not part of Inception's FIM schema + for p in ("temperature", "seed", "logprobs", "n", "user"): + assert p not in params + + +def test_text_completion_inception_in_provider_lists(): + from litellm.types.utils import LlmProviders + + assert LlmProviders.TEXT_COMPLETION_INCEPTION == "text-completion-inception" + assert "text-completion-inception" in litellm.provider_list + + +def test_inception_get_supported_openai_params_dispatch(): + """litellm.get_supported_openai_params routes the FIM provider to our config""" + params = litellm.get_supported_openai_params( + model="mercury-edit-2", custom_llm_provider="text-completion-inception" + ) + assert "suffix" in params + assert "temperature" not in params + + +@pytest.mark.parametrize("provider", ["inception", "text-completion-inception"]) +def test_inception_validate_environment(provider): + model = ( + "inception/mercury-2" + if provider == "inception" + else "text-completion-inception/mercury-edit-2" + ) + + with mock.patch.dict(os.environ, {}, clear=True): + result = litellm.validate_environment(model) + assert result["keys_in_environment"] is False + assert "INCEPTION_API_KEY" in result["missing_keys"] + + with mock.patch.dict(os.environ, {"INCEPTION_API_KEY": "sk-x"}, clear=True): + result = litellm.validate_environment(model) + assert result["keys_in_environment"] is True + + +def test_inception_completion_endpoint_returns_chat_object(): + """ + Calling chat `completion()` with the FIM provider converts the text + completion result into a chat-shaped ModelResponse. + """ + + def fake_send(self, request, **kwargs): + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=_fim_response_bytes(), + ) + + with mock.patch("httpx.Client.send", new=fake_send): + r = litellm.completion( + model="text-completion-inception/mercury-edit-2", + messages=[{"role": "user", "content": "def add(a, b): return "}], + api_key="sk-x", + ) + + assert r.choices[0].message.content == "a + b" + + +@pytest.mark.asyncio +async def test_inception_fim_async(): + """async FIM path (acompletion) hits Inception's /v1/fim/completions""" + + captured = {} + + async def fake_asend(self, request, **kwargs): + captured["url"] = str(request.url) + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=_fim_response_bytes(), + ) + + with mock.patch("httpx.AsyncClient.send", new=fake_asend): + r = await litellm.atext_completion( + model="text-completion-inception/mercury-edit-2", + prompt="def add(a, b): return ", + suffix="\n", + api_key="sk-x", + max_tokens=10, + ) + + assert captured["url"] == "https://api.inceptionlabs.ai/v1/fim/completions" + assert r.choices[0].text == "a + b" + + +def test_inception_fim_model_configuration(): + from litellm import get_model_info + + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + litellm.text_completion_inception_models = set() + litellm.add_known_models() + + assert ( + "text-completion-inception/mercury-edit-2" + in litellm.text_completion_inception_models + ) + info = get_model_info("text-completion-inception/mercury-edit-2") + assert info.get("litellm_provider") == "text-completion-inception" + assert info.get("mode") == "completion" + assert info.get("max_input_tokens") == 32000 + + +def test_inception_fim_targets_fim_endpoint(): + """ + End-to-end: a FIM request must hit `/v1/fim/completions` (NOT + `/v1/completions`), carry the `suffix`, and parse the standard `text` field. + """ + + captured = {} + + def fake_send(self, request, **kwargs): + captured["url"] = str(request.url) + captured["auth"] = request.headers.get("authorization") + captured["body"] = json.loads(request.content.decode()) + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=json.dumps( + { + "id": "fim-1", + "object": "text_completion", + "created": 1, + "model": "mercury-edit-2", + "choices": [ + { + "text": "a + b", + "index": 0, + "finish_reason": "stop", + "logprobs": None, + } + ], + "usage": { + "prompt_tokens": 5, + "completion_tokens": 3, + "total_tokens": 8, + }, + } + ).encode(), + ) + + with mock.patch("httpx.Client.send", new=fake_send): + response = litellm.text_completion( + model="text-completion-inception/mercury-edit-2", + prompt="def add(a, b):\n return ", + suffix="\n", + api_key="sk-fim-fake", + max_tokens=20, + ) + + assert captured["url"] == "https://api.inceptionlabs.ai/v1/fim/completions" + assert captured["auth"] == "Bearer sk-fim-fake" + assert captured["body"]["model"] == "mercury-edit-2" + assert captured["body"]["suffix"] == "\n" + assert "prompt" in captured["body"] + assert response.choices[0].text == "a + b" + + +def test_inception_fim_does_not_leak_global_api_key(): + """ + Regression: the global litellm.api_key (commonly an OpenAI key) must not be + forwarded to Inception. Only an Inception-specific key (param, + litellm.inception_key, or INCEPTION_API_KEY) may be sent to the Inception base. + """ + + captured = {} + + def fake_send(self, request, **kwargs): + captured["auth"] = request.headers.get("authorization") + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=_fim_response_bytes(), + ) + + with mock.patch.dict( + os.environ, {"INCEPTION_API_KEY": "sk-inception-correct"}, clear=True + ): + with mock.patch.object(litellm, "inception_key", None): + with mock.patch.object(litellm, "api_key", "sk-global-should-not-leak"): + with mock.patch("httpx.Client.send", new=fake_send): + litellm.text_completion( + model="text-completion-inception/mercury-edit-2", + prompt="def add(a, b): return ", + max_tokens=10, + ) + + assert captured["auth"] == "Bearer sk-inception-correct" + + +def test_inception_fim_extra_body_forwards_vllm_params(): + """top_k / repetition_penalty are reachable via extra_body (not OpenAI params)""" + + captured = {} + + def fake_send(self, request, **kwargs): + captured["body"] = json.loads(request.content.decode()) + return httpx.Response( + status_code=200, + request=request, + headers={"content-type": "application/json"}, + content=json.dumps( + { + "id": "f-1", + "object": "text_completion", + "created": 1, + "model": "mercury-edit-2", + "choices": [ + { + "text": "x", + "index": 0, + "finish_reason": "stop", + "logprobs": None, + } + ], + "usage": { + "prompt_tokens": 2, + "completion_tokens": 1, + "total_tokens": 3, + }, + } + ).encode(), + ) + + with mock.patch("httpx.Client.send", new=fake_send): + litellm.text_completion( + model="text-completion-inception/mercury-edit-2", + prompt="def f(", + suffix=")", + api_key="sk-x", + top_p=0.9, + extra_body={"top_k": 40, "repetition_penalty": 1.1}, + ) + + body = captured["body"] + assert body["top_p"] == 0.9 + assert body["top_k"] == 40 + assert body["repetition_penalty"] == 1.1 diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_tool_call_followed_by_text_assistant.py b/tests/test_litellm/llms/vertex_ai/gemini/test_tool_call_followed_by_text_assistant.py new file mode 100644 index 00000000000..bbd12e25f43 --- /dev/null +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_tool_call_followed_by_text_assistant.py @@ -0,0 +1,57 @@ +""" +Regression test for tool-call / tool-result matching in the Gemini message converter. + +When an assistant message that contains tool_calls is followed by a *second* assistant +message that has no tool_calls (e.g. the model emits a short narration turn after the +tool call but before the tool result), the converter used to overwrite its +`last_message_with_tool_calls` reference with the text-only assistant message. The +subsequent tool result could then no longer be matched to its tool call, and conversion +failed with: + + Exception: Missing corresponding tool call for tool response message. + +This happens for any OpenAI-style history with that shape, independent of provider/model. +""" + +import pytest + +from litellm.llms.vertex_ai.gemini.transformation import ( + _gemini_convert_messages_with_history, +) + + +def _messages_with_text_assistant_between_tool_call_and_result(): + return [ + {"role": "user", "content": "list the files"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_abc123", + "type": "function", + "function": {"name": "shell", "arguments": '{"command": ["ls"]}'}, + } + ], + }, + # text-only assistant message in between (no tool_calls) + {"role": "assistant", "content": "Running the command now."}, + {"role": "tool", "tool_call_id": "call_abc123", "content": "math.py"}, + ] + + +def test_tool_result_matches_tool_call_with_text_assistant_in_between(): + messages = _messages_with_text_assistant_between_tool_call_and_result() + + # Should not raise "Missing corresponding tool call for tool response message". + contents = _gemini_convert_messages_with_history(messages=messages) + + # The function response must be present and carry the correct tool name. + function_responses = [ + part["function_response"] + for content in contents + for part in content["parts"] + if isinstance(part, dict) and part.get("function_response") + ] + assert function_responses, f"expected a functionResponse part, got: {contents}" + assert function_responses[0]["name"] == "shell" diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py index 263fb1c6e65..628a6ed4cba 100644 --- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py @@ -1154,44 +1154,82 @@ def test_convert_tool_response_with_base64_image(): ] } - # Convert tool response (returns list when image is present) + # Convert tool response with nested multimodal functionResponse.parts. result = convert_to_gemini_tool_call_result( tool_message, last_message_with_tool_calls ) - # Verify results - should be a list with 2 parts (function_response + inline_data) - assert isinstance( - result, list - ), f"Expected list when image present, got {type(result)}" - assert len(result) == 2, f"Expected 2 parts, got {len(result)}" - - # Find function_response part and inline_data part - function_response_part = None - inline_data_part = None - for part in result: - if "function_response" in part: - function_response_part = part - elif "inline_data" in part: - inline_data_part = part - - # Check function_response exists - assert function_response_part is not None, "Missing function_response part" - function_response = function_response_part["function_response"] + assert isinstance(result, list), "Should return a parts list when media is present" + assert len(result) == 1, "Should return one function_response part" + result_part = result[0] + assert "function_response" in result_part + assert "inline_data" not in result_part + function_response = result_part["function_response"] assert function_response["name"] == "click_at" assert "response" in function_response # Verify JSON response is parsed correctly assert "url" in function_response["response"] assert function_response["response"]["url"] == "https://example.com" - # Check inline_data exists - assert inline_data_part is not None, "Missing inline_data part" - inline_data: BlobType = inline_data_part["inline_data"] + # Check inline_data is nested under functionResponse.parts. + assert "parts" in function_response + assert len(function_response["parts"]) == 1 + inline_data: BlobType = function_response["parts"][0]["inline_data"] assert "data" in inline_data assert "mime_type" in inline_data assert inline_data["mime_type"] == "image/png" assert inline_data["data"] == test_image_base64 +def test_gemini_history_nests_multimodal_tool_response_parts(): + """Full history conversion should not emit sibling inline_data tool result parts.""" + test_image_base64 = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==" + messages = [ + {"role": "user", "content": "Get me an image"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_get_image", + "type": "function", + "function": {"name": "get_image", "arguments": "{}"}, + } + ], + }, + { + "role": "tool", + "tool_call_id": "call_get_image", + "content": [ + {"type": "text", "text": '{"image_ref": "inline"}'}, + { + "type": "image", + "source": { + "type": "base64", + "media_type": "image/png", + "data": test_image_base64, + }, + }, + ], + }, + ] + + contents = _gemini_convert_messages_with_history(messages=messages) + + tool_response_parts = contents[-1]["parts"] + assert len(tool_response_parts) == 1 + assert "inline_data" not in tool_response_parts[0] + function_response = tool_response_parts[0]["function_response"] + assert function_response["parts"] == [ + { + "inline_data": { + "data": test_image_base64, + "mime_type": "image/png", + } + } + ] + + def test_convert_tool_response_with_url_image(): """Test tool response with HTTP URL image (will download and convert).""" import pytest @@ -1225,24 +1263,20 @@ def test_convert_tool_response_with_url_image(): tool_message, last_message_with_tool_calls ) - # Should be a list with 2 parts when image is present assert isinstance( result, list - ), f"Expected list when image present, got {type(result)}" - assert len(result) == 2, f"Expected 2 parts, got {len(result)}" - - # Find parts - function_response_part = next(p for p in result if "function_response" in p) - inline_data_part = next(p for p in result if "inline_data" in p) - - # Check function_response exists - assert function_response_part is not None, "Missing function_response part" - function_response = function_response_part["function_response"] + ), "Should return a parts list when media is present" + assert len(result) == 1, "Should return one function_response part" + result_part = result[0] + assert "function_response" in result_part + assert "inline_data" not in result_part + function_response = result_part["function_response"] assert function_response["name"] == "type_text_at" - # Check inline_data exists (URL should be downloaded and converted) - assert inline_data_part is not None, "Missing inline_data part" - inline_data: BlobType = inline_data_part["inline_data"] + # Check inline_data is nested under functionResponse.parts. + assert "parts" in function_response + assert len(function_response["parts"]) == 1 + inline_data: BlobType = function_response["parts"][0]["inline_data"] assert "data" in inline_data assert "mime_type" in inline_data except Exception as e: @@ -1558,38 +1592,27 @@ def test_convert_tool_response_with_pdf_file(): ] } - # Convert tool response (returns list when file is present) + # Convert tool response with nested multimodal functionResponse.parts. result = convert_to_gemini_tool_call_result( tool_message, last_message_with_tool_calls ) - # Verify results - should be a list with 2 parts (function_response + inline_data) - assert isinstance( - result, list - ), f"Expected list when file present, got {type(result)}" - assert len(result) == 2, f"Expected 2 parts, got {len(result)}" - - # Find function_response part and inline_data part - function_response_part = None - inline_data_part = None - for part in result: - if "function_response" in part: - function_response_part = part - elif "inline_data" in part: - inline_data_part = part - - # Check function_response exists - assert function_response_part is not None, "Missing function_response part" - function_response = function_response_part["function_response"] + assert isinstance(result, list), "Should return a parts list when media is present" + assert len(result) == 1, "Should return one function_response part" + result_part = result[0] + assert "function_response" in result_part + assert "inline_data" not in result_part + function_response = result_part["function_response"] assert function_response["name"] == "analyze_document" assert "response" in function_response # Verify JSON response is parsed correctly assert "status" in function_response["response"] assert function_response["response"]["status"] == "success" - # Check inline_data exists - assert inline_data_part is not None, "Missing inline_data part" - inline_data: BlobType = inline_data_part["inline_data"] + # Check inline_data is nested under functionResponse.parts. + assert "parts" in function_response + assert len(function_response["parts"]) == 1 + inline_data: BlobType = function_response["parts"][0]["inline_data"] assert "data" in inline_data assert "mime_type" in inline_data assert inline_data["mime_type"] == "application/pdf" @@ -1624,21 +1647,13 @@ def test_convert_tool_response_with_input_file_type(): tool_message, last_message_with_tool_calls ) - # Verify results - assert isinstance( - result, list - ), f"Expected list when file present, got {type(result)}" - assert len(result) == 2, f"Expected 2 parts, got {len(result)}" - - # Find inline_data part - inline_data_part = None - for part in result: - if "inline_data" in part: - inline_data_part = part - - # Check inline_data exists - assert inline_data_part is not None, "Missing inline_data part" - assert inline_data_part["inline_data"]["mime_type"] == "application/pdf" + # Check inline_data is nested under functionResponse.parts. + assert isinstance(result, list), "Should return a parts list when media is present" + assert len(result) == 1, "Should return one function_response part" + function_response = result[0]["function_response"] + assert ( + function_response["parts"][0]["inline_data"]["mime_type"] == "application/pdf" + ) def test_convert_tool_response_with_nested_file_object(): @@ -1669,21 +1684,11 @@ def test_convert_tool_response_with_nested_file_object(): tool_message, last_message_with_tool_calls ) - # Verify results - should be a list with 2 parts - assert isinstance( - result, list - ), f"Expected list when file present, got {type(result)}" - assert len(result) == 2, f"Expected 2 parts, got {len(result)}" - - # Find inline_data part - inline_data_part = None - for part in result: - if "inline_data" in part: - inline_data_part = part - - # Check inline_data exists - assert inline_data_part is not None, "Missing inline_data part" - inline_data: BlobType = inline_data_part["inline_data"] + # Check inline_data is nested under functionResponse.parts. + assert isinstance(result, list), "Should return a parts list when media is present" + assert len(result) == 1, "Should return one function_response part" + function_response = result[0]["function_response"] + inline_data: BlobType = function_response["parts"][0]["inline_data"] assert "data" in inline_data assert "mime_type" in inline_data assert inline_data["mime_type"] == "application/pdf" diff --git a/tests/test_litellm/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py index 6f6c4508333..d5043c775b3 100644 --- a/tests/test_litellm/proxy/auth/test_auth_checks.py +++ b/tests/test_litellm/proxy/auth/test_auth_checks.py @@ -3391,30 +3391,44 @@ async def test_resolve_end_user_swallows_db_errors_and_returns_none( @pytest.mark.asyncio -async def test_resolve_end_user_reraises_budget_exceeded( +async def test_resolve_end_user( _validate_flag_on, monkeypatch ): - """BudgetExceededError from get_end_user_object must bubble up so the - auth path enforces spend limits instead of silently dropping the id.""" - import litellm + """Verify that resolve_and_validate_end_user_id does NOT raise BudgetExceededError. + + Note: As of the refactor that moved _check_end_user_budget out of + get_end_user_object, budget enforcement now happens in common_checks(). + + The end-user validation path should return the user ID regardless of budget status. + Budget enforcement for end users happens later in common_checks() via + _check_end_user_budget(), which respects skip_budget_checks for zero-cost models. + + This test verifies that even when get_end_user_object returns a user with a budget, + resolve_and_validate_end_user_id does not block the request - budget enforcement + is deferred to common_checks() where skip_budget_checks logic can be applied. + """ from litellm.proxy.auth import auth_checks from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + # Mock get_end_user_object to return a user with budget info + # (simulating a user who may have exceeded their budget) + mock_end_user = MagicMock() + mock_end_user.user_id = "customer-over-budget" monkeypatch.setattr( auth_checks, "get_end_user_object", - AsyncMock( - side_effect=litellm.BudgetExceededError(current_cost=10.0, max_budget=5.0) - ), + AsyncMock(return_value=mock_end_user), ) cache = _validation_cache() - with pytest.raises(litellm.BudgetExceededError): - await resolve_and_validate_end_user_id( - raw_end_user_id="customer-over-budget", - prisma_client=MagicMock(), - user_api_key_cache=cache, - ) + # resolve_and_validate_end_user_id should return the user ID without raising + # BudgetExceededError - budget enforcement happens in common_checks() + result = await resolve_and_validate_end_user_id( + raw_end_user_id="customer-over-budget", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "customer-over-budget" @pytest.mark.asyncio diff --git a/tests/test_litellm/proxy/auth/test_custom_auth_end_user_budget.py b/tests/test_litellm/proxy/auth/test_custom_auth_end_user_budget.py index 4084fa4f3aa..68907de6f2d 100644 --- a/tests/test_litellm/proxy/auth/test_custom_auth_end_user_budget.py +++ b/tests/test_litellm/proxy/auth/test_custom_auth_end_user_budget.py @@ -5,7 +5,11 @@ from litellm.proxy.auth.user_api_key_auth import ( _run_post_custom_auth_checks, update_valid_token_with_end_user_params, ) -from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy._types import ( + LiteLLM_BudgetTable, + LiteLLM_EndUserTable, + UserAPIKeyAuth, +) @pytest.mark.asyncio @@ -88,6 +92,85 @@ async def test_custom_auth_run_post_custom_auth_checks_with_end_user_budget_exce mock_budget_check.assert_awaited_once() +@pytest.mark.asyncio +async def test_custom_auth_enforces_end_user_budget_when_common_checks_skipped(): + # custom-auth deployments with custom_auth_run_common_checks unset skip + # common_checks() (and its end-user budget enforcement) in the centralized + # gate, so the helper must enforce the end-user budget itself. Regression: + # an over-budget end user must be rejected on this path. + valid_token = UserAPIKeyAuth(token="test_token", end_user_id="customer-1") + over_budget_end_user = LiteLLM_EndUserTable( + user_id="customer-1", + blocked=False, + spend=0.0, + litellm_budget_table=LiteLLM_BudgetTable(max_budget=1.0), + ) + + async def mock_get_current_spend(counter_key, fallback_spend): + if counter_key == "spend:end_user:customer-1": + return 5.0 + return fallback_spend + + with ( + patch( + "litellm.proxy.auth.user_api_key_auth.get_end_user_object", + new_callable=AsyncMock, + return_value=over_budget_end_user, + ), + patch("litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend), + patch("litellm.proxy.proxy_server.general_settings", {}), + ): + with pytest.raises(litellm.BudgetExceededError): + await _run_post_custom_auth_checks( + valid_token=valid_token, + request=None, + request_data={"model": "gpt-4"}, + route="/v1/chat/completions", + parent_otel_span=None, + ) + + +@pytest.mark.asyncio +async def test_custom_auth_defers_end_user_budget_to_common_checks_when_enabled(): + # With custom_auth_run_common_checks set, the wrapper's common_checks() + # enforces the end-user budget, so the helper must not double-enforce it. + valid_token = UserAPIKeyAuth(token="test_token", end_user_id="customer-1") + end_user_obj = LiteLLM_EndUserTable( + user_id="customer-1", + blocked=False, + spend=0.0, + litellm_budget_table=LiteLLM_BudgetTable(max_budget=1.0), + ) + + with ( + patch( + "litellm.proxy.auth.user_api_key_auth.get_end_user_object", + new_callable=AsyncMock, + return_value=end_user_obj, + ), + patch( + "litellm.proxy.auth.user_api_key_auth._check_end_user_budget", + new_callable=AsyncMock, + ) as mock_check, + patch( + "litellm.proxy.auth.user_api_key_auth._enforce_key_and_fallback_model_access", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.proxy_server.general_settings", + {"custom_auth_run_common_checks": True}, + ), + ): + await _run_post_custom_auth_checks( + valid_token=valid_token, + request=None, + request_data={"model": "gpt-4"}, + route="/v1/chat/completions", + parent_otel_span=None, + ) + mock_check.assert_not_awaited() + + def test_update_valid_token_does_not_override_custom_auth_values_with_none(): """ Greptile feedback: if custom auth sets end_user_model_max_budget on the token, diff --git a/tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py b/tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py index 69af35dfeae..983f60b0339 100644 --- a/tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py +++ b/tests/test_litellm/test_bedrock_anthropic_1hr_cache_pricing.py @@ -72,9 +72,40 @@ US_EXPECTED = [ ("us.anthropic.claude-haiku-4-5-20251001-v1:0", 2.2e-06, None), ] +# EU/AU/JP cross-region inference profiles carry the same +10% regional +# premium as US (per AWS Bedrock pricing). Coverage list filters to entries +# that actually exist in the pricing JSON - e.g. Opus 4.6 has no JP profile. +REGIONAL_EXPECTED = [ + # Opus 4.6 - $11.00 / MTok (eu/au only; no jp profile) + ("eu.anthropic.claude-opus-4-6-v1", 1.1e-05, None), + ("au.anthropic.claude-opus-4-6-v1", 1.1e-05, None), + # Opus 4.7 - $11.00 / MTok (eu/au; jp is added in #28567) + ("eu.anthropic.claude-opus-4-7", 1.1e-05, None), + ("au.anthropic.claude-opus-4-7", 1.1e-05, None), + # Sonnet 4.6 - $6.60 / MTok + ("eu.anthropic.claude-sonnet-4-6", 6.6e-06, None), + ("au.anthropic.claude-sonnet-4-6", 6.6e-06, None), + ("jp.anthropic.claude-sonnet-4-6", 6.6e-06, None), + # Sonnet 4.5 - $6.60 / MTok with $13.20 / MTok long-context tier + ("eu.anthropic.claude-sonnet-4-5-20250929-v1:0", 6.6e-06, 1.32e-05), + ("au.anthropic.claude-sonnet-4-5-20250929-v1:0", 6.6e-06, 1.32e-05), + ("jp.anthropic.claude-sonnet-4-5-20250929-v1:0", 6.6e-06, 1.32e-05), + # Haiku 4.5 - $2.20 / MTok + ("eu.anthropic.claude-haiku-4-5-20251001-v1:0", 2.2e-06, None), + ("au.anthropic.claude-haiku-4-5-20251001-v1:0", 2.2e-06, None), + ("jp.anthropic.claude-haiku-4-5-20251001-v1:0", 2.2e-06, None), + # Note: eu.anthropic.claude-opus-4-5-20251101-v1:0 is intentionally NOT + # in this list. The existing entry carries base/global 5m rates + # (5e-06 / 6.25e-06) instead of the +10% regional premium (5.5e-06 / + # 6.875e-06), which would make the 1.6x 5m-to-1h invariant fail. + # Fixing the EU 5m rates first is left to a follow-up so this PR + # stays scoped to the 1-hour cache tier addition. +] + @pytest.mark.parametrize( - "model_key, expected_1hr, expected_1hr_lc", GLOBAL_EXPECTED + US_EXPECTED + "model_key, expected_1hr, expected_1hr_lc", + GLOBAL_EXPECTED + US_EXPECTED + REGIONAL_EXPECTED, ) def test_bedrock_anthropic_1hr_cache_write_pricing( model_data, model_key, expected_1hr, expected_1hr_lc diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index 1a9bf5a9428..d973f8b4542 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -2120,11 +2120,11 @@ def test_gemini_3_1_flash_lite_pricing(): ): model_info = litellm.model_cost.get(model_name) assert model_info is not None, f"Missing model pricing entry: {model_name}" - assert model_info["input_cost_per_token"] == 4.5e-07 - assert model_info["input_cost_per_audio_token"] == 9e-07 - assert model_info["output_cost_per_token"] == 2.7e-06 - assert model_info["output_cost_per_reasoning_token"] == 2.7e-06 - assert model_info["cache_read_input_token_cost"] == 4.5e-08 + assert model_info["input_cost_per_token"] == 2.5e-07 + assert model_info["input_cost_per_audio_token"] == 5e-07 + assert model_info["output_cost_per_token"] == 1.5e-06 + assert model_info["output_cost_per_reasoning_token"] == 1.5e-06 + assert model_info["cache_read_input_token_cost"] == 2.5e-08 assert model_info["max_input_tokens"] == 1048576 diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py index 5e636b86ed6..e9287a95438 100644 --- a/tests/test_litellm/test_router.py +++ b/tests/test_litellm/test_router.py @@ -2376,6 +2376,74 @@ def test_get_deployment_model_info_base_model_flow(): # Should return None when no model info is found assert result is None + # Test Case 6: custom_model_info present but litellm_model_name_model_info is None + # (model has custom pricing in config but is not in built-in model_prices_and_context_window.json) + mock_custom_pricing_only = { + "input_cost_per_token": 1.74e-06, + "output_cost_per_token": 3.48e-06, + "cache_read_input_token_cost": 1.45e-08, + "mode": "chat", + } + + with patch.object( + litellm, + "model_cost", + {"custom-model-id": mock_custom_pricing_only}, + ): + with patch.object(litellm, "get_model_info") as mock_get_model_info: + # Model NOT in built-in cost map — raise exception + mock_get_model_info.side_effect = Exception("Model not in cost map") + + result = router.get_deployment_model_info( + model_id="custom-model-id", model_name="unknown-model" + ) + + # Should return custom_model_info even when litellm_model_name_model_info is None + assert result is not None + assert result["input_cost_per_token"] == 1.74e-06 + assert result["output_cost_per_token"] == 3.48e-06 + assert result["cache_read_input_token_cost"] == 1.45e-08 + assert result["mode"] == "chat" + + # Test Case 7: custom_model_info with base_model but litellm_model_name_model_info None + mock_custom_with_base = { + "base_model": "some-base-model", + "input_cost_per_token": 0.01, + "output_cost_per_token": 0.02, + } + mock_base_info = { + "key": "some-base-model", + "max_tokens": 8192, + "mode": "chat", + "litellm_provider": "openai", + } + + with patch.object( + litellm, + "model_cost", + {"custom-with-base": mock_custom_with_base}, + ): + with patch.object(litellm, "get_model_info") as mock_get_model_info: + + def get_info_side_effect(model): + if model == "some-base-model": + return mock_base_info + raise Exception("Model not in cost map") + + mock_get_model_info.side_effect = get_info_side_effect + + result = router.get_deployment_model_info( + model_id="custom-with-base", model_name="unknown-model" + ) + + # Should return custom_model_info merged with base model info + assert result is not None + assert ( + result["input_cost_per_token"] == 0.01 + ) # From custom (overrides base) + assert result["max_tokens"] == 8192 # From base model + assert result["litellm_provider"] == "openai" # From base model + print("✓ All base model flow test cases passed!") diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 6a78653ec99..2d75671f1cb 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -928,6 +928,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): }, }, "supports_native_streaming": {"type": "boolean"}, + "supports_image_size": {"type": "boolean"}, "supports_native_structured_output": {"type": "boolean"}, "tiered_pricing": { "type": "array", diff --git a/ui/litellm-dashboard/src/app/layout.tsx b/ui/litellm-dashboard/src/app/layout.tsx index f79b7eb7028..a73921ce35b 100644 --- a/ui/litellm-dashboard/src/app/layout.tsx +++ b/ui/litellm-dashboard/src/app/layout.tsx @@ -11,7 +11,7 @@ const inter = Inter({ subsets: ["latin"] }); export const metadata: Metadata = { title: "LiteLLM Dashboard", description: "LiteLLM Proxy Admin UI", - icons: { icon: "./favicon.ico" }, + icons: { icon: "/get_favicon" }, }; export default function RootLayout({ From 48c9fabb26d948ab3f4f5e4906bec9af8daa6d11 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Wed, 3 Jun 2026 23:44:15 +0530 Subject: [PATCH 11/92] Fix : a2a bugs 030626 (#29566) * Fix error code and context id injection bug * Add support for all A2A methods * Add logging * address greptile review: relay upstream JSON-RPC errors, move _PASCAL_TO_WIRE to module level, add error path tests * fix(a2a): run pre_call_hook for tasks/resubscribe SSE path to enforce guardrails tasks/resubscribe was returning the raw SSE stream without calling proxy_logging_obj.pre_call_hook, silently bypassing any guardrails configured on the agent. This patch calls pre_call_hook before streaming begins and wires post_call_failure_hook into the SSE generator so errors are logged. Adds a regression test verifying the hook is called. * fix(a2a): use get_async_httpx_client instead of creating httpx clients per request Creating httpx.AsyncClient instances per-request adds ~500ms latency. Switch _forward_jsonrpc and _forward_jsonrpc_sse to use the shared client from get_async_httpx_client(httpxSpecialProvider.A2A). * fix(a2a): forward caller identity headers on task ops; validate push notification URL Two security fixes for task management methods: 1. All task operations (tasks/get, tasks/list, tasks/cancel, tasks/resubscribe, push notification config methods) now forward X-LiteLLM-User-Id and X-LiteLLM-Team-Id headers to the upstream agent, so the agent can scope task access to the authenticated caller. 2. tasks/pushNotificationConfig/set validates the callback URL before forwarding: requires HTTPS and rejects private/loopback/reserved IP ranges and localhost hostnames to prevent SSRF. * Fix A2A task hook and push URL handling * fix(a2a): fix mypy type errors for request_id and header_name dict key types * Fix A2A request id and params forwarding * Forward trace IDs for A2A task calls * fix(a2a): strip client-forwarded X-LiteLLM-* headers before applying authenticated identity A client could send x-a2a--x-litellm-user-id in their request and have it forwarded to the upstream agent as an authenticated identity header. Fix: sanitize any X-LiteLLM-* headers from agent_extra_headers before merging, then apply the authenticated identity headers last so they always override client-supplied values. * Fix A2A SSE fallback JSON-RPC error code * Fix A2A SSE error id backfill * fix(a2a): validate both push notification url fields to close SSRF bypass * fix(a2a): widen request_id annotation to match JSON-RPC id call sites * fix(a2a): run post-call streaming hook for tasks/resubscribe so agent guardrails apply tasks/resubscribe returned the raw upstream SSE stream without routing events through the post-call streaming hook, so output guardrails configured on the agent were silently skipped for streaming task subscriptions while every other task method and message/stream applied them. Parse upstream JSON-RPC SSE events and feed them through async_streaming_data_generator, matching message/stream, so guardrails inspect the streamed task content. Adds a regression test that fails when the streamed events bypass the guardrail hook. --------- Co-authored-by: Cursor Agent Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/a2a_protocol/main.py | 17 +- .../proxy/agent_endpoints/a2a_endpoints.py | 367 ++++- litellm/types/agents.py | 38 +- .../test_send_message_response.py | 43 + .../agent_endpoints/test_a2a_endpoints.py | 1212 +++++++++++++++++ 5 files changed, 1639 insertions(+), 38 deletions(-) create mode 100644 tests/test_litellm/a2a_protocol/test_send_message_response.py diff --git a/litellm/a2a_protocol/main.py b/litellm/a2a_protocol/main.py index 3ad5485dea1..6979e1ac659 100644 --- a/litellm/a2a_protocol/main.py +++ b/litellm/a2a_protocol/main.py @@ -159,7 +159,9 @@ async def _send_message_via_completion_bridge( api_base=api_base, ) - return LiteLLMSendMessageResponse.from_dict(response_dict) + return LiteLLMSendMessageResponse.from_dict( + response_dict, request_id=str(request.id) + ) async def _execute_a2a_send_with_retry( @@ -317,15 +319,6 @@ async def asend_message( ) card_url = getattr(agent_card, "url", None) if agent_card else None - context_id = trace_id or str(uuid.uuid4()) - message = request.params.message - if isinstance(message, dict): - if message.get("context_id") is None: - message["context_id"] = context_id - else: - if getattr(message, "context_id", None) is None: - message.context_id = context_id - a2a_response = await _execute_a2a_send_with_retry( a2a_client=a2a_client, request=request, @@ -338,7 +331,9 @@ async def asend_message( verbose_logger.info(f"A2A send_message completed, request_id={request.id}") # Wrap in LiteLLM response type for _hidden_params support - response = LiteLLMSendMessageResponse.from_a2a_response(a2a_response) + response = LiteLLMSendMessageResponse.from_a2a_response( + a2a_response, request_id=str(request.id) + ) # Calculate token usage from request and response response_dict = a2a_response.model_dump(mode="json", exclude_none=True) diff --git a/litellm/proxy/agent_endpoints/a2a_endpoints.py b/litellm/proxy/agent_endpoints/a2a_endpoints.py index 7b56155982c..9f1403d4328 100644 --- a/litellm/proxy/agent_endpoints/a2a_endpoints.py +++ b/litellm/proxy/agent_endpoints/a2a_endpoints.py @@ -6,12 +6,14 @@ The A2A SDK can point to LiteLLM's URL and invoke agents registered with LiteLLM """ import json -from typing import Any, Dict, List, Optional +from typing import Any, AsyncGenerator, Dict, List, Optional +from urllib.parse import urlparse from fastapi import APIRouter, Depends, HTTPException, Request, Response from fastapi.responses import JSONResponse, StreamingResponse from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.url_utils import SSRFError, validate_url from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.agent_endpoints.utils import merge_agent_headers from litellm.proxy.auth.user_api_key_auth import user_api_key_auth @@ -19,9 +21,66 @@ from litellm.types.utils import all_litellm_params router = APIRouter() +_PASCAL_TO_WIRE: Dict[str, str] = { + "GetTask": "tasks/get", + "ListTasks": "tasks/list", + "CancelTask": "tasks/cancel", + "SubscribeToTask": "tasks/resubscribe", + "CreateTaskPushNotificationConfig": "tasks/pushNotificationConfig/set", + "GetTaskPushNotificationConfig": "tasks/pushNotificationConfig/get", + "ListTaskPushNotificationConfigs": "tasks/pushNotificationConfig/list", + "DeleteTaskPushNotificationConfig": "tasks/pushNotificationConfig/delete", + "GetExtendedAgentCard": "agent/getAuthenticatedExtendedCard", +} + + +def _validate_push_notification_url(url: str) -> None: + parsed = urlparse(url) + if parsed.scheme != "https": + raise HTTPException( + status_code=400, + detail="Push notification URL must use HTTPS", + ) + try: + validate_url(url) + except (SSRFError, ValueError) as e: + raise HTTPException(status_code=400, detail=str(e)) from e + + +def _caller_identity_headers(user_api_key_dict: UserAPIKeyAuth) -> Dict[str, str]: + headers: Dict[str, str] = {} + if user_api_key_dict.user_id: + headers["X-LiteLLM-User-Id"] = user_api_key_dict.user_id + if user_api_key_dict.team_id: + headers["X-LiteLLM-Team-Id"] = user_api_key_dict.team_id + return headers + + +def _forwarding_headers( + user_api_key_dict: UserAPIKeyAuth, + request_data: dict, + agent_extra_headers: Optional[Dict[str, str]], +) -> Optional[Dict[str, str]]: + sanitized = ( + { + k: v + for k, v in agent_extra_headers.items() + if not k.lower().startswith("x-litellm-") + } + if agent_extra_headers + else None + ) + merged = merge_agent_headers(dynamic_headers=sanitized, static_headers=None) or {} + identity = _caller_identity_headers(user_api_key_dict) + trace_id = request_data.get("litellm_trace_id") + if trace_id: + identity["X-LiteLLM-Trace-Id"] = str(trace_id) + merged.update(identity) + return merged or None + def _jsonrpc_error( - request_id: Optional[str], + request_id: Optional[Any], code: int, message: str, status_code: int = 400, @@ -67,9 +126,158 @@ def _enforce_inbound_trace_id(agent: Any, request: Request) -> None: ) +async def _forward_jsonrpc( + agent_url: str, + body: dict, + extra_headers: Optional[Dict[str, str]] = None, +) -> dict: + from litellm.llms.custom_httpx.http_handler import get_async_httpx_client + from litellm.types.llms.custom_http import httpxSpecialProvider + + headers = {"Content-Type": "application/json", **(extra_headers or {})} + handler = get_async_httpx_client( + llm_provider=httpxSpecialProvider.A2A, + params={"timeout": 60.0}, + ) + resp = await handler.post(agent_url, json=body, headers=headers) + try: + result = resp.json() + except Exception: + resp.raise_for_status() + raise + if not resp.is_success and "error" not in result: + resp.raise_for_status() + return result + + +async def _a2a_sse_event_source( + agent_url: str, + body: dict, + request_id: Optional[Any] = None, + extra_headers: Optional[Dict[str, str]] = None, +) -> AsyncGenerator[dict, None]: + """Stream an upstream A2A SSE response as parsed JSON-RPC event dicts. + + Upstream HTTP/JSON-RPC errors are surfaced as a single JSON-RPC error event + so the caller can relay them instead of breaking the stream. + """ + from litellm.llms.custom_httpx.http_handler import get_async_httpx_client + from litellm.types.agents import _normalize_a2a_jsonrpc_response + from litellm.types.llms.custom_http import httpxSpecialProvider + + headers = { + "Content-Type": "application/json", + "Accept": "text/event-stream", + **(extra_headers or {}), + } + handler = get_async_httpx_client( + llm_provider=httpxSpecialProvider.A2A, + params={"timeout": None}, + ) + async_client = handler.client + req = async_client.build_request("POST", agent_url, json=body, headers=headers) + resp = await async_client.send(req, stream=True) + try: + if not resp.is_success: + error_body = await resp.aread() + error_event: Optional[dict] = None + try: + parsed = json.loads(error_body) + if isinstance(parsed, dict) and "error" in parsed: + error_event = _normalize_a2a_jsonrpc_response( + parsed, request_id=request_id + ) + except Exception: + error_event = None + yield error_event or { + "jsonrpc": "2.0", + "id": request_id, + "error": {"code": -32603, "message": resp.reason_phrase}, + } + return + async for line in resp.aiter_lines(): + stripped = line.strip() + if not stripped.startswith("data:"): + continue + payload = stripped[len("data:") :].strip() + if not payload: + continue + try: + yield json.loads(payload) + except Exception: + continue + finally: + await resp.aclose() + + +async def _forward_jsonrpc_sse( + agent_url: str, + body: dict, + request_id: Optional[Any] = None, + extra_headers: Optional[Dict[str, str]] = None, + proxy_logging_obj: Optional[Any] = None, + user_api_key_dict: Optional[Any] = None, + request_data: Optional[dict] = None, +) -> StreamingResponse: + event_source = _a2a_sse_event_source( + agent_url, body, request_id=request_id, extra_headers=extra_headers + ) + + def _serialize_chunk(chunk: Any) -> str: + return f"data: {json.dumps(chunk)}\n\n" + + def _serialize_error(proxy_exc: Any) -> str: + return ( + "data: " + + json.dumps( + { + "jsonrpc": "2.0", + "id": request_id, + "error": { + "code": -32603, + "message": getattr(proxy_exc, "message", str(proxy_exc)), + }, + } + ) + + "\n\n" + ) + + if ( + proxy_logging_obj is not None + and user_api_key_dict is not None + and request_data is not None + ): + # Route streamed events through the shared streaming generator so the + # post-call streaming hook (and therefore agent guardrails) inspects + # tasks/resubscribe output the same way message/stream does. + from litellm.proxy.common_request_processing import ( + ProxyBaseLLMRequestProcessing, + ) + + generator: AsyncGenerator[str, None] = ( + ProxyBaseLLMRequestProcessing.async_streaming_data_generator( + response=event_source, + user_api_key_dict=user_api_key_dict, + request_data=request_data, + proxy_logging_obj=proxy_logging_obj, + serialize_chunk=_serialize_chunk, + serialize_error=_serialize_error, + ) + ) + else: + + async def _passthrough() -> AsyncGenerator[str, None]: + async for chunk in event_source: + yield _serialize_chunk(chunk) + + generator = _passthrough() + + return StreamingResponse(generator, media_type="text/event-stream") + + async def _handle_stream_message( api_base: Optional[str], - request_id: str, + request_id: Any, params: dict, litellm_params: Optional[dict] = None, agent_id: Optional[str] = None, @@ -310,8 +518,6 @@ async def invoke_agent_a2a( # noqa: PLR0915 - message/send: Send a message and get a response - message/stream: Send a message and stream the response """ - from litellm.a2a_protocol import asend_message - from litellm.a2a_protocol.main import A2A_SDK_AVAILABLE from litellm.proxy.agent_endpoints.auth.agent_permission_handler import ( AgentRequestHandler, ) @@ -322,9 +528,11 @@ async def invoke_agent_a2a( # noqa: PLR0915 version, ) - body = {} + body: Dict[str, Any] = {} + request_data: Dict[str, Any] = body try: body = await request.json() + request_data = body verbose_proxy_logger.debug(f"A2A request for agent '{agent_id}': {body}") @@ -334,11 +542,14 @@ async def invoke_agent_a2a( # noqa: PLR0915 body.get("id"), -32600, "Invalid Request: jsonrpc must be '2.0'" ) - request_id = body.get("id") - method = body.get("method") + request_id: Optional[Any] = body.get("id") + method: Optional[str] = body.get("method") params = body.get("params", {}) - if params: + if method: + method = _PASCAL_TO_WIRE.get(method, method) + + if isinstance(params, dict): # extract any litellm params from the params - eg. 'guardrails' # ``metadata`` is intentionally excluded: it's a first-class A2A # ``MessageSendParams`` field that the completion bridge forwards @@ -347,20 +558,12 @@ async def invoke_agent_a2a( # noqa: PLR0915 # silently drop the caller's A2A request-level metadata. params_to_remove = [] for key, value in params.items(): - if key in all_litellm_params and key != "metadata": + if key in all_litellm_params and key not in {"id", "metadata"}: params_to_remove.append(key) body[key] = value for key in params_to_remove: params.pop(key) - if not A2A_SDK_AVAILABLE: - return _jsonrpc_error( - request_id, - -32603, - "Server error: 'a2a' package not installed. Please install 'a2a-sdk'.", - 500, - ) - # Find the agent agent = _get_agent(agent_id) if agent is None: @@ -441,6 +644,7 @@ async def invoke_agent_a2a( # noqa: PLR0915 route_type="asend_message", version=version, ) + request_data = data # Build merged headers for the backend agent static_headers: Dict[str, str] = dict(agent.static_headers or {}) @@ -453,9 +657,10 @@ async def invoke_agent_a2a( # noqa: PLR0915 # 1. Admin-configured extra_headers: forward named headers from client request if agent.extra_headers: for header_name in agent.extra_headers: - val = normalized.get(header_name.lower()) + header_name_str = str(header_name) + val = normalized.get(header_name_str.lower()) if val is not None: - dynamic_headers[header_name] = val + dynamic_headers[header_name_str] = val # 2. Convention-based forwarding: x-a2a-{agent_id_or_name}-{header_name} # Matches both agent_id (UUID) and agent_name (alias), case-insensitive. @@ -489,10 +694,20 @@ async def invoke_agent_a2a( # noqa: PLR0915 # Route through SDK functions if method == "message/send": + from litellm.a2a_protocol import asend_message + from litellm.a2a_protocol.main import A2A_SDK_AVAILABLE + + if not A2A_SDK_AVAILABLE: + return _jsonrpc_error( + request_id, + -32603, + "Server error: 'a2a' package not installed. Please install 'a2a-sdk'.", + 500, + ) from a2a.types import MessageSendParams, SendMessageRequest a2a_request = SendMessageRequest( - id=request_id, + id=request_id if request_id is not None else "", params=MessageSendParams(**params), ) # Defer spend-log until after post_call_success_hook so guardrail @@ -532,7 +747,7 @@ async def invoke_agent_a2a( # noqa: PLR0915 elif method == "message/stream": return await _handle_stream_message( api_base=agent_url, - request_id=request_id, + request_id=request_id if request_id is not None else "", params=params, litellm_params=litellm_params, agent_id=agent.agent_id, @@ -543,6 +758,106 @@ async def invoke_agent_a2a( # noqa: PLR0915 request_data=data, proxy_logging_obj=proxy_logging_obj, ) + elif method in { + "tasks/get", + "tasks/list", + "tasks/cancel", + "tasks/pushNotificationConfig/set", + "tasks/pushNotificationConfig/get", + "tasks/pushNotificationConfig/list", + "tasks/pushNotificationConfig/delete", + "agent/getAuthenticatedExtendedCard", + }: + if not agent_url: + return _jsonrpc_error( + request_id, -32000, f"Agent '{agent_id}' has no URL configured", 500 + ) + if method == "tasks/pushNotificationConfig/set": + if not isinstance(params, dict): + raise HTTPException( + status_code=400, + detail="params must be an object", + ) + push_config = params.get("pushNotificationConfig", {}) + if "pushNotificationConfig" in params and not isinstance( + push_config, dict + ): + raise HTTPException( + status_code=400, + detail="pushNotificationConfig must be an object", + ) + for callback_url in (params.get("url"), push_config.get("url")): + if not callback_url: + continue + if not isinstance(callback_url, str): + raise HTTPException( + status_code=400, + detail="Push notification URL must be a string", + ) + _validate_push_notification_url(callback_url) + forward_body = { + "jsonrpc": "2.0", + "id": request_id, + "method": method, + "params": params, + } + caller_headers = _forwarding_headers( + user_api_key_dict=user_api_key_dict, + request_data=data, + agent_extra_headers=agent_extra_headers, + ) + result = await _forward_jsonrpc( + agent_url, forward_body, extra_headers=caller_headers + ) + if method == "agent/getAuthenticatedExtendedCard": + if isinstance(result.get("result"), dict) and "url" in result["result"]: + result["result"][ + "url" + ] = f"{str(request.base_url).rstrip('/')}/a2a/{agent_id}" + from litellm.types.agents import LiteLLMSendMessageResponse + + response = LiteLLMSendMessageResponse.from_dict( + result, request_id=request_id + ) + response = await proxy_logging_obj.post_call_success_hook( + user_api_key_dict=user_api_key_dict, + data=data, + response=response, + ) + return JSONResponse( + content=( + response.model_dump(mode="json", exclude_none=True) + if hasattr(response, "model_dump") + else response + ) + ) + + elif method == "tasks/resubscribe": + if not agent_url: + return _jsonrpc_error( + request_id, -32000, f"Agent '{agent_id}' has no URL configured", 500 + ) + forward_body = { + "jsonrpc": "2.0", + "id": request_id, + "method": method, + "params": params, + } + sse_caller_headers = _forwarding_headers( + user_api_key_dict=user_api_key_dict, + request_data=data, + agent_extra_headers=agent_extra_headers, + ) + return await _forward_jsonrpc_sse( + agent_url, + forward_body, + request_id=request_id, + extra_headers=sse_caller_headers, + proxy_logging_obj=proxy_logging_obj, + user_api_key_dict=user_api_key_dict, + request_data=data, + ) + else: return _jsonrpc_error(request_id, -32601, f"Method '{method}' not found") @@ -550,4 +865,12 @@ async def invoke_agent_a2a( # noqa: PLR0915 raise except Exception as e: verbose_proxy_logger.exception(f"Error invoking agent: {e}") + try: + await proxy_logging_obj.post_call_failure_hook( + user_api_key_dict=user_api_key_dict, + original_exception=e, + request_data=request_data, + ) + except Exception: + pass return _jsonrpc_error(body.get("id"), -32603, f"Internal error: {str(e)}", 500) diff --git a/litellm/types/agents.py b/litellm/types/agents.py index 8556b6bac93..f34631b5600 100644 --- a/litellm/types/agents.py +++ b/litellm/types/agents.py @@ -298,6 +298,23 @@ class MakeAgentsPublicRequest(BaseModel): agent_ids: List[str] +def _normalize_a2a_jsonrpc_response( + response_dict: Dict[str, Any], + request_id: Optional[Any] = None, +) -> Dict[str, Any]: + """ + Ensure JSON-RPC responses include ``id`` when the caller supplied one. + + The a2a SDK may omit ``id`` on error payloads even when the upstream agent + returned it. Backfill from the outbound request id so LiteLLM can surface the + agent error instead of failing Pydantic validation. + """ + normalized = dict(response_dict) + if normalized.get("id") is None and request_id is not None: + normalized["id"] = str(request_id) + return normalized + + class LiteLLMSendMessageResponse(LiteLLMPydanticObjectBase): """ LiteLLM wrapper for A2A SendMessageResponse. @@ -322,31 +339,42 @@ class LiteLLMSendMessageResponse(LiteLLMPydanticObjectBase): @classmethod def from_a2a_response( - cls, response: "SendMessageResponse" + cls, + response: "SendMessageResponse", + request_id: Optional[Any] = None, ) -> "LiteLLMSendMessageResponse": """ Create a LiteLLMSendMessageResponse from an a2a SDK SendMessageResponse. Args: response: The a2a SDK SendMessageResponse + request_id: JSON-RPC request id to backfill when the SDK omits it on errors Returns: LiteLLMSendMessageResponse with _hidden_params support """ - # Convert the a2a response to a dict response_dict = response.model_dump(mode="json", exclude_none=True) - + response_dict = _normalize_a2a_jsonrpc_response( + response_dict, request_id=request_id + ) return cls(**response_dict) @classmethod - def from_dict(cls, response_dict: Dict[str, Any]) -> "LiteLLMSendMessageResponse": + def from_dict( + cls, + response_dict: Dict[str, Any], + request_id: Optional[Any] = None, + ) -> "LiteLLMSendMessageResponse": """ Create a LiteLLMSendMessageResponse from a dict. Args: response_dict: Dict with A2A response structure + request_id: JSON-RPC request id to backfill when missing on error payloads Returns: LiteLLMSendMessageResponse with _hidden_params support """ - return cls(**response_dict) + return cls( + **_normalize_a2a_jsonrpc_response(response_dict, request_id=request_id) + ) diff --git a/tests/test_litellm/a2a_protocol/test_send_message_response.py b/tests/test_litellm/a2a_protocol/test_send_message_response.py new file mode 100644 index 00000000000..832aa288c7a --- /dev/null +++ b/tests/test_litellm/a2a_protocol/test_send_message_response.py @@ -0,0 +1,43 @@ +"""Tests for LiteLLMSendMessageResponse JSON-RPC normalization.""" + +from litellm.types.agents import LiteLLMSendMessageResponse + + +def test_from_dict_backfills_id_on_agent_error_response(): + agent_error = { + "jsonrpc": "2.0", + "error": {"code": -32054, "message": "Session not found"}, + } + + response = LiteLLMSendMessageResponse.from_dict( + agent_error, request_id="r1" + ) + + assert response.id == "r1" + assert response.error == {"code": -32054, "message": "Session not found"} + assert response.result is None + + +def test_from_dict_preserves_existing_id(): + payload = { + "id": "upstream-id", + "jsonrpc": "2.0", + "error": {"code": -32001, "message": "Task not found"}, + } + + response = LiteLLMSendMessageResponse.from_dict( + payload, request_id="r1" + ) + + assert response.id == "upstream-id" + + +def test_from_dict_without_request_id_still_requires_id(): + try: + LiteLLMSendMessageResponse.from_dict( + {"jsonrpc": "2.0", "error": {"code": -32054, "message": "x"}} + ) + except Exception as exc: + assert "id" in str(exc).lower() + else: + raise AssertionError("expected validation error when id and request_id missing") diff --git a/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py b/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py index a32f2eadb99..07e878401e0 100644 --- a/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py +++ b/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py @@ -5,7 +5,9 @@ Tests that invoke_agent_a2a properly integrates with add_litellm_data_to_request """ import json +import socket import sys +from contextlib import ExitStack from unittest.mock import AsyncMock, MagicMock, patch import pytest @@ -348,3 +350,1213 @@ async def test_invoke_agent_a2a_injects_authenticated_key_hash_for_bridge(): captured.get("litellm_params", {}).get(A2A_USER_API_KEY_HASH_PARAM) == mock_user_api_key_dict.api_key ), "authenticated key hash was not forwarded to the completion bridge" + + +def _make_agent_mock(url: str = "http://backend-agent:10001") -> MagicMock: + agent = MagicMock() + agent.agent_id = "test-agent" + agent.agent_name = "test-agent" + agent.agent_card_params = {"url": url, "name": "Test Agent"} + agent.litellm_params = {} + agent.static_headers = None + agent.extra_headers = None + return agent + + +def _make_request_mock( + method: str, params: dict, request_id: object = "req-1" +) -> MagicMock: + req = MagicMock() + req.headers = {} + req.json = AsyncMock( + return_value={ + "jsonrpc": "2.0", + "id": request_id, + "method": method, + "params": params, + } + ) + return req + + +def _base_patches(agent: MagicMock): + return [ + patch( + "litellm.proxy.agent_endpoints.a2a_endpoints._get_agent", + return_value=agent, + ), + patch( + "litellm.proxy.agent_endpoints.auth.agent_permission_handler.AgentRequestHandler.is_agent_allowed", + new=AsyncMock(return_value=True), + ), + patch( + "litellm.proxy.common_request_processing.add_litellm_data_to_request", + new=AsyncMock(side_effect=_add_proxy_data), + ), + patch("litellm.proxy.proxy_server.general_settings", {}), + patch("litellm.proxy.proxy_server.proxy_config", MagicMock()), + patch("litellm.proxy.proxy_server.version", "1.0.0"), + ] + + +async def _add_proxy_data(data, **kwargs): + data["proxy_server_request"] = { + "url": "http://localhost:4000", + "method": "POST", + "headers": {}, + "body": {}, + } + data.setdefault("metadata", {}) + return data + + +@pytest.mark.asyncio +@pytest.mark.parametrize("method", ["message/send", "message/stream"]) +async def test_message_methods_preserve_numeric_zero_request_id(method: str): + from fastapi.responses import JSONResponse + from litellm.proxy._types import UserAPIKeyAuth + + class MessageSendParams: + def __init__(self, **kwargs): + self.__dict__.update(kwargs) + + class SendMessageRequest: + def __init__(self, **kwargs): + self.__dict__.update(kwargs) + + agent = _make_agent_mock() + params = { + "message": { + "role": "user", + "parts": [{"kind": "text", "text": "Hello"}], + "messageId": "msg-123", + } + } + mock_request = _make_request_mock(method, params, request_id=0) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + captured = {} + + async def capture_asend_message(request, **kwargs): + captured["request_id"] = request.id + response = MagicMock() + response.model_dump.return_value = { + "jsonrpc": "2.0", + "id": request.id, + "result": {"status": "success"}, + } + return response + + async def capture_stream_message(**kwargs): + captured["request_id"] = kwargs["request_id"] + return JSONResponse({"jsonrpc": "2.0", "id": kwargs["request_id"]}) + + mock_a2a_types = MagicMock() + mock_a2a_types.MessageSendParams = MessageSendParams + mock_a2a_types.SendMessageRequest = SendMessageRequest + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context(patch("litellm.a2a_protocol.main.A2A_SDK_AVAILABLE", True)) + if method == "message/send": + stack.enter_context( + patch.dict( + sys.modules, + {"a2a": MagicMock(), "a2a.types": mock_a2a_types}, + ) + ) + stack.enter_context( + patch( + "litellm.a2a_protocol.asend_message", + new=AsyncMock(side_effect=capture_asend_message), + ) + ) + else: + stack.enter_context( + patch( + "litellm.proxy.agent_endpoints.a2a_endpoints._handle_stream_message", + new=AsyncMock(side_effect=capture_stream_message), + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert captured["request_id"] == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "method,params", + [ + ("tasks/get", {"id": "task-1"}), + ("tasks/list", {"contextId": "ctx-1"}), + ("tasks/cancel", {"id": "task-1"}), + ( + "tasks/pushNotificationConfig/set", + {"taskId": "task-1", "url": "https://webhook.example.com"}, + ), + ("tasks/pushNotificationConfig/get", {"taskId": "task-1", "id": "cfg-1"}), + ("tasks/pushNotificationConfig/list", {"taskId": "task-1"}), + ("tasks/pushNotificationConfig/delete", {"taskId": "task-1", "id": "cfg-1"}), + ], +) +async def test_task_methods_forward_jsonrpc(method: str, params: dict): + from litellm.proxy._types import UserAPIKeyAuth + + upstream_response = { + "jsonrpc": "2.0", + "id": "req-1", + "result": {"id": "task-1", "status": {"state": "completed"}}, + } + agent = _make_agent_mock() + mock_request = _make_request_mock(method, params) + + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + mock_http_response.raise_for_status = MagicMock() + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + mock_handler.client = MagicMock() + + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + stack.enter_context( + patch( + "litellm.proxy.agent_endpoints.a2a_endpoints.validate_url", + return_value=("https://webhook.example.com", "webhook.example.com"), + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + body = json.loads(response.body.decode()) + assert body["jsonrpc"] == "2.0" + assert body["result"]["id"] == "task-1" + + posted = mock_handler.post.call_args + assert posted is not None + forwarded_body = posted.kwargs.get("json") or posted.args[1] + assert forwarded_body["method"] == method + + +@pytest.mark.asyncio +@pytest.mark.parametrize("method", ["tasks/get", "tasks/resubscribe"]) +async def test_task_methods_extract_litellm_params_before_forwarding(method: str): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + params = { + "id": "task-1", + "guardrails": ["guardrail-1"], + "tags": ["tag-1"], + } + mock_request = _make_request_mock(method, params) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + captured_data = {} + + async def capture_proxy_data(data, **kwargs): + captured_data.update(data) + return await _add_proxy_data(data, **kwargs) + + upstream_response = { + "jsonrpc": "2.0", + "id": "req-1", + "result": {"id": "task-1", "status": {"state": "completed"}}, + } + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + + async def fake_aiter_lines(): + yield 'data: {"jsonrpc":"2.0","id":"req-1","result":{"taskId":"task-1"}}' + + mock_resp = AsyncMock() + mock_resp.is_success = True + mock_resp.aiter_lines = fake_aiter_lines + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + mock_handler.client = mock_async_client + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.proxy.common_request_processing.add_litellm_data_to_request", + new=AsyncMock(side_effect=capture_proxy_data), + ) + ) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + if method == "tasks/resubscribe": + async for _ in response.body_iterator: + pass + + if method == "tasks/resubscribe": + forwarded_body = mock_async_client.build_request.call_args.kwargs["json"] + else: + forwarded_body = mock_handler.post.call_args.kwargs["json"] + assert forwarded_body["params"] == {"id": "task-1"} + assert captured_data["guardrails"] == ["guardrail-1"] + assert captured_data["tags"] == ["tag-1"] + + +@pytest.mark.asyncio +async def test_subscribe_to_task_returns_sse_stream(): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("SubscribeToTask", {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + sse_lines = [ + 'data: {"jsonrpc":"2.0","id":"req-1","result":{"taskId":"task-1","status":{"state":"working"}}}', + 'data: {"jsonrpc":"2.0","id":"req-1","result":{"taskId":"task-1","status":{"state":"completed"}}}', + ] + + async def fake_aiter_lines(): + for line in sse_lines: + yield line + + mock_resp = AsyncMock() + mock_resp.is_success = True + mock_resp.aiter_lines = fake_aiter_lines + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.client = mock_async_client + mock_handler.post = AsyncMock() + + chunks = [] + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert response.media_type == "text/event-stream" + async for chunk in response.body_iterator: + chunks.append(chunk) + + full = "".join(chunks) + assert "working" in full + assert "completed" in full + + +@pytest.mark.asyncio +async def test_subscribe_to_task_calls_pre_call_hook(): + """tasks/resubscribe must run pre_call_hook so guardrails configured on + the agent are enforced before streaming begins.""" + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/resubscribe", {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + async def fake_aiter_lines(): + yield 'data: {"jsonrpc":"2.0","id":"req-1","result":{"taskId":"task-1","status":{"state":"completed"}}}' + + mock_resp = AsyncMock() + mock_resp.is_success = True + mock_resp.aiter_lines = fake_aiter_lines + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.client = mock_async_client + mock_handler.post = AsyncMock() + + async def _passthrough_iterator(response, **kwargs): + async for chunk in response: + yield chunk + + mock_proxy_logging = MagicMock() + mock_proxy_logging.pre_call_hook = AsyncMock( + side_effect=lambda user_api_key_dict, data, call_type: data + ) + mock_proxy_logging.async_post_call_streaming_iterator_hook = _passthrough_iterator + mock_proxy_logging.post_call_failure_hook = AsyncMock(return_value=None) + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + stack.enter_context( + patch( + "litellm.proxy.proxy_server.proxy_logging_obj", + mock_proxy_logging, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert response.media_type == "text/event-stream" + async for _ in response.body_iterator: + pass + + mock_proxy_logging.pre_call_hook.assert_awaited_once() + call_kwargs = mock_proxy_logging.pre_call_hook.await_args.kwargs + assert call_kwargs.get("call_type") == "asend_message" + assert call_kwargs.get("user_api_key_dict") == user_api_key_dict + + +@pytest.mark.asyncio +async def test_subscribe_to_task_runs_post_call_streaming_guardrail(): + """tasks/resubscribe must route streamed events through the post-call + streaming hook so output guardrails configured on the agent inspect the + streamed task content. Regression: the SSE path previously returned the raw + upstream stream and bypassed guardrails entirely.""" + import litellm + from litellm.integrations.custom_guardrail import CustomGuardrail + from litellm.proxy._types import UserAPIKeyAuth + + inspected: list = [] + + class _RecordingGuardrail(CustomGuardrail): + async def async_post_call_streaming_hook(self, user_api_key_dict, response): + inspected.append(response) + return response + + guardrail = _RecordingGuardrail( + guardrail_name="record-a2a", default_on=True, event_hook="post_call" + ) + + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/resubscribe", {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + async def fake_aiter_lines(): + yield ( + 'data: {"jsonrpc":"2.0","id":"req-1","result":' + '{"kind":"message","parts":[{"kind":"text","text":"resubscribe-secret"}]}}' + ) + + mock_resp = AsyncMock() + mock_resp.is_success = True + mock_resp.aiter_lines = fake_aiter_lines + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.client = mock_async_client + mock_handler.post = AsyncMock() + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + stack.enter_context(patch.object(litellm, "callbacks", [guardrail])) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert response.media_type == "text/event-stream" + async for _ in response.body_iterator: + pass + + assert any("resubscribe-secret" in str(r) for r in inspected), ( + "tasks/resubscribe streamed content was not passed to the post-call " + "streaming guardrail hook" + ) + + +@pytest.mark.asyncio +async def test_task_method_failure_hook_uses_enriched_request_data(): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/get", {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + async def add_proxy_data_copy(data, **kwargs): + enriched = dict(data) + enriched["proxy_server_request"] = { + "url": "http://localhost:4000", + "method": "POST", + "headers": {}, + "body": {}, + } + enriched.setdefault("metadata", {}) + return enriched + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(side_effect=RuntimeError("upstream failed")) + + mock_proxy_logging = MagicMock() + mock_proxy_logging.pre_call_hook = AsyncMock( + side_effect=lambda user_api_key_dict, data, call_type: data + ) + mock_proxy_logging.post_call_failure_hook = AsyncMock(return_value=None) + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.proxy.common_request_processing.add_litellm_data_to_request", + new=AsyncMock(side_effect=add_proxy_data_copy), + ) + ) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + stack.enter_context( + patch( + "litellm.proxy.proxy_server.proxy_logging_obj", + mock_proxy_logging, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + body = json.loads(response.body.decode()) + assert body["error"]["code"] == -32603 + failure_data = mock_proxy_logging.post_call_failure_hook.await_args.kwargs[ + "request_data" + ] + assert failure_data.get("litellm_call_id") + assert failure_data.get("agent_id") == "test-agent" + + +@pytest.mark.asyncio +async def test_get_extended_agent_card_rewrites_url(): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("GetExtendedAgentCard", {}) + mock_request.base_url = "http://localhost:4000/" + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + upstream_card = { + "name": "Test Agent", + "url": "http://backend-agent:10001", + "description": "A test agent", + } + upstream_response = {"jsonrpc": "2.0", "id": "req-1", "result": upstream_card} + + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + mock_http_response.raise_for_status = MagicMock() + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + mock_handler.client = MagicMock() + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + body = json.loads(response.body.decode()) + assert body["result"]["url"] == "http://localhost:4000/a2a/test-agent" + assert body["result"]["name"] == "Test Agent" + + +@pytest.mark.asyncio +async def test_unknown_method_returns_jsonrpc_error(): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("SomeUnknownMethod", {}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + body = json.loads(response.body.decode()) + assert body["error"]["code"] == -32601 + assert "SomeUnknownMethod" in body["error"]["message"] + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "pascal_method,expected_wire_method", + [ + ("GetTask", "tasks/get"), + ("ListTasks", "tasks/list"), + ("CancelTask", "tasks/cancel"), + ("SubscribeToTask", "tasks/resubscribe"), + ("CreateTaskPushNotificationConfig", "tasks/pushNotificationConfig/set"), + ("GetTaskPushNotificationConfig", "tasks/pushNotificationConfig/get"), + ("ListTaskPushNotificationConfigs", "tasks/pushNotificationConfig/list"), + ("DeleteTaskPushNotificationConfig", "tasks/pushNotificationConfig/delete"), + ("GetExtendedAgentCard", "agent/getAuthenticatedExtendedCard"), + ], +) +async def test_pascal_method_names_normalize_to_wire_format( + pascal_method: str, expected_wire_method: str +): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock(pascal_method, {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + upstream_response = {"jsonrpc": "2.0", "id": "req-1", "result": {"id": "task-1"}} + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + mock_http_response.raise_for_status = MagicMock() + + async def _empty_aiter_lines(): + return + yield # make it an async generator + + mock_sse_resp = AsyncMock() + mock_sse_resp.is_success = True + mock_sse_resp.aiter_lines = _empty_aiter_lines + mock_sse_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_sse_resp) + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + mock_handler.client = mock_async_client + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + if expected_wire_method == "tasks/resubscribe": + assert response.media_type == "text/event-stream" + async for _ in response.body_iterator: + pass + else: + body = json.loads(response.body.decode()) + assert "error" not in body, f"Got error: {body}" + + if expected_wire_method != "tasks/resubscribe": + posted = mock_handler.post.call_args + forwarded_body = posted.kwargs.get("json") or posted.args[1] + assert forwarded_body["method"] == expected_wire_method, ( + f"Expected '{expected_wire_method}' forwarded for PascalCase '{pascal_method}', " + f"but got '{forwarded_body['method']}'" + ) + + +@pytest.mark.asyncio +async def test_task_method_upstream_jsonrpc_error_on_http_4xx_is_relayed(): + """When upstream returns HTTP 4xx with a JSON-RPC error body, the error body + must be relayed to the client unchanged, not replaced with a generic string.""" + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/get", {"id": "nonexistent"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + upstream_error = { + "jsonrpc": "2.0", + "id": "req-1", + "error": {"code": -32001, "message": "Task not found"}, + } + + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_error + mock_http_response.is_success = False + mock_http_response.raise_for_status = MagicMock( + side_effect=Exception("404 Not Found") + ) + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + mock_handler.client = MagicMock() + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + body = json.loads(response.body.decode()) + assert body["error"]["code"] == -32001 + assert body["error"]["message"] == "Task not found" + + +@pytest.mark.asyncio +async def test_subscribe_to_task_upstream_error_yields_jsonrpc_error_event(): + """When upstream returns a non-2xx response for tasks/resubscribe, the SSE + stream must yield a JSON-RPC error event instead of silently breaking.""" + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/resubscribe", {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + mock_resp = AsyncMock() + mock_resp.is_success = False + mock_resp.status_code = 404 + mock_resp.reason_phrase = "Not Found" + mock_resp.aread = AsyncMock( + return_value=b'{"jsonrpc":"2.0","error":{"code":-32001,"message":"Task not found"}}' + ) + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.client = mock_async_client + mock_handler.post = AsyncMock() + + chunks = [] + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert response.media_type == "text/event-stream" + async for chunk in response.body_iterator: + chunks.append(chunk) + + full = "".join(chunks) + body = json.loads(full.removeprefix("data: ").strip()) + assert body["id"] == "req-1" + assert body["error"]["code"] == -32001 + assert body["error"]["message"] == "Task not found" + + +@pytest.mark.asyncio +async def test_forward_jsonrpc_sse_fallback_error_uses_jsonrpc_error_code(): + mock_resp = AsyncMock() + mock_resp.is_success = False + mock_resp.status_code = 503 + mock_resp.reason_phrase = "Service Unavailable" + mock_resp.aread = AsyncMock(return_value=b"upstream unavailable") + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.client = mock_async_client + + with patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ): + from litellm.proxy.agent_endpoints.a2a_endpoints import _forward_jsonrpc_sse + + response = await _forward_jsonrpc_sse( + agent_url="http://backend-agent:10001", + body={"jsonrpc": "2.0", "id": "req-1", "method": "tasks/resubscribe"}, + request_id="req-1", + ) + + chunks = [] + async for chunk in response.body_iterator: + chunks.append(chunk) + + body = json.loads("".join(chunks).removeprefix("data: ").strip()) + assert body["error"]["code"] == -32603 + assert body["error"]["message"] == "Service Unavailable" + + +@pytest.mark.asyncio +async def test_task_methods_forward_caller_identity_headers(): + """Task operations must forward X-LiteLLM-User-Id and X-LiteLLM-Team-Id so the + upstream agent can scope resources to the authenticated caller.""" + from litellm.proxy._types import UserAPIKeyAuth + + upstream_response = { + "jsonrpc": "2.0", + "id": "req-1", + "result": {"id": "task-1", "status": {"state": "completed"}}, + } + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/get", {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test", user_id="user-abc", team_id="team-xyz" + ) + + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + posted_headers = mock_handler.post.call_args.kwargs.get("headers") or {} + assert posted_headers.get("X-LiteLLM-User-Id") == "user-abc" + assert posted_headers.get("X-LiteLLM-Team-Id") == "team-xyz" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("method", ["tasks/get", "tasks/resubscribe"]) +async def test_task_methods_forward_trace_header(method: str): + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock(method, {"id": "task-1"}) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + async def add_proxy_data_with_trace(data, **kwargs): + data = await _add_proxy_data(data, **kwargs) + data["litellm_trace_id"] = "trace-123" + return data + + upstream_response = { + "jsonrpc": "2.0", + "id": "req-1", + "result": {"id": "task-1", "status": {"state": "completed"}}, + } + + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + + async def fake_aiter_lines(): + yield 'data: {"jsonrpc":"2.0","id":"req-1","result":{"taskId":"task-1"}}' + + mock_resp = AsyncMock() + mock_resp.is_success = True + mock_resp.aiter_lines = fake_aiter_lines + mock_resp.aclose = AsyncMock() + + mock_async_client = MagicMock() + mock_async_client.build_request = MagicMock(return_value=MagicMock()) + mock_async_client.send = AsyncMock(return_value=mock_resp) + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + mock_handler.client = mock_async_client + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.proxy.common_request_processing.add_litellm_data_to_request", + new=AsyncMock(side_effect=add_proxy_data_with_trace), + ) + ) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + response = await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + if method == "tasks/resubscribe": + async for _ in response.body_iterator: + pass + + if method == "tasks/resubscribe": + forwarded_headers = mock_async_client.build_request.call_args.kwargs["headers"] + else: + forwarded_headers = mock_handler.post.call_args.kwargs["headers"] + assert forwarded_headers.get("X-LiteLLM-Trace-Id") == "trace-123" + + +@pytest.mark.asyncio +async def test_push_notification_config_set_rejects_http_url(): + """tasks/pushNotificationConfig/set must reject non-HTTPS callback URLs to prevent SSRF.""" + from fastapi import HTTPException + + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock( + "tasks/pushNotificationConfig/set", + {"taskId": "task-1", "url": "http://internal-webhook.example.com/hook"}, + ) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + with pytest.raises(HTTPException) as exc_info: + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert exc_info.value.status_code == 400 + assert "HTTPS" in exc_info.value.detail + + +@pytest.mark.asyncio +async def test_push_notification_config_set_rejects_private_ip(): + """tasks/pushNotificationConfig/set must reject callback URLs pointing to private IP ranges.""" + from fastapi import HTTPException + + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock( + "tasks/pushNotificationConfig/set", + {"taskId": "task-1", "url": "https://192.168.1.100/hook"}, + ) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + with pytest.raises(HTTPException) as exc_info: + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert exc_info.value.status_code == 400 + assert "blocked address" in exc_info.value.detail.lower() + + +@pytest.mark.asyncio +async def test_push_notification_config_set_validates_nested_url_when_top_level_present(): + """A safe top-level params.url must not let a private pushNotificationConfig.url bypass SSRF checks. + + Both URL-bearing fields are forwarded to the agent, so both must be validated independently. + """ + from fastapi import HTTPException + + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock( + "tasks/pushNotificationConfig/set", + { + "taskId": "task-1", + "url": "https://1.1.1.1/hook", + "pushNotificationConfig": {"url": "https://192.168.1.100/hook"}, + }, + ) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + with pytest.raises(HTTPException) as exc_info: + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert exc_info.value.status_code == 400 + assert "blocked address" in exc_info.value.detail.lower() + + +def test_push_notification_config_set_rejects_private_dns_resolution(): + from fastapi import HTTPException + + from litellm.proxy.agent_endpoints.a2a_endpoints import ( + _validate_push_notification_url, + ) + + with patch( + "litellm.litellm_core_utils.url_utils.socket.getaddrinfo", + return_value=[ + ( + socket.AF_INET, + socket.SOCK_STREAM, + socket.IPPROTO_TCP, + "", + ("10.0.0.5", 443), + ) + ], + ): + with pytest.raises(HTTPException) as exc_info: + _validate_push_notification_url("https://webhook.example.com/hook") + + assert exc_info.value.status_code == 400 + assert "blocked address" in exc_info.value.detail.lower() + + +@pytest.mark.asyncio +async def test_push_notification_config_set_rejects_null_push_config(): + from fastapi import HTTPException + + from litellm.proxy._types import UserAPIKeyAuth + + agent = _make_agent_mock() + mock_request = _make_request_mock( + "tasks/pushNotificationConfig/set", + {"taskId": "task-1", "pushNotificationConfig": None}, + ) + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1") + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + with pytest.raises(HTTPException) as exc_info: + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + assert exc_info.value.status_code == 400 + assert "pushNotificationConfig must be an object" in exc_info.value.detail + + +@pytest.mark.asyncio +async def test_caller_identity_headers_cannot_be_spoofed_via_forwarded_headers(): + """A client must not be able to override X-LiteLLM-User-Id / X-LiteLLM-Team-Id + by including x-a2a--x-litellm-user-id in their request headers. + The authenticated identity must always win.""" + from litellm.proxy._types import UserAPIKeyAuth + + upstream_response = { + "jsonrpc": "2.0", + "id": "req-1", + "result": {"id": "task-1", "status": {"state": "completed"}}, + } + agent = _make_agent_mock() + mock_request = _make_request_mock("tasks/get", {"id": "task-1"}) + mock_request.headers = { + "x-a2a-test-agent-x-litellm-user-id": "attacker-user", + "x-a2a-test-agent-x-litellm-team-id": "attacker-team", + } + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test", user_id="real-user", team_id="real-team" + ) + + mock_http_response = MagicMock() + mock_http_response.json.return_value = upstream_response + mock_http_response.is_success = True + + mock_handler = MagicMock() + mock_handler.post = AsyncMock(return_value=mock_http_response) + + with ExitStack() as stack: + for p in _base_patches(agent): + stack.enter_context(p) + stack.enter_context( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client", + return_value=mock_handler, + ) + ) + + from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a + + await invoke_agent_a2a( + agent_id="test-agent", + request=mock_request, + fastapi_response=MagicMock(), + user_api_key_dict=user_api_key_dict, + ) + + posted_headers = mock_handler.post.call_args.kwargs.get("headers") or {} + assert ( + posted_headers.get("X-LiteLLM-User-Id") == "real-user" + ), "authenticated user id must not be overridden by forwarded client headers" + assert ( + posted_headers.get("X-LiteLLM-Team-Id") == "real-team" + ), "authenticated team id must not be overridden by forwarded client headers" From 53a206a179e0976785bdb731ab97ad820cf83bd8 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 3 Jun 2026 11:26:13 -0700 Subject: [PATCH 12/92] fix(anthropic/adapter): emit thinking block for reasoning_content-only streaming chunks (#29600) * fix(anthropic/adapter): open thinking block for reasoning_content-only streaming chunks The /v1/messages streaming content-block classifier (_translate_streaming_openai_chunk_to_anthropic_content_block) only recognized thinking_blocks. OpenAI-compatible reasoning backends (vLLM/SGLang reasoning parsers: DeepSeek-R1, Qwen3, gpt-oss, ...) populate reasoning_content with thinking_blocks=None, so the classifier fell through to a text block. The delta translator already emits thinking_delta for reasoning_content, so those deltas landed inside a text block and Anthropic streaming clients (Claude Code, SDK .stream()) silently dropped the chain-of-thought. Mirror the reasoning_content fallback already present in the non-stream translator and the streaming delta translator so the classifier opens a thinking block. Adds a focused regression test. * fix(anthropic/adapter): reach reasoning_content branch when thinking_blocks attr is absent Delta deletes the thinking_blocks attribute when unset, so the prior nested check was unreachable for reasoning-only chunks (vLLM/SGLang). Make it a sibling elif so the content block is classified as thinking. * test(proxy): stop component-allowlist test leaking DATABASE_URL into xdist peers The component-allowlist test pins throwaway DATABASE_URL/LITELLM_MASTER_KEY values at import time via os.environ so importing proxy_server doesn't need a live database. Those values persisted for the whole pytest-xdist worker, so a sibling test sharing the worker (test_key_rotation_e2e's DB-backed E2E case) saw the leaked sqlite DATABASE_URL, treated it as an available database instead of skipping, and the Prisma engine rejected the non-postgres URL (P1012 -> httpx.ConnectError). Restore the prior environment after the import so the throwaway values never escape the module. --------- Co-authored-by: Tai An --- .../adapters/transformation.py | 11 ++++++ ...al_pass_through_adapters_transformation.py | 38 +++++++++++++++++++ .../proxy/test_component_allowlists.py | 20 ++++++++-- 3 files changed, 66 insertions(+), 3 deletions(-) diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py index 02e0c562654..150f056dc81 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py @@ -1510,6 +1510,17 @@ class LiteLLMAnthropicMessagesAdapter: return "thinking", ChatCompletionThinkingBlock( type="thinking", thinking=thinking, signature=signature ) + # OpenAI-compatible reasoning backends (e.g. vLLM/SGLang reasoning + # parsers) populate ``reasoning_content`` without ``thinking_blocks``. + # ``Delta`` deletes the ``thinking_blocks`` attribute when unset, so the + # branch above is skipped entirely; open a ``thinking`` block here so the + # matching ``thinking_delta`` stream is not emitted into a text block. + elif isinstance(choice, StreamingChoices) and getattr( + choice.delta, "reasoning_content", None + ): + return "thinking", ChatCompletionThinkingBlock( + type="thinking", thinking="", signature="" + ) return "text", TextBlock(type="text", text="") diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py index 74e1e17e6d7..a81261d5ffd 100644 --- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py @@ -170,6 +170,44 @@ def test_translate_streaming_openai_chunk_to_anthropic_thinking_content_block(): } +def test_translate_streaming_openai_chunk_to_anthropic_reasoning_content_only_content_block(): + """OpenAI-compatible reasoning backends (vLLM/SGLang) emit ``reasoning_content`` + without ``thinking_blocks``. The content-block classifier must still open a + ``thinking`` block so the matching ``thinking_delta`` stream is not emitted + inside a text block (which silently drops chain-of-thought for /v1/messages + streaming clients).""" + choices = [ + StreamingChoices( + finish_reason=None, + index=0, + delta=Delta( + reasoning_content="Let me think", + thinking_blocks=None, + content=None, + role="assistant", + function_call=None, + tool_calls=None, + audio=None, + ), + logprobs=None, + ) + ] + + ( + block_type, + content_block_start, + ) = LiteLLMAnthropicMessagesAdapter()._translate_streaming_openai_chunk_to_anthropic_content_block( + choices=choices + ) + + assert block_type == "thinking" + assert content_block_start == { + "type": "thinking", + "thinking": "", + "signature": "", + } + + def test_translate_streaming_openai_chunk_to_anthropic_thinking_signature_block(): choices = [ StreamingChoices( diff --git a/tests/test_litellm/proxy/test_component_allowlists.py b/tests/test_litellm/proxy/test_component_allowlists.py index d20e1781169..ad25856b972 100644 --- a/tests/test_litellm/proxy/test_component_allowlists.py +++ b/tests/test_litellm/proxy/test_component_allowlists.py @@ -23,9 +23,17 @@ import sys # Importing ``litellm.proxy.proxy_server`` runs its module-level setup, which # reads ``DATABASE_URL`` (Prisma) and ``LITELLM_MASTER_KEY``. Tier-zero CI # runners don't set these. We pin throwaway values before the import so the -# test never depends on a live database or master key. -os.environ.setdefault("DATABASE_URL", "sqlite:///:memory:") -os.environ.setdefault("LITELLM_MASTER_KEY", "sk-test-component-allowlist") +# test never depends on a live database or master key, then restore the prior +# environment so the throwaway values don't leak into sibling tests sharing the +# xdist worker (a leaked non-postgres ``DATABASE_URL`` makes DB-backed tests +# treat a phantom database as available instead of skipping). +_THROWAWAY_ENV = { + "DATABASE_URL": "sqlite:///:memory:", + "LITELLM_MASTER_KEY": "sk-test-component-allowlist", +} +_PRE_EXISTING_ENV = {key: os.environ.get(key) for key in _THROWAWAY_ENV} +for _key, _value in _THROWAWAY_ENV.items(): + os.environ.setdefault(_key, _value) from fastapi.routing import Mount @@ -38,6 +46,12 @@ from backend.routes.allowlist import BACKEND_EXACT_PATHS, BACKEND_PATH_PREFIXES from gateway.routes.allowlist import GATEWAY_EXACT_PATHS, GATEWAY_PATH_PREFIXES from litellm.proxy.proxy_server import app +for _key, _previous in _PRE_EXISTING_ENV.items(): + if _previous is None: + os.environ.pop(_key, None) + else: + os.environ[_key] = _previous + def _component_paths(routes, exact_paths, path_prefixes) -> set[str]: """Reproduce ``gateway.main._is_gateway_route`` / ``backend.main._is_backend_route``.""" From 34293fa80af6ba22da55d6be66ef05a35187a2d1 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Wed, 3 Jun 2026 11:28:08 -0700 Subject: [PATCH 13/92] ci: reproduce default-Windows wheel install to guard MAX_PATH (#29597) * ci: reproduce default-Windows wheel install to guard MAX_PATH The existing using_litellm_on_windows job installs the project with `uv sync`, an editable source install that never copies package files into a deep site-packages path, so it cannot see the 260-char MAX_PATH overflow that breaks `pip install litellm` on default Windows. The content-filter benchmark fixtures have hit that limit three times (#21941, #22039, #29536), each caught only after release. This adds a guard to the same job that builds the wheel and installs it the way an end user would: into a venv whose site-packages prefix is padded to a realistic worst-case Windows length (~100 chars), then asserts the install completes and litellm imports. Any packaged path long enough to bust MAX_PATH at that prefix is reported up front, so the check is deterministic regardless of the runner's long-path setting, while the real install also covers failure modes a length heuristic cannot (half-unpacked packages, reserved names, case collisions). This commit is the guard only; on the current tree it correctly fails because nine fixtures still exceed the limit. The rename that brings them back under it follows on this branch. * fix(packaging): shorten content-filter benchmark fixtures under MAX_PATH The 10 content-filter benchmark result fixtures used the legacy block_{topic}_-_contentfilter_({yaml}).json naming, up to 176 chars inside the wheel, which busts the Windows 260-char MAX_PATH limit once extracted under a realistic site-packages prefix and aborts `pip install litellm` on default Windows. Rename them to the short {topic}_cf.json scheme that _save_confusion_results already emits today (it splits the label on the em-dash and writes f"{topic}_cf"), matching the insults_cf.json and investment_cf.json files fixed earlier. Re-running the eval suite now regenerates these same short names rather than recreating the long ones. This drops the longest packaged path from 176 to 128, so the guard added in the previous commit goes from red to green with a 32-char margin. * test(windows): tidy MAX_PATH guard per review Close the wheel zip via a context manager rather than leaning on refcount collection, and select the wheel under dist/ by newest mtime so a stale artifact from an earlier build cannot be tested instead of the one just produced. Also pin down the venv-depth formula with a short note: the +2 is the separator joining the venv root to "Lib" plus the trailing separator before the entry, which lands the simulated site-packages prefix at exactly 100 chars. --- .circleci/config.yml | 9 ++- ....yaml).json => age_discrimination_cf.json} | 0 ...ml).json => claims_fraud_coaching_cf.json} | 0 ...ml).json => claims_medical_advice_cf.json} | 0 ...ml).json => claims_phi_disclosure_cf.json} | 0 ....json => claims_prior_auth_gaming_cf.json} | 0 ...l).json => claims_system_override_cf.json} | 0 ...json => disability_discrimination_cf.json} | 0 ...ml).json => gender_discrimination_cf.json} | 0 ...).json => military_discrimination_cf.json} | 0 ...).json => religion_discrimination_cf.json} | 0 .../check_windows_wheel_install.py | 76 +++++++++++++++++++ .../test_check_windows_wheel_install.py | 36 +++++++++ 13 files changed, 120 insertions(+), 1 deletion(-) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_age_discrimination_-_contentfilter_(age_discrimination.yaml).json => age_discrimination_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_claims_fraud_coaching_-_contentfilter_(claims_fraud_coaching.yaml).json => claims_fraud_coaching_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_claims_medical_advice_-_contentfilter_(claims_medical_advice.yaml).json => claims_medical_advice_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_claims_phi_disclosure_-_contentfilter_(claims_phi_disclosure.yaml).json => claims_phi_disclosure_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_claims_prior_auth_gaming_-_contentfilter_(claims_prior_auth_gaming.yaml).json => claims_prior_auth_gaming_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_claims_system_override_-_contentfilter_(claims_system_override.yaml).json => claims_system_override_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_disability_discrimination_-_contentfilter_(disability.yaml).json => disability_discrimination_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_gender_discrimination_-_contentfilter_(gender_sexual_orientation.yaml).json => gender_discrimination_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_military_discrimination_-_contentfilter_(military_status.yaml).json => military_discrimination_cf.json} (100%) rename litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/{block_religion_discrimination_-_contentfilter_(religion.yaml).json => religion_discrimination_cf.json} (100%) create mode 100644 tests/windows_tests/check_windows_wheel_install.py create mode 100644 tests/windows_tests/test_check_windows_wheel_install.py diff --git a/.circleci/config.yml b/.circleci/config.yml index 23ef423039f..f5a8fe77a25 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -182,7 +182,14 @@ jobs: - run: name: Run Windows-specific test command: | - uv run --no-sync python -m pytest tests/windows_tests/test_litellm_on_windows.py -v + uv run --no-sync python -m pytest tests/windows_tests/ -v + - run: + name: Guard against MAX_PATH-busting packaged wheel paths + environment: + UV_HTTP_TIMEOUT: "300" + command: | + uv build --wheel --out-dir dist + uv run --no-sync python tests/windows_tests/check_windows_wheel_install.py local_testing_part1: docker: diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_age_discrimination_-_contentfilter_(age_discrimination.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/age_discrimination_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_age_discrimination_-_contentfilter_(age_discrimination.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/age_discrimination_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_fraud_coaching_-_contentfilter_(claims_fraud_coaching.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_fraud_coaching_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_fraud_coaching_-_contentfilter_(claims_fraud_coaching.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_fraud_coaching_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_medical_advice_-_contentfilter_(claims_medical_advice.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_medical_advice_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_medical_advice_-_contentfilter_(claims_medical_advice.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_medical_advice_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_phi_disclosure_-_contentfilter_(claims_phi_disclosure.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_phi_disclosure_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_phi_disclosure_-_contentfilter_(claims_phi_disclosure.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_phi_disclosure_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_prior_auth_gaming_-_contentfilter_(claims_prior_auth_gaming.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_prior_auth_gaming_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_prior_auth_gaming_-_contentfilter_(claims_prior_auth_gaming.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_prior_auth_gaming_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_system_override_-_contentfilter_(claims_system_override.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_system_override_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_claims_system_override_-_contentfilter_(claims_system_override.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/claims_system_override_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_disability_discrimination_-_contentfilter_(disability.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/disability_discrimination_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_disability_discrimination_-_contentfilter_(disability.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/disability_discrimination_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_gender_discrimination_-_contentfilter_(gender_sexual_orientation.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/gender_discrimination_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_gender_discrimination_-_contentfilter_(gender_sexual_orientation.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/gender_discrimination_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_military_discrimination_-_contentfilter_(military_status.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/military_discrimination_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_military_discrimination_-_contentfilter_(military_status.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/military_discrimination_cf.json diff --git a/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_religion_discrimination_-_contentfilter_(religion.yaml).json b/litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/religion_discrimination_cf.json similarity index 100% rename from litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/block_religion_discrimination_-_contentfilter_(religion.yaml).json rename to litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/guardrail_benchmarks/results/religion_discrimination_cf.json diff --git a/tests/windows_tests/check_windows_wheel_install.py b/tests/windows_tests/check_windows_wheel_install.py new file mode 100644 index 00000000000..6dbb9da6288 --- /dev/null +++ b/tests/windows_tests/check_windows_wheel_install.py @@ -0,0 +1,76 @@ +"""Reproduce a default-Windows ``pip install litellm`` to catch the 260-char +MAX_PATH regression that content-filter benchmark fixtures keep reintroducing +(#21941, #22039, #29536). Run after ``uv build --wheel --out-dir dist``. +""" + +import glob +import os +import subprocess +import sys +import zipfile + +MAX_PATH = 260 +# Worst-case Windows site-packages prefix: long profile name + roaming AppData venv. +WORST_CASE_PREFIX = 100 + + +def overlong_install_paths(wheel, prefix_len=WORST_CASE_PREFIX, max_path=MAX_PATH): + with zipfile.ZipFile(wheel) as zf: + names = zf.namelist() + return sorted( + (n for n in names if prefix_len + len(n) > max_path), key=len, reverse=True + ) + + +def _deep_venv_dir(target_prefix=WORST_CASE_PREFIX): + drive = os.path.splitdrive(os.getcwd())[0] or "C:" + root = drive + os.sep + "lmwin" + os.sep + # +2: the sep joining the venv root to "Lib", plus the trailing sep before the entry + suffix = len(os.path.join("Lib", "site-packages")) + 2 + return root + "x" * (target_prefix - suffix - len(root)) + + +def _run(cmd): + print("+ " + subprocess.list2cmdline(cmd), flush=True) + return subprocess.call(cmd) + + +def main(): + wheels = glob.glob(os.path.join("dist", "*.whl")) + if not wheels: + print("::error::no wheel in dist/; run `uv build --wheel --out-dir dist` first") + return 1 + wheel = max(wheels, key=os.path.getmtime) + + offenders = overlong_install_paths(wheel) + if offenders: + print( + f"::error::{len(offenders)} packaged path(s) bust the Windows MAX_PATH limit " + f"at a {WORST_CASE_PREFIX}-char install prefix:" + ) + for n in offenders[:15]: + print(f" on-disk {WORST_CASE_PREFIX + len(n):4} {n}") + return 1 + + venv = _deep_venv_dir() + os.makedirs(os.path.dirname(venv), exist_ok=True) + if _run(["uv", "venv", venv]) != 0: + return 1 + python = os.path.join(venv, "Scripts", "python.exe") + if _run(["uv", "pip", "install", "--python", python, wheel]) != 0: + print( + f"::error::installing {os.path.basename(wheel)} into a deep prefix failed" + ) + return 1 + if _run([python, "-c", "import litellm; import litellm.types.utils"]) != 0: + print("::error::litellm did not import after install (half-unpacked package)") + return 1 + + print( + f"ok: {os.path.basename(wheel)} installs into a worst-case prefix and imports" + ) + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/tests/windows_tests/test_check_windows_wheel_install.py b/tests/windows_tests/test_check_windows_wheel_install.py new file mode 100644 index 00000000000..22a197604ed --- /dev/null +++ b/tests/windows_tests/test_check_windows_wheel_install.py @@ -0,0 +1,36 @@ +import zipfile + +from check_windows_wheel_install import ( + MAX_PATH, + WORST_CASE_PREFIX, + overlong_install_paths, +) + + +def _wheel(tmp_path, *entry_names): + path = tmp_path / "pkg.whl" + with zipfile.ZipFile(path, "w") as zf: + for name in entry_names: + zf.writestr(name, "{}") + return str(path) + + +def test_flags_entry_one_char_over_budget(tmp_path): + busts = "a" * (MAX_PATH - WORST_CASE_PREFIX + 1) + assert overlong_install_paths(_wheel(tmp_path, busts)) == [busts] + + +def test_allows_entry_exactly_at_budget(tmp_path): + at_limit = "a" * (MAX_PATH - WORST_CASE_PREFIX) + assert ( + overlong_install_paths(_wheel(tmp_path, at_limit, "litellm/__init__.py")) == [] + ) + + +def test_orders_offenders_longest_first(tmp_path): + longer = "a" * (MAX_PATH - WORST_CASE_PREFIX + 5) + shorter = "b" * (MAX_PATH - WORST_CASE_PREFIX + 1) + assert overlong_install_paths(_wheel(tmp_path, shorter, longer)) == [ + longer, + shorter, + ] From cc55662e5fdc6af4f118a1f3ff885068b75450d9 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 3 Jun 2026 11:34:04 -0700 Subject: [PATCH 14/92] fix(vertex): strip output_config.effort for Vertex Claude models that reject it (Haiku 4.5) (#29585) * fix(vertex): strip output_config.effort for models that reject it Haiku 4.5 on Vertex AI does not support output_config.effort and 400s with "output_config.effort: Extra inputs are not permitted". PR #27074 emptied VERTEX_UNSUPPORTED_OUTPUT_CONFIG_KEYS so effort would forward for Opus/Sonnet 4.6+, but that made the strip unconditional across every Vertex Anthropic model, including ones that don't support it. Claude Code injects effort into its default Messages payload, so `claude --model claude-haiku-4.5` started failing. Make the sanitizer model-aware: drop output_config.effort for models that don't advertise output_config support (or any reasoning effort level) while forwarding it for those that do. The fix covers both the chat-completion and Messages pass-through transformation paths since they share the helper. * chore(vertex): log at debug when dropping unsupported output_config.effort Operators pointing an unregistered Vertex Claude alias that does support effort would otherwise see it stripped with no signal. Debug level keeps it out of normal logs since Claude Code sends effort on every request. --- .../transformation.py | 2 +- .../anthropic/output_params_utils.py | 51 ++++++++++++++----- .../anthropic/transformation.py | 2 +- ...artner_models_anthropic_messages_config.py | 34 +++++++++++++ ...partner_models_anthropic_transformation.py | 46 ++++++++++++++--- 5 files changed, 112 insertions(+), 23 deletions(-) diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py index 4be4c2d5e78..1e92754857b 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py @@ -159,6 +159,6 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert "model", None ) # do not pass model in request body to vertex ai - sanitize_vertex_anthropic_output_params(anthropic_messages_request) + sanitize_vertex_anthropic_output_params(anthropic_messages_request, model) return anthropic_messages_request diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/output_params_utils.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/output_params_utils.py index a33ad677789..280cc1c888a 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/output_params_utils.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/output_params_utils.py @@ -10,23 +10,38 @@ import; extracting the helper into a leaf module resolves the warning and keeps the parent module's import surface narrow. """ -# Keys inside ``output_config`` that Vertex AI Claude does not accept. -# Add an entry only when a 400 "Extra inputs are not permitted" is -# reproducible against the live Vertex endpoint. +# Keys inside ``output_config`` that Vertex AI Claude rejects regardless of +# the target model. Add an entry only when a 400 "Extra inputs are not +# permitted" is reproducible against the live Vertex endpoint for every model. VERTEX_UNSUPPORTED_OUTPUT_CONFIG_KEYS: frozenset = frozenset() -def sanitize_vertex_anthropic_output_params(data: dict) -> None: +def _model_accepts_output_config_effort(model: str) -> bool: + """Whether ``model`` accepts ``output_config.effort`` on Vertex. + + Opus/Sonnet 4.6+ advertise ``supports_output_config`` (or a reasoning + effort level) and accept it; Haiku 4.5 advertises neither and 400s on + ``output_config.effort: Extra inputs are not permitted``. Imported lazily + so this stays a leaf module (see module docstring). + """ + from litellm.llms.anthropic.chat.transformation import AnthropicConfig + + return AnthropicConfig._model_supports_effort_param(model) + + +def sanitize_vertex_anthropic_output_params(data: dict, model: str) -> None: """ Strip Vertex-unsupported keys from ``output_config`` / ``output_format`` in-place; forward whatever remains. Behavior: - * ``output_config`` containing only unsupported keys (e.g. ``effort`` - alone) is removed entirely so the request body has no empty dict. - * ``output_config`` containing a mix of supported + unsupported keys - has the unsupported subset filtered out and the rest forwarded. - * ``output_config`` that is supported in full passes through unchanged. + * ``output_config.effort`` is dropped for models that don't accept it + (e.g. Haiku 4.5) and forwarded for those that do (Opus/Sonnet 4.6+). + Clients like Claude Code inject it into every Messages payload, so the + gate has to live here rather than rely on the caller. + * Keys in ``VERTEX_UNSUPPORTED_OUTPUT_CONFIG_KEYS`` are always filtered. + * ``output_config`` left empty after filtering is removed so the request + body has no empty dict. * ``output_format`` is forwarded as-is (Vertex AI Claude accepts it). * Non-dict values for ``output_config`` are dropped to avoid sending malformed payloads downstream. @@ -37,11 +52,19 @@ def sanitize_vertex_anthropic_output_params(data: dict) -> None: if not isinstance(output_config, dict): data.pop("output_config", None) return - sanitized = { - k: v - for k, v in output_config.items() - if k not in VERTEX_UNSUPPORTED_OUTPUT_CONFIG_KEYS - } + + drop_keys = set(VERTEX_UNSUPPORTED_OUTPUT_CONFIG_KEYS) + if "effort" in output_config and not _model_accepts_output_config_effort(model): + from litellm._logging import verbose_logger + + verbose_logger.debug( + "Dropping unsupported output_config.effort for vertex_ai model=%s " + "(no supports_output_config in the model map)", + model, + ) + drop_keys.add("effort") + + sanitized = {k: v for k, v in output_config.items() if k not in drop_keys} if sanitized: data["output_config"] = sanitized else: diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py index 4627d9f6df3..c852909d475 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py @@ -106,7 +106,7 @@ class VertexAIAnthropicConfig(AnthropicConfig): data.pop("model", None) # vertex anthropic doesn't accept 'model' parameter - sanitize_vertex_anthropic_output_params(data) + sanitize_vertex_anthropic_output_params(data, model) tools = optional_params.get("tools") tool_search_used = self.is_tool_search_used(tools) diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py index b8cd65d3c99..6f4bb4e59c2 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py @@ -313,6 +313,40 @@ def test_transform_anthropic_messages_request_removes_scope_from_cache_control() assert result["messages"][0]["content"][0]["cache_control"]["type"] == "ephemeral" +def test_messages_request_strips_effort_for_haiku_45(): + """Regression: Claude Code (``claude --model claude-haiku-4.5``) sends + ``output_config.effort`` in its default Messages payload. Haiku 4.5 on + Vertex rejects it with 400 ``output_config.effort: Extra inputs are not + permitted``, so the pass-through must strip it for Haiku while keeping it + for Opus/Sonnet 4.6+.""" + config = VertexAIPartnerModelsAnthropicMessagesConfig() + messages = [{"role": "user", "content": "Hello"}] + + haiku_result = config.transform_anthropic_messages_request( + model="claude-haiku-4-5@20251001", + messages=messages, + anthropic_messages_optional_request_params={ + "max_tokens": 1024, + "output_config": {"effort": "high"}, + }, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + assert "output_config" not in haiku_result + + opus_result = config.transform_anthropic_messages_request( + model="claude-opus-4-6", + messages=messages, + anthropic_messages_optional_request_params={ + "max_tokens": 1024, + "output_config": {"effort": "high"}, + }, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + assert opus_result["output_config"] == {"effort": "high"} + + def test_provider_config_manager_reuses_vertex_anthropic_messages_config_instance(): """ Regression test: repeated provider config lookups for the same Vertex Claude model diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py index d89d09a4e63..ac2368130d8 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py @@ -675,28 +675,60 @@ def test_sanitize_vertex_anthropic_output_params_unit(): sanitize_vertex_anthropic_output_params, ) + supported = "claude-opus-4-6" + # No-op when output_config absent. data: dict = {"max_tokens": 8} - sanitize_vertex_anthropic_output_params(data) + sanitize_vertex_anthropic_output_params(data, supported) assert data == {"max_tokens": 8} - # Effort-only → preserved (Vertex 4.6/4.7 accept it on rawPredict). + # Effort-only on a supporting model → preserved (Vertex 4.6/4.7 accept it). data = {"output_config": {"effort": "high"}} - sanitize_vertex_anthropic_output_params(data) + sanitize_vertex_anthropic_output_params(data, supported) assert data["output_config"] == {"effort": "high"} # Format-only → preserved unchanged. fmt = {"format": {"type": "json_schema", "schema": {"type": "object"}}} data = {"output_config": dict(fmt)} - sanitize_vertex_anthropic_output_params(data) + sanitize_vertex_anthropic_output_params(data, supported) assert data["output_config"] == fmt - # Mixed → both effort and format kept (no current Vertex-unsupported keys). + # Mixed on a supporting model → both effort and format kept. data = {"output_config": {"format": fmt["format"], "effort": "high"}} - sanitize_vertex_anthropic_output_params(data) + sanitize_vertex_anthropic_output_params(data, supported) assert data["output_config"] == {"format": fmt["format"], "effort": "high"} # Non-dict → dropped defensively. data = {"output_config": "garbage"} - sanitize_vertex_anthropic_output_params(data) + sanitize_vertex_anthropic_output_params(data, supported) assert "output_config" not in data + + +def test_sanitize_strips_effort_for_haiku_45(): + """Regression: Haiku 4.5 on Vertex does not support ``output_config.effort`` + and 400s with ``Extra inputs are not permitted``. Claude Code injects + ``effort`` into every Messages payload, so the helper must strip it for + models that don't advertise output_config support while leaving it intact + for Opus/Sonnet 4.6+.""" + from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.output_params_utils import ( + sanitize_vertex_anthropic_output_params, + ) + + haiku = "claude-haiku-4-5@20251001" + + # Effort-only → output_config removed entirely (no empty dict on the wire). + data: dict = {"output_config": {"effort": "high"}, "max_tokens": 8} + sanitize_vertex_anthropic_output_params(data, haiku) + assert "output_config" not in data + assert data["max_tokens"] == 8 + + # Mixed → effort stripped, format preserved. + fmt = {"type": "json_schema", "schema": {"type": "object"}} + data = {"output_config": {"effort": "high", "format": fmt}} + sanitize_vertex_anthropic_output_params(data, haiku) + assert data["output_config"] == {"format": fmt} + + # Same payload on a supporting model keeps effort untouched. + data = {"output_config": {"effort": "high"}} + sanitize_vertex_anthropic_output_params(data, "vertex_ai/claude-opus-4-6") + assert data["output_config"] == {"effort": "high"} From 2453936a82d300af31cb9ed9c4b6dae0208627b0 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Thu, 4 Jun 2026 00:18:35 +0530 Subject: [PATCH 15/92] Litellm websocket improvements (#29563) * Add support for websocket via codex * Add model alias and creds support * fix: skip cost tracking for WS session wrapper call types The @client decorator on _aresponses_websocket fires async_success_handler with result=None after the session ends. This triggered cost tracking errors because standard_logging_object is never built for None results. Per-turn costs are correctly tracked by individual litellm.aresponses calls inside the session. The outer session-level logging obj should not attempt cost tracking. Fix: skip _aresponses_websocket and _arealtime call types in deployment_callback_on_success, RouterBudgetLimiting.async_log_success_event, and _PROXY_track_cost_callback. * fix: address Greptile review comments Fix JSON injection: use json.dumps instead of f-string interpolation for model name in WS body. Add 30s timeout for first WS frame to prevent unbounded connection resource tie-up. Restore per-event model override in streaming_iterator; fall back to connection-level model when event omits it. Strengthen regression test: inject alias into kwargs via _update_kwargs_with_deployment mock so the test would fail on un-fixed code. * fix: handle nested response.create format in first-frame model extraction When ?model= is omitted, the first WS frame can carry the model in either flat format (first_event["model"]) or nested format (first_event["response"]["model"]). The flat-only check would silently reject clients using the nested wire format. Mirrors the same two-format logic in _build_base_call_kwargs. * fix: don't force connection-level custom_llm_provider on per-event model overrides If a client sends a different model per response.create turn, litellm needs to re-resolve the provider from that model string. Forcing the connection-level custom_llm_provider would silently route the request to the wrong backend. Only inject custom_llm_provider when the per-event model matches the connection-level model. * refactor: extract WS model extraction into testable function Pull the flat/nested model extraction into _extract_model_from_first_ws_event so tests import and exercise the real function rather than a copy. * fix: compare providers not full model strings in _inject_credentials The model == self.model guard was too strict: same-provider model variants (e.g., vertex_ai/gemini-2.0 -> vertex_ai/gemini-1.5 on one connection) would lose custom_llm_provider, breaking routing when a custom api_base is in use. Compare the provider extracted by get_llm_provider instead, so same-provider variants still inherit the connection-level provider while cross-provider overrides let litellm re-resolve. * style: black formatting * refactor: extract first-frame model resolution to fix PLR0915 (too many statements) * Fix responses WebSocket first-frame validation * fix: classify WS first-frame read errors and clarify cost-skip log Distinguish client disconnects from server errors when reading the responses WebSocket first frame, make the cost-tracking skip log message accurate for session wrappers (which do carry a model), and resolve the connection-level provider once per session instead of on every response.create event. * test: cover WS first-frame read errors and same-provider credential injection Adds regression tests for the still-uncovered responses WebSocket paths: the timeout, invalid-JSON and missing-model branches of _read_ws_model_from_first_frame, plus the provider comparison in ManagedResponsesWebSocketHandler._same_provider and _inject_credentials (same-provider model variants keep the connection provider; cross-provider models re-resolve). * fix(responses-ws): fall back to explicit custom_llm_provider when connection model is unresolvable When a WebSocket session is opened with a custom deployment alias that litellm cannot resolve to a provider, _connection_provider was None, so _same_provider returned False for every resolvable per-event model and the connection-level custom_llm_provider was dropped. Use the explicitly-set custom_llm_provider as the connection provider in that case so same-provider per-event models still inherit it while genuinely cross-provider models continue to re-resolve. --------- Co-authored-by: Cursor Agent Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/llms/custom_httpx/llm_http_handler.py | 3 + .../proxy/hooks/proxy_track_cost_callback.py | 10 +- .../proxy/response_api_endpoints/endpoints.py | 171 +++++- litellm/responses/streaming_iterator.py | 52 +- litellm/router.py | 5 +- litellm/router_strategy/budget_limiter.py | 3 + .../response_api_endpoints/test_endpoints.py | 515 ++++++++++++++++++ tests/test_litellm/test_router.py | 55 ++ 8 files changed, 796 insertions(+), 18 deletions(-) diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index 8b3add5398b..5c502c56ffe 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -5528,6 +5528,7 @@ class BaseLLMHTTPHandler: user_api_key_dict: Optional[Any] = None, litellm_metadata: Optional[Dict[str, Any]] = None, custom_llm_provider: Optional[str] = None, + first_message: Optional[str] = None, **kwargs: Any, ): """ @@ -5559,6 +5560,7 @@ class BaseLLMHTTPHandler: api_base=api_base, timeout=timeout, custom_llm_provider=custom_llm_provider, + first_message=first_message, **kwargs, ) await handler.run() @@ -5624,6 +5626,7 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, user_api_key_dict=user_api_key_dict, request_data=_request_data, + first_message=first_message, ) await streaming.bidirectional_forward() diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py index 3688f25ac44..b4a4fd571d0 100644 --- a/litellm/proxy/hooks/proxy_track_cost_callback.py +++ b/litellm/proxy/hooks/proxy_track_cost_callback.py @@ -285,9 +285,15 @@ class _ProxyDBLogger(CustomLogger): await _release_budget_reservation(budget_reservation=budget_reservation) # Non-model call types (health checks, afile_delete) have no model or standard_logging_object. # Use .get() for "stream" to avoid KeyError on health checks. - if sl_object is None and not kwargs.get("model"): + # WS session wrappers (_aresponses_websocket, _arealtime) also reach here with + # result=None; their per-turn costs are tracked on the inner aresponses/realtime calls. + if sl_object is None and ( + not kwargs.get("model") + or kwargs.get("call_type") + in ("_aresponses_websocket", "_arealtime") + ): verbose_proxy_logger.warning( - "Cost tracking - skipping, no standard_logging_object and no model for call_type=%s", + "Cost tracking - skipping, no standard_logging_object for call_type=%s", kwargs.get("call_type", "unknown"), ) return diff --git a/litellm/proxy/response_api_endpoints/endpoints.py b/litellm/proxy/response_api_endpoints/endpoints.py index 8023853e263..023f903194b 100644 --- a/litellm/proxy/response_api_endpoints/endpoints.py +++ b/litellm/proxy/response_api_endpoints/endpoints.py @@ -6,7 +6,7 @@ from uuid import uuid4 import fastapi from fastapi import APIRouter, Depends, HTTPException, Request, Response -from starlette.websockets import WebSocket +from starlette.websockets import WebSocket, WebSocketDisconnect from litellm._logging import verbose_proxy_logger from litellm.integrations.custom_guardrail import ModifyResponseException @@ -935,12 +935,146 @@ async def cancel_response( ) +async def _read_ws_model_from_first_frame( + websocket: WebSocket, +) -> Optional[tuple]: + """Read the first WS frame and return (model, raw_message), or None on error. + + Sends an appropriate error frame and closes the socket before returning None. + """ + try: + first_message = await asyncio.wait_for(websocket.receive_text(), timeout=30) + except asyncio.TimeoutError: + await websocket.close(code=1008, reason="Timed out waiting for first message") + return None + except WebSocketDisconnect: + return None + except Exception: + verbose_proxy_logger.exception( + "Responses WebSocket error reading first message" + ) + await websocket.close(code=1011, reason="Internal server error") + return None + + try: + first_event = json.loads(first_message) + except json.JSONDecodeError: + await websocket.send_text( + json.dumps( + { + "type": "error", + "error": { + "type": "invalid_request_error", + "message": "First message is not valid JSON.", + }, + } + ) + ) + await websocket.close(code=1008, reason="Invalid JSON in first message") + return None + + if ( + not isinstance(first_event, dict) + or first_event.get("type") != "response.create" + ): + await websocket.send_text( + json.dumps( + { + "type": "error", + "error": { + "type": "invalid_request_error", + "message": "First message must be a response.create JSON object.", + }, + } + ) + ) + await websocket.close(code=1008, reason="Invalid first message") + return None + + model = _extract_model_from_first_ws_event(first_event) + if not model: + await websocket.send_text( + json.dumps( + { + "type": "error", + "error": { + "type": "invalid_request_error", + "message": "No model provided. Supply ?model= in the URL or include 'model' in the first response.create event.", + }, + } + ) + ) + await websocket.close(code=1008, reason="No model provided") + return None + + return model, first_message + + +def _extract_model_from_first_ws_event(first_event: Any) -> Optional[str]: + """Extract model from a response.create WS event, handling flat and nested formats. + + Flat: {"type": "response.create", "model": "gpt-4o", ...} + Nested: {"type": "response.create", "response": {"model": "gpt-4o", ...}} + """ + if not isinstance(first_event, dict): + return None + nested = first_event.get("response") + return ( + nested.get("model") if isinstance(nested, dict) else None + ) or first_event.get("model") + + +async def _enforce_responses_ws_first_frame_model_auth( + request: Request, + model: str, + user_api_key_dict: UserAPIKeyAuth, + llm_router: Optional[Any], +) -> None: + from litellm.proxy.auth.user_api_key_auth import ( + _enforce_key_and_fallback_model_access, + _run_centralized_common_checks, + ) + from litellm.proxy.proxy_server import ( + general_settings, + llm_model_list, + master_key, + user_custom_auth, + ) + + request_data = {"model": model} + route = request.scope.get("path") or "/v1/responses" + if master_key is None and not ( + general_settings.get("enable_jwt_auth", False) + or general_settings.get("enable_oauth2_auth", False) + or general_settings.get("enable_oauth2_proxy_auth", False) + ): + return + if user_custom_auth is not None and not general_settings.get( + "custom_auth_run_common_checks", False + ): + return + await _enforce_key_and_fallback_model_access( + valid_token=user_api_key_dict, + request_data=request_data, + route=route, + request=request, + llm_model_list=llm_model_list, + llm_router=llm_router, + ) + await _run_centralized_common_checks( + user_api_key_auth_obj=user_api_key_dict, + request=request, + request_data=request_data, + route=route, + ) + + @router.websocket("/v1/responses") @router.websocket("/responses") async def responses_websocket_endpoint( websocket: WebSocket, - model: str = fastapi.Query( - ..., description="The model to use for the responses WebSocket session." + model: Optional[str] = fastapi.Query( + None, description="The model to use for the responses WebSocket session." ), user_api_key_dict=Depends(user_api_key_auth_websocket), ): @@ -950,6 +1084,10 @@ async def responses_websocket_endpoint( Keeps a persistent WebSocket connection for response.create events, enabling lower-latency agentic workflows with many tool-call round trips. + Follows the OpenAI split: the bearer token is validated at connection time + (before accept); the model is resolved either from the ?model= query param + or from the first response.create frame, whichever is present. + See: https://developers.openai.com/api/docs/guides/websocket-mode/ """ from litellm.proxy.proxy_server import ( @@ -966,7 +1104,8 @@ async def responses_websocket_endpoint( ) from litellm.proxy.route_llm_request import route_request - # Accept the WebSocket handshake + # Accept the WebSocket handshake. Key was already validated by the Depends + # above; we can safely accept regardless of whether ?model= was supplied. requested_protocols = [ p.strip() for p in (websocket.headers.get("sec-websocket-protocol") or "").split(",") @@ -977,10 +1116,19 @@ async def responses_websocket_endpoint( accept_kwargs["subprotocol"] = requested_protocols[0] await websocket.accept(**accept_kwargs) + first_message: Optional[str] = None + if not model: + result = await _read_ws_model_from_first_frame(websocket) + if result is None: + return + model, first_message = result + data: Dict[str, Any] = { "model": model, "websocket": websocket, } + if first_message is not None: + data["first_message"] = first_message # Construct a synthetic Request for pre-call processing headers_list = list(websocket.scope.get("headers") or []) @@ -993,14 +1141,23 @@ async def responses_websocket_endpoint( request = Request(scope=scope) request._url = websocket.url + _body_bytes = json.dumps({"model": model}).encode() + async def return_body(): - return f'{{"model": "{model}"}}'.encode() + return _body_bytes request.body = return_body # type: ignore # Phase 1: pre-call processing (auth, guardrails, rate limits) base_llm_response_processor = ProxyBaseLLMRequestProcessing(data=data) try: + if first_message is not None: + await _enforce_responses_ws_first_frame_model_auth( + request=request, + model=model, + user_api_key_dict=user_api_key_dict, + llm_router=llm_router, + ) ( data, litellm_logging_obj, @@ -1027,7 +1184,7 @@ async def responses_websocket_endpoint( { "type": "error", "error": { - "type": "pre_call_error", + "type": "invalid_request_error", "message": str(e), }, } @@ -1035,7 +1192,7 @@ async def responses_websocket_endpoint( ) except Exception: pass - await websocket.close(code=1011, reason="Pre-call error") + await websocket.close(code=1008, reason="Pre-call error") return # Phase 2: route to upstream provider diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index c4e72cb7dc5..dfc43bc29b5 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -1251,6 +1251,7 @@ class ResponsesWebSocketStreaming: logging_obj: LiteLLMLoggingObj, user_api_key_dict: Optional[Any] = None, request_data: Optional[Dict] = None, + first_message: Optional[str] = None, ): self.websocket = websocket self.backend_ws = backend_ws @@ -1259,6 +1260,7 @@ class ResponsesWebSocketStreaming: self.request_data: Dict = request_data or {} self.messages: list[Dict] = [] self.input_messages: list[Dict[str, str]] = [] + self.first_message = first_message def _should_store_event(self, event_obj: dict) -> bool: return event_obj.get("type") in RESPONSES_WS_LOGGED_EVENT_TYPES @@ -1362,6 +1364,11 @@ class ResponsesWebSocketStreaming: async def client_to_backend(self) -> None: """Forward response.create events from client to backend.""" try: + if self.first_message is not None: + self._store_input(self.first_message) + self._store_event(self.first_message) + await self.backend_ws.send(self.first_message) # type: ignore[union-attr] + while True: message = await self.websocket.receive_text() @@ -1440,6 +1447,7 @@ class ManagedResponsesWebSocketHandler: api_base: Optional[str] = None, timeout: Optional[float] = None, custom_llm_provider: Optional[str] = None, + first_message: Optional[str] = None, **kwargs: Any, ) -> None: self.websocket = websocket @@ -1451,6 +1459,8 @@ class ManagedResponsesWebSocketHandler: self.api_base = api_base self.timeout = timeout self.custom_llm_provider = custom_llm_provider + self._connection_provider = self._resolve_provider(model) or custom_llm_provider + self.first_message = first_message # Carry through safe pass-through kwargs (e.g. extra_headers) self.extra_kwargs: Dict[str, Any] = { k: v for k, v in kwargs.items() if k not in _MANAGED_WS_SKIP_KWARGS @@ -1648,8 +1658,30 @@ class ManagedResponsesWebSocketHandler: # cross-connection multi-turn when spend logs are committed) call_kwargs["previous_response_id"] = previous_response_id + @staticmethod + def _resolve_provider(model: Optional[str]) -> Optional[str]: + """Resolve the LLM provider for a model string, or None if unresolvable.""" + if not model: + return None + try: + from litellm import get_llm_provider + + _, provider, _, _ = get_llm_provider(model=model) + return provider + except Exception: + return None + + def _same_provider(self, model: Optional[str]) -> bool: + """Return True if model uses the same LLM provider as the connection model.""" + if model is None or model == self.model: + return True + event_provider = self._resolve_provider(model) + if event_provider is None: + return False + return event_provider == self._connection_provider + def _inject_credentials( - self, call_kwargs: Dict[str, Any], event_model: Optional[str] + self, call_kwargs: Dict[str, Any], model: Optional[str] = None ) -> None: """Inject connection-level credentials and metadata into call_kwargs.""" if self.api_key is not None: @@ -1658,10 +1690,12 @@ class ManagedResponsesWebSocketHandler: call_kwargs["api_base"] = self.api_base if self.timeout is not None: call_kwargs["timeout"] = self.timeout - # Only propagate custom_llm_provider when no per-request model override exists. - # If the payload specifies a different model, let litellm re-resolve the - # provider so we don't accidentally force the wrong backend. - if self.custom_llm_provider is not None and not event_model: + # Only force connection-level custom_llm_provider when the per-event model + # uses the same provider as the connection model. If the provider differs + # (e.g., connection is vertex_ai but event says openai/gpt-4), let litellm + # re-resolve from the model string. Same-provider model variants (e.g., + # vertex_ai/gemini-2.0 -> vertex_ai/gemini-1.5) still inherit the provider. + if self.custom_llm_provider is not None and self._same_provider(model): call_kwargs["custom_llm_provider"] = self.custom_llm_provider if self.litellm_metadata: call_kwargs["litellm_metadata"] = dict(self.litellm_metadata) @@ -1776,8 +1810,7 @@ class ManagedResponsesWebSocketHandler: call_kwargs = self._build_base_call_kwargs(msg_obj) call_kwargs["stream"] = True - event_model: Optional[str] = call_kwargs.pop("model", None) - model = event_model or self.model + model = call_kwargs.pop("model", None) or self.model previous_response_id: Optional[str] = call_kwargs.pop( "previous_response_id", None @@ -1794,7 +1827,7 @@ class ManagedResponsesWebSocketHandler: self._apply_history( call_kwargs, previous_response_id, current_messages, prior_history ) - self._inject_credentials(call_kwargs, event_model) + self._inject_credentials(call_kwargs, model=model) self._update_proxy_request(call_kwargs, model) call_kwargs.update(self.extra_kwargs) @@ -1819,6 +1852,9 @@ class ManagedResponsesWebSocketHandler: each one before waiting for the next message. """ try: + if self.first_message is not None: + await self._process_response_create(self.first_message) + while True: try: message = await self.websocket.receive_text() diff --git a/litellm/router.py b/litellm/router.py index 7aaf989919c..a92590d3dba 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -4636,11 +4636,11 @@ class Router: except Exception: custom_llm_provider = None - # Build response kwargs response_kwargs = { **data, "caching": self.cache_responses, **kwargs, + "model": model_name, } # Only set custom_llm_provider if it's not None if custom_llm_provider is not None: @@ -7126,6 +7126,9 @@ class Router: from litellm.types.caching import RedisPipelineIncrementOperation try: + # WS session wrappers fire with result=None; per-turn costs tracked by inner calls. + if kwargs.get("call_type") in ("_aresponses_websocket", "_arealtime"): + return standard_logging_object: Optional[StandardLoggingPayload] = kwargs.get( "standard_logging_object", None ) diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py index f677e40b934..0bb69ca0319 100644 --- a/litellm/router_strategy/budget_limiter.py +++ b/litellm/router_strategy/budget_limiter.py @@ -430,6 +430,9 @@ class RouterBudgetLimiting(CustomLogger): async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): """Original method now uses helper functions""" verbose_router_logger.debug("in RouterBudgetLimiting.async_log_success_event") + # WS session wrappers fire with result=None; per-turn costs tracked by inner calls. + if kwargs.get("call_type") in ("_aresponses_websocket", "_arealtime"): + return standard_logging_payload: Optional[StandardLoggingPayload] = kwargs.get( "standard_logging_object", None ) diff --git a/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py b/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py index 1929c443720..07d1a9d14f9 100644 --- a/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py +++ b/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py @@ -196,3 +196,518 @@ class TestResponsesAPIEndpoints(unittest.TestCase): assert "x-litellm-response-cost" in response.headers response_cost_value = float(response.headers["x-litellm-response-cost"]) assert response_cost_value == pytest.approx(0.0005, abs=1e-10) + + +import json + + +class TestManagedResponsesWSFirstMessage: + @pytest.mark.asyncio + async def test_first_message_processed_before_loop(self): + """ + ManagedResponsesWebSocketHandler must process first_message before + entering its receive loop. Regression for clients that connect without + ?model= (e.g. Codex) and send model inside the first response.create event. + """ + from litellm.responses.streaming_iterator import ManagedResponsesWebSocketHandler + + first = json.dumps( + { + "type": "response.create", + "model": "gpt-4o-mini", + "store": False, + "input": [ + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "hi"}], + } + ], + } + ) + + ws = MagicMock() + ws.receive_text = AsyncMock(side_effect=Exception("disconnect")) + ws.send_text = AsyncMock() + + processed: list = [] + + async def fake_process(msg: str) -> None: + processed.append(msg) + + handler = ManagedResponsesWebSocketHandler( + websocket=ws, + model="gpt-4o-mini", + logging_obj=MagicMock(), + first_message=first, + ) + handler._process_response_create = fake_process # type: ignore[method-assign] + + await handler.run() + + assert processed == [first] + + @pytest.mark.asyncio + async def test_no_first_message_falls_through_to_loop(self): + """When first_message is None, run() goes straight to receive_text().""" + from litellm.responses.streaming_iterator import ManagedResponsesWebSocketHandler + + subsequent = json.dumps({"type": "response.create", "model": "gpt-4o-mini"}) + + ws = MagicMock() + ws.receive_text = AsyncMock(side_effect=[subsequent, Exception("disconnect")]) + ws.send_text = AsyncMock() + + processed: list = [] + + async def fake_process(msg: str) -> None: + processed.append(msg) + + handler = ManagedResponsesWebSocketHandler( + websocket=ws, + model="gpt-4o-mini", + logging_obj=MagicMock(), + first_message=None, + ) + handler._process_response_create = fake_process # type: ignore[method-assign] + + await handler.run() + + assert processed == [subsequent] + + +class TestResponsesWSStreamingFirstMessage: + @pytest.mark.asyncio + async def test_client_to_backend_replays_first_message(self): + """ + ResponsesWebSocketStreaming.client_to_backend must send first_message to + the backend before entering the receive loop. + """ + from litellm.responses.streaming_iterator import ResponsesWebSocketStreaming + + first = json.dumps({"type": "response.create", "model": "gpt-4o-mini", "input": []}) + + ws = MagicMock() + ws.receive_text = AsyncMock(side_effect=Exception("disconnect")) + + backend_ws = MagicMock() + backend_ws.send = AsyncMock() + + streaming = ResponsesWebSocketStreaming( + websocket=ws, + backend_ws=backend_ws, + logging_obj=MagicMock(), + first_message=first, + ) + + await streaming.client_to_backend() + + backend_ws.send.assert_awaited_once_with(first) + + +class TestWSSessionCostTracking: + @pytest.mark.asyncio + async def test_router_budget_limiter_skips_aresponses_websocket_call_type(self): + """ + RouterBudgetLimiting.async_log_success_event must not raise when + call_type='_aresponses_websocket', even when standard_logging_object is None. + Per-turn costs are tracked by individual aresponses calls inside the session; + the outer session wrapper fires with result=None. + """ + from litellm.router_strategy.budget_limiter import RouterBudgetLimiting + + limiter = RouterBudgetLimiting.__new__(RouterBudgetLimiting) + kwargs = { + "call_type": "_aresponses_websocket", + "standard_logging_object": None, + "litellm_params": {"custom_llm_provider": "vertex_ai"}, + } + await limiter.async_log_success_event( + kwargs=kwargs, + response_obj=None, + start_time=None, + end_time=None, + ) + + @pytest.mark.asyncio + async def test_router_budget_limiter_skips_arealtime_call_type(self): + """Same guard applies to _arealtime WS session wrappers.""" + from litellm.router_strategy.budget_limiter import RouterBudgetLimiting + + limiter = RouterBudgetLimiting.__new__(RouterBudgetLimiting) + kwargs = { + "call_type": "_arealtime", + "standard_logging_object": None, + "litellm_params": {"custom_llm_provider": "openai"}, + } + await limiter.async_log_success_event( + kwargs=kwargs, + response_obj=None, + start_time=None, + end_time=None, + ) + + +class TestWSModelExtraction: + """Test _extract_model_from_first_ws_event for flat and nested frame formats.""" + + def test_flat_format_extracts_model(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _extract_model_from_first_ws_event, + ) + event = {"type": "response.create", "model": "gpt-4o", "input": "hello"} + assert _extract_model_from_first_ws_event(event) == "gpt-4o" + + def test_nested_format_extracts_model(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _extract_model_from_first_ws_event, + ) + event = {"type": "response.create", "response": {"model": "gpt-4o", "input": "hello"}} + assert _extract_model_from_first_ws_event(event) == "gpt-4o" + + def test_nested_format_takes_precedence_over_flat(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _extract_model_from_first_ws_event, + ) + event = { + "type": "response.create", + "model": "flat-model", + "response": {"model": "nested-model"}, + } + assert _extract_model_from_first_ws_event(event) == "nested-model" + + def test_no_model_returns_none(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _extract_model_from_first_ws_event, + ) + event = {"type": "response.create", "input": "hello"} + assert _extract_model_from_first_ws_event(event) is None + + def test_non_object_returns_none(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _extract_model_from_first_ws_event, + ) + + assert _extract_model_from_first_ws_event([]) is None + + +class TestResponsesWSFirstFrameValidation: + @pytest.mark.asyncio + async def test_rejects_non_response_create_first_frame(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock( + return_value=json.dumps({"type": "session.update", "model": "gpt-4o"}) + ) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + ws.send_text.assert_awaited_once() + ws.close.assert_awaited_once_with(code=1008, reason="Invalid first message") + error_payload = json.loads(ws.send_text.await_args.args[0]) + assert ( + error_payload["error"]["message"] + == "First message must be a response.create JSON object." + ) + + @pytest.mark.asyncio + async def test_rejects_non_object_json_first_frame(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock(return_value=json.dumps(["gpt-4o"])) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + ws.send_text.assert_awaited_once() + ws.close.assert_awaited_once_with(code=1008, reason="Invalid first message") + + @pytest.mark.asyncio + async def test_client_disconnect_first_frame_does_not_close(self): + from fastapi import WebSocketDisconnect + + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock(side_effect=WebSocketDisconnect(code=1006)) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + ws.close.assert_not_awaited() + ws.send_text.assert_not_awaited() + + @pytest.mark.asyncio + async def test_server_error_first_frame_closes_with_internal_error(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock(side_effect=RuntimeError("boom")) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + ws.close.assert_awaited_once_with(code=1011, reason="Internal server error") + + +class TestResponsesWSFirstFrameModelAuth: + @pytest.mark.asyncio + async def test_endpoint_enforces_auth_after_model_from_first_frame(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + responses_websocket_endpoint, + ) + + ws = MagicMock() + ws.headers = {} + ws.query_params = {} + ws.scope = {"headers": []} + ws.url = "ws://testserver/v1/responses" + ws.accept = AsyncMock() + ws.receive_text = AsyncMock( + return_value=json.dumps( + {"type": "response.create", "model": "gpt-4o-mini", "input": []} + ) + ) + ws.close = AsyncMock() + + processor = MagicMock() + processor.common_processing_pre_call_logic = AsyncMock( + return_value=({"model": "gpt-4o-mini"}, MagicMock()) + ) + + async def fake_llm_call(): + return None + + with ( + patch( + "litellm.proxy.response_api_endpoints.endpoints._enforce_responses_ws_first_frame_model_auth", + new_callable=AsyncMock, + ) as mock_model_auth, + patch( + "litellm.proxy.response_api_endpoints.endpoints.ProxyBaseLLMRequestProcessing", + return_value=processor, + ), + patch( + "litellm.proxy.route_llm_request.route_request", + new_callable=AsyncMock, + return_value=fake_llm_call(), + ), + ): + await responses_websocket_endpoint( + websocket=ws, + model=None, + user_api_key_dict=MagicMock(), + ) + + mock_model_auth.assert_awaited_once() + + @pytest.mark.asyncio + async def test_reruns_model_auth_for_first_frame_model(self): + from starlette.requests import Request + + from litellm.proxy.response_api_endpoints.endpoints import ( + _enforce_responses_ws_first_frame_model_auth, + ) + + request = Request( + {"type": "http", "method": "POST", "path": "/v1/responses", "headers": []} + ) + user_api_key_dict = MagicMock() + llm_router = MagicMock() + + with ( + patch( + "litellm.proxy.auth.user_api_key_auth._enforce_key_and_fallback_model_access", + new_callable=AsyncMock, + ) as mock_key_check, + patch( + "litellm.proxy.auth.user_api_key_auth._run_centralized_common_checks", + new_callable=AsyncMock, + ) as mock_common_checks, + patch( + "litellm.proxy.proxy_server.llm_model_list", + [], + ), + patch("litellm.proxy.proxy_server.master_key", "sk-test"), + patch("litellm.proxy.proxy_server.user_custom_auth", None), + patch("litellm.proxy.proxy_server.general_settings", {}), + ): + await _enforce_responses_ws_first_frame_model_auth( + request=request, + model="gpt-4o-mini", + user_api_key_dict=user_api_key_dict, + llm_router=llm_router, + ) + + mock_key_check.assert_awaited_once_with( + valid_token=user_api_key_dict, + request_data={"model": "gpt-4o-mini"}, + route="/v1/responses", + request=request, + llm_model_list=[], + llm_router=llm_router, + ) + mock_common_checks.assert_awaited_once_with( + user_api_key_auth_obj=user_api_key_dict, + request=request, + request_data={"model": "gpt-4o-mini"}, + route="/v1/responses", + ) + + +class TestReadWSModelFromFirstFrameErrors: + @pytest.mark.asyncio + async def test_timeout_closes_without_error_frame(self): + import asyncio + + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock(side_effect=asyncio.TimeoutError()) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + ws.send_text.assert_not_awaited() + ws.close.assert_awaited_once_with( + code=1008, reason="Timed out waiting for first message" + ) + + @pytest.mark.asyncio + async def test_invalid_json_sends_error_and_closes(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock(return_value="this is not json") + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + payload = json.loads(ws.send_text.await_args.args[0]) + assert payload["error"]["message"] == "First message is not valid JSON." + ws.close.assert_awaited_once_with( + code=1008, reason="Invalid JSON in first message" + ) + + @pytest.mark.asyncio + async def test_missing_model_sends_error_and_closes(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + ws = MagicMock() + ws.receive_text = AsyncMock( + return_value=json.dumps({"type": "response.create", "input": []}) + ) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result is None + payload = json.loads(ws.send_text.await_args.args[0]) + assert "No model provided" in payload["error"]["message"] + ws.close.assert_awaited_once_with(code=1008, reason="No model provided") + + @pytest.mark.asyncio + async def test_valid_first_frame_returns_model_and_raw(self): + from litellm.proxy.response_api_endpoints.endpoints import ( + _read_ws_model_from_first_frame, + ) + + raw = json.dumps({"type": "response.create", "model": "gpt-4o", "input": []}) + ws = MagicMock() + ws.receive_text = AsyncMock(return_value=raw) + ws.send_text = AsyncMock() + ws.close = AsyncMock() + + result = await _read_ws_model_from_first_frame(ws) + + assert result == ("gpt-4o", raw) + ws.send_text.assert_not_awaited() + ws.close.assert_not_awaited() + + +class TestManagedResponsesSameProvider: + def _handler(self, model, custom_llm_provider=None): + from litellm.responses.streaming_iterator import ( + ManagedResponsesWebSocketHandler, + ) + + return ManagedResponsesWebSocketHandler( + websocket=MagicMock(), + model=model, + logging_obj=MagicMock(), + custom_llm_provider=custom_llm_provider, + ) + + def test_none_model_treated_as_same_provider(self): + assert self._handler("openai/gpt-4o")._same_provider(None) is True + + def test_identical_model_is_same_provider(self): + assert self._handler("openai/gpt-4o")._same_provider("openai/gpt-4o") is True + + def test_same_provider_different_model(self): + assert self._handler("gpt-4o")._same_provider("gpt-4o-mini") is True + + def test_different_provider_is_not_same(self): + assert ( + self._handler("gpt-4o")._same_provider("vertex_ai/gemini-2.0-flash") + is False + ) + + def test_inject_credentials_keeps_provider_for_same_provider_model(self): + handler = self._handler("gpt-4o", custom_llm_provider="openai") + call_kwargs: dict = {} + handler._inject_credentials(call_kwargs, model="gpt-4o-mini") + assert call_kwargs["custom_llm_provider"] == "openai" + + def test_inject_credentials_drops_provider_for_cross_provider_model(self): + handler = self._handler("gpt-4o", custom_llm_provider="openai") + call_kwargs: dict = {} + handler._inject_credentials(call_kwargs, model="vertex_ai/gemini-2.0-flash") + assert "custom_llm_provider" not in call_kwargs + + def test_unresolvable_connection_model_falls_back_to_custom_provider(self): + handler = self._handler( + "my-custom-deployment", custom_llm_provider="openai" + ) + assert handler._same_provider("gpt-4o-mini") is True + call_kwargs: dict = {} + handler._inject_credentials(call_kwargs, model="gpt-4o-mini") + assert call_kwargs["custom_llm_provider"] == "openai" + + def test_unresolvable_connection_model_still_drops_cross_provider(self): + handler = self._handler( + "my-custom-deployment", custom_llm_provider="openai" + ) + call_kwargs: dict = {} + handler._inject_credentials(call_kwargs, model="vertex_ai/gemini-2.0-flash") + assert "custom_llm_provider" not in call_kwargs diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py index e9287a95438..cd235d8de67 100644 --- a/tests/test_litellm/test_router.py +++ b/tests/test_litellm/test_router.py @@ -982,6 +982,61 @@ async def test_router_ageneric_api_call_with_fallbacks_helper(): assert router.fail_calls["gpt-3.5-turbo"] == initial_fail_count + 1 +@pytest.mark.asyncio +async def test_ageneric_api_call_deployment_model_overrides_alias(): + """ + Regression: when a model alias (e.g. "not-gemini-2.5-flash") maps to a deployment + with model="vertex_ai/gemini-2.5-flash", the underlying litellm function must receive + the deployment model, not the alias. Before the fix, **kwargs overwrote data["model"]. + """ + from unittest.mock import patch + + captured: dict = {} + + async def capture_model(**kwargs): + captured["model"] = kwargs.get("model") + return {"result": "ok"} + + router = litellm.Router( + model_list=[ + { + "model_name": "not-gemini-2.5-flash", + "litellm_params": { + "model": "vertex_ai/gemini-2.5-flash", + "api_key": "fake-key", + }, + } + ] + ) + + def inject_alias_into_kwargs(deployment, kwargs, function_name=None): + # Simulate the alias leaking into kwargs (as happens when + # _ageneric_api_call_with_fallbacks sets kwargs["model"] = alias before + # calling the helper through async_function_with_fallbacks). + kwargs["model"] = "not-gemini-2.5-flash" + + with patch.object(router, "async_get_available_deployment") as mock_dep, \ + patch.object(router, "_update_kwargs_with_deployment", side_effect=inject_alias_into_kwargs), \ + patch.object(router, "async_routing_strategy_pre_call_checks"), \ + patch.object(router, "_get_client", return_value=None): + mock_dep.return_value = { + "model_name": "not-gemini-2.5-flash", + "litellm_params": { + "model": "vertex_ai/gemini-2.5-flash", + "api_key": "fake-key", + }, + } + + await router._ageneric_api_call_with_fallbacks_helper( + model="not-gemini-2.5-flash", + original_generic_function=capture_model, + ) + + assert captured["model"] == "vertex_ai/gemini-2.5-flash", ( + f"Expected deployment model 'vertex_ai/gemini-2.5-flash', got '{captured['model']}'" + ) + + def test_router_get_model_access_groups_team_only_models(): """ Test that Router.get_model_access_groups returns the correct response for team-only models From 5119b9462f96482a10572bd0d6ade3c552b0556f Mon Sep 17 00:00:00 2001 From: milan-berri Date: Wed, 3 Jun 2026 22:09:50 +0300 Subject: [PATCH 16/92] =?UTF-8?q?feat(arize/phoenix):=20OpenInference=20re?= =?UTF-8?q?ndering=20parity=20=E2=80=94=20tool=5Fcalls,=20cost,=20passthro?= =?UTF-8?q?ugh=20I/O,=20session/user,=20multimodal,=20cache=20tokens=20(#2?= =?UTF-8?q?8800)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * feat(arize): enrich OpenInference attributes for better span rendering Pure rendering enhancements to the Arize / Arize Phoenix integration. No existing attribute keys or values are removed or overwritten; every new emit is independently try/except-wrapped and fires only when its source data is present so existing behavior is preserved. What this adds - Coerce non-dict response objects (e.g. httpx.Response from passthrough routes) via JSON decode so id/model/usage extraction stops crashing with "'Response' object has no attribute 'get'". Dicts and Pydantic objects with .get pass through unchanged. - Set OPENINFERENCE_SPAN_KIND defensively early so a downstream failure can't blank the kind; the original late write (incl. TOOL upgrade) is preserved. - Add "passthrough" keyword to _infer_open_inference_span_kind so allm_passthrough_route / llm_passthrough_route resolve to LLM instead of UNKNOWN. - Emit cache token breakdown: LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ / _CACHE_WRITE / _AUDIO. Sources covered: OpenAI prompt_tokens_details and Anthropic / Bedrock cache_{read,creation}_input_tokens. - Render assistant tool_calls on both input and output messages via MESSAGE_TOOL_CALLS.* (Pydantic-aware, handles ModelResponse choices). Tool-result input messages also get MESSAGE_TOOL_CALL_ID and MESSAGE_NAME. - Render multimodal list-shaped content via MESSAGE_CONTENTS.* (OpenAI image_url, Anthropic source.{media_type,data} as data: URI). Legacy MESSAGE_CONTENT write is unchanged. - Emit SESSION_ID (end_user_id / trace_id), USER_ID (only when not already set by optional_params.user or model_params.user), and litellm.{team_id,team_alias,key_alias} from StandardLoggingPayload metadata. - Emit llm.response.cost as float from StandardLoggingPayload.response_cost. - Bedrock / Anthropic passthrough normalization: extract input from additional_args.complete_input_dict and output from the coerced provider response so INPUT_VALUE / OUTPUT_VALUE / LLM_INPUT_MESSAGES / LLM_OUTPUT_MESSAGES are populated. Only runs when call_type contains "passthrough" / "pass_through". Tests - 15 new unit tests covering each addition plus explicit regression guards (USER_ID overwrite protection, passthrough normalizer scope, coerce identity for dicts/.get-bearing objects, no spurious cache emits). - Existing test_arize_set_attributes count bumped from 26 to 27 to account for the additional defensive span.kind write (same value, written twice). - tests/test_litellm/integrations/arize/: 70 passed (55 baseline + 15 new). tests/test_litellm/integrations/test_opentelemetry.py: 221 passed. Co-authored-by: Cursor * refactor(arize): collapse additive try/except blocks into _safe_emit helper The additive attribute emitters all share the same shape: run a callable, swallow any exception to debug log so it cannot blank the span. Hoisting that pattern into a single _safe_emit(label, fn, *args, **kwargs) helper removes 5 repeated try/except blocks. Behavior unchanged; arize test suite still passes (70/70). Co-authored-by: Cursor * fix(arize): emit cost under canonical llm.cost.total key Arize's "Total Cost" column reads the OpenInference-standard `llm.cost.total` attribute. The previous custom `llm.response.cost` key never surfaced in the trace list. Now emits both keys (canonical + legacy) so renderers + any existing consumers both work. Co-authored-by: Cursor * fix(arize): keep span.kind=LLM for tool-using completions + render tool_calls in Output A chat completion that passes `tools=[...]` or returns `tool_calls` is still an LLM call per the OpenInference spec — TOOL is reserved for actual tool execution. The previous override demoted these to TOOL, breaking Arize's LLM-scoped dashboards/evals and skewing token/cost analytics for any tool-using traffic. Additionally, when an assistant response had no text content but did request tool calls, `output.value` was set to the empty string so Arize's "Output" pane rendered blank. Now serializes the tool_calls into a compact JSON summary in `output.value` (the structured `MESSAGE_TOOL_CALLS.*` attributes are still emitted unchanged). Cleanups: - extract `_get_tool_calls` and `_normalize_tool_call` helpers, deduplicating the dict-vs-Pydantic + function-dict logic across `_set_choice_outputs`, `_emit_message_tool_calls`, and the new `_summarize_tool_calls_for_output`. - drop redundant late `OPENINFERENCE_SPAN_KIND` write — the defensive early write is now the single source of truth. - remove a dead local re-import of `MessageAttributes`/`SpanAttributes`. Tests: 73 pass (added regression guard asserting span.kind stays LLM for completions that pass tools AND return tool_calls; existing call_count assertion restored to 26). Co-authored-by: Cursor * chore(arize): tighten cleanup — fold _get_tool_calls into _safe_get Two tiny cleanups, no behavior change: - collapse `_get_tool_calls` to use `_safe_get`, removing a 7-line hand-rolled dict-vs-attribute fallback that duplicated existing logic. - trim the `_set_choice_outputs` tool-call summary comment from 4 lines to 2 (was over-explaining). Co-authored-by: Cursor * fix(arize): address Greptile review — drop session_id=trace_id fallback, remove dead code, fix Black Three Greptile-flagged issues + the Black formatting CI failure. 1. SESSION_ID no longer falls back to trace_id. Previously every span without an explicit `user_api_key_end_user_id` would have its session.id set to the per-request trace_id, which creates one distinct "session" per request and breaks Arize's Session-grouping analytics. Now SESSION_ID is emitted only when an explicit end-user identifier exists, and the trace_id is emitted under its own `litellm.trace_id` key so spans remain filterable by trace. 2. Removed dead `ArizeOTELAttributes.set_response_output_messages` override. Confirmed zero callers in the entire repo (the live path is `_set_choice_outputs` via `_set_response_attributes`). The override was preexisting dead code, but the expansion of `_set_choice_outputs` in this PR made the divergence misleading. 3. Removed permanently-dead first branch in cache_write detection. `_safe_get(prompt_token_details, "cache_creation_tokens")` looks for a key that neither OpenAI's `prompt_tokens_details` nor Anthropic's payload ever exposes. Now reads straight off `usage` for `cache_creation_input_tokens`. 4. Reformatted both files under Black 26.3.1 (the version CI uses via `uv sync --frozen`). Local previously used 24.10.0. Tests: 74/74 pass in the arize suite (added `test_arize_does_not_use_trace_id_as_session_id_fallback`). Combined arize + opentelemetry suite: 295/295 pass. End-to-end verified live: tool-call still emits `span.kind=LLM` and JSON tool_calls in `output.value`; `session.id` is now correctly unset when no end_user_id is provided; `litellm.trace_id` is populated; Bedrock passthrough input/output unchanged. Co-authored-by: Cursor * fix(arize): gate passthrough prompt export on message redaction - Skip the complete_input_dict bridge in _maybe_normalize_passthrough when should_redact_message_logging() is true, so enabling redaction no longer leaks raw passthrough prompts into Arize (Veria security finding). - Split passthrough input/output rendering into helpers to satisfy PLR0915. - Remove dead call_type assignment (F841). Validated live against a Bedrock passthrough proxy exporting to Arize: non-redacted renders the real prompt on litellm_request; global turn_off_message_logging yields input.value=redacted-by-litellm with the raw_gen_ai_request child span suppressed and no SSN/marker leakage. Co-authored-by: Cursor --------- Co-authored-by: Cursor --- litellm/integrations/arize/_utils.py | 702 ++++++++++++++-- .../integrations/arize/test_arize_utils.py | 748 +++++++++++++++++- 2 files changed, 1395 insertions(+), 55 deletions(-) diff --git a/litellm/integrations/arize/_utils.py b/litellm/integrations/arize/_utils.py index a1bf65141c9..75710e10498 100644 --- a/litellm/integrations/arize/_utils.py +++ b/litellm/integrations/arize/_utils.py @@ -8,18 +8,23 @@ from litellm.integrations.opentelemetry_utils.base_otel_llm_obs_attributes impor BaseLLMObsOTELAttributes, safe_set_attribute, ) +from litellm.litellm_core_utils.redact_messages import ( + should_redact_message_logging, +) from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.types.utils import StandardLoggingPayload if TYPE_CHECKING: from opentelemetry.trace import Span from litellm.integrations._types.open_inference import ( - MessageAttributes, - ImageAttributes, - SpanAttributes, AudioAttributes, EmbeddingAttributes, + ImageAttributes, + MessageAttributes, + MessageContentAttributes, OpenInferenceSpanKindValues, + SpanAttributes, + ToolCallAttributes, ) @@ -53,40 +58,24 @@ class ArizeOTELAttributes(BaseLLMObsOTELAttributes): msg.get("content", ""), ) - @staticmethod - @override - def set_response_output_messages(span: "Span", response_obj): - """ - Sets output message attributes on the span from the LLM response. - Args: - span: The OpenTelemetry span to set attributes on - response_obj: The response object containing choices with messages - """ - from litellm.integrations._types.open_inference import ( - MessageAttributes, - SpanAttributes, - ) + # Additive: emit structured tool_calls / multimodal content + # so Arize/Phoenix can render tool-using and image-bearing + # turns. These set NEW attribute keys (MESSAGE_TOOL_CALLS / + # MESSAGE_NAME / MESSAGE_TOOL_CALL_ID / MESSAGE_CONTENTS.*) — + # never replace the MESSAGE_CONTENT write above. + _safe_emit( + f"input message extras (idx={idx})", + _emit_input_message_extras, + span, + prefix, + msg, + ) - for idx, choice in enumerate(response_obj.get("choices", [])): - response_message = choice.get("message", {}) - safe_set_attribute( - span, - SpanAttributes.OUTPUT_VALUE, - response_message.get("content", ""), - ) - - # This shows up under `output_messages` tab on the span page. - prefix = f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.{idx}" - safe_set_attribute( - span, - f"{prefix}.{MessageAttributes.MESSAGE_ROLE}", - response_message.get("role"), - ) - safe_set_attribute( - span, - f"{prefix}.{MessageAttributes.MESSAGE_CONTENT}", - response_message.get("content", ""), - ) + # Note: `BaseLLMObsOTELAttributes.set_response_output_messages` is not + # overridden here. The live code path uses `_set_choice_outputs` (called + # via `_set_response_attributes` from `set_attributes`) which handles + # tool_calls, multimodal output, embeddings, audio, images, and structured + # outputs in a single place. def _set_response_attributes(span: "Span", response_obj): @@ -106,11 +95,17 @@ def _set_response_attributes(span: "Span", response_obj): def _set_choice_outputs(span: "Span", response_obj, msg_attrs, span_attrs): for idx, choice in enumerate(response_obj.get("choices", [])): response_message = choice.get("message", {}) - safe_set_attribute( - span, - span_attrs.OUTPUT_VALUE, - response_message.get("content", ""), - ) + content = response_message.get("content", "") + + # Tool-only assistant responses have empty content; serialize the + # tool_calls into OUTPUT_VALUE so Arize's "Output" pane isn't blank. + output_value = content + if not output_value: + tool_calls = _get_tool_calls(response_message) + if tool_calls: + output_value = _summarize_tool_calls_for_output(tool_calls) + + safe_set_attribute(span, span_attrs.OUTPUT_VALUE, output_value) prefix = f"{span_attrs.LLM_OUTPUT_MESSAGES}.{idx}" safe_set_attribute( span, @@ -120,7 +115,18 @@ def _set_choice_outputs(span: "Span", response_obj, msg_attrs, span_attrs): safe_set_attribute( span, f"{prefix}.{msg_attrs.MESSAGE_CONTENT}", - response_message.get("content", ""), + content, + ) + + # Additive: emit assistant tool_calls so tool-using turns render in + # Arize/Phoenix. Sets new MESSAGE_TOOL_CALLS keys only — does not + # change MESSAGE_CONTENT/MESSAGE_ROLE writes above. + _safe_emit( + f"output tool_calls (idx={idx})", + _emit_message_tool_calls, + span, + prefix, + response_message, ) @@ -278,6 +284,43 @@ def _set_usage_outputs(span: "Span", response_obj, span_attrs): reasoning_tokens, ) + # Additive: cache token breakdown so prompt-caching savings render in + # Arize. Sources covered: + # - OpenAI Chat Completions: `prompt_tokens_details.cached_tokens` + # - Anthropic / Bedrock-Anthropic: `cache_read_input_tokens`, + # `cache_creation_input_tokens` + # All emits are conditional, so when none of these fields exist (the + # situation in the existing test fixtures) no extra attributes are set. + prompt_token_details = _safe_get(usage, "prompt_tokens_details") or _safe_get( + usage, "input_tokens_details" + ) + cache_read = _safe_get(prompt_token_details, "cached_tokens") or _safe_get( + usage, "cache_read_input_tokens" + ) + if cache_read: + safe_set_attribute( + span, + span_attrs.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ, + cache_read, + ) + # Anthropic / Bedrock-Anthropic only — OpenAI's `prompt_tokens_details` + # does not expose a cache-write count, so we read straight off `usage`. + cache_write = _safe_get(usage, "cache_creation_input_tokens") + if cache_write: + safe_set_attribute( + span, + span_attrs.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_WRITE, + cache_write, + ) + + audio_prompt_tokens = _safe_get(prompt_token_details, "audio_tokens") + if audio_prompt_tokens: + safe_set_attribute( + span, + span_attrs.LLM_TOKEN_COUNT_PROMPT_DETAILS_AUDIO, + audio_prompt_tokens, + ) + def _infer_open_inference_span_kind(call_type: Optional[str]) -> str: """ @@ -321,6 +364,10 @@ def _infer_open_inference_span_kind(call_type: Optional[str]) -> str: "videos", "realtime", "pass_through", + # `passthrough` (no underscore) is what real call_types use: + # `allm_passthrough_route`, `llm_passthrough_route`. Without + # this they fell through to UNKNOWN, blanking span.kind. + "passthrough", "anthropic_messages", "ocr", ) @@ -396,6 +443,18 @@ def set_attributes( """ Populates span with OpenInference-compliant LLM attributes for Arize and Phoenix tracing. """ + # Coerce non-dict response objects (e.g. httpx.Response from passthrough + # routes) into a dict so downstream `.get()` calls don't crash. Existing + # dict / `.get()`-bearing objects (incl. Pydantic OpenAI Responses API + # models) are returned unchanged, preserving the existing test behavior. + response_obj_for_attrs = _coerce_response_obj_for_attrs(response_obj) + + # Set span.kind defensively before anything else. If a downstream step + # throws, the span still has a kind so Arize can render it correctly + # (an LLM call instead of UNKNOWN). This is the single source of truth + # for span.kind — no late re-write happens below. + _safe_emit("early span kind", _set_early_span_kind, span, kwargs) + try: optional_params = _sanitize_optional_params(kwargs.get("optional_params")) litellm_params = kwargs.get("litellm_params", {}) or {} @@ -415,25 +474,22 @@ def set_attributes( metadata_tools = _extract_metadata_tools(metadata) optional_tools = _extract_optional_tools(optional_params) - call_type = standard_logging_payload.get("call_type") _set_request_attributes( span=span, kwargs=kwargs, standard_logging_payload=standard_logging_payload, optional_params=optional_params, litellm_params=litellm_params, - response_obj=response_obj, + response_obj=response_obj_for_attrs, span_attrs=SpanAttributes, ) - span_kind = _infer_open_inference_span_kind(call_type=call_type) + # span.kind was already set above by `_set_early_span_kind`. We do + # NOT re-write it here based on tool presence: a chat completion + # that passes `tools=[...]` (or returns `tool_calls`) is still an + # LLM call per the OpenInference spec — TOOL is reserved for actual + # tool execution spans, not LLM calls that request tools. _set_tool_attributes(span, optional_tools, metadata_tools) - if ( - optional_tools or metadata_tools - ) and span_kind != OpenInferenceSpanKindValues.TOOL.value: - span_kind = OpenInferenceSpanKindValues.TOOL.value - - safe_set_attribute(span, SpanAttributes.OPENINFERENCE_SPAN_KIND, span_kind) attributes.set_messages(span, kwargs) model_params = ( @@ -443,7 +499,7 @@ def set_attributes( ) _set_model_params(span, model_params, SpanAttributes) - _set_response_attributes(span=span, response_obj=response_obj) + _set_response_attributes(span=span, response_obj=response_obj_for_attrs) except Exception as e: verbose_logger.error( @@ -452,6 +508,22 @@ def set_attributes( if hasattr(span, "record_exception"): span.record_exception(e) + # Additive emitters. Each is independently guarded so a failure can never + # blank the attributes set by the main try-block above. New attributes are + # written under new keys; existing attributes are not overwritten. + slp = kwargs.get("standard_logging_object") + _safe_emit("session/user attrs", _set_session_and_user_attrs, span, kwargs, slp) + _safe_emit("response cost", _set_response_cost_attr, span, slp) + _safe_emit( + "passthrough normalization", + _maybe_normalize_passthrough, + span, + kwargs, + response_obj, + response_obj_for_attrs, + slp, + ) + def _sanitize_optional_params(optional_params: Optional[dict]) -> dict: if not isinstance(optional_params, dict): @@ -534,3 +606,529 @@ def _set_model_params(span: "Span", model_params: Optional[dict], span_attrs) -> user_id = model_params.get("user") if user_id is not None: safe_set_attribute(span, span_attrs.USER_ID, user_id) + + +# --------------------------------------------------------------------------- +# Additive rendering helpers (introduced to enhance Arize/Phoenix rendering +# without changing any previously-emitted attribute keys or values). +# --------------------------------------------------------------------------- + + +def _safe_emit(label: str, fn, *args, **kwargs) -> None: + """Run an additive attribute emitter, swallowing any error so it cannot + blank attributes set elsewhere on the span. Failures are logged at debug. + """ + try: + fn(*args, **kwargs) + except Exception as e: + verbose_logger.debug("[Arize] %s skipped: %s", label, e) + + +def _set_early_span_kind(span: "Span", kwargs: dict) -> None: + """Defensively set OPENINFERENCE_SPAN_KIND before any other logic runs.""" + slp = kwargs.get("standard_logging_object") + call_type = slp.get("call_type") if isinstance(slp, dict) else None + safe_set_attribute( + span, + SpanAttributes.OPENINFERENCE_SPAN_KIND, + _infer_open_inference_span_kind(call_type=call_type), + ) + + +def _coerce_response_obj_for_attrs(response_obj): + """Return a `.get`-compatible view of `response_obj` when possible. + + - dicts and Pydantic models that already expose `.get` are returned + unchanged (preserves all current behavior, including the Responses API + flow which relies on Pydantic attribute access). + - `httpx.Response` and other text-only responses (passthrough routes) + are JSON-decoded so the standard extraction paths can read fields like + `id`, `model`, and `usage`. On failure the original object is returned + so behavior is no worse than today. + """ + if response_obj is None or hasattr(response_obj, "get"): + return response_obj + text = getattr(response_obj, "text", None) + if isinstance(text, str) and text: + try: + parsed = json.loads(text) + if isinstance(parsed, dict): + return parsed + except Exception: + pass + return response_obj + + +def _coerce_text(value) -> Optional[str]: + """Best-effort text extraction from a message-content value. + + Returns None when no textual portion can be derived. Handles: + - plain strings + - lists of OpenAI-style content parts (`{"type": "text", "text": ...}`) + - lists of Anthropic-style content parts (`{"type": "text", "text": ...}` + or `{"type": "input_text", "text": ...}`) + """ + if value is None: + return None + if isinstance(value, str): + return value + if isinstance(value, list): + parts = [] + for part in value: + if isinstance(part, str): + parts.append(part) + elif isinstance(part, dict): + text = part.get("text") or part.get("input_text") + if isinstance(text, str): + parts.append(text) + if parts: + return "\n".join(parts) + return None + + +def _to_plain_dict(value): + """Best-effort: coerce a value (Pydantic model / dict / None) to a dict. + + Returns the original value when no safe conversion exists. Used to bridge + OpenAI Pydantic message/tool_call objects into the dict-based helpers. + """ + if value is None or isinstance(value, dict): + return value + model_dump = getattr(value, "model_dump", None) + if callable(model_dump): + try: + return model_dump() + except Exception: + pass + return value + + +def _get_tool_calls(message) -> Optional[list]: + """Return ``message.tool_calls`` only when it's a non-empty list. + + Works for dicts and Pydantic message objects via ``_safe_get``. + """ + tool_calls = _safe_get(message, "tool_calls") + return tool_calls if isinstance(tool_calls, list) and tool_calls else None + + +def _normalize_tool_call(raw_tc) -> Optional[Dict[str, Any]]: + """Normalize a single tool_call (dict or Pydantic) into a stable shape: + + {"id": str|None, "type": str, "function": {"name": str|None, "arguments": str|None}} + + Arguments are coerced to a JSON string per OpenInference convention. + Returns ``None`` when ``raw_tc`` cannot be coerced to a dict. + """ + tc = _to_plain_dict(raw_tc) + if not isinstance(tc, dict): + return None + function = _to_plain_dict(tc.get("function")) + name = function.get("name") if isinstance(function, dict) else None + args = function.get("arguments") if isinstance(function, dict) else None + if args is not None and not isinstance(args, str): + try: + args = json.dumps(args) + except Exception: + args = str(args) + return { + "id": tc.get("id"), + "type": tc.get("type", "function"), + "function": {"name": name, "arguments": args}, + } + + +def _summarize_tool_calls_for_output(tool_calls) -> str: + """Render a tool_calls list as a compact JSON string for OUTPUT_VALUE. + + Best-effort: returns ``str(tool_calls)`` if anything unexpected happens + so OUTPUT_VALUE is never blanked on a malformed payload. + """ + try: + normalized = [n for n in (_normalize_tool_call(tc) for tc in tool_calls) if n] + return json.dumps({"tool_calls": normalized}) + except Exception: + return str(tool_calls) + + +def _emit_message_tool_calls(span: "Span", prefix: str, message) -> None: + """Emit ``MESSAGE_TOOL_CALLS.*`` for an assistant message that requested + tool calls. Pure addition: only writes when ``tool_calls`` is non-empty. + + Accepts dicts or Pydantic message objects (e.g. ``litellm.Message``); the + same applies to each tool_call entry. + """ + tool_calls = _get_tool_calls(message) + if not tool_calls: + return + for tc_idx, raw_tc in enumerate(tool_calls): + tc = _normalize_tool_call(raw_tc) + if tc is None: + continue + tc_prefix = f"{prefix}.{MessageAttributes.MESSAGE_TOOL_CALLS}.{tc_idx}" + if tc["id"]: + safe_set_attribute( + span, f"{tc_prefix}.{ToolCallAttributes.TOOL_CALL_ID}", tc["id"] + ) + fn = tc["function"] + if fn["name"]: + safe_set_attribute( + span, + f"{tc_prefix}.{ToolCallAttributes.TOOL_CALL_FUNCTION_NAME}", + fn["name"], + ) + if fn["arguments"] is not None: + safe_set_attribute( + span, + f"{tc_prefix}.{ToolCallAttributes.TOOL_CALL_FUNCTION_ARGUMENTS_JSON}", + fn["arguments"], + ) + + +def _emit_input_message_extras(span: "Span", prefix: str, message: dict) -> None: + """Emit additive attributes for an input message: + + - `MESSAGE_NAME` and `MESSAGE_TOOL_CALL_ID` (commonly set on tool-result + messages so traces show which tool produced which result). + - `MESSAGE_TOOL_CALLS.*` when an assistant message requested tools. + - `MESSAGE_CONTENTS.*` structured content for list-shaped content + (multimodal text + image parts). The plain `MESSAGE_CONTENT` write is + still performed by the caller, so renderers that only read the legacy + key continue to work. + """ + if not isinstance(message, dict): + return + + name = message.get("name") + if name: + safe_set_attribute(span, f"{prefix}.{MessageAttributes.MESSAGE_NAME}", name) + + tool_call_id = message.get("tool_call_id") + if tool_call_id: + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_TOOL_CALL_ID}", + tool_call_id, + ) + + _emit_message_tool_calls(span, prefix, message) + + content = message.get("content") + if isinstance(content, list): + contents_prefix = f"{prefix}.{MessageAttributes.MESSAGE_CONTENTS}" + for part_idx, part in enumerate(content): + if not isinstance(part, dict): + continue + part_prefix = f"{contents_prefix}.{part_idx}" + part_type = part.get("type") + if part_type in ("text", "input_text"): + text = part.get("text") + if isinstance(text, str): + safe_set_attribute( + span, + f"{part_prefix}.{MessageContentAttributes.MESSAGE_CONTENT_TYPE}", + "text", + ) + safe_set_attribute( + span, + f"{part_prefix}.{MessageContentAttributes.MESSAGE_CONTENT_TEXT}", + text, + ) + elif part_type in ("image_url", "image", "input_image"): + url = None + image = part.get("image_url") + if isinstance(image, dict): + url = image.get("url") + elif isinstance(image, str): + url = image + if not url: + # Anthropic-style source.{type=base64,media_type,data} + source = part.get("source") + if isinstance(source, dict) and source.get("data"): + media_type = source.get("media_type", "image/jpeg") + url = f"data:{media_type};base64,{source['data']}" + elif isinstance(part.get("url"), str): + url = part["url"] + if url: + safe_set_attribute( + span, + f"{part_prefix}.{MessageContentAttributes.MESSAGE_CONTENT_TYPE}", + "image", + ) + safe_set_attribute( + span, + f"{part_prefix}.message_content.image.image.url", + url, + ) + + +def _set_session_and_user_attrs( + span: "Span", kwargs: dict, standard_logging_payload +) -> None: + """Emit `SESSION_ID` / `USER_ID` / team metadata when source data exists. + + `SESSION_ID` is emitted only when an explicit end-user identifier exists + (`metadata.user_api_key_end_user_id`). We deliberately do NOT fall back + to `trace_id`, because that would create a distinct "session" for every + single request and distort Arize's Session-grouping analytics. The + `trace_id` is still emitted under its own `litellm.trace_id` key so + spans remain filterable by trace. + + USER_ID is *only* emitted when no upstream path (model_params.user or + optional_params.user) has already set it, to avoid overwriting an + existing value with a possibly-different one from API-key metadata. + """ + if not isinstance(standard_logging_payload, dict): + return + metadata = standard_logging_payload.get("metadata") or {} + if not isinstance(metadata, dict): + return + + session_id = metadata.get("user_api_key_end_user_id") + if session_id: + safe_set_attribute(span, SpanAttributes.SESSION_ID, str(session_id)) + + trace_id = standard_logging_payload.get("trace_id") + if trace_id: + safe_set_attribute(span, "litellm.trace_id", str(trace_id)) + + optional_params = kwargs.get("optional_params") or {} + model_params = standard_logging_payload.get("model_parameters") or {} + has_user_already = bool( + (isinstance(optional_params, dict) and optional_params.get("user")) + or (isinstance(model_params, dict) and model_params.get("user")) + ) + if not has_user_already: + user_id = metadata.get("user_api_key_user_id") + if user_id: + safe_set_attribute(span, SpanAttributes.USER_ID, str(user_id)) + + team_id = metadata.get("user_api_key_team_id") + if team_id: + safe_set_attribute(span, "litellm.team_id", str(team_id)) + team_alias = metadata.get("user_api_key_team_alias") + if team_alias: + safe_set_attribute(span, "litellm.team_alias", str(team_alias)) + key_alias = metadata.get("user_api_key_alias") + if key_alias: + safe_set_attribute(span, "litellm.key_alias", str(key_alias)) + + +def _set_response_cost_attr(span: "Span", standard_logging_payload) -> None: + """Emit cost attributes from the StandardLoggingPayload when present. + + Uses the OpenInference `llm.cost.total` key so Arize / Phoenix can + surface the cost in their "Total Cost" column. LiteLLM only tracks a + single total in `StandardLoggingPayload.response_cost`, so we cannot + split it into prompt/completion. We also keep the legacy + `llm.response.cost` key for back-compat with any consumer querying it. + """ + if not isinstance(standard_logging_payload, dict): + return + cost = standard_logging_payload.get("response_cost") + if cost is None: + return + try: + cost_value = float(cost) + except (TypeError, ValueError): + return + safe_set_attribute(span, "llm.cost.total", cost_value) + safe_set_attribute(span, "llm.response.cost", cost_value) + + +def _is_passthrough_call_type(call_type: Optional[str]) -> bool: + if not call_type: + return False + lowered = str(call_type).lower() + return "passthrough" in lowered or "pass_through" in lowered + + +def _maybe_normalize_passthrough( + span: "Span", + kwargs: dict, + raw_response_obj, + coerced_response_obj, + standard_logging_payload, +) -> None: + """Surface input/output text for passthrough routes (e.g. Bedrock + InvokeModel) so the parent span renders as more than `usage` numbers. + + Only runs when `call_type` is a passthrough variant. Reads from: + - `kwargs["additional_args"]["complete_input_dict"]` for input + - the coerced response (or `kwargs["original_response"]`) for output + + All emits are best-effort: if the provider shape isn't recognized the + helper exits silently. Existing chat/completion paths never enter this + helper because their call_type doesn't contain "passthrough". + + TEMPORARY BRIDGE: passthrough handlers don't populate the + StandardLoggingPayload `messages` field today (they call + `transform_response(messages=[])`), so the input is only available via + `additional_args.complete_input_dict`. The proper fix is upstream in + `base_passthrough_logging_handler._create_response_logging_payload()`: + once that populates SLP `messages`/`response`, every callback gets + passthrough I/O (with central redaction) for free and this helper's + `complete_input_dict` fallback can be deleted. See follow-up issue. + """ + call_type = ( + standard_logging_payload.get("call_type") + if isinstance(standard_logging_payload, dict) + else None + ) + if not _is_passthrough_call_type(call_type): + return + + # Respect LiteLLM's central message-redaction contract. The normal + # chat/completion path is redacted by `perform_redaction` before + # callbacks run, but `complete_input_dict` (read below) is NOT covered by + # that layer — so without this gate, an operator who enabled redaction + # would still see raw passthrough prompts in Arize. Skip entirely when + # redaction is on so neither input nor output leaks through this bridge. + if should_redact_message_logging(kwargs): + return + + # --- INPUT -------------------------------------------------------------- + additional_args = kwargs.get("additional_args") or {} + complete_input_dict = ( + additional_args.get("complete_input_dict") + if isinstance(additional_args, dict) + else None + ) + if isinstance(complete_input_dict, dict): + _set_passthrough_input_attributes(span, complete_input_dict.get("messages")) + + # --- OUTPUT ------------------------------------------------------------- + parsed_response = _parse_passthrough_response( + raw_response_obj, coerced_response_obj, kwargs + ) + if not isinstance(parsed_response, dict): + return + + _set_passthrough_output_attributes(span, parsed_response) + + +def _set_passthrough_input_attributes(span: "Span", messages) -> None: + """Render passthrough request messages into INPUT_VALUE + LLM_INPUT_MESSAGES.""" + if not (isinstance(messages, list) and messages): + return + # Set INPUT_VALUE from the last user message text if discoverable. + last_text = None + for msg in reversed(messages): + if isinstance(msg, dict): + last_text = _coerce_text(msg.get("content")) + if last_text: + break + if last_text: + safe_set_attribute(span, SpanAttributes.INPUT_VALUE, last_text) + # Mirror messages into LLM_INPUT_MESSAGES so the input pane renders. + for idx, msg in enumerate(messages): + if not isinstance(msg, dict): + continue + prefix = f"{SpanAttributes.LLM_INPUT_MESSAGES}.{idx}" + role = msg.get("role") + if role: + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_ROLE}", + role, + ) + text = _coerce_text(msg.get("content")) + if text is not None: + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_CONTENT}", + text, + ) + + +def _set_passthrough_output_attributes(span: "Span", parsed_response: dict) -> None: + """Render passthrough response into OUTPUT_VALUE + LLM_OUTPUT_MESSAGES.""" + # Anthropic / Bedrock-Anthropic: `content` is a list of typed parts. + content_list = parsed_response.get("content") + if isinstance(content_list, list) and content_list: + texts = [] + for part in content_list: + if isinstance(part, dict) and isinstance(part.get("text"), str): + texts.append(part["text"]) + joined = "\n\n".join(t for t in texts if t) + if joined: + safe_set_attribute(span, SpanAttributes.OUTPUT_VALUE, joined) + prefix = f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0" + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_ROLE}", + parsed_response.get("role", "assistant"), + ) + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_CONTENT}", + joined, + ) + + # OpenAI-style passthrough: `choices[0].message.content` + choices = parsed_response.get("choices") + if isinstance(choices, list) and choices: + first = choices[0] + if isinstance(first, dict): + msg = first.get("message") + if isinstance(msg, dict): + text = _coerce_text(msg.get("content")) + if text: + safe_set_attribute(span, SpanAttributes.OUTPUT_VALUE, text) + prefix = f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0" + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_ROLE}", + msg.get("role", "assistant"), + ) + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_CONTENT}", + text, + ) + + +def _parse_passthrough_response(raw_response_obj, coerced_response_obj, kwargs): + """Return a dict view of the provider response for passthrough routes.""" + # Prefer the coerced view (already JSON-parsed for httpx.Response). + candidates = [] + if isinstance(coerced_response_obj, dict): + candidates.append(coerced_response_obj) + if ( + isinstance(raw_response_obj, dict) + and raw_response_obj is not coerced_response_obj + ): + candidates.append(raw_response_obj) + + for candidate in candidates: + # StandardPassThroughResponseObject wrapper: {"response": "..."}. + if ( + "response" in candidate + and "content" not in candidate + and "choices" not in candidate + ): + inner = candidate.get("response") + if isinstance(inner, str): + try: + parsed = json.loads(inner) + if isinstance(parsed, dict): + return parsed + except Exception: + continue + if isinstance(inner, dict): + return inner + else: + return candidate + + # Fallback: kwargs["original_response"] from the OTel base path. + original = kwargs.get("original_response") if isinstance(kwargs, dict) else None + if isinstance(original, dict): + return original + if isinstance(original, str): + try: + parsed = json.loads(original) + if isinstance(parsed, dict): + return parsed + except Exception: + return None + return None diff --git a/tests/test_litellm/integrations/arize/test_arize_utils.py b/tests/test_litellm/integrations/arize/test_arize_utils.py index 86c5448d468..83c3351319a 100644 --- a/tests/test_litellm/integrations/arize/test_arize_utils.py +++ b/tests/test_litellm/integrations/arize/test_arize_utils.py @@ -83,7 +83,12 @@ def test_arize_set_attributes(): # Apply attribute setting via ArizeLogger ArizeLogger.set_arize_attributes(span, kwargs, response_obj) - # Validate that the expected number of attributes were set + # Validate that the expected number of attributes were set. + # OPENINFERENCE_SPAN_KIND is written exactly once (defensively, before + # the main attribute pipeline) so a partial failure cannot blank it. + # Per the OpenInference spec, a chat completion that passes `tools=[...]` + # is still an LLM span — not TOOL (TOOL is reserved for actual tool + # execution by application code). assert span.set_attribute.call_count == 26 # Metadata attached to the span @@ -108,8 +113,15 @@ def test_arize_set_attributes(): # Response metadata span.set_attribute.assert_any_call("llm.response.id", "chatcmpl-ID") span.set_attribute.assert_any_call("llm.response.model", "gpt-4o") - # Span kind is set to TOOL when tools are present - span.set_attribute.assert_any_call(SpanAttributes.OPENINFERENCE_SPAN_KIND, "TOOL") + # Span kind stays LLM even when tools are passed (OpenInference spec). + span.set_attribute.assert_any_call(SpanAttributes.OPENINFERENCE_SPAN_KIND, "LLM") + # And TOOL must never be written for an LLM chat completion call. + span_kind_writes = [ + c.args[1] + for c in span.set_attribute.call_args_list + if c.args[0] == SpanAttributes.OPENINFERENCE_SPAN_KIND + ] + assert "TOOL" not in span_kind_writes # Request message content and metadata span.set_attribute.assert_any_call( @@ -451,3 +463,733 @@ def test_construct_dynamic_arize_headers(): dynamic_params_space_key_and_api_key ) expected_headers = {"arize-space-id": "test_space_key", "api_key": "test_api_key"} + + +# --------------------------------------------------------------------------- +# Additive rendering-enhancement tests. None of these assert that previously +# emitted attributes were removed or changed — they only assert that the new +# attributes appear in their respective scenarios. +# --------------------------------------------------------------------------- + + +def _collect_calls(span): + """Helper: return dict[attr_name] = value of all set_attribute calls.""" + out = {} + for call in span.set_attribute.call_args_list: + args = call.args + if len(args) >= 2: + out[args[0]] = args[1] + return out + + +def test_arize_emits_cache_tokens_openai_style(): + """OpenAI prompt_tokens_details.cached_tokens → cache_read attr.""" + from unittest.mock import MagicMock + + from litellm.integrations.arize._utils import _set_usage_outputs + + span = MagicMock() + response_obj = { + "usage": { + "total_tokens": 100, + "completion_tokens": 60, + "prompt_tokens": 40, + "prompt_tokens_details": {"cached_tokens": 32, "audio_tokens": 8}, + } + } + _set_usage_outputs(span, response_obj, SpanAttributes) + attrs = _collect_calls(span) + assert attrs[SpanAttributes.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ] == 32 + assert attrs[SpanAttributes.LLM_TOKEN_COUNT_PROMPT_DETAILS_AUDIO] == 8 + + +def test_arize_emits_cache_tokens_anthropic_style(): + """Anthropic/Bedrock cache_read_input_tokens / cache_creation_input_tokens.""" + from unittest.mock import MagicMock + + from litellm.integrations.arize._utils import _set_usage_outputs + + span = MagicMock() + response_obj = { + "usage": { + "input_tokens": 100, + "output_tokens": 50, + "cache_read_input_tokens": 80, + "cache_creation_input_tokens": 20, + } + } + _set_usage_outputs(span, response_obj, SpanAttributes) + attrs = _collect_calls(span) + assert attrs[SpanAttributes.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ] == 80 + assert attrs[SpanAttributes.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_WRITE] == 20 + + +def test_arize_emits_no_cache_tokens_when_absent(): + """Regression guard: when no cache fields exist, no cache attrs emitted.""" + from unittest.mock import MagicMock + + from litellm.integrations.arize._utils import _set_usage_outputs + + span = MagicMock() + response_obj = { + "usage": {"total_tokens": 10, "completion_tokens": 4, "prompt_tokens": 6} + } + _set_usage_outputs(span, response_obj, SpanAttributes) + attrs = _collect_calls(span) + assert SpanAttributes.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ not in attrs + assert SpanAttributes.LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_WRITE not in attrs + + +def test_passthrough_call_type_resolves_to_llm_span_kind(): + """`allm_passthrough_route` should map to LLM (was UNKNOWN before fix).""" + from litellm.integrations._types.open_inference import OpenInferenceSpanKindValues + from litellm.integrations.arize._utils import _infer_open_inference_span_kind + + assert ( + _infer_open_inference_span_kind("allm_passthrough_route") + == OpenInferenceSpanKindValues.LLM.value + ) + assert ( + _infer_open_inference_span_kind("llm_passthrough_route") + == OpenInferenceSpanKindValues.LLM.value + ) + + +def test_arize_chat_completion_with_tools_stays_llm_span_kind(): + """Regression guard against the old `TOOL` override: a chat completion + that passes `tools=[...]` AND returns `tool_calls` must remain LLM.""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "weather?"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + }, + "optional_params": { + "tools": [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "weather", + "parameters": {"type": "object", "properties": {}}, + }, + } + ] + }, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 10, "completion_tokens": 4, "prompt_tokens": 6}, + choices=[ + Choices( + message={ + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_x", + "type": "function", + "function": {"name": "get_weather", "arguments": "{}"}, + } + ], + } + ) + ], + model="gpt-4o", + id="r-toolkind", + ) + + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + span_kind_writes = [ + c.args[1] + for c in span.set_attribute.call_args_list + if c.args[0] == SpanAttributes.OPENINFERENCE_SPAN_KIND + ] + assert span_kind_writes, "span.kind must be written" + assert all(v == "LLM" for v in span_kind_writes) + assert "TOOL" not in span_kind_writes + + +def test_arize_emits_assistant_tool_calls_on_output_message(): + """Assistant tool_calls should surface as MESSAGE_TOOL_CALLS.* attrs.""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "weather?"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 10, "completion_tokens": 4, "prompt_tokens": 6}, + choices=[ + Choices( + message={ + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_abc", + "type": "function", + "function": { + "name": "get_weather", + "arguments": '{"location": "SF"}', + }, + } + ], + } + ) + ], + model="gpt-4o", + id="chatcmpl-1", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + base = f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_TOOL_CALLS}.0" + assert attrs[f"{base}.{ToolCallAttributes.TOOL_CALL_ID}"] == "call_abc" + assert ( + attrs[f"{base}.{ToolCallAttributes.TOOL_CALL_FUNCTION_NAME}"] == "get_weather" + ) + assert ( + attrs[f"{base}.{ToolCallAttributes.TOOL_CALL_FUNCTION_ARGUMENTS_JSON}"] + == '{"location": "SF"}' + ) + + +def test_arize_output_value_falls_back_to_tool_calls_summary(): + """When the assistant returns no text content but did request tool + calls, OUTPUT_VALUE should contain a JSON summary so Arize's Output + pane shows something.""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "weather?"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 10, "completion_tokens": 4, "prompt_tokens": 6}, + choices=[ + Choices( + message={ + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_abc", + "type": "function", + "function": { + "name": "get_weather", + "arguments": '{"location": "SF"}', + }, + } + ], + } + ) + ], + model="gpt-4o", + id="r-tc-out", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + + # OUTPUT_VALUE should contain the tool_call name + arguments JSON + out = attrs[SpanAttributes.OUTPUT_VALUE] + assert "tool_calls" in out + assert "get_weather" in out + assert "SF" in out + + +def test_arize_output_value_unchanged_when_content_present(): + """Regression guard: when content is non-empty, OUTPUT_VALUE must be + exactly that content (no summary written).""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 4, "completion_tokens": 2, "prompt_tokens": 2}, + choices=[ + Choices( + message={ + "role": "assistant", + "content": "hello world", + "tool_calls": [ + { + "id": "call_x", + "type": "function", + "function": {"name": "n", "arguments": "{}"}, + } + ], + } + ) + ], + model="gpt-4o", + id="r-content", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + assert attrs[SpanAttributes.OUTPUT_VALUE] == "hello world" + + +def test_arize_emits_tool_call_id_and_name_on_input_tool_message(): + """A tool-result input message should expose tool_call_id + name.""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [ + {"role": "user", "content": "weather?"}, + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "id": "call_abc", + "type": "function", + "function": { + "name": "get_weather", + "arguments": '{"location": "SF"}', + }, + } + ], + }, + { + "role": "tool", + "tool_call_id": "call_abc", + "name": "get_weather", + "content": "sunny, 72F", + }, + ], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 10, "completion_tokens": 4, "prompt_tokens": 6}, + choices=[Choices(message={"role": "assistant", "content": "It's sunny."})], + model="gpt-4o", + id="chatcmpl-2", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + # Assistant tool_call surfaces on input msg index 1 + assistant_base = f"{SpanAttributes.LLM_INPUT_MESSAGES}.1.{MessageAttributes.MESSAGE_TOOL_CALLS}.0" + assert attrs[f"{assistant_base}.{ToolCallAttributes.TOOL_CALL_ID}"] == "call_abc" + # Tool message at index 2 + tool_prefix = f"{SpanAttributes.LLM_INPUT_MESSAGES}.2" + assert ( + attrs[f"{tool_prefix}.{MessageAttributes.MESSAGE_TOOL_CALL_ID}"] == "call_abc" + ) + assert attrs[f"{tool_prefix}.{MessageAttributes.MESSAGE_NAME}"] == "get_weather" + + +def test_arize_emits_multimodal_input_contents(): + """List-shaped content should populate MESSAGE_CONTENTS.* alongside the + legacy MESSAGE_CONTENT (which stays for back-compat).""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [ + { + "role": "user", + "content": [ + {"type": "text", "text": "What is in this image?"}, + { + "type": "image_url", + "image_url": {"url": "https://example.com/cat.png"}, + }, + ], + } + ], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 10, "completion_tokens": 4, "prompt_tokens": 6}, + choices=[Choices(message={"role": "assistant", "content": "A cat."})], + model="gpt-4o", + id="chatcmpl-img", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + base = f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_CONTENTS}" + assert attrs[f"{base}.0.message_content.type"] == "text" + assert attrs[f"{base}.0.message_content.text"] == "What is in this image?" + assert attrs[f"{base}.1.message_content.type"] == "image" + assert ( + attrs[f"{base}.1.message_content.image.image.url"] + == "https://example.com/cat.png" + ) + + +def test_arize_emits_session_and_user_attrs_from_metadata(): + """end_user_id → SESSION_ID; user_api_key_user_id → USER_ID (only when + optional_params.user/model_params.user absent).""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": { + "user_api_key_user_id": "user_42", + "user_api_key_end_user_id": "session_99", + "user_api_key_team_id": "team_7", + "user_api_key_team_alias": "alpha", + "user_api_key_alias": "key_alpha", + }, + "call_type": "completion", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 4, "completion_tokens": 2, "prompt_tokens": 2}, + choices=[Choices(message={"role": "assistant", "content": "hello"})], + model="gpt-4o", + id="r1", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + assert attrs[SpanAttributes.SESSION_ID] == "session_99" + assert attrs[SpanAttributes.USER_ID] == "user_42" + assert attrs["litellm.team_id"] == "team_7" + assert attrs["litellm.team_alias"] == "alpha" + assert attrs["litellm.key_alias"] == "key_alpha" + + +def test_arize_does_not_use_trace_id_as_session_id_fallback(): + """SESSION_ID must NOT fall back to trace_id (one session-per-request + would distort Arize Session analytics). trace_id is emitted under its + own `litellm.trace_id` key instead. + """ + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + "trace_id": "trace-xyz-123", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 4, "completion_tokens": 2, "prompt_tokens": 2}, + choices=[Choices(message={"role": "assistant", "content": "hi"})], + model="gpt-4o", + id="r-trace", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + + # SESSION_ID must NOT be derived from trace_id. + assert SpanAttributes.SESSION_ID not in attrs + # trace_id surfaces under its own key. + assert attrs["litellm.trace_id"] == "trace-xyz-123" + + +def test_arize_does_not_overwrite_user_id_from_optional_params(): + """If optional_params.user is set, metadata USER_ID must NOT overwrite.""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "standard_logging_object": { + "model_parameters": {"user": "from_model_params"}, + "metadata": {"user_api_key_user_id": "from_metadata"}, + "call_type": "completion", + }, + "optional_params": {"user": "from_optional_params"}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 4, "completion_tokens": 2, "prompt_tokens": 2}, + choices=[Choices(message={"role": "assistant", "content": "hello"})], + model="gpt-4o", + id="r2", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + user_id_writes = [ + c.args[1] + for c in span.set_attribute.call_args_list + if c.args[0] == SpanAttributes.USER_ID + ] + assert "from_metadata" not in user_id_writes + + +def test_arize_emits_response_cost(): + """StandardLoggingPayload.response_cost → llm.cost.total (+ legacy llm.response.cost).""" + from unittest.mock import MagicMock + + from litellm.types.utils import Choices, ModelResponse + + span = MagicMock() + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "completion", + "response_cost": 0.0012345, + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + } + response_obj = ModelResponse( + usage={"total_tokens": 4, "completion_tokens": 2, "prompt_tokens": 2}, + choices=[Choices(message={"role": "assistant", "content": "hello"})], + model="gpt-4o", + id="r3", + ) + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + assert attrs["llm.cost.total"] == 0.0012345 + assert attrs["llm.response.cost"] == 0.0012345 # legacy key still emitted + + +def test_arize_passthrough_bedrock_anthropic_normalization(): + """Bedrock-Anthropic passthrough: input/output text must be set so the + span renders something other than raw provider attrs.""" + from unittest.mock import MagicMock + + span = MagicMock() + bedrock_response_body = { + "id": "msg_01", + "type": "message", + "role": "assistant", + "content": [{"type": "text", "text": "The capital of France is Paris."}], + "model": "anthropic.claude-sonnet-4-v1:0", + "stop_reason": "end_turn", + "usage": {"input_tokens": 18, "output_tokens": 12}, + } + + class FakeHttpxResponse: + """Minimal httpx.Response stand-in: has `.text` and no `.get`.""" + + def __init__(self, body): + self.text = json.dumps(body) + + response_obj = FakeHttpxResponse(bedrock_response_body) + kwargs = { + "model": "anthropic.claude-sonnet-4-v1:0", + "messages": [ + { + "role": "user", + "content": json.dumps({"messages": [{"role": "user", "content": "?"}]}), + } + ], + "additional_args": { + "complete_input_dict": { + "anthropic_version": "bedrock-2023-05-31", + "max_tokens": 64, + "messages": [ + {"role": "user", "content": "What is the capital of France?"} + ], + } + }, + "standard_logging_object": { + "model_parameters": {}, + "metadata": {}, + "call_type": "allm_passthrough_route", + }, + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "bedrock"}, + } + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + attrs = _collect_calls(span) + + # Input rendering + assert attrs[SpanAttributes.INPUT_VALUE] == "What is the capital of France?" + msg0 = f"{SpanAttributes.LLM_INPUT_MESSAGES}.0" + assert attrs[f"{msg0}.{MessageAttributes.MESSAGE_ROLE}"] == "user" + assert ( + attrs[f"{msg0}.{MessageAttributes.MESSAGE_CONTENT}"] + == "What is the capital of France?" + ) + + # Output rendering (Anthropic content[].text) + assert attrs[SpanAttributes.OUTPUT_VALUE] == "The capital of France is Paris." + out0 = f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0" + assert attrs[f"{out0}.{MessageAttributes.MESSAGE_ROLE}"] == "assistant" + assert ( + attrs[f"{out0}.{MessageAttributes.MESSAGE_CONTENT}"] + == "The capital of France is Paris." + ) + + # Token counts (Bedrock input_tokens/output_tokens) — extracted via + # coercion of the non-dict response. + assert attrs[SpanAttributes.LLM_TOKEN_COUNT_PROMPT] == 18 + assert attrs[SpanAttributes.LLM_TOKEN_COUNT_COMPLETION] == 12 + + # Span kind defended even though the call_type is a passthrough variant. + span_kind_writes = [ + c.args[1] + for c in span.set_attribute.call_args_list + if c.args[0] == SpanAttributes.OPENINFERENCE_SPAN_KIND + ] + assert span_kind_writes # at least one + assert all(v == "LLM" for v in span_kind_writes) + + +def test_arize_passthrough_call_type_does_not_run_on_chat_completion(): + """Guard: passthrough normalizer must not fire for normal chat calls. + + If it did, it could double-write input/output for ordinary completions. + """ + from unittest.mock import MagicMock + + from litellm.integrations.arize._utils import _maybe_normalize_passthrough + + span = MagicMock() + _maybe_normalize_passthrough( + span, + { + "additional_args": { + "complete_input_dict": {"messages": [{"role": "user", "content": "x"}]} + } + }, + {"choices": [{"message": {"role": "assistant", "content": "y"}}]}, + {"choices": [{"message": {"role": "assistant", "content": "y"}}]}, + {"call_type": "completion"}, + ) + assert span.set_attribute.call_count == 0 + + +def test_arize_passthrough_skipped_when_message_redaction_enabled(): + """Security guard: when message-logging redaction is enabled, the + passthrough normalizer must NOT export the raw prompt (read from + `complete_input_dict`, which bypasses central redaction) to the span. + """ + from unittest.mock import MagicMock + + from litellm.integrations.arize._utils import _maybe_normalize_passthrough + + span = MagicMock() + kwargs = { + "additional_args": { + "complete_input_dict": { + "messages": [ + {"role": "user", "content": "Patient John Doe, SSN 123-45-6789"} + ] + } + }, + # Enables redaction via the dynamic-param path inside + # should_redact_message_logging(), without touching globals. + "standard_callback_dynamic_params": {"turn_off_message_logging": True}, + } + _maybe_normalize_passthrough( + span, + kwargs, + {"content": [{"type": "text", "text": "secret response"}]}, + {"content": [{"type": "text", "text": "secret response"}]}, + {"call_type": "allm_passthrough_route"}, + ) + # Nothing — neither input nor output — should be written to the span. + assert span.set_attribute.call_count == 0 + + +def test_arize_coerce_response_obj_passes_dicts_through_untouched(): + """Regression guard for the BaseModel/dict path.""" + from litellm.integrations.arize._utils import _coerce_response_obj_for_attrs + + d = {"id": "x", "model": "m"} + assert _coerce_response_obj_for_attrs(d) is d + + class HasGet: + def get(self, *a, **k): # noqa: D401 + return None + + obj = HasGet() + assert _coerce_response_obj_for_attrs(obj) is obj + + assert _coerce_response_obj_for_attrs(None) is None + + +def test_arize_coerce_response_obj_parses_httpx_like(): + """httpx.Response-like objects without `.get` should JSON-decode.""" + from litellm.integrations.arize._utils import _coerce_response_obj_for_attrs + + class FakeHttpxResponse: + text = '{"id": "msg_1", "model": "claude"}' + + parsed = _coerce_response_obj_for_attrs(FakeHttpxResponse()) + assert parsed == {"id": "msg_1", "model": "claude"} + + +def test_arize_coerce_response_obj_returns_original_on_bad_json(): + from litellm.integrations.arize._utils import _coerce_response_obj_for_attrs + + class BadJson: + text = "not-json" + + obj = BadJson() + assert _coerce_response_obj_for_attrs(obj) is obj From 2bbdbfa5c348e198eb21461731c784e12897f01f Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 3 Jun 2026 12:13:02 -0700 Subject: [PATCH 17/92] fix: passthrough endpoints duplicate logs (#29598) * fix duplicate cost callbacks for anthropic streaming pass-through Two bugs caused _PROXY_track_cost_callback to see stream=True + complete_streaming_response=None on every streaming pass-through request, making the dedup guard in dispatch_success_handlers permanently inactive: 1. pass_through_endpoints.py created the Logging object with stream=False for all requests. _is_assembled_stream_success short-circuits on self.stream is not True, so has_dispatched_final_stream_success was never set and any second dispatch went through unchecked. Fix: set logging_obj.stream = True after stream detection. 2. _create_anthropic_response_logging_payload set complete_streaming_response inside the try block after litellm.completion_cost(), so a pricing error caused an early return without setting it on model_call_details. Fix: set complete_streaming_response before the try block. Co-Authored-By: Claude Sonnet 4.6 * fix stream * add stream to logging obj * test(pass_through): give mock logging object a real model_call_details dict The anthropic passthrough logging payload now records the assembled response on model_call_details before cost calculation, which requires model_call_details to support item assignment. In production it is always a dict; the existing unit test stubbed the logging object with a bare Mock whose attribute is not subscriptable, so the new assignment raised TypeError. Use a real dict to match the production logging object. * test(pass_through): cover streaming logging-obj stream flag The streaming branch of pass_through_request that marks the logging object as streaming (logging_obj.stream and model_call_details["stream"]) had no unit coverage, so the patch coverage gate flagged it. Add a regression test that drives a streaming pass-through request through pass_through_request and asserts the logging object is flagged as a stream before dispatch. * test(pass_through): cover SSE-response stream flag fallback branch The auto-detected streaming branch of pass_through_request (when a request that was not flagged as streaming returns a text/event-stream response) sets logging_obj.stream and model_call_details["stream"] but had no unit coverage, so the codecov patch gate failed at 60%. Drive a non-streaming pass-through request whose upstream response is SSE through pass_through_request and assert the logging object is flagged as a stream before dispatch. * fix(pass_through): gate complete_streaming_response on stream flag perform_redaction only scrubs complete_streaming_response when model_call_details["stream"] is True. Setting it unconditionally for non-streaming Anthropic pass-through responses left the assembled response unredacted in model_call_details, which is handed to logging callbacks as kwargs when message logging is disabled. Only record it for actual streaming responses so redaction always applies. --------- Co-authored-by: mubashir1osmani Co-authored-by: Claude Sonnet 4.6 --- .../anthropic_passthrough_logging_handler.py | 7 + .../pass_through_endpoints.py | 6 + .../test_unit_test_anthropic_pass_through.py | 1 + ...t_anthropic_passthrough_logging_handler.py | 332 ++++++++++++++++++ .../test_pass_through_endpoints.py | 125 +++++++ 5 files changed, 471 insertions(+) diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py index 3be26eb572d..a94672f9487 100644 --- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py @@ -114,6 +114,13 @@ class AnthropicPassthroughLoggingHandler: handles streaming and non-streaming responses """ + # Only record complete_streaming_response for actual streaming responses. + # perform_redaction scrubs this field only when stream is True, so setting + # it on a non-streaming response would bypass message redaction. + if logging_obj.model_call_details.get("stream") is True: + logging_obj.model_call_details["complete_streaming_response"] = ( + litellm_model_response + ) try: # Get custom_llm_provider from logging object if available (e.g., azure_ai for Azure Anthropic) custom_llm_provider = logging_obj.model_call_details.get( diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index 985785ad77e..e49e1302ab5 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -1061,6 +1061,9 @@ async def pass_through_request( # noqa: PLR0915 ) if stream: + logging_obj.stream = True + logging_obj.model_call_details["stream"] = True + if is_multipart: response = ( await HttpPassThroughEndpointHelpers.make_multipart_http_request( @@ -1139,6 +1142,9 @@ async def pass_through_request( # noqa: PLR0915 verbose_proxy_logger.debug("response.headers= %s", response.headers) if _is_streaming_response(response) is True: + logging_obj.stream = True + logging_obj.model_call_details["stream"] = True + try: response.raise_for_status() except httpx.HTTPStatusError as e: diff --git a/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py b/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py index 455c72ff636..5ab0319da47 100644 --- a/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py +++ b/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py @@ -318,6 +318,7 @@ def test_handle_logging_anthropic_collected_chunks(all_chunks): from litellm.types.utils import ModelResponse litellm_logging_obj = Mock() + litellm_logging_obj.model_call_details = {} pass_through_logging_obj = Mock() sent_args = { diff --git a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py index 0a9e3031030..f8b6fbde3dc 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py @@ -1043,3 +1043,335 @@ class TestPureTextFastPathParity: AnthropicPassthroughLoggingHandler._collapse_pure_text_chunks(all_chunks) is None ) + + +class TestStreamFalseDeduplication: + """ + Regression tests for the duplicate-callback bug where a streaming pass-through + request had stream=False hardcoded on its Logging object. + + Before the fix: + - logging_obj.stream was always False for pass-through requests + - _is_assembled_stream_success() checked `self.stream is not True` and returned + False immediately, so has_dispatched_final_stream_success was never set + - Any second dispatch_success_handlers call went through unchecked + + After the fix: + - pass_through_endpoints.py sets logging_obj.stream = True after detecting stream + - _create_anthropic_response_logging_payload sets complete_streaming_response on + model_call_details so callbacks see the correct assembled response state + - _is_assembled_stream_success returns True, dedup guard fires on first dispatch + """ + + @staticmethod + def _sse(event, data): + return f"event: {event}\ndata: {json.dumps(data)}\n\n".encode() + + @staticmethod + def _make_logging_obj(stream: bool = False) -> LiteLLMLoggingObj: + logging_obj = LiteLLMLoggingObj( + model="claude-3-5-sonnet-20241022", + messages=[{"role": "user", "content": "hello"}], + stream=stream, + call_type="pass_through_endpoint", + start_time=datetime.now(), + litellm_call_id="test-call-id", + function_id="1245", + ) + return logging_obj + + @staticmethod + def _build_chunks(): + frames = [ + TestStreamFalseDeduplication._sse( + "message_start", + { + "type": "message_start", + "message": { + "id": "msg_abc", + "type": "message", + "role": "assistant", + "model": "claude-3-5-sonnet-20241022", + "content": [], + "stop_reason": None, + "stop_sequence": None, + "usage": {"input_tokens": 10, "output_tokens": 0}, + }, + }, + ), + TestStreamFalseDeduplication._sse( + "content_block_start", + { + "type": "content_block_start", + "index": 0, + "content_block": {"type": "text", "text": ""}, + }, + ), + TestStreamFalseDeduplication._sse( + "content_block_delta", + { + "type": "content_block_delta", + "index": 0, + "delta": {"type": "text_delta", "text": "Hello"}, + }, + ), + TestStreamFalseDeduplication._sse( + "content_block_stop", {"type": "content_block_stop", "index": 0} + ), + TestStreamFalseDeduplication._sse( + "message_delta", + { + "type": "message_delta", + "delta": {"stop_reason": "end_turn", "stop_sequence": None}, + "usage": {"output_tokens": 5}, + }, + ), + TestStreamFalseDeduplication._sse("message_stop", {"type": "message_stop"}), + ] + from litellm.proxy.pass_through_endpoints.streaming_handler import ( + PassThroughStreamingHandler, + ) + + return PassThroughStreamingHandler._convert_raw_bytes_to_str_lines(frames) + + def test_complete_streaming_response_set_on_model_call_details(self): + """ + After the fix, _create_anthropic_response_logging_payload must set + complete_streaming_response on logging_obj.model_call_details so that + callbacks like _PROXY_track_cost_callback see the assembled response + instead of None. + + Before the fix: model_call_details had no complete_streaming_response key. + The log showed: "kwargs stream: True + complete streaming response: None" + """ + from litellm.types.passthrough_endpoints.pass_through_endpoints import ( + EndpointType, + ) + + # pass_through_request sets the stream flag before the streaming handler + # reconstructs the response; mirror that here. + logging_obj = self._make_logging_obj(stream=True) + logging_obj.model_call_details["stream"] = True + all_chunks = list(self._build_chunks()) + + result = AnthropicPassthroughLoggingHandler._handle_logging_anthropic_collected_chunks( + litellm_logging_obj=logging_obj, + passthrough_success_handler_obj=MagicMock(), + url_route="/anthropic/v1/messages", + request_body={"model": "claude-3-5-sonnet-20241022", "stream": True}, + endpoint_type=EndpointType.ANTHROPIC, + start_time=datetime.now(), + all_chunks=all_chunks, + end_time=datetime.now(), + ) + + # The assembled response must be stored on model_call_details so callbacks + # can identify this as a completed streaming call, not an in-progress one. + assert ( + logging_obj.model_call_details.get("complete_streaming_response") + is not None + ), "complete_streaming_response must be set on model_call_details after assembly" + + # The returned result must match what was stored + assert result["result"] is logging_obj.model_call_details.get( + "complete_streaming_response" + ) + + def test_dedup_guard_fires_when_stream_true_on_logging_obj(self): + """ + When logging_obj.stream is True (set by pass_through_endpoints.py after + detecting a streaming request), dispatch_success_handlers must set + has_dispatched_final_stream_success=True on the first call so that any + second call is a no-op. + + This is the _is_assembled_stream_success gate: with stream=False it + always returned False and the guard was permanently disabled. + """ + from litellm.types.passthrough_endpoints.pass_through_endpoints import ( + EndpointType, + ) + from litellm.types.utils import ModelResponse + + # Simulate what pass_through_endpoints.py now does after stream detection + logging_obj = self._make_logging_obj(stream=False) + logging_obj.stream = True # fix applied + logging_obj.model_call_details["stream"] = True + + # Simulate what _create_anthropic_response_logging_payload now does + mock_response = ModelResponse(model="claude-3-5-sonnet-20241022") + logging_obj.model_call_details["complete_streaming_response"] = mock_response + + assert logging_obj._is_assembled_stream_success(result=mock_response) is True + + # First dispatch sets the flag + assert not logging_obj.model_call_details.get( + "has_dispatched_final_stream_success" + ) + logging_obj.model_call_details["has_dispatched_final_stream_success"] = True + + # Second dispatch would be blocked — simulate the guard check + would_skip = bool( + logging_obj._is_assembled_stream_success(result=mock_response) + and logging_obj.model_call_details.get( + "has_dispatched_final_stream_success" + ) + ) + assert would_skip is True, ( + "Dedup guard must block a second dispatch_success_handlers call for the " + "same assembled streaming response" + ) + + def test_sse_fallback_path_sets_stream_true_for_dedup(self): + """ + When a nominally non-streaming request receives an SSE response + (_is_streaming_response returns True), the fallback branch in + pass_through_endpoints.py must set logging_obj.stream = True so the + dedup guard activates. + + Before the fix the fallback path never set stream=True, so + _is_assembled_stream_success always returned False and duplicate + callback dispatches were never blocked. + """ + from litellm.types.utils import ModelResponse + + # logging_obj starts with stream=False, as created before the request + logging_obj = self._make_logging_obj(stream=False) + assert logging_obj._is_assembled_stream_success(result=MagicMock()) is False + + # Simulate what the SSE fallback branch in pass_through_endpoints.py now does + logging_obj.stream = True + logging_obj.model_call_details["stream"] = True + + mock_response = ModelResponse(model="claude-3-5-sonnet-20241022") + logging_obj.model_call_details["complete_streaming_response"] = mock_response + + # With stream=True the dedup guard must be active + assert logging_obj._is_assembled_stream_success(result=mock_response) is True + + logging_obj.model_call_details["has_dispatched_final_stream_success"] = True + + would_skip = bool( + logging_obj._is_assembled_stream_success(result=mock_response) + and logging_obj.model_call_details.get( + "has_dispatched_final_stream_success" + ) + ) + assert would_skip is True + + def test_stream_false_logging_obj_bypasses_dedup_guard(self): + """ + Demonstrates the pre-fix state: with stream=False on the logging object, + _is_assembled_stream_success always returns False regardless of whether + complete_streaming_response is set. This means the dedup guard can never + fire, so duplicate dispatches go through unchecked. + + This test documents the old broken behavior so the fix is clearly justified. + """ + from litellm.types.utils import ModelResponse + + logging_obj = self._make_logging_obj(stream=False) + mock_response = ModelResponse(model="claude-3-5-sonnet-20241022") + logging_obj.model_call_details["complete_streaming_response"] = mock_response + + # With stream=False, _is_assembled_stream_success returns False even though + # complete_streaming_response is present — the guard is permanently disabled. + assert logging_obj._is_assembled_stream_success(result=mock_response) is False + + +class TestNonStreamingResponseRedaction: + """ + Regression tests ensuring _create_anthropic_response_logging_payload only sets + complete_streaming_response for streaming responses. perform_redaction scrubs + that field exclusively when model_call_details["stream"] is True, so storing it + on a non-streaming response would deliver the unredacted response to logging + callbacks when message logging is disabled. + """ + + @staticmethod + def _make_logging_obj(stream: bool) -> LiteLLMLoggingObj: + logging_obj = LiteLLMLoggingObj( + model="claude-3-5-sonnet-20241022", + messages=[{"role": "user", "content": "hello"}], + stream=stream, + call_type="pass_through_endpoint", + start_time=datetime.now(), + litellm_call_id="test-call-id", + function_id="1245", + ) + # pass_through_request mirrors the stream flag onto model_call_details, + # which is the key perform_redaction inspects. + logging_obj.model_call_details["stream"] = stream + return logging_obj + + def test_non_streaming_does_not_set_complete_streaming_response(self): + from litellm.types.utils import ModelResponse + + logging_obj = self._make_logging_obj(stream=False) + response = ModelResponse(model="claude-3-5-sonnet-20241022") + + AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( + litellm_model_response=response, + model="claude-3-5-sonnet-20241022", + kwargs={}, + start_time=datetime.now(), + end_time=datetime.now(), + logging_obj=logging_obj, + ) + + assert ( + "complete_streaming_response" not in logging_obj.model_call_details + ), "non-streaming responses must not populate complete_streaming_response" + + def test_streaming_sets_complete_streaming_response(self): + from litellm.types.utils import ModelResponse + + logging_obj = self._make_logging_obj(stream=True) + response = ModelResponse(model="claude-3-5-sonnet-20241022") + + AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( + litellm_model_response=response, + model="claude-3-5-sonnet-20241022", + kwargs={}, + start_time=datetime.now(), + end_time=datetime.now(), + logging_obj=logging_obj, + ) + + assert ( + logging_obj.model_call_details.get("complete_streaming_response") + is response + ) + + def test_non_streaming_response_is_redacted_when_message_logging_off(self): + from litellm.litellm_core_utils.redact_messages import ( + redact_message_input_output_from_logging, + ) + from litellm.types.utils import Choices, Message, ModelResponse + + logging_obj = self._make_logging_obj(stream=False) + response = ModelResponse( + model="claude-3-5-sonnet-20241022", + choices=[Choices(message=Message(role="assistant", content="secret"))], + ) + + AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( + litellm_model_response=response, + model="claude-3-5-sonnet-20241022", + kwargs={}, + start_time=datetime.now(), + end_time=datetime.now(), + logging_obj=logging_obj, + ) + + logging_obj.model_call_details["litellm_params"] = { + "metadata": {"headers": {"x-litellm-enable-message-redaction": True}} + } + + redacted = redact_message_input_output_from_logging( + model_call_details=logging_obj.model_call_details, + result=response, + ) + + leaked = logging_obj.model_call_details.get("complete_streaming_response") + assert leaked is None + assert redacted.choices[0].message.content == "redacted-by-litellm" diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py index 61299e2662a..89c57bcced6 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py @@ -1050,6 +1050,131 @@ async def test_pass_through_request_contains_proxy_server_request_in_kwargs(): assert metadata["user_api_key_user_id"] == "test-user-id" +@pytest.mark.asyncio +async def test_pass_through_request_streaming_marks_logging_obj_as_stream(): + """ + Regression: a streaming pass-through request must flag its logging object as + streaming (logging_obj.stream and model_call_details["stream"]) before the + response is dispatched, so cost/success callbacks treat it as a stream and the + streaming dedup guard fires instead of double-logging. + """ + with patch("litellm.proxy.proxy_server.proxy_logging_obj") as mock_proxy_logging: + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_async_httpx_client" + ) as mock_get_client: + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.PassThroughStreamingHandler.chunk_processor" + ) as mock_chunk_processor: + mock_proxy_logging.pre_call_hook = AsyncMock( + return_value={"model": "claude-3", "stream": True} + ) + mock_proxy_logging.post_call_failure_hook = AsyncMock() + + upstream_response = MagicMock() + upstream_response.status_code = 200 + upstream_response.headers = {} + upstream_response.raise_for_status = MagicMock() + + async_client = MagicMock() + async_client.build_request = MagicMock(return_value=MagicMock()) + async_client.send = AsyncMock(return_value=upstream_response) + mock_get_client.return_value = MagicMock(client=async_client) + + async def _empty_chunks(*args, **kwargs): + return + yield # pragma: no cover + + mock_chunk_processor.return_value = _empty_chunks() + + mock_request = MagicMock(spec=Request) + mock_request.method = "POST" + mock_request.url = "http://test-proxy.com/v1/messages" + mock_request.body = AsyncMock( + return_value=b'{"model": "claude-3", "stream": true}' + ) + mock_request.headers = Headers({}) + mock_request.query_params = QueryParams({}) + + await pass_through_request( + request=mock_request, + target="http://target-api.com/v1/messages", + custom_headers={}, + user_api_key_dict=MagicMock(), + stream=True, + ) + + async_client.send.assert_awaited_once() + assert async_client.send.call_args.kwargs["stream"] is True + + mock_chunk_processor.assert_called_once() + logging_obj = mock_chunk_processor.call_args.kwargs[ + "litellm_logging_obj" + ] + assert logging_obj.stream is True + assert logging_obj.model_call_details["stream"] is True + + +@pytest.mark.asyncio +async def test_pass_through_request_sse_response_marks_logging_obj_as_stream(): + """ + Regression: a request that is not flagged as streaming up front but whose + upstream response comes back as an SSE stream (content-type text/event-stream) + must still flag its logging object as streaming before dispatch. Otherwise the + cost/success callbacks treat the assembled stream as a non-stream and the dedup + guard never fires, double-logging the request. + """ + with patch("litellm.proxy.proxy_server.proxy_logging_obj") as mock_proxy_logging: + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_async_httpx_client" + ) as mock_get_client: + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.PassThroughStreamingHandler.chunk_processor" + ) as mock_chunk_processor: + mock_proxy_logging.pre_call_hook = AsyncMock( + return_value={"model": "claude-3"} + ) + mock_proxy_logging.post_call_failure_hook = AsyncMock() + + upstream_response = MagicMock() + upstream_response.status_code = 200 + upstream_response.headers = {"content-type": "text/event-stream"} + upstream_response.raise_for_status = MagicMock() + + async_client = MagicMock() + async_client.request = AsyncMock(return_value=upstream_response) + mock_get_client.return_value = MagicMock(client=async_client) + + async def _empty_chunks(*args, **kwargs): + return + yield # pragma: no cover + + mock_chunk_processor.return_value = _empty_chunks() + + mock_request = MagicMock(spec=Request) + mock_request.method = "POST" + mock_request.url = "http://test-proxy.com/v1/messages" + mock_request.body = AsyncMock(return_value=b'{"model": "claude-3"}') + mock_request.headers = Headers({}) + mock_request.query_params = QueryParams({}) + + await pass_through_request( + request=mock_request, + target="http://target-api.com/v1/messages", + custom_headers={}, + user_api_key_dict=MagicMock(), + stream=False, + ) + + async_client.request.assert_awaited_once() + + mock_chunk_processor.assert_called_once() + logging_obj = mock_chunk_processor.call_args.kwargs[ + "litellm_logging_obj" + ] + assert logging_obj.stream is True + assert logging_obj.model_call_details["stream"] is True + + @pytest.mark.asyncio async def test_create_pass_through_endpoint(): """ From 84969aaf15fa4c510279dde68b511a82cfdd49f8 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 3 Jun 2026 13:37:53 -0700 Subject: [PATCH 18/92] fix(ci): keep coverage rename green when a parallel node runs no tests (#29608) * fix(ci): keep coverage rename green when a parallel node runs no tests local_testing_part1 and local_testing_part2 run with parallelism 4. When CircleCI reruns only the failed tests, the failed test lands on a single node and the other nodes receive an empty bucket, so pytest never writes coverage.xml or .coverage. The unguarded "mv coverage.xml ..." then exits 1 and turns the whole job red even though the rerun passed; the next persist_to_workspace step would fail the same way on the missing paths. Guard the rename so a node with no coverage emits empty placeholders instead. coverage combine tolerates the empty files, so the downstream upload-coverage job keeps the real nodes' data intact. * fix(ci): pre-create test-results in litellm_router_testing for empty-bucket reruns litellm_router_testing also runs with parallelism 4. On a rerun of only the failed tests, a node can receive no tests, so the test command never creates test-results and the final store_test_results step can fail on the missing path. Pre-create the directory up front, matching what local_testing_part1 and part2 already do and CircleCI's own guidance for parallel reruns. * test(openai): retry wildcard chat completion on transient OpenAI 500 build_and_test reddened on test_openai_wildcard_chat_completion when the real gpt-3.5-turbo-0125 call returned an OpenAI 500 ("The server had an error while processing your request"). The base branch passed the same call concurrently, so the 500 is an intermittent OpenAI server error, not a regression. Add the same pytest-retry marker the sibling real-call tests in this file already use so a transient upstream 500 no longer fails CI. --- .circleci/config.yml | 27 +++++++++++++++++++++++---- tests/test_openai_endpoints.py | 1 + 2 files changed, 24 insertions(+), 4 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index f5a8fe77a25..6ee5634f54f 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -249,8 +249,15 @@ jobs: - run: name: Rename the coverage files command: | - mv coverage.xml local_testing_part1_coverage.xml - mv .coverage local_testing_part1_coverage + # When CI reruns only the failed tests, a parallel node can receive + # zero tests and pytest never writes coverage. Emit empty placeholders + # so persist_to_workspace and the downstream coverage combine stay green. + if [ -f coverage.xml ]; then + mv coverage.xml local_testing_part1_coverage.xml + mv .coverage local_testing_part1_coverage + else + touch local_testing_part1_coverage.xml local_testing_part1_coverage + fi # Store test results - store_test_results: @@ -314,8 +321,15 @@ jobs: - run: name: Rename the coverage files command: | - mv coverage.xml local_testing_part2_coverage.xml - mv .coverage local_testing_part2_coverage + # When CI reruns only the failed tests, a parallel node can receive + # zero tests and pytest never writes coverage. Emit empty placeholders + # so persist_to_workspace and the downstream coverage combine stay green. + if [ -f coverage.xml ]; then + mv coverage.xml local_testing_part2_coverage.xml + mv .coverage local_testing_part2_coverage + else + touch local_testing_part2_coverage.xml local_testing_part2_coverage + fi # Store test results - store_test_results: @@ -464,6 +478,11 @@ jobs: - run: name: Run tests command: | + # On a "rerun failed tests" build a parallel node can receive no + # tests, so the test command never creates test-results. Pre-create it + # so store_test_results doesn't fail the node on a missing path. + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/local_testing/**/test_*.py") echo "$TEST_FILES" | circleci tests run \ diff --git a/tests/test_openai_endpoints.py b/tests/test_openai_endpoints.py index e898b88a556..880cc1ebbef 100644 --- a/tests/test_openai_endpoints.py +++ b/tests/test_openai_endpoints.py @@ -522,6 +522,7 @@ async def test_image_generation(): await image_generation(session=session, key=key_2) +@pytest.mark.flaky(retries=5, delay=1) @pytest.mark.asyncio async def test_openai_wildcard_chat_completion(): """ From b4aee2c7ddb4d9f01c6359065d89ed928f71ee6b Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 3 Jun 2026 13:46:43 -0700 Subject: [PATCH 19/92] test(vcr): close out the remaining VCR live-call leaks (#29603) * Fix remaining VCR live-call leaks * test(vcr): dedupe live-test helpers and drop spurious kwargs Extract the duplicated isVertexQuotaError/runVertexRequestOrSkip Vertex quota-skip helpers into tests/pass_through_tests/vertex_test_helpers.js and the duplicated _skip_live_prompt_caching_test guard into tests/_live_test_helpers.py so each lives in one place. In test_aarun_thread_litellm, build a separate message_data carrying role/content for add_message and a thread_data without them for run_thread/run_thread_stream/get_messages, which no longer receive the spurious message fields. * test(overhead): assert mock transport is exercised in non-streaming and stream tests --- tests/_live_test_helpers.py | 10 + tests/_vcr_conftest_common.py | 19 + tests/litellm_utils_tests/conftest.py | 27 +- .../test_aws_secret_manager.py | 11 +- .../test_litellm_overhead.py | 342 +++++----- tests/llm_translation/base_llm_unit_tests.py | 5 + tests/llm_translation/conftest.py | 8 +- .../test_bedrock_completion.py | 5 + .../test_bedrock_invoke_tests.py | 10 +- tests/local_testing/conftest.py | 3 - tests/local_testing/test_assistants.py | 601 ++++++++++-------- tests/logging_callback_tests/conftest.py | 9 +- .../test_amazing_s3_logs.py | 58 +- tests/ocr_tests/conftest.py | 22 +- tests/ocr_tests/test_ocr_vertex_ai.py | 8 + tests/pass_through_tests/test_vertex.test.js | 18 +- tests/pass_through_tests/test_vertex_ai.py | 17 +- .../test_vertex_with_spend.test.js | 18 +- .../pass_through_tests/vertex_test_helpers.js | 27 + ..._anthropic_messages_prompt_caching_test.py | 15 +- tests/pass_through_unit_tests/conftest.py | 11 +- 21 files changed, 702 insertions(+), 542 deletions(-) create mode 100644 tests/_live_test_helpers.py create mode 100644 tests/pass_through_tests/vertex_test_helpers.js diff --git a/tests/_live_test_helpers.py b/tests/_live_test_helpers.py new file mode 100644 index 00000000000..a79b81e82c1 --- /dev/null +++ b/tests/_live_test_helpers.py @@ -0,0 +1,10 @@ +import os + +import pytest + + +def _skip_live_prompt_caching_test(): + if os.environ.get("LITELLM_RUN_LIVE_PROMPT_CACHING_TESTS") != "1": + pytest.skip("Live prompt-caching E2E tests are opt-in") + if os.environ.get("CASSETTE_REDIS_URL"): + pytest.skip("Live prompt-caching E2E tests cannot run under VCR replay") diff --git a/tests/_vcr_conftest_common.py b/tests/_vcr_conftest_common.py index 995c333ad0e..4d5a73779ea 100644 --- a/tests/_vcr_conftest_common.py +++ b/tests/_vcr_conftest_common.py @@ -1930,6 +1930,25 @@ def emit_vcr_classification_summary(terminalreporter) -> None: continue terminalreporter.write_line(f" [{verdict}] {n}") + leak_verdicts = ( + VERDICT_PARTIAL, + VERDICT_MISS_OVERFLOW, + VERDICT_MISS_NOT_PERSISTED, + VERDICT_UNMARKED_LIVE_CALL, + ) + leak_counts = {verdict: counts.get(verdict, 0) for verdict in leak_verdicts} + total_leaks = sum(leak_counts.values()) + terminalreporter.write_sep("-", "VCR COST LEAK CHECK", bold=True) + if total_leaks: + rendered = ", ".join( + f"{verdict}={count}" for verdict, count in leak_counts.items() if count + ) + terminalreporter.write_line(f" FAIL: {rendered}") + else: + terminalreporter.write_line( + " PASS: no overflow, partial, not-persisted, or unmarked live-call verdicts" + ) + overflow = snapshot["overflow_tests"] if overflow: terminalreporter.write_sep( diff --git a/tests/litellm_utils_tests/conftest.py b/tests/litellm_utils_tests/conftest.py index d20203da3a7..68c281a045f 100644 --- a/tests/litellm_utils_tests/conftest.py +++ b/tests/litellm_utils_tests/conftest.py @@ -28,32 +28,9 @@ from tests._vcr_conftest_common import ( # noqa: E402,F401 _verbose_state = VerboseReporterState() +_VCR_INCOMPATIBLE_FILES = frozenset() -# Files where VCR replay breaks the test: -# - ``test_litellm_overhead.py``: asserts overhead/total < 40%, which -# inverts when cached replay collapses the upstream time to microseconds. -_VCR_INCOMPATIBLE_FILES = frozenset( - { - "test_litellm_overhead.py", - } -) - -# AWS Secrets Manager resource-lifecycle tests. Each run creates a secret -# under a per-run unique name (``litellm_test_``) and either asserts the -# API response echoes that exact unique name or reads it straight back. The -# name *must* be unique per run because AWS enforces a >=7-day deletion -# recovery window — a fixed name can't be re-created on the daily VCR -# re-record. Deterministic replay returns the previously-recorded (different) -# name, so the unique-name round-trip cannot be reproduced offline. The -# config-parsing tests in the same file (settings / STS endpoint) make no such -# unique-resource calls and stay VCR-cached. -_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = ( - "::test_write_and_read_simple_secret", - "::test_write_and_read_json_secret", - "::test_read_nonexistent_secret", - "::test_primary_secret_functionality", - "::test_write_secret_with_description_and_tags", -) +_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = () @pytest.fixture(scope="function", autouse=True) diff --git a/tests/litellm_utils_tests/test_aws_secret_manager.py b/tests/litellm_utils_tests/test_aws_secret_manager.py index 674f9b3ca82..46e8d004534 100644 --- a/tests/litellm_utils_tests/test_aws_secret_manager.py +++ b/tests/litellm_utils_tests/test_aws_secret_manager.py @@ -10,7 +10,6 @@ from dotenv import load_dotenv import litellm.types import litellm.types.utils - load_dotenv() import io @@ -52,6 +51,11 @@ def skip_on_throttling(func): def check_aws_credentials(): """Helper function to check if AWS credentials are set""" + if os.getenv("LITELLM_RUN_LIVE_AWS_SECRET_MANAGER_TESTS") != "1": + pytest.skip("Live AWS Secrets Manager E2E tests are opt-in") + if os.getenv("CASSETTE_REDIS_URL"): + pytest.skip("Live AWS Secrets Manager E2E tests cannot run under VCR replay") + required_vars = ["AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", "AWS_REGION_NAME"] missing_vars = [var for var in required_vars if not os.getenv(var)] if missing_vars: @@ -444,6 +448,11 @@ async def test_end_to_end_iam_role_secret_write(): - TEST_IAM_ROLE_ARN environment variable with ARN of a role that can be assumed - Proper AWS credentials configured (via instance profile, IAM role, or environment) """ + if os.getenv("LITELLM_RUN_LIVE_AWS_SECRET_MANAGER_TESTS") != "1": + pytest.skip("Live AWS Secrets Manager E2E tests are opt-in") + if os.getenv("CASSETTE_REDIS_URL"): + pytest.skip("Live AWS Secrets Manager E2E tests cannot run under VCR replay") + # Skip if TEST_IAM_ROLE_ARN is not set test_role_arn = os.getenv("TEST_IAM_ROLE_ARN") if not test_role_arn: diff --git a/tests/litellm_utils_tests/test_litellm_overhead.py b/tests/litellm_utils_tests/test_litellm_overhead.py index 3a428e9d588..95c376c24ff 100644 --- a/tests/litellm_utils_tests/test_litellm_overhead.py +++ b/tests/litellm_utils_tests/test_litellm_overhead.py @@ -1,237 +1,185 @@ +import asyncio import json -import os -import sys import time -from contextlib import asynccontextmanager, contextmanager -from datetime import datetime -from unittest.mock import AsyncMock, patch, MagicMock + import httpx import pytest -import asyncio -sys.path.insert( - 0, os.path.abspath("../..") -) # Adds the parent directory to the system path import litellm +OPENAI_API_BASE = "https://example.openai.test/v1" -# Fake Vertex AI Gemini response for mocking -FAKE_VERTEX_GEMINI_RESPONSE = { - "candidates": [ + +def _completion_payload(response_id="chatcmpl-test"): + return { + "id": response_id, + "object": "chat.completion", + "created": 1, + "model": "gpt-4o", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "Hello"}, + "finish_reason": "stop", + } + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, + } + + +def _stream_payload(response_id="chatcmpl-stream"): + chunks = [ { - "content": { - "parts": [{"text": "Hello! How can I help you today?"}], - "role": "model", - }, - "finishReason": "STOP", - } - ], - "usageMetadata": { - "promptTokenCount": 5, - "candidatesTokenCount": 8, - "totalTokenCount": 13, - }, -} + "id": response_id, + "object": "chat.completion.chunk", + "created": 1, + "model": "gpt-4o", + "choices": [ + { + "index": 0, + "delta": {"role": "assistant", "content": "Hello"}, + "finish_reason": None, + } + ], + }, + { + "id": response_id, + "object": "chat.completion.chunk", + "created": 1, + "model": "gpt-4o", + "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, + }, + ] + return ( + "".join(f"data: {json.dumps(chunk)}\n\n" for chunk in chunks) + + "data: [DONE]\n\n" + ).encode() -def _make_fake_httpx_response(url: str) -> httpx.Response: - """Create a fake httpx.Response that looks like a Vertex AI Gemini response.""" - response = httpx.Response( - status_code=200, - json=FAKE_VERTEX_GEMINI_RESPONSE, - request=httpx.Request("POST", url), +def _mock_openai_completion_transport( + monkeypatch, *, stream=False, response_id="chatcmpl-test" +): + from litellm.llms.custom_httpx.aiohttp_transport import LiteLLMAiohttpTransport + + calls = {"count": 0} + + async def delayed_response(_transport, request): + calls["count"] += 1 + await asyncio.sleep(0.2) + if stream: + return httpx.Response( + 200, + content=_stream_payload(response_id), + headers={"content-type": "text/event-stream"}, + request=request, + ) + return httpx.Response( + 200, json=_completion_payload(response_id), request=request + ) + + monkeypatch.setattr( + LiteLLMAiohttpTransport, + "handle_async_request", + delayed_response, ) - return response + return calls -@asynccontextmanager -async def _vertex_ai_mocks(): - """Context manager that mocks Vertex AI auth and HTTP calls. - - Mocks at the httpx.AsyncClient.send level so that the - @track_llm_api_timing decorator on AsyncHTTPHandler.post still runs, - preserving the overhead measurement. - """ - fake_response = _make_fake_httpx_response( - "https://fake-vertex-endpoint/v1/models/gemini-1.5-flash:generateContent" - ) - - async def fake_send(self, request, **kwargs): - await asyncio.sleep(0.2) # simulate ~200ms network latency - return fake_response - - with ( - patch( - "litellm.llms.vertex_ai.vertex_llm_base.VertexBase._ensure_access_token_async", - new_callable=AsyncMock, - return_value=("Bearer fake-token", "fake-project"), - ), - patch.object( - httpx.AsyncClient, - "send", - new=fake_send, - ), - ): - yield - - -@pytest.mark.asyncio -@pytest.mark.parametrize( - "model", - [ - "bedrock/mistral.mistral-7b-instruct-v0:2", - "openai/gpt-4o", - "openai/self_hosted", - "bedrock/anthropic.claude-3-5-haiku-20241022-v1:0", - "vertex_ai/gemini-1.5-flash", - ], -) -async def test_litellm_overhead_non_streaming(model): - """ - - Test we can see the litellm overhead and that it is less than 40% of the total request time - """ - - litellm._turn_on_debug() - start_time = datetime.now() - kwargs = { - "messages": [{"role": "user", "content": "Hello, world!"}], - "model": model, - } - ######################################################### - # Specific cases for models - ######################################################### - if model == "vertex_ai/gemini-1.5-flash": - kwargs["vertex_project"] = "fake-project" - kwargs["vertex_location"] = "us-central1" - if model == "openai/self_hosted": - kwargs["api_base"] = os.environ.get("FAKE_OPENAI_API_BASE") - - async def _run(): - return await litellm.acompletion(**kwargs) - - if model == "vertex_ai/gemini-1.5-flash": - async with _vertex_ai_mocks(): - response = await _run() - else: - response = await _run() - ######################################################### - # End of specific cases for models - ######################################################### - end_time = datetime.now() - total_time_ms = (end_time - start_time).total_seconds() * 1000 - print(response) - print(response._hidden_params) +def _assert_overhead_is_smaller_than_total(response, total_time_ms): litellm_overhead_ms = response._hidden_params["litellm_overhead_time_ms"] - # calculate percent of overhead caused by litellm overhead_percent = litellm_overhead_ms * 100 / total_time_ms - print("##########################\n") - print("total_time_ms", total_time_ms) - print("response litellm_overhead_ms", litellm_overhead_ms) - print("litellm overhead_percent {}%".format(overhead_percent)) - print("##########################\n") + assert litellm_overhead_ms > 0 assert litellm_overhead_ms < 1000 - - # latency overhead should be less than total request time - assert litellm_overhead_ms < (end_time - start_time).total_seconds() * 1000 - - # latency overhead should be under 40% of total request time + assert litellm_overhead_ms < total_time_ms assert overhead_percent < 40 - pass + +@pytest.fixture(autouse=True) +def reset_litellm_state(): + litellm.cache = None + litellm.success_callback = [] + litellm._async_success_callback = [] + litellm.failure_callback = [] + litellm.callbacks = [] + yield + litellm.cache = None + litellm.callbacks = [] @pytest.mark.asyncio -@pytest.mark.parametrize( - "model", - [ - "bedrock/mistral.mistral-7b-instruct-v0:2", - "openai/gpt-4o", - "bedrock/anthropic.claude-3-5-haiku-20241022-v1:0", - "openai/self_hosted", - ], -) -async def test_litellm_overhead_stream(model): +async def test_litellm_overhead_non_streaming(monkeypatch): + calls = _mock_openai_completion_transport( + monkeypatch, response_id="chatcmpl-non-stream" + ) - litellm._turn_on_debug() - start_time = datetime.now() - kwargs = { - "messages": [{"role": "user", "content": "Hello, world!"}], - "model": model, - "stream": True, - } - ######################################################### - # Specific cases for models - ######################################################### - if model == "openai/self_hosted": - kwargs["api_base"] = "https://exampleopenaiendpoint-production.up.railway.app/" - # warmup call for auth validation on vertex_ai models - await litellm.acompletion(**kwargs) + start_time = time.perf_counter() + response = await litellm.acompletion( + model="gpt-4o", + api_key="test-key", + api_base=OPENAI_API_BASE, + messages=[{"role": "user", "content": "Hello, world!"}], + ) + total_time_ms = (time.perf_counter() - start_time) * 1000 - response = await litellm.acompletion(**kwargs) - - async for chunk in response: - print() - - end_time = datetime.now() - total_time_ms = (end_time - start_time).total_seconds() * 1000 - print(response) - print(response._hidden_params) - litellm_overhead_ms = response._hidden_params["litellm_overhead_time_ms"] - # calculate percent of overhead caused by litellm - overhead_percent = litellm_overhead_ms * 100 / total_time_ms - print("##########################\n") - print("total_time_ms", total_time_ms) - print("response litellm_overhead_ms", litellm_overhead_ms) - print("litellm overhead_percent {}%".format(overhead_percent)) - print("##########################\n") - assert litellm_overhead_ms > 0 - assert litellm_overhead_ms < 1000 - - # latency overhead should be less than total request time - assert litellm_overhead_ms < (end_time - start_time).total_seconds() * 1000 - - # latency overhead should be under 40% of total request time - assert overhead_percent < 40 - - pass + assert calls["count"] == 1 + _assert_overhead_is_smaller_than_total(response, total_time_ms) @pytest.mark.asyncio -async def test_litellm_overhead_cache_hit(): - """ - Test that litellm overhead is tracked on cache hits. - Makes two identical requests and checks that the second one (cache hit) has overhead in hidden params. - """ +async def test_litellm_overhead_stream(monkeypatch): + calls = _mock_openai_completion_transport( + monkeypatch, stream=True, response_id="chatcmpl-stream" + ) + + start_time = time.perf_counter() + response = await litellm.acompletion( + model="gpt-4o", + api_key="test-key", + api_base=OPENAI_API_BASE, + messages=[{"role": "user", "content": "Hello, world!"}], + stream=True, + ) + + async for _chunk in response: + pass + + total_time_ms = (time.perf_counter() - start_time) * 1000 + + assert calls["count"] == 1 + _assert_overhead_is_smaller_than_total(response, total_time_ms) + + +@pytest.mark.asyncio +async def test_litellm_overhead_cache_hit(monkeypatch): from litellm.caching.caching import Cache - litellm._turn_on_debug() + calls = _mock_openai_completion_transport(monkeypatch, response_id="chatcmpl-cache") litellm.cache = Cache() - print("test2 for caching") - litellm.set_verbose = True + messages = [{"role": "user", "content": "Hello, world! Cache test"}] response1 = await litellm.acompletion( - model="gpt-4.1-nano", messages=messages, caching=True + model="gpt-4o", + api_key="test-key", + api_base=OPENAI_API_BASE, + messages=messages, + caching=True, ) - await asyncio.sleep(2) - # Wait for any pending background tasks to complete - pending_tasks = [task for task in asyncio.all_tasks() if not task.done()] - print("all pending tasks", pending_tasks) - if pending_tasks: - await asyncio.wait(pending_tasks, timeout=1.0) - + await asyncio.sleep(0.5) response2 = await litellm.acompletion( - model="gpt-4.1-nano", messages=messages, caching=True + model="gpt-4o", + api_key="test-key", + api_base=OPENAI_API_BASE, + messages=messages, + caching=True, ) - print("RESPONSE 1", response1) - print("RESPONSE 2", response2) + + assert calls["count"] == 1 assert response1.id == response2.id - - print("response 2 hidden params", response2._hidden_params) - assert "_response_ms" in response2._hidden_params - total_time_ms = response2._hidden_params["_response_ms"] + assert response2._hidden_params["litellm_overhead_time_ms"] > 0 assert ( - response2._hidden_params["litellm_overhead_time_ms"] > 0 - and response2._hidden_params["litellm_overhead_time_ms"] < total_time_ms + response2._hidden_params["litellm_overhead_time_ms"] + < response2._hidden_params["_response_ms"] ) diff --git a/tests/llm_translation/base_llm_unit_tests.py b/tests/llm_translation/base_llm_unit_tests.py index 77850dac457..fef1d23d867 100644 --- a/tests/llm_translation/base_llm_unit_tests.py +++ b/tests/llm_translation/base_llm_unit_tests.py @@ -30,6 +30,10 @@ from litellm.types.utils import Usage, ModelResponse from abc import ABC, abstractmethod from openai import OpenAI +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))) + +from tests._live_test_helpers import _skip_live_prompt_caching_test # noqa: E402 + def _usage_format_tests(usage: litellm.Usage): """ @@ -960,6 +964,7 @@ class BaseLLMChatTest(ABC): @pytest.mark.flaky(retries=4, delay=1) def test_prompt_caching(self): + _skip_live_prompt_caching_test() print("test_prompt_caching") litellm.set_verbose = True from litellm.utils import supports_prompt_caching diff --git a/tests/llm_translation/conftest.py b/tests/llm_translation/conftest.py index d346dae4308..dba3812ee1c 100644 --- a/tests/llm_translation/conftest.py +++ b/tests/llm_translation/conftest.py @@ -39,13 +39,7 @@ from tests._vcr_conftest_common import ( # noqa: E402,F401 # itself run under a live cassette context. _VCR_AUTO_MARKER_SKIP_FILES = frozenset({"test_vcr_redis_persister.py"}) -# Tests that observe live cross-call provider state (e.g. prompt-cache -# warm-up between two consecutive calls); replay can't reproduce that state. -_VCR_INCOMPATIBLE_NODEID_SUFFIXES = ( - "::test_prompt_caching", - "TestBedrockInvokeNovaJson::test_json_response_pydantic_obj", - "::test_bedrock_converse__streaming_passthrough", -) +_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = () _verbose_state = VerboseReporterState() diff --git a/tests/llm_translation/test_bedrock_completion.py b/tests/llm_translation/test_bedrock_completion.py index aecd7bc699a..9cf253c379d 100644 --- a/tests/llm_translation/test_bedrock_completion.py +++ b/tests/llm_translation/test_bedrock_completion.py @@ -3220,6 +3220,11 @@ async def test_bedrock_converse__streaming_passthrough(monkeypatch): from litellm.integrations.custom_logger import CustomLogger import asyncio + if os.environ.get("LITELLM_RUN_LIVE_BEDROCK_PASSTHROUGH_TESTS") != "1": + pytest.skip("Live Bedrock passthrough E2E tests are opt-in") + if os.environ.get("CASSETTE_REDIS_URL"): + pytest.skip("Live Bedrock passthrough E2E tests cannot run under VCR replay") + class MockCustomLogger(CustomLogger): pass diff --git a/tests/llm_translation/test_bedrock_invoke_tests.py b/tests/llm_translation/test_bedrock_invoke_tests.py index 23f436d5b28..901b43542f7 100644 --- a/tests/llm_translation/test_bedrock_invoke_tests.py +++ b/tests/llm_translation/test_bedrock_invoke_tests.py @@ -3,7 +3,6 @@ import pytest import sys import os - sys.path.insert( 0, os.path.abspath("../..") ) # Adds the parent directory to the system path @@ -41,6 +40,15 @@ class TestBedrockInvokeNovaJson(BaseLLMChatTest): f"Skipping non-JSON test: {request.function.__name__} does not contain 'json'" ) + def test_json_response_pydantic_obj(self): + if os.environ.get("LITELLM_RUN_LIVE_BEDROCK_NOVA_JSON_TESTS") != "1": + pytest.skip("Live Bedrock Nova response-schema E2E tests are opt-in") + if os.environ.get("CASSETTE_REDIS_URL"): + pytest.skip( + "Live Bedrock Nova response-schema E2E tests cannot run under VCR replay" + ) + super().test_json_response_pydantic_obj() + def test_nova_invoke_remove_empty_system_messages(): """Test that _remove_empty_system_messages removes empty system list.""" diff --git a/tests/local_testing/conftest.py b/tests/local_testing/conftest.py index 0831313c136..d45caec22d8 100644 --- a/tests/local_testing/conftest.py +++ b/tests/local_testing/conftest.py @@ -57,13 +57,10 @@ from tests._vcr_conftest_common import ( # noqa: E402,F401 # blacklisting was masking valid cache opportunities. # Files where VCR replay breaks the test: -# - ``test_assistants.py``: polls fresh per-session run IDs that no cassette -# can match, so every CI run re-records and the suite times out. # - ``test_router_caching.py``: asserts upstream returns a *new* id per call, # which a deterministic cassette replay violates. _VCR_INCOMPATIBLE_FILES = frozenset( { - "test_assistants.py", "test_router_caching.py", } ) diff --git a/tests/local_testing/test_assistants.py b/tests/local_testing/test_assistants.py index ee1c8fb6518..8dc4f9e48e1 100644 --- a/tests/local_testing/test_assistants.py +++ b/tests/local_testing/test_assistants.py @@ -1,22 +1,13 @@ -# What is this? -## Unit Tests for OpenAI Assistants API -import json import os import sys -import traceback - -from dotenv import load_dotenv - -load_dotenv() -sys.path.insert( - 0, os.path.abspath("../..") -) # Adds the parent directory to the system path -import asyncio -import logging import pytest +from dotenv import load_dotenv from openai.types.beta.assistant import Assistant -from typing_extensions import override +from openai.types.beta.assistant_deleted import AssistantDeleted + +load_dotenv() +sys.path.insert(0, os.path.abspath("../..")) import litellm from litellm import create_thread, get_thread @@ -25,40 +16,264 @@ from litellm.llms.openai.openai import ( AsyncAssistantEventHandler, AsyncCursorPage, MessageData, - OpenAIAssistantsAPI, + OpenAIMessage as Message, + Run, + SyncCursorPage, + Thread, ) -from litellm.llms.openai.openai import OpenAIMessage as Message -from litellm.llms.openai.openai import SyncCursorPage, Thread -""" -V0 Scope: - -- Add Message -> `/v1/threads/{thread_id}/messages` -- Run Thread -> `/v1/threads/{thread_id}/run` -""" +ASSISTANT_INSTRUCTIONS = ( + "You are a personal math tutor. When asked a question, write and run Python " + "code to answer the question." +) +ASSISTANT_ID = "asst_test" +THREAD_ID = "thread_test" +MESSAGE_ID = "msg_test" +RUN_ID = "run_test" -def _add_azure_related_dynamic_params(data: dict) -> dict: - data["api_version"] = "2024-02-15-preview" - data["api_base"] = os.getenv("AZURE_AI_API_BASE") - data["api_key"] = os.getenv("AZURE_AI_API_KEY") +def _assistant(**overrides): + data = { + "id": ASSISTANT_ID, + "object": "assistant", + "created_at": 1, + "name": "Math Tutor", + "description": None, + "model": "gpt-4.1", + "instructions": ASSISTANT_INSTRUCTIONS, + "tools": [], + "metadata": {}, + "top_p": 1.0, + "temperature": 1.0, + "response_format": "auto", + } + data.update(overrides) + return Assistant(**data) + + +def _thread(thread_id=THREAD_ID): + return Thread(id=thread_id, object="thread", created_at=1, metadata={}) + + +def _message(thread_id=THREAD_ID): + return Message( + id=MESSAGE_ID, + object="thread.message", + created_at=1, + thread_id=thread_id, + role="user", + content=[ + { + "type": "text", + "text": {"value": "Hey, how's it going?", "annotations": []}, + } + ], + assistant_id=None, + run_id=None, + attachments=[], + metadata={}, + status="completed", + ) + + +def _run(thread_id=THREAD_ID, assistant_id=ASSISTANT_ID): + return Run( + id=RUN_ID, + object="thread.run", + created_at=1, + assistant_id=assistant_id, + thread_id=thread_id, + status="completed", + started_at=1, + expires_at=None, + cancelled_at=None, + failed_at=None, + completed_at=1, + last_error=None, + model="gpt-4.1", + instructions=ASSISTANT_INSTRUCTIONS, + tools=[], + metadata={}, + usage={"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, + required_action=None, + incomplete_details=None, + temperature=1.0, + top_p=1.0, + max_prompt_tokens=None, + max_completion_tokens=None, + truncation_strategy={"type": "auto", "last_messages": None}, + response_format="auto", + tool_choice="auto", + parallel_tool_calls=True, + ) + + +def _sync_page(data): + first_id = data[0].id if data else None + return SyncCursorPage( + data=data, + object="list", + first_id=first_id, + last_id=first_id, + has_more=False, + ) + + +def _async_page(data): + first_id = data[0].id if data else None + return AsyncCursorPage( + data=data, + object="list", + first_id=first_id, + last_id=first_id, + has_more=False, + ) + + +class _FakeAssistantEventHandler(AssistantEventHandler): + def until_done(self): + return None + + +class _FakeAsyncAssistantEventHandler(AsyncAssistantEventHandler): + async def until_done(self): + return None + + +class _FakeAssistantStream: + def __enter__(self): + return _FakeAssistantEventHandler() + + def __exit__(self, exc_type, exc, tb): + return False + + +class _FakeAsyncAssistantStream: + async def __aenter__(self): + return _FakeAsyncAssistantEventHandler() + + async def __aexit__(self, exc_type, exc, tb): + return False + + +class _SyncAssistants: + def list(self, **_kwargs): + return _sync_page([_assistant()]) + + def create(self, **kwargs): + return _assistant(**kwargs) + + def delete(self, assistant_id): + return AssistantDeleted( + id=assistant_id, object="assistant.deleted", deleted=True + ) + + +class _AsyncAssistants: + async def list(self, **_kwargs): + return _async_page([_assistant()]) + + async def create(self, **kwargs): + return _assistant(**kwargs) + + async def delete(self, assistant_id): + return AssistantDeleted( + id=assistant_id, object="assistant.deleted", deleted=True + ) + + +class _SyncMessages: + def create(self, thread_id, **_kwargs): + return _message(thread_id) + + def list(self, thread_id): + return _sync_page([_message(thread_id)]) + + +class _AsyncMessages: + async def create(self, thread_id, **_kwargs): + return _message(thread_id) + + async def list(self, thread_id): + return _async_page([_message(thread_id)]) + + +class _SyncRuns: + def create_and_poll(self, thread_id, assistant_id, **_kwargs): + return _run(thread_id=thread_id, assistant_id=assistant_id) + + def stream(self, **_kwargs): + return _FakeAssistantStream() + + +class _AsyncRuns: + async def create_and_poll(self, thread_id, assistant_id, **_kwargs): + return _run(thread_id=thread_id, assistant_id=assistant_id) + + def stream(self, **_kwargs): + return _FakeAsyncAssistantStream() + + +class _SyncThreads: + def __init__(self): + self.messages = _SyncMessages() + self.runs = _SyncRuns() + + def create(self, **_kwargs): + return _thread() + + def retrieve(self, thread_id): + return _thread(thread_id) + + +class _AsyncThreads: + def __init__(self): + self.messages = _AsyncMessages() + self.runs = _AsyncRuns() + + async def create(self, **_kwargs): + return _thread() + + async def retrieve(self, thread_id): + return _thread(thread_id) + + +class _FakeBeta: + def __init__(self, *, async_mode): + self.assistants = _AsyncAssistants() if async_mode else _SyncAssistants() + self.threads = _AsyncThreads() if async_mode else _SyncThreads() + + +class _FakeAssistantClient: + def __init__(self, *, async_mode): + self.beta = _FakeBeta(async_mode=async_mode) + + +@pytest.fixture +def assistant_client(sync_mode): + return _FakeAssistantClient(async_mode=not sync_mode) + + +def _request_data(provider, assistant_client, **kwargs): + data = {"custom_llm_provider": provider, "client": assistant_client, **kwargs} + if provider == "azure": + data.update( + { + "api_version": "2024-02-15-preview", + "api_base": "https://example.azure.test", + "api_key": "test-key", + } + ) return data @pytest.mark.parametrize("provider", ["openai", "azure"]) -@pytest.mark.parametrize( - "sync_mode", - [True, False], -) +@pytest.mark.parametrize("sync_mode", [True, False]) @pytest.mark.asyncio -async def test_get_assistants(provider, sync_mode): - data = { - "custom_llm_provider": provider, - } - if provider == "azure": - data = _add_azure_related_dynamic_params(data) +async def test_get_assistants(provider, sync_mode, assistant_client): + data = _request_data(provider, assistant_client) - if sync_mode == True: + if sync_mode: assistants = litellm.get_assistants(**data) assert isinstance(assistants, SyncCursorPage) else: @@ -67,276 +282,152 @@ async def test_get_assistants(provider, sync_mode): @pytest.mark.parametrize("provider", ["azure", "openai"]) -@pytest.mark.parametrize( - "sync_mode", - [True, False], -) +@pytest.mark.parametrize("sync_mode", [True, False]) @pytest.mark.asyncio() -@pytest.mark.flaky(retries=3, delay=1) -async def test_create_delete_assistants(provider, sync_mode): - litellm.ssl_verify = False - litellm._turn_on_debug() - data = { - "custom_llm_provider": provider, - "model": "gpt-4.1", - "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.", - "name": "Math Tutor", - "tools": [{"type": "code_interpreter"}], - } - if provider == "azure": - data = _add_azure_related_dynamic_params(data) +async def test_create_delete_assistants(provider, sync_mode, assistant_client): + data = _request_data( + provider, + assistant_client, + model="gpt-4.1", + instructions=ASSISTANT_INSTRUCTIONS, + name="Math Tutor", + tools=[{"type": "code_interpreter"}], + ) - if sync_mode == True: + if sync_mode: assistant = litellm.create_assistants(**data) - - print("New assistants", assistant) assert isinstance(assistant, Assistant) - assert ( - assistant.instructions - == "You are a personal math tutor. When asked a question, write and run Python code to answer the question." - ) + assert assistant.instructions == ASSISTANT_INSTRUCTIONS assert assistant.id is not None - # delete the created assistant - delete_data = { - "custom_llm_provider": provider, - "assistant_id": assistant.id, - } - if provider == "azure": - delete_data = _add_azure_related_dynamic_params(delete_data) - response = litellm.delete_assistant(**delete_data) - print("Response deleting assistant", response) + response = litellm.delete_assistant( + **_request_data( + provider, + assistant_client, + assistant_id=assistant.id, + ) + ) assert response.id == assistant.id else: assistant = await litellm.acreate_assistants(**data) - print("New assistants", assistant) assert isinstance(assistant, Assistant) - assert ( - assistant.instructions - == "You are a personal math tutor. When asked a question, write and run Python code to answer the question." - ) + assert assistant.instructions == ASSISTANT_INSTRUCTIONS assert assistant.id is not None - # delete the created assistant - delete_data = { - "custom_llm_provider": provider, - "assistant_id": assistant.id, - } - if provider == "azure": - delete_data = _add_azure_related_dynamic_params(delete_data) - response = await litellm.adelete_assistant(**delete_data) - print("Response deleting assistant", response) + response = await litellm.adelete_assistant( + **_request_data( + provider, + assistant_client, + assistant_id=assistant.id, + ) + ) assert response.id == assistant.id -@pytest.mark.parametrize("provider", ["openai", "azure"]) -@pytest.mark.parametrize("sync_mode", [True, False]) -@pytest.mark.asyncio -async def test_create_thread_litellm(sync_mode, provider) -> Thread: +async def _create_thread_litellm(sync_mode, provider, assistant_client) -> Thread: message: MessageData = {"role": "user", "content": "Hey, how's it going?"} # type: ignore - data = { - "custom_llm_provider": provider, - "message": [message], - } - if provider == "azure": - data = _add_azure_related_dynamic_params(data) + data = _request_data(provider, assistant_client, message=[message]) if sync_mode: new_thread = create_thread(**data) else: new_thread = await litellm.acreate_thread(**data) - assert isinstance( - new_thread, Thread - ), f"type of thread={type(new_thread)}. Expected Thread-type" - + assert isinstance(new_thread, Thread) return new_thread @pytest.mark.parametrize("provider", ["openai", "azure"]) @pytest.mark.parametrize("sync_mode", [True, False]) @pytest.mark.asyncio -async def test_get_thread_litellm(provider, sync_mode): - new_thread = test_create_thread_litellm(sync_mode, provider) +async def test_create_thread_litellm(sync_mode, provider, assistant_client): + await _create_thread_litellm(sync_mode, provider, assistant_client) - if asyncio.iscoroutine(new_thread): - _new_thread = await new_thread - else: - _new_thread = new_thread - data = { - "custom_llm_provider": provider, - "thread_id": _new_thread.id, - } - if provider == "azure": - data = _add_azure_related_dynamic_params(data) +@pytest.mark.parametrize("provider", ["openai", "azure"]) +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +async def test_get_thread_litellm(provider, sync_mode, assistant_client): + new_thread = await _create_thread_litellm(sync_mode, provider, assistant_client) + data = _request_data(provider, assistant_client, thread_id=new_thread.id) if sync_mode: received_thread = get_thread(**data) else: received_thread = await litellm.aget_thread(**data) - assert isinstance( - received_thread, Thread - ), f"type of thread={type(received_thread)}. Expected Thread-type" - return new_thread + assert isinstance(received_thread, Thread) @pytest.mark.parametrize("provider", ["openai", "azure"]) @pytest.mark.parametrize("sync_mode", [True, False]) @pytest.mark.asyncio -async def test_add_message_litellm(sync_mode, provider): +async def test_add_message_litellm(sync_mode, provider, assistant_client): + new_thread = await _create_thread_litellm(sync_mode, provider, assistant_client) message: MessageData = {"role": "user", "content": "Hey, how's it going?"} # type: ignore - new_thread = test_create_thread_litellm(sync_mode, provider) + data = _request_data(provider, assistant_client, thread_id=new_thread.id, **message) - if asyncio.iscoroutine(new_thread): - _new_thread = await new_thread - else: - _new_thread = new_thread - # add message to thread - message: MessageData = {"role": "user", "content": "Hey, how's it going?"} # type: ignore - - data = {"custom_llm_provider": provider, "thread_id": _new_thread.id, **message} - if provider == "azure": - data = _add_azure_related_dynamic_params(data) if sync_mode: added_message = litellm.add_message(**data) else: added_message = await litellm.a_add_message(**data) - print(f"added message: {added_message}") - assert isinstance(added_message, Message) -@pytest.mark.parametrize( - "provider", - [ - "azure", - "openai", - ], -) # -@pytest.mark.parametrize( - "sync_mode", - [ - True, - False, - ], -) -@pytest.mark.parametrize( - "is_streaming", - [True, False], -) # +@pytest.mark.parametrize("provider", ["azure", "openai"]) +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.parametrize("is_streaming", [True, False]) @pytest.mark.asyncio -@pytest.mark.flaky(retries=3, delay=1) -async def test_aarun_thread_litellm(sync_mode, provider, is_streaming): - """ - - Get Assistants - - Create thread - - Create run w/ Assistants + Thread - """ - import openai +async def test_aarun_thread_litellm( + sync_mode, provider, is_streaming, assistant_client +): + get_assistants_data = _request_data(provider, assistant_client) + if sync_mode: + assistants = litellm.get_assistants(**get_assistants_data) + else: + assistants = await litellm.aget_assistants(**get_assistants_data) - try: - get_assistants_data = { - "custom_llm_provider": provider, - } - if provider == "azure": - get_assistants_data = _add_azure_related_dynamic_params(get_assistants_data) - if sync_mode: - assistants = litellm.get_assistants(**get_assistants_data) + assistant_id = assistants.data[0].id + new_thread = await _create_thread_litellm(sync_mode, provider, assistant_client) + message: MessageData = {"role": "user", "content": "Hey, how's it going?"} # type: ignore + thread_data = _request_data(provider, assistant_client, thread_id=new_thread.id) + message_data = _request_data( + provider, assistant_client, thread_id=new_thread.id, **message + ) + + if sync_mode: + added_message = litellm.add_message(**message_data) + assert isinstance(added_message, Message) + + if is_streaming: + run = litellm.run_thread_stream(assistant_id=assistant_id, **thread_data) + with run as run: + assert isinstance(run, AssistantEventHandler) + run.until_done() else: - assistants = await litellm.aget_assistants(**get_assistants_data) + run = litellm.run_thread( + assistant_id=assistant_id, stream=is_streaming, **thread_data + ) + assert run.status == "completed" + messages = litellm.get_messages(**thread_data) + assert isinstance(messages.data[0], Message) + else: + added_message = await litellm.a_add_message(**message_data) + assert isinstance(added_message, Message) - ## get the first assistant ### - try: - assistant_id = assistants.data[0].id - except IndexError: - pytest.skip("No assistants found") - - new_thread = test_create_thread_litellm(sync_mode=sync_mode, provider=provider) - - if asyncio.iscoroutine(new_thread): - _new_thread = await new_thread + if is_streaming: + run = litellm.arun_thread_stream(assistant_id=assistant_id, **thread_data) + async with run as run: + assert isinstance(run, AsyncAssistantEventHandler) + await run.until_done() else: - _new_thread = new_thread - - thread_id = _new_thread.id - - # add message to thread - message: MessageData = {"role": "user", "content": "Hey, how's it going?"} # type: ignore - - data = {"custom_llm_provider": provider, "thread_id": _new_thread.id, **message} - if provider == "azure": - data = _add_azure_related_dynamic_params(data) - - if sync_mode: - added_message = litellm.add_message(**data) - - if is_streaming: - run = litellm.run_thread_stream(assistant_id=assistant_id, **data) - with run as run: - assert isinstance(run, AssistantEventHandler) - print(run) - run.until_done() - else: - run = litellm.run_thread( - assistant_id=assistant_id, stream=is_streaming, **data - ) - if run.status == "completed": - messages = litellm.get_messages( - thread_id=_new_thread.id, custom_llm_provider=provider - ) - assert isinstance(messages.data[0], Message) - elif ( - run.status == "failed" - and run.last_error - and "No connection matching model" in run.last_error.message - ): - pytest.skip(f"Azure deployment not found: {run.last_error.message}") - else: - pytest.fail( - "An unexpected error occurred when running the thread, {}".format( - run - ) - ) - - else: - added_message = await litellm.a_add_message(**data) - - if is_streaming: - run = litellm.arun_thread_stream(assistant_id=assistant_id, **data) - async with run as run: - print(f"run: {run}") - assert isinstance( - run, - AsyncAssistantEventHandler, - ) - print(run) - await run.until_done() - else: - run = await litellm.arun_thread( - custom_llm_provider=provider, - thread_id=thread_id, - assistant_id=assistant_id, - ) - - if run.status == "completed": - messages = await litellm.aget_messages( - thread_id=_new_thread.id, custom_llm_provider=provider - ) - assert isinstance(messages.data[0], Message) - elif ( - run.status == "failed" - and run.last_error - and "No connection matching model" in run.last_error.message - ): - pytest.skip(f"Azure deployment not found: {run.last_error.message}") - else: - pytest.fail( - "An unexpected error occurred when running the thread, {}".format( - run - ) - ) - except openai.APIError as e: - pass + run = await litellm.arun_thread( + custom_llm_provider=provider, + thread_id=new_thread.id, + assistant_id=assistant_id, + client=assistant_client, + ) + assert run.status == "completed" + messages = await litellm.aget_messages(**thread_data) + assert isinstance(messages.data[0], Message) diff --git a/tests/logging_callback_tests/conftest.py b/tests/logging_callback_tests/conftest.py index 6dde85f2ca7..dedff9a5aee 100644 --- a/tests/logging_callback_tests/conftest.py +++ b/tests/logging_callback_tests/conftest.py @@ -42,14 +42,7 @@ _RESPX_CONFLICTING_FILES = frozenset( } ) -# Files where VCR replay breaks the test: -# - ``test_amazing_s3_logs.py``: vcrpy's boto3 stub intercepts a real S3 -# PUT/LIST round-trip the test asserts on, so the per-run id is never found. -_VCR_INCOMPATIBLE_FILES = frozenset( - { - "test_amazing_s3_logs.py", - } -) +_VCR_INCOMPATIBLE_FILES = frozenset() _VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = () diff --git a/tests/logging_callback_tests/test_amazing_s3_logs.py b/tests/logging_callback_tests/test_amazing_s3_logs.py index dab2a0cc0b9..08b9ac7d01a 100644 --- a/tests/logging_callback_tests/test_amazing_s3_logs.py +++ b/tests/logging_callback_tests/test_amazing_s3_logs.py @@ -1,6 +1,7 @@ import sys import os import io, asyncio +from collections import defaultdict # import logging # logging.basicConfig(level=logging.DEBUG) @@ -18,6 +19,60 @@ from litellm._logging import verbose_logger import logging +class _FakeS3Paginator: + def __init__(self, objects): + self.objects = objects + + def paginate(self, Bucket): + keys = sorted(self.objects[Bucket]) + if not keys: + return [{}] + return [{"Contents": [{"Key": key} for key in keys]}] + + +class _FakeS3Client: + def __init__(self): + self.objects = defaultdict(dict) + + def clear(self): + self.objects.clear() + + def put_object(self, Bucket, Key, Body, **_kwargs): + self.objects[Bucket][Key] = Body + return {"ResponseMetadata": {"HTTPStatusCode": 200}} + + def delete_object(self, Bucket, Key): + self.objects[Bucket].pop(Key, None) + return {"ResponseMetadata": {"HTTPStatusCode": 204}} + + def get_paginator(self, name): + assert name == "list_objects_v2" + return _FakeS3Paginator(self.objects) + + def list_objects(self, Bucket): + keys = sorted(self.objects[Bucket]) + return {"Contents": [{"Key": key, "LastModified": 0} for key in keys]} + + +_FAKE_S3_CLIENT = _FakeS3Client() + + +@pytest.fixture(autouse=True) +def fake_s3_client(monkeypatch): + _FAKE_S3_CLIENT.clear() + + def fake_boto3_client(service_name, *args, **kwargs): + assert service_name == "s3" + return _FAKE_S3_CLIENT + + monkeypatch.setattr(boto3, "client", fake_boto3_client) + litellm.success_callback = [] + litellm.callbacks = [] + yield _FAKE_S3_CLIENT + litellm.success_callback = [] + litellm.callbacks = [] + + @pytest.mark.asyncio @pytest.mark.parametrize( "sync_mode,streaming", [(True, True), (True, False), (False, True), (False, False)] @@ -172,6 +227,7 @@ async def test_basic_s3_v2_logging_failure(): model="gpt-5-mini", api_key="invalid-api-key", messages=[{"role": "user", "content": "This is a test"}], + mock_response=Exception("forced failure for S3 logging test"), ) except Exception as e: print(f"Expected error: {e}") @@ -407,7 +463,7 @@ from litellm.integrations.s3_v2 import S3Logger class TestS3Logger(S3Logger): def __init__(self, *args, **kwargs): self.recorded_requests = {} - self.logged_standard_logging_payload: Optional[StandardLoggingPayload] = None + self.logged_standard_logging_payload = None super().__init__(*args, **kwargs) async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): diff --git a/tests/ocr_tests/conftest.py b/tests/ocr_tests/conftest.py index 7a74dde3e41..09d535dee4b 100644 --- a/tests/ocr_tests/conftest.py +++ b/tests/ocr_tests/conftest.py @@ -26,27 +26,7 @@ from tests._vcr_conftest_common import ( # noqa: E402,F401 vcr_config_dict, ) -# Vertex AI MaaS Mistral OCR tests that cannot be VCR-cached in CI. -# -# ``vertex_ai/mistral-ocr-2505`` is a Model-as-a-Service partner model that -# must be explicitly enabled in the GCP project's Model Garden. It is not -# provisioned in the CI project (``litellm-ci-cd``), so the live -# ``:rawPredict`` call fails on every run and ``BaseOCRTest`` catches the -# provider error and skips. Because the doomed live call is recorded but the -# test then skips, the persister refuses to save it (skipped tests don't -# persist) and the cassette is never seeded — so the test re-records live and -# is classified MISS:NOT_PERSISTED on every single run, forever. No cassette -# can be recorded until the model is provisioned. Mark the tests VCR- -# incompatible so they are honestly accounted as live calls (UNMARKED:LIVE_CALL) -# rather than phantom cache misses; behaviour is unchanged (they still run and -# still skip on the provider error). The sibling direct-Mistral and Azure OCR -# tests replay from cache normally and are unaffected. Remove these entries if -# the MaaS model is enabled in the CI project. -_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = ( - "test_ocr_vertex_ai.py::TestVertexAIMistralOCR::test_ocr_response_structure", - "test_ocr_vertex_ai.py::TestVertexAIMistralOCR::test_basic_ocr_with_url[True]", - "test_ocr_vertex_ai.py::TestVertexAIMistralOCR::test_basic_ocr_with_url[False]", -) +_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = () _verbose_state = VerboseReporterState() diff --git a/tests/ocr_tests/test_ocr_vertex_ai.py b/tests/ocr_tests/test_ocr_vertex_ai.py index 1b58b955de6..1ba5b9d0883 100644 --- a/tests/ocr_tests/test_ocr_vertex_ai.py +++ b/tests/ocr_tests/test_ocr_vertex_ai.py @@ -62,6 +62,14 @@ class TestVertexAIMistralOCR(BaseOCRTest): sending to the API, since Vertex AI OCR endpoint doesn't have internet access. """ + def setup_method(self): + if os.environ.get("LITELLM_RUN_LIVE_VERTEX_MISTRAL_OCR_TESTS") != "1": + pytest.skip("Live Vertex AI Mistral OCR E2E tests are opt-in") + if os.environ.get("CASSETTE_REDIS_URL"): + pytest.skip( + "Live Vertex AI Mistral OCR E2E tests cannot run under VCR replay" + ) + def get_base_ocr_call_args(self) -> dict: """ Return the base OCR call args for Vertex AI Mistral OCR. diff --git a/tests/pass_through_tests/test_vertex.test.js b/tests/pass_through_tests/test_vertex.test.js index e0e879c2897..3663d35d192 100644 --- a/tests/pass_through_tests/test_vertex.test.js +++ b/tests/pass_through_tests/test_vertex.test.js @@ -8,6 +8,8 @@ const { writeFileSync } = require('fs'); // Import fetch if the SDK uses it const originalFetch = global.fetch || require('node-fetch'); +const { runVertexRequestOrSkip } = require('./vertex_test_helpers'); + // Monkey-patch the fetch used internally global.fetch = async function patchedFetch(url, options) { // Modify the URL to use HTTP instead of HTTPS @@ -89,7 +91,12 @@ describe('Vertex AI Tests', () => { contents: [{role: 'user', parts: [{text: 'How are you doing today tell me your name?'}]}], }; - const streamingResult = await generativeModel.generateContentStream(request); + const streamingResult = await runVertexRequestOrSkip(() => + generativeModel.generateContentStream(request) + ); + if (streamingResult === null) { + return; + } // Add some assertions expect(streamingResult).toBeDefined(); @@ -122,11 +129,16 @@ describe('Vertex AI Tests', () => { ); const request = {contents: [{role: 'user', parts: [{text: 'What is 2+2?'}]}]}; - const result = await generativeModel.generateContent(request); + const result = await runVertexRequestOrSkip(() => + generativeModel.generateContent(request) + ); + if (result === null) { + return; + } expect(result).toBeDefined(); expect(result.response).toBeDefined(); console.log('non-streaming response:', JSON.stringify(result.response)); }, VERTEX_TEST_TIMEOUT_MS ); -}); \ No newline at end of file +}); diff --git a/tests/pass_through_tests/test_vertex_ai.py b/tests/pass_through_tests/test_vertex_ai.py index bf1200489aa..0ac66b470c6 100644 --- a/tests/pass_through_tests/test_vertex_ai.py +++ b/tests/pass_through_tests/test_vertex_ai.py @@ -12,7 +12,6 @@ import os import pytest import asyncio - # Path to your service account JSON file SERVICE_ACCOUNT_FILE = "path/to/your/service-account.json" @@ -95,6 +94,15 @@ async def call_spend_logs_endpoint(): LITE_LLM_ENDPOINT = "http://localhost:4000" +def _is_vertex_quota_error(exc: Exception) -> bool: + message = str(exc) + return ( + "429" in message + or "Too Many Requests" in message + or "RESOURCE_EXHAUSTED" in message + ) + + @pytest.mark.asyncio() async def test_basic_vertex_ai_pass_through_with_spendlog(): @@ -109,7 +117,12 @@ async def test_basic_vertex_ai_pass_through_with_spendlog(): ) model = GenerativeModel(model_name="gemini-3.1-flash-lite") - response = model.generate_content("hi") + try: + response = model.generate_content("hi") + except Exception as exc: + if _is_vertex_quota_error(exc): + pytest.skip("Vertex AI quota exhausted") + raise print("response", response) diff --git a/tests/pass_through_tests/test_vertex_with_spend.test.js b/tests/pass_through_tests/test_vertex_with_spend.test.js index 4dee890dc78..5914908e66a 100644 --- a/tests/pass_through_tests/test_vertex_with_spend.test.js +++ b/tests/pass_through_tests/test_vertex_with_spend.test.js @@ -10,6 +10,8 @@ const originalFetch = global.fetch || require('node-fetch'); let lastCallId; +const { runVertexRequestOrSkip } = require('./vertex_test_helpers'); + // Monkey-patch the fetch used internally global.fetch = async function patchedFetch(url, options) { // Modify the URL to use HTTP instead of HTTPS @@ -93,7 +95,12 @@ describe('Vertex AI Tests', () => { contents: [{role: 'user', parts: [{text: 'Say "hello test" and nothing else'}]}] }; - const result = await generativeModel.generateContent(request); + const result = await runVertexRequestOrSkip(() => + generativeModel.generateContent(request) + ); + if (result === null) { + return; + } expect(result).toBeDefined(); // Use the captured callId @@ -152,7 +159,12 @@ describe('Vertex AI Tests', () => { contents: [{role: 'user', parts: [{text: 'Say "hello test" and nothing else'}]}] }; - const streamingResult = await generativeModel.generateContentStream(request); + const streamingResult = await runVertexRequestOrSkip(() => + generativeModel.generateContentStream(request) + ); + if (streamingResult === null) { + return; + } expect(streamingResult).toBeDefined(); @@ -198,4 +210,4 @@ describe('Vertex AI Tests', () => { expect(spendData[0].spend).toBeGreaterThan(0); expect(spendData[0].custom_llm_provider).toBe('vertex_ai'); }, 90000); -}); \ No newline at end of file +}); diff --git a/tests/pass_through_tests/vertex_test_helpers.js b/tests/pass_through_tests/vertex_test_helpers.js new file mode 100644 index 00000000000..d637f20f916 --- /dev/null +++ b/tests/pass_through_tests/vertex_test_helpers.js @@ -0,0 +1,27 @@ +function isVertexQuotaError(error) { + const message = [ + error && error.message, + error && error.stack, + error && error.cause && JSON.stringify(error.cause), + ].filter(Boolean).join('\n'); + + return ( + message.includes('429') || + message.includes('Too Many Requests') || + message.includes('RESOURCE_EXHAUSTED') + ); +} + +async function runVertexRequestOrSkip(requestFn) { + try { + return await requestFn(); + } catch (error) { + if (isVertexQuotaError(error)) { + console.warn('Vertex AI quota exhausted; skipping live provider assertions for this run'); + return null; + } + throw error; + } +} + +module.exports = { isVertexQuotaError, runVertexRequestOrSkip }; diff --git a/tests/pass_through_unit_tests/base_anthropic_messages_prompt_caching_test.py b/tests/pass_through_unit_tests/base_anthropic_messages_prompt_caching_test.py index 5fc4ecefb33..e8d14b00681 100644 --- a/tests/pass_through_unit_tests/base_anthropic_messages_prompt_caching_test.py +++ b/tests/pass_through_unit_tests/base_anthropic_messages_prompt_caching_test.py @@ -18,14 +18,15 @@ from abc import ABC, abstractmethod from typing import Any, Dict, List sys.path.insert(0, os.path.abspath("../../..")) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))) import pytest import litellm +from tests._live_test_helpers import _skip_live_prompt_caching_test # Large document for caching tests (needs 1024+ tokens for Claude models) -LARGE_DOCUMENT_FOR_CACHING = ( - """ +LARGE_DOCUMENT_FOR_CACHING = """ This is a comprehensive legal agreement between Party A and Party B. ARTICLE 1: DEFINITIONS @@ -77,9 +78,7 @@ ARTICLE 9: GENERAL PROVISIONS 9.5 Waiver of any provision shall not constitute ongoing waiver. IN WITNESS WHEREOF, the parties have executed this Agreement. -""" - * 8 -) # Repeat to ensure we have enough tokens (need 1024+ for Claude models) +""" * 8 # Repeat to ensure we have enough tokens (need 1024+ for Claude models) class BaseAnthropicMessagesPromptCachingTest(ABC): @@ -130,6 +129,7 @@ class BaseAnthropicMessagesPromptCachingTest(ABC): This validates that the cache_control field is being passed through correctly and the provider is creating a cache. """ + _skip_live_prompt_caching_test() litellm._turn_on_debug() messages = self.get_messages_with_cache_control() @@ -167,6 +167,7 @@ class BaseAnthropicMessagesPromptCachingTest(ABC): This validates that caching is working end-to-end. """ + _skip_live_prompt_caching_test() litellm._turn_on_debug() messages = self.get_messages_with_cache_control() @@ -207,6 +208,7 @@ class BaseAnthropicMessagesPromptCachingTest(ABC): """ E2E test: Prompt caching with system message should work. """ + _skip_live_prompt_caching_test() litellm._turn_on_debug() messages = [ @@ -268,6 +270,7 @@ class BaseAnthropicMessagesPromptCachingTest(ABC): This validates that cache_creation_input_tokens and cache_read_input_tokens are correctly returned in the streaming response's message_delta event. """ + _skip_live_prompt_caching_test() litellm._turn_on_debug() messages = self.get_messages_with_cache_control() @@ -365,6 +368,7 @@ class BaseAnthropicMessagesPromptCachingTest(ABC): """ E2E test: Second streaming call should return cache_read_input_tokens > 0. """ + _skip_live_prompt_caching_test() litellm._turn_on_debug() messages = self.get_messages_with_cache_control() @@ -443,6 +447,7 @@ class BaseAnthropicMessagesPromptCachingTest(ABC): didn't include cache fields in message_start, causing clients to think caching wasn't supported. """ + _skip_live_prompt_caching_test() litellm._turn_on_debug() messages = self.get_messages_with_cache_control() diff --git a/tests/pass_through_unit_tests/conftest.py b/tests/pass_through_unit_tests/conftest.py index 390e14b7f11..10615ddcb73 100644 --- a/tests/pass_through_unit_tests/conftest.py +++ b/tests/pass_through_unit_tests/conftest.py @@ -19,16 +19,7 @@ from tests._vcr_conftest_common import ( # noqa: E402,F401 vcr_config_dict, ) -# Tests that observe live cross-call provider state — typically a -# warm-up call followed by an assertion that the *second* call sees the -# upstream's prompt-cache (Anthropic / Bedrock prompt-caching). VCR's -# deterministic replay can't model this: both calls match the same -# cassette episode, so the second call returns the first call's -# pre-warmup response. Opt these out so they run live (no caching). -_VCR_INCOMPATIBLE_NODEID_SUFFIXES = ( - "::test_prompt_caching_returns_cache_read_tokens_on_second_call", - "::test_prompt_caching_streaming_second_call_returns_cache_read", -) +_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = () _verbose_state = VerboseReporterState() From 97ba7e1a30588b9bce87c9efc96b34bf2d1de375 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Wed, 3 Jun 2026 14:07:59 -0700 Subject: [PATCH 20/92] fix(key_generate): exempt UI/CLI session tokens from the budget ceiling for team keys (#29612) Non-admin users creating a team key through the UI were rejected with "max_budget cannot exceed the caller's own max_budget (0.25)". The request is authenticated by a UI/CLI session token whose max_budget is the per-session chat spend cap (max_ui_session_budget, default $0.25), and the delegated-authority budget ceiling (GHSA-q775-qw9r-2r4g) treated that cap as a delegation limit. Skip the ceiling only when a session token creates a team key (data.team_id set); that key's spend is bounded by the team budget at request time. Personal keys and every other non-admin caller keep the ceiling, so a session token cannot mint an arbitrary-budget personal key. --- .../key_management_endpoints.py | 9 ++ .../test_key_management_endpoints.py | 84 +++++++++++++++++++ 2 files changed, 93 insertions(+) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index cf90f0661b3..771f8287b6e 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -722,8 +722,17 @@ async def _common_key_generation_helper( # noqa: PLR0915 # Delegated-authority ceiling (GHSA-q775-qw9r-2r4g): a non-admin caller # with an explicit budget cannot grant a key a higher budget than their own. # Callers with max_budget=None (unlimited) can delegate any budget. + # A UI/CLI session token's max_budget is a per-session chat spend cap + # (max_ui_session_budget), not a delegation authority, so it is exempt only + # when creating a team key - that key's spend is bounded by the team budget + # at request time. Personal keys keep the ceiling; nothing else bounds them. + is_ui_session_team_key = ( + user_api_key_dict.team_id == UI_SESSION_TOKEN_TEAM_ID + and data.team_id is not None + ) if ( user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN.value + and not is_ui_session_team_key and _requested_max_budget is not None and user_api_key_dict.max_budget is not None and _requested_max_budget > user_api_key_dict.max_budget diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index cda22da6ebd..ca4a3f4fea0 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -11539,3 +11539,87 @@ async def test_ghsa_q775_admin_bypasses_budget_ceiling(): litellm_changed_by=None, ) assert result is not None + + +@pytest.mark.asyncio +async def test_ghsa_q775_ui_session_token_team_key_exempt_from_budget_ceiling(): + """ + Regression: a UI/CLI session token (team_id=litellm-dashboard) creating a + TEAM key (data.team_id set) is exempt from the delegated-authority ceiling. + The session max_budget is a per-session chat spend cap (max_ui_session_budget, + default $0.25), not a delegation authority, and the team key's spend is bounded + by the team budget at request time. This is the team-admin key-creation flow + blocked since v1.86.x. Calls the helper directly so the ceiling runs (mocking + out _common_key_generation_helper would mock out the check under test). + """ + from litellm.constants import UI_SESSION_TOKEN_TEAM_ID + + data = GenerateKeyRequest(max_budget=500, team_id="team-abc") + user_api_key_dict = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-ui-session", + user_id="user-1", + team_id=UI_SESSION_TOKEN_TEAM_ID, + max_budget=0.25, + ) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", AsyncMock()), + patch("litellm.proxy.proxy_server.user_api_key_cache", MagicMock()), + patch("litellm.proxy.proxy_server.llm_router", None), + patch("litellm.proxy.proxy_server.premium_user", False), + patch("litellm.proxy.proxy_server.litellm_proxy_admin_name", "default_user_id"), + ): + try: + await _common_key_generation_helper( + data=data, + user_api_key_dict=user_api_key_dict, + litellm_changed_by=None, + team_table=MagicMock(), + ) + except (HTTPException, ProxyException) as err: + msg = str(getattr(err, "detail", "")) + str(getattr(err, "message", "")) + assert ( + "cannot exceed" not in msg.lower() + ), "UI/CLI session token creating a team key must be exempt from the ceiling" + + +@pytest.mark.asyncio +async def test_ghsa_q775_ui_session_token_personal_key_still_capped(): + """ + Security regression for GHSA-q775: the session-token exemption must NOT extend + to personal keys. A UI/CLI session token (team_id=litellm-dashboard) creating a + key with no data.team_id is still bound by the ceiling; otherwise a session + token - or a leaked one, whose blast radius is the $0.25 chat cap - could mint + an arbitrary-budget personal key, the exact escalation GHSA-q775 closed. Unlike + a team key, nothing else bounds a personal key's spend. + """ + from litellm.constants import UI_SESSION_TOKEN_TEAM_ID + + data = GenerateKeyRequest(max_budget=500) + user_api_key_dict = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-ui-session", + user_id="user-1", + team_id=UI_SESSION_TOKEN_TEAM_ID, + max_budget=0.25, + ) + + mock_prisma_client = AsyncMock() + + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client), + patch("litellm.proxy.proxy_server.user_api_key_cache", MagicMock()), + patch("litellm.proxy.proxy_server.user_custom_key_generate", None), + ): + with pytest.raises((HTTPException, ProxyException)) as exc_info: + await generate_key_fn( + data=data, + user_api_key_dict=user_api_key_dict, + litellm_changed_by=None, + ) + err = exc_info.value + code = getattr(err, "status_code", None) or getattr(err, "code", None) + msg = str(getattr(err, "detail", "")) + str(getattr(err, "message", "")) + assert str(code) == "400" + assert "cannot exceed" in msg.lower() From 5ee526d78ee34a084d6c9ac7f83b98e4aaaef0c5 Mon Sep 17 00:00:00 2001 From: milan-berri Date: Thu, 4 Jun 2026 00:59:18 +0300 Subject: [PATCH 21/92] fix(realtime): allow null transcripts in stream logging payloads (#29625) Allow realtime event transcript fields to be nullable so GA conversation.item payloads with transcript=null don't fail logging normalization and suppress success callbacks. Co-authored-by: Cursor --- litellm/types/llms/openai.py | 4 +-- tests/test_litellm/test_cost_calculator.py | 38 ++++++++++++++++++++++ 2 files changed, 40 insertions(+), 2 deletions(-) diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py index 51e408f8c63..0c854d89bb1 100644 --- a/litellm/types/llms/openai.py +++ b/litellm/types/llms/openai.py @@ -1892,7 +1892,7 @@ class OpenAIRealtimeStreamResponseOutputItemContent(TypedDict, total=False): """The ID of the previous conversation item for reference""" text: str """The text content, used for 'input_text' / 'text' / 'output_text' content types""" - transcript: str + transcript: Optional[str] """The transcript content, used for 'input_audio' / 'audio' content types""" type: Literal[ "input_audio", @@ -1998,7 +1998,7 @@ class OpenAIRealtimeResponseContentPart(TypedDict, total=False): text: str """The text content, if type is 'text' or 'output_text'""" - transcript: str + transcript: Optional[str] """The transcript content, if type is 'audio' or 'output_audio'""" type: Union[ diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index d973f8b4542..3d45a3409d8 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -12,6 +12,7 @@ from pydantic import BaseModel import litellm from litellm.cost_calculator import ( + RealtimeAPITokenUsageProcessor, completion_cost, cost_per_token, handle_realtime_stream_cost_calculation, @@ -385,6 +386,43 @@ def test_handle_realtime_stream_cost_calculation(): assert cost == 0.0 # No usage, no cost +def test_realtime_logging_object_allows_null_transcript_in_conversation_item_added(): + results: OpenAIRealtimeStreamList = [ + { + "type": "conversation.item.added", + "event_id": "event_added", + "item": { + "id": "item_123", + "type": "message", + "role": "assistant", + "status": "in_progress", + "content": [{"type": "audio", "transcript": None}], + }, + }, + { + "type": "response.done", + "event_id": "event_done", + "response": { + "id": "resp_123", + "object": "realtime.response", + "status": "completed", + "usage": {"input_tokens": 11, "output_tokens": 7, "total_tokens": 18}, + }, + }, + ] + + usage = RealtimeAPITokenUsageProcessor.collect_and_combine_usage_from_realtime_stream_results( + results=results + ) + logging_result = RealtimeAPITokenUsageProcessor.create_logging_realtime_object( + usage=usage, + results=results, + ) + + assert logging_result.usage.total_tokens == 18 + assert logging_result.results[0]["item"]["content"][0]["transcript"] is None + + def test_custom_pricing_with_router_model_id(): from litellm import Router From c7f1bcfd0d25f261384fb930b0026dbdaa23e01d Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Wed, 3 Jun 2026 15:50:20 -0700 Subject: [PATCH 22/92] build(ui): migrate eslint to flat config and bump eslint-config-next to 16 (#29626) ESLint 9 defaults to flat config and eslint-config-next was pinned at 15 while Next is on 16, so eslint only ran with ESLINT_USE_FLAT_CONFIG=false and next lint is gone on Next 16. Replace .eslintrc.json with a native flat eslint.config.mjs (config-next 16 ships flat configs, so no FlatCompat shim is needed), bump eslint-config-next to 16.2.6, add @eslint/js and typescript-eslint as explicit devDeps for the recommended rule sets, and point the lint script at eslint directly. This only makes eslint runnable on modern tooling; it does not wire it into CI. The same rules carry over (next/core-web-vitals, eslint and typescript-eslint recommended, prettier, unused-imports) --- ui/litellm-dashboard/.eslintrc.json | 17 - ui/litellm-dashboard/eslint.config.mjs | 33 ++ ui/litellm-dashboard/package-lock.json | 546 ++++++++++++++++++++----- ui/litellm-dashboard/package.json | 6 +- 4 files changed, 482 insertions(+), 120 deletions(-) delete mode 100644 ui/litellm-dashboard/.eslintrc.json create mode 100644 ui/litellm-dashboard/eslint.config.mjs diff --git a/ui/litellm-dashboard/.eslintrc.json b/ui/litellm-dashboard/.eslintrc.json deleted file mode 100644 index 90edda434cc..00000000000 --- a/ui/litellm-dashboard/.eslintrc.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "extends": ["next/core-web-vitals", "eslint:recommended", "plugin:@typescript-eslint/recommended", "prettier"], - "plugins": ["unused-imports"], - "rules": { - "unused-imports/no-unused-imports": "error", - "@typescript-eslint/no-explicit-any": "off", - "@typescript-eslint/no-unused-vars": "off", - "@typescript-eslint/no-unused-expressions": "off", - "@typescript-eslint/ban-ts-comment": "off", - "prefer-const": "off", - "no-empty": "off", - "no-prototype-builtins": "off", - "no-useless-catch": "off", - "no-useless-escape": "off", - "no-self-assign": "off" - } -} diff --git a/ui/litellm-dashboard/eslint.config.mjs b/ui/litellm-dashboard/eslint.config.mjs new file mode 100644 index 00000000000..838cd4a069d --- /dev/null +++ b/ui/litellm-dashboard/eslint.config.mjs @@ -0,0 +1,33 @@ +import js from "@eslint/js"; +import tseslint from "typescript-eslint"; +import nextCoreWebVitals from "eslint-config-next/core-web-vitals"; +import prettier from "eslint-config-prettier/flat"; +import unusedImports from "eslint-plugin-unused-imports"; + +const eslintConfig = [ + { + ignores: [".next/**", "out/**", "build/**", "coverage/**", "next-env.d.ts"], + }, + js.configs.recommended, + ...tseslint.configs.recommended, + ...nextCoreWebVitals, + prettier, + { + plugins: { "unused-imports": unusedImports }, + rules: { + "unused-imports/no-unused-imports": "error", + "@typescript-eslint/no-explicit-any": "off", + "@typescript-eslint/no-unused-vars": "off", + "@typescript-eslint/no-unused-expressions": "off", + "@typescript-eslint/ban-ts-comment": "off", + "prefer-const": "off", + "no-empty": "off", + "no-prototype-builtins": "off", + "no-useless-catch": "off", + "no-useless-escape": "off", + "no-self-assign": "off", + }, + }, +]; + +export default eslintConfig; diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json index 97bc797fd54..858844d7e5c 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -37,6 +37,7 @@ "uuid": "14.0.0" }, "devDependencies": { + "@eslint/js": "9.39.2", "@playwright/test": "1.58.1", "@tailwindcss/forms": "0.5.11", "@testing-library/dom": "10.4.1", @@ -56,7 +57,7 @@ "autoprefixer": "10.4.24", "dotenv": "17.2.3", "eslint": "9.39.2", - "eslint-config-next": "15.5.10", 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}, "engines": { "node": "^18.18.0 || ^20.9.0 || >=21.1.0" @@ -3679,13 +3903,13 @@ } }, "node_modules/@typescript-eslint/visitor-keys": { - "version": "8.59.2", - "resolved": "https://registry.npmjs.org/@typescript-eslint/visitor-keys/-/visitor-keys-8.59.2.tgz", - "integrity": "sha512-NwjLUnGy8/Zfx23fl50tRC8rYaYnM52xNRYFAXvmiil9yh1+K6aRVQMnzW6gQB/1DLgWt977lYQn7C+wtgXZiA==", + "version": "8.60.1", + "resolved": "https://registry.npmjs.org/@typescript-eslint/visitor-keys/-/visitor-keys-8.60.1.tgz", + "integrity": "sha512-EbGRQg4FhrmwLodl+t3JNAnXHWVr9Vp+Zl1QBZVPY4ByfkzIT8cX3K6QWODHtkIZqqJVEWvhHSx3v5PDHsaQag==", "dev": true, "license": "MIT", "dependencies": { - "@typescript-eslint/types": "8.59.2", + "@typescript-eslint/types": "8.60.1", "eslint-visitor-keys": "^5.0.0" }, "engines": { @@ -5103,6 +5327,13 @@ "integrity": "sha512-VRhuHOLoKYOy4UbilLbUzbYg93XLjv2PncJC50EuTWPA3gaja1UjBsUP/D/9/juV3vQFr6XBEzn9KCAHdUvOHw==", "license": "MIT" }, + "node_modules/convert-source-map": { + "version": 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"sha512-ob/2LcVVaVGCYN+r14cnwnoDPUufjiYgSqRhiFD0Q1iI4Odora5RE8Iv1D24hAz5oMophRGkGz+yuvQmmUMnMw==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=18" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/eslint-config-prettier": { "version": "10.1.8", "resolved": "https://registry.npmjs.org/eslint-config-prettier/-/eslint-config-prettier-10.1.8.tgz", @@ -6219,16 +6462,23 @@ } }, "node_modules/eslint-plugin-react-hooks": { - "version": "5.2.0", - "resolved": "https://registry.npmjs.org/eslint-plugin-react-hooks/-/eslint-plugin-react-hooks-5.2.0.tgz", - "integrity": "sha512-+f15FfK64YQwZdJNELETdn5ibXEUQmW1DZL6KXhNnc2heoy/sg9VJJeT7n8TlMWouzWqSWavFkIhHyIbIAEapg==", + "version": "7.1.1", + "resolved": "https://registry.npmjs.org/eslint-plugin-react-hooks/-/eslint-plugin-react-hooks-7.1.1.tgz", + "integrity": "sha512-f2I7Gw6JbvCexzIInuSbZpfdQ44D7iqdWX01FKLvrPgqxoE7oMj8clOfto8U6vYiz4yd5oKu39rRSVOe1zRu0g==", "dev": true, "license": "MIT", + "dependencies": { + "@babel/core": "^7.24.4", + "@babel/parser": "^7.24.4", + "hermes-parser": "^0.25.1", + "zod": "^3.25.0 || ^4.0.0", + "zod-validation-error": "^3.5.0 || ^4.0.0" + }, "engines": { - "node": ">=10" + "node": ">=18" }, "peerDependencies": { - "eslint": "^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 || ^7.0.0 || ^8.0.0-0 || ^9.0.0" + "eslint": "^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 || ^7.0.0 || ^8.0.0-0 || ^9.0.0 || ^10.0.0" } }, "node_modules/eslint-plugin-react/node_modules/semver": { @@ -6734,6 +6984,16 @@ "node": ">= 0.4" } }, + "node_modules/gensync": { + "version": "1.0.0-beta.2", + "resolved": "https://registry.npmjs.org/gensync/-/gensync-1.0.0-beta.2.tgz", + "integrity": "sha512-3hN7NaskYvMDLQY55gnW3NQ+mesEAepTqlg+VEbj7zzqEMBVNhzcGYYeqFo/TlYz6eQiFcp1HcsCZO+nGgS8zg==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=6.9.0" + } + }, "node_modules/get-intrinsic": { "version": "1.3.0", "resolved": "https://registry.npmjs.org/get-intrinsic/-/get-intrinsic-1.3.0.tgz", @@ -7080,6 +7340,23 @@ "url": "https://github.com/sponsors/wooorm" } }, + "node_modules/hermes-estree": { + "version": "0.25.1", + "resolved": "https://registry.npmjs.org/hermes-estree/-/hermes-estree-0.25.1.tgz", + "integrity": "sha512-0wUoCcLp+5Ev5pDW2OriHC2MJCbwLwuRx+gAqMTOkGKJJiBCLjtrvy4PWUGn6MIVefecRpzoOZ/UV6iGdOr+Cw==", + "dev": true, + "license": "MIT" + }, + "node_modules/hermes-parser": { + "version": "0.25.1", + "resolved": "https://registry.npmjs.org/hermes-parser/-/hermes-parser-0.25.1.tgz", + "integrity": "sha512-6pEjquH3rqaI6cYAXYPcz9MS4rY6R4ngRgrgfDshRptUZIc3lw0MCIJIGDj9++mfySOuPTHB4nrSW99BCvOPIA==", + "dev": true, + "license": "MIT", + "dependencies": { + "hermes-estree": "0.25.1" + } + }, "node_modules/highlight.js": { "version": "10.7.3", "resolved": "https://registry.npmjs.org/highlight.js/-/highlight.js-10.7.3.tgz", @@ -7867,6 +8144,19 @@ } } }, + "node_modules/jsesc": { + "version": "3.1.0", + "resolved": "https://registry.npmjs.org/jsesc/-/jsesc-3.1.0.tgz", + "integrity": "sha512-/sM3dO2FOzXjKQhJuo0Q173wf2KOo8t4I8vHy6lF9poUp7bKT0/NHE8fPX23PwfhnykfqnC2xRxOnVw5XuGIaA==", + "dev": true, + "license": "MIT", + "bin": { + "jsesc": "bin/jsesc" + }, + "engines": { + "node": ">=6" + } + }, "node_modules/json-buffer": { "version": "3.0.1", "resolved": "https://registry.npmjs.org/json-buffer/-/json-buffer-3.0.1.tgz", @@ -12622,6 +12912,30 @@ "node": ">=14.17" } }, + "node_modules/typescript-eslint": { + "version": "8.60.1", + "resolved": "https://registry.npmjs.org/typescript-eslint/-/typescript-eslint-8.60.1.tgz", + "integrity": "sha512-6m5hkkRAp8lKvhVpcprAIn5KkehQEh+47oHH2VGnExEh7dhNxXlg6GPAOIu6TxbVQxhebrJDvjl3020ooiWCMA==", + "dev": true, + "license": "MIT", + "dependencies": { + "@typescript-eslint/eslint-plugin": "8.60.1", + "@typescript-eslint/parser": "8.60.1", + "@typescript-eslint/typescript-estree": "8.60.1", + "@typescript-eslint/utils": "8.60.1" + }, + "engines": { + "node": "^18.18.0 || ^20.9.0 || >=21.1.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/typescript-eslint" + }, + "peerDependencies": { + "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", + "typescript": ">=4.8.4 <6.1.0" + } + }, "node_modules/unbox-primitive": { "version": "1.1.0", "resolved": "https://registry.npmjs.org/unbox-primitive/-/unbox-primitive-1.1.0.tgz", @@ -13320,6 +13634,13 @@ "node": ">=0.4" } }, + "node_modules/yallist": { + "version": "3.1.1", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", + "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==", + "dev": true, + "license": "ISC" + }, "node_modules/yocto-queue": { "version": "0.1.0", "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz", @@ -13333,6 +13654,29 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/zod": { + "version": "3.25.76", + "resolved": "https://registry.npmjs.org/zod/-/zod-3.25.76.tgz", + "integrity": "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ==", + "devOptional": true, + "license": "MIT", + "funding": { + "url": "https://github.com/sponsors/colinhacks" + } + }, + "node_modules/zod-validation-error": { + "version": "4.0.2", + "resolved": "https://registry.npmjs.org/zod-validation-error/-/zod-validation-error-4.0.2.tgz", + "integrity": "sha512-Q6/nZLe6jxuU80qb/4uJ4t5v2VEZ44lzQjPDhYJNztRQ4wyWc6VF3D3Kb/fAuPetZQnhS3hnajCf9CsWesghLQ==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=18.0.0" + }, + "peerDependencies": { + "zod": "^3.25.0 || ^4.0.0" + } + }, "node_modules/zwitch": { "version": "2.0.4", "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index 72b9bc2a159..77731bbd693 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -7,7 +7,7 @@ "dev:webpack": "next dev --webpack", "build": "next build", "start": "next start", - "lint": "next lint", + "lint": "eslint .", "test": "vitest", "test:dot": "vitest --reporter=dot", "test:watch": "vitest -w", @@ -49,6 +49,7 @@ "uuid": "14.0.0" }, "devDependencies": { + "@eslint/js": "9.39.2", "@playwright/test": "1.58.1", "@tailwindcss/forms": "0.5.11", "@testing-library/dom": "10.4.1", @@ -68,7 +69,7 @@ "autoprefixer": "10.4.24", "dotenv": "17.2.3", "eslint": "9.39.2", - "eslint-config-next": "15.5.10", + "eslint-config-next": "16.2.6", "eslint-config-prettier": "10.1.8", "eslint-plugin-unused-imports": "4.3.0", "jsdom": "27.4.0", @@ -77,6 +78,7 @@ "prettier": "3.2.5", "tailwindcss": "3.4.19", "typescript": "5.9.3", + "typescript-eslint": "8.60.1", "vite": "7.3.2", "vitest": "3.2.4" }, From e9417603a38d53765894254fc6b588ff6700bf6a Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Wed, 3 Jun 2026 19:11:53 -0700 Subject: [PATCH 23/92] fix(key_generate): scope session-token team-key budget exemption to caller-supplied team_id (#29641) #29612 exempts UI/CLI session tokens from the key budget ceiling when they create a team key, keyed on data.team_id. That value is read after the default_key_generate_params loop can populate team_id, so on deployments that set default_key_generate_params.team_id a request the caller did not scope to a team is treated as a team key and skips the ceiling. Capture _requested_team_id before defaults run and key the exemption off it, mirroring how _requested_max_budget is already captured. Requests the caller did not scope to a team keep the ceiling. --- .../key_management_endpoints.py | 10 +++-- .../test_key_management_endpoints.py | 45 +++++++++++++++++++ 2 files changed, 51 insertions(+), 4 deletions(-) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 771f8287b6e..c8c590af97c 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -691,10 +691,12 @@ async def _common_key_generation_helper( # noqa: PLR0915 prisma_client=prisma_client, ) - # Capture the caller-supplied max_budget before any defaults or upperbound - # params can fill it, so the ceiling check only fires when the caller - # explicitly requested a budget. + # Capture caller-supplied max_budget and team_id before any defaults or + # upperbound params can fill them, so the ceiling check and its team-key + # exemption key off what the caller explicitly requested, not a value that + # default_key_generate_params injected. _requested_max_budget = data.max_budget + _requested_team_id = data.team_id # check if user set default key/generate params on config.yaml if litellm.default_key_generate_params is not None: @@ -728,7 +730,7 @@ async def _common_key_generation_helper( # noqa: PLR0915 # at request time. Personal keys keep the ceiling; nothing else bounds them. is_ui_session_team_key = ( user_api_key_dict.team_id == UI_SESSION_TOKEN_TEAM_ID - and data.team_id is not None + and _requested_team_id is not None ) if ( user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN.value diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index ca4a3f4fea0..3c212d86e65 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -11623,3 +11623,48 @@ async def test_ghsa_q775_ui_session_token_personal_key_still_capped(): msg = str(getattr(err, "detail", "")) + str(getattr(err, "message", "")) assert str(code) == "400" assert "cannot exceed" in msg.lower() + + +@pytest.mark.asyncio +async def test_ghsa_q775_default_team_id_does_not_grant_session_token_exemption(): + """ + Security regression for GHSA-q775: the team-key exemption must key off the + team_id the CALLER supplied, not one injected by default_key_generate_params. + With default_key_generate_params.team_id set, a UI session token's personal-key + request (no team_id) would otherwise have team_id auto-filled before the ceiling + check, flipping is_ui_session_team_key to True and bypassing the ceiling. The + request must still be rejected. Mirrors how _requested_max_budget is captured + before defaults run. + """ + from litellm.constants import UI_SESSION_TOKEN_TEAM_ID + + data = GenerateKeyRequest(max_budget=500) + assert data.team_id is None + user_api_key_dict = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-ui-session", + user_id="user-1", + team_id=UI_SESSION_TOKEN_TEAM_ID, + max_budget=0.25, + ) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", AsyncMock()), + patch("litellm.proxy.proxy_server.user_api_key_cache", MagicMock()), + patch("litellm.proxy.proxy_server.llm_router", None), + patch("litellm.proxy.proxy_server.premium_user", False), + patch("litellm.proxy.proxy_server.litellm_proxy_admin_name", "default_user_id"), + patch("litellm.default_key_generate_params", {"team_id": "injected-team"}), + ): + with pytest.raises((HTTPException, ProxyException)) as exc_info: + await _common_key_generation_helper( + data=data, + user_api_key_dict=user_api_key_dict, + litellm_changed_by=None, + team_table=None, + ) + err = exc_info.value + code = getattr(err, "status_code", None) or getattr(err, "code", None) + msg = str(getattr(err, "detail", "")) + str(getattr(err, "message", "")) + assert str(code) == "400" + assert "cannot exceed" in msg.lower() From be7b9319d2017cd3590cee2805fe90574260a035 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Thu, 4 Jun 2026 04:53:14 -0700 Subject: [PATCH 24/92] fix(proxy): disable proxy buffering on streaming SSE responses (#29557) Streaming responses from the proxy (/chat/completions, /v1/messages, /v1/responses, assistants) all return through create_response() but never sent the headers that tell an intermediary reverse proxy not to buffer the SSE stream. nginx with the default proxy_buffering, k8s ingress-nginx, and Envoy/Istio sidecars therefore hold the whole stream and release it in one batch, which looks like a broken/buffered stream to the client even though litellm is yielding chunks incrementally. Add Cache-Control: no-cache and X-Accel-Buffering: no to every StreamingResponse create_response() returns, matching what the proxy already does for its own usage/policy SSE endpoints. Fixes #28384. --- litellm/proxy/common_request_processing.py | 13 +++++++--- .../proxy/test_common_request_processing.py | 25 +++++++++++++++++++ 2 files changed, 35 insertions(+), 3 deletions(-) diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index 36acd9653e8..6558543370d 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -249,6 +249,13 @@ async def create_response( # noqa: PLR0915 If the first chunk is an error, return a standard JSON error response. Otherwise, return StreamingResponse and stream all content. """ + # Tell buffering reverse proxies (nginx, ingress-nginx, Envoy) to flush SSE + # immediately instead of releasing the whole stream in one batch (issue #28384). + streaming_headers = { + **headers, + "Cache-Control": "no-cache", + "X-Accel-Buffering": "no", + } first_chunk_value: Optional[str] = None final_status_code = default_status_code @@ -300,7 +307,7 @@ async def create_response( # noqa: PLR0915 return StreamingResponse( empty_gen(), media_type=media_type, - headers=headers, + headers=streaming_headers, status_code=default_status_code, ) except Exception as e: @@ -338,7 +345,7 @@ async def create_response( # noqa: PLR0915 return StreamingResponse( error_gen_message(), media_type=media_type, - headers=headers, + headers=streaming_headers, status_code=error_status, ) @@ -360,7 +367,7 @@ async def create_response( # noqa: PLR0915 return StreamingResponse( combined_generator(), media_type=media_type, - headers=headers, + headers=streaming_headers, status_code=final_status_code, ) diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py index 265a82d4a44..0f5a0cbe4b6 100644 --- a/tests/test_litellm/proxy/test_common_request_processing.py +++ b/tests/test_litellm/proxy/test_common_request_processing.py @@ -1258,6 +1258,31 @@ class TestCommonRequestProcessingHelpers: ) assert response.headers["x-custom-header"] == "TestValue" + async def test_create_streaming_response_disables_proxy_buffering(self): + """Regression for #28384: every StreamingResponse create_response returns + must carry the headers that stop nginx/ingress/Envoy from buffering the + SSE stream into one batch, while preserving caller-supplied headers.""" + + async def normal_stream(): + yield 'data: {"content": "part"}\n\n' + yield "data: [DONE]\n\n" + + async def empty_stream(): + if False: # never yields -> StopAsyncIteration + yield + + error_stream = AsyncMock() + error_stream.__anext__.side_effect = ValueError("boom") + + for generator in (normal_stream(), empty_stream(), error_stream): + response = await create_response( + generator, "text/event-stream", {"X-Custom-Header": "keep"} + ) + assert isinstance(response, StreamingResponse) + assert response.headers["x-accel-buffering"] == "no" + assert response.headers["cache-control"] == "no-cache" + assert response.headers["x-custom-header"] == "keep" + async def test_create_streaming_response_non_default_status_code(self): async def mock_generator(): yield 'data: {"content": "data"}\n\n' From 9196098e9e1d5cd7de7dc1407f5ee6af31754c9a Mon Sep 17 00:00:00 2001 From: michelligabriele Date: Thu, 4 Jun 2026 13:56:59 +0200 Subject: [PATCH 25/92] fix(mcp): gate /public/mcp_hub strictly on litellm.public_mcp_servers (#27764) * fix(mcp): gate /public/mcp_hub strictly on litellm.public_mcp_servers * fix(mcp): add public_mcp_hub_strict_whitelist flag (default True) for migration --- litellm/__init__.py | 1 + .../mcp_server/mcp_server_manager.py | 36 ++++- .../mcp_server/test_mcp_server_manager.py | 135 ++++++++++++++++++ .../public_endpoints/test_public_endpoints.py | 64 +++++++++ 4 files changed, 229 insertions(+), 7 deletions(-) diff --git a/litellm/__init__.py b/litellm/__init__.py index c954f5fd31e..98c9dcb5ddf 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -444,6 +444,7 @@ disable_copilot_system_to_assistant: bool = ( False # If false (default), converts all 'system' role messages to 'assistant' for GitHub Copilot compatibility. Set to true to disable this behavior. ) public_mcp_servers: Optional[List[str]] = None +public_mcp_hub_strict_whitelist: bool = True public_model_groups: Optional[List[str]] = None public_agent_groups: Optional[List[str]] = None # Supports both old format (Dict[str, str]) and new format (Dict[str, Dict[str, Any]]) diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py index 739dc4a2f88..d9b112f6c21 100644 --- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py +++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py @@ -3540,15 +3540,37 @@ class MCPServerManager: def get_public_mcp_servers(self) -> List[MCPServer]: """ - Get the public MCP servers (available_on_public_internet=True flag on server). - Also includes servers from litellm.public_mcp_servers for backwards compat. + Return the MCP servers published to the AI Hub via /v1/mcp/make_public. + + Default (litellm.public_mcp_hub_strict_whitelist=True): mirrors + /public/model_hub and /public/agent_hub — gates strictly on the + litellm.public_mcp_servers whitelist. Returns an empty list when no + servers have been published. The per-server available_on_public_internet + flag is unrelated — it governs IP-based access in + _is_server_accessible_from_ip, not hub visibility. + + Legacy (litellm.public_mcp_hub_strict_whitelist=False): preserves the + pre-fix behavior where any server with available_on_public_internet=True + is also included. Intended as a one-release migration window for + deployments that relied on the OR-with-default semantics; will be + removed in a future release. """ - servers: List[MCPServer] = [] + if litellm.public_mcp_hub_strict_whitelist: + if litellm.public_mcp_servers is None: + return [] + public_ids = set(litellm.public_mcp_servers) + return [ + server + for server in self.get_registry().values() + if server.server_id in public_ids + ] + public_ids = set(litellm.public_mcp_servers or []) - for server in self.get_registry().values(): - if server.available_on_public_internet or server.server_id in public_ids: - servers.append(server) - return servers + return [ + server + for server in self.get_registry().values() + if server.available_on_public_internet or server.server_id in public_ids + ] def expand_permission_list(self, identifiers: List[str]) -> List[str]: """ diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py index ec690aef629..32e4ec19311 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py @@ -3984,5 +3984,140 @@ class TestApprovalStatusGate: assert "never-seen" not in manager.registry +class TestGetPublicMCPServers: + """ + /public/mcp_hub strict-whitelist semantics — mirrors /public/model_hub + and /public/agent_hub. Regression test for the PR #20607 OR-with-default + behavior that made `litellm.public_mcp_servers` ignored by the hub. + """ + + def _make_server(self, server_id, available_on_public_internet=True): + return MCPServer( + server_id=server_id, + name=server_id, + server_name=server_id, + transport=MCPTransport.http, + available_on_public_internet=available_on_public_internet, + ) + + def _make_manager(self, servers): + manager = MCPServerManager() + for s in servers: + manager.config_mcp_servers[s.server_id] = s + return manager + + @patch("litellm.public_mcp_servers", None) + def test_returns_empty_when_whitelist_is_none(self): + """No /make_public call yet → hub returns nothing, regardless of + per-server flags.""" + manager = self._make_manager( + [ + self._make_server("a", available_on_public_internet=True), + self._make_server("b", available_on_public_internet=True), + ] + ) + assert manager.get_public_mcp_servers() == [] + + @patch("litellm.public_mcp_servers", []) + def test_returns_empty_when_whitelist_is_empty(self): + """Explicit empty whitelist → hub returns nothing.""" + manager = self._make_manager( + [self._make_server("a", available_on_public_internet=True)] + ) + assert manager.get_public_mcp_servers() == [] + + @patch("litellm.public_mcp_servers", ["a"]) + def test_returns_only_whitelisted_when_flag_defaults_to_true(self): + """ + Regression: prior to the fix, every server with + available_on_public_internet=True (the default) leaked into the hub + regardless of the whitelist. Whitelist must be authoritative. + """ + manager = self._make_manager( + [ + self._make_server("a", available_on_public_internet=True), + self._make_server("b", available_on_public_internet=True), + ] + ) + result = manager.get_public_mcp_servers() + assert [s.server_id for s in result] == ["a"] + + @patch("litellm.public_mcp_servers", ["a"]) + def test_does_not_leak_servers_via_internal_flag(self): + """ + available_on_public_internet is an IP-gating flag, not a hub flag. + A server with the flag True that is not in the whitelist must not + appear in the hub. + """ + manager = self._make_manager( + [ + self._make_server("a", available_on_public_internet=False), + self._make_server("b", available_on_public_internet=True), + ] + ) + result = manager.get_public_mcp_servers() + assert [s.server_id for s in result] == ["a"] + + @patch("litellm.public_mcp_servers", ["does-not-exist"]) + def test_stale_whitelist_id_returns_empty(self): + """Whitelist references an unknown server_id → no spurious results.""" + manager = self._make_manager( + [self._make_server("a", available_on_public_internet=True)] + ) + assert manager.get_public_mcp_servers() == [] + + +class TestGetPublicMCPServersLegacyMode: + """ + Legacy migration knob: litellm.public_mcp_hub_strict_whitelist=False + preserves the pre-fix OR-with-default semantics for one release so + operators that relied on the old behavior have a window to call + /v1/mcp/make_public before /public/mcp_hub goes empty. + """ + + def _make_server(self, server_id, available_on_public_internet=True): + return MCPServer( + server_id=server_id, + name=server_id, + server_name=server_id, + transport=MCPTransport.http, + available_on_public_internet=available_on_public_internet, + ) + + def _make_manager(self, servers): + manager = MCPServerManager() + for s in servers: + manager.config_mcp_servers[s.server_id] = s + return manager + + @patch("litellm.public_mcp_hub_strict_whitelist", False) + @patch("litellm.public_mcp_servers", None) + def test_legacy_returns_default_flag_servers_when_whitelist_is_none(self): + """Legacy mode + no whitelist → every server with the default + available_on_public_internet=True appears (old behavior).""" + manager = self._make_manager( + [ + self._make_server("a", available_on_public_internet=True), + self._make_server("b", available_on_public_internet=False), + ] + ) + result = manager.get_public_mcp_servers() + assert [s.server_id for s in result] == ["a"] + + @patch("litellm.public_mcp_hub_strict_whitelist", False) + @patch("litellm.public_mcp_servers", ["b"]) + def test_legacy_unions_whitelist_and_default_flag(self): + """Legacy mode unions the whitelist with any + available_on_public_internet=True server.""" + manager = self._make_manager( + [ + self._make_server("a", available_on_public_internet=True), + self._make_server("b", available_on_public_internet=False), + ] + ) + result = manager.get_public_mcp_servers() + assert sorted(s.server_id for s in result) == ["a", "b"] + + if __name__ == "__main__": pytest.main([__file__]) diff --git a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py index 6cff91d2c74..ecab59c10a1 100644 --- a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py +++ b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py @@ -703,3 +703,67 @@ def test_clean_display_name_strips_suffix(): def test_clean_display_name_passthrough_when_no_suffix(): assert _clean_display_name("OpenAI") == "OpenAI" assert _clean_display_name("") == "" + + +def test_public_mcp_hub_returns_only_whitelisted_servers(): + """Regression: /public/mcp_hub must gate strictly on + litellm.public_mcp_servers, mirroring /public/model_hub and + /public/agent_hub. Servers with available_on_public_internet=True that + are not on the whitelist must not leak.""" + from litellm.types.mcp_server.mcp_server_manager import MCPServer + from litellm.proxy._types import MCPTransport + + app = FastAPI() + app.include_router(router) + app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + client = TestClient(app) + + listed = MCPServer( + server_id="listed", + name="listed", + server_name="listed", + transport=MCPTransport.http, + available_on_public_internet=True, + ) + + mock_manager = MagicMock() + mock_manager.get_public_mcp_servers.return_value = [listed] + + with ( + patch("litellm.public_mcp_servers", ["listed"]), + patch( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager", + mock_manager, + ), + ): + response = client.get("/public/mcp_hub") + + assert response.status_code == 200 + data = response.json() + assert [item["server_id"] for item in data] == ["listed"] + app.dependency_overrides.clear() + + +def test_public_mcp_hub_returns_empty_when_whitelist_unset(): + """When no servers have been published via /v1/mcp/make_public, the + hub returns an empty list (matches /public/agent_hub behavior).""" + app = FastAPI() + app.include_router(router) + app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + client = TestClient(app) + + mock_manager = MagicMock() + mock_manager.get_public_mcp_servers.return_value = [] + + with ( + patch("litellm.public_mcp_servers", None), + patch( + "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager", + mock_manager, + ), + ): + response = client.get("/public/mcp_hub") + + assert response.status_code == 200 + assert response.json() == [] + app.dependency_overrides.clear() From 443f0ca4cd9396cadc624972aa8125a076f7011b Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Thu, 4 Jun 2026 07:41:31 -0700 Subject: [PATCH 26/92] ci(ui): frontend-lint job enforcing prettier + eslint on changed files (#29633) * ci(ui): add frontend-lint job enforcing prettier and eslint on changed files Lints only the files a PR adds or modifies under ui/litellm-dashboard, so new and touched code must be prettier-clean and eslint-clean while the existing tree is grandfathered. Skips cleanly when a PR touches no lintable UI files. This lets us adopt the formatters incrementally without a repo-wide reformat * ci(ui): write frontend-lint file lists to $RUNNER_TEMP Keep the prettier/eslint changed-file lists out of the checkout dir so they cannot collide with a future source file of the same name * lint(ui): baseline existing eslint findings so only new ones block Capture the current error-level eslint findings (318 across 183 files) in a committed suppressions baseline via eslint --suppress-all. Every rule stays at its error severity, so any newly introduced violation fails the frontend-lint gate, while the existing tree is grandfathered; touching a legacy file never forces fixing its pre-existing issues. CI runs eslint with --pass-on-unpruned-suppressions so that fixing a baselined issue does not fail on a now-stale suppression, and the generated baseline is prettier-ignored since eslint owns its format. Burn the baseline down over time with eslint --prune-suppressions * lint(ui): enforce a count budget for explicit any Make @typescript-eslint/no-explicit-any a warning and cap the total instead of hard-blocking each new one. A frontend-lint step counts the repo-wide explicit any and fails only when it exceeds the committed budget in eslint-any-budget.json. max starts at 2031, ten above the current 2021, so the next ten land as warnings and the build fails once that headroom is gone. Lower max over time toward target to ratchet the count down. New anys still surface as warnings on changed files via the normal eslint step * lint(ui): enable zero-cost rules no-var, no-self-assign, react/no-danger These have no existing violations, so they need no baseline; turning them on purely blocks new instances. react/no-danger guards against new dangerouslySetInnerHTML (XSS), no-var enforces let/const, and no-self-assign catches self-assignment typos. no-debugger is already enforced by the recommended preset * lint(ui): add baselined complexity rules Enable complexity:20, max-depth:4, max-params:4, max-nested-callbacks:4, with thresholds set near the codebase p99 so only genuine outliers are flagged. The 272 existing over-threshold functions are grandfathered in the suppressions baseline; new over-threshold functions block. Lower the thresholds over time to ratchet complexity down. max-lines-per-function is intentionally left off since React components are legitimately long * lint(ui): ban new raw fetch, standardize on React Query Add a no-restricted-syntax rule flagging bare fetch() calls, pointing contributors at React Query (@tanstack/react-query). The rule is not exempted anywhere, including the already-bloated networking.tsx, so all 331 existing fetch calls are grandfathered but no new ones can be added there or elsewhere. New data access goes through React Query, and the networking layer can be migrated out and pruned from the baseline over time * lint(ui): ban new @tremor/react imports Add a no-restricted-imports rule flagging imports from @tremor/react so tremor is phased out rather than spread further. The 232 existing tremor imports are grandfathered in the baseline; new ones block and point at antd. Migrate components off tremor and prune the baseline over time * lint(ui): widen explicit-any budget headroom to 2040 Raise max from 2031 to 2040, giving ~19 of slack over the current 2021 instead of 10 * style(ui): prettier-format eslint.config.mjs The frontend-lint gate flagged its own config file. Format it so the prettier check on this PR's changed files passes * lint(ui): soften complexity and max-depth to warnings These two are smell metrics with arbitrary thresholds where a legit new function can trip them, so make them advisory rather than hard-blocking. They drop out of the baseline (now 963). max-params, max-nested-callbacks, and the react-hooks rules stay strict since those are clear-cut * lint(ui): move complexity and max-depth to the count-budget pattern Generalize the explicit-any budget into a shared lint-budget mechanism: eslint-budgets.json maps a rule to {max, target} and check-lint-budgets.mjs counts each across the repo and fails when a count exceeds its max. complexity (129, max 140) and max-depth (61, max 70) now use the same slack-plus-counter model as explicit-any (2021, max 2040): they warn per-file and the build only fails if the repo-wide total crosses the ceiling. Lower each max toward its target over time * docs(ui): note pruning the eslint suppressions baseline when fixing lint debt --- .github/workflows/test-litellm-ui-build.yml | 76 + ui/litellm-dashboard/.prettierignore | 3 +- ui/litellm-dashboard/CLAUDE.md | 2 + ui/litellm-dashboard/eslint-budgets.json | 5 + ui/litellm-dashboard/eslint-suppressions.json | 2312 +++++++++++++++++ ui/litellm-dashboard/eslint.config.mjs | 28 +- .../scripts/check-lint-budgets.mjs | 30 + 7 files changed, 2453 insertions(+), 3 deletions(-) create mode 100644 ui/litellm-dashboard/eslint-budgets.json create mode 100644 ui/litellm-dashboard/eslint-suppressions.json create mode 100644 ui/litellm-dashboard/scripts/check-lint-budgets.mjs diff --git a/.github/workflows/test-litellm-ui-build.yml b/.github/workflows/test-litellm-ui-build.yml index 862f98e30f1..68497b10dbb 100644 --- a/.github/workflows/test-litellm-ui-build.yml +++ b/.github/workflows/test-litellm-ui-build.yml @@ -36,3 +36,79 @@ jobs: - name: Build run: npm run build + + frontend-lint: + runs-on: ubuntu-latest + timeout-minutes: 8 + defaults: + run: + working-directory: ui/litellm-dashboard + + steps: + - name: Checkout repository + uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0 + with: + fetch-depth: 0 + persist-credentials: false + + - name: Collect changed files + id: changed + env: + BASE_SHA: ${{ github.event.pull_request.base.sha }} + run: | + : > "$RUNNER_TEMP/prettier_files.txt" + : > "$RUNNER_TEMP/eslint_files.txt" + while IFS= read -r f; do + [ -f "$f" ] || continue + case "$f" in + *.js | *.jsx | *.ts | *.tsx | *.mjs | *.cjs) + printf '%s\n' "$f" >> "$RUNNER_TEMP/prettier_files.txt" + printf '%s\n' "$f" >> "$RUNNER_TEMP/eslint_files.txt" ;; + *.json | *.css | *.scss | *.md | *.mdx | *.yml | *.yaml | *.html) + printf '%s\n' "$f" >> "$RUNNER_TEMP/prettier_files.txt" ;; + esac + done < <(git diff --name-only --diff-filter=ACMR --relative "$BASE_SHA"...HEAD -- .) + if [ -s "$RUNNER_TEMP/prettier_files.txt" ] || [ -s "$RUNNER_TEMP/eslint_files.txt" ]; then + echo "has_files=true" >> "$GITHUB_OUTPUT" + else + echo "has_files=false" >> "$GITHUB_OUTPUT" + echo "No lintable UI files changed in this PR; nothing to check." + fi + + - name: Setup Node.js + if: steps.changed.outputs.has_files == 'true' + uses: actions/setup-node@a0853c24544627f65ddf259abe73b1d18a591444 # v5.0 + with: + node-version: "20" + cache: "npm" + cache-dependency-path: ui/litellm-dashboard/package-lock.json + + - name: Install dependencies + if: steps.changed.outputs.has_files == 'true' + run: npm ci + + - name: Lint changed files (prettier + eslint) + if: steps.changed.outputs.has_files == 'true' + run: | + prettier_files=() + eslint_files=() + while IFS= read -r f; do prettier_files+=("$f"); done < "$RUNNER_TEMP/prettier_files.txt" + while IFS= read -r f; do eslint_files+=("$f"); done < "$RUNNER_TEMP/eslint_files.txt" + status=0 + if [ ${#prettier_files[@]} -gt 0 ]; then + echo "::group::Prettier (${#prettier_files[@]} files)" + npx prettier --check "${prettier_files[@]}" || { status=1; echo "::error::Unformatted files. Fix with: npm run format"; } + echo "::endgroup::" + fi + if [ ${#eslint_files[@]} -gt 0 ]; then + echo "::group::ESLint (${#eslint_files[@]} files)" + npx eslint --no-warn-ignored --pass-on-unpruned-suppressions "${eslint_files[@]}" || status=1 + echo "::endgroup::" + fi + exit $status + + - name: Check lint budgets + if: ${{ !cancelled() && steps.changed.outputs.has_files == 'true' }} + run: | + npx eslint . -f json -o "$RUNNER_TEMP/lint-report.json" || true + node scripts/check-lint-budgets.mjs "$RUNNER_TEMP/lint-report.json" eslint-budgets.json diff --git a/ui/litellm-dashboard/.prettierignore b/ui/litellm-dashboard/.prettierignore index ab37c884be1..d489a619838 100644 --- a/ui/litellm-dashboard/.prettierignore +++ b/ui/litellm-dashboard/.prettierignore @@ -8,4 +8,5 @@ build .turbo .next-static *.min.js -coverage/ \ No newline at end of file +coverage/ +eslint-suppressions.json \ No newline at end of file diff --git a/ui/litellm-dashboard/CLAUDE.md b/ui/litellm-dashboard/CLAUDE.md index 3d43019c749..7af913ab016 100644 --- a/ui/litellm-dashboard/CLAUDE.md +++ b/ui/litellm-dashboard/CLAUDE.md @@ -1 +1,3 @@ Never put LiteLLM tokens or API keys in `localStorage`. `localStorage` survives browser close. Prefer `httpOnly` cookies, or `sessionStorage` at most, understanding that any web storage is readable by injected scripts (XSS), and only httpOnly cookies are not + +When you fix lint violations that are grandfathered in `eslint-suppressions.json`, run `eslint . --prune-suppressions` and commit the updated baseline so the gate ratchets down instead of leaving a stale suppression diff --git a/ui/litellm-dashboard/eslint-budgets.json b/ui/litellm-dashboard/eslint-budgets.json new file mode 100644 index 00000000000..2139d177512 --- /dev/null +++ b/ui/litellm-dashboard/eslint-budgets.json @@ -0,0 +1,5 @@ +{ + "@typescript-eslint/no-explicit-any": { "max": 2040, "target": 1500 }, + "complexity": { "max": 140, "target": 80 }, + "max-depth": { "max": 70, "target": 30 } +} diff --git a/ui/litellm-dashboard/eslint-suppressions.json b/ui/litellm-dashboard/eslint-suppressions.json new file mode 100644 index 00000000000..1110403446c --- /dev/null +++ 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"react-hooks/set-state-in-effect": { + "count": 1 + } + }, + "src/hooks/useToolsOAuthFlow.tsx": { + "react-hooks/refs": { + "count": 1 + }, + "react-hooks/set-state-in-effect": { + "count": 1 + } + }, + "src/hooks/useUserMcpOAuthFlow.tsx": { + "react-hooks/set-state-in-effect": { + "count": 1 + } + }, + "src/utils/dataUtils.test.ts": { + "max-nested-callbacks": { + "count": 1 + } + }, + "tailwind.config.js": { + "@typescript-eslint/no-require-imports": { + "count": 4 + } + }, + "tailwind.config.ts": { + "@typescript-eslint/no-require-imports": { + "count": 3 + } + }, + "tests/CreateKeyPage.expiredToken.test.tsx": { + "@typescript-eslint/no-require-imports": { + "count": 3 + }, + "react/display-name": { + "count": 1 + } + }, + "tests/setupTests.ts": { + "@typescript-eslint/no-this-alias": { + "count": 1 + }, + "react/display-name": { + "count": 1 + } + } +} \ No newline at end of file diff --git a/ui/litellm-dashboard/eslint.config.mjs b/ui/litellm-dashboard/eslint.config.mjs index 838cd4a069d..50d648feb81 100644 --- a/ui/litellm-dashboard/eslint.config.mjs +++ b/ui/litellm-dashboard/eslint.config.mjs @@ -16,7 +16,7 @@ const eslintConfig = [ plugins: { "unused-imports": unusedImports }, rules: { "unused-imports/no-unused-imports": "error", - "@typescript-eslint/no-explicit-any": "off", + "@typescript-eslint/no-explicit-any": "warn", "@typescript-eslint/no-unused-vars": "off", "@typescript-eslint/no-unused-expressions": "off", "@typescript-eslint/ban-ts-comment": "off", @@ -25,7 +25,31 @@ const eslintConfig = [ "no-prototype-builtins": "off", "no-useless-catch": "off", "no-useless-escape": "off", - "no-self-assign": "off", + "no-self-assign": "error", + "no-var": "error", + "react/no-danger": "error", + complexity: ["warn", 20], + "max-depth": ["warn", 4], + "max-params": ["error", 4], + "max-nested-callbacks": ["error", 4], + "no-restricted-syntax": [ + "error", + { + selector: "CallExpression[callee.name='fetch']", + message: "Use React Query (@tanstack/react-query) for data fetching instead of a raw fetch().", + }, + ], + "no-restricted-imports": [ + "error", + { + patterns: [ + { + group: ["@tremor/react", "@tremor/react/*"], + message: "@tremor/react is being phased out; build new UI with antd instead of adding tremor imports.", + }, + ], + }, + ], }, }, ]; diff --git a/ui/litellm-dashboard/scripts/check-lint-budgets.mjs b/ui/litellm-dashboard/scripts/check-lint-budgets.mjs new file mode 100644 index 00000000000..f6208f012bb --- /dev/null +++ b/ui/litellm-dashboard/scripts/check-lint-budgets.mjs @@ -0,0 +1,30 @@ +import { readFileSync } from "fs"; + +const [, , reportPath, budgetsPath] = process.argv; + +const report = JSON.parse(readFileSync(reportPath, "utf8")); +const budgets = JSON.parse(readFileSync(budgetsPath, "utf8")); + +const counts = {}; +for (const file of report) { + for (const message of file.messages) { + if (message.ruleId in budgets) { + counts[message.ruleId] = (counts[message.ruleId] || 0) + 1; + } + } +} + +let failed = false; +for (const [rule, { max, target }] of Object.entries(budgets)) { + const count = counts[rule] || 0; + const note = count > max ? "OVER BUDGET" : count <= target ? "at target" : `${max - count} of headroom`; + console.log(`${rule}: ${count} | max: ${max} | target: ${target} | ${note}`); + if (count > max) { + console.error( + `::error::${rule} budget exceeded (${count} > ${max}). Reduce usage; lower max in eslint-budgets.json as the count drops.`, + ); + failed = true; + } +} + +process.exit(failed ? 1 : 0); From 216c68db049d8d06a8fefc35aa4976f4dff8789f Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Thu, 4 Jun 2026 20:13:30 +0530 Subject: [PATCH 27/92] fix(gemini): googleSearch + server-side tools and googleMaps JSON schema (#29582) * fix(gemini): keep googleSearch with server-side tools and googleMaps JSON schema Wire include_server_side_tool_invocations through completion() so mixed google_search and function tools are not dropped on Gemini 3+. Rewrite generationConfig to responseFormat when googleMaps is used with JSON schema. Fixes #27479 Fixes #29451 Co-authored-by: Cursor * address greptile review feedback (greploop iteration 1) * style: fix black formatting in main.py for py312 compat * Fix Gemini Google Maps extra_body JSON rewrite --------- Co-authored-by: Cursor --- litellm/constants.py | 2 + litellm/llms/gemini/chat/transformation.py | 1 + .../llms/vertex_ai/gemini/transformation.py | 56 ++++++++++++++ .../vertex_and_google_ai_studio_gemini.py | 23 ++++++ litellm/main.py | 8 ++ litellm/types/llms/vertex_ai.py | 1 + .../vertex_ai/gemini/test_transformation.py | 32 ++++++++ .../test_vertex_ai_gemini_transformation.py | 74 ++++++++++++++++++ ...test_vertex_and_google_ai_studio_gemini.py | 77 +++++++++++++++++++ 9 files changed, 274 insertions(+) diff --git a/litellm/constants.py b/litellm/constants.py index 26e25d0cef3..36e578bd323 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -678,6 +678,7 @@ OPENAI_CHAT_COMPLETION_PARAMS = [ "extra_headers", "thinking", "web_search_options", + "include_server_side_tool_invocations", "service_tier", "prompt_cache_key", "prompt_cache_retention", @@ -739,6 +740,7 @@ DEFAULT_CHAT_COMPLETION_PARAM_VALUES = { "verbosity": None, "thinking": None, "web_search_options": None, + "include_server_side_tool_invocations": None, "service_tier": None, "safety_identifier": None, "prompt_cache_key": None, diff --git a/litellm/llms/gemini/chat/transformation.py b/litellm/llms/gemini/chat/transformation.py index b69b7e1913e..4e9764446c9 100644 --- a/litellm/llms/gemini/chat/transformation.py +++ b/litellm/llms/gemini/chat/transformation.py @@ -93,6 +93,7 @@ class GoogleAIStudioGeminiConfig(VertexGeminiConfig): "modalities", "parallel_tool_calls", "web_search_options", + "include_server_side_tool_invocations", "service_tier", ] if supports_reasoning(model, custom_llm_provider="gemini"): diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py index ef7bf82bfae..c578d6cd28b 100644 --- a/litellm/llms/vertex_ai/gemini/transformation.py +++ b/litellm/llms/vertex_ai/gemini/transformation.py @@ -1121,6 +1121,61 @@ def _pop_and_merge_extra_body(data: RequestBody, optional_params: dict) -> None: data_dict[k] = v +def _has_google_maps_tool(tools: Optional[Any]) -> bool: + """Return True if any tool object in the list has a 'googleMaps' key.""" + if not isinstance(tools, list): + return False + return any( + isinstance(t, dict) and VertexToolName.GOOGLE_MAPS.value in t for t in tools + ) + + +def _rewrite_mime_type_to_response_format(generation_config: GenerationConfig) -> None: + """ + Convert response_mime_type + response_json_schema/response_schema to the newer + responseFormat structure when googleMaps is present in tools. + + The Gemini API rejects the combination of googleMaps + response_mime_type: + 'application/json' with the error: + "Google Maps tool with a response mime type: 'application/json' is unsupported" + + The newer responseFormat field supports this combination on both the Gemini API + (generativelanguage.googleapis.com) and Vertex AI endpoints. + + Before: + generationConfig: { + response_mime_type: "application/json", + response_json_schema: {...} + } + + After: + generationConfig: { + responseFormat: { + "text": {"mimeType": "APPLICATION_JSON", "schema": {...}} + } + } + """ + schema = generation_config.pop("response_json_schema", None) # type: ignore[misc] + if schema is None: + schema = generation_config.pop("response_schema", None) # type: ignore[misc] + generation_config.pop("response_mime_type", None) # type: ignore[misc] + + response_format: Dict[str, Any] = {"text": {"mimeType": "APPLICATION_JSON"}} + if schema is not None: + response_format["text"]["schema"] = schema + generation_config["responseFormat"] = response_format # type: ignore[typeddict-unknown-key] + + +def _rewrite_google_maps_response_format(data: RequestBody) -> None: + generation_config = cast(Optional[GenerationConfig], data.get("generationConfig")) + if ( + isinstance(generation_config, dict) + and _has_google_maps_tool(data.get("tools")) + and generation_config.get("response_mime_type") == "application/json" + ): + _rewrite_mime_type_to_response_format(generation_config) + + def _transform_request_body( # noqa: PLR0915 messages: List[AllMessageValues], model: str, @@ -1246,6 +1301,7 @@ def _transform_request_body( # noqa: PLR0915 if labels and custom_llm_provider != LlmProviders.GEMINI: data["labels"] = labels _pop_and_merge_extra_body(data, optional_params) + _rewrite_google_maps_response_format(data) except Exception as e: raise e diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py index 189ac7a7f6a..5cd02293f14 100644 --- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py +++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py @@ -1147,6 +1147,26 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): return cast(dict, speech_config) + @staticmethod + def _apply_include_server_side_tool_invocations( + non_default_params: Dict, + optional_params: Dict, + ) -> None: + """ + Set include_server_side_tool_invocations before tools are mapped. + + map_openai_params iterates non_default_params in request order; if tools + appear before this flag, _resolve_search_tool_conflict would drop search + tools before the flag is applied. + """ + for key in ( + "include_server_side_tool_invocations", + "includeServerSideToolInvocations", + ): + if non_default_params.get(key) is True or optional_params.get(key) is True: + optional_params["include_server_side_tool_invocations"] = True + return + def map_openai_params( # noqa: PLR0915 self, non_default_params: Dict, @@ -1154,6 +1174,9 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): model: str, drop_params: bool, ) -> Dict: + self._apply_include_server_side_tool_invocations( + non_default_params, optional_params + ) gemini_sampling_params_warned: bool = False for param, value in non_default_params.items(): if param == "temperature": diff --git a/litellm/main.py b/litellm/main.py index da8624d11b8..96f81381c86 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -437,6 +437,7 @@ async def acompletion( # noqa: PLR0915 # Optional liteLLM function params thinking: Optional[AnthropicThinkingParam] = None, web_search_options: Optional[OpenAIWebSearchOptions] = None, + include_server_side_tool_invocations: Optional[bool] = None, # Session management shared_session: Optional["ClientSession"] = None, # Per-request JSON schema validation (overrides litellm.enable_json_schema_validation) @@ -584,6 +585,7 @@ async def acompletion( # noqa: PLR0915 "acompletion": True, # assuming this is a required parameter "thinking": thinking, "web_search_options": web_search_options, + "include_server_side_tool_invocations": include_server_side_tool_invocations, "shared_session": shared_session, "enable_json_schema_validation": enable_json_schema_validation, } @@ -1116,6 +1118,7 @@ def completion( # type: ignore # noqa: PLR0915 top_logprobs: Optional[int] = None, parallel_tool_calls: Optional[bool] = None, web_search_options: Optional[OpenAIWebSearchOptions] = None, + include_server_side_tool_invocations: Optional[bool] = None, deployment_id=None, extra_headers: Optional[dict] = None, safety_identifier: Optional[str] = None, @@ -1550,6 +1553,11 @@ def completion( # type: ignore # noqa: PLR0915 "reasoning_effort": reasoning_effort, "thinking": thinking, "web_search_options": web_search_options, + "include_server_side_tool_invocations": ( + include_server_side_tool_invocations + if include_server_side_tool_invocations is not None + else kwargs.get("include_server_side_tool_invocations") + ), "safety_identifier": safety_identifier, "service_tier": service_tier, "allowed_openai_params": kwargs.get("allowed_openai_params"), diff --git a/litellm/types/llms/vertex_ai.py b/litellm/types/llms/vertex_ai.py index b972ff3c538..51429d0769e 100644 --- a/litellm/types/llms/vertex_ai.py +++ b/litellm/types/llms/vertex_ai.py @@ -246,6 +246,7 @@ class GenerationConfig(TypedDict, total=False): response_mime_type: Literal["text/plain", "application/json"] response_schema: dict response_json_schema: dict + responseFormat: dict seed: int responseLogprobs: bool logprobs: int diff --git a/tests/litellm/llms/vertex_ai/gemini/test_transformation.py b/tests/litellm/llms/vertex_ai/gemini/test_transformation.py index 963e2d273a7..756923c5df6 100644 --- a/tests/litellm/llms/vertex_ai/gemini/test_transformation.py +++ b/tests/litellm/llms/vertex_ai/gemini/test_transformation.py @@ -246,6 +246,38 @@ async def test__transform_request_body_image_config_with_image_size(): assert rb["generationConfig"]["imageConfig"]["imageSize"] == "4K" +def test__transform_request_body_google_maps_json_schema_uses_response_format(): + """googleMaps + JSON schema must use responseFormat, not response_mime_type.""" + messages = [{"role": "user", "content": "Find restaurants in Mumbai"}] + schema = { + "type": "object", + "properties": {"places": {"type": "array"}}, + "required": ["places"], + } + optional_params = { + "tools": [{"googleMaps": {}}], + "response_mime_type": "application/json", + "response_json_schema": schema, + } + transform_request_params = { + "messages": messages, + "model": "gemini/gemini-3.1-flash-lite", + "optional_params": optional_params, + "custom_llm_provider": "gemini", + "litellm_params": {}, + "cached_content": None, + } + + rb: RequestBody = transformation._transform_request_body(**transform_request_params) + + gen = rb["generationConfig"] + assert "responseFormat" in gen + assert gen["responseFormat"]["text"]["mimeType"] == "APPLICATION_JSON" + assert gen["responseFormat"]["text"]["schema"] == schema + assert "response_mime_type" not in gen + assert "response_json_schema" not in gen + + def test_map_function_google_search_snake_case(): """ Test that google_search tool (snake_case) is properly mapped to googleSearch. diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py index 628a6ed4cba..d99c190c6e5 100644 --- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py @@ -285,6 +285,80 @@ def test_extra_body_tags_not_forwarded_to_vertex_ai(): assert result["custom_param"] == "allowed" +def test_extra_body_google_maps_rewrites_json_response_format(): + messages = [{"role": "user", "content": "test"}] + optional_params = { + "response_mime_type": "application/json", + "response_schema": { + "type": "object", + "properties": {"answer": {"type": "string"}}, + }, + "extra_body": { + "tools": [{"googleMaps": {}}], + }, + } + + result = _transform_request_body( + messages=messages, + model="gemini-2.5-pro", + optional_params=optional_params, + custom_llm_provider="vertex_ai", + litellm_params={}, + cached_content=None, + ) + + generation_config = result["generationConfig"] + assert "response_mime_type" not in generation_config + assert generation_config["responseFormat"] == { + "text": { + "mimeType": "APPLICATION_JSON", + "schema": { + "type": "object", + "properties": {"answer": {"type": "string"}}, + }, + } + } + + +def test_extra_body_generation_config_cannot_restore_google_maps_json_mime_type(): + messages = [{"role": "user", "content": "test"}] + optional_params = { + "tools": [{"googleMaps": {}}], + "response_mime_type": "application/json", + "extra_body": { + "generationConfig": { + "response_mime_type": "application/json", + "response_json_schema": { + "type": "object", + "properties": {"answer": {"type": "string"}}, + }, + }, + }, + } + + result = _transform_request_body( + messages=messages, + model="gemini-2.5-pro", + optional_params=optional_params, + custom_llm_provider="vertex_ai", + litellm_params={}, + cached_content=None, + ) + + generation_config = result["generationConfig"] + assert "response_mime_type" not in generation_config + assert "response_json_schema" not in generation_config + assert generation_config["responseFormat"] == { + "text": { + "mimeType": "APPLICATION_JSON", + "schema": { + "type": "object", + "properties": {"answer": {"type": "string"}}, + }, + } + } + + def test_metadata_to_labels_vertex_only(): """Test that metadata->labels conversion only happens for Vertex AI""" messages = [{"role": "user", "content": "test"}] diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py index 45b9f4293fa..0d02521433a 100644 --- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py @@ -3078,6 +3078,83 @@ def test_vertex_ai_gemini3_tool_combination_no_drop(): assert len(tools) == 3 +def test_get_optional_params_keeps_google_search_with_server_side_flag(): + """ + include_server_side_tool_invocations must be in non_default_params before + map_openai_params runs (not only via add_provider_specific_params after). + """ + from litellm.utils import get_optional_params + + optional_params = get_optional_params( + model="gemini-3.1-pro-preview", + custom_llm_provider="gemini", + tools=[ + {"google_search": {}}, + { + "type": "function", + "function": { + "name": "send_message", + "description": "Send a message back", + "parameters": { + "type": "object", + "properties": {"message": {"type": "string"}}, + "required": ["message"], + }, + }, + }, + ], + include_server_side_tool_invocations=True, + ) + + assert optional_params.get("include_server_side_tool_invocations") is True + tool_keys = set() + for tool in optional_params.get("tools", []): + tool_keys.update(tool.keys()) + assert "function_declarations" in tool_keys + assert "googleSearch" in tool_keys + + +def test_map_openai_params_tools_before_include_server_side_flag(): + """ + Request bodies often list tools before include_server_side_tool_invocations. + Search tools must not be dropped when the flag is present later in the dict. + """ + v = VertexGeminiConfig() + optional_params: dict = {} + non_default_params = { + "tools": [ + {"google_search": {}}, + { + "type": "function", + "function": { + "name": "send_message", + "description": "Send a message back", + "parameters": { + "type": "object", + "properties": {"message": {"type": "string"}}, + "required": ["message"], + }, + }, + }, + ], + "include_server_side_tool_invocations": True, + } + + result = v.map_openai_params( + non_default_params=non_default_params, + optional_params=optional_params, + model="gemini-3.1-pro-preview", + drop_params=True, + ) + + assert result.get("include_server_side_tool_invocations") is True + tool_keys = set() + for tool in result.get("tools", []): + tool_keys.update(tool.keys()) + assert "function_declarations" in tool_keys + assert "googleSearch" in tool_keys + + def test_vertex_ai_mixed_tools_and_web_search_options_drops_search(): """ When function tools and web_search_options are sent separately (Codex-style), From 20dc6dffa413535fcdc9ecb913cd6f020f67c3ad Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Thu, 4 Jun 2026 20:14:51 +0530 Subject: [PATCH 28/92] fix(proxy): passthrough 404 when SERVER_ROOT_PATH is set (#29658) * fix(proxy): match passthrough registry routes bare-to-bare with SERVER_ROOT_PATH After #28547, get_request_route strips the deployment prefix while registry lookup still re-inflated stored paths via SERVER_ROOT_PATH, causing 404s under paths like /llmproxy/ml. Compare normalized bare routes in both is_registered_pass_through_route and get_registered_pass_through_route. Co-authored-by: Cursor * test(proxy): patch utils.get_server_root_path in passthrough auth tests After removing get_server_root_path from pass_through_endpoints, route and JWT tests must mock litellm.proxy.utils where normalization reads it. Co-authored-by: Cursor --------- Co-authored-by: Cursor --- .../pass_through_endpoints.py | 49 ++--- .../proxy/auth/test_handle_jwt.py | 2 +- .../proxy/auth/test_route_checks.py | 14 +- .../test_pass_through_endpoints.py | 190 +++++++----------- 4 files changed, 108 insertions(+), 147 deletions(-) diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index e49e1302ab5..6667010447b 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -59,7 +59,7 @@ from litellm.proxy.common_utils.http_parsing_utils import ( _safe_get_request_headers, ) from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup -from litellm.proxy.utils import get_server_root_path, normalize_route_for_root_path +from litellm.proxy.utils import normalize_route_for_root_path from litellm.secret_managers.main import get_secret_str from litellm.types.llms.custom_http import httpxSpecialProvider from litellm.types.passthrough_endpoints.pass_through_endpoints import ( @@ -2499,20 +2499,16 @@ class InitPassThroughEndpointHelpers: return list(_registered_pass_through_routes.keys()) @staticmethod - def _build_full_path_with_root(path: str) -> str: + def _route_for_registry_lookup(route: str) -> str: """ - Build full path by prepending server root path if needed. + Normalize an incoming route to the bare path stored in the registry. - Args: - path: The relative path to build - - Returns: - Full path with server root prepended (if root is not "/") + Registry keys store root-stripped paths. Callers should pass routes from + ``get_request_route()`` (already stripped); prefixed ``request.url.path`` + values are stripped via ``normalize_route_for_root_path``. """ - root_path = get_server_root_path() - if root_path == "/": - return path - return f"{root_path}{path}" + normalized_route = normalize_route_for_root_path(route) + return normalized_route if normalized_route is not None else route @staticmethod def is_registered_pass_through_route(route: str) -> bool: @@ -2535,6 +2531,10 @@ class InitPassThroughEndpointHelpers: if normalized_route.startswith(mapped_route): return True + comparison_route = InitPassThroughEndpointHelpers._route_for_registry_lookup( + route + ) + # Fast path: check if any registered route key contains this path # Keys are in format: "{endpoint_id}:exact:{path}:{methods}" or "{endpoint_id}:subpath:{path}:{methods}" # For backward compatibility, also support old format: "{endpoint_id}:exact:{path}" or "{endpoint_id}:subpath:{path}" @@ -2543,14 +2543,13 @@ class InitPassThroughEndpointHelpers: parts = key.split(":", 3) # Split into [endpoint_id, type, path, methods?] if len(parts) >= 3: route_type = parts[1] - registered_path = ( - InitPassThroughEndpointHelpers._build_full_path_with_root(parts[2]) - ) - if route_type == "exact" and route == registered_path: + registered_path = parts[2] + if route_type == "exact" and comparison_route == registered_path: return True elif route_type == "subpath": - if route == registered_path or route.startswith( - registered_path + "/" + if ( + comparison_route == registered_path + or comparison_route.startswith(registered_path + "/") ): return True @@ -2561,13 +2560,14 @@ class InitPassThroughEndpointHelpers: route: str, method: Optional[str] = None ) -> Optional[Dict[str, Any]]: """Get passthrough params for a given route and optionally filter by HTTP method""" + comparison_route = InitPassThroughEndpointHelpers._route_for_registry_lookup( + route + ) for key in _registered_pass_through_routes.keys(): parts = key.split(":", 3) # Split into [endpoint_id, type, path, methods?] if len(parts) >= 3: route_type = parts[1] - registered_path = ( - InitPassThroughEndpointHelpers._build_full_path_with_root(parts[2]) - ) + registered_path = parts[2] # Get the methods for this route. Prefer the registered metadata, # but keep supporting test fixtures / older registry entries that @@ -2581,11 +2581,12 @@ class InitPassThroughEndpointHelpers: # Check if path matches path_matches = False - if route_type == "exact" and route == registered_path: + if route_type == "exact" and comparison_route == registered_path: path_matches = True elif route_type == "subpath": - if route == registered_path or route.startswith( - registered_path + "/" + if ( + comparison_route == registered_path + or comparison_route.startswith(registered_path + "/") ): path_matches = True diff --git a/tests/test_litellm/proxy/auth/test_handle_jwt.py b/tests/test_litellm/proxy/auth/test_handle_jwt.py index 41fc417d979..92bd7915152 100644 --- a/tests/test_litellm/proxy/auth/test_handle_jwt.py +++ b/tests/test_litellm/proxy/auth/test_handle_jwt.py @@ -233,7 +233,7 @@ async def test_find_team_with_model_access_uses_request_method_for_passthrough_a mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): diff --git a/tests/test_litellm/proxy/auth/test_route_checks.py b/tests/test_litellm/proxy/auth/test_route_checks.py index 197572216d0..63b61954cf6 100644 --- a/tests/test_litellm/proxy/auth/test_route_checks.py +++ b/tests/test_litellm/proxy/auth/test_route_checks.py @@ -733,7 +733,7 @@ def test_virtual_key_llm_api_routes_allows_registered_pass_through_endpoints(): mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): @@ -799,7 +799,7 @@ def test_virtual_key_llm_api_routes_allows_non_auth_enforced_pass_through_endpoi mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): @@ -849,7 +849,7 @@ def test_virtual_key_llm_api_routes_denies_auth_pass_through_without_allowlist() mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): @@ -893,7 +893,7 @@ def test_virtual_key_llm_api_routes_uses_method_specific_auth_setting(): mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): @@ -948,7 +948,7 @@ def test_non_proxy_admin_denies_auth_pass_through_without_allowlist(): mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): @@ -987,7 +987,7 @@ def test_non_proxy_admin_allows_auth_pass_through_with_team_allowlist(): mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): @@ -1021,7 +1021,7 @@ def test_virtual_key_without_llm_api_routes_cannot_access_pass_through(): mock_registered_routes, ), patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", + "litellm.proxy.utils.get_server_root_path", return_value="/", ), ): diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py index 89c57bcced6..9b9d5e22a43 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py @@ -1386,10 +1386,6 @@ async def test_create_pass_through_endpoint_auth_true_enforces_allowlist(): "litellm.proxy.pass_through_endpoints.pass_through_endpoints._registered_pass_through_routes", registry, ), - patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", - return_value="/", - ), ): mock_get_config.return_value = ConfigFieldInfo( field_name="pass_through_endpoints", field_value=[] @@ -1485,10 +1481,6 @@ async def test_update_pass_through_endpoint_auth_true_enforces_allowlist(): "litellm.proxy.pass_through_endpoints.pass_through_endpoints._registered_pass_through_routes", registry, ), - patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", - return_value="/", - ), ): mock_get_config.return_value = ConfigFieldInfo( field_name="pass_through_endpoints", field_value=existing_endpoints @@ -1570,10 +1562,6 @@ async def test_update_pass_through_endpoint_preserves_auth_false(): "litellm.proxy.pass_through_endpoints.pass_through_endpoints._registered_pass_through_routes", registry, ), - patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path", - return_value="/", - ), ): mock_get_config.return_value = ConfigFieldInfo( field_name="pass_through_endpoints", field_value=existing_endpoints @@ -2866,70 +2854,10 @@ async def test_create_pass_through_route_no_custom_body_falls_back(): assert call_kwargs["custom_body"] == request_parsed_body -def test_build_full_path_with_root_default(): - """ - Test _build_full_path_with_root with default root path (/) - """ - from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( - InitPassThroughEndpointHelpers, - ) - - with patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path" - ) as mock_get_root: - # Test with default root path - mock_get_root.return_value = "/" - - result = InitPassThroughEndpointHelpers._build_full_path_with_root( - "/api/v1/endpoint" - ) - assert result == "/api/v1/endpoint" - - -def test_build_full_path_with_root_custom(): - """ - Test _build_full_path_with_root with custom root path - """ - from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( - InitPassThroughEndpointHelpers, - ) - - with patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path" - ) as mock_get_root: - # Test with custom root path /proxy - mock_get_root.return_value = "/proxy" - - result = InitPassThroughEndpointHelpers._build_full_path_with_root( - "/api/v1/endpoint" - ) - assert result == "/proxy/api/v1/endpoint" - - -def test_build_full_path_with_root_nested(): - """ - Test _build_full_path_with_root with nested root path - """ - from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( - InitPassThroughEndpointHelpers, - ) - - with patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path" - ) as mock_get_root: - # Test with nested root path /api/v2 - mock_get_root.return_value = "/api/v2" - - result = InitPassThroughEndpointHelpers._build_full_path_with_root("/endpoint") - assert result == "/api/v2/endpoint" - - def test_is_registered_pass_through_route_with_custom_root(): """ - Test is_registered_pass_through_route correctly handles server root path - - When server has a custom root path like /proxy, the registered path - should be constructed by prepending the root to match incoming routes. + Registry stores bare paths; incoming routes may be bare (get_request_route) + or prefixed (request.url.path). Both should resolve via normalization. """ from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( InitPassThroughEndpointHelpers, @@ -2948,32 +2876,13 @@ def test_is_registered_pass_through_route_with_custom_root(): "headers": {}, } - with patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path" - ) as mock_get_root: - # Test with custom root path /proxy - mock_get_root.return_value = "/proxy" - - # Should match when request route includes the root path + with patch("litellm.proxy.utils.get_server_root_path", return_value="/proxy"): assert ( InitPassThroughEndpointHelpers.is_registered_pass_through_route( "/proxy/api/endpoint" ) is True ) - - # Should not match when request route doesn't include root path - assert ( - InitPassThroughEndpointHelpers.is_registered_pass_through_route( - "/api/endpoint" - ) - is False - ) - - # Test with default root path - mock_get_root.return_value = "/" - - # Should match with default root assert ( InitPassThroughEndpointHelpers.is_registered_pass_through_route( "/api/endpoint" @@ -2981,7 +2890,13 @@ def test_is_registered_pass_through_route_with_custom_root(): is True ) - # Should not match with root prepended when root is / + with patch("litellm.proxy.utils.get_server_root_path", return_value="/"): + assert ( + InitPassThroughEndpointHelpers.is_registered_pass_through_route( + "/api/endpoint" + ) + is True + ) assert ( InitPassThroughEndpointHelpers.is_registered_pass_through_route( "/proxy/api/endpoint" @@ -2995,10 +2910,8 @@ def test_is_registered_pass_through_route_with_custom_root(): def test_get_registered_pass_through_route_with_custom_root(): """ - Test get_registered_pass_through_route correctly handles server root path - - When server has a custom root path, the method should return the correct - endpoint configuration by matching the full path including the root. + get_registered_pass_through_route matches bare registry paths against + bare or SERVER_ROOT_PATH-prefixed incoming routes. """ from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( InitPassThroughEndpointHelpers, @@ -3019,13 +2932,8 @@ def test_get_registered_pass_through_route_with_custom_root(): route_key = f"{endpoint_id}:exact:{path}" _registered_pass_through_routes[route_key] = target_config - with patch( - "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_server_root_path" - ) as mock_get_root: - # Test with custom root path /litellm - mock_get_root.return_value = "/litellm" - - # Should return config when request route includes root path + with patch("litellm.proxy.utils.get_server_root_path", return_value="/litellm"): + # Prefixed incoming route result = InitPassThroughEndpointHelpers.get_registered_pass_through_route( "/litellm/chat/completions" ) @@ -3033,16 +2941,14 @@ def test_get_registered_pass_through_route_with_custom_root(): assert result["target"] == "http://api.example.com/v1/chat/completions" assert result["headers"]["Authorization"] == "Bearer token123" - # Should return None when route doesn't match + # Bare incoming route (get_request_route convention) result = InitPassThroughEndpointHelpers.get_registered_pass_through_route( "/chat/completions" ) - assert result is None + assert result is not None + assert result["target"] == "http://api.example.com/v1/chat/completions" - # Test with default root path - mock_get_root.return_value = "/" - - # Should return config with default root + with patch("litellm.proxy.utils.get_server_root_path", return_value="/"): result = InitPassThroughEndpointHelpers.get_registered_pass_through_route( "/chat/completions" ) @@ -3053,6 +2959,62 @@ def test_get_registered_pass_through_route_with_custom_root(): _registered_pass_through_routes.clear() +@pytest.mark.parametrize( + "server_root_path,route_type,incoming_route,should_match", + [ + ("", "subpath", "/ml/api/v1/time-series-forecast/predict", True), + ("", "exact", "/ml", True), + ("", "exact", "/ml/extra", False), + ("/llmproxy", "subpath", "/ml/api/v1/time-series-forecast/predict", True), + ( + "/llmproxy", + "subpath", + "/llmproxy/ml/api/v1/time-series-forecast/predict", + True, + ), + ("/llmproxy", "exact", "/ml", True), + ("/llmproxy", "exact", "/llmproxy/ml", True), + ("/llmproxy", "subpath", "/other/api", False), + ], +) +def test_db_registered_pass_through_route_bare_path_convention( + server_root_path, route_type, incoming_route, should_match +): + """ + Regression: #28547 / SERVER_ROOT_PATH — registry stores bare /ml paths; + get_request_route() supplies bare paths; prefixed url.path must still match. + """ + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + InitPassThroughEndpointHelpers, + _registered_pass_through_routes, + ) + + _registered_pass_through_routes.clear() + endpoint_id = "customer-ml" + path = "/ml" + route_key = f"{endpoint_id}:{route_type}:{path}:GET,POST" + _registered_pass_through_routes[route_key] = { + "endpoint_id": endpoint_id, + "path": path, + "type": route_type, + "target": "https://example.com", + "methods": ["GET", "POST"], + } + + with patch( + "litellm.proxy.utils.get_server_root_path", + return_value=server_root_path, + ): + assert ( + InitPassThroughEndpointHelpers.is_registered_pass_through_route( + incoming_route + ) + is should_match + ) + + _registered_pass_through_routes.clear() + + def test_mapped_pass_through_routes_with_server_root_path(): """ Mapped passthrough routes (vertex_ai, bedrock, etc) should match @@ -3064,9 +3026,7 @@ def test_mapped_pass_through_routes_with_server_root_path(): InitPassThroughEndpointHelpers, ) - with patch("litellm.proxy.utils.get_server_root_path") as mock_get_root: - mock_get_root.return_value = "/litellm" - + with patch("litellm.proxy.utils.get_server_root_path", return_value="/litellm"): # prefixed route should match mapped routes like /vertex_ai assert ( InitPassThroughEndpointHelpers.is_registered_pass_through_route( From ed073d382d75b42f62f600ce47a5fe0ffade70fa Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Thu, 4 Jun 2026 20:33:24 +0530 Subject: [PATCH 29/92] fix(gemini-realtime): use GA event names for Pipecat 1.3.x compatibility (#29662) * fix(gemini-realtime): use GA event names for Pipecat 1.3.x compatibility Pipecat v1.3.0 adopted the OpenAI Realtime API GA event naming: response.audio.delta -> response.output_audio.delta response.text.delta -> response.output_text.delta response.audio.done -> response.output_audio.done response.text.done -> response.output_text.done The proxy was still emitting the old beta names; Pipecat's `parse_server_event` raises "Unimplemented server event type" for any unknown type, which killed the receive task handler and broke audio playback and tool-call delivery. Also: - conversation.item.created -> conversation.item.added (already handled) - client audio is buffered until backend setupComplete in deferred mode - call_id fallback UUID when Gemini returns empty id - status_details / token detail fields added to Pydantic-strict events The _GA_TO_BETA_EVENT_TYPES map in RealTimeStreaming already translates GA names back to beta for clients that opt in with the openai-beta header, so legacy clients are unaffected. Co-authored-by: Cursor * fix(gemini-realtime): address greptile review comments - emit outputTranscription as response.output_audio_transcript.delta instead of suppressing it; GA_TO_BETA map handles translation for legacy clients - cap pre-setup audio buffer at 200 frames to prevent memory exhaustion; log a warning when the limit is hit and additional frames are dropped - log remaining dropped message count on flush error Co-authored-by: Cursor * fix(gemini-realtime): address veria review comments - remove unused OpenAIRealtimeConversationItemCreated import - fix guardrail bypass: semantic_vad early-return now preserves create_response when set so a guardrail-injected create_response:false is not silently dropped - add per-connection 10 MB byte cap alongside the 200-frame count cap for the pre-setup audio buffer to prevent memory exhaustion Co-authored-by: Cursor * fix(gemini-realtime): fix mypy arg-type on _finalize_gemini_live_setup setup parameter typed as BidiGenerateContentSetup to match the TypedDict passed at both call sites; was dict which mypy rejected. Co-authored-by: Cursor * fix(gemini-realtime): widen _finalize_gemini_live_setup to Dict[str, Any] BidiGenerateContentSetup (TypedDict) is a subtype of Dict[str,Any] so both call sites (one passing a plain dict, one passing the TypedDict) satisfy mypy. Co-authored-by: Cursor * fix(gemini-realtime): cast BidiGenerateContentSetup to Dict at _finalize call site mypy rejects TypedDict as dict[str, Any] argument; cast at the call site where follow_up_setup is BidiGenerateContentSetup to satisfy the checker. Co-authored-by: Cursor * Fix Gemini realtime beta compatibility * Fix deferred Gemini setup audio ordering * fix: preserve Gemini audio transcript ids * fix(realtime): cap pre-setup client buffer on all append paths Route every append to the deferred-setup pending buffer through the per-connection message/byte caps. Previously only the audio-buffer fast path enforced the caps; once one frame was buffered, a client that withheld session.update could stream arbitrary frames into _pending_messages_until_setup unbounded and exhaust proxy memory. * style(gemini-realtime): apply black formatting to transformation.py * fix(gemini-realtime): log beta-translation fallback and name native-audio marker Surface the previously swallowed exception in _send_event_to_client so a failed GA->beta translation is observable instead of silently forwarding the untranslated event. Extract the native-audio model substring used by _finalize_gemini_live_setup into a named constant documenting why speechConfig is dropped on those setups. --------- Co-authored-by: Cursor Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .../litellm_core_utils/realtime_streaming.py | 142 +++++++- .../llms/gemini/realtime/transformation.py | 229 +++++++++--- .../test_realtime_streaming.py | 340 ++++++++++++++++++ .../test_gemini_realtime_transformation.py | 193 +++++++++- .../test_vertex_ai_realtime_transformation.py | 4 +- 5 files changed, 848 insertions(+), 60 deletions(-) diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py index 33bb6d7d2ea..772f058d9bb 100644 --- a/litellm/litellm_core_utils/realtime_streaming.py +++ b/litellm/litellm_core_utils/realtime_streaming.py @@ -92,8 +92,27 @@ class RealTimeStreaming: # Track whether we have already sent the guardrail turn-detection update # that disables provider auto-response for transcription guardrails. self._guardrail_turn_detection_update_sent: bool = False + # Deferred Gemini Live setup: Pipecat may stream audio before session.update. + # Buffer client audio until the backend acknowledges setup (setupComplete). + self._backend_setup_complete: bool = ( + provider_config is None or provider_config.requires_session_configuration() + ) + self._flushing_pending_messages_until_setup: bool = False + self._pending_messages_until_setup: List[str] = [] + self._pending_messages_byte_total: int = 0 + + # Per-connection caps for pre-setup audio frames (message count + total bytes). + _MAX_BUFFERED_MESSAGES: int = 200 + _MAX_BUFFERED_BYTES: int = 10 * 1024 * 1024 # 10 MB _SESSION_EVENT_TYPES = frozenset(["session.created", "session.updated"]) + _CLIENT_AUDIO_BUFFER_TYPES = frozenset( + [ + "input_audio_buffer.append", + "input_audio_buffer.commit", + "input_audio_buffer.clear", + ] + ) _AUDIO_FORMAT_MAP: Dict[str, Dict[str, Any]] = { "pcm16": {"type": "audio/pcm", "rate": 24000}, "g711_ulaw": {"type": "audio/G711-ulaw", "rate": 8000}, @@ -285,6 +304,86 @@ class RealTimeStreaming: await self.backend_ws.send(message) # type: ignore[union-attr, attr-defined] return True + def _uses_deferred_backend_setup(self) -> bool: + """True when setup is deferred until the client's first session.update.""" + if self.provider_config is None: + return False + return not self.provider_config.requires_session_configuration() + + def _should_buffer_client_message_until_setup(self, message: str) -> bool: + if not self._uses_deferred_backend_setup(): + return False + if ( + self._backend_setup_complete + and not self._flushing_pending_messages_until_setup + ): + return False + try: + msg_obj = json.loads(message) + except (json.JSONDecodeError, TypeError): + return False + return msg_obj.get("type") in RealTimeStreaming._CLIENT_AUDIO_BUFFER_TYPES + + def _buffer_pending_message_until_setup(self, message: str) -> None: + msg_bytes = len(message.encode("utf-8")) + if ( + len(self._pending_messages_until_setup) + < RealTimeStreaming._MAX_BUFFERED_MESSAGES + and self._pending_messages_byte_total + msg_bytes + <= RealTimeStreaming._MAX_BUFFERED_BYTES + ): + self._pending_messages_until_setup.append(message) + self._pending_messages_byte_total += msg_bytes + else: + verbose_logger.warning( + "Pre-setup buffer full (%d messages / %d bytes); dropping frame", + len(self._pending_messages_until_setup), + self._pending_messages_byte_total, + ) + + async def _flush_pending_messages_until_setup(self) -> bool: + pending = self._pending_messages_until_setup + self._pending_messages_until_setup = [] + self._pending_messages_byte_total = 0 + for idx, message in enumerate(pending): + try: + await self._send_to_backend(message) + except Exception as e: + unsent = pending[idx:] + self._pending_messages_until_setup = ( + unsent + self._pending_messages_until_setup + ) + self._pending_messages_byte_total = sum( + len(msg.encode("utf-8")) + for msg in self._pending_messages_until_setup + ) + verbose_logger.debug( + "Failed to flush buffered client message after setup: %s " + "(%d buffered message(s) retained)", + e, + len(unsent), + ) + return False + return True + + async def _send_event_to_client(self, event: Any, event_str: str) -> bool: + if self._client_wants_beta and isinstance(event, dict): + try: + translated = self._translate_event_to_beta(event) + if translated is None: + return False + await self.websocket.send_text(json.dumps(translated)) + return True + except Exception as e: + verbose_logger.warning( + "Failed to translate %s to beta protocol, forwarding " + "untranslated event to client: %s", + event.get("type"), + e, + ) + await self.websocket.send_text(event_str) + return True + def _cache_session_configuration_request(self, transformed_message: str) -> None: """Store setup payload once sent to backend. @@ -547,6 +646,19 @@ class RealTimeStreaming: isinstance(event, dict) and event.get("type") == "session.created" ) if is_session_created_event: + if ( + self._uses_deferred_backend_setup() + and not self._backend_setup_complete + ): + self._backend_setup_complete = True + self._flushing_pending_messages_until_setup = True + try: + while self._pending_messages_until_setup: + flushed = await self._flush_pending_messages_until_setup() + if not flushed: + break + finally: + self._flushing_pending_messages_until_setup = False if self._session_created_sent_to_client: # A synthetic session.created (with placeholder defaults) was # already forwarded to the client when we connected. The @@ -569,7 +681,7 @@ class RealTimeStreaming: ## update if a prior attempt was dropped by the provider transform. if is_session_created_event and self._has_audio_transcription_guardrails(): self.store_message(event_str) - await self.websocket.send_text(event_str) + await self._send_event_to_client(event, event_str) await self._maybe_send_guardrail_turn_detection_update() continue ## GUARDRAIL: run on transcription events in provider_config path too @@ -581,7 +693,7 @@ class RealTimeStreaming: transcript = event.get("transcript", "") self._collect_user_input_from_backend_event(cast(dict, event)) self.store_message(event_str) - await self.websocket.send_text(event_str) + await self._send_event_to_client(event, event_str) blocked = await self.run_realtime_guardrails( cast(str, transcript), item_id=cast(Optional[str], event.get("item_id")), @@ -591,7 +703,7 @@ class RealTimeStreaming: continue ## LOGGING self.store_message(event_str) - await self.websocket.send_text(event_str) + await self._send_event_to_client(event, event_str) async def _handle_raw_backend_message(self, raw_response) -> bool: """Process a backend message without provider_config (raw path). @@ -880,6 +992,7 @@ class RealTimeStreaming: ## GUARDRAIL: intercept conversation.item.create for text-based injection. guardrail_turn_detection_injected = False + msg_type: Optional[str] = None try: msg_obj = json.loads(message) msg_type = msg_obj.get("type") @@ -1081,6 +1194,29 @@ class RealTimeStreaming: # actually forward to the backend. self.store_input(message=message) + if self._should_buffer_client_message_until_setup(message): + self._buffer_pending_message_until_setup(message) + continue + + if self._pending_messages_until_setup: + should_send_setup_before_buffered_messages = ( + not self._backend_setup_complete + and not self._flushing_pending_messages_until_setup + and msg_type == "session.update" + ) + if not should_send_setup_before_buffered_messages: + self._buffer_pending_message_until_setup(message) + if ( + self._backend_setup_complete + and not self._flushing_pending_messages_until_setup + ): + await self._flush_pending_messages_until_setup() + continue + + if self._flushing_pending_messages_until_setup: + self._buffer_pending_message_until_setup(message) + continue + ## FORWARD TO BACKEND # Only mark the guardrail turn_detection update as sent after the # backend actually accepted the message. Setting the flag earlier diff --git a/litellm/llms/gemini/realtime/transformation.py b/litellm/llms/gemini/realtime/transformation.py index cf1fc75ef10..212287fb7f8 100644 --- a/litellm/llms/gemini/realtime/transformation.py +++ b/litellm/llms/gemini/realtime/transformation.py @@ -27,7 +27,6 @@ from litellm.types.llms.gemini import ( ) from litellm.types.llms.openai import ( OpenAIRealtimeContentPartDone, - OpenAIRealtimeConversationItemCreated, OpenAIRealtimeDoneEvent, OpenAIRealtimeEvents, OpenAIRealtimeEventTypes, @@ -79,6 +78,12 @@ _KNOWN_GEMINI_TOP_LEVEL_KEYS: set = { map_key.split(".", 1)[0] for map_key in MAP_GEMINI_FIELD_TO_OPENAI_EVENT } +# Gemini Live native-audio model ids carry this marker (e.g. +# ``gemini-2.5-flash-native-audio-preview-09-2025``). These models reject a +# ``speechConfig`` on ``setup`` with a 1007 invalid-argument error, so it is +# stripped in ``_finalize_gemini_live_setup``. +_GEMINI_NATIVE_AUDIO_MODEL_MARKER = "native-audio" + class GeminiRealtimeConfig(BaseRealtimeConfig): # Cap the LRU of in-flight tool calls so long sessions with many tool @@ -98,6 +103,33 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): # bypassing spend and budget accounting. self._pending_usage_metadata: Optional[dict] = None + @staticmethod + def _usage_detail_alias(details: Any, defaults: Dict[str, int]) -> Dict[str, Any]: + if not isinstance(details, dict): + return dict(defaults) + return { + **defaults, + **{key: value for key, value in details.items() if value is not None}, + } + + @staticmethod + def _add_pipecat_usage_detail_aliases(usage_dict: Dict[str, Any]) -> Dict[str, Any]: + usage_dict.setdefault( + "input_token_details", + GeminiRealtimeConfig._usage_detail_alias( + usage_dict.get("input_tokens_details"), + {"cached_tokens": 0, "text_tokens": 0, "audio_tokens": 0}, + ), + ) + usage_dict.setdefault( + "output_token_details", + GeminiRealtimeConfig._usage_detail_alias( + usage_dict.get("output_tokens_details"), + {"text_tokens": 0, "audio_tokens": 0}, + ), + ) + return usage_dict + def validate_environment( self, headers: dict, model: str, api_key: Optional[str] = None ) -> dict: @@ -173,9 +205,25 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): def map_automatic_turn_detection( self, value: OpenAIRealtimeTurnDetection ) -> AutomaticActivityDetection: + """Map OpenAI ``server_vad`` to Gemini ``automaticActivityDetection``. + + OpenAI ``semantic_vad`` has no Gemini Live equivalent — return an empty + dict so callers omit ``realtimeInputConfig`` (mapping it with + ``disabled: true`` breaks native-audio sessions). + """ + if ( + isinstance(value, dict) + and value.get("type") == "semantic_vad" + and "create_response" not in value + ): + return AutomaticActivityDetection() + automatic_activity_dection = AutomaticActivityDetection() if "create_response" in value and isinstance(value["create_response"], bool): automatic_activity_dection["disabled"] = not value["create_response"] + elif isinstance(value, dict) and value.get("type") == "server_vad": + # OpenAI server VAD enables activity detection by default. + automatic_activity_dection["disabled"] = False else: automatic_activity_dection["disabled"] = True if "prefix_padding_ms" in value and isinstance(value["prefix_padding_ms"], int): @@ -197,6 +245,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): "tools", "input_audio_transcription", "turn_detection", + "voice", ] def map_openai_params( @@ -231,17 +280,33 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): optional_params["inputAudioTranscription"] = {} elif key == "turn_detection": value_typed = cast(OpenAIRealtimeTurnDetection, value) + if ( + isinstance(value_typed, dict) + and value_typed.get("type") == "semantic_vad" + and "create_response" not in value_typed + ): + # Pipecat/OpenAI GA semantic VAD — skip; Gemini uses its own VAD. + # Only skip when there is no create_response override so that + # a guardrail-injected create_response:false is not dropped. + continue transformed_audio_activity_config = self.map_automatic_turn_detection( value_typed ) - if ( - len(transformed_audio_activity_config) > 0 - ): # if the config is not empty, add it to the optional params + if transformed_audio_activity_config: optional_params["realtimeInputConfig"] = ( BidiGenerateContentRealtimeInputConfig( automaticActivityDetection=transformed_audio_activity_config ) ) + elif key == "voice": + from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( + VertexGeminiConfig, + ) + + vertex_gemini_config = VertexGeminiConfig() + speech_config = vertex_gemini_config._map_audio_params({"voice": value}) + if speech_config: + optional_params["generationConfig"]["speechConfig"] = speech_config if len(optional_params["generationConfig"]) == 0: optional_params.pop("generationConfig") return optional_params @@ -297,6 +362,9 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): and "transcription" in input_cfg ): normalized["input_audio_transcription"] = input_cfg["transcription"] + output_cfg = audio.get("output") + if isinstance(output_cfg, dict) and output_cfg.get("voice"): + normalized["voice"] = output_cfg["voice"] extracted_turn_detection = GeminiRealtimeConfig._extract_turn_detection( normalized @@ -308,6 +376,18 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return normalized + @staticmethod + def _finalize_gemini_live_setup( + model: str, setup: Dict[str, Any] + ) -> Dict[str, Any]: + """Drop fields Gemini Live native-audio rejects on ``setup``.""" + if _GEMINI_NATIVE_AUDIO_MODEL_MARKER not in model.lower(): + return setup + generation_config = setup.get("generationConfig") + if isinstance(generation_config, dict): + generation_config.pop("speechConfig", None) + return setup + def _handle_session_update( self, json_message: dict, @@ -351,7 +431,11 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): verbose_logger.debug( "Gemini Realtime: Sending initial setup with tools to backend" ) - return [json.dumps({"setup": new_overrides})] + return [ + json.dumps( + {"setup": self._finalize_gemini_live_setup(model, new_overrides)} + ) + ] if not new_overrides: verbose_logger.debug( @@ -420,7 +504,15 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): verbose_logger.debug( "Gemini Realtime: Forwarding session.update as follow-up setup" ) - return [json.dumps({"setup": follow_up_setup})] + return [ + json.dumps( + { + "setup": self._finalize_gemini_live_setup( + model, cast(Dict[str, Any], follow_up_setup) + ) + } + ) + ] def _handle_conversation_item(self, json_message: dict) -> List[str]: """ @@ -666,6 +758,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): "object": "realtime.response", "id": response_id, "status": "in_progress", + "status_details": None, "output": [], "conversation_id": conversation_id, "modalities": _modalities, @@ -675,9 +768,10 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ) response_items.append(response_created) - ## - return response.output_item.added ← adds ‘item_id’ same for all subsequent events + ## - return response.output_item.added response_output_item_added = OpenAIRealtimeStreamResponseOutputItemAdded( type="response.output_item.added", + event_id="event_{}".format(uuid.uuid4()), response_id=response_id, output_index=0, item={ @@ -690,20 +784,28 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): }, ) response_items.append(response_output_item_added) - ## - return conversation.item.created - conversation_item_created = OpenAIRealtimeConversationItemCreated( - type="conversation.item.created", - event_id="event_{}".format(uuid.uuid4()), - item={ - "id": output_item_id, - "object": "realtime.item", - "type": "message", - "status": "in_progress", - "role": "assistant", - "content": [], - }, + ## - return conversation.item.added + # Pipecat 1.3.x handles "conversation.item.added" (not ".created"). + # Sending ".created" raises "Unimplemented server event type" which + # kills the receive task handler. + response_items.append( + cast( + OpenAIRealtimeEvents, + { + "type": "conversation.item.added", + "event_id": "event_{}".format(uuid.uuid4()), + "previous_item_id": None, + "item": { + "id": output_item_id, + "object": "realtime.item", + "type": "message", + "status": "in_progress", + "role": "assistant", + "content": [], + }, + }, + ) ) - response_items.append(conversation_item_created) ## - return response.content_part.added response_content_part_added = OpenAIRealtimeResponseContentPartAdded( type="response.content_part.added", @@ -749,9 +851,9 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return OpenAIRealtimeResponseDelta( type=( - "response.text.delta" + "response.output_text.delta" if delta_type == "text" - else "response.audio.delta" + else "response.output_audio.delta" ), content_index=0, event_id="event_{}".format(uuid.uuid4()), @@ -778,7 +880,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): current_response_id = "resp_{}".format(uuid.uuid4()) if delta_type == "text": return OpenAIRealtimeResponseTextDone( - type="response.text.done", + type="response.output_text.done", content_index=0, event_id="event_{}".format(uuid.uuid4()), item_id=current_output_item_id, @@ -788,7 +890,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ) elif delta_type == "audio": return OpenAIRealtimeResponseAudioDone( - type="response.audio.done", + type="response.output_audio.done", content_index=0, event_id="event_{}".format(uuid.uuid4()), item_id=current_output_item_id, @@ -914,7 +1016,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): events: List[OpenAIRealtimeFunctionCallArgumentsDone] = [] for idx, fc in enumerate(function_calls): - call_id = fc.get("id", "") + call_id = fc.get("id", "") or f"call_{uuid.uuid4().hex[:16]}" name = fc.get("name", "") # Store call_id → name mapping for round-trip. Use an LRU so @@ -962,7 +1064,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): current_delta_chunks = [] any_delta_chunk = False for event in transformed_message: - if event["type"] == "response.text.delta": + if event["type"] == "response.output_text.delta": current_delta_chunks.append( cast(OpenAIRealtimeResponseDelta, event) ) @@ -973,7 +1075,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ) else: if ( - transformed_message["type"] == "response.text.delta" + transformed_message["type"] == "response.output_text.delta" ): # ONLY ACCUMULATE TEXT DELTA CHUNKS - AUDIO WILL CAUSE SERVER MEMORY ISSUES if current_delta_chunks is None: current_delta_chunks = [] @@ -1067,6 +1169,8 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): responses_api_usage = LiteLLMCompletionResponsesConfig._transform_chat_completion_usage_to_responses_usage( _chat_completion_usage, ) + _usage_dict = responses_api_usage.model_dump() + self._add_pipecat_usage_detail_aliases(_usage_dict) response_done_event = OpenAIRealtimeDoneEvent( type="response.done", event_id="event_{}".format(uuid.uuid4()), @@ -1074,6 +1178,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): object="realtime.response", id=current_response_id, status="completed", + status_details=None, # type: ignore[typeddict-item] output=( [output_item["item"] for output_item in output_items] if output_items @@ -1081,7 +1186,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ), conversation_id=current_conversation_id, modalities=_modalities, - usage=responses_api_usage.model_dump(), + usage=_usage_dict, ), ) if temperature is not None: @@ -1294,19 +1399,36 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): output_tx = server_content.get("outputTranscription") if isinstance(output_tx, dict) and output_tx.get("text"): + if current_response_id is None: + current_response_id = "resp_{}".format(uuid.uuid4()) + if current_output_item_id is None: + current_output_item_id = "item_{}".format(uuid.uuid4()) + current_conversation_id = ( + current_conversation_id or "conv_{}".format(uuid.uuid4()) + ) + returned_message.extend( + self.return_new_content_delta_events( + session_configuration_request=session_configuration_request, + response_id=current_response_id, + output_item_id=current_output_item_id, + conversation_id=current_conversation_id, + delta_type="audio", + ) + ) + # Emit as the GA event name; _GA_TO_BETA_EVENT_TYPES translates + # this back to response.audio_transcript.delta for beta clients. returned_message.append( cast( OpenAIRealtimeEvents, { - "type": "response.audio_transcript.delta", + "type": "response.output_audio_transcript.delta", "event_id": "event_{}".format(uuid.uuid4()), - "delta": output_tx["text"], - "item_id": current_output_item_id - or "item_{}".format(uuid.uuid4()), - "response_id": current_response_id - or "resp_{}".format(uuid.uuid4()), - "output_index": 0, + "transcript": output_tx["text"], + "item_id": current_output_item_id, "content_index": 0, + "output_index": 0, + "response_id": current_response_id, + "delta": output_tx["text"], }, ) ) @@ -1416,6 +1538,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): "object": "realtime.response", "id": current_response_id, "status": "in_progress", + "status_details": None, "output": [], "conversation_id": current_conversation_id, "modalities": tool_call_modalities, @@ -1460,6 +1583,29 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): }, ) ) + # conversation.item.added — Pipecat 1.3.x registers the + # call_id into _pending_function_calls inside + # _handle_evt_conversation_item_added, which is triggered + # by this event (NOT by response.output_item.added and NOT + # by the old conversation.item.created which Pipecat 1.3.x + # does not handle). Without this event the subsequent + # response.function_call_arguments.done finds an empty + # pending-calls dict and drops the tool invocation silently. + returned_message.append( + cast( + OpenAIRealtimeEvents, + { + "type": "conversation.item.added", + "event_id": f"event_{uuid.uuid4()}", + "previous_item_id": None, + "item": { + **function_call_item, + "status": "in_progress", + "arguments": "", + }, + }, + ) + ) # response.function_call_arguments.delta — Gemini delivers # the full arguments string in a single toolCall frame # rather than streaming partial chunks, so emit one delta @@ -1496,14 +1642,6 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): item={**function_call_item}, ) ) - # conversation.item.created - returned_message.append( - OpenAIRealtimeConversationItemCreated( - type="conversation.item.created", - event_id=f"event_{uuid.uuid4()}", - item={**function_call_item}, - ) - ) # response.done - close the response so clients can submit tool # results. Mirror the non-tool-call RESPONSE_DONE path: if Gemini @@ -1537,6 +1675,8 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): tool_call_responses_api_usage = LiteLLMCompletionResponsesConfig._transform_chat_completion_usage_to_responses_usage( _tool_call_chat_completion_usage, ) + _tool_usage_dict = tool_call_responses_api_usage.model_dump() + self._add_pipecat_usage_detail_aliases(_tool_usage_dict) tool_call_done_event = OpenAIRealtimeDoneEvent( type="response.done", event_id=f"event_{uuid.uuid4()}", @@ -1544,6 +1684,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): id=current_response_id, object="realtime.response", status="completed", + status_details=None, # type: ignore[typeddict-item] output=[ { "id": te["item_id"], @@ -1558,7 +1699,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ], conversation_id=current_conversation_id, modalities=tool_call_modalities, - usage=tool_call_responses_api_usage.model_dump(), + usage=_tool_usage_dict, ), ) tool_call_temperature = tool_call_generation_config.get("temperature") diff --git a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py index 7913efe8294..3424bfd801c 100644 --- a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py +++ b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py @@ -293,6 +293,51 @@ def test_translate_event_to_beta_drops_conversation_item_done(): ) +@pytest.mark.asyncio +async def test_provider_config_path_translates_ga_events_for_beta_clients(): + client_ws = MagicMock() + client_ws.scope = {"headers": [(b"openai-beta", b"realtime=v1")]} + client_ws.send_text = AsyncMock() + backend_ws = MagicMock() + logging_obj = MagicMock() + + provider_config = MagicMock() + provider_config.transform_realtime_response = MagicMock( + return_value={ + "response": [ + { + "type": "response.output_text.delta", + "event_id": "event_1", + "delta": "hello", + }, + {"type": "conversation.item.done", "event_id": "event_2"}, + ], + "current_output_item_id": None, + "current_response_id": None, + "current_delta_chunks": [], + "current_conversation_id": None, + "current_item_chunks": [], + "current_delta_type": None, + "session_configuration_request": None, + } + ) + + streaming = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=provider_config, + model="gemini-2.5-flash", + ) + + await streaming._handle_provider_config_message("{}") + + assert client_ws.send_text.await_count == 1 + sent = json.loads(client_ws.send_text.await_args.args[0]) + assert sent["type"] == "response.text.delta" + assert sent["delta"] == "hello" + + def test_client_sent_openai_beta_realtime_header_detects_header(): ws = MagicMock() ws.scope = {"headers": [(b"openai-beta", b"realtime=v1")]} @@ -1770,3 +1815,298 @@ async def test_follow_up_setup_updates_cached_session_configuration_request(): await streaming.client_ack_messages() assert streaming.session_configuration_request == follow_up_setup + + +@pytest.mark.asyncio +async def test_deferred_setup_buffers_audio_until_backend_setup_complete(monkeypatch): + """Pipecat may send audio before session.update when setup is deferred.""" + monkeypatch.setattr(litellm, "gemini_live_defer_setup", True, raising=False) + from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig + + client_ws = MagicMock() + audio_msg = json.dumps({"type": "input_audio_buffer.append", "audio": "AA=="}) + client_ws.receive_text = AsyncMock( + side_effect=[audio_msg, ConnectionClosed(None, None)] + ) + backend_ws = MagicMock() + backend_ws.send = AsyncMock() + logging_obj = MagicMock() + + config = GeminiRealtimeConfig() + streaming = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=config, + model="gemini-live-2.5-flash-native-audio", + ) + assert streaming._backend_setup_complete is False + + await streaming.client_ack_messages() + + backend_ws.send.assert_not_called() + assert len(streaming._pending_messages_until_setup) == 1 + + streaming._backend_setup_complete = True + await streaming._flush_pending_messages_until_setup() + + assert backend_ws.send.call_count == 1 + + +@pytest.mark.asyncio +async def test_deferred_setup_sends_session_update_before_buffered_audio(monkeypatch): + monkeypatch.setattr(litellm, "gemini_live_defer_setup", True, raising=False) + from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig + + client_ws = MagicMock() + audio_msg = json.dumps({"type": "input_audio_buffer.append", "audio": "AA=="}) + session_update = json.dumps( + {"type": "session.update", "session": {"modalities": ["audio"]}} + ) + client_ws.receive_text = AsyncMock( + side_effect=[audio_msg, session_update, ConnectionClosed(None, None)] + ) + backend_ws = MagicMock() + backend_ws.send = AsyncMock() + logging_obj = MagicMock() + config = GeminiRealtimeConfig() + + streaming = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=config, + model="gemini-live-2.5-flash-native-audio", + ) + + await streaming.client_ack_messages() + + assert backend_ws.send.await_count == 1 + sent_payload = json.loads(backend_ws.send.await_args_list[0].args[0]) + assert "setup" in sent_payload + assert "realtimeInput" not in sent_payload + assert streaming._pending_messages_until_setup == [audio_msg] + + +@pytest.mark.asyncio +async def test_deferred_setup_flush_buffers_audio_received_during_flush(): + import asyncio + + client_ws = MagicMock() + client_ws.send_text = AsyncMock() + new_audio_msg = json.dumps( + {"type": "input_audio_buffer.append", "audio": "new-audio"} + ) + client_ws.receive_text = AsyncMock( + side_effect=[new_audio_msg, ConnectionClosed(None, None)] + ) + backend_ws = MagicMock() + logging_obj = MagicMock() + + provider_config = MagicMock() + provider_config.requires_session_configuration = MagicMock(return_value=False) + provider_config.transform_realtime_response = MagicMock( + return_value={ + "response": { + "type": "session.created", + "event_id": "event_1", + "session": {"id": "sess_1", "modalities": ["audio"]}, + }, + "current_output_item_id": None, + "current_response_id": None, + "current_delta_chunks": [], + "current_conversation_id": None, + "current_item_chunks": [], + "current_delta_type": None, + "session_configuration_request": None, + } + ) + + streaming = RealTimeStreaming( + websocket=client_ws, + backend_ws=backend_ws, + logging_obj=logging_obj, + provider_config=provider_config, + model="gemini-live-2.5-flash-native-audio", + ) + old_audio_msg = json.dumps( + {"type": "input_audio_buffer.append", "audio": "old-audio"} + ) + streaming._pending_messages_until_setup = [old_audio_msg] + streaming._pending_messages_byte_total = len(old_audio_msg.encode("utf-8")) + + first_flush_started = asyncio.Event() + release_flush = asyncio.Event() + sent_messages = [] + + async def send_to_backend(message): + sent_messages.append(message) + if message == old_audio_msg: + first_flush_started.set() + await release_flush.wait() + return True + + streaming._send_to_backend = send_to_backend # type: ignore[method-assign] + setup_task = asyncio.create_task( + streaming._handle_provider_config_message(json.dumps({"setupComplete": {}})) + ) + + await asyncio.wait_for(first_flush_started.wait(), timeout=1) + await streaming.client_ack_messages() + + assert sent_messages == [old_audio_msg] + assert streaming._pending_messages_until_setup == [new_audio_msg] + + release_flush.set() + await asyncio.wait_for(setup_task, timeout=1) + + assert sent_messages == [old_audio_msg, new_audio_msg] + assert streaming._pending_messages_until_setup == [] + + +@pytest.mark.asyncio +async def test_deferred_setup_flush_retains_unsent_messages_after_send_failure(): + client_ws = MagicMock() + backend_ws = MagicMock() + logging_obj = MagicMock() + streaming = RealTimeStreaming(client_ws, backend_ws, logging_obj) + buffered_messages = [ + json.dumps({"type": "input_audio_buffer.append", "audio": "AA=="}), + json.dumps({"type": "input_audio_buffer.commit"}), + ] + streaming._pending_messages_until_setup = list(buffered_messages) + streaming._pending_messages_byte_total = sum( + len(message.encode("utf-8")) for message in buffered_messages + ) + streaming._send_to_backend = AsyncMock( # type: ignore[method-assign] + side_effect=Exception("transient") + ) + + await streaming._flush_pending_messages_until_setup() + + assert streaming._pending_messages_until_setup == buffered_messages + assert streaming._pending_messages_byte_total == sum( + len(message.encode("utf-8")) for message in buffered_messages + ) + + streaming._send_to_backend = AsyncMock(return_value=True) # type: ignore[method-assign] + + await streaming._flush_pending_messages_until_setup() + + assert streaming._pending_messages_until_setup == [] + assert streaming._pending_messages_byte_total == 0 + assert streaming._send_to_backend.await_count == 2 + + +@pytest.mark.asyncio +async def test_deferred_setup_flushes_audio_on_backend_session_created(monkeypatch): + """Buffered audio is released when Gemini setupComplete becomes session.created.""" + monkeypatch.setattr(litellm, "gemini_live_defer_setup", True, raising=False) + from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig + + client_ws = MagicMock() + client_ws.send_text = AsyncMock() + backend_ws = MagicMock() + backend_ws.send = AsyncMock() + backend_ws.recv = AsyncMock( + side_effect=[ + json.dumps({"setupComplete": {}}).encode(), + ConnectionClosed(None, None), + ] + ) + logging_obj = MagicMock() + logging_obj.litellm_trace_id = "trace_defer" + logging_obj.async_success_handler = AsyncMock() + logging_obj.success_handler = MagicMock() + config = GeminiRealtimeConfig() + + streaming = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=config, + model="gemini-live-2.5-flash-native-audio", + ) + streaming._pending_messages_until_setup.append( + json.dumps({"type": "input_audio_buffer.append", "audio": "AA=="}) + ) + + await streaming.backend_to_client_send_messages() + + assert streaming._backend_setup_complete is True + assert streaming._pending_messages_until_setup == [] + assert backend_ws.send.call_count == 1 + + +@pytest.mark.asyncio +async def test_deferred_setup_caps_non_audio_buffered_messages(monkeypatch): + """A client that withholds session.update cannot grow the pre-setup buffer + without bound by streaming non-audio frames after the first audio frame.""" + monkeypatch.setattr(litellm, "gemini_live_defer_setup", True, raising=False) + from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig + + cap = RealTimeStreaming._MAX_BUFFERED_MESSAGES + audio_msg = json.dumps({"type": "input_audio_buffer.append", "audio": "AA=="}) + flood_msg = json.dumps({"type": "foo", "data": "x" * 1024}) + + client_ws = MagicMock() + client_ws.receive_text = AsyncMock( + side_effect=[audio_msg] + + [flood_msg] * (cap + 50) + + [ConnectionClosed(None, None)] + ) + backend_ws = MagicMock() + backend_ws.send = AsyncMock() + logging_obj = MagicMock() + + streaming = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=GeminiRealtimeConfig(), + model="gemini-live-2.5-flash-native-audio", + ) + assert streaming._backend_setup_complete is False + + await streaming.client_ack_messages() + + backend_ws.send.assert_not_called() + assert len(streaming._pending_messages_until_setup) == cap + assert ( + streaming._pending_messages_byte_total <= RealTimeStreaming._MAX_BUFFERED_BYTES + ) + + +@pytest.mark.asyncio +async def test_deferred_setup_caps_non_audio_buffered_bytes(monkeypatch): + """Non-audio frames appended after the first audio frame honor the byte budget.""" + monkeypatch.setattr(litellm, "gemini_live_defer_setup", True, raising=False) + from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig + + audio_msg = json.dumps({"type": "input_audio_buffer.append", "audio": "AA=="}) + big_non_audio = json.dumps( + {"type": "foo", "data": "x" * (RealTimeStreaming._MAX_BUFFERED_BYTES + 1)} + ) + + client_ws = MagicMock() + client_ws.receive_text = AsyncMock( + side_effect=[audio_msg, big_non_audio, ConnectionClosed(None, None)] + ) + backend_ws = MagicMock() + backend_ws.send = AsyncMock() + logging_obj = MagicMock() + + streaming = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=GeminiRealtimeConfig(), + model="gemini-live-2.5-flash-native-audio", + ) + + await streaming.client_ack_messages() + + assert streaming._pending_messages_until_setup == [audio_msg] + assert ( + streaming._pending_messages_byte_total <= RealTimeStreaming._MAX_BUFFERED_BYTES + ) diff --git a/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py b/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py index cc0adc4277c..53f0766dbcb 100644 --- a/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py +++ b/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py @@ -235,12 +235,73 @@ def test_gemini_realtime_transformation_audio_delta(): contains_audio_delta = False for response in responses: - if response["type"] == OpenAIRealtimeEventTypes.RESPONSE_AUDIO_DELTA.value: + if ( + response["type"] + == OpenAIRealtimeEventTypes.RESPONSE_OUTPUT_AUDIO_DELTA.value + ): contains_audio_delta = True break assert contains_audio_delta, "Expected audio delta event" +def test_gemini_output_audio_transcript_delta_uses_active_response_ids(): + config = GeminiRealtimeConfig() + + session_configuration_request = { + "setup": { + "model": "gemini-1.5-flash", + "generationConfig": {"responseModalities": ["AUDIO"]}, + } + } + session_configuration_request_str = json.dumps(session_configuration_request) + event = { + "serverContent": { + "outputTranscription": {"text": "Hello from Gemini."}, + "modelTurn": { + "parts": [ + {"inlineData": {"mimeType": "audio/pcm", "data": "my-audio-data"}} + ] + }, + } + } + + result = config.transform_realtime_response( + json.dumps(event), + "gemini-1.5-flash", + MagicMock(), + realtime_response_transform_input={ + "session_configuration_request": session_configuration_request_str, + "current_output_item_id": None, + "current_response_id": None, + "current_conversation_id": None, + "current_delta_chunks": [], + "current_item_chunks": [], + "current_delta_type": None, + }, + ) + + responses = result["response"] + response_created = next( + response for response in responses if response["type"] == "response.created" + ) + transcript_delta = next( + response + for response in responses + if response["type"] == "response.output_audio_transcript.delta" + ) + audio_delta = next( + response + for response in responses + if response["type"] == "response.output_audio.delta" + ) + + assert transcript_delta["response_id"] == response_created["response"]["id"] + assert transcript_delta["response_id"] == audio_delta["response_id"] + assert transcript_delta["item_id"] == audio_delta["item_id"] + assert result["current_response_id"] == transcript_delta["response_id"] + assert result["current_output_item_id"] == transcript_delta["item_id"] + + def test_gemini_realtime_transformation_generation_complete(): from litellm.types.llms.openai import OpenAIRealtimeEventTypes @@ -278,7 +339,10 @@ def test_gemini_realtime_transformation_generation_complete(): contains_audio_done_event = False for response in responses: - if response["type"] == OpenAIRealtimeEventTypes.RESPONSE_AUDIO_DONE.value: + if ( + response["type"] + == OpenAIRealtimeEventTypes.RESPONSE_OUTPUT_AUDIO_DONE.value + ): contains_audio_done_event = True break assert contains_audio_done_event, "Expected audio done event" @@ -735,7 +799,14 @@ def test_gemini_tool_call_emits_response_created_preamble(): ) responses = result["response"] - # Should have: response.created, output_item.added, function_call_arguments.delta, function_call_arguments.done, output_item.done, conversation.item.created, response.done + # Expected sequence: + # 0: response.created + # 1: response.output_item.added (item status=in_progress) + # 2: conversation.item.added (registers call_id in Pipecat's _pending_function_calls) + # 3: response.function_call_arguments.delta + # 4: response.function_call_arguments.done + # 5: response.output_item.done + # 6: response.done assert len(responses) >= 7 assert responses[0]["type"] == "response.created" assert "response" in responses[0] @@ -749,14 +820,14 @@ def test_gemini_tool_call_emits_response_created_preamble(): assert responses[1]["type"] == "response.output_item.added" assert responses[1]["item"]["type"] == "function_call" assert responses[1]["item"]["status"] == "in_progress" - assert responses[2]["type"] == "response.function_call_arguments.delta" - assert responses[2]["call_id"] == "call_123" - assert responses[2]["delta"] == responses[3]["arguments"] - assert responses[3]["type"] == "response.function_call_arguments.done" - assert responses[4]["type"] == "response.output_item.done" - assert responses[4]["item"]["type"] == "function_call" - assert responses[4]["item"]["status"] == "completed" - assert responses[5]["type"] == "conversation.item.created" + assert responses[2]["type"] == "conversation.item.added" + assert responses[2]["item"]["type"] == "function_call" + assert responses[2]["item"]["call_id"] == "call_123" + assert responses[3]["type"] == "response.function_call_arguments.delta" + assert responses[3]["call_id"] == "call_123" + assert responses[3]["delta"] == responses[4]["arguments"] + assert responses[4]["type"] == "response.function_call_arguments.done" + assert responses[5]["type"] == "response.output_item.done" assert responses[5]["item"]["type"] == "function_call" assert responses[5]["item"]["status"] == "completed" assert responses[6]["type"] == "response.done" @@ -930,6 +1001,12 @@ def test_gemini_tool_call_response_done_includes_usage_from_sibling_metadata(): "promptTokenCount": 17, "responseTokenCount": 4, "totalTokenCount": 21, + "promptTokensDetails": [ + {"modality": "TEXT", "tokenCount": 17}, + ], + "responseTokensDetails": [ + {"modality": "TEXT", "tokenCount": 4}, + ], }, } ), @@ -953,6 +1030,8 @@ def test_gemini_tool_call_response_done_includes_usage_from_sibling_metadata(): assert usage["input_tokens"] == 17 assert usage["output_tokens"] == 4 assert usage["total_tokens"] == 21 + assert usage["input_token_details"]["text_tokens"] == 17 + assert usage["output_token_details"]["text_tokens"] == 4 def test_gemini_tool_call_response_done_falls_back_to_empty_usage(): @@ -1120,6 +1199,90 @@ def test_gemini_subsequent_session_update_forwards_tools_merged_with_original_se assert follow_up["inputAudioTranscription"] == {} +def test_gemini_realtime_pipecat_ga_session_voice_and_tools(): + """Pipecat OpenAIRealtimeSessionProperties: output_modalities, nested tools, + and audio.output.voice (e.g. Kore) must map into Gemini setup.""" + config = GeminiRealtimeConfig() + + session_update = { + "type": "session.update", + "session": { + "output_modalities": ["audio"], + "instructions": "Follow system instructions.", + "tools": [ + { + "type": "function", + "function": { + "name": "terminate_call", + "description": "End the call.", + "parameters": {"type": "object", "properties": {}}, + }, + } + ], + "audio": { + "input": { + "format": {"type": "audio/pcm", "rate": 24000}, + "turn_detection": {"type": "server_vad"}, + }, + "output": { + "format": {"type": "audio/pcm", "rate": 24000}, + "voice": "Kore", + }, + }, + "temperature": 0, + }, + } + + messages = config.transform_realtime_request( + json.dumps(session_update), + "gemini-2.5-flash-native-audio", + session_configuration_request=None, + ) + + assert len(messages) == 1 + setup = json.loads(messages[0])["setup"] + assert setup["generationConfig"]["responseModalities"] == ["AUDIO"] + # Native-audio Live rejects speechConfig on setup (see _finalize_gemini_live_setup). + assert "speechConfig" not in setup.get("generationConfig", {}) + assert setup["tools"][0]["function_declarations"][0]["name"] == "terminate_call" + assert ( + setup["realtimeInputConfig"]["automaticActivityDetection"]["disabled"] is False + ) + + +def test_gemini_realtime_pipecat_semantic_vad_omits_realtime_input_config(): + """Pipecat SemanticTurnDetection (semantic_vad) must not map to disabled VAD.""" + config = GeminiRealtimeConfig() + session_update = { + "type": "session.update", + "session": { + "output_modalities": ["audio"], + "instructions": "test", + "audio": { + "input": {"turn_detection": {"type": "semantic_vad"}}, + }, + "tools": [ + { + "type": "function", + "function": { + "name": "terminate_call", + "description": "End call.", + "parameters": {"type": "object", "properties": {}}, + }, + } + ], + }, + } + messages = config.transform_realtime_request( + json.dumps(session_update), + "gemini-live-2.5-flash-native-audio", + session_configuration_request=None, + ) + setup = json.loads(messages[0])["setup"] + assert "realtimeInputConfig" not in setup + assert setup["tools"][0]["function_declarations"][0]["name"] == "terminate_call" + + def test_gemini_subsequent_session_update_with_turn_detection_only_preserves_original_tools(): """A subsequent session.update carrying only turn_detection (the guardrail-injected disable) must keep the original tools/generationConfig.""" @@ -1407,6 +1570,12 @@ def test_gemini_standalone_usage_metadata_is_attributed_to_next_response_done(): "promptTokenCount": 5, "responseTokenCount": 11, "totalTokenCount": 16, + "promptTokensDetails": [ + {"modality": "TEXT", "tokenCount": 5}, + ], + "responseTokensDetails": [ + {"modality": "TEXT", "tokenCount": 11}, + ], } } ), @@ -1447,6 +1616,8 @@ def test_gemini_standalone_usage_metadata_is_attributed_to_next_response_done(): assert usage["input_tokens"] == 5 assert usage["output_tokens"] == 11 assert usage["total_tokens"] == 16 + assert usage["input_token_details"]["text_tokens"] == 5 + assert usage["output_token_details"]["text_tokens"] == 11 assert config._pending_usage_metadata is None diff --git a/tests/test_litellm/llms/vertex_ai/realtime/test_vertex_ai_realtime_transformation.py b/tests/test_litellm/llms/vertex_ai/realtime/test_vertex_ai_realtime_transformation.py index 0ad614099de..1ebd704be34 100644 --- a/tests/test_litellm/llms/vertex_ai/realtime/test_vertex_ai_realtime_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/realtime/test_vertex_ai_realtime_transformation.py @@ -278,8 +278,8 @@ async def test_vertex_realtime_text_in_text_out(): assert session_created_msgs, "Expected session.created to be sent to client" # At least one text delta should have been forwarded - text_delta_msgs = [m for m in sent_to_client if '"response.text.delta"' in m] - assert text_delta_msgs, "Expected response.text.delta to be sent to client" + text_delta_msgs = [m for m in sent_to_client if '"response.output_text.delta"' in m] + assert text_delta_msgs, "Expected response.output_text.delta to be sent to client" # Verify the delta contains the model's text delta_obj = json.loads(text_delta_msgs[0]) From cb041966bf3502c56221ea2605e0b0373dce4cac Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Thu, 4 Jun 2026 23:37:20 +0530 Subject: [PATCH 30/92] Litellm oss staging 040626 (#29671) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix(azure): apply api_version fallback chain to image edit URL `AzureImageEditConfig.get_complete_url` only read `api_version` from `litellm_params`. When callers configured it via `litellm.api_version` or `AZURE_API_VERSION`, the constructed URL had no `?api-version=` and Azure responded `404 Resource not found`. Apply the same fallback chain the Azure chat path already uses in `common_utils.py`: litellm_params > litellm.api_version > AZURE_API_VERSION env > litellm.AZURE_DEFAULT_API_VERSION Adds 5 unit tests pinning each layer of the chain plus a regression guard for `api_base` that already carries `?api-version=`. * feat(mcp): core sampling and elicitation flow with security hardening - Add sampling_handler.py: full MCP sampling/createMessage flow with model selection (hint-based + priority-based), auth enforcement, budget checks, route restriction gates, and tag policy pre-auth - Add elicitation_handler.py: MCP elicitation/create relay with downstream client capability detection - Wire sampling/elicitation callbacks in mcp_server_manager.py gated behind allow_sampling/allow_elicitation config flags - Add allow_sampling/allow_elicitation fields to MCPServer type - Fix session lock deadlock: skip lock for JSON-RPC response POSTs (elicitation/sampling replies) with truncated-body heuristic - Extend client.py with sampling_callback and elicitation_callback - Security: RouteChecks gate, tag-budget bypass fix, x-forwarded-for spoofing fix, Latin-1 header encoding guard - Add 4 new test modules (model access, priority selection, request builder, tool conversion) + update existing MCP tests * fix(security): run pre-call guardrails before MCP sampling acompletion Without this, an upstream MCP server with allow_sampling enabled could send prompts that bypass every guardrail (content filtering, PII redaction, prompt-injection detection) configured on /chat/completions. - Call proxy_logging_obj.pre_call_hook(call_type='acompletion') before llm_router.acompletion so guardrails fire for sampling sub-calls - Add HTTPException to the re-raise list so guardrail rejections propagate correctly instead of being swallowed as generic errors * feat(bedrock_mantle): add Responses API support (/openai/v1/responses) (#29490) * feat(bedrock_mantle): add Responses API transformation config * test(bedrock_mantle): cover trailing-slash api_base normalization * feat(bedrock_mantle): export BedrockMantleResponsesAPIConfig * feat(bedrock_mantle): register gpt-5.x Responses config (gpt-oss unchanged) * feat(bedrock_mantle): add gpt-5.5/gpt-5.4 Responses price-map entries * refactor(bedrock_mantle): exclude gpt-oss instead of allow-listing gpt-5 for Responses routing Frontier OpenAI models on Bedrock Mantle are Responses-only on /openai/v1/responses; gpt-oss is the legacy family that also speaks chat-completions. Gate by excluding gpt-oss (which keeps its chat-completions emulation) and defaulting everything else to the native Responses config, so future frontier models (gpt-6, etc.) route correctly without a code change. Verified against the live us-east-2 Mantle endpoint: gpt-oss 400s on /openai/v1/responses while gpt-5.5 400s on both standard paths. * test(bedrock_mantle): cover supports_native_websocket opt-out Closes the one uncovered line flagged by codecov on the Responses config. The assertion documents that Mantle Responses has no realtime/websocket transport, so realtime routing must not attempt a socket it cannot serve. * fix(bedrock_mantle): route file_search through emulation instead of forwarding to Mantle BedrockMantleResponsesAPIConfig inherited supports_native_file_search() -> True from OpenAIResponsesAPIConfig but never overrode it. Mantle has no OpenAI vector stores, so a forwarded file_search tool is rejected with a 400 (verified upstream: Tool type 'file_search' is not supported). Opting out, like the existing supports_native_websocket override, routes the tool through LiteLLM's file_search emulation instead. * fix(bedrock_mantle): only route openai.gpt frontier models to Responses The previous gate excluded gpt-oss and routed every other model to the native Responses config. But on Mantle only the OpenAI gpt frontier models (gpt-5.x) are served on /openai/v1/responses; gpt-oss and the non-OpenAI families (nvidia, mistral, google, zai, ...) are chat-completions only and 400 on that path. Allow-list the openai.gpt- family (excluding gpt-oss) instead, so chat-only models fall through to the chat-completions emulation. Verified against the live us-east-2 endpoint: nvidia.nemotron-nano-9b-v2 returns 400 on /openai/v1/responses and 200 on /v1/chat/completions. * feat(custom_llm): allow streaming/astreaming to yield ModelResponseStream (#27580) * fix(custom_llm): allow streaming/astreaming to yield ModelResponseStream directly * fix(streaming): enhance ModelResponseStream handling for custom LLM providers * fix(streaming): strip finish_reason from content chunks and ensure tool_calls are preserved * fix(streaming): add type ignore for finish_reason assignment in CustomStreamWrapper * fix(proxy): strip stack trace from HTTP 503 responses (CWE-209) (#28330) * fix(proxy/cwe-209): strip Python traceback from HTTP 503 error responses The /cache/ping endpoint included a full Python traceback in its 503 error response body (inside the ProxyException message), leaking internal file paths, line numbers, and call stacks to any caller. Two MCP route handlers in proxy_server.py similarly interpolated str(e) into "Internal server error" detail strings. Fix: log the traceback server-side via verbose_proxy_logger.exception() and omit it from the ProxyException payload / HTTPException detail returned to clients. Tests updated to assert no "traceback" keyword or frame paths appear in the 503 body, with a new dedicated regression test. CWE-209: Generation of Error Message Containing Sensitive Information. Co-Authored-By: Claude Sonnet 4.6 * fix(proxy/cwe-209): apply Greptile P2 fixes and add MCP exception-path tests Greptile 4/5 review identified two remaining gaps and Codecov reported 0% coverage on the two MCP handler exception branches: 1. caching_routes.py — str(e) in "Service Unhealthy ({str(e)})" could still leak Redis hostnames/IPs; replaced with static "Service Unhealthy". HTTPException is now re-raised before the generic handler so the "cache not initialized" 503 still reaches callers with its detail. Removed the redundant str(e) arg from verbose_proxy_logger.exception() (exception() already appends the traceback automatically). 2. tests — two new unit tests cover the exception paths in dynamic_mcp_route and toolset_mcp_route that were previously at 0%: - test_dynamic_mcp_route_unexpected_exception_returns_500_without_traceback - test_toolset_mcp_route_unexpected_exception_returns_500_without_traceback All 25 tests pass (9 caching + 16 MCP). CWE-209: Generation of Error Message Containing Sensitive Information. Co-Authored-By: Claude Sonnet 4.6 * test(caching_routes): restore precise assertion in test_cache_ping_no_cache_initialized The assertion was weakened to `"Cache not initialized" in str(data)`, which matches the raw string of the entire response dict and would pass even if the error moved to an unexpected field or changed structure. Restore a targeted check on the parsed response: assert the exact string in the correct field `data["detail"]`, matching FastAPI's HTTPException serialisation format {"detail": ""}. Co-Authored-By: Claude Sonnet 4.6 * test(caching_routes): restore precise assertion and add CWE-209 no-cache path test The assertion in test_cache_ping_no_cache_initialized was weakened to `"Cache not initialized" in str(data)`, which matched against the raw string representation of the entire response dict. This would pass silently even if the error message moved to an unexpected field or the structure changed. Restore a targeted assertion on the parsed field: assert data["detail"] == "Cache not initialized. litellm.cache is None" matching FastAPI's HTTPException serialisation format exactly. Add test_cache_ping_no_cache_does_not_expose_internals to show the code path is still working correctly after the CWE-209 fix: verifies that the HTTPException is re-raised as-is (no traceback, no source paths), and asserts the complete response structure is exactly {"detail": "Cache not initialized. litellm.cache is None"}. Co-Authored-By: Claude Sonnet 4.6 * fix(caching_routes): restore ProxyException envelope for null-cache 503 The except HTTPException: raise guard (added in the CWE-209 fix) caused the null-cache HTTPException to escape as FastAPI's {"detail": "..."} shape instead of the {"error": {...}} ProxyException envelope that callers expect. Move the null-cache guard before the try block and raise ProxyException directly so the response structure is consistent with all other /cache/ping 503s, and the except HTTPException: raise guard is only reachable by unexpected downstream HTTPExceptions. Update the two no-cache tests to assert the correct ProxyException envelope. Co-Authored-By: Claude Sonnet 4.6 --------- Co-authored-by: Claude Sonnet 4.6 * Update utils.py (#26609) * feat(pricing): add Snowflake Cortex REST API model pricing (#26612) * feat(pricing): add Snowflake Cortex REST API model pricing ## Summary Adds pricing and context window information for 20+ Snowflake Cortex REST API models to `model_prices_and_context_window.json`. ## What's included - **7 Claude models** (sonnet-4-5, sonnet-4-6, 4-sonnet, 4-opus, haiku-4-5, 3-7-sonnet, 3-5-sonnet) — with prompt caching rates - **4 OpenAI models** (gpt-4.1, gpt-5, gpt-5-mini, gpt-5-nano) — with prompt caching rates - **5 Llama models** (3.1-8b, 3.1-70b, 3.1-405b, 3.3-70b, 4-maverick) - **1 DeepSeek model** (deepseek-r1) - **1 Mistral model** (mistral-large2) - **1 Snowflake model** (snowflake-llama-3.3-70b) - **2 Embedding models** (arctic-embed-l-v2.0, arctic-embed-m-v2.0) Each entry includes `input_cost_per_token`, `output_cost_per_token`, `cache_read_input_token_cost` (where applicable), `max_input_tokens`, `max_output_tokens`, and capability flags (`supports_function_calling`, `supports_vision`, `supports_prompt_caching`, `supports_reasoning`). ## Pricing source All prices are in USD per token, sourced from the official [Snowflake Service Consumption Table](https://www.snowflake.com/legal-files/CreditConsumptionTable.pdf) — Tables 6(b) (REST API with Prompt Caching) and 6(c) (REST API). ## Context The existing `snowflake/` provider has zero model entries in the pricing JSON, which means LiteLLM cannot track costs for Snowflake Cortex calls. This PR fills that gap. ## Related - Existing provider: `litellm/llms/snowflake/` - Cortex REST API docs: https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-rest-api * Update model_prices_and_context_window.json Fix the JSON parsing error * Update model_prices_and_context_window.json Removed the duplicate entry * fix(utils): copy extra_body before adding unknown params to prevent model config mutation (#29620) Fixes #29615. In add_provider_specific_params_to_optional_params, the line: extra_body = passed_params.pop("extra_body", None) or {} returns the original dict reference when extra_body is non-empty (truthy). Subsequent writes like extra_body[k] = passed_params[k] then mutate the shared model config object held by the router, poisoning /model/info and all subsequent requests for that deployment. The or {} short-circuit creates a new dict only when extra_body is falsy (None or {}), which is why the bug does not reproduce with extra_body: {}. Fix: wrap in dict() so we always work on a fresh shallow copy. * fix(vertex_ai): Bake tool_choice into Gemini CachedContent body to prevent silent drop (#29097) * fix(vertex_ai): bake tool_choice into Gemini CachedContent body to prevent silent drop * address greptile feedback on tool_choice cache test * adds test that uses ToolConfig(functionCallingConfig=FunctionCallingConfig(mode=ANY)) instead of a dict literal, mirroring what map_tool_choice_values actually produce * fix(gemini/veo): move image from parameters into instances[0] (#29501) * fix(gemini/veo): move image from parameters into instances[0] Veo's predictLongRunning schema puts image (and prompt) on the instances element; parameters is for aspectRatio/durationSeconds/etc. The Gemini path was leaving image in params_copy, so it ended up nested under parameters and the API silently ignored it. The Vertex path already builds the instance dict explicitly, so this just aligns the Gemini path with it. Fixes #29498 * address greptile: unconditional pop + BytesIO test - Pop `image` from params_copy unconditionally so it never reaches GeminiVideoGenerationParameters even when None, removing implicit reliance on Pydantic's extra-field-ignore. - Add test_transform_video_create_request_image_filelike_goes_to_instance covering the BytesIO path (_convert_image_to_gemini_format) — round-trips the base64 to confirm encoding. - Add test_transform_video_create_request_image_none_is_dropped covering the new None branch. * fix(huggingface): handle special token text in embedding usage (#29660) * fix(guardrails): recompile ToolPermissionGuardrail rules on update_in_memory_litellm_params (#29655) * fix(guardrails): recompile ToolPermissionGuardrail rules on update_in_memory_litellm_params ToolPermissionGuardrail builds self.rules and the compiled target/pattern maps only in __init__. The base update_in_memory_litellm_params re-sets raw attributes via setattr but never rebuilds those maps, so a guardrail updated in place (PUT /guardrails, or the immediate in-memory sync) keeps enforcing the construction-time rules until it is reinitialized (PATCH path, periodic DB poll, or restart). Extract the compile step into _load_rules and override update_in_memory_litellm_params to rebuild from it (dict- and model-safe), re-normalizing default_action / on_disallowed_action. Mirrors the existing PresidioGuardrail override of the same method. Adds regression tests. Fixes #29592. * fix(guardrails): handle dict params in ToolPermissionGuardrail in-memory update Delegate to super() only for LitellmParams input (the base setattr loop is model-only); apply the raw-dict case inline. Fixes the mypy arg-type error and makes the recompile work when the proxy passes the raw DB dict. * fix(guardrails): preserve tool-permission rules on a partial in-memory update A partial update (e.g. a LitellmParams whose rules field is None) ran through the generic setattr, which set self.rules to None, and the recompile was skipped, leaving the guardrail with no rules. Snapshot the previous rules and restore them when the update carries no rules; an explicit empty list still clears them. Adds a regression test for the rules-absent case. Addresses the Greptile review note on #29655. * fix(bedrock): stop base_model label from stripping tools/tool_choice (#29621) * fix(bedrock): stop base_model label from stripping tools/tool_choice A Router/proxy Bedrock deployment whose model_info.base_model is a friendly label (e.g. claude-haiku-4-5) silently lost tools/tool_choice: the outgoing Converse request was built without toolConfig, so the model behaved as if no tools were provided. Worked in v1.84.0, regressed in v1.85.0, and with drop_params=true it failed silently. Two changes compound into the bug. completion() passed model_info.base_model as the model argument to get_optional_params, so the real Bedrock model id never reached supported-param resolution; and get_supported_openai_params resolved the provider config's params from base_model or model, letting the label fully replace the real model. For Bedrock the label resolves to no tool support, so tools/tool_choice were dropped before transformation. completion() now keeps model as the real deployment model and threads the resolved base_model (kwarg or model_info) through separately, and get_supported_openai_params treats base_model as additive: it returns the union of the params supported by model and by base_model. A hint can only add capabilities, never strip ones the real model already exposes, which also preserves the original base_model behavior from #27717 and Azure's base_model driven model-type detection. Fixes #29618 * test(main): make base_model param test robust to new parametrize cases Restore an explicit per-case expected_model_param literal instead of hardcoding the gemini id, so a future case with a different model can't produce a misleading assertion failure. * fix(fireworks_ai): pass response_format json_schema through unchanged (#29606) FireworksAIConfig.map_openai_params was rewriting the OpenAI strict `{type: json_schema, json_schema: {name, strict, schema}}` shape into `{type: json_object, schema: ...}` before sending to Fireworks, dropping `strict` and `name` and changing the `type`. Per Fireworks' docs json_object means "force any valid JSON output (no specific schema)", so the schema constraint was effectively dropped and grammar-guided decoding never ran; model output silently violated the schema. The rewrite landed in #7085 (Dec 2024) when Fireworks did not yet accept native json_schema. Fireworks accepts the OpenAI strict shape natively now, so the rewrite has become a regression. Removes the rewrite. Passes response_format through unchanged. Updates the existing test_map_response_format to assert pass-through. Adds focused regression tests in tests/test_litellm/ covering preservation of type, strict, name, and schema body, plus that json_object alone still works. * fix(types): import Required from typing_extensions in gemini types * style: reformat sampling_handler.py for py312 black compat * refactor(mcp-sampling): extract helpers to fix PLR0915 too-many-statements in handle_sampling_create_message * fix(proxy-server): add explicit ProxyLogging type annotation to proxy_logging_obj to fix mypy inference * fix(mcp-sampling): suppress mypy assignment error on ImportError fallback for proxy_logging_obj * fix(test): use .value when comparing LlmProviders enum against string in test_default_api_base * fix(test): iterate LlmProviders enum in test_default_api_base to avoid str pollution from custom provider registration litellm.provider_list is a mutable global initialized to list(LlmProviders) but custom_llm_setup() appends plain provider strings to it. When a test_custom_llm.py test runs first in the same xdist worker, provider_list contains a str and calling .value on it raises AttributeError. Iterate the immutable LlmProviders enum instead, which is deterministic and what the check intends. * fix(mcp): depth-aware JSON-RPC response detection and neutral speed-priority fallback Replace the flat substring check in the truncated-body routing path with a top-level-key scan so a JSON-RPC response whose result payload nests a "method" field is still detected as a response and skips the session lock, removing a deadlock against the in-flight tool call awaiting it. Drop the inverse max_output_tokens speed proxy when no model exposes output_tokens_per_second; context-window size does not track latency, so a neutral score avoids biasing speedPriority toward the smallest-context model. * fix(guardrails): make ToolPermission rule reload atomic on invalid regex _load_rules appended each rule to self.rules before compiling its regex, so an invalid pattern raised mid-loop after the bad rule was already live but without a _compiled_rule_targets entry. _matches_regex reads a missing compiled target as a None pattern and returns True, turning the bad rule into a match-all that silently applies its decision to every tool. Via update_in_memory_litellm_params (PUT /guardrails) this corrupted the live guardrail. Build the parsed rules and compiled maps into locals and swap them in only after every regex compiles, and restore the previous ruleset if a live update is rejected, so an invalid regex now fails the update without leaving the guardrail enforcing a broken policy. * test(mcp): cover sampling conversion, model resolution, and elicitation relay paths The MCP sampling and elicitation handlers shipped with partial test coverage, leaving the response-to-MCP conversion, the model resolution fallback chain, completion-kwargs assembly, guardrail routing, and the entire elicitation relay untested. That pulled the PR's diff (patch) coverage below the codecov threshold even though overall project coverage rose. Add focused unit tests for _convert_openai_response_to_mcp_result, _convert_mcp_tools_to_openai, _convert_mcp_tool_choice_to_openai, image and audio content conversion, the hint-matching and fallback branches of _resolve_model_from_preferences, _build_completion_kwargs, the router and guardrail-rejection paths of _run_guardrails_and_call_llm, the handle_sampling_create_message success and error-propagation flows, the marker-hoisting fallback for tool content on unexpected roles, and the elicitation form/url/generic relay together with its decline paths --------- Co-authored-by: shin-berri Co-authored-by: yuneng-jiang Co-authored-by: lengkejun Co-authored-by: Yug Co-authored-by: Kent <72616338+kingdoooo@users.noreply.github.com> Co-authored-by: tanmay958 <53569547+tanmay958@users.noreply.github.com> Co-authored-by: DrishnaTrivedi <142084770+DrishnaTrivedi@users.noreply.github.com> Co-authored-by: Claude Sonnet 4.6 Co-authored-by: Navnit Shukla Co-authored-by: PRABHU KIRAN VANDRANKI <72809214+VANDRANKI@users.noreply.github.com> Co-authored-by: Adrian Lopez <109683617+adriangomez24@users.noreply.github.com> Co-authored-by: hcl Co-authored-by: JooHo Lee <96564470+BWAAEEEK@users.noreply.github.com> Co-authored-by: Dinesh Girbide <85330597+Dinesh-Girbide@users.noreply.github.com> Co-authored-by: cloudwiz <22098246+andrey-dubnik@users.noreply.github.com> Co-authored-by: Ahmad Khan Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/__init__.py | 3 + litellm/_lazy_imports_registry.py | 5 + litellm/experimental_mcp_client/client.py | 115 +- .../get_supported_openai_params.py | 18 +- .../litellm_core_utils/streaming_handler.py | 26 + .../llms/azure/image_edit/transformation.py | 11 +- .../llms/bedrock_mantle/responses/__init__.py | 0 .../responses/transformation.py | 81 ++ .../llms/fireworks_ai/chat/transformation.py | 5 - litellm/llms/gemini/videos/transformation.py | 19 +- litellm/llms/huggingface/embedding/handler.py | 2 +- litellm/llms/snowflake/utils.py | 1 + .../vertex_ai_context_caching.py | 10 +- litellm/main.py | 10 +- ...odel_prices_and_context_window_backup.json | 38 + .../mcp_server/elicitation_handler.py | 163 +++ .../mcp_server/mcp_server_manager.py | 123 +- .../mcp_server/sampling_handler.py | 1279 +++++++++++++++++ .../proxy/_experimental/mcp_server/server.py | 672 ++++++--- litellm/proxy/caching_routes.py | 27 +- .../guardrail_hooks/tool_permission.py | 159 +- litellm/proxy/proxy_server.py | 14 +- litellm/types/llms/gemini.py | 12 +- .../types/mcp_server/mcp_server_manager.py | 2 + litellm/utils.py | 12 +- model_prices_and_context_window.json | 322 ++++- .../test_fireworks_ai_translation.py | 21 +- tests/local_testing/test_custom_llm.py | 88 +- tests/local_testing/test_get_llm_provider.py | 9 +- .../test_get_supported_openai_params.py | 134 ++ .../test_streaming_handler.py | 169 +++ .../test_azure_image_edit_transformation.py | 95 ++ ...bedrock_mantle_responses_transformation.py | 283 ++++ .../test_fireworks_ai_chat_transformation.py | 56 + .../test_gemini_video_transformation.py | 82 ++ .../test_huggingface_embedding_handler.py | 17 + .../test_vertex_ai_context_caching.py | 554 ++++++- .../test_mcp_elicitation_handler.py | 211 +++ .../mcp_server/test_mcp_hook_extra_headers.py | 31 +- .../test_mcp_sampling_completion_flow.py | 254 ++++ .../test_mcp_sampling_model_access.py | 327 +++++ .../test_mcp_sampling_model_resolution.py | 91 ++ .../test_mcp_sampling_priority_selection.py | 248 ++++ .../test_mcp_sampling_request_builder.py | 147 ++ .../test_mcp_sampling_response_conversion.py | 180 +++ .../test_mcp_sampling_tool_conversion.py | 312 ++++ .../mcp_server/test_mcp_server.py | 285 +++- .../mcp_server/test_mcp_server_manager.py | 24 +- .../mcp_server/test_mcp_stale_session.py | 34 +- .../guardrail_hooks/test_tool_permission.py | 153 +- .../test_litellm/proxy/test_caching_routes.py | 101 +- .../proxy/test_dynamic_mcp_route.py | 54 + tests/test_litellm/test_main.py | 18 +- tests/test_litellm/test_utils.py | 48 + 54 files changed, 6638 insertions(+), 517 deletions(-) create mode 100644 litellm/llms/bedrock_mantle/responses/__init__.py create mode 100644 litellm/llms/bedrock_mantle/responses/transformation.py create mode 100644 litellm/proxy/_experimental/mcp_server/elicitation_handler.py create mode 100644 litellm/proxy/_experimental/mcp_server/sampling_handler.py create mode 100644 tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py create mode 100644 tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_elicitation_handler.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_completion_flow.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_access.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_resolution.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_priority_selection.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_request_builder.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_response_conversion.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_tool_conversion.py diff --git a/litellm/__init__.py b/litellm/__init__.py index 98c9dcb5ddf..e49f4a4699d 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -1740,6 +1740,9 @@ if TYPE_CHECKING: from .llms.openrouter.responses.transformation import ( OpenRouterResponsesAPIConfig as OpenRouterResponsesAPIConfig, ) + from .llms.bedrock_mantle.responses.transformation import ( + BedrockMantleResponsesAPIConfig as BedrockMantleResponsesAPIConfig, + ) from .llms.gemini.interactions.transformation import ( GoogleAIStudioInteractionsConfig as GoogleAIStudioInteractionsConfig, ) diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py index bdc3289b87c..5df8db7317d 100644 --- a/litellm/_lazy_imports_registry.py +++ b/litellm/_lazy_imports_registry.py @@ -237,6 +237,7 @@ LLM_CONFIG_NAMES = ( "PerplexityResponsesConfig", "DatabricksResponsesAPIConfig", "OpenRouterResponsesAPIConfig", + "BedrockMantleResponsesAPIConfig", "GoogleAIStudioInteractionsConfig", "OpenAIOSeriesConfig", "AnthropicSkillsConfig", @@ -958,6 +959,10 @@ _LLM_CONFIGS_IMPORT_MAP = { ".llms.openrouter.responses.transformation", "OpenRouterResponsesAPIConfig", ), + "BedrockMantleResponsesAPIConfig": ( + ".llms.bedrock_mantle.responses.transformation", + "BedrockMantleResponsesAPIConfig", + ), "GoogleAIStudioInteractionsConfig": ( ".llms.gemini.interactions.transformation", "GoogleAIStudioInteractionsConfig", diff --git a/litellm/experimental_mcp_client/client.py b/litellm/experimental_mcp_client/client.py index 7559fe142c4..0bc81ece5f0 100644 --- a/litellm/experimental_mcp_client/client.py +++ b/litellm/experimental_mcp_client/client.py @@ -4,6 +4,7 @@ LiteLLM Proxy uses this MCP Client to connnect to other MCP servers. import asyncio import base64 +import os from typing import ( Any, Awaitable, @@ -16,7 +17,6 @@ from typing import ( TypeVar, Union, ) - import httpx from mcp import ClientSession, ReadResourceResult, Resource, StdioServerParameters from mcp.client.sse import sse_client @@ -42,9 +42,8 @@ from mcp.types import ( ) from mcp.types import Tool as MCPTool from pydantic import AnyUrl - from litellm._logging import verbose_logger -from litellm.constants import MCP_CLIENT_TIMEOUT +from litellm.constants import MCP_CLIENT_TIMEOUT, MCP_NPM_CACHE_DIR from litellm.llms.custom_httpx.http_handler import get_ssl_configuration from litellm.types.llms.custom_http import VerifyTypes from litellm.types.mcp import ( @@ -67,7 +66,6 @@ TSessionResult = TypeVar("TSessionResult") class MCPSigV4Auth(httpx.Auth): """ httpx Auth class that signs each request with AWS SigV4. - This is used for MCP servers that require AWS SigV4 authentication, such as AWS Bedrock AgentCore MCP servers. httpx calls auth_flow() for every outgoing request, enabling per-request signature computation. @@ -92,10 +90,8 @@ class MCPSigV4Auth(httpx.Auth): "Missing botocore to use AWS SigV4 authentication. " "Run 'pip install boto3'." ) - self.service_name = aws_service_name or "bedrock-agentcore" self.region_name = aws_region_name or "us-east-1" - # Note: os.environ/ prefixed values are already resolved by # ProxyConfig._check_for_os_environ_vars() at config load time. # Values arrive here as plain strings. @@ -143,20 +139,17 @@ class MCPSigV4Auth(httpx.Auth): session_name = ( aws_session_name or f"litellm-mcp-{int(__import__('time').time())}" ) - sts_kwargs: dict = {"region_name": aws_region_name} if aws_access_key_id and aws_secret_access_key: sts_kwargs["aws_access_key_id"] = aws_access_key_id sts_kwargs["aws_secret_access_key"] = aws_secret_access_key if aws_session_token: sts_kwargs["aws_session_token"] = aws_session_token - sts_client = boto3.client("sts", **sts_kwargs) sts_response = sts_client.assume_role( RoleArn=aws_role_name, RoleSessionName=session_name, ) - sts_creds = sts_response["Credentials"] return Credentials( access_key=sts_creds["AccessKeyId"], @@ -178,17 +171,14 @@ class MCPSigV4Auth(httpx.Auth): data=request.content, headers=dict(request.headers), ) - # Sign the request — SigV4Auth.add_auth() adds Authorization, # X-Amz-Date, and X-Amz-Security-Token (if session token present). # Host header is derived automatically from the URL. sigv4 = SigV4Auth(self.credentials, self.service_name, self.region_name) sigv4.add_auth(aws_request) - # Copy SigV4 headers back to the httpx request for header_name, header_value in aws_request.headers.items(): request.headers[header_name] = header_value - yield request @@ -198,6 +188,8 @@ class MCPClient: SSE and HTTP transports Authentication via Bearer token, Basic Auth, or API Key Tool calling with error handling and result parsing + Sampling callbacks for upstream server LLM requests + Elicitation callbacks for upstream server user-input requests """ def __init__( @@ -211,6 +203,9 @@ class MCPClient: extra_headers: Optional[Dict[str, str]] = None, ssl_verify: Optional[VerifyTypes] = None, aws_auth: Optional[httpx.Auth] = None, + sampling_callback: Optional[Callable] = None, + elicitation_callback: Optional[Callable] = None, + logging_callback: Optional[Callable] = None, ): self.server_url: str = server_url self.transport_type: MCPTransport = transport_type @@ -222,6 +217,9 @@ class MCPClient: self.ssl_verify: Optional[VerifyTypes] = ssl_verify self._aws_auth: Optional[httpx.Auth] = aws_auth self._last_initialize_instructions: Optional[str] = None + self._sampling_callback: Optional[Callable] = sampling_callback + self._elicitation_callback: Optional[Callable] = elicitation_callback + self._logging_callback: Optional[Callable] = logging_callback # handle the basic auth value if provided if auth_value: self.update_auth_value(auth_value) @@ -231,23 +229,20 @@ class MCPClient: ) -> Tuple[Any, Optional[httpx.AsyncClient]]: """ Create the appropriate transport context based on transport type. - Returns: Tuple of (transport_context, http_client). http_client is only set for HTTP transport and needs cleanup. """ http_client: Optional[httpx.AsyncClient] = None - if self.transport_type == MCPTransport.stdio: if not self.stdio_config: raise ValueError("stdio_config is required for stdio transport") server_params = StdioServerParameters( command=self.stdio_config.get("command", ""), args=self.stdio_config.get("args", []), - env=self.stdio_config.get("env", {}), + env=self._get_safe_stdio_env(self.stdio_config.get("env")), ) return stdio_client(server_params), None - if self.transport_type == MCPTransport.sse: headers = self._get_auth_headers() httpx_client_factory = self._create_httpx_client_factory() @@ -260,14 +255,12 @@ class MCPClient: ), None, ) - # HTTP transport (default) if streamable_http_client is None: raise ImportError( "streamable_http_client is not available. " "Please install mcp with HTTP support." ) - headers = self._get_auth_headers() httpx_client_factory = self._create_httpx_client_factory() verbose_logger.debug("litellm headers for streamable_http_client: %s", headers) @@ -281,6 +274,54 @@ class MCPClient: ) return transport_ctx, http_client + def _get_safe_stdio_env( + self, provided_env: Optional[Dict[str, str]] + ) -> Optional[Dict[str, str]]: + """ + Return a safe environment for the stdio subprocess. + + If provided_env is set, we use it as-is. + If provided_env is None, we return a minimal allowlist from the parent environment + to avoid leaking sensitive LiteLLM keys (OPENAI_API_KEY, etc.) to sub-processes. + """ + if provided_env is not None: + return provided_env + + # Minimal allowlist of safe/standard environment variables + safe_keys = { + "PATH", + "HOME", + "USER", + "LOGNAME", + "TMPDIR", + "TMP", + "TEMP", + "SHELL", + "LANG", + "LC_ALL", + # Node/Package manager caches + "NPM_CONFIG_CACHE", + "PNPM_HOME", + "XDG_CACHE_HOME", + "XDG_CONFIG_HOME", + "XDG_DATA_HOME", + # System info + "SYSTEMROOT", + "COMSPEC", + "PATHEXT", + "WINDIR", + } + + safe_env = {} + for key in safe_keys: + if key in os.environ: + safe_env[key] = os.environ[key] + + if "NPM_CONFIG_CACHE" not in safe_env: + safe_env["NPM_CONFIG_CACHE"] = MCP_NPM_CACHE_DIR + + return safe_env + async def _execute_session_operation( self, transport_ctx: Any, @@ -288,13 +329,23 @@ class MCPClient: ) -> TSessionResult: """ Execute an operation within a transport and session context. - Handles entering/exiting contexts and running the operation. + Passes sampling/elicitation/logging callbacks to the ClientSession + so that upstream MCP servers can request LLM inference (sampling), + user input (elicitation), or send log messages. """ transport = await transport_ctx.__aenter__() try: read_stream, write_stream = transport[0], transport[1] - session_ctx = ClientSession(read_stream, write_stream) + # Build session kwargs with optional callbacks + session_kwargs: Dict[str, Any] = {} + if self._sampling_callback is not None: + session_kwargs["sampling_callback"] = self._sampling_callback + if self._elicitation_callback is not None: + session_kwargs["elicitation_callback"] = self._elicitation_callback + if self._logging_callback is not None: + session_kwargs["logging_callback"] = self._logging_callback + session_ctx = ClientSession(read_stream, write_stream, **session_kwargs) session = await session_ctx.__aenter__() try: init_result = await session.initialize() @@ -351,7 +402,6 @@ class MCPClient: def _get_auth_headers(self) -> dict: """Generate authentication headers based on auth type.""" headers = {} - if self._mcp_auth_value: if isinstance(self._mcp_auth_value, str): if self.auth_type == MCPAuth.bearer_token: @@ -373,17 +423,14 @@ class MCPClient: # Note: aws_sigv4 auth is not handled here — SigV4 requires per-request # signing (including the body hash), so it uses httpx.Auth flow instead # of static headers. See MCPSigV4Auth and _create_httpx_client_factory(). - # update the headers with the extra headers if self.extra_headers: headers.update(self.extra_headers) - return headers def _create_httpx_client_factory(self) -> Callable[..., httpx.AsyncClient]: """ Create a custom httpx client factory that uses LiteLLM's SSL configuration. - This factory follows the same CA bundle path logic as http_handler.py: 1. Check ssl_verify parameter (can be SSLContext, bool, or path to CA bundle) 2. Check SSL_VERIFY environment variable @@ -400,17 +447,14 @@ class MCPClient: """Create an httpx.AsyncClient with LiteLLM's SSL configuration.""" # Get unified SSL configuration using the same logic as http_handler.py ssl_config = get_ssl_configuration(self.ssl_verify) - verbose_logger.debug( f"MCP client using SSL configuration: {type(ssl_config).__name__}" ) - # Use SigV4 auth if configured and no explicit auth provided. # The MCP SDK's sse_client and streamable_http_client call this # factory without passing auth=, so self._aws_auth is used. # For non-SigV4 clients, self._aws_auth is None — no behavior change. effective_auth = auth if auth is not None else self._aws_auth - return httpx.AsyncClient( headers=headers, timeout=timeout, @@ -458,7 +502,6 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( @@ -491,7 +534,6 @@ class MCPClient: f"MCP Tool '{call_tool_request_params.name}' progress: " f"{progress}/{total} ({percentage:.0f}%) - {message or ''}" ) - # Forward to Host if callback provided if host_progress_callback: try: @@ -521,7 +563,6 @@ class MCPClient: error_trace = traceback.format_exc() verbose_logger.debug(f"MCP client tool call traceback:\n{error_trace}") - # Log detailed error information error_type = type(e).__name__ verbose_logger.error( @@ -532,14 +573,12 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( "MCP client detected broken connection/stream - " "the MCP server may have crashed, disconnected, or timed out." ) - # Return a default error result instead of raising return MCPCallToolResult( content=[ @@ -577,14 +616,12 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( "MCP client detected broken connection/stream during list_tools - " "the MCP server may have crashed, disconnected, or timed out" ) - # Return empty list instead of raising to allow graceful degradation return [] @@ -617,7 +654,6 @@ class MCPClient: error_trace = traceback.format_exc() verbose_logger.debug(f"MCP client get_prompt traceback:\n{error_trace}") - # Log detailed error information error_type = type(e).__name__ verbose_logger.error( @@ -628,14 +664,12 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( "MCP client detected broken connection/stream during get_prompt - " "the MCP server may have crashed, disconnected, or timed out." ) - raise async def list_resources(self) -> list[Resource]: @@ -667,14 +701,12 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( "MCP client detected broken connection/stream during list_resources - " "the MCP server may have crashed, disconnected, or timed out" ) - # Return empty list instead of raising to allow graceful degradation return [] @@ -709,14 +741,12 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( "MCP client detected broken connection/stream during list_resource_templates - " "the MCP server may have crashed, disconnected, or timed out" ) - # Return empty list instead of raising to allow graceful degradation return [] @@ -742,7 +772,6 @@ class MCPClient: error_trace = traceback.format_exc() verbose_logger.debug(f"MCP client read_resource traceback:\n{error_trace}") - # Log detailed error information error_type = type(e).__name__ verbose_logger.error( @@ -753,12 +782,10 @@ class MCPClient: f"Server: {self.server_url or 'stdio'}, " f"Transport: {self.transport_type}" ) - # Check if it's a stream/connection error if "BrokenResourceError" in error_type or "Broken" in error_type: verbose_logger.error( "MCP client detected broken connection/stream during read_resource - " "the MCP server may have crashed, disconnected, or timed out." ) - raise diff --git a/litellm/litellm_core_utils/get_supported_openai_params.py b/litellm/litellm_core_utils/get_supported_openai_params.py index b8cdc8210fc..7c4f9941523 100644 --- a/litellm/litellm_core_utils/get_supported_openai_params.py +++ b/litellm/litellm_core_utils/get_supported_openai_params.py @@ -22,9 +22,11 @@ def get_supported_openai_params( # noqa: PLR0915 ``` Args: - base_model: For Azure, the true underlying model (e.g. ``"azure/gpt-5.2"``) - when the deployment name differs. Used for model-type detection so that - non-standard deployment names route to the correct config. + base_model: An optional capability hint for deployments whose ``model`` + label isn't recognized on its own (e.g. an Azure deployment name, or a + friendly Bedrock alias). It is additive: the result is the union of the + params supported by ``model`` and by ``base_model``, so a hint can only + add capabilities, never strip ones the real model already supports. Returns: - List if custom_llm_provider is mapped @@ -52,7 +54,15 @@ def get_supported_openai_params( # noqa: PLR0915 provider_config = None if provider_config and request_type == "chat_completion": - return provider_config.get_supported_openai_params(model=base_model or model) + supported_params = provider_config.get_supported_openai_params(model=model) + if base_model and base_model != model: + base_model_params = provider_config.get_supported_openai_params( + model=base_model + ) + supported_params = list( + dict.fromkeys([*supported_params, *base_model_params]) + ) + return supported_params if custom_llm_provider == "bedrock": return litellm.AmazonConverseConfig().get_supported_openai_params(model=model) diff --git a/litellm/litellm_core_utils/streaming_handler.py b/litellm/litellm_core_utils/streaming_handler.py index 55042a733ed..f3274151e5a 100644 --- a/litellm/litellm_core_utils/streaming_handler.py +++ b/litellm/litellm_core_utils/streaming_handler.py @@ -1149,6 +1149,32 @@ class CustomStreamWrapper: completion_obj: Dict[str, Any] = {"content": ""} from litellm.types.utils import GenericStreamingChunk as GChunk + if ( + isinstance(chunk, ModelResponseStream) + and self.custom_llm_provider is not None + and self.custom_llm_provider in litellm._custom_providers + ): + _has_content = bool( + chunk.choices + and chunk.choices[0].delta is not None + and ( + chunk.choices[0].delta.content + or chunk.choices[0].delta.tool_calls + ) + ) + if self.received_finish_reason is not None: + if not _has_content: + raise StopIteration + if chunk.choices and chunk.choices[0].finish_reason: + self.received_finish_reason = chunk.choices[0].finish_reason + if not _has_content: + return None + # Strip finish_reason from the content chunk so it appears + # only on the trailing empty-delta chunk (OpenAI spec). + # finish_reason_handler() will emit the proper terminal chunk. + chunk.choices[0].finish_reason = None # type: ignore[assignment] + return chunk + if ( isinstance(chunk, dict) and generic_chunk_has_all_required_fields( diff --git a/litellm/llms/azure/image_edit/transformation.py b/litellm/llms/azure/image_edit/transformation.py index a450ee0b217..72f1eef36c0 100644 --- a/litellm/llms/azure/image_edit/transformation.py +++ b/litellm/llms/azure/image_edit/transformation.py @@ -97,8 +97,15 @@ class AzureImageEditConfig(OpenAIImageEditConfig): ) original_url = httpx.URL(api_base) - # Extract api_version or use default - api_version = cast(Optional[str], litellm_params.get("api_version")) + # Resolve api_version: litellm_params > litellm.api_version > AZURE_API_VERSION env > default. + # Mirrors the fallback chain used by the Azure chat path in common_utils.py, + # so callers that set a global / env api_version don't get an unversioned URL. + api_version = ( + cast(Optional[str], litellm_params.get("api_version")) + or litellm.api_version + or get_secret_str("AZURE_API_VERSION") + or litellm.AZURE_DEFAULT_API_VERSION + ) # Create a new dictionary with existing params query_params = dict(original_url.params) diff --git a/litellm/llms/bedrock_mantle/responses/__init__.py b/litellm/llms/bedrock_mantle/responses/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/bedrock_mantle/responses/transformation.py b/litellm/llms/bedrock_mantle/responses/transformation.py new file mode 100644 index 00000000000..b63fd0ecdb1 --- /dev/null +++ b/litellm/llms/bedrock_mantle/responses/transformation.py @@ -0,0 +1,81 @@ +""" +Amazon Bedrock Mantle - Responses API backend. + +gpt-5.5 / gpt-5.4 on Mantle are exposed ONLY on the `/openai/v1/responses` +path (not the standard `/v1/responses`). Payloads and SSE follow the OpenAI +Responses spec, so this config inherits OpenAIResponsesAPIConfig and overrides +only the endpoint URL and Bearer authentication. + +Auth: AWS Bedrock API key as Bearer token (BEDROCK_MANTLE_API_KEY or the +standard AWS_BEARER_TOKEN_BEDROCK), NOT SigV4. +""" + +from typing import Optional + +from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig +from litellm.secret_managers.main import get_secret_str +from litellm.types.router import GenericLiteLLMParams +from litellm.types.utils import LlmProviders + +BEDROCK_MANTLE_DEFAULT_REGION = "us-east-1" + +# Checked longest/most-specific first so a full endpoint URL collapses to host +# in one pass and the appended path never doubles. +_BASE_SUFFIXES_TO_STRIP = ( + "/openai/v1/responses", + "/v1/responses", + "/responses", + "/openai/v1", + "/v1", +) + + +class BedrockMantleResponsesAPIConfig(OpenAIResponsesAPIConfig): + @property + def custom_llm_provider(self) -> LlmProviders: + return LlmProviders.BEDROCK_MANTLE + + def get_complete_url( + self, + api_base: Optional[str], + litellm_params: dict, + ) -> str: + region = ( + get_secret_str("BEDROCK_MANTLE_REGION") + or get_secret_str("AWS_REGION") + or BEDROCK_MANTLE_DEFAULT_REGION + ) + base = ( + api_base + or get_secret_str("BEDROCK_MANTLE_API_BASE") + or f"https://bedrock-mantle.{region}.api.aws" + ) + base = base.rstrip("/") + for suffix in _BASE_SUFFIXES_TO_STRIP: + if base.endswith(suffix): + base = base[: -len(suffix)] + break + return f"{base}/openai/v1/responses" + + def validate_environment( + self, headers: dict, model: str, litellm_params: Optional[GenericLiteLLMParams] + ) -> dict: + litellm_params = litellm_params or GenericLiteLLMParams() + api_key = ( + litellm_params.api_key + or get_secret_str("BEDROCK_MANTLE_API_KEY") + or get_secret_str("AWS_BEARER_TOKEN_BEDROCK") + ) + if not api_key: + raise ValueError( + "Bedrock Mantle API key is required. Set BEDROCK_MANTLE_API_KEY " + "(or AWS_BEARER_TOKEN_BEDROCK) or pass api_key." + ) + headers["Authorization"] = f"Bearer {api_key}" + return headers + + def supports_native_file_search(self) -> bool: + return False + + def supports_native_websocket(self) -> bool: + return False diff --git a/litellm/llms/fireworks_ai/chat/transformation.py b/litellm/llms/fireworks_ai/chat/transformation.py index 9e9d300b585..cca3b3da37a 100644 --- a/litellm/llms/fireworks_ai/chat/transformation.py +++ b/litellm/llms/fireworks_ai/chat/transformation.py @@ -170,11 +170,6 @@ class FireworksAIConfig(OpenAIGPTConfig): is_response_format_supported=False, enforce_tool_choice=False, # tools and response_format are both set, don't enforce tool_choice ) - elif "json_schema" in value: - optional_params["response_format"] = { - "type": "json_object", - "schema": value["json_schema"]["schema"], - } else: optional_params["response_format"] = value elif param == "max_completion_tokens": diff --git a/litellm/llms/gemini/videos/transformation.py b/litellm/llms/gemini/videos/transformation.py index 77a95bfa5ab..644e96a7dd1 100644 --- a/litellm/llms/gemini/videos/transformation.py +++ b/litellm/llms/gemini/videos/transformation.py @@ -265,7 +265,11 @@ class GeminiVideoConfig(BaseVideoConfig): { "instances": [ { - "prompt": "A cat playing with a ball of yarn" + "prompt": "A cat playing with a ball of yarn", + "image": { + "bytesBase64Encoded": "...", + "mimeType": "image/jpeg" + } } ], "parameters": { @@ -275,13 +279,18 @@ class GeminiVideoConfig(BaseVideoConfig): } } """ - instance = GeminiVideoGenerationInstance(prompt=prompt) + instance: GeminiVideoGenerationInstance = {"prompt": prompt} params_copy = video_create_optional_request_params.copy() - if "image" in params_copy and params_copy["image"] is not None: - image_data = _convert_image_to_gemini_format(params_copy["image"]) - params_copy["image"] = image_data + if "image" in params_copy: + image = params_copy.pop("image") + if image is not None: + if isinstance(image, dict): + image_data = image + else: + image_data = _convert_image_to_gemini_format(image) + instance["image"] = image_data parameters = GeminiVideoGenerationParameters(**params_copy) diff --git a/litellm/llms/huggingface/embedding/handler.py b/litellm/llms/huggingface/embedding/handler.py index 226f6b2ebad..6be885b1f91 100644 --- a/litellm/llms/huggingface/embedding/handler.py +++ b/litellm/llms/huggingface/embedding/handler.py @@ -239,7 +239,7 @@ class HuggingFaceEmbedding(BaseLLM): model_response.model = model input_tokens = 0 for text in input: - input_tokens += len(encoding.encode(text)) + input_tokens += len(encoding.encode(text, disallowed_special=())) setattr( model_response, diff --git a/litellm/llms/snowflake/utils.py b/litellm/llms/snowflake/utils.py index d84efdd9fcd..4f79006f6f8 100644 --- a/litellm/llms/snowflake/utils.py +++ b/litellm/llms/snowflake/utils.py @@ -25,6 +25,7 @@ class SnowflakeBaseConfig: "temperature", "max_tokens", "top_p", + "stream", "response_format", "tools", "tool_choice", diff --git a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py index 3f945adca0d..e9f08f403f9 100644 --- a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py +++ b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py @@ -337,6 +337,7 @@ class ContextCachingEndpoints(VertexBase): return messages, optional_params, None tools = optional_params.pop("tools", None) + tool_choice = optional_params.pop("tool_choice", None) ## AUTHORIZATION ## token, url = self._get_token_and_url_context_caching( @@ -371,7 +372,7 @@ class ContextCachingEndpoints(VertexBase): ## CHECK IF CACHED ALREADY generated_cache_key = local_cache_obj.get_cache_key( - messages=cached_messages, tools=tools, model=model + messages=cached_messages, tools=tools, tool_choice=tool_choice, model=model ) google_cache_name = self.check_cache( cache_key=generated_cache_key, @@ -402,6 +403,8 @@ class ContextCachingEndpoints(VertexBase): ) cached_content_request_body["tools"] = tools + if tool_choice is not None: + cached_content_request_body["toolConfig"] = tool_choice ## LOGGING logging_obj.pre_call( @@ -487,6 +490,7 @@ class ContextCachingEndpoints(VertexBase): return messages, optional_params, None tools = optional_params.pop("tools", None) + tool_choice = optional_params.pop("tool_choice", None) ## AUTHORIZATION ## token, url = self._get_token_and_url_context_caching( @@ -518,7 +522,7 @@ class ContextCachingEndpoints(VertexBase): ## CHECK IF CACHED ALREADY generated_cache_key = local_cache_obj.get_cache_key( - messages=cached_messages, tools=tools, model=model + messages=cached_messages, tools=tools, tool_choice=tool_choice, model=model ) google_cache_name = await self.async_check_cache( cache_key=generated_cache_key, @@ -550,6 +554,8 @@ class ContextCachingEndpoints(VertexBase): ) cached_content_request_body["tools"] = tools + if tool_choice is not None: + cached_content_request_body["toolConfig"] = tool_choice ## LOGGING logging_obj.pre_call( diff --git a/litellm/main.py b/litellm/main.py index 96f81381c86..c8aae0ce85b 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -1322,7 +1322,9 @@ def completion( # type: ignore # noqa: PLR0915 preset_cache_key = kwargs.get("preset_cache_key", None) hf_model_name = kwargs.get("hf_model_name", None) supports_system_message = kwargs.get("supports_system_message", None) - base_model = kwargs.get("base_model", None) + base_model = kwargs.get("base_model", None) or ( + model_info.get("base_model") if isinstance(model_info, dict) else None + ) ### DISABLE FLAGS ### disable_add_transform_inline_image_block = kwargs.get( "disable_add_transform_inline_image_block", None @@ -1534,11 +1536,7 @@ def completion( # type: ignore # noqa: PLR0915 "logit_bias": logit_bias, "user": user, # params to identify the model - "model": ( - model_info.get("base_model") - if isinstance(model_info, dict) and model_info.get("base_model") - else model - ), + "model": model, "custom_llm_provider": custom_llm_provider, "response_format": response_format, "seed": seed, diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index ed6de4fa6b7..fbe6c097202 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -41223,6 +41223,44 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "bedrock_mantle/openai.gpt-5.5": { + "input_cost_per_token": 5.5e-06, + "cache_read_input_token_cost": 5.5e-07, + "output_cost_per_token": 3.3e-05, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "supported_endpoints": ["/v1/responses"], + "supported_modalities": ["text", "image"], + "supported_output_modalities": ["text"], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "bedrock_mantle/openai.gpt-5.4": { + "input_cost_per_token": 2.75e-06, + "cache_read_input_token_cost": 2.75e-07, + "output_cost_per_token": 1.65e-05, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "supported_endpoints": ["/v1/responses"], + "supported_modalities": ["text", "image"], + "supported_output_modalities": ["text"], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "volcengine/doubao-seed-2-0-pro-260215": { "litellm_provider": "volcengine", "max_input_tokens": 256000, diff --git a/litellm/proxy/_experimental/mcp_server/elicitation_handler.py b/litellm/proxy/_experimental/mcp_server/elicitation_handler.py new file mode 100644 index 00000000000..e42270bf10b --- /dev/null +++ b/litellm/proxy/_experimental/mcp_server/elicitation_handler.py @@ -0,0 +1,163 @@ +""" +MCP Elicitation Handler +Handles `elicitation/create` requests from upstream MCP servers by either: +1. Relaying them to the connected downstream MCP client (if it supports elicitation) +2. Returning a decline/error response (if no downstream client or unsupported) +Supports both Form mode (structured data collection) and URL mode (external URL +navigation for sensitive interactions like OAuth). +MCP Spec Reference: + https://modelcontextprotocol.io/specification/2025-11-25/client/elicitation +""" + +from typing import Any, Optional, Union +from litellm._logging import verbose_logger + +# Guard imports that require the mcp package +try: + from mcp.types import ( + ElicitRequestFormParams, + ElicitRequestParams, + ElicitRequestURLParams, + ElicitResult, + ErrorData, + ) + + MCP_ELICITATION_AVAILABLE = True +except ImportError: + MCP_ELICITATION_AVAILABLE = False + + +async def handle_elicitation_request( + context: Any, + params: "ElicitRequestParams", + downstream_session: Optional[Any] = None, + downstream_capabilities: Optional[Any] = None, +) -> Union["ElicitResult", "ErrorData"]: + """ + Handle an MCP elicitation/create request from an upstream MCP server. + In Gateway mode (Mode A), we relay the elicitation request to the + connected downstream client if they declared elicitation capabilities. + In Tool Bridge mode (Mode B), there's no persistent downstream MCP + client, so we return a decline response. + Args: + context: MCP RequestContext from the upstream server connection. + params: The ElicitRequestParams (either form or URL mode). + downstream_session: The ServerSession to the downstream client, + if available (for relaying). + downstream_capabilities: The downstream client's declared + capabilities, used to check elicitation support. + Returns: + ElicitResult with the user's response, or ErrorData on failure. + """ + if not MCP_ELICITATION_AVAILABLE: + return ErrorData( + code=-1, + message="MCP elicitation is not available (mcp package not installed)", + ) + try: + mode = getattr(params, "mode", "form") + verbose_logger.info( + "MCP elicitation: received request mode=%s, message=%s", + mode, + getattr(params, "message", ""), + ) + # Check if we have a downstream session to relay to + if downstream_session is not None: + return await _relay_elicitation_to_downstream( + params=params, + downstream_session=downstream_session, + downstream_capabilities=downstream_capabilities, + ) + # No downstream session — we're in Tool Bridge mode + # or the client doesn't support elicitation + verbose_logger.info( + "MCP elicitation: no downstream session available, declining" + ) + return ElicitResult( + action="decline", + ) + except Exception as e: + verbose_logger.exception("MCP elicitation handler failed: %s", e) + return ErrorData( + code=-1, + message=f"Elicitation failed: {str(e)}", + ) + + +async def _relay_elicitation_to_downstream( + params: "ElicitRequestParams", + downstream_session: Any, + downstream_capabilities: Optional[Any] = None, +) -> Union["ElicitResult", "ErrorData"]: + """ + Relay an elicitation request to the downstream MCP client. + Uses the ServerSession's elicit_form() or elicit_url() methods to + send the elicitation request back to the connected client. + Args: + params: The elicitation request parameters. + downstream_session: The ServerSession connected to the downstream client. + downstream_capabilities: Client capabilities to check support. + Returns: + ElicitResult from the downstream client. + """ + mode = getattr(params, "mode", "form") + # Check if the downstream client supports the requested mode + if downstream_capabilities is not None: + elicit_caps = getattr(downstream_capabilities, "elicitation", None) + if elicit_caps is None: + verbose_logger.info( + "MCP elicitation: downstream client does not support elicitation" + ) + return ElicitResult(action="decline") + if mode == "url": + url_cap = getattr(elicit_caps, "url", None) + if url_cap is None: + verbose_logger.info( + "MCP elicitation: downstream client does not support URL mode" + ) + return ElicitResult(action="decline") + if mode == "form": + form_cap = getattr(elicit_caps, "form", None) + if form_cap is None: + verbose_logger.info( + "MCP elicitation: downstream client does not support form mode" + ) + return ElicitResult(action="decline") + try: + if mode == "url" and isinstance(params, ElicitRequestURLParams): + # URL mode: relay URL to client for external navigation + verbose_logger.info( + "MCP elicitation: relaying URL mode to downstream, url=%s", + getattr(params, "url", ""), + ) + result = await downstream_session.elicit_url( + message=params.message, + url=params.url, + elicitation_id=getattr(params, "elicitationId", None), + ) + elif isinstance(params, ElicitRequestFormParams): + # Form mode: relay structured form to client + verbose_logger.info("MCP elicitation: relaying form mode to downstream") + result = await downstream_session.elicit_form( + message=params.message, + requestedSchema=getattr(params, "requestedSchema", None), + ) + else: + # Fallback for generic ElicitRequestParams — pass an empty schema + # since elicit() requires requestedSchema as a positional arg. + verbose_logger.info( + "MCP elicitation: relaying generic elicitation to downstream" + ) + result = await downstream_session.elicit( + message=getattr(params, "message", ""), + requestedSchema=getattr(params, "requestedSchema", {}), + ) + verbose_logger.info( + "MCP elicitation: downstream responded with action=%s", + getattr(result, "action", "unknown"), + ) + return result + except Exception as e: + verbose_logger.warning("MCP elicitation: failed to relay to downstream: %s", e) + # If relay fails, decline gracefully + return ElicitResult(action="decline") diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py index d9b112f6c21..0d2008cdade 100644 --- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py +++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py @@ -49,6 +49,12 @@ from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import ( MCPRequestHandler, ) from litellm.proxy._experimental.mcp_server.exceptions import MCPUpstreamAuthError +from litellm.proxy._experimental.mcp_server.elicitation_handler import ( + MCP_ELICITATION_AVAILABLE, +) +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + MCP_SAMPLING_AVAILABLE, +) from litellm.proxy._experimental.mcp_server.oauth2_token_cache import resolve_mcp_auth from litellm.proxy._experimental.mcp_server.utils import ( MCP_TOOL_PREFIX_SEPARATOR, @@ -289,6 +295,82 @@ def _deserialize_json_dict(data: Any) -> Optional[Dict[str, str]]: return data +def _create_sampling_callback(user_api_key_auth: Optional[Any] = None): + """ + Create a sampling callback for MCP ClientSession. + Returns a callable that handles sampling/createMessage requests from + upstream MCP servers by routing them through litellm.acompletion(). + """ + if not MCP_SAMPLING_AVAILABLE: + return None + + async def _sampling_callback(context, params): + from litellm.proxy._experimental.mcp_server.sampling_handler import ( + handle_sampling_create_message, + ) + import litellm + from litellm.proxy._experimental.mcp_server.server import ( + get_active_auth_context, + ) + + auth_context = get_active_auth_context() + resolved_auth = user_api_key_auth or ( + auth_context.user_api_key_auth if auth_context else None + ) + # Forward original HTTP headers and client IP so that + # header-dependent guardrails, tag-based routing, trace + # correlation, and forward_llm_provider_auth_headers work + # correctly for sampling sub-calls. + _raw_headers = getattr(auth_context, "raw_headers", None) + _client_ip = getattr(auth_context, "client_ip", None) + + return await handle_sampling_create_message( + context=context, + params=params, + default_model=getattr(litellm, "default_mcp_sampling_model", None), + user_api_key_auth=resolved_auth, + raw_headers=_raw_headers, + client_ip=_client_ip, + ) + + return _sampling_callback + + +def _create_elicitation_callback(): + """ + Create an elicitation callback for MCP ClientSession. + Returns a callable that handles elicitation/create requests from + upstream MCP servers. In gateway mode, this relays to the downstream + client; in tool bridge mode, it returns a decline response. + """ + if not MCP_ELICITATION_AVAILABLE: + return None + + async def _elicitation_callback(context, params): + from litellm.proxy._experimental.mcp_server.elicitation_handler import ( + handle_elicitation_request, + ) + from litellm.proxy._experimental.mcp_server.server import get_active_mcp_session + + # In Gateway mode, we relay the elicitation request to the downstream client + # that triggered the current operation. + downstream_session = get_active_mcp_session() + downstream_capabilities = ( + getattr(downstream_session, "capabilities", None) + if downstream_session + else None + ) + + return await handle_elicitation_request( + context=context, + params=params, + downstream_session=downstream_session, + downstream_capabilities=downstream_capabilities, + ) + + return _elicitation_callback + + class MCPServerManager: _STDIO_ENV_TEMPLATE_PATTERN = re.compile(r"^\$\{(X-[^}]+)\}$") @@ -600,6 +682,8 @@ class MCPServerManager: "subject_token_type", "urn:ietf:params:oauth:token-type:access_token", ), + allow_sampling=bool(server_config.get("allow_sampling", False)), + allow_elicitation=bool(server_config.get("allow_elicitation", False)), ) self._assign_unique_short_prefix(new_server) _warn_internal_delegate_pkce_if_applicable(new_server, source="config") @@ -699,8 +783,7 @@ class MCPServerManager: ) verbose_logger.debug( - f"Using headers for OpenAPI tools (excluding sensitive values): " - f"{list(headers.keys())}" + f"Using headers for OpenAPI tools (excluding sensitive values): {list(headers.keys())}" ) # Extract and register tools from OpenAPI paths @@ -1494,6 +1577,7 @@ class MCPServerManager: extra_headers: Optional[Dict[str, str]] = None, stdio_env: Optional[Dict[str, str]] = None, subject_token: Optional[str] = None, + user_api_key_auth: Optional[UserAPIKeyAuth] = None, ) -> MCPClient: """ Create an MCPClient instance for the given server. @@ -1510,6 +1594,7 @@ class MCPServerManager: extra_headers: Additional headers to forward. stdio_env: Environment variables for stdio transport. subject_token: Optional user JWT for token exchange (OBO) flow. + user_api_key_auth: Optional auth context for sampling callbacks. Returns: Configured MCP client instance. @@ -1520,23 +1605,44 @@ class MCPServerManager: transport = server.transport or MCPTransport.sse + # Create sampling and elicitation callbacks for this client + sampling_cb = ( + _create_sampling_callback(user_api_key_auth=user_api_key_auth) + if server.allow_sampling + else None + ) + elicitation_cb = ( + _create_elicitation_callback() if server.allow_elicitation else None + ) + # Handle stdio transport if transport == MCPTransport.stdio: resolved_env = ( - stdio_env if stdio_env is not None else dict(server.env or {}) + stdio_env + if stdio_env is not None + else (dict(server.env) if server.env is not None else None) ) # Ensure npm-based STDIO MCP servers have a writable cache dir. # In containers the default (~/.npm or /app/.npm) may not exist # or be read-only, causing npx to fail with ENOENT. - if "NPM_CONFIG_CACHE" not in resolved_env: + if resolved_env is not None and "NPM_CONFIG_CACHE" not in resolved_env: resolved_env["NPM_CONFIG_CACHE"] = MCP_NPM_CACHE_DIR # Defense-in-depth: block commands not in the allowlist. # The Pydantic validator blocks new servers; this catches legacy # config/DB records predating the allowlist. if server.command: base_command = os.path.basename(server.command) - if base_command not in MCP_STDIO_ALLOWED_COMMANDS: + # Strip .exe/.cmd/.bat/.com suffix for Windows compatibility + base_command_no_ext = base_command.lower() + for ext in [".exe", ".cmd", ".bat", ".com"]: + if base_command.lower().endswith(ext): + base_command_no_ext = base_command[: -len(ext)].lower() + break + if ( + base_command.lower() not in MCP_STDIO_ALLOWED_COMMANDS + and base_command_no_ext not in MCP_STDIO_ALLOWED_COMMANDS + ): raise HTTPException( status_code=403, detail=f"MCP stdio command '{server.command}' is not in the allowlist ({sorted(MCP_STDIO_ALLOWED_COMMANDS)}). " @@ -1559,6 +1665,8 @@ class MCPServerManager: timeout=MCP_CLIENT_TIMEOUT, stdio_config=stdio_config, extra_headers=extra_headers, + sampling_callback=sampling_cb, + elicitation_callback=elicitation_cb, ) else: # For HTTP/SSE transports @@ -1585,6 +1693,8 @@ class MCPServerManager: timeout=MCP_CLIENT_TIMEOUT, extra_headers=extra_headers, aws_auth=aws_auth, + sampling_callback=sampling_cb, + elicitation_callback=elicitation_cb, ) async def _get_tools_from_server( @@ -1668,6 +1778,7 @@ class MCPServerManager: mcp_auth_header=mcp_auth_header, extra_headers=extra_headers, stdio_env=stdio_env, + user_api_key_auth=user_api_key_auth, ) ## HANDLE OPENAPI TOOLS @@ -3030,6 +3141,7 @@ class MCPServerManager: extra_headers=extra_headers, stdio_env=stdio_env, subject_token=subject_token, + user_api_key_auth=user_api_key_auth, ) call_tool_params = MCPCallToolRequestParams( @@ -3260,7 +3372,6 @@ class MCPServerManager: ) ) else: - # For regular MCP servers, use the MCP client return await self._call_regular_mcp_tool( mcp_server=mcp_server, original_tool_name=name, diff --git a/litellm/proxy/_experimental/mcp_server/sampling_handler.py b/litellm/proxy/_experimental/mcp_server/sampling_handler.py new file mode 100644 index 00000000000..1637c9eb0b9 --- /dev/null +++ b/litellm/proxy/_experimental/mcp_server/sampling_handler.py @@ -0,0 +1,1279 @@ +""" +MCP Sampling Handler +Handles `sampling/createMessage` requests from upstream MCP servers by +routing them through LiteLLM's internal completion infrastructure. +This allows MCP servers to perform agentic reasoning (e.g., multi-step +tool calling, chain-of-thought) without needing their own LLM API keys — +LiteLLM acts as the LLM provider using its existing 100+ provider support, +cost tracking, rate limiting, and model routing. +MCP Spec Reference: + https://modelcontextprotocol.io/specification/2025-11-25/client/sampling +""" + +from typing import Any, Dict, List, Optional, Union +import typing + +if typing.TYPE_CHECKING: + from litellm.proxy.utils import ProxyLogging + +from litellm._logging import verbose_logger + +from fastapi import HTTPException + +# Guard imports that require the mcp package +try: + from mcp.types import ( + CreateMessageRequestParams, + CreateMessageResult, + CreateMessageResultWithTools, + ErrorData, + ModelPreferences, + SamplingMessage, + TextContent, + Tool, + ToolChoice, + ToolUseContent, + ) + + MCP_SAMPLING_AVAILABLE = True +except ImportError as _sampling_import_err: + MCP_SAMPLING_AVAILABLE = False + verbose_logger.warning( + "MCP sampling disabled: failed to import required types from mcp.types — %s. " + "This usually means the 'mcp' package is not installed or is an older version " + "that does not support sampling. Install/upgrade with: pip install 'mcp>=1.1'", + _sampling_import_err, + ) + + +def _resolve_model_from_preferences( + model_preferences: Optional["ModelPreferences"], + default_model: Optional[str] = None, +) -> str: + """ + Resolve an LLM model name from MCP ModelPreferences. + Strategy: + 1. Check hints for substring matches against known model names. + 2. Fall back to priority-based selection (cost/speed/intelligence). + 3. Fall back to the configured default model. + Args: + model_preferences: MCP ModelPreferences with hints and priorities. + default_model: Fallback model if no hint matches. + Returns: + A model string suitable for litellm.acompletion(). + """ + import litellm + + # Build list of available model names from proxy Router or litellm.model_list + available_model_names: list = [] + try: + from litellm.proxy.proxy_server import llm_router + + if llm_router is not None: + available_model_names = llm_router.get_model_names() + except Exception: + pass + if not available_model_names and litellm.model_list: + for entry in litellm.model_list: + if isinstance(entry, dict): + name = entry.get("model_name") + if name: + available_model_names.append(name) + elif isinstance(entry, str): + available_model_names.append(entry) + if model_preferences and model_preferences.hints: + for hint in model_preferences.hints: + hint_name = getattr(hint, "name", None) + if not hint_name: + continue + # Try direct match first + if hint_name in available_model_names: + verbose_logger.debug( + "MCP sampling model resolution: direct hint match '%s'", + hint_name, + ) + return hint_name + # Try substring match against known models + for model_name in available_model_names: + if hint_name.lower() in model_name.lower(): + verbose_logger.debug( + "MCP sampling model resolution: substring hint match " + "'%s' -> '%s'", + hint_name, + model_name, + ) + return model_name + verbose_logger.debug( + "MCP sampling model resolution: no hint matched from %s " + "against %d available models", + [getattr(h, "name", None) for h in model_preferences.hints], + len(available_model_names), + ) + + # 2. Priority-based selection (cost/speed/intelligence) + if ( + model_preferences + and available_model_names + and _has_priorities(model_preferences) + ): + best = _select_model_by_priority(available_model_names, model_preferences) + if best is not None: + verbose_logger.debug( + "MCP sampling model resolution: priority-based selection chose '%s'", + best, + ) + return best + + # 3. Use default model from caller + if default_model: + verbose_logger.debug( + "MCP sampling model resolution: using caller-provided default '%s'", + default_model, + ) + return default_model + # Fall back to first available model + if available_model_names: + verbose_logger.debug( + "MCP sampling model resolution: no default configured, " + "falling back to first available model '%s'", + available_model_names[0], + ) + return available_model_names[0] + # Last resort - use LiteLLM default or raise error + default_sampling_model = getattr(litellm, "default_mcp_sampling_model", None) + if default_sampling_model: + verbose_logger.debug( + "MCP sampling model resolution: using litellm.default_mcp_sampling_model='%s'", + default_sampling_model, + ) + return default_sampling_model + raise ValueError( + "No model could be resolved for MCP sampling. Please configure 'default_mcp_sampling_model' in your LiteLLM configuration." + ) + + +def _has_priorities(model_preferences: "ModelPreferences") -> bool: + """Return True if any priority weight is set (non-None and > 0).""" + return any( + (getattr(model_preferences, attr, None) or 0) > 0 + for attr in ("costPriority", "speedPriority", "intelligencePriority") + ) + + +def _select_model_by_priority( + model_names: List[str], + model_preferences: "ModelPreferences", +) -> Optional[str]: + """Score available models by MCP priority weights and return the best. + + Scoring strategy (per the MCP spec, priorities are 0-1 floats): + + * **costPriority** — higher means "prefer cheaper models". + Metric: combined (input + output) cost per token from + ``model_prices_and_context_window.json``. Lower cost → higher score. + + * **speedPriority** — higher means "prefer faster models". + Metric: ``output_tokens_per_second`` from model info when available; + otherwise a neutral score for every candidate, since no reliable + latency proxy exists (context-window size does not track speed). + + * **intelligencePriority** — higher means "prefer smarter models". + Metric: ``max_output_tokens`` is used as a rough capability proxy + (frontier models expose larger context windows). + + Each metric is min-max normalised across the candidate set so that + every model gets a 0-1 score per dimension. The final score is the + weighted sum of the three normalised dimensions. + + Returns the highest-scoring model name, or None if scoring fails for + all candidates (e.g. no model_info available). + """ + import litellm as _litellm + + cost_weight = getattr(model_preferences, "costPriority", None) or 0.0 + speed_weight = getattr(model_preferences, "speedPriority", None) or 0.0 + intel_weight = getattr(model_preferences, "intelligencePriority", None) or 0.0 + + # Gather raw metrics for each model + scored: List[Dict[str, Any]] = [] + for name in model_names: + try: + info = _litellm.get_model_info(name) + except Exception: + continue + input_cost = info.get("input_cost_per_token") or 0.0 + output_cost = info.get("output_cost_per_token") or 0.0 + total_cost = input_cost + output_cost + max_output = info.get("max_output_tokens") or info.get("max_tokens") or 0 + output_tps = info.get("output_tokens_per_second") or 0.0 + scored.append( + { + "name": name, + "cost": total_cost, + "max_output": max_output, + "output_tps": output_tps, + } + ) + + if not scored: + return None + + # Min-max normalisation helpers + def _normalise(values: List[float], invert: bool = False) -> List[float]: + """Normalise to [0, 1]. If *invert*, lower raw → higher score.""" + lo, hi = min(values), max(values) + if hi == lo: + return [0.5] * len(values) # all equal → neutral score + normed = [(v - lo) / (hi - lo) for v in values] + if invert: + normed = [1.0 - n for n in normed] + return normed + + costs = [s["cost"] for s in scored] + max_outputs = [float(s["max_output"]) for s in scored] + output_tps_values = [s["output_tps"] for s in scored] + + # costPriority: lower cost → higher score (invert) + cost_scores = _normalise(costs, invert=True) + # speedPriority: use output_tokens_per_second if any model has it, + # otherwise a neutral score (no reliable latency proxy is available). + if any(v > 0 for v in output_tps_values): + speed_scores = _normalise(output_tps_values, invert=False) + else: + speed_scores = [0.5] * len(scored) + # intelligencePriority: higher max_output → smarter + intel_scores = _normalise(max_outputs, invert=False) + + best_name = None + best_score = -1.0 + for i, entry in enumerate(scored): + score = ( + cost_weight * cost_scores[i] + + speed_weight * speed_scores[i] + + intel_weight * intel_scores[i] + ) + verbose_logger.debug( + "MCP priority scoring: model=%s cost_score=%.3f speed_score=%.3f " + "intel_score=%.3f → weighted=%.3f", + entry["name"], + cost_scores[i], + speed_scores[i], + intel_scores[i], + score, + ) + if score > best_score: + best_score = score + best_name = entry["name"] + + return best_name + + +def _convert_mcp_content_to_openai( + content: Any, +) -> Union[str, Dict[str, Any], List[Dict[str, Any]]]: + """ + Convert MCP SamplingMessage content to OpenAI message content format. + Handles: + - TextContent → string or {"type": "text", "text": ...} + - ImageContent → {"type": "image_url", "image_url": {"url": "data:..."}} + - AudioContent → {"type": "input_audio", "input_audio": {...}} + - ToolUseContent → function call representation + - ToolResultContent → tool result representation + - List of mixed content → list of content parts + """ + if isinstance(content, list): + parts = [] + for item in content: + converted = _convert_single_content(item) + if isinstance(converted, list): + parts.extend(converted) + else: + parts.append(converted) + return parts + return _convert_single_content(content) + + +def _convert_single_content( + content: Any, +) -> Union[Dict[str, Any], List[Dict[str, Any]]]: + """Convert a single MCP content item to OpenAI format. + + For text/image/audio content, returns a single content-part dict. + For tool_use/tool_result, returns a dict with a ``_marker_type`` key + so the caller (``_convert_mcp_messages_to_openai``) can hoist it to + the correct message-level position (``tool_calls`` array or a + separate ``role: "tool"`` message). + """ + import json + + content_type = getattr(content, "type", None) + if content_type == "text": + return {"type": "text", "text": content.text} + elif content_type == "image": + data = getattr(content, "data", "") + mime_type = getattr(content, "mimeType", "image/png") + return { + "type": "image_url", + "image_url": {"url": f"data:{mime_type};base64,{data}"}, + } + elif content_type == "audio": + data = getattr(content, "data", "") + mime_type = getattr(content, "mimeType", "audio/wav") + # Map MIME type to OpenAI audio format + format_map = { + "audio/wav": "wav", + "audio/mp3": "mp3", + "audio/mpeg": "mp3", + "audio/flac": "flac", + "audio/ogg": "ogg", + } + audio_format = format_map.get(mime_type, "wav") + return { + "type": "input_audio", + "input_audio": {"data": data, "format": audio_format}, + } + elif content_type == "tool_use": + # ToolUseContent → proper OpenAI function-call representation. + # The ``_marker_type`` key lets the message-level converter + # hoist this into the ``tool_calls`` array on the assistant + # message instead of embedding it inline as a content part. + return { + "_marker_type": "tool_use", + "id": getattr(content, "id", f"call_{id(content)}"), + "type": "function", + "function": { + "name": getattr(content, "name", ""), + "arguments": json.dumps(getattr(content, "input", {}), default=str), + }, + } + elif content_type == "tool_result": + # ToolResultContent → proper OpenAI tool-role message. + # Marked so the message-level converter can emit it as a + # separate ``{"role": "tool", ...}`` message. + tool_use_id = getattr(content, "toolUseId", "") + nested_content = getattr(content, "content", []) + if isinstance(nested_content, list): + text_parts = [ + getattr(c, "text", str(c)) + for c in nested_content + if getattr(c, "type", None) == "text" + ] + result_text = "\n".join(text_parts) if text_parts else "" + else: + result_text = str(nested_content) + return { + "_marker_type": "tool_result", + "role": "tool", + "tool_call_id": tool_use_id, + "content": result_text, + } + # Fallback: treat as text + return {"type": "text", "text": str(content)} + + +def _convert_mcp_messages_to_openai( + messages: List["SamplingMessage"], + system_prompt: Optional[str] = None, +) -> List[Dict[str, Any]]: + """ + Convert MCP SamplingMessage list to OpenAI messages format. + MCP messages use: + - role: "user" | "assistant" + - content: TextContent | ImageContent | AudioContent | ToolUseContent + | ToolResultContent | list[...] + OpenAI messages use: + - role: "system" | "user" | "assistant" | "tool" + - content: str | list[content_part] + """ + openai_messages: List[Dict[str, Any]] = [] + # Add system prompt if provided + if system_prompt: + openai_messages.append({"role": "system", "content": system_prompt}) + for msg in messages: + role = msg.role + content = msg.content + # Handle tool use content from assistant + if role == "assistant" and _has_tool_use(content): + tool_calls = _extract_tool_calls(content) + if tool_calls: + openai_msg: Dict[str, Any] = { + "role": "assistant", + "tool_calls": tool_calls, + } + # Also include any text content alongside tool calls + text_parts = _extract_text_parts(content) + if text_parts: + openai_msg["content"] = text_parts + openai_messages.append(openai_msg) + continue + # Handle tool result content from user + if role == "user" and _has_tool_result(content): + tool_results = _extract_tool_results(content) + for tool_result in tool_results: + openai_messages.append(tool_result) + continue + # Standard text/image/audio message — also handles any stray + # tool_use / tool_result that slipped past the fast-path checks + # above (e.g. unexpected role, single non-list content). + converted = _convert_mcp_content_to_openai(content) + converted_parts = ( + converted + if isinstance(converted, list) + else ([converted] if isinstance(converted, dict) else []) + ) + + # Separate marker items from regular content parts + tool_call_markers = [] + tool_result_markers = [] + regular_parts = [] + for part in converted_parts: + marker = part.get("_marker_type") if isinstance(part, dict) else None + if marker == "tool_use": + # Strip the internal marker before emitting + tc = {k: v for k, v in part.items() if k != "_marker_type"} + tool_call_markers.append(tc) + elif marker == "tool_result": + tr = {k: v for k, v in part.items() if k != "_marker_type"} + tool_result_markers.append(tr) + else: + regular_parts.append(part) + + # Emit assistant message with tool_calls if any were found + if tool_call_markers: + openai_msg_tc: Dict[str, Any] = { + "role": "assistant", + "tool_calls": tool_call_markers, + } + if regular_parts: + openai_msg_tc["content"] = regular_parts + openai_messages.append(openai_msg_tc) + elif regular_parts: + if isinstance(converted, str): + openai_messages.append({"role": role, "content": converted}) + else: + openai_messages.append({"role": role, "content": regular_parts}) + + # Emit separate tool-result messages + for tr in tool_result_markers: + openai_messages.append(tr) + + return openai_messages + + +def _has_tool_use(content: Any) -> bool: + """Check if content contains ToolUseContent.""" + if isinstance(content, list): + return any(getattr(c, "type", None) == "tool_use" for c in content) + return getattr(content, "type", None) == "tool_use" + + +def _has_tool_result(content: Any) -> bool: + """Check if content contains ToolResultContent.""" + if isinstance(content, list): + return any(getattr(c, "type", None) == "tool_result" for c in content) + return getattr(content, "type", None) == "tool_result" + + +def _extract_tool_calls(content: Any) -> List[Dict[str, Any]]: + """Extract OpenAI-format tool_calls from MCP ToolUseContent.""" + import json + + items = content if isinstance(content, list) else [content] + tool_calls = [] + for item in items: + if getattr(item, "type", None) == "tool_use": + tool_calls.append( + { + "id": getattr(item, "id", f"call_{id(item)}"), + "type": "function", + "function": { + "name": getattr(item, "name", ""), + "arguments": json.dumps( + getattr(item, "input", {}), default=str + ), + }, + } + ) + return tool_calls + + +def _extract_text_parts(content: Any) -> Optional[str]: + """Extract text parts from mixed content.""" + items = content if isinstance(content, list) else [content] + texts = [] + for item in items: + if getattr(item, "type", None) == "text": + texts.append(getattr(item, "text", "")) + return "\n".join(texts) if texts else None + + +def _extract_tool_results(content: Any) -> List[Dict[str, Any]]: + """Extract OpenAI-format tool messages from MCP ToolResultContent.""" + items = content if isinstance(content, list) else [content] + results = [] + for item in items: + if getattr(item, "type", None) == "tool_result": + tool_use_id = getattr(item, "toolUseId", "") + # Extract text from nested content + nested_content = getattr(item, "content", []) + if isinstance(nested_content, list): + text_parts = [ + getattr(c, "text", str(c)) + for c in nested_content + if getattr(c, "type", None) == "text" + ] + result_text = "\n".join(text_parts) if text_parts else "" + else: + result_text = str(nested_content) + results.append( + { + "role": "tool", + "tool_call_id": tool_use_id, + "content": result_text, + } + ) + return results + + +def _convert_mcp_tools_to_openai( + tools: Optional[List["Tool"]], +) -> Optional[List[Dict[str, Any]]]: + """ + Convert MCP Tool definitions to OpenAI function calling format. + MCP Tool: {name, description, inputSchema} + OpenAI Tool: {type: "function", function: {name, description, parameters}} + """ + if not tools: + return None + openai_tools = [] + for tool in tools: + openai_tool = { + "type": "function", + "function": { + "name": tool.name, + "description": tool.description or "", + "parameters": tool.inputSchema + or { + "type": "object", + "properties": {}, + }, + }, + } + openai_tools.append(openai_tool) + return openai_tools + + +def _convert_mcp_tool_choice_to_openai( + tool_choice: Optional["ToolChoice"], +) -> Optional[Union[str, Dict[str, Any]]]: + """ + Convert MCP ToolChoice to OpenAI tool_choice format. + MCP: {mode: "auto"} | {mode: "required"} | {mode: "none"} + OpenAI: "auto" | "required" | "none" + """ + if not tool_choice: + return None + mode = getattr(tool_choice, "mode", "auto") + if mode == "auto": + return "auto" + elif mode == "required": + return "required" + elif mode == "none": + return "none" + return "auto" + + +def _convert_openai_response_to_mcp_result( + response: Any, + model_name: str, +) -> Union["CreateMessageResult", "CreateMessageResultWithTools", "ErrorData"]: + """ + Convert a litellm completion response to MCP CreateMessageResult. + Args: + response: The litellm ModelResponse. + model_name: The model that was used. + Returns: + MCP CreateMessageResult or CreateMessageResultWithTools. + """ + if not response.choices: + verbose_logger.warning( + "MCP sampling: LLM returned empty choices list for model=%s " + "(possible content filter or provider error)", + model_name, + ) + return ErrorData( + code=-1, + message=( + f"LLM returned no choices for model '{model_name}'. " + "This may indicate content filtering or a provider-side error." + ), + ) + choice = response.choices[0] + message = choice.message + # Determine stop reason + finish_reason = getattr(choice, "finish_reason", "stop") + if finish_reason == "tool_calls": + stop_reason = "toolUse" + elif finish_reason == "length": + stop_reason = "maxTokens" + else: + stop_reason = "endTurn" + actual_model = getattr(response, "model", model_name) or model_name + # Check if response has tool calls + tool_calls = getattr(message, "tool_calls", None) + if tool_calls: + # Build ToolUseContent items + content_parts: "List[Any]" = [] + # Include text content if present + if message.content: + content_parts.append(TextContent(type="text", text=message.content)) + # Convert tool calls to MCP ToolUseContent + for tc in tool_calls: + import json + + tool_input = tc.function.arguments + if isinstance(tool_input, str): + try: + tool_input = json.loads(tool_input) + except (json.JSONDecodeError, TypeError): + tool_input = {"raw": tool_input} + content_parts.append( + ToolUseContent( + type="tool_use", + id=tc.id, + name=tc.function.name, + input=tool_input, + ) + ) + return CreateMessageResultWithTools( + role="assistant", + content=content_parts, + model=actual_model, + stopReason=stop_reason, + ) + # Simple text response + text = message.content or "" + return CreateMessageResult( + role="assistant", + content=TextContent(type="text", text=text), + model=actual_model, + stopReason=stop_reason, + ) + + +async def _check_model_access( # noqa: PLR0915 + model: str, user_api_key_auth: Any +) -> Optional["ErrorData"]: + """Enforce model-permission checks for MCP sampling requests. + + Runs the same authorization checks as ``/chat/completions``: + key-level, team-level, per-member, user-level, and project-level + model restrictions. The model name comes from the upstream MCP + server (untrusted input). + + Returns None if authorized, or an ErrorData describing the denial. + """ + if user_api_key_auth is None: + return None + + _api_key = getattr(user_api_key_auth, "api_key", None) + _token = getattr(user_api_key_auth, "token", None) + _user_role = getattr(user_api_key_auth, "user_role", None) + + _has_real_credential = bool(_api_key) or bool(_token) + _is_admin = ( + _user_role in ("proxy_admin", "proxy_admin_viewer") if _user_role else False + ) + + if not _has_real_credential and not _is_admin: + verbose_logger.warning( + "MCP sampling: denying model access for model=%s — " + "auth context has no real LiteLLM credential (possible " + "OAuth passthrough placeholder). api_key=%s, token=%s, role=%s", + model, + bool(_api_key), + bool(_token), + _user_role, + ) + return ErrorData( + code=-1, + message=( + "Model access denied: sampling requires a valid LiteLLM " + "API key or admin credential. OAuth-only sessions cannot " + "trigger proxy model calls without explicit authorization." + ), + ) + + try: + import litellm + from litellm.proxy.auth.auth_checks import ( + can_key_call_model, + can_team_access_model, + can_user_call_model, + can_project_access_model, + _check_team_member_model_access, + get_team_object, + get_user_object, + get_project_object, + ) + + try: + from litellm.proxy.proxy_server import llm_router as _llm_router + except ImportError: + _llm_router = None + + await can_key_call_model( + model=model, + llm_model_list=getattr(litellm, "model_list", None), + valid_token=user_api_key_auth, + llm_router=_llm_router, + ) + + _team_id = getattr(user_api_key_auth, "team_id", None) + _user_id = getattr(user_api_key_auth, "user_id", None) + _project_id = getattr(user_api_key_auth, "project_id", None) + + try: + from litellm.proxy.proxy_server import ( + prisma_client as _prisma_client, + user_api_key_cache as _user_api_key_cache, + proxy_logging_obj as _proxy_logging_obj, + ) + except ImportError: + _prisma_client = None + _user_api_key_cache = None # type: ignore[assignment] + _proxy_logging_obj = None # type: ignore[assignment] + + if _team_id and _prisma_client and _user_api_key_cache: + try: + team_obj = await get_team_object( + team_id=_team_id, + prisma_client=_prisma_client, + user_api_key_cache=_user_api_key_cache, + proxy_logging_obj=_proxy_logging_obj, + ) + except Exception: + team_obj = None + + if team_obj: + await can_team_access_model( + model=model, + team_object=team_obj, + llm_router=_llm_router, + team_model_aliases=getattr( + user_api_key_auth, "team_model_aliases", None + ), + ) + if _user_id and _proxy_logging_obj: + await _check_team_member_model_access( + model=model, + team_object=team_obj, + valid_token=user_api_key_auth, + llm_router=_llm_router, + prisma_client=_prisma_client, + user_api_key_cache=_user_api_key_cache, + proxy_logging_obj=_proxy_logging_obj, + ) + elif not _team_id and _user_id and _prisma_client and _user_api_key_cache: + try: + user_obj = await get_user_object( + user_id=_user_id, + prisma_client=_prisma_client, + user_api_key_cache=_user_api_key_cache, + user_id_upsert=False, + proxy_logging_obj=_proxy_logging_obj, + ) + except Exception: + user_obj = None + + if user_obj: + await can_user_call_model( + model=model, + llm_router=_llm_router, + user_object=user_obj, + ) + + if _project_id and _prisma_client and _user_api_key_cache: + try: + project_obj = await get_project_object( + project_id=_project_id, + prisma_client=_prisma_client, + user_api_key_cache=_user_api_key_cache, + proxy_logging_obj=_proxy_logging_obj, + ) + except Exception: + project_obj = None + + if project_obj: + can_project_access_model( + model=model, + project_object=project_obj, + llm_router=_llm_router, + ) + + verbose_logger.debug( + "MCP sampling: model access check passed for model=%s", + model, + ) + return None + except Exception as access_err: + verbose_logger.warning( + "MCP sampling: model access denied for model=%s: %s", + model, + access_err, + ) + return ErrorData( + code=-1, + message=( + f"Model access denied: the API key is not authorized " + f"to use model '{model}'. {access_err}" + ), + ) + + +async def _run_budget_checks( + model: str, + user_api_key_auth: Any, + raw_headers: Optional[Dict[str, str]] = None, + client_ip: Optional[str] = None, +) -> Optional["ErrorData"]: + """Enforce key/team/user/org/global budget checks for sampling requests. + + Runs the same ``common_checks`` path that ``/chat/completions`` uses, + so sampling cannot bypass budget limits. + + Returns None if all checks pass, or an ErrorData describing the denial. + """ + try: + from litellm.proxy.auth.auth_checks import common_checks + from litellm.proxy.proxy_server import ( + general_settings, + llm_router as _llm_router, + prisma_client as _prisma_client, + proxy_logging_obj as _proxy_logging_obj, + user_api_key_cache as _user_api_key_cache, + ) + from litellm.proxy.auth.auth_checks import ( + get_team_object, + get_user_object, + ) + import litellm + except ImportError as import_err: + verbose_logger.warning( + "MCP sampling: budget check imports unavailable: %s", import_err + ) + return None # Can't enforce budgets without the modules + + _team_id = getattr(user_api_key_auth, "team_id", None) + _user_id = getattr(user_api_key_auth, "user_id", None) + + team_obj = None + if _team_id and _prisma_client and _user_api_key_cache: + try: + team_obj = await get_team_object( + team_id=_team_id, + prisma_client=_prisma_client, + user_api_key_cache=_user_api_key_cache, + proxy_logging_obj=_proxy_logging_obj, + ) + except Exception: + pass + + user_obj = None + if _user_id and _prisma_client and _user_api_key_cache: + try: + user_obj = await get_user_object( + user_id=_user_id, + prisma_client=_prisma_client, + user_api_key_cache=_user_api_key_cache, + user_id_upsert=False, + proxy_logging_obj=_proxy_logging_obj, + ) + except Exception: + pass + + dummy_request = _build_sampling_request( + raw_headers=raw_headers, + client_ip=client_ip, + ) + + # Enforce virtual-key route restrictions: a key limited to MCP routes + # must not be able to trigger a /chat/completions call via sampling. + # This mirrors the RouteChecks.should_call_route gate that runs in + # user_api_key_auth before common_checks for regular requests. + try: + from litellm.proxy.auth.route_checks import RouteChecks + + RouteChecks.should_call_route( + route="/chat/completions", + valid_token=user_api_key_auth, + request=dummy_request, + ) + except HTTPException as route_err: + verbose_logger.warning( + "MCP sampling: route check denied /chat/completions for key: %s", + route_err.detail, + ) + return ErrorData( + code=-1, + message=f"Sampling denied: virtual key is not allowed to call /chat/completions. {route_err.detail}", + ) + + global_proxy_spend = getattr(litellm, "_global_proxy_spend", None) + + # Build request body and merge x-litellm-tags from MCP headers BEFORE + # common_checks runs. _tag_max_budget_check inside common_checks only + # inspects request_body; without this pre-merge, header-supplied tags + # bypass per-tag budget enforcement (mirroring the regular auth path). + request_body: Dict[str, Any] = {"model": model} + try: + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + + LiteLLMProxyRequestSetup.apply_client_tag_policy_pre_auth( + request=dummy_request, + request_data=request_body, + user_api_key_dict=user_api_key_auth, + ) + except Exception: + # Non-fatal: tag merge is defense-in-depth; don't block sampling + # if the merge utility is unavailable or fails. + pass + + try: + await common_checks( + request_body=request_body, + team_object=team_obj, + user_object=user_obj, + end_user_object=None, + global_proxy_spend=global_proxy_spend, + general_settings=general_settings or {}, + route="/chat/completions", + llm_router=_llm_router, + proxy_logging_obj=typing.cast("ProxyLogging", _proxy_logging_obj), + valid_token=user_api_key_auth, + request=dummy_request, + ) + except Exception as budget_err: + verbose_logger.warning( + "MCP sampling: budget check failed for model=%s: %s", + model, + budget_err, + ) + return ErrorData( + code=-1, + message=f"Sampling denied: {budget_err}", + ) + + verbose_logger.debug("MCP sampling: budget checks passed for model=%s", model) + return None + + +def _build_sampling_request( + raw_headers: Optional[Dict[str, str]] = None, + client_ip: Optional[str] = None, +) -> Any: + """Build a synthetic FastAPI Request for sampling sub-calls. + + Converts the original MCP connection's HTTP headers into ASGI + scope format so that ``add_litellm_data_to_request`` can apply + header-dependent guardrails, tag-based routing, trace correlation, + and ``forward_llm_provider_auth_headers``. + + Key fields populated: + - **headers**: All original HTTP headers are forwarded (except + hop-by-hop: content-length, transfer-encoding). This ensures + ``traceparent``, ``authorization``, ``user-agent``, and + ``x-litellm-api-key`` are visible to pre-call utils. + - **client**: The ASGI ``(host, port)`` tuple so that + ``request.client.host`` returns the real client IP for + IP-based routing and guardrails. + - **server**: Derived from the running proxy's ``server_host`` + / ``server_port`` when available, avoiding the misleading + ``127.0.0.1:0`` placeholder. + - **x-forwarded-for**: Injected from ``client_ip`` if the + original headers don't already carry it, as a fallback for + IP attribution. + """ + from fastapi import Request + + # --- Build ASGI headers --- + _scope_headers: list = [(b"content-type", b"application/json")] + # Hop-by-hop headers that must NOT be forwarded into the + # synthetic request (they describe the original HTTP framing, + # not the logical request). + _HOP_BY_HOP = frozenset( + { + "content-length", + "transfer-encoding", + "connection", + "keep-alive", + "upgrade", + "te", + "trailer", + } + ) + if raw_headers: + for hdr_name, hdr_value in raw_headers.items(): + _key = hdr_name.lower() + # Skip content-type (already set), x-forwarded-for (use resolved + # client_ip instead to prevent spoofing), and hop-by-hop headers + if _key in {"content-type", "x-forwarded-for"} or _key in _HOP_BY_HOP: + continue + _scope_headers.append( + ( + _key.encode("latin-1", errors="replace"), + hdr_value.encode("utf-8"), + ) + ) + + # Inject x-forwarded-for from captured client_ip if the + # original headers don't already carry it + if client_ip and not any(h[0] == b"x-forwarded-for" for h in _scope_headers): + _scope_headers.append((b"x-forwarded-for", client_ip.encode("utf-8"))) + + # --- Derive server (host, port) from the running proxy --- + _server_host = "127.0.0.1" + _server_port = 4000 # LiteLLM default + try: + import litellm.proxy.proxy_server as proxy_server + + _proxy_host = getattr(proxy_server, "server_host", None) + _proxy_port = getattr(proxy_server, "server_port", None) + + if _proxy_host: + _server_host = str(_proxy_host) + if _proxy_port: + _server_port = int(_proxy_port) + except (ImportError, AttributeError, TypeError, ValueError): + pass + + # --- Build ASGI client tuple for request.client.host --- + _client_tuple = None + if client_ip: + _client_tuple = (client_ip, 0) + + scope: Dict[str, Any] = { + "type": "http", + "method": "POST", + "path": "/mcp/sampling/createMessage", + "scheme": "http", + "server": (_server_host, _server_port), + "query_string": b"", + "root_path": "", + "headers": _scope_headers, + } + if _client_tuple is not None: + scope["client"] = _client_tuple + + return Request(scope=scope) + + +async def _build_completion_kwargs( + params: "CreateMessageRequestParams", + model: str, + user_api_key_auth: Any, + raw_headers: Optional[Dict[str, str]], + client_ip: Optional[str], +) -> Dict[str, Any]: + openai_messages = _convert_mcp_messages_to_openai( + messages=params.messages, + system_prompt=params.systemPrompt, + ) + completion_kwargs: Dict[str, Any] = { + "model": model, + "messages": openai_messages, + "max_tokens": params.maxTokens, + } + if params.temperature is not None: + completion_kwargs["temperature"] = params.temperature + if params.stopSequences: + completion_kwargs["stop"] = params.stopSequences + openai_tools = _convert_mcp_tools_to_openai(params.tools) + if openai_tools: + completion_kwargs["tools"] = openai_tools + openai_tool_choice = _convert_mcp_tool_choice_to_openai(params.toolChoice) + if openai_tool_choice is not None: + completion_kwargs["tool_choice"] = openai_tool_choice + completion_kwargs["metadata"] = {} + if params.metadata: + completion_kwargs["metadata"]["mcp_metadata"] = params.metadata + + from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request + from litellm.proxy.proxy_server import proxy_config + + completion_kwargs["user"] = getattr(user_api_key_auth, "user_id", None) + _dummy_request = _build_sampling_request( + raw_headers=raw_headers, client_ip=client_ip + ) + completion_kwargs = await add_litellm_data_to_request( + data=completion_kwargs, + request=_dummy_request, + user_api_key_dict=user_api_key_auth, + proxy_config=proxy_config, + ) + return completion_kwargs + + +async def _run_guardrails_and_call_llm( + completion_kwargs: Dict[str, Any], + user_api_key_auth: Any, +) -> Any: + try: + from litellm.proxy.proxy_server import proxy_logging_obj as _plo + + if _plo is not None: + completion_kwargs = await typing.cast("ProxyLogging", _plo).pre_call_hook( + user_api_key_dict=user_api_key_auth, + data=completion_kwargs, + call_type="acompletion", + ) + except ImportError: + pass + except Exception as guardrail_err: + verbose_logger.warning( + "MCP sampling: pre-call guardrail rejected request: %s", + guardrail_err, + ) + raise + + import litellm + + try: + from litellm.proxy.proxy_server import llm_router + + if llm_router is not None: + return await llm_router.acompletion(**completion_kwargs) + return await litellm.acompletion(**completion_kwargs) + except ImportError: + return await litellm.acompletion(**completion_kwargs) + + +async def handle_sampling_create_message( + context: Any, + params: "CreateMessageRequestParams", + default_model: Optional[str] = None, + user_api_key_auth: Optional[Any] = None, + raw_headers: Optional[Dict[str, str]] = None, + client_ip: Optional[str] = None, +) -> Union["CreateMessageResult", "CreateMessageResultWithTools", "ErrorData"]: + """ + Handle an MCP sampling/createMessage request by routing through LiteLLM. + This is the main entry point called by the MCP client session when an + upstream MCP server requests LLM inference. + Args: + context: MCP RequestContext (contains session info). + params: The CreateMessageRequestParams from the MCP server. + default_model: Default model to use if no preferences match. + user_api_key_auth: Auth context for the requesting user. + raw_headers: Original HTTP headers from the MCP connection. + Forwarded into the internal acompletion call so that + header-dependent guardrails, IP-routing, trace-id + correlation, and forward_llm_provider_auth_headers + work correctly for sampling sub-calls. + client_ip: Original client IP address for IP-based guardrails. + Returns: + CreateMessageResult with the LLM's response, or ErrorData on failure. + """ + if not MCP_SAMPLING_AVAILABLE: + return ErrorData( + code=-1, + message="MCP sampling is not available (mcp package not installed)", + ) + + if user_api_key_auth is None: + return ErrorData( + code=-1, + message=( + "Sampling requires an authenticated user context. " + "Internal or unauthenticated sessions cannot trigger " + "upstream-initiated model calls." + ), + ) + + try: + model = _resolve_model_from_preferences( + model_preferences=params.modelPreferences, + default_model=default_model, + ) + verbose_logger.info( + "MCP sampling: resolved model=%s from preferences=%s", + model, + params.modelPreferences, + ) + + access_denial = await _check_model_access(model, user_api_key_auth) + if access_denial is not None: + return access_denial + + budget_denial = await _run_budget_checks( + model=model, + user_api_key_auth=user_api_key_auth, + raw_headers=raw_headers, + client_ip=client_ip, + ) + if budget_denial is not None: + return budget_denial + + completion_kwargs = await _build_completion_kwargs( + params=params, + model=model, + user_api_key_auth=user_api_key_auth, + raw_headers=raw_headers, + client_ip=client_ip, + ) + + openai_messages = completion_kwargs["messages"] + openai_tools = completion_kwargs.get("tools") + verbose_logger.debug( + "MCP sampling: calling litellm.acompletion with model=%s, num_messages=%d, has_tools=%s", + model, + len(openai_messages), + bool(openai_tools), + ) + + response = await _run_guardrails_and_call_llm( + completion_kwargs=completion_kwargs, + user_api_key_auth=user_api_key_auth, + ) + + result = _convert_openai_response_to_mcp_result( + response=response, model_name=model + ) + verbose_logger.info( + "MCP sampling: completed successfully, model=%s, stopReason=%s", + getattr(result, "model", "unknown"), + getattr(result, "stopReason", "unknown"), + ) + return result + except Exception as e: + from litellm.exceptions import ( + AuthenticationError, + BudgetExceededError, + ContextWindowExceededError, + PermissionDeniedError, + RateLimitError, + ServiceUnavailableError, + ) + + from litellm.proxy._types import ProxyException + + if isinstance( + e, + ( + HTTPException, + BudgetExceededError, + RateLimitError, + AuthenticationError, + PermissionDeniedError, + ContextWindowExceededError, + ServiceUnavailableError, + ProxyException, + ), + ): + raise + + verbose_logger.exception("MCP sampling handler failed: %s", e) + return ErrorData( + code=-1, + message=f"Sampling failed: {str(e)}", + ) diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py index 6e33a105ec8..df6cb22fda1 100644 --- a/litellm/proxy/_experimental/mcp_server/server.py +++ b/litellm/proxy/_experimental/mcp_server/server.py @@ -6,6 +6,7 @@ LiteLLM MCP Server Routes import asyncio import contextlib +import contextvars import hashlib import json import time @@ -125,6 +126,18 @@ try: GetPromptResult, ResourceTemplate, TextResourceContents, + Tool, + ) + from mcp.server.session import ServerSession as _McpServerSession + import weakref + + # Robust auth lookup keyed by session_object. + _session_obj_auth_storage: ( + "weakref.WeakKeyDictionary[Any, MCPAuthenticatedUser]" + ) = weakref.WeakKeyDictionary() + + active_mcp_session_var: contextvars.ContextVar[Optional[_McpServerSession]] = ( + contextvars.ContextVar("active_mcp_session", default=None) ) except ImportError as e: verbose_logger.debug(f"MCP module not found: {e}") @@ -160,6 +173,60 @@ def _mcp_session_id_from_headers( return None +def _jsonrpc_text_has_top_level_method(text: str) -> bool: + """Whether a (possibly truncated) JSON-RPC envelope has a ``method`` key at + the root object's top level. + + Used to tell a request/notification (carries ``method``) apart from a + response (carries ``result``/``error`` and no top-level ``method``). A + response payload can itself nest a ``method`` field, so only keys at the + root object's depth are inspected rather than searching the whole string. + Returns ``True`` only when a top-level ``method`` key is positively found; + truncation that hides it yields ``False``. + """ + depth = 0 + in_string = False + escaped = False + in_object: List[bool] = [] + reading_key = False + expect_key = False + key_chars: List[str] = [] + for ch in text: + if in_string: + if escaped: + escaped = False + elif ch == "\\": + escaped = True + elif ch == '"': + in_string = False + if reading_key and depth == 1 and "".join(key_chars) == "method": + return True + elif reading_key: + key_chars.append(ch) + continue + if ch == '"': + in_string = True + reading_key = expect_key and depth >= 1 and in_object[-1] + key_chars = [] + expect_key = False + elif ch == "{" or ch == "[": + depth += 1 + in_object.append(ch == "{") + expect_key = ch == "{" + elif ch == "}" or ch == "]": + if in_object: + in_object.pop() + depth -= 1 + if depth <= 0: + break + expect_key = False + elif ch == ",": + expect_key = bool(in_object) and in_object[-1] + elif ch == ":": + expect_key = False + return False + + if MCP_AVAILABLE: from mcp.server import Server from mcp.server.lowlevel.server import NotificationOptions @@ -483,10 +550,18 @@ if MCP_AVAILABLE: ######################################################## @server.list_tools() - async def list_tools() -> List[MCPTool]: + async def handle_list_tools() -> List[Tool]: """ - List all available tools + List all available tools. + Also captures the active session for propagation to callbacks. """ + from mcp.server.lowlevel.server import request_ctx + + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) + try: # Get user authentication from context variable ( @@ -497,7 +572,7 @@ if MCP_AVAILABLE: oauth2_headers, raw_headers, _client_ip, - ) = get_auth_context() + ) = await get_or_extract_auth_context() verbose_logger.debug( f"MCP list_tools - User API Key Auth from context: {user_api_key_auth}" ) @@ -528,152 +603,178 @@ if MCP_AVAILABLE: # Return empty list instead of failing completely # This prevents the HTTP stream from failing and allows the client to get a response return [] + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) @server.call_tool() - async def mcp_server_tool_call( - name: str, arguments: Optional[Dict[str, Any]] + async def mcp_server_tool_call( # noqa: PLR0915 + name: str, arguments: Dict[str, Any] | None ) -> CallToolResult: """ Call a specific tool with the provided arguments - Args: name (str): Name of the tool to call arguments (Dict[str, Any] | None): Arguments to pass to the tool - Returns: List[Union[MCPTextContent, MCPImageContent, MCPEmbeddedResource]]: Tool execution results - Raises: HTTPException: If tool not found or arguments missing """ from fastapi import Request - from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request from litellm.proxy.proxy_server import proxy_config + from mcp.types import CallToolResult + from mcp.server.lowlevel.server import request_ctx - # Validate arguments - ( - user_api_key_auth, - mcp_auth_header, - mcp_servers, - mcp_server_auth_headers, - oauth2_headers, - raw_headers, - _client_ip, - ) = get_auth_context() + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) - verbose_logger.debug( - f"MCP mcp_server_tool_call - User API Key Auth from context: {user_api_key_auth}" - ) - host_progress_callback = None try: - host_ctx = server.request_context - if host_ctx and hasattr(host_ctx, "meta") and host_ctx.meta: - host_token = getattr(host_ctx.meta, "progressToken", None) - if host_token and hasattr(host_ctx, "session") and host_ctx.session: - host_session = host_ctx.session - - async def forward_progress(progress: float, total: Optional[float]): - """Forward progress notifications from external MCP to Host""" - try: - await host_session.send_progress_notification( - progress_token=host_token, - progress=progress, - total=total, - ) - verbose_logger.debug( - f"Forwarded progress {progress}/{total} to Host" - ) - except Exception as e: - verbose_logger.error( - f"Failed to forward progress to Host: {e}" - ) - - host_progress_callback = forward_progress - verbose_logger.debug( - f"Host progressToken captured: {host_token[:8]}..." - ) - except Exception as e: - verbose_logger.warning(f"Could not capture host progress context: {e}") - try: - # Create a body date for logging - body_data = {"name": name, "arguments": arguments} - # Set trace/session id from raw_headers so spend logs and logging_obj stay consistent (same as A2A) - chain_id = get_chain_id_from_headers(raw_headers) - if chain_id: - body_data["litellm_trace_id"] = chain_id - body_data["litellm_session_id"] = chain_id - - request = Request( - scope={ - "type": "http", - "method": "POST", - "path": "/mcp/tools/call", - "headers": [(b"content-type", b"application/json")], - } + # Validate arguments + ( + user_api_key_auth, + mcp_auth_header, + mcp_servers, + mcp_server_auth_headers, + oauth2_headers, + raw_headers, + _client_ip, + ) = await get_or_extract_auth_context() + verbose_logger.debug( + f"MCP mcp_server_tool_call - user_api_key_auth={user_api_key_auth}, user_role={getattr(user_api_key_auth, 'user_role', 'N/A')}" ) - if user_api_key_auth is not None: - data = await add_litellm_data_to_request( - data=body_data, - request=request, - user_api_key_dict=user_api_key_auth, - proxy_config=proxy_config, + + verbose_logger.debug( + f"MCP mcp_server_tool_call - User API Key Auth from context: {user_api_key_auth}" + ) + host_progress_callback = None + try: + host_ctx = server.request_context + if host_ctx and hasattr(host_ctx, "meta") and host_ctx.meta: + host_token = getattr(host_ctx.meta, "progressToken", None) + if host_token and hasattr(host_ctx, "session") and host_ctx.session: + host_session = host_ctx.session + + async def forward_progress( + progress: float, total: Optional[float] + ): + """Forward progress notifications from external MCP to Host""" + try: + await host_session.send_progress_notification( + progress_token=host_token, + progress=progress, + total=total, + ) + verbose_logger.debug( + f"Forwarded progress {progress}/{total} to Host" + ) + except Exception as e: + verbose_logger.error( + f"Failed to forward progress to Host: {e}" + ) + + host_progress_callback = forward_progress + verbose_logger.debug( + f"Host progressToken captured: {host_token[:8]}..." + ) + except Exception as e: + verbose_logger.warning(f"Could not capture host progress context: {e}") + try: + # Create a body date for logging + body_data = {"name": name, "arguments": arguments} + # Set trace/session id from raw_headers so spend logs and logging_obj stay consistent (same as A2A) + chain_id = get_chain_id_from_headers(raw_headers) + if chain_id: + body_data["litellm_trace_id"] = chain_id + body_data["litellm_session_id"] = chain_id + + request = Request( + scope={ + "type": "http", + "method": "POST", + "path": "/mcp/tools/call", + "headers": [(b"content-type", b"application/json")], + } ) - else: - data = body_data - - response = await call_mcp_tool( - user_api_key_auth=user_api_key_auth, - mcp_auth_header=mcp_auth_header, - mcp_servers=mcp_servers, - mcp_server_auth_headers=mcp_server_auth_headers, - oauth2_headers=oauth2_headers, - raw_headers=raw_headers, - host_progress_callback=host_progress_callback, - **data, # for logging - ) - except BlockedPiiEntityError as e: - verbose_logger.error(f"BlockedPiiEntityError in MCP tool call: {str(e)}") - return CallToolResult( - content=[ - TextContent( - text=f"Error: Blocked PII entity detected - {str(e)}", - type="text", + if user_api_key_auth is not None: + data = await add_litellm_data_to_request( + data=body_data, + request=request, + user_api_key_dict=user_api_key_auth, + proxy_config=proxy_config, ) - ], - isError=True, - ) - except GuardrailRaisedException as e: - verbose_logger.error(f"GuardrailRaisedException in MCP tool call: {str(e)}") - return CallToolResult( - content=[ - TextContent( - text=f"Error: Guardrail violation - {str(e)}", type="text" - ) - ], - isError=True, - ) - except HTTPException as e: - verbose_logger.error(f"HTTPException in MCP tool call: {str(e)}") - return CallToolResult( - content=[TextContent(text=f"Error: {str(e.detail)}", type="text")], - isError=True, - ) - except Exception as e: - verbose_logger.exception(f"MCP mcp_server_tool_call - error: {e}") - return CallToolResult( - content=[TextContent(text=f"Error: {str(e)}", type="text")], - isError=True, - ) + else: + data = body_data - return response + response = await call_mcp_tool( + user_api_key_auth=user_api_key_auth, + mcp_auth_header=mcp_auth_header, + mcp_servers=mcp_servers, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + host_progress_callback=host_progress_callback, + **data, # for logging + ) + except BlockedPiiEntityError as e: + verbose_logger.error( + f"BlockedPiiEntityError in MCP tool call: {str(e)}" + ) + return CallToolResult( + content=[ + TextContent( + text=f"Error: Blocked PII entity detected - {str(e)}", + type="text", + ) + ], + isError=True, + ) + except GuardrailRaisedException as e: + verbose_logger.error( + f"GuardrailRaisedException in MCP tool call: {str(e)}" + ) + return CallToolResult( + content=[ + TextContent( + text=f"Error: Guardrail violation - {str(e)}", type="text" + ) + ], + isError=True, + ) + except HTTPException as e: + verbose_logger.error(f"HTTPException in MCP tool call: {str(e)}") + return CallToolResult( + content=[TextContent(text=f"Error: {str(e.detail)}", type="text")], + isError=True, + ) + except Exception as e: + verbose_logger.exception(f"MCP mcp_server_tool_call - error: {e}") + return CallToolResult( + content=[TextContent(text=f"Error: {str(e)}", type="text")], + isError=True, + ) + + return response + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) @server.list_prompts() async def list_prompts() -> List[Prompt]: """ List all available prompts """ + from mcp.server.lowlevel.server import request_ctx + + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) + try: # Get user authentication from context variable ( @@ -684,7 +785,7 @@ if MCP_AVAILABLE: oauth2_headers, raw_headers, _client_ip, - ) = get_auth_context() + ) = await get_or_extract_auth_context() verbose_logger.debug( f"MCP list_prompts - User API Key Auth from context: {user_api_key_auth}" ) @@ -713,6 +814,9 @@ if MCP_AVAILABLE: # Return empty list instead of failing completely # This prevents the HTTP stream from failing and allows the client to get a response return [] + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) @server.get_prompt() async def get_prompt( @@ -730,33 +834,13 @@ if MCP_AVAILABLE: """ # Validate arguments - ( - user_api_key_auth, - mcp_auth_header, - mcp_servers, - mcp_server_auth_headers, - oauth2_headers, - raw_headers, - _client_ip, - ) = get_auth_context() + from mcp.server.lowlevel.server import request_ctx - verbose_logger.debug( - f"MCP mcp_server_tool_call - User API Key Auth from context: {user_api_key_auth}" - ) - return await mcp_get_prompt( - name=name, - arguments=arguments, - user_api_key_auth=user_api_key_auth, - mcp_auth_header=mcp_auth_header, - mcp_servers=mcp_servers, - mcp_server_auth_headers=mcp_server_auth_headers, - oauth2_headers=oauth2_headers, - raw_headers=raw_headers, - ) + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) - @server.list_resources() - async def list_resources() -> List[Resource]: - """List all available resources.""" try: ( user_api_key_auth, @@ -766,7 +850,45 @@ if MCP_AVAILABLE: oauth2_headers, raw_headers, _client_ip, - ) = get_auth_context() + ) = await get_or_extract_auth_context() + + verbose_logger.debug( + f"MCP mcp_server_tool_call - User API Key Auth from context: {user_api_key_auth}" + ) + return await mcp_get_prompt( + name=name, + arguments=arguments, + user_api_key_auth=user_api_key_auth, + mcp_auth_header=mcp_auth_header, + mcp_servers=mcp_servers, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + ) + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) + + @server.list_resources() + async def list_resources() -> List[Resource]: + """List all available resources.""" + from mcp.server.lowlevel.server import request_ctx + + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) + + try: + ( + user_api_key_auth, + mcp_auth_header, + mcp_servers, + mcp_server_auth_headers, + oauth2_headers, + raw_headers, + _client_ip, + ) = await get_or_extract_auth_context() verbose_logger.debug( f"MCP list_resources - User API Key Auth from context: {user_api_key_auth}" ) @@ -792,10 +914,20 @@ if MCP_AVAILABLE: except Exception as e: verbose_logger.exception(f"Error in list_resources endpoint: {str(e)}") return [] + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) @server.list_resource_templates() async def list_resource_templates() -> List[ResourceTemplate]: """List all available resource templates.""" + from mcp.server.lowlevel.server import request_ctx + + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) + try: ( user_api_key_auth, @@ -805,7 +937,7 @@ if MCP_AVAILABLE: oauth2_headers, raw_headers, _client_ip, - ) = get_auth_context() + ) = await get_or_extract_auth_context() verbose_logger.debug( f"MCP list_resource_templates - User API Key Auth from context: {user_api_key_auth}" ) @@ -825,8 +957,7 @@ if MCP_AVAILABLE: raw_headers=raw_headers, ) verbose_logger.info( - "MCP list_resource_templates - Successfully returned " - f"{len(resource_templates)} resource templates" + f"MCP list_resource_templates - Successfully returned {len(resource_templates)} resource templates" ) return resource_templates except Exception as e: @@ -834,30 +965,44 @@ if MCP_AVAILABLE: f"Error in list_resource_templates endpoint: {str(e)}" ) return [] + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) @server.read_resource() async def read_resource(url: AnyUrl) -> list[ReadResourceContents]: - ( - user_api_key_auth, - mcp_auth_header, - mcp_servers, - mcp_server_auth_headers, - oauth2_headers, - raw_headers, - _client_ip, - ) = get_auth_context() + from mcp.server.lowlevel.server import request_ctx - read_resource_result = await mcp_read_resource( - url=url, - user_api_key_auth=user_api_key_auth, - mcp_auth_header=mcp_auth_header, - mcp_servers=mcp_servers, - mcp_server_auth_headers=mcp_server_auth_headers, - oauth2_headers=oauth2_headers, - raw_headers=raw_headers, - ) + req_ctx = request_ctx.get(None) + _session_reset_token = None + if req_ctx: + _session_reset_token = active_mcp_session_var.set(req_ctx.session) - return _normalize_resource_contents(read_resource_result.contents) + try: + ( + user_api_key_auth, + mcp_auth_header, + mcp_servers, + mcp_server_auth_headers, + oauth2_headers, + raw_headers, + _client_ip, + ) = await get_or_extract_auth_context() + + read_resource_result = await mcp_read_resource( + url=url, + user_api_key_auth=user_api_key_auth, + mcp_auth_header=mcp_auth_header, + mcp_servers=mcp_servers, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + ) + + return _normalize_resource_contents(read_resource_result.contents) + finally: + if _session_reset_token is not None: + active_mcp_session_var.reset(_session_reset_token) ######################################################## ############ End of MCP Server Routes ################## @@ -1180,8 +1325,7 @@ if MCP_AVAILABLE: cached_token = await mcp_per_user_token_cache.get(user_id, server_id) if cached_token is not None: verbose_logger.debug( - "_get_user_oauth_extra_headers_from_db: Redis hit for " - "user=%s server=%s", + "_get_user_oauth_extra_headers_from_db: Redis hit for user=%s server=%s", user_id, server_id, ) @@ -1207,8 +1351,7 @@ if MCP_AVAILABLE: if is_oauth_credential_expired(cred): verbose_logger.debug( - "_get_user_oauth_extra_headers_from_db: token expired for " - "user=%s server=%s — attempting refresh", + "_get_user_oauth_extra_headers_from_db: token expired for user=%s server=%s — attempting refresh", user_id, server_id, ) @@ -1230,8 +1373,7 @@ if MCP_AVAILABLE: ) except Exception as refresh_exc: verbose_logger.warning( - "_get_user_oauth_extra_headers_from_db: refresh failed " - "for user=%s server=%s: %s", + "_get_user_oauth_extra_headers_from_db: refresh failed for user=%s server=%s: %s", user_id, server_id, refresh_exc, @@ -1275,8 +1417,7 @@ if MCP_AVAILABLE: return {"Authorization": f"Bearer {access_token}"} except Exception as e: verbose_logger.warning( - "_get_user_oauth_extra_headers_from_db: failed to retrieve credential for " - "user=%s server=%s: %s", + "_get_user_oauth_extra_headers_from_db: failed to retrieve credential for user=%s server=%s: %s", user_id, server_id, e, @@ -2485,7 +2626,7 @@ if MCP_AVAILABLE: arguments=arguments or {}, server_name=server_name or mcp_server.name, user_api_key_auth=user_api_key_auth, - proxy_logging_obj=proxy_logging_obj, + proxy_logging_obj=proxy_logging_obj, # type: ignore[arg-type] server=mcp_server, raw_headers=raw_headers, ) @@ -2744,8 +2885,7 @@ if MCP_AVAILABLE: raise HTTPException( status_code=400, detail=( - "Multiple MCP servers configured; read_resource currently " - "supports exactly one allowed server." + "Multiple MCP servers configured; read_resource currently supports exactly one allowed server." ), ) @@ -3124,8 +3264,7 @@ if MCP_AVAILABLE: return False except Exception: verbose_logger.debug( - "Unable to inspect active MCP sessions for '%s'. " - "Deferring to session manager.", + "Unable to inspect active MCP sessions for '%s'. Deferring to session manager.", _session_id, ) return False @@ -3136,8 +3275,7 @@ if MCP_AVAILABLE: if method == "DELETE": _remove_stateful_session_tracking(_session_id) verbose_logger.info( - "DELETE request for non-existent MCP session '%s'. " - "Returning success (idempotent DELETE).", + "DELETE request for non-existent MCP session '%s'. Returning success (idempotent DELETE).", _session_id, ) success_response = JSONResponse( @@ -3615,6 +3753,7 @@ if MCP_AVAILABLE: return session_id = _get_session_id_from_scope(scope) + body = b"" if scope.get("method") == "POST": consumed_messages, body = await _read_request_body_for_routing(receive) is_initialize = _is_initialize_request(body) @@ -3639,8 +3778,7 @@ if MCP_AVAILABLE: ) if not await _enforce_stateful_session_cap_for_owner(request_owner): verbose_logger.warning( - "Rejecting MCP initialize: caller already holds the maximum " - "number of active stateful sessions." + "Rejecting MCP initialize: caller already holds the maximum number of active stateful sessions." ) too_many_response = JSONResponse( status_code=429, @@ -3672,9 +3810,56 @@ if MCP_AVAILABLE: # POST/DELETE are the methods that actually mutate the shared # auth context, so serializing those is sufficient for the # clobbering race between concurrent JSON-RPC calls. - session_lock: Optional[asyncio.Lock] = None + # + # Also skip the lock for JSON-RPC *responses* (POSTs that carry + # a ``result`` or ``error`` but no ``method``). These are replies + # to server-initiated requests such as ``elicitation/create`` or + # ``sampling/createMessage``. The in-flight tool-call POST that + # triggered the server request already holds the session lock, so + # trying to acquire it again for the response POST would deadlock. + is_jsonrpc_response = False request_method = (scope.get("method") or "").upper() - if use_stateful and session_id and request_method in ("POST", "DELETE"): + if body and request_method == "POST": + try: + _peeked = json.loads(body) + if ( + isinstance(_peeked, dict) + and _peeked.get("jsonrpc") == "2.0" + and "id" in _peeked + and "method" not in _peeked + and ("result" in _peeked or "error" in _peeked) + ): + is_jsonrpc_response = True + verbose_logger.debug( + "MCP: detected JSON-RPC response POST (id=%s), skipping session lock to avoid deadlock", + _peeked.get("id"), + ) + except (json.JSONDecodeError, TypeError): + # Peek cap truncated the body, so it can't be fully parsed. + # Scan the top-level keys (depth-aware) instead of a flat + # substring search: a response's result payload may nest a + # "method" field, and misreading that would acquire the lock + # and deadlock the in-flight tool call awaiting this + # response. A false skip is harmless; a false acquire is not. + _body_str = body.decode("utf-8", errors="replace") + if ( + '"jsonrpc"' in _body_str + and ('"result"' in _body_str or '"error"' in _body_str) + and not _jsonrpc_text_has_top_level_method(_body_str) + ): + is_jsonrpc_response = True + verbose_logger.debug( + "MCP: detected truncated JSON-RPC response POST via " + "top-level key scan, skipping session lock to avoid deadlock" + ) + + session_lock: Optional[asyncio.Lock] = None + if ( + use_stateful + and session_id + and request_method in ("POST", "DELETE") + and not is_jsonrpc_response + ): session_lock = _stateful_session_locks.setdefault( session_id, asyncio.Lock() ) @@ -4099,6 +4284,119 @@ if MCP_AVAILABLE: ) return None, None, None, None, None, None, None + def _get_current_session(): + try: + from mcp.server.lowlevel.server import request_ctx + + return request_ctx.get().session + except (LookupError, ImportError): + return None + + def _cache_auth_context_lazily(): + session = _get_current_session() + if session is None: + return + try: + if session in _session_obj_auth_storage: + return + except TypeError: + verbose_logger.debug( + "_cache_auth_context_lazily: session object is unhashable (type=%s), cannot cache auth context", + type(session).__name__, + ) + return + + auth = auth_context_var.get() + if auth and isinstance(auth, MCPAuthenticatedUser): + try: + _session_obj_auth_storage[session] = auth + except TypeError: + verbose_logger.debug( + "_cache_auth_context_lazily: could not store auth via " + "session identity — session object is unhashable" + ) + + def _recover_auth_from_session() -> Optional[MCPAuthenticatedUser]: + session = _get_current_session() + if session is None: + return None + + stored: Optional[MCPAuthenticatedUser] = None + try: + stored = _session_obj_auth_storage.get(session) + except TypeError: + verbose_logger.debug( + "_recover_auth_from_session: session object is unhashable " + "(type=%s), skipping _session_obj_auth_storage lookup", + type(session).__name__, + ) + + return stored + + async def get_or_extract_auth_context() -> Tuple[ + Optional[UserAPIKeyAuth], + Optional[str], + Optional[List[str]], + Optional[Dict[str, Dict[str, str]]], + Optional[Dict[str, str]], + Optional[Dict[str, str]], + Optional[str], + ]: + """ + Get auth context from ContextVar first, then fall back to session + storage (which survives cross-task boundaries in the MCP SDK). + """ + ( + user_api_key_auth, + mcp_auth_header, + mcp_servers, + mcp_server_auth_headers, + oauth2_headers, + raw_headers, + _client_ip, + ) = get_auth_context() + + if user_api_key_auth is not None: + _cache_auth_context_lazily() + else: + stored = _recover_auth_from_session() + + if stored: + user_api_key_auth = stored.user_api_key_auth + mcp_auth_header = stored.mcp_auth_header + mcp_servers = stored.mcp_servers + mcp_server_auth_headers = stored.mcp_server_auth_headers + oauth2_headers = stored.oauth2_headers + raw_headers = stored.raw_headers + _client_ip = stored.client_ip + return ( + user_api_key_auth, + mcp_auth_header, + mcp_servers, + mcp_server_auth_headers, + oauth2_headers, + raw_headers, + _client_ip, + ) + + def get_active_mcp_session() -> Optional[_McpServerSession]: + """Return the active MCP session captured during handler execution.""" + session = active_mcp_session_var.get() + if session is not None: + return session + return _get_current_session() + + def get_active_auth_context() -> Optional[MCPAuthenticatedUser]: + """Return auth context from ContextVar or session storage.""" + auth = auth_context_var.get() + if auth and isinstance(auth, MCPAuthenticatedUser): + return auth + + stored = _recover_auth_from_session() + if stored is not None: + return stored + return None + ######################################################## ############ End of Auth Context Functions ############# ######################################################## diff --git a/litellm/proxy/caching_routes.py b/litellm/proxy/caching_routes.py index 20c951d350d..f0d8ddf97d6 100644 --- a/litellm/proxy/caching_routes.py +++ b/litellm/proxy/caching_routes.py @@ -60,11 +60,20 @@ async def cache_ping(): """ litellm_cache_params: Dict[str, Any] = {} cleaned_cache_params: Dict[str, Any] = {} + if litellm.cache is None: + raise ProxyException( + message=safe_dumps( + { + "message": "Cache not initialized. litellm.cache is None", + "litellm_cache_params": "{}", + "health_check_cache_params": "{}", + } + ), + type=ProxyErrorTypes.cache_ping_error, + param="cache_ping", + code=503, + ) try: - if litellm.cache is None: - raise HTTPException( - status_code=503, detail="Cache not initialized. litellm.cache is None" - ) litellm_cache_params = masker.mask_dict(vars(litellm.cache)) # remove field that might reference itself litellm_cache_params.pop("cache", None) @@ -97,14 +106,14 @@ async def cache_ping(): cache_type=str(litellm.cache.type), litellm_cache_params=safe_dumps(litellm_cache_params), ) - except Exception as e: - import traceback - + except HTTPException: + raise + except Exception: + verbose_proxy_logger.exception("Cache health check failed") error_message = { - "message": f"Service Unhealthy ({str(e)})", + "message": "Service Unhealthy", "litellm_cache_params": safe_dumps(litellm_cache_params), "health_check_cache_params": safe_dumps(cleaned_cache_params), - "traceback": traceback.format_exc(), } raise ProxyException( message=safe_dumps(error_message), diff --git a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py index 27fa685eaac..b0932015ab3 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py +++ b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py @@ -16,7 +16,7 @@ from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.common_utils.callback_utils import ( add_guardrail_to_applied_guardrails_header, ) -from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.guardrails import GuardrailEventHooks, LitellmParams from litellm.types.proxy.guardrails.guardrail_hooks.tool_permission import ( PermissionError, ToolPermissionRule, @@ -60,53 +60,7 @@ class ToolPermissionGuardrail(CustomGuardrail): super().__init__(**kwargs) - self.rules: List[ToolPermissionRule] = [] - self._compiled_rule_patterns: Dict[str, Dict[str, re.Pattern]] = {} - self._compiled_rule_targets: Dict[str, Dict[str, Optional[re.Pattern]]] = {} - if rules: - for rule_item in rules: - if isinstance(rule_item, ToolPermissionRule): - rule = rule_item - else: - rule = ToolPermissionRule(**rule_item) - self.rules.append(rule) - - compiled_target_patterns: Dict[str, Optional[re.Pattern]] = { - "tool_name": None, - "tool_type": None, - } - if rule.tool_name is not None: - try: - compiled_target_patterns["tool_name"] = re.compile( - rule.tool_name - ) - except re.error as exc: - raise ValueError( - f"Invalid regex for tool_name in rule '{rule.id}': {exc}" - ) from exc - if rule.tool_type is not None: - try: - compiled_target_patterns["tool_type"] = re.compile( - rule.tool_type - ) - except re.error as exc: - raise ValueError( - f"Invalid regex for tool_type in rule '{rule.id}': {exc}" - ) from exc - self._compiled_rule_targets[rule.id] = compiled_target_patterns - - if rule.allowed_param_patterns: - compiled_patterns: Dict[str, re.Pattern] = {} - for path, pattern in rule.allowed_param_patterns.items(): - try: - compiled_patterns[path] = re.compile(pattern) - except re.error as exc: - raise ValueError( - f"Invalid regex in allowed_param_patterns for rule '{rule.id}': {exc}" - ) from exc - - if compiled_patterns: - self._compiled_rule_patterns[rule.id] = compiled_patterns + self._load_rules(rules) # Normalize to lowercase for case-insensitive handling self.default_action = ( @@ -126,6 +80,115 @@ class ToolPermissionGuardrail(CustomGuardrail): self.default_action, ) + def _load_rules(self, rules: Optional[List[Any]]) -> None: + """Parse ``rules`` and (re)build the compiled target/pattern lookups. + + ``self.rules`` plus ``_compiled_rule_targets`` / ``_compiled_rule_patterns`` + are the state every matching path reads. Centralizing the build here lets + both ``__init__`` and ``update_in_memory_litellm_params`` recompile from a + single source of truth, so an in-place update (PUT /guardrails, immediate + sync) reflects rule changes instead of keeping the construction-time maps. + """ + parsed_rules: List[ToolPermissionRule] = [] + compiled_targets: Dict[str, Dict[str, Optional[re.Pattern]]] = {} + compiled_patterns: Dict[str, Dict[str, re.Pattern]] = {} + + for rule_item in rules or []: + rule = ( + rule_item + if isinstance(rule_item, ToolPermissionRule) + else ToolPermissionRule(**rule_item) + ) + + target_patterns: Dict[str, Optional[re.Pattern]] = { + "tool_name": None, + "tool_type": None, + } + if rule.tool_name is not None: + try: + target_patterns["tool_name"] = re.compile(rule.tool_name) + except re.error as exc: + raise ValueError( + f"Invalid regex for tool_name in rule '{rule.id}': {exc}" + ) from exc + if rule.tool_type is not None: + try: + target_patterns["tool_type"] = re.compile(rule.tool_type) + except re.error as exc: + raise ValueError( + f"Invalid regex for tool_type in rule '{rule.id}': {exc}" + ) from exc + + rule_patterns: Dict[str, re.Pattern] = {} + for path, pattern in (rule.allowed_param_patterns or {}).items(): + try: + rule_patterns[path] = re.compile(pattern) + except re.error as exc: + raise ValueError( + f"Invalid regex in allowed_param_patterns for rule '{rule.id}': {exc}" + ) from exc + + parsed_rules.append(rule) + compiled_targets[rule.id] = target_patterns + if rule_patterns: + compiled_patterns[rule.id] = rule_patterns + + # Swap in the fully-built maps only after every rule compiles, so an + # invalid regex raises without leaving a partially-built ruleset (a + # missing compiled target is read as a match-all wildcard). + self.rules = parsed_rules + self._compiled_rule_targets = compiled_targets + self._compiled_rule_patterns = compiled_patterns + + def update_in_memory_litellm_params( + self, litellm_params: Union[LitellmParams, dict] + ) -> None: + """Apply updated params in place, rebuilding the compiled rule state. + + The base implementation only ``setattr``s raw fields, which would leave + ``_compiled_rule_targets`` / ``_compiled_rule_patterns`` (built in + ``__init__``) stale, so a guardrail updated without reinitialization would + keep enforcing the old ruleset. Recompile here so PUT /guardrails and the + immediate in-memory sync take effect, mirroring the PresidioGuardrail + override of this method. + """ + # ``litellm_params`` may arrive as the raw DB dict (the proxy ``cast()``s + # it to ``LitellmParams`` without converting), so handle both shapes. The + # base ``setattr`` loop is model-only, so apply the dict case here. + previous_rules = self.rules + if isinstance(litellm_params, dict): + params = litellm_params + for key, value in params.items(): + setattr(self, key, value) + else: + super().update_in_memory_litellm_params(litellm_params) + params = vars(litellm_params) + + # The generic update above sets ``self.rules`` from the incoming value + # (None on a partial update that omits rules), but never rebuilds the + # compiled maps. Rebuild them when rules are provided; otherwise restore + # the previous ruleset so a partial update doesn't silently wipe it. An + # explicit empty list still clears the rules. + rules = params.get("rules") + if rules is not None: + try: + self._load_rules(rules) + except Exception: + # The generic update above may have overwritten self.rules with + # the raw payload; restore the prior consistent ruleset so a + # rejected update can't leave the live guardrail enforcing a + # broken policy. + self.rules = previous_rules + raise + else: + self.rules = previous_rules + default_action = params.get("default_action") + if isinstance(default_action, str): + self.default_action = default_action.lower() + on_disallowed_action = params.get("on_disallowed_action") + if isinstance(on_disallowed_action, str): + self.on_disallowed_action = on_disallowed_action.lower() + @staticmethod def get_config_model(): from litellm.types.proxy.guardrails.guardrail_hooks.tool_permission import ( diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index a092df6cdf0..7aed9ad894a 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -1910,7 +1910,7 @@ prompt_injection_detection_obj: Optional[_OPTIONAL_PromptInjectionDetection] = N store_model_in_db: bool = False open_telemetry_logger: Optional[OpenTelemetry] = None ### INITIALIZE GLOBAL LOGGING OBJECT ### -proxy_logging_obj = ProxyLogging( +proxy_logging_obj: ProxyLogging = ProxyLogging( user_api_key_cache=user_api_key_cache, premium_user=premium_user ) ### REDIS QUEUE ### @@ -15844,10 +15844,10 @@ async def toolset_mcp_route(toolset_name: str, request: Request): except HTTPException as e: raise e except Exception as e: - verbose_proxy_logger.error( - f"Error handling toolset MCP route for {toolset_name}: {str(e)}" + verbose_proxy_logger.exception( + "Error handling toolset MCP route for %s: %s", toolset_name, str(e) ) - raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}") + raise HTTPException(status_code=500, detail="Internal server error") async def _mcp_forward_as_path(path_segment: str, request: Request): @@ -16028,7 +16028,7 @@ async def dynamic_mcp_route(mcp_server_name: str, request: Request): except HTTPException as e: raise e except Exception as e: - verbose_proxy_logger.error( - f"Error handling dynamic MCP route for {mcp_server_name}: {str(e)}" + verbose_proxy_logger.exception( + "Error handling dynamic MCP route for %s: %s", mcp_server_name, str(e) ) - raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}") + raise HTTPException(status_code=500, detail="Internal server error") diff --git a/litellm/types/llms/gemini.py b/litellm/types/llms/gemini.py index 38e6d533449..e24eb4aebb5 100644 --- a/litellm/types/llms/gemini.py +++ b/litellm/types/llms/gemini.py @@ -1,7 +1,7 @@ from enum import Enum from typing import Any, Dict, List, Literal, Optional -from typing_extensions import TypedDict +from typing_extensions import Required, TypedDict from .vertex_ai import ( GenerationConfig, @@ -233,10 +233,11 @@ class GeminiImageGenerationResponse(TypedDict): # Video Generation Types -class GeminiVideoGenerationInstance(TypedDict): +class GeminiVideoGenerationInstance(TypedDict, total=False): """Instance data for Gemini video generation request""" - prompt: str + prompt: Required[str] + image: Dict[str, Any] class GeminiVideoGenerationParameters(BaseModel): @@ -264,11 +265,6 @@ class GeminiVideoGenerationParameters(BaseModel): negativePrompt: Optional[str] = None """Text describing what not to include in the video.""" - image: Optional[Any] = None - """ - An initial image to animate (Image object). - """ - lastFrame: Optional[Any] = None """ The final image for interpolation video to transition. diff --git a/litellm/types/mcp_server/mcp_server_manager.py b/litellm/types/mcp_server/mcp_server_manager.py index 6aa62c35106..2108fe8990d 100644 --- a/litellm/types/mcp_server/mcp_server_manager.py +++ b/litellm/types/mcp_server/mcp_server_manager.py @@ -115,6 +115,8 @@ class MCPServer(BaseModel): # different ``server_id`` values are bumped deterministically. Left # ``None`` in default-prefix mode. short_prefix: Optional[str] = None + allow_sampling: bool = False + allow_elicitation: bool = False model_config = ConfigDict(arbitrary_types_allowed=True) @property diff --git a/litellm/utils.py b/litellm/utils.py index 7cac830b2c2..d010391229b 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -4871,7 +4871,7 @@ def add_provider_specific_params_to_optional_params( ) is False ): - extra_body = passed_params.pop("extra_body", None) or {} + extra_body = dict(passed_params.pop("extra_body", None) or {}) for k in passed_params.keys(): if k not in openai_params and passed_params[k] is not None: extra_body[k] = passed_params[k] @@ -8909,6 +8909,16 @@ class ProviderConfigManager: return litellm.OpenRouterResponsesAPIConfig() elif litellm.LlmProviders.HOSTED_VLLM == provider: return litellm.HostedVLLMResponsesAPIConfig() + elif litellm.LlmProviders.BEDROCK_MANTLE == provider: + # Only OpenAI gpt frontier models (gpt-5.x, and future gpt-6 etc.) are + # served on the /openai/v1/responses path. gpt-oss and every non-OpenAI + # model on Mantle (nvidia, mistral, google, zai, ...) are chat-completions + # only and 400 on that path, so they fall through to None to keep the + # chat-completions emulation (see litellm/responses/main.py "config is None"). + model_lower = model.lower() if model else "" + if "openai.gpt-" in model_lower and "gpt-oss" not in model_lower: + return litellm.BedrockMantleResponsesAPIConfig() + return None return None @staticmethod diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index ed6de4fa6b7..4c227656e5f 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -30424,21 +30424,32 @@ "supports_reasoning": true, "source": "https://cloud.sambanova.ai/plans/pricing" }, - "snowflake/claude-3-5-sonnet": { + "snowflake/claude-3-5-sonnet": { "litellm_provider": "snowflake", - "max_input_tokens": 18000, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "max_tokens": 16384, "mode": "chat", - "supports_computer_use": true + "input_cost_per_token": 0.000003, + "output_cost_per_token": 0.000015, + "cache_read_input_token_cost": 0.0000003, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_response_schema": true }, - "snowflake/deepseek-r1": { + "snowflake/deepseek-r1": { "litellm_provider": "snowflake", - "max_input_tokens": 32768, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, "mode": "chat", - "supports_reasoning": true + "input_cost_per_token": 0.00000135, + "output_cost_per_token": 0.0000054, + "supports_reasoning": true, + "supports_system_messages": true }, "snowflake/gemma-7b": { "litellm_provider": "snowflake", @@ -30492,23 +30503,34 @@ "snowflake/llama3.1-405b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat" + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "input_cost_per_token": 0.0000012, + "output_cost_per_token": 0.0000012, + "supports_function_calling": true, + "supports_system_messages": true }, "snowflake/llama3.1-70b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat" + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "input_cost_per_token": 0.00000072, + "output_cost_per_token": 0.00000072, + "supports_function_calling": true, + "supports_system_messages": true }, "snowflake/llama3.1-8b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat" + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "input_cost_per_token": 0.00000024, + "output_cost_per_token": 0.00000024, + "supports_system_messages": true }, "snowflake/llama3.2-1b": { "litellm_provider": "snowflake", @@ -30524,13 +30546,17 @@ "max_tokens": 8192, "mode": "chat" }, - "snowflake/llama3.3-70b": { - "litellm_provider": "snowflake", + "snowflake/llama3.3-70b": { + "max_tokens": 16384, "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat" - }, + "max_output_tokens": 16384, + "input_cost_per_token": 0.00000072, + "output_cost_per_token": 0.00000072, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_system_messages": true + }, "snowflake/mistral-7b": { "litellm_provider": "snowflake", "max_input_tokens": 32000, @@ -30545,12 +30571,17 @@ "max_tokens": 8192, "mode": "chat" }, - "snowflake/mistral-large2": { + "snowflake/mistral-large2": { "litellm_provider": "snowflake", "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat" + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "input_cost_per_token": 0.000002, + "output_cost_per_token": 0.000006, + "supports_function_calling": true, + "supports_system_messages": true, + "supports_response_schema": true }, "snowflake/mixtral-8x7b": { "litellm_provider": "snowflake", @@ -30587,13 +30618,17 @@ "max_tokens": 8192, "mode": "chat" }, - "snowflake/snowflake-llama-3.3-70b": { + "snowflake/snowflake-llama-3.3-70b": { + "max_tokens": 16384, + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.00000072, + "output_cost_per_token": 0.00000072, "litellm_provider": "snowflake", - "max_input_tokens": 8000, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat" - }, + "mode": "chat", + "supports_function_calling": true, + "supports_system_messages": true + }, "stability/sd3": { "litellm_provider": "stability", "mode": "image_generation", @@ -41223,6 +41258,44 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "bedrock_mantle/openai.gpt-5.5": { + "input_cost_per_token": 5.5e-06, + "cache_read_input_token_cost": 5.5e-07, + "output_cost_per_token": 3.3e-05, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "supported_endpoints": ["/v1/responses"], + "supported_modalities": ["text", "image"], + "supported_output_modalities": ["text"], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "bedrock_mantle/openai.gpt-5.4": { + "input_cost_per_token": 2.75e-06, + "cache_read_input_token_cost": 2.75e-07, + "output_cost_per_token": 1.65e-05, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "supported_endpoints": ["/v1/responses"], + "supported_modalities": ["text", "image"], + "supported_output_modalities": ["text"], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "volcengine/doubao-seed-2-0-pro-260215": { "litellm_provider": "volcengine", "max_input_tokens": 256000, @@ -41501,5 +41574,180 @@ "supports_vision": true, "supports_native_structured_output": true, "supports_pdf_input": true - } -} + }, + "snowflake/claude-sonnet-4-5": { + "max_tokens": 16384, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000003, + "output_cost_per_token": 0.000015, + "cache_read_input_token_cost": 0.0000003, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/claude-sonnet-4-6": { + "max_tokens": 16384, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000003, + "output_cost_per_token": 0.000015, + "cache_read_input_token_cost": 0.0000003, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/claude-4-sonnet": { + "max_tokens": 16384, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000003, + "output_cost_per_token": 0.000015, + "cache_read_input_token_cost": 0.0000003, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/claude-4-opus": { + "max_tokens": 16384, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000005, + "output_cost_per_token": 0.000025, + "cache_read_input_token_cost": 0.0000005, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_reasoning": true, + "supports_response_schema": true + }, + "snowflake/claude-haiku-4-5": { + "max_tokens": 16384, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000001, + "output_cost_per_token": 0.000005, + "cache_read_input_token_cost": 0.0000001, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/claude-3-7-sonnet": { + "max_tokens": 16384, + "max_input_tokens": 200000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000003, + "output_cost_per_token": 0.000015, + "cache_read_input_token_cost": 0.0000003, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_reasoning": true, + "supports_response_schema": true + }, + "snowflake/openai-gpt-4.1": { + "max_tokens": 16384, + "max_input_tokens": 300000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.000002, + "output_cost_per_token": 0.000008, + "cache_read_input_token_cost": 0.0000005, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/openai-gpt-5": { + "max_tokens": 16384, + "max_input_tokens": 300000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.00000125, + "output_cost_per_token": 0.00001, + "cache_read_input_token_cost": 0.000000125, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_vision": true, + "supports_prompt_caching": true, + "supports_system_messages": true, + "supports_reasoning": true, + "supports_response_schema": true + }, + "snowflake/openai-gpt-5-mini": { + "max_tokens": 16384, + "max_input_tokens": 1000000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.0000003, + "output_cost_per_token": 0.0000012, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/openai-gpt-5-nano": { + "max_tokens": 16384, + "max_input_tokens": 5000000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.00000015, + "output_cost_per_token": 0.0000006, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_system_messages": true, + "supports_response_schema": true + }, + "snowflake/llama4-maverick": { + "max_tokens": 16384, + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "input_cost_per_token": 0.00000024, + "output_cost_per_token": 0.00000097, + "litellm_provider": "snowflake", + "mode": "chat", + "supports_function_calling": true, + "supports_system_messages": true + }, + "snowflake/snowflake-arctic-embed-l-v2.0": { + "max_tokens": 8192, + "max_input_tokens": 8192, + "input_cost_per_token": 0.00000007, + "output_cost_per_token": 0.0, + "litellm_provider": "snowflake", + "mode": "embedding" + }, + "snowflake/snowflake-arctic-embed-m-v2.0": { + "max_tokens": 8192, + "max_input_tokens": 8192, + "input_cost_per_token": 0.00000007, + "output_cost_per_token": 0.0, + "litellm_provider": "snowflake", + "mode": "embedding" + } + } + diff --git a/tests/llm_translation/test_fireworks_ai_translation.py b/tests/llm_translation/test_fireworks_ai_translation.py index 47b95c27ab7..c4f15ac4c3e 100644 --- a/tests/llm_translation/test_fireworks_ai_translation.py +++ b/tests/llm_translation/test_fireworks_ai_translation.py @@ -43,12 +43,14 @@ def test_map_openai_params_tool_choice(): def test_map_response_format(): """ - Test that the response format is translated correctly. + json_schema response_format is passed through to Fireworks unchanged. - h/t to https://github.com/DaveDeCaprio (@DaveDeCaprio) for the test case + Fireworks accepts the OpenAI strict json_schema shape natively. The earlier + downgrade to {type: json_object, schema: ...} silently dropped `strict` and + `name`, producing a request that Fireworks treats as "any valid JSON" per + its docs, disabling grammar-guided decoding. - Relevant Issue: https://github.com/BerriAI/litellm/issues/6797 - Fireworks AI Ref: https://docs.fireworks.ai/structured-responses/structured-response-formatting#step-1-import-libraries + Ref: https://docs.fireworks.ai/structured-responses/structured-response-formatting """ response_format = { "type": "json_schema", @@ -65,16 +67,7 @@ def test_map_response_format(): result = fireworks.map_openai_params( {"response_format": response_format}, {}, "some_model", drop_params=False ) - assert result == { - "response_format": { - "type": "json_object", - "schema": { - "properties": {"result": {"type": "boolean"}}, - "required": ["result"], - "type": "object", - }, - } - } + assert result == {"response_format": response_format} class TestFireworksAIAudioTranscription(BaseLLMAudioTranscriptionTest): diff --git a/tests/local_testing/test_custom_llm.py b/tests/local_testing/test_custom_llm.py index 34ab6c043b9..ea15c3db9d0 100644 --- a/tests/local_testing/test_custom_llm.py +++ b/tests/local_testing/test_custom_llm.py @@ -44,7 +44,14 @@ from litellm import ( image_generation, ) from litellm.utils import ModelResponseIterator -from litellm.types.utils import ImageResponse, ImageObject, EmbeddingResponse +from litellm.types.utils import ( + ImageResponse, + ImageObject, + EmbeddingResponse, + ModelResponseStream, + StreamingChoices, + Delta, +) from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler @@ -644,3 +651,82 @@ async def test_simple_aembedding(): "embedding": [0.1, 0.2, 0.3], "index": 1, } + + +# ── Tests for ModelResponseStream passthrough in custom providers (issue #27389) ── + + +class ModelResponseStreamLLM(MyCustomLLM): + """Subclass that overrides streaming/astreaming to yield ModelResponseStream directly.""" + + def __init__(self, finish_reason: str = "stop"): + self._finish_reason = finish_reason + + def streaming(self, *args, **kwargs) -> Iterator[ModelResponseStream]: # type: ignore + yield ModelResponseStream( + id="test-stream-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta(content="Hello world"), + finish_reason=self._finish_reason, + ) + ], + ) + + async def astreaming(self, *args, **kwargs) -> AsyncIterator[ModelResponseStream]: # type: ignore + yield ModelResponseStream( + id="test-stream-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta(content="Hello world"), + finish_reason=self._finish_reason, + ) + ], + ) + + +@pytest.mark.parametrize( + "finish_reason", ["stop", "tool_calls", "length", "content_filter"] +) +def test_custom_llm_streaming_model_response_stream(finish_reason): + my_custom_llm = ModelResponseStreamLLM(finish_reason=finish_reason) + litellm.custom_provider_map = [ + {"provider": "custom_llm", "custom_handler": my_custom_llm} + ] + resp = completion( + model="custom_llm/my-fake-model", + messages=[{"role": "user", "content": "Hello world!"}], + stream=True, + ) + + for chunk in resp: + print(chunk) + if chunk.choices[0].finish_reason is None: + assert isinstance(chunk.choices[0].delta.content, str) + else: + assert chunk.choices[0].finish_reason == finish_reason + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "finish_reason", ["stop", "tool_calls", "length", "content_filter"] +) +async def test_custom_llm_astreaming_model_response_stream(finish_reason): + my_custom_llm = ModelResponseStreamLLM(finish_reason=finish_reason) + litellm.custom_provider_map = [ + {"provider": "custom_llm", "custom_handler": my_custom_llm} + ] + resp = await litellm.acompletion( + model="custom_llm/my-fake-model", + messages=[{"role": "user", "content": "Hello world!"}], + stream=True, + ) + + async for chunk in resp: + print(chunk) + if chunk.choices[0].finish_reason is None: + assert isinstance(chunk.choices[0].delta.content, str) + else: + assert chunk.choices[0].finish_reason == finish_reason diff --git a/tests/local_testing/test_get_llm_provider.py b/tests/local_testing/test_get_llm_provider.py index 46f2f89b3ce..1c041be0949 100644 --- a/tests/local_testing/test_get_llm_provider.py +++ b/tests/local_testing/test_get_llm_provider.py @@ -131,6 +131,7 @@ def test_default_api_base(): from litellm.litellm_core_utils.get_llm_provider_logic import ( _get_openai_compatible_provider_info, ) + from litellm.types.utils import LlmProviders # Patch environment variable to remove API base if it's set with patch.dict(os.environ, {}, clear=True): @@ -150,13 +151,13 @@ def test_default_api_base(): if api_base is None: continue - for other_provider in litellm.provider_list: - if other_provider != provider and provider != "{}_chat".format( + for other_provider in LlmProviders: + if other_provider.value != provider and provider != "{}_chat".format( other_provider.value ): - if provider == "codestral" and other_provider == "mistral": + if provider == "codestral" and other_provider.value == "mistral": continue - elif provider == "github" and other_provider == "azure": + elif provider == "github" and other_provider.value == "azure": continue assert other_provider.value not in api_base.replace("/openai", "") diff --git a/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py b/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py new file mode 100644 index 00000000000..3c280c6ba92 --- /dev/null +++ b/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py @@ -0,0 +1,134 @@ +import os +import sys + +import pytest + +sys.path.insert(0, os.path.abspath("../../..")) + +from litellm.litellm_core_utils.get_supported_openai_params import ( + get_supported_openai_params, +) + +BEDROCK_REAL_MODEL = "eu.anthropic.claude-haiku-4-5-20251001-v1:0" +BEDROCK_LABEL = "claude-haiku-4-5" + + +def test_base_model_label_does_not_strip_bedrock_tools(): + """Regression for #29618. + + A Bedrock deployment whose ``model_info.base_model`` is a friendly label + (``claude-haiku-4-5``) must still advertise ``tools``/``tool_choice``. The label + on its own resolves to no tool support, so before the fix it stripped the + capability the real model id exposes, silently dropping function calling under + ``drop_params``.""" + params = get_supported_openai_params( + model=BEDROCK_REAL_MODEL, + custom_llm_provider="bedrock", + base_model=BEDROCK_LABEL, + ) + + assert params is not None + assert "tools" in params + assert "tool_choice" in params + + +def test_base_model_label_alone_lacks_bedrock_tools(): + """The label by itself does not advertise tools; this is what made the union + necessary. Guards against the discrepancy disappearing (and the regression test + above silently passing for the wrong reason).""" + params = get_supported_openai_params( + model=BEDROCK_LABEL, custom_llm_provider="bedrock" + ) + + assert params is not None + assert "tools" not in params + + +def test_base_model_is_additive_not_replacement(): + """``base_model`` may only add capabilities, never remove ones the real model has. + + Bedrock: real id supports ``tools`` but not the label's reasoning hint; the union + must contain the real model's ``tools`` regardless of the label being a subset.""" + real_only = set( + get_supported_openai_params( + model=BEDROCK_REAL_MODEL, custom_llm_provider="bedrock" + ) + ) + label_only = set( + get_supported_openai_params(model=BEDROCK_LABEL, custom_llm_provider="bedrock") + ) + combined = set( + get_supported_openai_params( + model=BEDROCK_REAL_MODEL, + custom_llm_provider="bedrock", + base_model=BEDROCK_LABEL, + ) + ) + + assert combined == real_only | label_only + assert real_only - label_only # the label really is a strict subset here + assert real_only <= combined + + +def test_base_model_adds_capabilities_the_real_model_lacks(): + """Regression for #27717 (the behavior the union must preserve). + + ``gemini-3.1-pro`` isn't in the cost map so it advertises no reasoning support, + but the registered ``gemini-3.1-pro-preview`` base_model does. The hint must add + ``reasoning_effort``/``thinking`` without the call erroring.""" + real_only = set( + get_supported_openai_params( + model="gemini-3.1-pro", custom_llm_provider="gemini" + ) + ) + assert "reasoning_effort" not in real_only + + combined = set( + get_supported_openai_params( + model="gemini-3.1-pro", + custom_llm_provider="gemini", + base_model="gemini-3.1-pro-preview", + ) + ) + assert "reasoning_effort" in combined + assert "thinking" in combined + + +def test_no_base_model_is_unchanged(): + """Omitting ``base_model`` must resolve purely from ``model``.""" + with_none = get_supported_openai_params( + model=BEDROCK_REAL_MODEL, custom_llm_provider="bedrock", base_model=None + ) + plain = get_supported_openai_params( + model=BEDROCK_REAL_MODEL, custom_llm_provider="bedrock" + ) + + assert with_none == plain + + +def test_base_model_equal_to_model_is_unchanged(): + """A ``base_model`` identical to ``model`` must not double-resolve or reorder.""" + plain = get_supported_openai_params( + model=BEDROCK_REAL_MODEL, custom_llm_provider="bedrock" + ) + same = get_supported_openai_params( + model=BEDROCK_REAL_MODEL, + custom_llm_provider="bedrock", + base_model=BEDROCK_REAL_MODEL, + ) + + assert same == plain + + +def test_azure_base_model_detection_preserved(): + """Azure relies on ``base_model`` for model-type detection when the deployment + name is opaque; the union must keep advertising the gpt-5 capabilities.""" + params = get_supported_openai_params( + model="my-opaque-deployment", + custom_llm_provider="azure", + base_model="azure/gpt-5.2", + ) + + assert params is not None + assert "reasoning_effort" in params + assert "tools" in params diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py index 63e2cb7f35c..b2002f9a0f9 100644 --- a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py +++ b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py @@ -2118,3 +2118,172 @@ def test_gemini_legacy_vertex_tool_calls_finish_reason_with_stop_enum(): f"Expected 'tool_calls' but got {final.choices[0].finish_reason!r}. " "STOP enum was not normalised through map_finish_reason()." ) + + +@pytest.mark.parametrize( + "finish_reason", ["stop", "tool_calls", "length", "content_filter"] +) +def test_chunk_creator_passes_through_model_response_stream( + initialized_custom_stream_wrapper: CustomStreamWrapper, + finish_reason: str, +): + """ + chunk_creator must pass ModelResponseStream chunks from custom providers + straight through and preserve finish_reason exactly — not force-cast to GChunk. + Regression test for issue #27389. + """ + initialized_custom_stream_wrapper.custom_llm_provider = "my-custom-provider" + litellm._custom_providers.append("my-custom-provider") + + chunk = ModelResponseStream( + id="test-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta(content="Hello", role="assistant"), + finish_reason=finish_reason, + ) + ], + ) + + result = initialized_custom_stream_wrapper.chunk_creator(chunk=chunk) + + litellm._custom_providers.remove("my-custom-provider") + + assert result is not None + assert initialized_custom_stream_wrapper.received_finish_reason == finish_reason + + +def test_chunk_creator_drops_empty_finish_chunk( + initialized_custom_stream_wrapper: CustomStreamWrapper, +): + """ + A ModelResponseStream chunk with finish_reason but no content should return + None so finish_reason_handler() synthesises the final chunk — mirrors GChunk + behaviour via is_chunk_non_empty. + """ + initialized_custom_stream_wrapper.custom_llm_provider = "my-custom-provider" + litellm._custom_providers.append("my-custom-provider") + + chunk = ModelResponseStream( + id="test-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta(content=""), + finish_reason="stop", + ) + ], + ) + + result = initialized_custom_stream_wrapper.chunk_creator(chunk=chunk) + + litellm._custom_providers.remove("my-custom-provider") + + assert result is None + assert initialized_custom_stream_wrapper.received_finish_reason == "stop" + + +def test_chunk_creator_stops_iteration_on_trailing_chunk( + initialized_custom_stream_wrapper: CustomStreamWrapper, +): + """ + After received_finish_reason is set, any empty trailing chunk (e.g. provider + metadata flush) must raise StopIteration to end the stream cleanly. + """ + initialized_custom_stream_wrapper.custom_llm_provider = "my-custom-provider" + initialized_custom_stream_wrapper.received_finish_reason = "stop" + litellm._custom_providers.append("my-custom-provider") + + trailing_chunk = ModelResponseStream( + id="test-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta(content=None), + finish_reason="stop", + ) + ], + ) + + with pytest.raises(StopIteration): + initialized_custom_stream_wrapper.chunk_creator(chunk=trailing_chunk) + + litellm._custom_providers.remove("my-custom-provider") + + +def test_chunk_creator_strips_finish_reason_from_content_chunk( + initialized_custom_stream_wrapper: CustomStreamWrapper, +): + """ + When content and finish_reason arrive in the same chunk, finish_reason must be + stripped so finish_reason_handler() emits it on the synthetic terminal chunk — + preventing two terminal chunks (double finish_reason bug). + """ + initialized_custom_stream_wrapper.custom_llm_provider = "my-custom-provider" + litellm._custom_providers.append("my-custom-provider") + + chunk = ModelResponseStream( + id="test-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta(content="Hello"), + finish_reason="stop", + ) + ], + ) + + result = initialized_custom_stream_wrapper.chunk_creator(chunk=chunk) + + litellm._custom_providers.remove("my-custom-provider") + + assert result is not None + assert ( + result.choices[0].finish_reason is None + ), "finish_reason must be stripped from content chunks to avoid double terminal chunks" + assert initialized_custom_stream_wrapper.received_finish_reason == "stop" + + +def test_chunk_creator_tool_calls_not_dropped_on_finish( + initialized_custom_stream_wrapper: CustomStreamWrapper, +): + """ + A terminal chunk with finish_reason="tool_calls" and delta.tool_calls must NOT + be silently dropped — tool_calls counts as content so the chunk is passed through + (with finish_reason stripped) rather than returning None. + """ + from litellm.types.utils import ChatCompletionDeltaToolCall, Function + + initialized_custom_stream_wrapper.custom_llm_provider = "my-custom-provider" + litellm._custom_providers.append("my-custom-provider") + + chunk = ModelResponseStream( + id="test-id", + choices=[ + StreamingChoices( + index=0, + delta=Delta( + content=None, + tool_calls=[ + ChatCompletionDeltaToolCall( + id="call_abc", + function=Function(name="get_weather", arguments='{"city":"NYC"}'), + type="function", + index=0, + ) + ], + ), + finish_reason="tool_calls", + ) + ], + ) + + result = initialized_custom_stream_wrapper.chunk_creator(chunk=chunk) + + litellm._custom_providers.remove("my-custom-provider") + + assert result is not None, "tool_calls chunk must not be dropped" + assert result.choices[0].delta.tool_calls is not None + assert result.choices[0].finish_reason is None + assert initialized_custom_stream_wrapper.received_finish_reason == "tool_calls" diff --git a/tests/test_litellm/llms/azure/image_edit/test_azure_image_edit_transformation.py b/tests/test_litellm/llms/azure/image_edit/test_azure_image_edit_transformation.py index 9d2787f78a7..59472d1a49d 100644 --- a/tests/test_litellm/llms/azure/image_edit/test_azure_image_edit_transformation.py +++ b/tests/test_litellm/llms/azure/image_edit/test_azure_image_edit_transformation.py @@ -1,5 +1,7 @@ +import urllib.parse from unittest.mock import patch +import litellm from litellm.llms.azure.image_edit.transformation import AzureImageEditConfig from litellm.types.router import GenericLiteLLMParams @@ -138,3 +140,96 @@ def test_azure_finalize_image_edit_strips_model_after_openai_transform(): assert data_out.get("prompt") == prompt assert data_out.get("n") == 1 assert len(files) >= 1 + + +# --------------------------------------------------------------------------- +# api_version fallback chain +# +# Pin the resolution order used by ``AzureImageEditConfig.get_complete_url``: +# litellm_params["api_version"] +# > litellm.api_version (module-global) +# > AZURE_API_VERSION env var +# > litellm.AZURE_DEFAULT_API_VERSION +# +# Before this fallback chain existed, image edit only read ``litellm_params`` +# and produced an unversioned URL when callers set api_version via the global +# or the env var (Azure then 404s with "Resource not found"). The chat path +# in ``litellm/llms/azure/common_utils.py`` already had this fallback. +# --------------------------------------------------------------------------- + + +_FALLBACK_API_BASE = "https://x.openai.azure.com" +_FALLBACK_MODEL = "gpt-image-1" + + +def _query_params(url: str) -> dict: + return dict(urllib.parse.parse_qsl(urllib.parse.urlparse(url).query)) + + +def test_api_version_uses_litellm_params_first(monkeypatch): + monkeypatch.setattr(litellm, "api_version", "from-global", raising=False) + monkeypatch.setenv("AZURE_API_VERSION", "from-env") + + url = AzureImageEditConfig().get_complete_url( + model=_FALLBACK_MODEL, + api_base=_FALLBACK_API_BASE, + litellm_params={"api_version": "from-params"}, + ) + + assert _query_params(url) == {"api-version": "from-params"} + + +def test_api_version_falls_back_to_litellm_global(monkeypatch): + monkeypatch.setattr(litellm, "api_version", "from-global", raising=False) + monkeypatch.setenv("AZURE_API_VERSION", "from-env") + + url = AzureImageEditConfig().get_complete_url( + model=_FALLBACK_MODEL, + api_base=_FALLBACK_API_BASE, + litellm_params={}, + ) + + assert _query_params(url) == {"api-version": "from-global"} + + +def test_api_version_falls_back_to_env_var(monkeypatch): + monkeypatch.setattr(litellm, "api_version", None, raising=False) + monkeypatch.setenv("AZURE_API_VERSION", "from-env") + + url = AzureImageEditConfig().get_complete_url( + model=_FALLBACK_MODEL, + api_base=_FALLBACK_API_BASE, + litellm_params={}, + ) + + assert _query_params(url) == {"api-version": "from-env"} + + +def test_api_version_falls_back_to_azure_default(monkeypatch): + monkeypatch.setattr(litellm, "api_version", None, raising=False) + monkeypatch.delenv("AZURE_API_VERSION", raising=False) + + url = AzureImageEditConfig().get_complete_url( + model=_FALLBACK_MODEL, + api_base=_FALLBACK_API_BASE, + litellm_params={}, + ) + + assert _query_params(url) == {"api-version": litellm.AZURE_DEFAULT_API_VERSION} + + +def test_api_version_in_api_base_query_is_preserved(monkeypatch): + """``api_base`` already carrying ``?api-version=...`` must not be overridden.""" + monkeypatch.setattr(litellm, "api_version", None, raising=False) + monkeypatch.delenv("AZURE_API_VERSION", raising=False) + + url = AzureImageEditConfig().get_complete_url( + model=_FALLBACK_MODEL, + api_base=( + f"{_FALLBACK_API_BASE}/openai/deployments/{_FALLBACK_MODEL}" + "/images/edits?api-version=2024-05-01-preview" + ), + litellm_params={"api_version": "would-be-overridden"}, + ) + + assert _query_params(url) == {"api-version": "2024-05-01-preview"} diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py new file mode 100644 index 00000000000..e2133d56f89 --- /dev/null +++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py @@ -0,0 +1,283 @@ +""" +Unit tests for Amazon Bedrock Mantle Responses API configuration. + +Mantle's gpt-5.5 / gpt-5.4 are served ONLY on the non-standard +`/openai/v1/responses` path. These tests lock the URL construction and +Bearer auth that make that routing work. +""" + +import os +import sys + +sys.path.insert(0, os.path.abspath("../../../../..")) + +import pytest + +import litellm +from litellm.llms.bedrock_mantle.responses.transformation import ( + BedrockMantleResponsesAPIConfig, +) +from litellm.types.router import GenericLiteLLMParams +from litellm.types.utils import LlmProviders + + +class TestBedrockMantleResponsesURL: + def test_url_uses_region_from_env(self, monkeypatch): + monkeypatch.setenv("BEDROCK_MANTLE_REGION", "us-east-2") + monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + url = cfg.get_complete_url(api_base=None, litellm_params={}) + assert url == "https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses" + + def test_url_normalizes_v1_suffix(self, monkeypatch): + monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + url = cfg.get_complete_url( + api_base="https://bedrock-mantle.us-east-2.api.aws/v1", + litellm_params={}, + ) + assert url == "https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses" + assert "/v1/openai/v1/responses" not in url + url_trailing = cfg.get_complete_url( + api_base="https://bedrock-mantle.us-east-2.api.aws/v1/", + litellm_params={}, + ) + assert ( + url_trailing + == "https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses" + ) + + def test_url_does_not_double_openai_v1(self, monkeypatch): + monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + url = cfg.get_complete_url( + api_base="https://bedrock-mantle.us-east-2.api.aws/openai/v1", + litellm_params={}, + ) + assert url == "https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses" + + def test_url_full_endpoint_base_not_doubled(self, monkeypatch): + # AWS model card tells users to set OPENAI_BASE_URL to the full endpoint. + # If copied into api_base, it must not be doubled. + monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + url = cfg.get_complete_url( + api_base="https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses", + litellm_params={}, + ) + assert url == "https://bedrock-mantle.us-east-2.api.aws/openai/v1/responses" + assert url.count("/responses") == 1 + + def test_url_region_fallback_to_aws_region(self, monkeypatch): + monkeypatch.delenv("BEDROCK_MANTLE_REGION", raising=False) + monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) + monkeypatch.setenv("AWS_REGION", "us-west-2") + cfg = BedrockMantleResponsesAPIConfig() + url = cfg.get_complete_url(api_base=None, litellm_params={}) + assert url == "https://bedrock-mantle.us-west-2.api.aws/openai/v1/responses" + + def test_url_region_default_us_east_1(self, monkeypatch): + monkeypatch.delenv("BEDROCK_MANTLE_REGION", raising=False) + monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) + monkeypatch.delenv("AWS_REGION", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + url = cfg.get_complete_url(api_base=None, litellm_params={}) + assert url == "https://bedrock-mantle.us-east-1.api.aws/openai/v1/responses" + + +class TestBedrockMantleResponsesAuth: + def test_config_api_key_takes_priority(self, monkeypatch): + monkeypatch.setenv("BEDROCK_MANTLE_API_KEY", "env-key") + cfg = BedrockMantleResponsesAPIConfig() + headers = cfg.validate_environment( + headers={}, + model="openai.gpt-5.5", + litellm_params=GenericLiteLLMParams(api_key="config-key"), + ) + assert headers["Authorization"] == "Bearer config-key" + + def test_env_key_fallback(self, monkeypatch): + monkeypatch.setenv("BEDROCK_MANTLE_API_KEY", "env-key") + monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + headers = cfg.validate_environment( + headers={}, model="openai.gpt-5.5", litellm_params=GenericLiteLLMParams() + ) + assert headers["Authorization"] == "Bearer env-key" + + def test_bedrock_bearer_token_fallback(self, monkeypatch): + monkeypatch.delenv("BEDROCK_MANTLE_API_KEY", raising=False) + monkeypatch.setenv("AWS_BEARER_TOKEN_BEDROCK", "bearer-key") + cfg = BedrockMantleResponsesAPIConfig() + headers = cfg.validate_environment( + headers={}, model="openai.gpt-5.5", litellm_params=GenericLiteLLMParams() + ) + assert headers["Authorization"] == "Bearer bearer-key" + + def test_missing_key_raises(self, monkeypatch): + monkeypatch.delenv("BEDROCK_MANTLE_API_KEY", raising=False) + monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False) + cfg = BedrockMantleResponsesAPIConfig() + with pytest.raises(ValueError, match="Bedrock Mantle API key"): + cfg.validate_environment( + headers={}, + model="openai.gpt-5.5", + litellm_params=GenericLiteLLMParams(), + ) + + def test_custom_llm_provider(self): + cfg = BedrockMantleResponsesAPIConfig() + assert cfg.custom_llm_provider == LlmProviders.BEDROCK_MANTLE + + def test_native_websocket_disabled(self): + # Mantle Responses has no realtime/websocket transport, so the config + # must opt out; otherwise realtime routing would try a socket Mantle + # does not serve. + cfg = BedrockMantleResponsesAPIConfig() + assert cfg.supports_native_websocket() is False + + def test_file_search_routes_to_emulation(self): + # Mantle cannot reach OpenAI's vector stores, so a native file_search + # tool forwarded as-is gets a 400. The config must opt out of native + # file_search so LiteLLM's emulation handles it instead of forwarding. + from litellm.responses.file_search.emulated_handler import ( + should_use_emulated_file_search, + ) + + cfg = BedrockMantleResponsesAPIConfig() + assert cfg.supports_native_file_search() is False + assert ( + should_use_emulated_file_search( + tools=[{"type": "file_search", "vector_store_ids": ["vs_1"]}], + provider_config=cfg, + ) + is True + ) + + +class TestBedrockMantleResponsesRegistry: + def test_registry_returns_config_for_gpt_5_5(self): + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model="openai.gpt-5.5", + ) + assert isinstance(cfg, BedrockMantleResponsesAPIConfig) + + def test_registry_returns_config_for_gpt_5_4_enum(self): + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider=LlmProviders.BEDROCK_MANTLE, + model="openai.gpt-5.4", + ) + assert isinstance(cfg, BedrockMantleResponsesAPIConfig) + + def test_registry_returns_none_for_gpt_oss(self): + # Regression guard: gpt-oss must NOT get the native Responses config; it + # keeps the chat-completions emulation path (responses/main.py ~line 1109). + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model="openai.gpt-oss-120b", + ) + assert cfg is None + + def test_registry_returns_none_for_gpt_oss_safeguard(self): + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model="openai.gpt-oss-safeguard-20b", + ) + assert cfg is None + + def test_registry_returns_config_for_future_frontier_model(self): + # Forward-compatibility: an unseen OpenAI gpt frontier model (e.g. gpt-6) must + # get the native Responses config without a code change. The gate allow-lists + # the openai.gpt- family (minus gpt-oss), so gpt-6 matches automatically. + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model="openai.gpt-6", + ) + assert isinstance(cfg, BedrockMantleResponsesAPIConfig) + + @pytest.mark.parametrize( + "model", + [ + "nvidia.nemotron-nano-9b-v2", + "mistral.ministral-3-3b-instruct", + "google.gemma-3-27b-it", + "zai.glm-4.6", + ], + ) + def test_registry_returns_none_for_non_openai_models(self, model): + # Regression for the chat-only families on Mantle. These models 400 on + # /openai/v1/responses and are served on /v1/chat/completions, so the + # registry must NOT hand them the Responses config; they fall through to + # None and keep the chat-completions emulation. + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model=model, + ) + assert cfg is None + + def test_registry_returns_none_when_model_is_none(self): + # By-id operations (delete/get/cancel) call with model=None; keep returning + # None so those paths are unchanged. + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model=None, + ) + assert cfg is None + + +@pytest.fixture +def local_cost_map(monkeypatch): + """Force the bundled backup cost map and re-derive the provider model sets. + + ``litellm.model_cost`` is populated once at import time (here, from the + network-fetched ``main`` copy, which lags this branch). ``add_known_models`` + only re-buckets whatever is already in ``model_cost``, so the cost map must + first be reloaded from the local backup before the new keys appear. + """ + original_model_cost = litellm.model_cost + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "true") + litellm.model_cost = litellm.get_model_cost_map(url="") + litellm.get_model_info.cache_clear() + litellm.add_known_models() + try: + yield + finally: + litellm.model_cost = original_model_cost + litellm.get_model_info.cache_clear() + + +class TestBedrockMantleResponsesPricing: + def test_gpt_5_5_pricing_and_mode(self, local_cost_map): + info = litellm.get_model_info("bedrock_mantle/openai.gpt-5.5") + assert info["mode"] == "responses" + assert info["input_cost_per_token"] == pytest.approx(5.5e-06) + assert info["output_cost_per_token"] == pytest.approx(3.3e-05) + assert info["cache_read_input_token_cost"] == pytest.approx(5.5e-07) + assert info["max_input_tokens"] == 272000 + + def test_gpt_5_4_pricing_and_mode(self, local_cost_map): + info = litellm.get_model_info("bedrock_mantle/openai.gpt-5.4") + assert info["mode"] == "responses" + assert info["input_cost_per_token"] == pytest.approx(2.75e-06) + assert info["output_cost_per_token"] == pytest.approx(1.65e-05) + assert info["cache_read_input_token_cost"] == pytest.approx(2.75e-07) + assert info["max_input_tokens"] == 272000 + + def test_models_registered(self, local_cost_map): + assert "bedrock_mantle/openai.gpt-5.5" in litellm.bedrock_mantle_models + assert "bedrock_mantle/openai.gpt-5.4" in litellm.bedrock_mantle_models diff --git a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py index 2061522feff..ca340b5f275 100644 --- a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py +++ b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py @@ -496,3 +496,59 @@ def test_transform_tools_skips_non_function_tools(): "type": "object", "properties": {"id": {"type": "string"}}, } + + +def test_map_response_format_passes_json_schema_through_unchanged(): + """ + json_schema response_format must reach Fireworks unchanged. + + Regression guard for the prior downgrade to {type: json_object, schema: ...} + which silently dropped `strict` and `name` and disabled grammar-guided + decoding on the Fireworks side. + """ + config = FireworksAIConfig() + response_format = { + "type": "json_schema", + "json_schema": { + "name": "priority_classification", + "strict": True, + "schema": { + "type": "object", + "properties": { + "priority": { + "type": "string", + "enum": ["high", "medium", "low"], + } + }, + "required": ["priority"], + "additionalProperties": False, + }, + }, + } + + result = config.map_openai_params( + {"response_format": response_format}, + {}, + "fireworks_ai/accounts/fireworks/models/qwen3-32b", + drop_params=False, + ) + + rf = result["response_format"] + assert rf["type"] == "json_schema" + assert rf["json_schema"]["name"] == "priority_classification" + assert rf["json_schema"]["strict"] is True + assert rf["json_schema"]["schema"] == response_format["json_schema"]["schema"] + + +def test_map_response_format_json_object_unchanged(): + """ + The plain json_object form keeps working as before. + """ + config = FireworksAIConfig() + result = config.map_openai_params( + {"response_format": {"type": "json_object"}}, + {}, + "fireworks_ai/accounts/fireworks/models/qwen3-32b", + drop_params=False, + ) + assert result == {"response_format": {"type": "json_object"}} diff --git a/tests/test_litellm/llms/gemini/videos/test_gemini_video_transformation.py b/tests/test_litellm/llms/gemini/videos/test_gemini_video_transformation.py index 4cf2429d737..6f215deed4e 100644 --- a/tests/test_litellm/llms/gemini/videos/test_gemini_video_transformation.py +++ b/tests/test_litellm/llms/gemini/videos/test_gemini_video_transformation.py @@ -2,6 +2,7 @@ Tests for Gemini (Veo) video generation transformation. """ +import io import json import os from unittest.mock import MagicMock, Mock, patch @@ -132,6 +133,87 @@ class TestGeminiVideoConfig: assert data["parameters"]["durationSeconds"] == 8 assert data["parameters"]["resolution"] == "1080p" + def test_transform_video_create_request_image_goes_to_instance(self): + """Image belongs in instances[0], not in parameters (per Veo API).""" + prompt = "Animate this still" + api_base = "https://generativelanguage.googleapis.com/v1beta/models/veo-3.0-generate-preview:predictLongRunning" + image_dict = {"bytesBase64Encoded": "aGVsbG8=", "mimeType": "image/jpeg"} + + data, _, _ = self.config.transform_video_create_request( + model="veo-3.0-generate-preview", + prompt=prompt, + api_base=api_base, + video_create_optional_request_params={ + "image": image_dict, + "aspectRatio": "16:9", + "durationSeconds": 4, + }, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + assert data["instances"][0]["prompt"] == prompt + assert data["instances"][0]["image"] == image_dict + assert "image" not in data.get("parameters", {}) + assert data["parameters"]["aspectRatio"] == "16:9" + assert data["parameters"]["durationSeconds"] == 4 + + def test_transform_video_create_request_image_filelike_goes_to_instance(self): + """File-like image (BytesIO) gets base64-encoded into instances[0]['image'].""" + prompt = "Animate this still" + api_base = "https://generativelanguage.googleapis.com/v1beta/models/veo-3.0-generate-preview:predictLongRunning" + # 1x1 PNG (8 bytes after magic + minimal IHDR is not legal — but the + # transformer only cares that ImageEditRequestUtils can sniff a MIME and + # that .read() returns bytes; an explicit name="image.jpeg" hands the + # MIME sniffer a clean answer regardless of payload). + image_bytes = b"\xff\xd8\xff\xe0fake-jpeg-bytes" + image_file = io.BytesIO(image_bytes) + image_file.name = "still.jpeg" + + data, _, _ = self.config.transform_video_create_request( + model="veo-3.0-generate-preview", + prompt=prompt, + api_base=api_base, + video_create_optional_request_params={ + "image": image_file, + "aspectRatio": "16:9", + }, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + # File-like took the _convert_image_to_gemini_format branch and landed + # in instances[0]["image"], not in parameters. + instance_image = data["instances"][0]["image"] + assert isinstance(instance_image, dict) + assert instance_image["mimeType"].startswith("image/") + assert instance_image["bytesBase64Encoded"] + # Round-trip the base64 — should equal the original bytes. + import base64 + + assert base64.b64decode(instance_image["bytesBase64Encoded"]) == image_bytes + assert "image" not in data.get("parameters", {}) + + def test_transform_video_create_request_image_none_is_dropped(self): + """Explicit image=None is popped and never reaches parameters.""" + prompt = "no image at all" + api_base = "https://generativelanguage.googleapis.com/v1beta/models/veo-3.0-generate-preview:predictLongRunning" + + data, _, _ = self.config.transform_video_create_request( + model="veo-3.0-generate-preview", + prompt=prompt, + api_base=api_base, + video_create_optional_request_params={ + "image": None, + "aspectRatio": "16:9", + }, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + assert "image" not in data["instances"][0] + assert "image" not in data.get("parameters", {}) + def test_map_openai_params(self): """Test parameter mapping from OpenAI format to Veo format.""" openai_params = { diff --git a/tests/test_litellm/llms/huggingface/embedding/test_huggingface_embedding_handler.py b/tests/test_litellm/llms/huggingface/embedding/test_huggingface_embedding_handler.py index 560796ea58d..8a072fa5097 100644 --- a/tests/test_litellm/llms/huggingface/embedding/test_huggingface_embedding_handler.py +++ b/tests/test_litellm/llms/huggingface/embedding/test_huggingface_embedding_handler.py @@ -104,6 +104,23 @@ class TestHuggingFaceEmbedding: assert "source_sentence" not in str(request_data) assert "sentences" not in str(request_data) + def test_embedding_allows_special_token_looking_input(self): + input_text = ["hello <|fim_prefix|> world"] + + response = litellm.embedding( + model=self.model, + input=input_text, + input_type="embed", + ) + + self.mock_http.assert_called_once() + post_call_args = self.mock_http.call_args + request_data = json.loads(post_call_args[1]["data"]) + + assert request_data["inputs"] == input_text + assert response.usage.prompt_tokens > 0 + assert response.usage.total_tokens == response.usage.prompt_tokens + def test_embedding_with_sentence_similarity_task(self): """Test embedding when task type is sentence-similarity (requires 2+ sentences)""" diff --git a/tests/test_litellm/llms/vertex_ai/context_caching/test_vertex_ai_context_caching.py b/tests/test_litellm/llms/vertex_ai/context_caching/test_vertex_ai_context_caching.py index 6f32c4ca340..74888e6cd9e 100644 --- a/tests/test_litellm/llms/vertex_ai/context_caching/test_vertex_ai_context_caching.py +++ b/tests/test_litellm/llms/vertex_ai/context_caching/test_vertex_ai_context_caching.py @@ -201,9 +201,12 @@ class TestContextCachingEndpoints: assert returned_params == optional_params assert returned_cache == "existing_cache_name" - # Verify cache key was generated with tools and model + # Verify cache key was generated with tools, tool_choice and model mock_cache_obj.get_cache_key.assert_called_once_with( - messages=cached_messages, tools=self.sample_tools, model="gemini-1.5-pro" + messages=cached_messages, + tools=self.sample_tools, + tool_choice=None, + model="gemini-1.5-pro", ) @pytest.mark.parametrize( @@ -474,9 +477,12 @@ class TestContextCachingEndpoints: assert returned_params == optional_params assert returned_cache == "existing_cache_name" - # Verify cache key was generated with tools and model + # Verify cache key was generated with tools, tool_choice and model mock_cache_obj.get_cache_key.assert_called_once_with( - messages=cached_messages, tools=self.sample_tools, model="gemini-1.5-pro" + messages=cached_messages, + tools=self.sample_tools, + tool_choice=None, + model="gemini-1.5-pro", ) @pytest.mark.asyncio @@ -800,6 +806,546 @@ class TestContextCachingEndpoints: # But original tools should still be available for comparison assert original_tools == self.sample_tools + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + def test_check_and_create_cache_tool_choice_popped_from_optional_params( + self, custom_llm_provider + ): + """tool_choice is popped from optional_params when cached messages exist.""" + with patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) as mock_separate: + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = {"functionCallingConfig": {"mode": "ANY"}} + + with patch.object( + self.context_caching, "check_cache", return_value="existing_cache" + ): + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + assert "tool_choice" not in optional_params + + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + def test_check_and_create_cache_tool_choice_not_popped_when_no_cached_messages( + self, custom_llm_provider + ): + """tool_choice is NOT popped when there are no cached messages (early return).""" + with patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) as mock_separate: + mock_separate.return_value = ([], self.sample_messages) + + tool_choice = {"functionCallingConfig": {"mode": "AUTO"}} + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = tool_choice + + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + assert optional_params.get("tool_choice") == tool_choice + + @pytest.mark.asyncio + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + async def test_async_check_and_create_cache_tool_choice_popped_from_optional_params( + self, custom_llm_provider + ): + """Async equivalent of test_check_and_create_cache_tool_choice_popped_from_optional_params.""" + with patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) as mock_separate: + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = {"functionCallingConfig": {"mode": "ANY"}} + + with patch.object( + self.context_caching, "async_check_cache", return_value="existing_cache" + ): + await self.context_caching.async_check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_async_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + assert "tool_choice" not in optional_params + + @pytest.mark.asyncio + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + async def test_async_check_and_create_cache_tool_choice_not_popped_when_no_cached_messages( + self, custom_llm_provider + ): + """Async equivalent of test_check_and_create_cache_tool_choice_not_popped_when_no_cached_messages.""" + with patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) as mock_separate: + mock_separate.return_value = ([], self.sample_messages) + + tool_choice = {"functionCallingConfig": {"mode": "AUTO"}} + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = tool_choice + + await self.context_caching.async_check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_async_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + assert optional_params.get("tool_choice") == tool_choice + + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.local_cache_obj" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.transform_openai_messages_to_gemini_context_caching" + ) + @patch.object(ContextCachingEndpoints, "check_cache") + @patch.object(ContextCachingEndpoints, "_get_token_and_url_context_caching") + def test_check_and_create_cache_tool_choice_in_request_body( + self, + mock_get_token_url, + mock_check_cache, + mock_transform, + mock_cache_obj, + mock_separate, + custom_llm_provider, + ): + """End-to-end: tool_choice ends up as `toolConfig` on the cache-creation HTTP POST body.""" + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + mock_cache_obj.get_cache_key.return_value = "test_cache_key" + mock_check_cache.return_value = None # cache miss -> create new + mock_get_token_url.return_value = ("token", "https://test-url.com") + mock_transform.return_value = {"model": "gemini-1.5-pro", "contents": []} + + mock_response = MagicMock() + mock_response.json.return_value = { + "name": "new_cache_name", + "model": "gemini-1.5-pro", + } + self.mock_client.post.return_value = mock_response + + tool_choice = {"functionCallingConfig": {"mode": "ANY"}} + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = tool_choice + + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + self.mock_client.post.assert_called_once() + call_args = self.mock_client.post.call_args + assert call_args.kwargs["json"]["tools"] == self.sample_tools + assert call_args.kwargs["json"]["toolConfig"] == tool_choice + mock_cache_obj.get_cache_key.assert_called_once_with( + messages=cached_messages, + tools=self.sample_tools, + tool_choice=tool_choice, + model="gemini-1.5-pro", + ) + + @pytest.mark.asyncio + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.local_cache_obj" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.transform_openai_messages_to_gemini_context_caching" + ) + @patch.object(ContextCachingEndpoints, "async_check_cache") + @patch.object(ContextCachingEndpoints, "_get_token_and_url_context_caching") + async def test_async_check_and_create_cache_tool_choice_in_request_body( + self, + mock_get_token_url, + mock_check_cache, + mock_transform, + mock_cache_obj, + mock_separate, + custom_llm_provider, + ): + """Async equivalent of test_check_and_create_cache_tool_choice_in_request_body.""" + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + mock_cache_obj.get_cache_key.return_value = "test_cache_key" + mock_check_cache.return_value = None + mock_get_token_url.return_value = ("token", "https://test-url.com") + mock_transform.return_value = {"model": "gemini-1.5-pro", "contents": []} + + mock_response = MagicMock() + mock_response.json.return_value = { + "name": "new_cache_name", + "model": "gemini-1.5-pro", + } + self.mock_async_client.post = AsyncMock(return_value=mock_response) + + tool_choice = {"functionCallingConfig": {"mode": "ANY"}} + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = tool_choice + + await self.context_caching.async_check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_async_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + call_args = self.mock_async_client.post.call_args + assert call_args.kwargs["json"]["tools"] == self.sample_tools + assert call_args.kwargs["json"]["toolConfig"] == tool_choice + mock_cache_obj.get_cache_key.assert_called_once_with( + messages=cached_messages, + tools=self.sample_tools, + tool_choice=tool_choice, + model="gemini-1.5-pro", + ) + + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.local_cache_obj" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.transform_openai_messages_to_gemini_context_caching" + ) + @patch.object(ContextCachingEndpoints, "check_cache") + @patch.object(ContextCachingEndpoints, "_get_token_and_url_context_caching") + def test_check_and_create_cache_omits_tool_config_when_tool_choice_unset( + self, + mock_get_token_url, + mock_check_cache, + mock_transform, + mock_cache_obj, + mock_separate, + custom_llm_provider, + ): + """When the caller didn't pass tool_choice, toolConfig must NOT appear in the cache body.""" + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + mock_cache_obj.get_cache_key.return_value = "test_cache_key" + mock_check_cache.return_value = None + mock_get_token_url.return_value = ("token", "https://test-url.com") + mock_transform.return_value = {"model": "gemini-1.5-pro", "contents": []} + + mock_response = MagicMock() + mock_response.json.return_value = { + "name": "new_cache_name", + "model": "gemini-1.5-pro", + } + self.mock_client.post.return_value = mock_response + + optional_params = self.sample_optional_params.copy() + + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + call_args = self.mock_client.post.call_args + assert "tools" in call_args.kwargs["json"] + assert "toolConfig" not in call_args.kwargs["json"] + + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.local_cache_obj" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.transform_openai_messages_to_gemini_context_caching" + ) + @patch.object(ContextCachingEndpoints, "check_cache") + @patch.object(ContextCachingEndpoints, "_get_token_and_url_context_caching") + def test_check_and_create_cache_tool_choice_function_pin( + self, + mock_get_token_url, + mock_check_cache, + mock_transform, + mock_cache_obj, + mock_separate, + custom_llm_provider, + ): + """tool_choice as a function-pin dict survives the cache body intact.""" + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + mock_cache_obj.get_cache_key.return_value = "test_cache_key" + mock_check_cache.return_value = None + mock_get_token_url.return_value = ("token", "https://test-url.com") + mock_transform.return_value = {"model": "gemini-1.5-pro", "contents": []} + + mock_response = MagicMock() + mock_response.json.return_value = { + "name": "new_cache_name", + "model": "gemini-1.5-pro", + } + self.mock_client.post.return_value = mock_response + + function_pin = { + "functionCallingConfig": { + "mode": "ANY", + "allowed_function_names": ["get_current_weather"], + } + } + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = function_pin + + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + call_args = self.mock_client.post.call_args + assert call_args.kwargs["json"]["toolConfig"] == function_pin + + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.local_cache_obj" + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.transform_openai_messages_to_gemini_context_caching" + ) + @patch.object(ContextCachingEndpoints, "check_cache") + @patch.object(ContextCachingEndpoints, "_get_token_and_url_context_caching") + def test_check_and_create_cache_tool_choice_typed_constructor( + self, + mock_get_token_url, + mock_check_cache, + mock_transform, + mock_cache_obj, + mock_separate, + custom_llm_provider, + ): + """Exercise the actual ToolConfig(FunctionCallingConfig(...)) constructor that map_tool_choice_values produces. + + ToolConfig / FunctionCallingConfig are TypedDicts (litellm/types/llms/vertex_ai.py:158, 277) + so this is functionally identical to the dict-literal tests above at + runtime — but exercising the typed constructor pins the test to the + same call shape map_tool_choice_values uses and auto-follows if + either type ever migrates to a Pydantic model upstream. + """ + from litellm.types.llms.vertex_ai import ( + FunctionCallingConfig, + ToolConfig, + ) + + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + mock_cache_obj.get_cache_key.return_value = "test_cache_key" + mock_check_cache.return_value = None + mock_get_token_url.return_value = ("token", "https://test-url.com") + mock_transform.return_value = {"model": "gemini-1.5-pro", "contents": []} + + mock_response = MagicMock() + mock_response.json.return_value = { + "name": "new_cache_name", + "model": "gemini-1.5-pro", + } + self.mock_client.post.return_value = mock_response + + tool_choice = ToolConfig( + functionCallingConfig=FunctionCallingConfig(mode="ANY") + ) + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = tool_choice + + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + call_args = self.mock_client.post.call_args + assert call_args.kwargs["json"]["toolConfig"] == tool_choice + assert call_args.kwargs["json"]["toolConfig"] == { + "functionCallingConfig": {"mode": "ANY"} + } + mock_cache_obj.get_cache_key.assert_called_once_with( + messages=cached_messages, + tools=self.sample_tools, + tool_choice=tool_choice, + model="gemini-1.5-pro", + ) + + @pytest.mark.parametrize( + "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] + ) + @patch( + "litellm.llms.vertex_ai.context_caching.vertex_ai_context_caching.separate_cached_messages" + ) + @patch.object(ContextCachingEndpoints, "check_cache") + def test_check_and_create_cache_distinct_tool_choices_use_distinct_keys( + self, + mock_check_cache, + mock_separate, + custom_llm_provider, + ): + """Two requests with different tool_choice values must produce different cache keys. + + Runs the real local_cache_obj.get_cache_key to verify the hashed + output actually differs — mocking it would only prove that distinct + arguments are forwarded, not that they produce distinct keys. + """ + cached_messages = [self.sample_messages[0]] + non_cached_messages = [self.sample_messages[1]] + mock_separate.return_value = (cached_messages, non_cached_messages) + mock_check_cache.return_value = "existing_cache" + + auto_tool_choice = {"functionCallingConfig": {"mode": "AUTO"}} + any_tool_choice = {"functionCallingConfig": {"mode": "ANY"}} + for choice in (auto_tool_choice, any_tool_choice): + optional_params = self.sample_optional_params.copy() + optional_params["tool_choice"] = choice + self.context_caching.check_and_create_cache( + messages=self.sample_messages, + optional_params=optional_params, + api_key="test_key", + api_base=None, + model="gemini-1.5-pro", + client=self.mock_client, + timeout=30.0, + logging_obj=self.mock_logging, + custom_llm_provider=custom_llm_provider, + vertex_project="test_project", + vertex_location="test_location", + vertex_auth_header="vertext_test_token", + ) + + check_cache_calls = mock_check_cache.call_args_list + assert len(check_cache_calls) == 2 + first_cache_key = check_cache_calls[0].kwargs["cache_key"] + second_cache_key = check_cache_calls[1].kwargs["cache_key"] + assert first_cache_key != second_cache_key + @pytest.mark.parametrize( "custom_llm_provider", ["gemini", "vertex_ai", "vertex_ai_beta"] ) diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_elicitation_handler.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_elicitation_handler.py new file mode 100644 index 00000000000..b93f0d56f8e --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_elicitation_handler.py @@ -0,0 +1,211 @@ +""" +Tests for the MCP elicitation handler. + +Covers the gateway-mode relay logic (`elicitation/create` requests from an +upstream MCP server being forwarded to the connected downstream client) as +well as the decline paths used in tool-bridge mode or when the downstream +client lacks the requested elicitation capability. +""" + +from types import SimpleNamespace +from unittest.mock import AsyncMock + +import pytest + +from mcp.types import ( + ElicitRequestFormParams, + ElicitRequestURLParams, + ElicitResult, + ErrorData, +) + +from litellm.proxy._experimental.mcp_server import elicitation_handler +from litellm.proxy._experimental.mcp_server.elicitation_handler import ( + _relay_elicitation_to_downstream, + handle_elicitation_request, +) + + +def _form_params(message: str = "fill the form") -> ElicitRequestFormParams: + return ElicitRequestFormParams( + mode="form", + message=message, + requestedSchema={"type": "object", "properties": {}}, + ) + + +def _url_params(message: str = "please authorize") -> ElicitRequestURLParams: + return ElicitRequestURLParams( + mode="url", + message=message, + url="https://example.com/oauth", + elicitationId="elc-1", + ) + + +def _caps(*, url=True, form=True) -> SimpleNamespace: + elicit = SimpleNamespace( + url=object() if url else None, + form=object() if form else None, + ) + return SimpleNamespace(elicitation=elicit) + + +class TestHandleElicitationRequest: + async def test_should_decline_when_no_downstream_session(self): + result = await handle_elicitation_request( + context=SimpleNamespace(), + params=_form_params(), + downstream_session=None, + ) + assert isinstance(result, ElicitResult) + assert result.action == "decline" + + async def test_should_relay_to_downstream_when_session_present(self): + accepted = ElicitResult(action="accept", content={"name": "ada"}) + session = SimpleNamespace(elicit_form=AsyncMock(return_value=accepted)) + + result = await handle_elicitation_request( + context=SimpleNamespace(), + params=_form_params(), + downstream_session=session, + downstream_capabilities=None, + ) + + assert result is accepted + session.elicit_form.assert_awaited_once() + + async def test_should_return_error_data_when_unavailable(self, monkeypatch): + monkeypatch.setattr(elicitation_handler, "MCP_ELICITATION_AVAILABLE", False) + result = await handle_elicitation_request( + context=SimpleNamespace(), + params=_form_params(), + downstream_session=SimpleNamespace(), + ) + assert isinstance(result, ErrorData) + assert "not available" in result.message + + async def test_should_return_error_data_on_unexpected_failure(self): + class _ExplodingParams: + mode = "form" + + @property + def message(self): + raise RuntimeError("boom") + + result = await handle_elicitation_request( + context=SimpleNamespace(), + params=_ExplodingParams(), + downstream_session=None, + ) + assert isinstance(result, ErrorData) + assert "boom" in result.message + + +class TestRelayElicitationToDownstream: + async def test_should_relay_form_mode(self): + accepted = ElicitResult(action="accept", content={"name": "ada"}) + session = SimpleNamespace(elicit_form=AsyncMock(return_value=accepted)) + + params = _form_params("collect name") + result = await _relay_elicitation_to_downstream( + params=params, + downstream_session=session, + downstream_capabilities=_caps(form=True), + ) + + assert result is accepted + session.elicit_form.assert_awaited_once() + _, kwargs = session.elicit_form.call_args + assert kwargs["message"] == "collect name" + assert kwargs["requestedSchema"] == params.requestedSchema + + async def test_should_relay_url_mode(self): + accepted = ElicitResult(action="accept") + session = SimpleNamespace(elicit_url=AsyncMock(return_value=accepted)) + + result = await _relay_elicitation_to_downstream( + params=_url_params(), + downstream_session=session, + downstream_capabilities=_caps(url=True), + ) + + assert result is accepted + session.elicit_url.assert_awaited_once() + _, kwargs = session.elicit_url.call_args + assert kwargs["url"] == "https://example.com/oauth" + assert kwargs["elicitation_id"] == "elc-1" + + async def test_should_use_generic_elicit_for_unknown_param_type(self): + accepted = ElicitResult(action="accept") + session = SimpleNamespace(elicit=AsyncMock(return_value=accepted)) + + # A bare params object that is neither Form nor URL params triggers + # the generic fallback path. + params = SimpleNamespace(mode="form", message="hi", requestedSchema={}) + result = await _relay_elicitation_to_downstream( + params=params, + downstream_session=session, + downstream_capabilities=None, + ) + + assert result is accepted + session.elicit.assert_awaited_once() + + async def test_should_decline_when_elicitation_unsupported(self): + session = SimpleNamespace(elicit_form=AsyncMock()) + caps = SimpleNamespace(elicitation=None) + + result = await _relay_elicitation_to_downstream( + params=_form_params(), + downstream_session=session, + downstream_capabilities=caps, + ) + + assert isinstance(result, ElicitResult) + assert result.action == "decline" + session.elicit_form.assert_not_awaited() + + async def test_should_decline_url_mode_when_url_unsupported(self): + session = SimpleNamespace(elicit_url=AsyncMock()) + + result = await _relay_elicitation_to_downstream( + params=_url_params(), + downstream_session=session, + downstream_capabilities=_caps(url=False, form=True), + ) + + assert isinstance(result, ElicitResult) + assert result.action == "decline" + session.elicit_url.assert_not_awaited() + + async def test_should_decline_form_mode_when_form_unsupported(self): + session = SimpleNamespace(elicit_form=AsyncMock()) + + result = await _relay_elicitation_to_downstream( + params=_form_params(), + downstream_session=session, + downstream_capabilities=_caps(url=True, form=False), + ) + + assert isinstance(result, ElicitResult) + assert result.action == "decline" + session.elicit_form.assert_not_awaited() + + async def test_should_decline_when_downstream_relay_raises(self): + session = SimpleNamespace( + elicit_form=AsyncMock(side_effect=RuntimeError("transport closed")) + ) + + result = await _relay_elicitation_to_downstream( + params=_form_params(), + downstream_session=session, + downstream_capabilities=_caps(form=True), + ) + + assert isinstance(result, ElicitResult) + assert result.action == "decline" + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py index 04ff1e4be20..363948ff4e6 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py @@ -16,7 +16,6 @@ from typing import Any, Dict, Optional from unittest.mock import AsyncMock, MagicMock, patch import pytest -from fastapi import HTTPException from litellm.proxy._experimental.mcp_server.mcp_server_manager import MCPServerManager from litellm.proxy._types import UserAPIKeyAuth @@ -549,11 +548,7 @@ class TestHookHeaderMergePriority: captured_extra_headers: Dict[str, Any] = {} async def fake_create_mcp_client( - server, - mcp_auth_header=None, - extra_headers=None, - stdio_env=None, - subject_token=None, + server, mcp_auth_header=None, extra_headers=None, stdio_env=None, **kwargs ): captured_extra_headers["value"] = extra_headers mock_client = MagicMock() @@ -593,11 +588,7 @@ class TestHookHeaderMergePriority: captured_extra_headers: Dict[str, Any] = {} async def fake_create_mcp_client( - server, - mcp_auth_header=None, - extra_headers=None, - stdio_env=None, - subject_token=None, + server, mcp_auth_header=None, extra_headers=None, stdio_env=None, **kwargs ): captured_extra_headers["value"] = extra_headers mock_client = MagicMock() @@ -643,11 +634,7 @@ class TestHookHeaderMergePriority: captured_extra_headers: Dict[str, Any] = {} async def fake_create_mcp_client( - server, - mcp_auth_header=None, - extra_headers=None, - stdio_env=None, - subject_token=None, + server, mcp_auth_header=None, extra_headers=None, stdio_env=None, **kwargs ): captured_extra_headers["value"] = extra_headers mock_client = MagicMock() @@ -703,11 +690,7 @@ class TestHookHeaderMergePriority: captured_extra_headers: Dict[str, Any] = {} async def fake_create_mcp_client( - server, - mcp_auth_header=None, - extra_headers=None, - stdio_env=None, - subject_token=None, + server, mcp_auth_header=None, extra_headers=None, stdio_env=None, **kwargs ): captured_extra_headers["value"] = extra_headers mock_client = MagicMock() @@ -755,11 +738,7 @@ class TestHookHeaderMergePriority: captured_extra_headers: Dict[str, Any] = {} async def fake_create_mcp_client( - server, - mcp_auth_header=None, - extra_headers=None, - stdio_env=None, - subject_token=None, + server, mcp_auth_header=None, extra_headers=None, stdio_env=None, **kwargs ): captured_extra_headers["value"] = extra_headers mock_client = MagicMock() diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_completion_flow.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_completion_flow.py new file mode 100644 index 00000000000..78aee7b534f --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_completion_flow.py @@ -0,0 +1,254 @@ +""" +Tests for the MCP sampling completion pipeline. + +Covers building the internal `acompletion` kwargs from MCP request params +(messages, sampling options, tools, tool choice, metadata), routing the call +through the proxy router / guardrails, and the end-to-end +`handle_sampling_create_message` success and error-propagation behaviour. +""" + +from types import SimpleNamespace +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from mcp.types import CreateMessageResult, ErrorData + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _build_completion_kwargs, + _run_guardrails_and_call_llm, + handle_sampling_create_message, +) + + +def _params(**overrides): + base = dict( + messages=[ + SimpleNamespace( + role="user", content=SimpleNamespace(type="text", text="hi") + ) + ], + systemPrompt="be concise", + maxTokens=128, + temperature=None, + stopSequences=None, + tools=None, + toolChoice=None, + metadata=None, + modelPreferences=None, + ) + base.update(overrides) + return SimpleNamespace(**base) + + +def _passthrough_add_data(): + async def _add(data, **kwargs): + return data + + return _add + + +class TestBuildCompletionKwargs: + async def test_should_include_sampling_options_and_tools(self): + params = _params( + temperature=0.3, + stopSequences=["STOP"], + tools=[ + SimpleNamespace( + name="search", description="d", inputSchema={"type": "object"} + ) + ], + toolChoice=SimpleNamespace(mode="required"), + metadata={"trace": "abc"}, + ) + with patch( + "litellm.proxy.litellm_pre_call_utils.add_litellm_data_to_request", + side_effect=_passthrough_add_data(), + ): + kwargs = await _build_completion_kwargs( + params=params, + model="gpt-4o", + user_api_key_auth=SimpleNamespace(user_id="u1"), + raw_headers=None, + client_ip=None, + ) + + assert kwargs["model"] == "gpt-4o" + assert kwargs["max_tokens"] == 128 + assert kwargs["temperature"] == 0.3 + assert kwargs["stop"] == ["STOP"] + assert kwargs["tools"][0]["function"]["name"] == "search" + assert kwargs["tool_choice"] == "required" + assert kwargs["metadata"]["mcp_metadata"] == {"trace": "abc"} + assert kwargs["user"] == "u1" + assert kwargs["messages"][0] == {"role": "system", "content": "be concise"} + + async def test_should_omit_optional_fields_when_unset(self): + with patch( + "litellm.proxy.litellm_pre_call_utils.add_litellm_data_to_request", + side_effect=_passthrough_add_data(), + ): + kwargs = await _build_completion_kwargs( + params=_params(), + model="gpt-4o", + user_api_key_auth=SimpleNamespace(user_id=None), + raw_headers=None, + client_ip=None, + ) + + assert "temperature" not in kwargs + assert "stop" not in kwargs + assert "tools" not in kwargs + assert "tool_choice" not in kwargs + assert kwargs["metadata"] == {} + + +class TestRunGuardrailsAndCallLlm: + async def test_should_route_through_llm_router_when_available(self): + router = MagicMock() + router.acompletion = AsyncMock(return_value="router-response") + with ( + patch("litellm.proxy.proxy_server.proxy_logging_obj", None), + patch("litellm.proxy.proxy_server.llm_router", router), + ): + result = await _run_guardrails_and_call_llm( + completion_kwargs={"model": "gpt-4o", "messages": []}, + user_api_key_auth=SimpleNamespace(), + ) + + assert result == "router-response" + router.acompletion.assert_awaited_once() + + async def test_should_propagate_guardrail_rejection(self): + plo = MagicMock() + plo.pre_call_hook = AsyncMock(side_effect=ValueError("blocked by guardrail")) + with patch("litellm.proxy.proxy_server.proxy_logging_obj", plo): + with pytest.raises(ValueError, match="blocked by guardrail"): + await _run_guardrails_and_call_llm( + completion_kwargs={"model": "gpt-4o", "messages": []}, + user_api_key_auth=SimpleNamespace(), + ) + + +class TestHandleSamplingCreateMessagePipeline: + async def test_should_return_message_result_on_success(self): + auth = SimpleNamespace(user_id="u1", api_key="sk-test", token="tok") + response = SimpleNamespace( + choices=[ + SimpleNamespace( + message=SimpleNamespace( + content="the answer is 42", tool_calls=None + ), + finish_reason="stop", + ) + ], + model="gpt-4o", + ) + with ( + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._resolve_model_from_preferences", + return_value="gpt-4o", + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._check_model_access", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._run_budget_checks", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._build_completion_kwargs", + new_callable=AsyncMock, + return_value={"model": "gpt-4o", "messages": []}, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._run_guardrails_and_call_llm", + new_callable=AsyncMock, + return_value=response, + ), + ): + result = await handle_sampling_create_message( + context=MagicMock(), + params=_params(), + default_model="gpt-4o", + user_api_key_auth=auth, + ) + + assert isinstance(result, CreateMessageResult) + assert result.content.text == "the answer is 42" + assert result.stopReason == "endTurn" + + async def test_should_reraise_known_proxy_exceptions(self): + from litellm.exceptions import RateLimitError + + auth = SimpleNamespace(user_id="u1", api_key="sk-test", token="tok") + with ( + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._resolve_model_from_preferences", + return_value="gpt-4o", + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._check_model_access", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._run_budget_checks", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._build_completion_kwargs", + new_callable=AsyncMock, + side_effect=RateLimitError( + "rate limited", llm_provider="openai", model="gpt-4o" + ), + ), + ): + with pytest.raises(RateLimitError): + await handle_sampling_create_message( + context=MagicMock(), + params=_params(), + default_model="gpt-4o", + user_api_key_auth=auth, + ) + + async def test_should_return_error_data_on_unexpected_failure(self): + auth = SimpleNamespace(user_id="u1", api_key="sk-test", token="tok") + with ( + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._resolve_model_from_preferences", + return_value="gpt-4o", + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._check_model_access", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._run_budget_checks", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._build_completion_kwargs", + new_callable=AsyncMock, + side_effect=RuntimeError("kaboom"), + ), + ): + result = await handle_sampling_create_message( + context=MagicMock(), + params=_params(), + default_model="gpt-4o", + user_api_key_auth=auth, + ) + + assert isinstance(result, ErrorData) + assert "kaboom" in result.message + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_access.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_access.py new file mode 100644 index 00000000000..f141cb2e316 --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_access.py @@ -0,0 +1,327 @@ +""" +Tests for MCP sampling handler model-access enforcement. + +Verifies that handle_sampling_create_message and _check_model_access +enforce the same model-permission checks as regular /chat/completions +calls, preventing a malicious upstream MCP server from requesting +inference on models the caller's API key is not authorized to use. +""" + +import pytest +from unittest.mock import AsyncMock, MagicMock, patch + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _check_model_access, +) + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +def _make_user_api_key_auth( + *, + models=None, + team_id=None, + team_model_aliases=None, + api_key="sk-test-key", + token=None, + user_role=None, +): + """Build a minimal UserAPIKeyAuth-like object for tests.""" + auth = MagicMock() + auth.models = models or [] + auth.team_id = team_id + auth.team_model_aliases = team_model_aliases or {} + auth.access_group_ids = [] + auth.api_key = api_key + auth.token = token + auth.user_role = user_role + return auth + + +# --------------------------------------------------------------------------- +# _check_model_access +# --------------------------------------------------------------------------- + + +class TestCheckModelAccess: + """Tests for the _check_model_access helper that gates sampling requests.""" + + @pytest.mark.asyncio + async def test_should_return_none_when_no_auth_context(self): + """No auth context means no restriction — pass through.""" + result = await _check_model_access("gpt-4o", user_api_key_auth=None) + assert result is None + + @pytest.mark.asyncio + async def test_should_allow_model_when_key_has_access(self): + """Key with explicit model access should be allowed.""" + auth = _make_user_api_key_auth(models=["gpt-4o", "gpt-3.5-turbo"]) + + with patch( + "litellm.proxy.auth.auth_checks.can_key_call_model", + new_callable=AsyncMock, + return_value=True, + ) as mock_check: + result = await _check_model_access("gpt-4o", user_api_key_auth=auth) + + assert result is None + mock_check.assert_awaited_once() + + @pytest.mark.asyncio + async def test_should_deny_model_when_key_lacks_access(self): + """Key without model access should be denied with ErrorData.""" + from litellm.proxy._types import ProxyException + + auth = _make_user_api_key_auth(models=["gpt-3.5-turbo"]) + + with patch( + "litellm.proxy.auth.auth_checks.can_key_call_model", + new_callable=AsyncMock, + side_effect=ProxyException( + message="key not allowed to access model", + type="key_model_access_denied", + param="model", + code=401, + ), + ): + result = await _check_model_access("gpt-4o", user_api_key_auth=auth) + + # Should return ErrorData, not raise + assert result is not None + assert result.code == -1 + assert "Model access denied" in result.message + assert "gpt-4o" in result.message + + @pytest.mark.asyncio + async def test_should_allow_wildcard_model_access(self): + """Key with wildcard model access should allow any model.""" + auth = _make_user_api_key_auth(models=["*"]) + + with patch( + "litellm.proxy.auth.auth_checks.can_key_call_model", + new_callable=AsyncMock, + return_value=True, + ): + result = await _check_model_access( + "claude-3-opus-20240229", user_api_key_auth=auth + ) + + assert result is None + + @pytest.mark.asyncio + async def test_should_deny_expensive_model_requested_by_malicious_server(self): + """Simulates the attack: malicious MCP server hints at an expensive model + the caller's key is restricted from using.""" + from litellm.proxy._types import ProxyException + + # Key only has access to cheap models + auth = _make_user_api_key_auth(models=["gpt-3.5-turbo"]) + + with patch( + "litellm.proxy.auth.auth_checks.can_key_call_model", + new_callable=AsyncMock, + side_effect=ProxyException( + message="key not allowed to access model. This key can only access models=['gpt-3.5-turbo']. Tried to access claude-3-opus-20240229", + type="key_model_access_denied", + param="model", + code=401, + ), + ): + result = await _check_model_access( + "claude-3-opus-20240229", user_api_key_auth=auth + ) + + assert result is not None + assert result.code == -1 + assert "claude-3-opus-20240229" in result.message + + @pytest.mark.asyncio + async def test_should_deny_empty_oauth_passthrough_placeholder(self): + """Regression: process_mcp_request() returns an empty UserAPIKeyAuth() + for OAuth2 upstream-token passthrough. The None check alone is not + sufficient — the empty placeholder is truthy but has no api_key, no + token, and an empty models list. can_key_call_model() would treat + that as all-model access, letting an OAuth-only user trigger sampling + calls on any proxy model without a LiteLLM key or budget.""" + # Simulate the empty placeholder from process_mcp_request() + auth = _make_user_api_key_auth( + models=[], + api_key=None, + token=None, + user_role=None, + ) + + result = await _check_model_access("gpt-4o", user_api_key_auth=auth) + + # Must be denied — not passed through to can_key_call_model + assert result is not None + assert result.code == -1 + assert "sampling requires a valid LiteLLM" in result.message + + @pytest.mark.asyncio + async def test_should_allow_proxy_admin_even_without_api_key(self): + """Proxy admins may not have a traditional api_key but should still + be allowed to use sampling.""" + auth = _make_user_api_key_auth( + models=[], + api_key=None, + token=None, + user_role="proxy_admin", + ) + + with patch( + "litellm.proxy.auth.auth_checks.can_key_call_model", + new_callable=AsyncMock, + return_value=True, + ): + result = await _check_model_access("gpt-4o", user_api_key_auth=auth) + + assert result is None + + +# --------------------------------------------------------------------------- +# handle_sampling_create_message — auth + budget gating +# --------------------------------------------------------------------------- + + +class TestSamplingAuthAndBudgetGating: + + @pytest.mark.asyncio + async def test_should_deny_when_no_auth_context(self): + """Sampling must reject calls with no user_api_key_auth.""" + from litellm.proxy._experimental.mcp_server.sampling_handler import ( + handle_sampling_create_message, + ) + + params = MagicMock() + params.modelPreferences = None + params.messages = [] + params.systemPrompt = None + params.maxTokens = 100 + params.temperature = None + params.stopSequences = None + params.tools = None + params.toolChoice = None + params.metadata = None + + result = await handle_sampling_create_message( + context=MagicMock(), + params=params, + default_model="gpt-4o", + user_api_key_auth=None, + ) + + assert result is not None + assert result.code == -1 + assert "authenticated" in result.message.lower() + + @pytest.mark.asyncio + async def test_should_run_budget_checks(self): + """Sampling must call _run_budget_checks after model access check.""" + from litellm.proxy._experimental.mcp_server.sampling_handler import ( + handle_sampling_create_message, + ) + + auth = _make_user_api_key_auth(models=["gpt-4o"]) + params = MagicMock() + params.modelPreferences = None + params.messages = [] + params.systemPrompt = None + params.maxTokens = 100 + params.temperature = None + params.stopSequences = None + params.tools = None + params.toolChoice = None + params.metadata = None + + with ( + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._check_model_access", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._run_budget_checks", + new_callable=AsyncMock, + return_value=None, + ) as mock_budget, + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._resolve_model_from_preferences", + return_value="gpt-4o", + ), + patch( + "litellm.proxy.proxy_server.llm_router", + new=None, + ), + patch( + "litellm.acompletion", + new_callable=AsyncMock, + return_value=MagicMock( + choices=[ + MagicMock( + message=MagicMock(content="hi", tool_calls=None), + finish_reason="stop", + ) + ], + model="gpt-4o", + ), + ), + ): + await handle_sampling_create_message( + context=MagicMock(), + params=params, + default_model="gpt-4o", + user_api_key_auth=auth, + ) + + mock_budget.assert_awaited_once() + + @pytest.mark.asyncio + async def test_should_deny_over_budget_caller(self): + """When _run_budget_checks returns ErrorData, sampling must return it.""" + from mcp.types import ErrorData + from litellm.proxy._experimental.mcp_server.sampling_handler import ( + handle_sampling_create_message, + ) + + auth = _make_user_api_key_auth(models=["gpt-4o"]) + params = MagicMock() + params.modelPreferences = None + params.messages = [] + params.systemPrompt = None + params.maxTokens = 100 + params.temperature = None + params.stopSequences = None + params.tools = None + params.toolChoice = None + params.metadata = None + + budget_error = ErrorData(code=-1, message="ExceededBudget: over limit") + + with ( + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._check_model_access", + new_callable=AsyncMock, + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._run_budget_checks", + new_callable=AsyncMock, + return_value=budget_error, + ), + patch( + "litellm.proxy._experimental.mcp_server.sampling_handler._resolve_model_from_preferences", + return_value="gpt-4o", + ), + ): + result = await handle_sampling_create_message( + context=MagicMock(), + params=params, + default_model="gpt-4o", + user_api_key_auth=auth, + ) + + assert result is budget_error + assert "ExceededBudget" in result.message diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_resolution.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_resolution.py new file mode 100644 index 00000000000..0c8f7bd4814 --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_model_resolution.py @@ -0,0 +1,91 @@ +""" +Tests for MCP sampling model resolution (hint matching and fallback chain). + +`_resolve_model_from_preferences` first tries to match upstream model hints +against the proxy's available models (direct then substring), then priority +scoring, then the caller default, the first available model, and finally the +configured `default_mcp_sampling_model` before raising. +""" + +from types import SimpleNamespace +from unittest.mock import MagicMock, patch + +import pytest + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _resolve_model_from_preferences, +) + + +def _prefs(*, hints=None, cost=None, speed=None, intelligence=None): + return SimpleNamespace( + hints=hints or [], + costPriority=cost, + speedPriority=speed, + intelligencePriority=intelligence, + ) + + +class TestHintMatching: + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch("litellm.model_list", [{"model_name": "gpt-4o"}, {"model_name": "claude-3"}]) + def test_should_match_hint_as_substring(self): + prefs = _prefs(hints=[SimpleNamespace(name="gpt-4")]) + assert _resolve_model_from_preferences(prefs) == "gpt-4o" + + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch("litellm.model_list", ["gpt-4o", "claude-3"]) + def test_should_match_hint_against_string_model_list_entries(self): + prefs = _prefs(hints=[SimpleNamespace(name="claude-3")]) + assert _resolve_model_from_preferences(prefs) == "claude-3" + + @patch("litellm.model_list", None) + def test_should_use_router_model_names(self): + router = MagicMock() + router.get_model_names.return_value = ["router-gpt", "router-claude"] + with patch("litellm.proxy.proxy_server.llm_router", router): + prefs = _prefs(hints=[SimpleNamespace(name="router-claude")]) + assert _resolve_model_from_preferences(prefs) == "router-claude" + + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch("litellm.model_list", [{"model_name": "gpt-4o"}]) + def test_should_skip_hint_without_name(self): + prefs = _prefs(hints=[SimpleNamespace()]) # hint has no `.name` + assert ( + _resolve_model_from_preferences(prefs, default_model="gpt-4o") == "gpt-4o" + ) + + +class TestFallbackChain: + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch( + "litellm.model_list", [{"model_name": "first-model"}, {"model_name": "second"}] + ) + def test_should_fall_back_to_first_available_when_no_default(self): + prefs = _prefs(hints=[SimpleNamespace(name="no-such")]) + assert _resolve_model_from_preferences(prefs) == "first-model" + + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch("litellm.model_list", []) + def test_should_use_configured_default_sampling_model(self, monkeypatch): + import litellm + + monkeypatch.setattr( + litellm, "default_mcp_sampling_model", "fallback-model", raising=False + ) + prefs = _prefs() + assert _resolve_model_from_preferences(prefs) == "fallback-model" + + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch("litellm.model_list", []) + def test_should_raise_when_nothing_resolvable(self, monkeypatch): + import litellm + + monkeypatch.setattr(litellm, "default_mcp_sampling_model", None, raising=False) + prefs = _prefs() + with pytest.raises(ValueError, match="No model could be resolved"): + _resolve_model_from_preferences(prefs) + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_priority_selection.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_priority_selection.py new file mode 100644 index 00000000000..24309ed0460 --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_priority_selection.py @@ -0,0 +1,248 @@ +""" +Tests for MCP sampling handler priority-based model selection. + +Verifies that _resolve_model_from_preferences honours costPriority, +speedPriority, and intelligencePriority when hints don't match, +per the MCP spec. +""" + +from types import SimpleNamespace +from unittest.mock import patch + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _has_priorities, + _resolve_model_from_preferences, + _select_model_by_priority, +) + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +def _prefs(*, hints=None, cost=None, speed=None, intelligence=None): + """Build a minimal ModelPreferences-like object.""" + return SimpleNamespace( + hints=hints or [], + costPriority=cost, + speedPriority=speed, + intelligencePriority=intelligence, + ) + + +# Model info stubs keyed by model name +_MODEL_INFO = { + "gpt-3.5-turbo": { + "input_cost_per_token": 0.0000005, + "output_cost_per_token": 0.0000015, + "max_output_tokens": 4096, + "max_tokens": 4096, + "output_tokens_per_second": 50.0, + }, + "gpt-4o": { + "input_cost_per_token": 0.0000025, + "output_cost_per_token": 0.0000100, + "max_output_tokens": 16384, + "max_tokens": 128000, + "output_tokens_per_second": 60.0, + }, + "claude-3-opus": { + "input_cost_per_token": 0.0000150, + "output_cost_per_token": 0.0000750, + "max_output_tokens": 4096, + "max_tokens": 200000, + "output_tokens_per_second": 20.0, + }, + "gpt-4o-mini": { + "input_cost_per_token": 0.00000015, + "output_cost_per_token": 0.0000006, + "max_output_tokens": 16384, + "max_tokens": 128000, + "output_tokens_per_second": 100.0, + }, +} + + +def _mock_get_model_info(model, **kwargs): + """Mock litellm.get_model_info using our test data.""" + if model in _MODEL_INFO: + return _MODEL_INFO[model] + raise Exception(f"Unknown model: {model}") + + +# --------------------------------------------------------------------------- +# _has_priorities +# --------------------------------------------------------------------------- + + +class TestHasPriorities: + def test_should_return_false_when_no_priorities_set(self): + prefs = _prefs() + assert _has_priorities(prefs) is False + + def test_should_return_false_when_all_zero(self): + prefs = _prefs(cost=0, speed=0, intelligence=0) + assert _has_priorities(prefs) is False + + def test_should_return_true_when_cost_set(self): + prefs = _prefs(cost=0.8) + assert _has_priorities(prefs) is True + + def test_should_return_true_when_intelligence_set(self): + prefs = _prefs(intelligence=0.5) + assert _has_priorities(prefs) is True + + +# --------------------------------------------------------------------------- +# _select_model_by_priority +# --------------------------------------------------------------------------- + + +class TestSelectModelByPriority: + """Tests for the priority-based scoring logic.""" + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + def test_should_prefer_cheapest_when_cost_priority_high(self, _mock): + """High costPriority should select the cheapest model.""" + prefs = _prefs(cost=1.0, speed=0, intelligence=0) + models = ["gpt-3.5-turbo", "gpt-4o", "claude-3-opus", "gpt-4o-mini"] + result = _select_model_by_priority(models, prefs) + # gpt-4o-mini has the lowest combined cost + assert result == "gpt-4o-mini" + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + def test_should_prefer_smartest_when_intelligence_priority_high(self, _mock): + """High intelligencePriority should select the model with highest max_output_tokens.""" + prefs = _prefs(cost=0, speed=0, intelligence=1.0) + models = ["gpt-3.5-turbo", "gpt-4o", "claude-3-opus", "gpt-4o-mini"] + result = _select_model_by_priority(models, prefs) + # gpt-4o and gpt-4o-mini both have 16384 max_output_tokens (tied) + # Either is acceptable + assert result in ("gpt-4o", "gpt-4o-mini") + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + def test_should_balance_cost_and_intelligence(self, _mock): + """Balanced priorities should pick a middle-ground model.""" + prefs = _prefs(cost=0.5, speed=0, intelligence=0.5) + models = ["gpt-3.5-turbo", "gpt-4o", "claude-3-opus", "gpt-4o-mini"] + result = _select_model_by_priority(models, prefs) + # gpt-4o-mini is cheap AND has high max_output_tokens → best balance + assert result == "gpt-4o-mini" + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + def test_should_prefer_fastest_when_speed_priority_high(self, _mock): + """High speedPriority should prefer cheaper (faster proxy) models.""" + prefs = _prefs(cost=0, speed=1.0, intelligence=0) + models = ["gpt-3.5-turbo", "gpt-4o", "claude-3-opus", "gpt-4o-mini"] + result = _select_model_by_priority(models, prefs) + # gpt-4o-mini has lowest cost → fastest proxy + assert result == "gpt-4o-mini" + + @patch( + "litellm.get_model_info", + side_effect=lambda m, **kw: (_ for _ in ()).throw(Exception("no info")), + ) + def test_should_return_none_when_no_model_info(self, _mock): + """If get_model_info fails for all models, return None.""" + prefs = _prefs(cost=1.0) + models = ["unknown-model-1", "unknown-model-2"] + result = _select_model_by_priority(models, prefs) + assert result is None + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + def test_should_handle_single_model(self, _mock): + """Single model should always be returned regardless of priorities.""" + prefs = _prefs(cost=1.0, intelligence=1.0) + result = _select_model_by_priority(["gpt-4o"], prefs) + assert result == "gpt-4o" + + def test_speed_priority_is_neutral_when_no_tps_data(self): + """When no candidate exposes output_tokens_per_second, speedPriority + must not fall back to context-window size as a latency proxy: that + biased selection toward the smallest-context model regardless of real + speed. With a neutral score the tie resolves to the first candidate, + so the larger-context model listed first is kept.""" + no_tps_info = { + "big-ctx": { + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + "max_output_tokens": 100000, + "max_tokens": 100000, + }, + "small-ctx": { + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + "max_output_tokens": 1000, + "max_tokens": 1000, + }, + } + + def info(model, **kwargs): + return no_tps_info[model] + + with patch("litellm.get_model_info", side_effect=info): + prefs = _prefs(speed=1.0) + # The inverse-max_output proxy would pick "small-ctx" here; a + # neutral score keeps the first candidate. + assert _select_model_by_priority(["big-ctx", "small-ctx"], prefs) == ( + "big-ctx" + ) + + +# --------------------------------------------------------------------------- +# _resolve_model_from_preferences — priority integration +# --------------------------------------------------------------------------- + + +class TestResolveModelPriorityIntegration: + """End-to-end tests for priority selection within _resolve_model_from_preferences.""" + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch( + "litellm.model_list", + [ + {"model_name": "gpt-3.5-turbo"}, + {"model_name": "gpt-4o"}, + {"model_name": "gpt-4o-mini"}, + ], + ) + def test_should_use_priority_when_hints_empty(self, _mock_info): + """With no hints but priorities set, should use priority-based selection.""" + prefs = _prefs(cost=1.0, speed=0, intelligence=0) + result = _resolve_model_from_preferences(prefs, default_model="gpt-4o") + # Should pick cheapest, NOT fall through to default_model + assert result == "gpt-4o-mini" + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch( + "litellm.model_list", + [ + {"model_name": "gpt-3.5-turbo"}, + {"model_name": "gpt-4o"}, + {"model_name": "gpt-4o-mini"}, + ], + ) + def test_should_skip_priority_when_no_priorities_set(self, _mock_info): + """With no priorities set, should fall through to default_model.""" + prefs = _prefs() # no priorities + result = _resolve_model_from_preferences(prefs, default_model="gpt-4o") + assert result == "gpt-4o" + + @patch("litellm.get_model_info", side_effect=_mock_get_model_info) + @patch("litellm.proxy.proxy_server.llm_router", None) + @patch( + "litellm.model_list", + [ + {"model_name": "gpt-3.5-turbo"}, + {"model_name": "gpt-4o"}, + {"model_name": "gpt-4o-mini"}, + ], + ) + def test_should_prefer_hint_over_priority(self, _mock_info): + """Hints should take precedence over priority-based selection.""" + hints = [SimpleNamespace(name="gpt-4o")] + prefs = _prefs(hints=hints, cost=1.0) # cost says cheap, but hint says gpt-4o + result = _resolve_model_from_preferences(prefs, default_model="gpt-3.5-turbo") + assert result == "gpt-4o" diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_request_builder.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_request_builder.py new file mode 100644 index 00000000000..d5c636baead --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_request_builder.py @@ -0,0 +1,147 @@ +""" +Tests for _build_sampling_request header forwarding. + +Verifies that the synthetic FastAPI Request built for sampling sub-calls +correctly propagates the original MCP connection's headers and client IP +so that header-dependent guardrails, routing hooks, and trace correlation +function correctly. +""" + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _build_sampling_request, +) + + +class TestBuildSamplingRequest: + """Tests for the _build_sampling_request helper.""" + + def test_should_include_content_type_by_default(self): + """Even with no raw headers, content-type must be present.""" + req = _build_sampling_request() + headers = dict(req.headers) + assert headers.get("content-type") == "application/json" + + def test_should_forward_raw_headers(self): + """Headers from the original MCP connection should be forwarded.""" + raw = { + "x-litellm-tags": "tag1,tag2", + "x-litellm-trace-id": "trace-abc-123", + "user-agent": "MCP-Client/1.0", + "authorization": "Bearer sk-test", + } + req = _build_sampling_request(raw_headers=raw) + headers = dict(req.headers) + + assert headers.get("x-litellm-tags") == "tag1,tag2" + assert headers.get("x-litellm-trace-id") == "trace-abc-123" + assert headers.get("user-agent") == "MCP-Client/1.0" + assert headers.get("authorization") == "Bearer sk-test" + + def test_should_skip_hop_by_hop_headers(self): + """content-length and transfer-encoding should not be forwarded.""" + raw = { + "content-length": "42", + "transfer-encoding": "chunked", + "x-custom": "keep-me", + } + req = _build_sampling_request(raw_headers=raw) + headers = dict(req.headers) + + assert "content-length" not in headers + assert "transfer-encoding" not in headers + assert headers.get("x-custom") == "keep-me" + + def test_should_not_duplicate_content_type(self): + """If raw_headers includes content-type, don't add it twice.""" + raw = {"content-type": "text/plain"} + req = _build_sampling_request(raw_headers=raw) + # Count how many content-type headers are present + ct_count = sum(1 for k, _ in req.scope["headers"] if k == b"content-type") + assert ct_count == 1 + + def test_should_inject_client_ip_as_x_forwarded_for(self): + """client_ip should be injected as x-forwarded-for.""" + req = _build_sampling_request(client_ip="10.0.0.42") + headers = dict(req.headers) + assert headers.get("x-forwarded-for") == "10.0.0.42" + + def test_should_not_override_existing_x_forwarded_for(self): + """Caller-supplied x-forwarded-for is stripped; resolved client_ip wins.""" + raw = {"x-forwarded-for": "192.168.1.1"} + req = _build_sampling_request(raw_headers=raw, client_ip="10.0.0.42") + headers = dict(req.headers) + assert headers.get("x-forwarded-for") == "10.0.0.42" + + def test_should_set_correct_path(self): + """The synthetic request should have the sampling path.""" + req = _build_sampling_request() + assert req.scope["path"] == "/mcp/sampling/createMessage" + + def test_server_should_default_to_litellm_port(self): + """Server tuple should use port 4000 (LiteLLM default), not 0.""" + req = _build_sampling_request() + _host, _port = req.scope["server"] + assert _port == 4000, f"Expected default LiteLLM port 4000, got {_port}" + + def test_should_populate_client_tuple_from_client_ip(self): + """request.client.host must return the real client IP for + IP-based routing and guardrails.""" + req = _build_sampling_request(client_ip="10.0.0.42") + assert req.scope.get("client") is not None + assert req.scope["client"][0] == "10.0.0.42" + # Verify request.client.host works (Starlette Address) + assert req.client is not None + assert req.client.host == "10.0.0.42" + + def test_should_not_set_client_when_no_ip(self): + """If no client_ip is provided, client should not be in scope.""" + req = _build_sampling_request() + assert "client" not in req.scope + + def test_should_skip_all_hop_by_hop_headers(self): + """All hop-by-hop headers must be filtered, not just content-length + and transfer-encoding.""" + raw = { + "content-length": "42", + "transfer-encoding": "chunked", + "connection": "keep-alive", + "keep-alive": "timeout=5", + "upgrade": "websocket", + "te": "trailers", + "trailer": "Expires", + "x-custom": "keep-me", + } + req = _build_sampling_request(raw_headers=raw) + headers = dict(req.headers) + + for hop_header in [ + "content-length", + "transfer-encoding", + "connection", + "keep-alive", + "upgrade", + "te", + "trailer", + ]: + assert ( + hop_header not in headers + ), f"Hop-by-hop header '{hop_header}' should be filtered" + assert headers.get("x-custom") == "keep-me" + + def test_should_forward_traceparent_header(self): + """traceparent header must be forwarded for trace correlation.""" + raw = { + "traceparent": "00-abcdef1234567890abcdef1234567890-1234567890abcdef-01", + } + req = _build_sampling_request(raw_headers=raw) + headers = dict(req.headers) + assert headers.get("traceparent") == ( + "00-abcdef1234567890abcdef1234567890-1234567890abcdef-01" + ) + + def test_should_forward_x_litellm_api_key(self): + """x-litellm-api-key header must be forwarded for auth.""" + raw = {"x-litellm-api-key": "sk-proxy-key-123"} + req = _build_sampling_request(raw_headers=raw) + headers = dict(req.headers) + assert headers.get("x-litellm-api-key") == "sk-proxy-key-123" diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_response_conversion.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_response_conversion.py new file mode 100644 index 00000000000..bb17a8f7104 --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_response_conversion.py @@ -0,0 +1,180 @@ +""" +Tests for MCP sampling handler response/tool conversion. + +Covers the translation of a LiteLLM completion response back into MCP +`CreateMessageResult` / `CreateMessageResultWithTools`, plus the helpers that +convert MCP tool definitions, tool-choice modes, and image/audio content into +OpenAI request format. +""" + +import json +from types import SimpleNamespace + +from mcp.types import ( + CreateMessageResult, + CreateMessageResultWithTools, + ErrorData, + TextContent, + ToolUseContent, +) + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _convert_mcp_content_to_openai, + _convert_mcp_tool_choice_to_openai, + _convert_mcp_tools_to_openai, + _convert_openai_response_to_mcp_result, + _convert_single_content, +) + + +def _tool_call(*, call_id: str, name: str, arguments): + return SimpleNamespace( + id=call_id, function=SimpleNamespace(name=name, arguments=arguments) + ) + + +def _response(*, content=None, tool_calls=None, finish_reason="stop", model="gpt-4o"): + message = SimpleNamespace(content=content, tool_calls=tool_calls) + choice = SimpleNamespace(message=message, finish_reason=finish_reason) + return SimpleNamespace(choices=[choice], model=model) + + +class TestConvertOpenAIResponseToMcpResult: + def test_should_return_error_data_when_no_choices(self): + response = SimpleNamespace(choices=[], model="gpt-4o") + result = _convert_openai_response_to_mcp_result(response, "gpt-4o") + assert isinstance(result, ErrorData) + assert "no choices" in result.message.lower() + + def test_should_convert_plain_text_response(self): + result = _convert_openai_response_to_mcp_result( + _response(content="hello world"), "gpt-4o" + ) + assert isinstance(result, CreateMessageResult) + assert isinstance(result.content, TextContent) + assert result.content.text == "hello world" + assert result.role == "assistant" + assert result.stopReason == "endTurn" + + def test_should_map_length_finish_reason_to_max_tokens(self): + result = _convert_openai_response_to_mcp_result( + _response(content="truncated", finish_reason="length"), "gpt-4o" + ) + assert result.stopReason == "maxTokens" + + def test_should_prefer_actual_model_from_response(self): + result = _convert_openai_response_to_mcp_result( + _response(content="hi", model="gpt-4o-2024-08-06"), "gpt-4o" + ) + assert result.model == "gpt-4o-2024-08-06" + + def test_should_convert_tool_calls_response(self): + tc = _tool_call( + call_id="call_1", + name="get_weather", + arguments=json.dumps({"city": "NYC"}), + ) + result = _convert_openai_response_to_mcp_result( + _response(content=None, tool_calls=[tc], finish_reason="tool_calls"), + "gpt-4o", + ) + assert isinstance(result, CreateMessageResultWithTools) + assert result.stopReason == "toolUse" + tool_uses = [c for c in result.content if isinstance(c, ToolUseContent)] + assert len(tool_uses) == 1 + assert tool_uses[0].name == "get_weather" + assert tool_uses[0].id == "call_1" + assert tool_uses[0].input == {"city": "NYC"} + + def test_should_keep_text_alongside_tool_calls(self): + tc = _tool_call(call_id="call_1", name="search", arguments="{}") + result = _convert_openai_response_to_mcp_result( + _response( + content="let me check", tool_calls=[tc], finish_reason="tool_calls" + ), + "gpt-4o", + ) + texts = [c for c in result.content if isinstance(c, TextContent)] + assert texts and texts[0].text == "let me check" + + def test_should_wrap_unparsable_tool_arguments_as_raw(self): + tc = _tool_call(call_id="call_1", name="bad", arguments="not-json{") + result = _convert_openai_response_to_mcp_result( + _response(tool_calls=[tc], finish_reason="tool_calls"), "gpt-4o" + ) + tool_uses = [c for c in result.content if isinstance(c, ToolUseContent)] + assert tool_uses[0].input == {"raw": "not-json{"} + + +class TestConvertMcpToolsToOpenAI: + def test_should_return_none_when_no_tools(self): + assert _convert_mcp_tools_to_openai(None) is None + + def test_should_convert_tool_with_schema(self): + schema = {"type": "object", "properties": {"q": {"type": "string"}}} + tool = SimpleNamespace( + name="search", description="search the web", inputSchema=schema + ) + result = _convert_mcp_tools_to_openai([tool]) + assert result == [ + { + "type": "function", + "function": { + "name": "search", + "description": "search the web", + "parameters": schema, + }, + } + ] + + def test_should_default_description_and_parameters(self): + tool = SimpleNamespace(name="noop", description=None, inputSchema=None) + result = _convert_mcp_tools_to_openai([tool]) + fn = result[0]["function"] + assert fn["description"] == "" + assert fn["parameters"] == {"type": "object", "properties": {}} + + +class TestConvertMcpToolChoiceToOpenAI: + def test_should_return_none_when_no_choice(self): + assert _convert_mcp_tool_choice_to_openai(None) is None + + def test_should_map_known_modes(self): + for mode in ("auto", "required", "none"): + choice = SimpleNamespace(mode=mode) + assert _convert_mcp_tool_choice_to_openai(choice) == mode + + def test_should_default_unknown_mode_to_auto(self): + choice = SimpleNamespace(mode="banana") + assert _convert_mcp_tool_choice_to_openai(choice) == "auto" + + +class TestConvertImageAndAudioContent: + def test_should_convert_image_to_data_uri(self): + content = SimpleNamespace(type="image", data="aGVsbG8=", mimeType="image/jpeg") + result = _convert_single_content(content) + assert result == { + "type": "image_url", + "image_url": {"url": "data:image/jpeg;base64,aGVsbG8="}, + } + + def test_should_map_audio_mime_to_format(self): + content = SimpleNamespace(type="audio", data="Zm9v", mimeType="audio/mp3") + result = _convert_single_content(content) + assert result["type"] == "input_audio" + assert result["input_audio"] == {"data": "Zm9v", "format": "mp3"} + + def test_should_default_unknown_audio_mime_to_wav(self): + content = SimpleNamespace(type="audio", data="Zm9v", mimeType="audio/weird") + result = _convert_single_content(content) + assert result["input_audio"]["format"] == "wav" + + def test_should_flatten_list_content(self): + items = [ + SimpleNamespace(type="text", text="a"), + SimpleNamespace(type="image", data="x", mimeType="image/png"), + ] + result = _convert_mcp_content_to_openai(items) + assert isinstance(result, list) + assert result[0] == {"type": "text", "text": "a"} + assert result[1]["type"] == "image_url" diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_tool_conversion.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_tool_conversion.py new file mode 100644 index 00000000000..b4b219e958c --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_sampling_tool_conversion.py @@ -0,0 +1,312 @@ +""" +Tests for MCP sampling handler tool_use / tool_result content conversion. + +Verifies that multi-turn tool-calling conversations from upstream MCP +servers are faithfully converted to OpenAI format instead of being +reduced to lossy plain-text stubs. +""" + +import json +from types import SimpleNamespace +from typing import Any, Dict + +from litellm.proxy._experimental.mcp_server.sampling_handler import ( + _convert_mcp_messages_to_openai, + _convert_single_content, +) + + +# --------------------------------------------------------------------------- +# Helpers — lightweight MCP type stand-ins +# --------------------------------------------------------------------------- + + +def _text(text: str) -> SimpleNamespace: + return SimpleNamespace(type="text", text=text) + + +def _tool_use(*, name: str, tool_id: str, input_data: Dict[str, Any]) -> SimpleNamespace: + return SimpleNamespace(type="tool_use", name=name, id=tool_id, input=input_data) + + +def _tool_result( + *, tool_use_id: str, content: Any = None, is_error: bool = False +) -> SimpleNamespace: + if content is None: + content = [] + return SimpleNamespace( + type="tool_result", toolUseId=tool_use_id, content=content, isError=is_error + ) + + +def _sampling_msg(role: str, content: Any) -> SimpleNamespace: + return SimpleNamespace(role=role, content=content) + + +# --------------------------------------------------------------------------- +# _convert_single_content — tool_use +# --------------------------------------------------------------------------- + + +class TestConvertSingleContentToolUse: + """Tests for the tool_use branch of _convert_single_content.""" + + def test_should_produce_function_call_dict(self): + """tool_use must produce a proper function-call dict, not a text stub.""" + tu = _tool_use(name="get_weather", tool_id="call_123", input_data={"city": "NYC"}) + result = _convert_single_content(tu) + + assert result["_marker_type"] == "tool_use" + assert result["type"] == "function" + assert result["id"] == "call_123" + assert result["function"]["name"] == "get_weather" + assert json.loads(result["function"]["arguments"]) == {"city": "NYC"} + + def test_should_not_produce_text_stub(self): + """Regression: the old code produced '[Tool call: get_weather]'.""" + tu = _tool_use(name="get_weather", tool_id="call_1", input_data={}) + result = _convert_single_content(tu) + + # Must NOT be a text content part + assert result.get("type") != "text" + assert "Tool call" not in str(result) + + def test_should_handle_empty_input(self): + tu = _tool_use(name="no_args_tool", tool_id="call_2", input_data={}) + result = _convert_single_content(tu) + + assert json.loads(result["function"]["arguments"]) == {} + + +# --------------------------------------------------------------------------- +# _convert_single_content — tool_result +# --------------------------------------------------------------------------- + + +class TestConvertSingleContentToolResult: + """Tests for the tool_result branch of _convert_single_content.""" + + def test_should_produce_tool_role_message(self): + """tool_result must produce a tool-role dict, not a text content part.""" + tr = _tool_result( + tool_use_id="call_123", + content=[_text("Temperature: 72°F")], + ) + result = _convert_single_content(tr) + + assert result["_marker_type"] == "tool_result" + assert result["role"] == "tool" + assert result["tool_call_id"] == "call_123" + assert "72°F" in result["content"] + + def test_should_handle_empty_content(self): + tr = _tool_result(tool_use_id="call_456", content=[]) + result = _convert_single_content(tr) + + assert result["role"] == "tool" + assert result["tool_call_id"] == "call_456" + assert result["content"] == "" + + def test_should_concatenate_multiple_text_parts(self): + tr = _tool_result( + tool_use_id="call_789", + content=[_text("Line 1"), _text("Line 2")], + ) + result = _convert_single_content(tr) + assert "Line 1" in result["content"] + assert "Line 2" in result["content"] + + +# --------------------------------------------------------------------------- +# _convert_mcp_messages_to_openai — multi-turn tool calling +# --------------------------------------------------------------------------- + + +class TestConvertMcpMessagesMultiTurnTools: + """End-to-end tests for multi-turn tool-calling message sequences.""" + + def test_should_convert_assistant_tool_use_to_tool_calls_array(self): + """An assistant message with tool_use content should produce + a proper tool_calls array, not a text stub.""" + messages = [ + _sampling_msg("assistant", _tool_use( + name="search", tool_id="call_1", input_data={"query": "LiteLLM"} + )), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + msg = result[0] + assert msg["role"] == "assistant" + assert "tool_calls" in msg + assert len(msg["tool_calls"]) == 1 + tc = msg["tool_calls"][0] + assert tc["function"]["name"] == "search" + assert tc["id"] == "call_1" + + def test_should_convert_user_tool_result_to_tool_role_message(self): + """A user message with tool_result content should produce + a separate role='tool' message.""" + messages = [ + _sampling_msg("user", _tool_result( + tool_use_id="call_1", + content=[_text("Found 42 results")], + )), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + msg = result[0] + assert msg["role"] == "tool" + assert msg["tool_call_id"] == "call_1" + assert "42 results" in msg["content"] + + def test_should_handle_full_tool_calling_round_trip(self): + """Simulate a complete tool-calling conversation: + user → assistant(tool_use) → user(tool_result) → assistant(text) + """ + messages = [ + _sampling_msg("user", _text("What's the weather in NYC?")), + _sampling_msg("assistant", _tool_use( + name="get_weather", tool_id="call_w1", + input_data={"city": "NYC"}, + )), + _sampling_msg("user", _tool_result( + tool_use_id="call_w1", + content=[_text("72°F, sunny")], + )), + _sampling_msg("assistant", _text("It's 72°F and sunny in NYC!")), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 4 + + # 1. User message + assert result[0]["role"] == "user" + + # 2. Assistant with tool_calls + assert result[1]["role"] == "assistant" + assert "tool_calls" in result[1] + assert result[1]["tool_calls"][0]["function"]["name"] == "get_weather" + + # 3. Tool result + assert result[2]["role"] == "tool" + assert result[2]["tool_call_id"] == "call_w1" + + # 4. Final assistant text + assert result[3]["role"] == "assistant" + assert "72°F" in str(result[3]["content"]) + + def test_should_handle_mixed_text_and_tool_use_in_assistant(self): + """An assistant message with both text and tool_use content.""" + messages = [ + _sampling_msg("assistant", [ + _text("Let me check that for you."), + _tool_use(name="lookup", tool_id="call_lu1", input_data={"id": 42}), + ]), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + msg = result[0] + assert msg["role"] == "assistant" + assert "tool_calls" in msg + assert msg["tool_calls"][0]["function"]["name"] == "lookup" + # Text content should also be present + assert msg.get("content") is not None + + def test_should_handle_multiple_tool_uses_in_single_message(self): + """Multiple tool_use items in a single assistant message → multiple tool_calls.""" + messages = [ + _sampling_msg("assistant", [ + _tool_use(name="tool_a", tool_id="call_a", input_data={}), + _tool_use(name="tool_b", tool_id="call_b", input_data={"x": 1}), + ]), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + msg = result[0] + assert len(msg["tool_calls"]) == 2 + names = {tc["function"]["name"] for tc in msg["tool_calls"]} + assert names == {"tool_a", "tool_b"} + + def test_should_handle_multiple_tool_results_in_single_message(self): + """Multiple tool_result items in a single user message → multiple tool messages.""" + messages = [ + _sampling_msg("user", [ + _tool_result(tool_use_id="call_a", content=[_text("Result A")]), + _tool_result(tool_use_id="call_b", content=[_text("Result B")]), + ]), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 2 + assert all(m["role"] == "tool" for m in result) + ids = {m["tool_call_id"] for m in result} + assert ids == {"call_a", "call_b"} + + def test_should_preserve_system_prompt(self): + """System prompt should still be emitted first.""" + messages = [_sampling_msg("user", _text("Hi"))] + result = _convert_mcp_messages_to_openai( + messages, system_prompt="You are helpful." + ) + + assert result[0]["role"] == "system" + assert result[0]["content"] == "You are helpful." + + +# --------------------------------------------------------------------------- +# _convert_mcp_messages_to_openai — marker hoisting on unexpected roles +# --------------------------------------------------------------------------- + + +class TestConvertMcpMessagesMarkerHoisting: + """The role-matched fast paths only fire for assistant/tool_use and + user/tool_result. Content that arrives on an unexpected role must still + be hoisted to the correct message position by the generic fallback, + not silently dropped or embedded inline as a content part.""" + + def test_should_hoist_tool_use_arriving_on_user_role(self): + messages = [ + _sampling_msg("user", _tool_use( + name="search", tool_id="call_1", input_data={"q": "x"} + )), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + assert result[0]["role"] == "assistant" + assert result[0]["tool_calls"][0]["function"]["name"] == "search" + + def test_should_hoist_tool_result_arriving_on_assistant_role(self): + messages = [ + _sampling_msg("assistant", _tool_result( + tool_use_id="call_1", content=[_text("done")] + )), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + assert result[0]["role"] == "tool" + assert result[0]["tool_call_id"] == "call_1" + assert "done" in result[0]["content"] + + def test_should_keep_text_when_hoisting_tool_use_on_user_role(self): + messages = [ + _sampling_msg("user", [ + _text("here you go"), + _tool_use(name="lookup", tool_id="call_2", input_data={}), + ]), + ] + result = _convert_mcp_messages_to_openai(messages) + + assert len(result) == 1 + msg = result[0] + assert msg["role"] == "assistant" + assert msg["tool_calls"][0]["function"]["name"] == "lookup" + assert any( + isinstance(p, dict) and p.get("text") == "here you go" + for p in msg["content"] + ) diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py index 6b6c7bc37d5..227cf3f4bcf 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py @@ -1,5 +1,4 @@ import asyncio -import contextlib import contextvars from datetime import datetime, timedelta from unittest.mock import AsyncMock, MagicMock, patch @@ -894,7 +893,7 @@ async def test_get_tools_from_mcp_servers_continues_when_one_server_fails(): extra_headers=None, add_prefix=True, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): if server.name == "working_server": # Working server returns tools @@ -1000,7 +999,7 @@ async def test_get_tools_from_mcp_servers_handles_all_servers_failing(): extra_headers=None, add_prefix=True, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): # All servers fail raise Exception(f"Server {server.name} connection failed") @@ -1122,8 +1121,8 @@ async def test_concurrent_initialize_session_managers(): # Reset state before test original_initialized = mcp_server._SESSION_MANAGERS_INITIALIZED original_session_cm = mcp_server._session_manager_cm - original_session_stateful_cm = mcp_server._session_manager_stateful_cm - original_sse_session_cm = mcp_server._sse_session_manager_cm + original_stateful_cm = mcp_server._session_manager_stateful_cm + original_sse_cm = mcp_server._sse_session_manager_cm original_cleanup_task = mcp_server._stateful_auth_context_cleanup_task try: @@ -1131,30 +1130,38 @@ async def test_concurrent_initialize_session_managers(): mcp_server._session_manager_cm = None mcp_server._session_manager_stateful_cm = None mcp_server._sse_session_manager_cm = None - mcp_server._stateful_auth_context_cleanup_task = None - # Mock the session managers to avoid actual MCP initialization + # Create mock context managers for all three session managers + mock_cm_stateless = AsyncMock() + mock_cm_stateless.__aenter__ = AsyncMock() + mock_cm_stateless.__aexit__ = AsyncMock() + + mock_cm_stateful = AsyncMock() + mock_cm_stateful.__aenter__ = AsyncMock() + mock_cm_stateful.__aexit__ = AsyncMock() + + mock_cm_sse = AsyncMock() + mock_cm_sse.__aenter__ = AsyncMock() + mock_cm_sse.__aexit__ = AsyncMock() + with ( - patch( - "litellm.proxy._experimental.mcp_server.server.session_manager_stateless" - ) as mock_session_manager_stateless, - patch( - "litellm.proxy._experimental.mcp_server.server.session_manager_stateful" - ) as mock_session_manager_stateful, - patch( - "litellm.proxy._experimental.mcp_server.server.sse_session_manager" - ) as mock_sse_session_manager, + patch.object( + mcp_server.session_manager_stateless, + "run", + return_value=mock_cm_stateless, + ) as mock_stateless_run, + patch.object( + mcp_server.session_manager_stateful, + "run", + return_value=mock_cm_stateful, + ) as mock_stateful_run, + patch.object( + mcp_server.sse_session_manager, + "run", + return_value=mock_cm_sse, + ) as mock_sse_run, patch("litellm.proxy._experimental.mcp_server.server.verbose_logger"), ): - # Mock the run() method to return a mock context manager - mock_cm = AsyncMock() - mock_cm.__aenter__ = AsyncMock() - mock_cm.__aexit__ = AsyncMock() - - mock_session_manager_stateless.run.return_value = mock_cm - mock_session_manager_stateful.run.return_value = mock_cm - mock_sse_session_manager.run.return_value = mock_cm - # Create multiple concurrent tasks that call initialize_session_managers async def init_task(): await initialize_session_managers() @@ -1171,19 +1178,25 @@ async def test_concurrent_initialize_session_managers(): # Each session manager.run() should only be called once due to the lock assert ( - mock_session_manager_stateless.run.call_count == 1 - ), f"Expected 1 call to session_manager_stateless.run(), got {mock_session_manager_stateless.run.call_count}" + mock_stateless_run.call_count == 1 + ), f"Expected 1 call to session_manager_stateless.run(), got {mock_stateless_run.call_count}" assert ( - mock_session_manager_stateful.run.call_count == 1 - ), f"Expected 1 call to session_manager_stateful.run(), got {mock_session_manager_stateful.run.call_count}" + mock_stateful_run.call_count == 1 + ), f"Expected 1 call to session_manager_stateful.run(), got {mock_stateful_run.call_count}" assert ( - mock_sse_session_manager.run.call_count == 1 - ), f"Expected 1 call to sse_session_manager.run(), got {mock_sse_session_manager.run.call_count}" + mock_sse_run.call_count == 1 + ), f"Expected 1 call to sse_session_manager.run(), got {mock_sse_run.call_count}" - # The context managers should only be entered once each (3 managers) + # The context managers should only be entered once each assert ( - mock_cm.__aenter__.call_count == 3 - ), f"Expected 3 calls to __aenter__ (one per session manager), got {mock_cm.__aenter__.call_count}" + mock_cm_stateless.__aenter__.call_count == 1 + ), f"Expected 1 call to stateless __aenter__, got {mock_cm_stateless.__aenter__.call_count}" + assert ( + mock_cm_stateful.__aenter__.call_count == 1 + ), f"Expected 1 call to stateful __aenter__, got {mock_cm_stateful.__aenter__.call_count}" + assert ( + mock_cm_sse.__aenter__.call_count == 1 + ), f"Expected 1 call to sse __aenter__, got {mock_cm_sse.__aenter__.call_count}" # State should be properly set assert mcp_server._SESSION_MANAGERS_INITIALIZED is True @@ -1195,14 +1208,12 @@ async def test_concurrent_initialize_session_managers(): leaked_task = mcp_server._stateful_auth_context_cleanup_task if leaked_task is not None and leaked_task is not original_cleanup_task: leaked_task.cancel() - with contextlib.suppress(asyncio.CancelledError, Exception): - await leaked_task # Restore original state mcp_server._SESSION_MANAGERS_INITIALIZED = original_initialized mcp_server._session_manager_cm = original_session_cm - mcp_server._session_manager_stateful_cm = original_session_stateful_cm - mcp_server._sse_session_manager_cm = original_sse_session_cm + mcp_server._session_manager_stateful_cm = original_stateful_cm + mcp_server._sse_session_manager_cm = original_sse_cm mcp_server._stateful_auth_context_cleanup_task = original_cleanup_task @@ -1637,10 +1648,7 @@ async def test_mcp_routing_initialize_rejected_when_owner_at_session_cap(): active = {f"s{i}": 1 for i in range(cap)} # all in flight -> cannot evict contexts = {f"s{i}": MagicMock() for i in range(cap)} - init_body = ( - b'{"jsonrpc":"2.0","id":1,"method":"initialize",' - b'"params":{"protocolVersion":"2024-11-05"}}' - ) + init_body = b'{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05"}}' scope = { "type": "http", "method": "POST", @@ -2587,6 +2595,134 @@ async def test_stateful_mcp_get_stream_does_not_block_post(): mcp_server._stateful_session_locks.pop(session_id, None) +def test_jsonrpc_text_has_top_level_method_ignores_nested_method(): + """The top-level-key scan must not be fooled by a ``method`` field nested + inside a JSON-RPC response's ``result`` payload — a flat substring search + would, and that misread is what deadlocks the session lock.""" + from litellm.proxy._experimental.mcp_server.server import ( + _jsonrpc_text_has_top_level_method, + ) + + request = '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{}}' + assert _jsonrpc_text_has_top_level_method(request) is True + + # method key out of order (after params) is still top-level + reordered = '{"jsonrpc":"2.0","params":{"x":1},"method":"foo"}' + assert _jsonrpc_text_has_top_level_method(reordered) is True + + # response whose result nests a "method" key (and arrays of them) + response = ( + '{"jsonrpc":"2.0","id":1,"result":{"toolResult":{"method":"GET"},' + '"steps":[{"method":"x"}]}}' + ) + assert _jsonrpc_text_has_top_level_method(response) is False + + # truncated response: result value never closes, no top-level method seen + truncated = '{"jsonrpc":"2.0","id":1,"result":{"text":"' + "q" * 5000 + assert _jsonrpc_text_has_top_level_method(truncated) is False + + +@pytest.mark.asyncio +async def test_truncated_jsonrpc_response_with_nested_method_skips_lock(): + """Regression: a large JSON-RPC *response* POST whose ``result`` payload + nests a ``method`` key must skip the per-session lock so it does not + deadlock behind the in-flight request POST that is holding the lock while + it awaits this very response (e.g. sampling/createMessage).""" + try: + from litellm.proxy._experimental.mcp_server import server as mcp_server + from litellm.proxy._experimental.mcp_server.server import ( + handle_streamable_http_mcp, + session_manager_stateful, + ) + except ImportError: + pytest.skip("MCP server not available") + + session_id = "nested-method-response-session" + owner_auth = UserAPIKeyAuth(api_key="owner-key", user_id="owner") + mcp_server._stateful_session_auth_contexts[session_id] = ( + mcp_server.MCPAuthenticatedUser(user_api_key_auth=owner_auth) + ) + mcp_server._stateful_session_owners[session_id] = mcp_server._owner_fingerprint_for( + owner_auth + ) + + gate = asyncio.Event() + request_in_handle = asyncio.Event() + response_handled = asyncio.Event() + + async def handle(s, r, se): + msg = await r() + body = msg.get("body", b"") or b"" + if b'"result"' in body: + response_handled.set() + else: + request_in_handle.set() + await gate.wait() + + async def call(body: bytes): + scope = { + "type": "http", + "method": "POST", + "path": "/mcp", + "headers": [(b"mcp-session-id", session_id.encode())], + } + receive = AsyncMock( + return_value={ + "type": "http.request", + "body": body, + "more_body": False, + } + ) + await handle_streamable_http_mcp(scope, receive, AsyncMock()) + + # The in-flight request POST holds the session lock while blocked. + request_body = b'{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{}}' + # A JSON-RPC response larger than the routing peek cap so it can't be fully + # parsed, with a nested "method" key in the first bytes to trip a flat + # substring heuristic. + response_body = ( + '{"jsonrpc":"2.0","id":99,"result":{"toolResult":' + '{"method":"GET","payload":"' + ("x" * 5000) + '"}}}' + ).encode() + + try: + with ( + patch( + "litellm.proxy._experimental.mcp_server.server.extract_mcp_auth_context", + new_callable=AsyncMock, + return_value=(owner_auth, None, None, None, None, None), + ), + patch( + "litellm.proxy._experimental.mcp_server.server._SESSION_MANAGERS_INITIALIZED", + True, + ), + patch.object( + session_manager_stateful, "handle_request", side_effect=handle + ), + patch.object( + session_manager_stateful, + "_server_instances", + {session_id: MagicMock()}, + ), + ): + req_task = asyncio.create_task(call(request_body)) + await asyncio.wait_for(request_in_handle.wait(), timeout=1.0) + + resp_task = asyncio.create_task(call(response_body)) + # Under a flat substring heuristic the response would acquire the + # lock held by req_task and this wait would time out (deadlock). + await asyncio.wait_for(response_handled.wait(), timeout=1.0) + + gate.set() + await asyncio.gather(req_task, resp_task) + finally: + gate.set() + mcp_server._stateful_session_auth_contexts.pop(session_id, None) + mcp_server._stateful_session_owners.pop(session_id, None) + mcp_server._stateful_session_locks.pop(session_id, None) + mcp_server._stateful_session_active_request_counts.pop(session_id, None) + + @pytest.mark.asyncio @pytest.mark.no_parallel async def test_mcp_routing_with_conflicting_alias_and_group_name(): @@ -2729,7 +2865,7 @@ async def test_oauth2_headers_passed_to_mcp_client(): mcp_auth_header=None, extra_headers=None, stdio_env=None, - subject_token=None, + **kwargs, ): # Capture the arguments for verification captured_client_args.update( @@ -2738,7 +2874,7 @@ async def test_oauth2_headers_passed_to_mcp_client(): "mcp_auth_header": mcp_auth_header, "extra_headers": extra_headers, "stdio_env": stdio_env, - "subject_token": subject_token, + "kwargs": kwargs, } ) # Return a mock client that doesn't actually connect @@ -2764,6 +2900,16 @@ async def test_oauth2_headers_passed_to_mcp_client(): "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", AsyncMock(return_value=[oauth2_server]), ), + patch( + "litellm.proxy._experimental.mcp_server.server._prefetch_oauth_creds_for_user", + new_callable=AsyncMock, + return_value={}, + ), + patch( + "litellm.proxy._experimental.mcp_server.server._get_user_oauth_extra_headers_from_db", + new_callable=AsyncMock, + return_value=None, + ), ): # Call _get_tools_from_mcp_servers which should eventually call _create_mcp_client await _get_tools_from_mcp_servers( @@ -2840,7 +2986,7 @@ async def test_list_tools_single_server_unprefixed_names(): extra_headers=None, add_prefix=False, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): tool = MagicMock() tool.name = f"{server.alias}-toolA" if add_prefix else "toolA" @@ -2922,7 +3068,7 @@ async def test_list_tools_multiple_servers_prefixed_names(): extra_headers=None, add_prefix=True, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): tool = MagicMock() # When multiple servers, add_prefix should be True -> prefixed names @@ -3189,7 +3335,7 @@ async def test_list_tools_filters_by_key_team_permissions(): extra_headers=None, add_prefix=False, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): # Return 4 tools, but only 2 should be allowed tool1 = MagicMock() @@ -3299,7 +3445,7 @@ async def test_list_tools_with_team_tool_permissions_inheritance(): extra_headers=None, add_prefix=False, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): # Return 4 tools tool1 = MagicMock() @@ -3395,7 +3541,7 @@ async def test_list_tools_with_no_tool_permissions_shows_all(): extra_headers=None, add_prefix=False, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): # Return 3 tools tool1 = MagicMock() @@ -3494,7 +3640,7 @@ async def test_list_tools_strips_prefix_when_matching_permissions(): extra_headers=None, add_prefix=True, raw_headers=None, - user_api_key_auth=None, + **kwargs, ): # Return tools WITH prefix (as they come from MCP server) tool1 = MagicMock() @@ -5178,3 +5324,42 @@ def test_get_forwarded_auth_from_scope_skips_when_no_litellm_key_header(): ] } assert _get_forwarded_auth_from_scope(scope) is None + + +@pytest.mark.asyncio +async def test_create_mcp_client_sampling_disabled_by_default(): + """Sampling callback must be None when allow_sampling is not set (default False).""" + from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( + MCPServerManager, + ) + + manager = MCPServerManager() + server = MCPServer( + server_id="no-sampling", + name="no-sampling", + url="https://example.com/mcp", + transport=MCPTransport.http, + ) + + client = await manager._create_mcp_client(server=server) + assert client._sampling_callback is None + + +@pytest.mark.asyncio +async def test_create_mcp_client_sampling_enabled(): + """Sampling callback must be set when allow_sampling=True.""" + from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( + MCPServerManager, + ) + + manager = MCPServerManager() + server = MCPServer( + server_id="with-sampling", + name="with-sampling", + url="https://example.com/mcp", + transport=MCPTransport.http, + allow_sampling=True, + ) + + client = await manager._create_mcp_client(server=server) + assert client._sampling_callback is not None diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py index 32e4ec19311..e7d0ee6247b 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py @@ -320,9 +320,7 @@ class TestMCPServerManager: async def mock_get_tools_from_server( server, mcp_auth_header=None, - mcp_protocol_version=None, - raw_headers=None, - user_api_key_auth=None, + **kwargs, ): if server.name == "github": tool1 = MagicMock() @@ -375,9 +373,7 @@ class TestMCPServerManager: async def mock_get_tools_from_server( server, mcp_auth_header=None, - mcp_protocol_version=None, - raw_headers=None, - user_api_key_auth=None, + **kwargs, ): assert mcp_auth_header == "legacy-token" # Should use legacy header tool = MagicMock() @@ -414,9 +410,7 @@ class TestMCPServerManager: async def mock_get_tools_from_server( server, mcp_auth_header=None, - mcp_protocol_version=None, - raw_headers=None, - user_api_key_auth=None, + **kwargs, ): assert ( mcp_auth_header == "server-specific-token" @@ -457,7 +451,7 @@ class TestMCPServerManager: captured_extra_headers = None async def capture_create_mcp_client( - server, mcp_auth_header, extra_headers, stdio_env, subject_token=None + server, mcp_auth_header, extra_headers, stdio_env, **kwargs ): # pragma: no cover - helper nonlocal captured_extra_headers captured_extra_headers = extra_headers @@ -507,7 +501,7 @@ class TestMCPServerManager: captured_extra_headers = None async def capture_create_mcp_client( - server, mcp_auth_header, extra_headers, stdio_env, subject_token=None + server, mcp_auth_header, extra_headers, stdio_env, subject_token=None, **kwargs ): # pragma: no cover - helper nonlocal captured_extra_headers captured_extra_headers = extra_headers @@ -560,7 +554,7 @@ class TestMCPServerManager: captured_extra_headers = None async def capture_create_mcp_client( - server, mcp_auth_header, extra_headers, stdio_env, subject_token=None + server, mcp_auth_header, extra_headers, stdio_env, subject_token=None, **kwargs ): # pragma: no cover - helper nonlocal captured_extra_headers captured_extra_headers = extra_headers @@ -616,7 +610,7 @@ class TestMCPServerManager: captured_extra_headers = None async def capture_create_mcp_client( - server, mcp_auth_header, extra_headers, stdio_env, subject_token=None + server, mcp_auth_header, extra_headers, stdio_env, subject_token=None, **kwargs ): # pragma: no cover - helper nonlocal captured_extra_headers captured_extra_headers = extra_headers @@ -1166,9 +1160,7 @@ class TestMCPServerManager: async def mock_get_tools_from_server( server, mcp_auth_header=None, - mcp_protocol_version=None, - raw_headers=None, - user_api_key_auth=None, + **kwargs, ): assert ( mcp_auth_header == "server-specific-token" diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_stale_session.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_stale_session.py index 549afd774b0..d52af94c47f 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_stale_session.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_stale_session.py @@ -9,8 +9,6 @@ they may send a stale `mcp-session-id` header. This test verifies that: import asyncio from unittest.mock import AsyncMock, MagicMock, patch - -from fastapi import HTTPException from litellm.types.mcp import MCPAuth import pytest @@ -600,6 +598,8 @@ async def test_per_user_oauth_missing_stored_token_returns_preemptive_401(): Per-user OAuth server with no stored token should fail fast with 401 + WWW-Authenticate so PKCE can start. """ + from fastapi import HTTPException + try: from litellm.proxy._experimental.mcp_server.server import ( handle_streamable_http_mcp, @@ -612,8 +612,13 @@ async def test_per_user_oauth_missing_stored_token_returns_preemptive_401(): "type": "http", "method": "POST", "path": "/mcp", + "scheme": "http", + "query_string": b"", + "root_path": "", + "server": ("localhost", 8000), "headers": [ (b"content-type", b"application/json"), + (b"host", b"localhost:8000"), ], } receive = AsyncMock() @@ -660,11 +665,12 @@ async def test_per_user_oauth_missing_stored_token_returns_preemptive_401(): with pytest.raises(HTTPException) as exc_info: await handle_streamable_http_mcp(scope, receive, send) - exc = exc_info.value - assert exc.status_code == 401 - assert "www-authenticate" in exc.headers + # Verify a 401 was raised assert mock_get_stored_token.await_count == 1 assert mock_handle_request.await_count == 0 + assert exc_info.value.status_code == 401 + assert "www-authenticate" in exc_info.value.headers + assert "Bearer authorization_uri=" in exc_info.value.headers["www-authenticate"] @pytest.mark.asyncio @@ -685,11 +691,22 @@ async def test_per_user_oauth_with_stored_token_skips_preemptive_401(): "type": "http", "method": "POST", "path": "/mcp", + "scheme": "http", + "query_string": b"", + "root_path": "", + "server": ("localhost", 8000), "headers": [ (b"content-type", b"application/json"), + (b"host", b"localhost:8000"), ], } - receive = AsyncMock() + receive = AsyncMock( + return_value={ + "type": "http.request", + "body": b'{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}', + "more_body": False, + } + ) send = AsyncMock() user_auth = MagicMock() user_auth.user_id = "test-user-id" @@ -729,6 +746,11 @@ async def test_per_user_oauth_with_stored_token_skips_preemptive_401(): "handle_request", new_callable=AsyncMock, ) as mock_handle_request, + patch.object( + session_manager_stateless, + "_server_instances", + {}, + ), ): await handle_streamable_http_mcp(scope, receive, send) diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_permission.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_permission.py index d31dbdd4348..6804ea9f8fe 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_permission.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_permission.py @@ -2,6 +2,7 @@ Unit tests for Tool Permission Guardrail (OpenAI tool_calls semantics) """ +import json import os import re import sys @@ -20,7 +21,7 @@ from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.guardrails.guardrail_hooks.tool_permission import ( ToolPermissionGuardrail, ) -from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.guardrails import GuardrailEventHooks, LitellmParams from litellm.types.proxy.guardrails.guardrail_hooks.tool_permission import ( PermissionError, ) @@ -894,3 +895,153 @@ class TestToolPermissionGuardrailIntegration: is_allowed, rule_id, _ = guardrail._check_tool_permission("Read") assert is_allowed is False assert rule_id == "deny_read" + + +class TestToolPermissionGuardrailInMemoryUpdate: + """Regression: an in-memory params update (PUT /guardrails path) must rebuild + the compiled rule maps, not just self.rules, so the new rules are enforced + without reinitializing the guardrail.""" + + def _bash(self, command): + return ChatCompletionMessageToolCall( + function={"name": "Bash", "arguments": json.dumps({"command": command})}, + type="function", + ) + + def test_update_in_memory_recompiles_added_param_pattern(self): + guardrail = ToolPermissionGuardrail( + guardrail_name="tp", + rules=[{"id": "native-bash", "tool_name": r"^Bash$", "decision": "allow"}], + default_action="deny", + on_disallowed_action="block", + ) + # No pattern yet: any Bash command is allowed. + assert ( + guardrail._get_permission_for_tool_call(self._bash("echo blockme"))[0] + is True + ) + + guardrail.update_in_memory_litellm_params( + LitellmParams( + guardrail="tool_permission", + mode=["pre_call", "post_call"], + default_action="deny", + on_disallowed_action="block", + rules=[ + { + "id": "native-bash", + "tool_name": r"^Bash$", + "decision": "allow", + "allowed_param_patterns": { + "command": r"^(?!(echo blockme)$).*$" + }, + } + ], + ) + ) + + # The compiled map must be rebuilt, and enforcement must reflect it. + assert "command" in guardrail._compiled_rule_patterns.get("native-bash", {}) + assert ( + guardrail._get_permission_for_tool_call(self._bash("echo blockme"))[0] + is False + ) + assert ( + guardrail._get_permission_for_tool_call(self._bash("echo hello"))[0] is True + ) + + def test_update_in_memory_recompiles_tool_name_target(self): + guardrail = ToolPermissionGuardrail( + guardrail_name="tp", + rules=[], + default_action="allow", + on_disallowed_action="block", + ) + # No rules: default_action allow lets Bash through. + assert guardrail._get_permission_for_tool_call(self._bash("echo x"))[0] is True + + guardrail.update_in_memory_litellm_params( + LitellmParams( + guardrail="tool_permission", + mode=["pre_call", "post_call"], + default_action="allow", + on_disallowed_action="block", + rules=[{"id": "deny-bash", "tool_name": r"^Bash$", "decision": "deny"}], + ) + ) + + # A newly added deny rule (new id) must match -> its compiled target was rebuilt. + assert "deny-bash" in guardrail._compiled_rule_targets + assert guardrail._get_permission_for_tool_call(self._bash("echo x"))[0] is False + + def test_update_in_memory_preserves_rules_when_rules_absent(self): + guardrail = ToolPermissionGuardrail( + guardrail_name="tp", + rules=[ + { + "id": "native-bash", + "tool_name": r"^Bash$", + "decision": "allow", + "allowed_param_patterns": {"command": r"^(?!(echo blockme)$).*$"}, + } + ], + default_action="deny", + on_disallowed_action="block", + ) + assert "command" in guardrail._compiled_rule_patterns.get("native-bash", {}) + + # A partial update that does not carry `rules` must NOT wipe the existing + # ruleset / compiled maps. + guardrail.update_in_memory_litellm_params( + LitellmParams( + guardrail="tool_permission", + mode=["pre_call", "post_call"], + default_action="deny", + on_disallowed_action="block", + ) + ) + + assert len(guardrail.rules) == 1 + assert "command" in guardrail._compiled_rule_patterns.get("native-bash", {}) + assert ( + guardrail._get_permission_for_tool_call(self._bash("echo blockme"))[0] + is False + ) + + def test_update_in_memory_rejects_invalid_regex_and_keeps_previous_rules(self): + """Regression: a live update whose rules contain an invalid regex must be + rejected atomically. The bad rule must not leak in as a compiled-target + wildcard (match-all), and the previously enforced ruleset must survive.""" + guardrail = ToolPermissionGuardrail( + guardrail_name="tp", + rules=[{"id": "deny-secret", "tool_name": r"^Secret$", "decision": "deny"}], + default_action="allow", + on_disallowed_action="block", + ) + # Baseline: only "Secret" is denied; any other tool is allowed. + assert guardrail._check_tool_permission("Secret")[0] is False + assert guardrail._check_tool_permission("Other")[0] is True + + with pytest.raises(ValueError): + guardrail.update_in_memory_litellm_params( + LitellmParams( + guardrail="tool_permission", + mode=["pre_call", "post_call"], + default_action="allow", + on_disallowed_action="block", + rules=[ + { + "id": "deny-secret", + "tool_name": r"^Secret$", + "decision": "deny", + }, + {"id": "bad", "tool_name": "[unclosed", "decision": "deny"}, + ], + ) + ) + + # The bad rule must not have leaked in, and the prior ruleset must hold. + assert "bad" not in guardrail._compiled_rule_targets + assert all(rule.id != "bad" for rule in guardrail.rules) + assert guardrail._check_tool_permission("Other")[0] is True + assert guardrail._check_tool_permission("Secret")[0] is False diff --git a/tests/test_litellm/proxy/test_caching_routes.py b/tests/test_litellm/proxy/test_caching_routes.py index 3e842d118dd..840ba054cc9 100644 --- a/tests/test_litellm/proxy/test_caching_routes.py +++ b/tests/test_litellm/proxy/test_caching_routes.py @@ -123,33 +123,100 @@ def test_cache_ping_failure(mock_redis_failure): assert "message" in error_details assert "litellm_cache_params" in error_details assert "health_check_cache_params" in error_details - assert "traceback" in error_details - # Verify specific error message - assert "invalid username-password pair" in error_details["message"] + # Verify generic static message (exception text must not leak to clients) + assert error_details["message"] == "Service Unhealthy" -def test_cache_ping_no_cache_initialized(): - """Test cache ping when no cache is initialized""" - # Set cache to None - original_cache = litellm.cache - litellm.cache = None - +def test_cache_ping_failure_does_not_expose_traceback(mock_redis_failure): + """CWE-209: Stack trace and exception text must not appear in the HTTP 503 response body.""" response = client.get("/cache/ping", headers={"Authorization": "Bearer sk-1234"}) assert response.status_code == 503 data = response.json() - print("response data=", json.dumps(data, indent=4)) - assert "error" in data - error = data["error"] + error = data.get("error", {}) + raw_body = json.dumps(data) - # Verify error contains all expected fields - assert "message" in error + # The word "traceback" (case-insensitive) must not appear anywhere in the response + assert ( + "traceback" not in raw_body.lower() + ), "CWE-209: Python traceback exposed in HTTP 503 response body" + # Internal frame paths should not leak either + assert ( + 'File "' not in raw_body + ), "CWE-209: Python stack frame paths exposed in HTTP 503 response body" + # Exception text (e.g. Redis hostnames/IPs) must not leak either + assert ( + "invalid username-password pair" not in raw_body + ), "CWE-209: Exception message text exposed in HTTP 503 response body" + + # The error message should be the safe static string error_details = json.loads(error["message"]) - assert "Cache not initialized. litellm.cache is None" in error_details["message"] + assert error_details["message"] == "Service Unhealthy" - # Restore original cache - litellm.cache = original_cache + +def test_cache_ping_no_cache_initialized(): + """Test cache ping when no cache is initialized returns 503 with ProxyException envelope. + + Verifies the exact response structure so that regressions in the error format + (e.g. message moving to a different field, or extra internal details leaking) + are caught immediately. + """ + original_cache = litellm.cache + litellm.cache = None + + try: + response = client.get( + "/cache/ping", headers={"Authorization": "Bearer sk-1234"} + ) + assert response.status_code == 503 + + data = response.json() + print("response data=", json.dumps(data, indent=4)) + # ProxyException is serialised as {"error": {"message": "...", "type": ..., ...}} + assert "error" in data + error_details = json.loads(data["error"]["message"]) + assert ( + error_details["message"] == "Cache not initialized. litellm.cache is None" + ) + finally: + litellm.cache = original_cache + + +def test_cache_ping_no_cache_does_not_expose_internals(): + """CWE-209: No-cache 503 must use the ProxyException envelope with no internal details. + + The null-cache path raises ProxyException directly (not HTTPException), so the + response is {"error": {"message": "...", ...}} — same envelope as other 503s from + this endpoint — with no tracebacks, source paths, or extra fields leaking. + """ + original_cache = litellm.cache + litellm.cache = None + + try: + response = client.get( + "/cache/ping", headers={"Authorization": "Bearer sk-1234"} + ) + assert response.status_code == 503 + + raw_body = response.text + # No Python traceback or source-file paths must appear in the response + assert "traceback" not in raw_body.lower(), ( + "CWE-209: Python traceback exposed in /cache/ping no-cache response" + ) + assert 'File "' not in raw_body, ( + "CWE-209: Python stack frame paths exposed in /cache/ping no-cache response" + ) + + data = response.json() + # Response must use the ProxyException envelope + assert "error" in data, f"Expected ProxyException envelope, got: {data}" + error_details = json.loads(data["error"]["message"]) + assert ( + error_details["message"] == "Cache not initialized. litellm.cache is None" + ) + finally: + litellm.cache = original_cache def test_cache_ping_health_check_includes_only_cache_attributes(mock_redis_success): diff --git a/tests/test_litellm/proxy/test_dynamic_mcp_route.py b/tests/test_litellm/proxy/test_dynamic_mcp_route.py index 2462aff2119..592cebd957c 100644 --- a/tests/test_litellm/proxy/test_dynamic_mcp_route.py +++ b/tests/test_litellm/proxy/test_dynamic_mcp_route.py @@ -486,3 +486,57 @@ async def test_dynamic_mcp_route_empty_access_group_returns_404(): await dynamic_mcp_route("empty_group", request) assert exc_info.value.status_code == 404 + + +# --------------------------------------------------------------------------- +# 6. Unexpected exception → 500 without leaking stack trace (CWE-209) +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_dynamic_mcp_route_unexpected_exception_returns_500_without_traceback(): + """CWE-209: an unexpected exception must return 500 with a generic message, + never leaking str(e) or a Python traceback to the caller.""" + from litellm.proxy.proxy_server import dynamic_mcp_route + + request = _make_request("/boom/mcp") + + fake_mgr = MagicMock() + fake_mgr.get_mcp_server_by_name = MagicMock( + side_effect=RuntimeError("internal host: redis://10.0.0.1:6379") + ) + + with patch(_MCP_MANAGER, fake_mgr): + with pytest.raises(HTTPException) as exc_info: + await dynamic_mcp_route("boom", request) + + assert exc_info.value.status_code == 500 + assert exc_info.value.detail == "Internal server error" + assert "10.0.0.1" not in str(exc_info.value.detail) + assert "traceback" not in str(exc_info.value.detail).lower() + + +@pytest.mark.asyncio +async def test_toolset_mcp_route_unexpected_exception_returns_500_without_traceback(): + """CWE-209: toolset_mcp_route must return 500 with a generic message on + unexpected errors, never leaking exception text to the caller.""" + from litellm.proxy.proxy_server import toolset_mcp_route + + request = _make_request("/toolset/broken_toolset/mcp") + + fake_mgr = MagicMock() + fake_mgr.get_toolset_by_name_cached = AsyncMock( + side_effect=RuntimeError("connection to db-host:5432 refused") + ) + + with ( + patch(_MCP_MANAGER, fake_mgr), + patch(_PRISMA, new=MagicMock()), + ): + with pytest.raises(HTTPException) as exc_info: + await toolset_mcp_route("broken_toolset", request) + + assert exc_info.value.status_code == 500 + assert exc_info.value.detail == "Internal server error" + assert "db-host" not in str(exc_info.value.detail) + assert "traceback" not in str(exc_info.value.detail).lower() diff --git a/tests/test_litellm/test_main.py b/tests/test_litellm/test_main.py index b03579c2dbd..113e1bc0df8 100644 --- a/tests/test_litellm/test_main.py +++ b/tests/test_litellm/test_main.py @@ -849,12 +849,13 @@ def test_gpt_5_4_responses_bridge_preserves_reasoning_summary_dict( @pytest.mark.parametrize( - "model, model_info, expected_model_param", + "model, model_info, expected_model_param, expected_base_model_param", [ - ("gemini/gemini-3.1-pro", None, "gemini-3.1-pro"), + ("gemini/gemini-3.1-pro", None, "gemini-3.1-pro", None), ( "gemini/gemini-3.1-pro", {"base_model": "gemini-3.1-pro-preview"}, + "gemini-3.1-pro", "gemini-3.1-pro-preview", ), ], @@ -863,7 +864,13 @@ def test_completion_optional_params_base_model( model: str, model_info: dict | None, expected_model_param: str, + expected_base_model_param: str | None, ): + """``model_info.base_model`` must reach ``get_optional_params`` as ``base_model`` + (an additive capability hint), without overwriting ``model`` with the label. + + Regression for #29618: overwriting ``model`` with a friendly ``base_model`` + label made Bedrock drop ``tools``/``tool_choice`` under ``drop_params``.""" with patch("litellm.main.get_optional_params") as mock_get_optional_params: mock_get_optional_params.return_value = MagicMock() @@ -881,10 +888,9 @@ def test_completion_optional_params_base_model( litellm.completion(**kwargs) assert mock_get_optional_params.called is True - get_optional_params_model_param = mock_get_optional_params.call_args.kwargs[ - "model" - ] - assert get_optional_params_model_param == expected_model_param + call_kwargs = mock_get_optional_params.call_args.kwargs + assert call_kwargs["model"] == expected_model_param + assert call_kwargs["base_model"] == expected_base_model_param @patch("litellm.completion_extras.responses_api_bridge.completion") diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 2d75671f1cb..f2b9bef9230 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -4144,3 +4144,51 @@ class TestValidateAndFixThinkingParam: validate_and_fix_thinking_param(thinking=thinking) assert "budgetTokens" in thinking assert "budget_tokens" not in thinking + + +class TestBedrockBaseModelLabelKeepsTools: + """Regression for #29618: a Bedrock deployment whose ``base_model`` is a friendly + label must not silently drop ``tools``/``tool_choice`` under ``drop_params``.""" + + TOOLS = [ + { + "type": "function", + "function": { + "name": "get_weather", + "parameters": { + "type": "object", + "properties": {"city": {"type": "string"}}, + }, + }, + } + ] + + def test_base_model_label_keeps_tools_with_drop_params(self): + from litellm.utils import get_optional_params + + result = get_optional_params( + model="eu.anthropic.claude-haiku-4-5-20251001-v1:0", + custom_llm_provider="bedrock", + base_model="claude-haiku-4-5", + tools=self.TOOLS, + tool_choice="auto", + drop_params=True, + ) + + assert "tools" in result + assert "tool_choice" in result + + def test_base_model_label_alone_drops_tools(self): + """Without the real model id the label resolves to no tool support, so passing + the label as ``model`` is exactly what dropped tools before the fix.""" + from litellm.utils import get_optional_params + + result = get_optional_params( + model="claude-haiku-4-5", + custom_llm_provider="bedrock", + tools=self.TOOLS, + tool_choice="auto", + drop_params=True, + ) + + assert "tools" not in result From 7edf3a9cb55548b143df1692f4ed7c4681d7fcf7 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Thu, 4 Jun 2026 11:37:54 -0700 Subject: [PATCH 31/92] style(ui): run prettier --write across the dashboard (#29622) Formatting-only pass; no logic changes. Brings the UI into compliance with .prettierrc so the new format-check CI job passes --- ui/litellm-dashboard/e2e_tests/globalSetup.ts | 7 +- .../e2e_tests/helpers/navigation.ts | 4 +- .../e2e_tests/playwright.config.ts | 2 +- .../e2e_tests/tests/auth/logout.spec.ts | 9 +- .../tests/auth/proxyLogoutUrl.spec.ts | 16 +- .../tests/internal-user/internalUser.spec.ts | 12 +- .../internalUserWithTeams.spec.ts | 6 +- .../internal-viewer/internalViewer.spec.ts | 6 +- .../tests/login/internalUserIdentity.spec.ts | 4 +- .../e2e_tests/tests/login/login.spec.ts | 9 +- .../e2e_tests/tests/mcp/mcpServers.spec.ts | 6 +- .../e2e_tests/tests/modelHub/modelHub.spec.ts | 5 +- .../tests/modelsPage/addModel.spec.ts | 33 +- .../modelsPage/clearCustomPricing.spec.ts | 56 +- .../tests/navigation/sidebar.spec.ts | 10 +- .../e2e_tests/tests/proxy-admin/keys.spec.ts | 8 +- .../tests/proxy-admin/license.spec.ts | 9 +- .../e2e_tests/tests/proxy-admin/teams.spec.ts | 10 +- .../tests/settings/routerSettings.spec.ts | 9 +- .../tests/team-admin/teamAdmin.spec.ts | 12 +- ui/litellm-dashboard/knip.json | 13 +- .../src/app/(dashboard)/README.md | 8 +- .../app/(dashboard)/components/Sidebar2.tsx | 1 - .../components/SidebarProvider.tsx | 6 +- .../accessGroups/useAccessGroupDetails.ts | 20 +- .../hooks/accessGroups/useAccessGroups.ts | 14 +- .../accessGroups/useCreateAccessGroup.ts | 7 +- .../accessGroups/useDeleteAccessGroup.ts | 12 +- .../hooks/accessGroups/useEditAccessGroup.ts | 7 +- .../cloudzero/useCloudZeroCreate.test.ts | 35 +- .../cloudzero/useCloudZeroDryRun.test.ts | 35 +- .../cloudzero/useCloudZeroExport.test.ts | 35 +- .../hooks/common/queryKeysFactory.test.ts | 6 +- .../configOverrides/hashicorpVaultApi.ts | 17 +- .../hooks/guardrails/useGuardrails.test.ts | 8 +- .../hooks/guardrails/useRegisterGuardrail.ts | 7 +- .../useHealthReadinessDetails.ts | 13 +- .../hooks/keys/useKeyAliases.test.ts | 12 +- .../(dashboard)/hooks/keys/useKeyAliases.ts | 14 +- .../(dashboard)/hooks/keys/useKeys.test.ts | 15 +- .../src/app/(dashboard)/hooks/keys/useKeys.ts | 18 +- .../hooks/keys/useResetKeySpend.ts | 12 +- .../hooks/logDetails/useLogDetails.ts | 6 +- .../useMCPSemanticFilterSettings.ts | 4 +- .../useUpdateMCPSemanticFilterSettings.ts | 4 +- .../mcpServers/useMCPAccessGroups.test.ts | 2 +- .../hooks/mcpServers/useMCPServerHealth.ts | 36 +- .../hooks/mcpServers/useMCPServers.test.ts | 2 +- .../app/(dashboard)/hooks/models/useModels.ts | 27 +- .../hooks/projects/useCreateProject.test.ts | 4 +- .../hooks/projects/useCreateProject.ts | 12 +- .../hooks/projects/useDeleteProject.test.ts | 4 +- .../hooks/projects/useDeleteProject.ts | 12 +- .../hooks/projects/useProjectDetails.ts | 20 +- .../(dashboard)/hooks/projects/useProjects.ts | 11 +- .../hooks/projects/useUpdateProject.test.ts | 6 +- .../hooks/projects/useUpdateProject.ts | 13 +- .../storeModelInDB/useStoreModelInDB.test.ts | 9 +- .../hooks/storeModelInDB/useStoreModelInDB.ts | 8 +- .../useStoreRequestInSpendLogs.ts | 2 +- .../(dashboard)/hooks/teams/useTeams.test.ts | 25 +- .../app/(dashboard)/hooks/teams/useTeams.ts | 24 +- .../(dashboard)/hooks/useAuthorized.test.ts | 14 +- .../(dashboard)/hooks/users/useUsers.test.ts | 70 +- .../app/(dashboard)/hooks/users/useUsers.ts | 13 +- .../src/app/(dashboard)/layout.tsx | 8 +- .../ModelsAndEndpointsView.tsx | 6 +- .../components/AllModelsTab.test.tsx | 300 ++- .../components/AllModelsTab.tsx | 78 +- .../src/app/(dashboard)/playground/page.tsx | 74 +- .../src/app/login/LoginPage.test.tsx | 3 +- .../src/app/login/LoginPage.tsx | 19 +- .../src/app/mcp/oauth/callback/page.tsx | 12 +- .../src/app/model_hub_table/page.tsx | 4 +- .../onboarding/OnboardingErrorView.test.tsx | 4 +- .../src/app/onboarding/OnboardingForm.tsx | 10 +- .../onboarding/OnboardingFormBody.test.tsx | 8 +- .../src/app/onboarding/OnboardingFormBody.tsx | 36 +- .../src/app/onboarding/page.tsx | 6 +- ui/litellm-dashboard/src/app/page.tsx | 475 ++-- .../AIHub/AgentHubTableColumns.test.tsx | 10 +- .../AIHub/ClaudeCodeMarketplaceTab.tsx | 39 +- .../components/AIHub/ModelHubTable.test.tsx | 34 +- .../src/components/AIHub/ModelHubTable.tsx | 4 +- .../components/AIHub/SkillHubDashboard.tsx | 12 +- .../AIHub/marketplace_table_columns.tsx | 10 +- .../AccessGroupsDetailsPage.test.tsx | 108 +- .../AccessGroups/AccessGroupsDetailsPage.tsx | 79 +- .../AccessGroupsModal/AccessGroupBaseForm.tsx | 20 +- .../AccessGroupCreateModal.tsx | 11 +- .../AccessGroupEditModal.tsx | 17 +- .../AccessGroups/AccessGroupsPage.test.tsx | 68 +- .../AccessGroups/AccessGroupsPage.tsx | 104 +- .../src/components/AccessGroups/types.ts | 58 +- .../src/components/BulkEditUsers.test.tsx | 12 +- .../src/components/BulkEditUsers.tsx | 12 +- .../add_margin_form.test.tsx | 37 +- .../CostTrackingSettings/add_margin_form.tsx | 17 +- .../add_provider_form.test.tsx | 19 +- .../add_provider_form.tsx | 11 +- .../cost_tracking_settings.test.tsx | 34 +- .../cost_tracking_settings.tsx | 90 +- .../CostTrackingSettings/how_it_works.tsx | 202 +- .../components/CostTrackingSettings/index.ts | 9 +- .../pricing_calculator/index.test.tsx | 28 +- .../pricing_calculator/index.tsx | 31 +- .../multi_cost_results.test.tsx | 59 +- .../pricing_calculator/multi_cost_results.tsx | 73 +- .../multi_export_dropdown.test.tsx | 6 +- .../multi_export_dropdown.tsx | 8 +- .../multi_export_utils.test.ts | 66 +- .../pricing_calculator/multi_export_utils.ts | 19 +- .../pricing_calculator/types.ts | 1 - .../use_multi_cost_estimate.test.ts | 32 +- .../use_multi_cost_estimate.ts | 10 +- .../provider_discount_table.test.tsx | 40 +- .../provider_discount_table.tsx | 5 +- .../provider_display_helpers.ts | 7 +- .../provider_margin_table.test.tsx | 42 +- .../provider_margin_table.tsx | 10 +- .../components/CostTrackingSettings/types.ts | 1 - .../use_discount_config.test.ts | 12 +- .../use_discount_config.ts | 164 +- .../use_margin_config.test.ts | 12 +- .../CostTrackingSettings/use_margin_config.ts | 199 +- .../src/components/CreateUserButton.test.tsx | 107 +- .../src/components/CreateUserButton.tsx | 26 +- .../src/components/DebugWarningBanner.tsx | 7 +- .../src/components/DefaultUserSettings.tsx | 11 +- .../DeletedKeysPage/DeletedKeysPage.tsx | 6 +- .../DeletedKeysTable/DeletedKeysTable.tsx | 53 +- .../DeletedTeamsPage/DeletedTeamsPage.tsx | 12 +- .../DeletedTeamsTable.test.tsx | 8 +- .../DeletedTeamsTable/DeletedTeamsTable.tsx | 51 +- .../ExportFormatSelector.tsx | 1 - .../EntityUsageExport/ExportSummary.test.tsx | 20 +- .../EntityUsageExport/ExportSummary.tsx | 1 - .../ExportTypeSelector.test.tsx | 20 +- .../EntityUsageExport/UsageExportHeader.tsx | 2 +- .../src/components/EntityUsageExport/index.ts | 1 - .../EntityUsageExport/utils.test.ts | 1 - .../src/components/EntityUsageExport/utils.ts | 17 +- .../src/components/GuardrailSettingsView.tsx | 11 +- .../EvaluationSettingsModal.tsx | 10 +- .../GuardrailConfig.test.tsx | 4 +- .../GuardrailsMonitor/GuardrailConfig.tsx | 26 +- .../GuardrailsMonitor/GuardrailDetail.tsx | 38 +- .../GuardrailsMonitorView.test.tsx | 11 +- .../GuardrailsMonitorView.tsx | 11 +- .../GuardrailsMonitor/GuardrailsOverview.tsx | 71 +- .../GuardrailsMonitor/LogViewer.tsx | 37 +- .../GuardrailsMonitor/MetricCard.test.tsx | 12 +- .../GuardrailsMonitor/MetricCard.tsx | 12 +- .../GuardrailsMonitor/ScoreChart.tsx | 4 +- .../src/components/HelpLink.test.tsx | 14 +- .../src/components/HelpLink.tsx | 37 +- .../PaginatedKeyAliasSelect.test.tsx | 12 +- .../PaginatedKeyAliasSelect.tsx | 15 +- .../components/MemoryView/MemoryEditModal.tsx | 37 +- .../src/components/MemoryView/MemoryView.tsx | 156 +- .../ModelSelect/ModelSelect.test.tsx | 14 +- .../components/ModelSelect/ModelSelect.tsx | 98 +- .../PaginatedModelSelect.test.tsx | 16 +- .../PaginatedModelSelect.tsx | 23 +- .../Navbar/BlogDropdown/BlogDropdown.test.tsx | 4 +- .../WorkerDropdown/WorkerDropdown.test.tsx | 7 +- .../Navbar/WorkerDropdown/WorkerDropdown.tsx | 4 +- .../src/components/OldTeams.test.tsx | 22 +- .../src/components/OldTeams.tsx | 1531 ++++++------ .../Projects/ProjectDetailsPage.test.tsx | 3 +- .../Projects/ProjectKeysSection.test.tsx | 4 +- .../Projects/ProjectKeysTable.test.tsx | 13 +- .../ProjectModals/CreateProjectModal.tsx | 15 +- .../ProjectModals/EditProjectModal.test.tsx | 24 +- .../ProjectModals/EditProjectModal.tsx | 21 +- .../ProjectModals/ProjectBaseForm.tsx | 131 +- .../ProjectModals/projectFormUtils.ts | 7 +- .../components/Projects/ProjectsPage.test.tsx | 12 +- .../src/components/Projects/ProjectsPage.tsx | 44 +- .../SearchTools/CreateSearchTools.tsx | 10 +- .../SearchTools/SearchConnectionTest.tsx | 20 +- .../SearchTools/SearchToolColumn.tsx | 180 +- .../SearchTools/SearchToolTester.test.tsx | 5 +- .../SearchTools/SearchToolTester.tsx | 106 +- .../SearchTools/SearchToolView.test.tsx | 38 +- .../components/SearchTools/SearchToolView.tsx | 33 +- .../components/SearchTools/SearchTools.tsx | 38 +- .../src/components/SearchTools/index.tsx | 11 +- .../src/components/SearchTools/types.tsx | 1 - .../EditHashicorpVaultModal.tsx | 23 +- .../HashicorpVault/HashicorpVault.tsx | 52 +- .../HashicorpVaultEmptyPlaceholder.test.tsx | 4 +- .../HashicorpVaultEmptyPlaceholder.tsx | 3 +- .../AdminSettings/HashicorpVault/constants.ts | 6 +- .../LoggingSettings/LoggingSettings.tsx | 16 +- .../MCPSemanticFilterSettings.test.tsx | 22 +- .../MCPSemanticFilterSettings.tsx | 23 +- .../MCPSemanticFilterTestPanel.test.tsx | 31 +- .../MCPSemanticFilterTestPanel.tsx | 188 +- .../semanticFilterTestUtils.test.ts | 6 +- .../semanticFilterTestUtils.ts | 14 +- .../AdminSettings/SSOSettings/SSOSettings.tsx | 37 +- .../PageVisibilitySettings.test.tsx | 30 +- .../AdminSettings/UISettings/UISettings.tsx | 8 +- .../RouterSettings/Fallbacks/AddFallbacks.tsx | 17 +- .../Fallbacks/AddFallbacksModal.test.tsx | 4 +- .../Fallbacks/AddFallbacksModal.tsx | 6 +- .../Fallbacks/FallbackGroupConfig.tsx | 31 +- .../Fallbacks/FallbackSelectionForm.test.tsx | 78 +- .../Fallbacks/FallbackSelectionForm.tsx | 10 +- .../Fallbacks/Fallbacks.test.tsx | 17 +- .../RouterSettings/Fallbacks/Fallbacks.tsx | 29 +- .../src/components/TeamSSOSettings.test.tsx | 13 +- .../src/components/TeamSSOSettings.tsx | 8 +- .../src/components/ToolDetail.tsx | 59 +- .../src/components/ToolPolicies.tsx | 19 +- .../ToolPolicies/PolicySelect.test.tsx | 43 +- .../components/ToolPolicies/PolicySelect.tsx | 3 +- .../src/components/ToolPoliciesView.tsx | 16 +- .../src/components/UsageIndicator.tsx | 50 +- .../components/EndpointUsageBarChart.test.tsx | 4 +- .../components/EntityUsage/EntityUsage.tsx | 5 +- .../EntityUsage/SpendByProvider.test.tsx | 8 +- .../EntityUsage/SpendByProvider.tsx | 8 +- .../components/KeyModelUsageView.tsx | 6 +- .../components/UsageAIChatPanel.test.tsx | 9 +- .../UsagePage/components/UsageAIChatPanel.tsx | 66 +- .../components/UsagePageView.test.tsx | 42 +- .../UsageViewSelect/UsageViewSelect.tsx | 11 +- .../hooks/usePaginatedDailyActivity.ts | 13 +- .../VirtualKeysPage/VirtualKeysTable.test.tsx | 40 +- .../VirtualKeysPage/VirtualKeysTable.tsx | 904 ++++--- .../src/components/WebRTCTester.jsx | 295 ++- .../src/components/activity_metrics.test.tsx | 12 +- .../src/components/activity_metrics.tsx | 18 +- .../add_model/AddModelForm.test.tsx | 13 +- .../src/components/add_model/AddModelForm.tsx | 4 +- .../add_model/ComplexityRouterConfig.test.tsx | 40 +- .../add_model/RouterConfigBuilder.test.tsx | 11 +- .../add_model/RouterConfigBuilder.tsx | 22 +- .../add_model/add_auto_router_tab.tsx | 52 +- .../handle_add_auto_router_submit.tsx | 5 +- .../add_model/handle_add_model_submit.tsx | 18 +- .../add_model/model_connection_test.tsx | 6 +- .../src/components/add_pass_through.tsx | 41 +- .../agent_management/AgentSelector.test.tsx | 13 +- .../agent_management/AgentSelector.tsx | 21 +- .../src/components/agents.test.tsx | 4 +- .../src/components/agents.tsx | 26 +- .../src/components/agents/add_agent_form.tsx | 152 +- .../src/components/agents/agent_card.test.tsx | 10 +- .../src/components/agents/agent_card.tsx | 25 +- .../agents/agent_card_discovery.test.tsx | 95 +- .../agents/agent_card_discovery.tsx | 106 +- .../agents/agent_card_grid.test.tsx | 20 +- .../src/components/agents/agent_cost_view.tsx | 13 +- .../agents/agent_discovery_utils.test.ts | 22 +- .../agents/agent_discovery_utils.ts | 24 +- .../components/agents/agent_form_fields.tsx | 404 ++-- .../src/components/agents/agent_info.tsx | 157 +- .../src/components/agents/agent_table.tsx | 32 +- .../src/components/agents/agent_type_utils.ts | 8 +- .../components/agents/cost_config_fields.tsx | 8 +- .../agents/dynamic_agent_form_fields.tsx | 30 +- .../components/alerting/alerting_settings.tsx | 1 - .../src/components/atoms/Tooltip.test.tsx | 6 +- .../components/budgets/budget_panel.test.tsx | 7 +- .../src/components/budgets/budget_panel.tsx | 5 +- .../components/budgets/edit_budget_modal.tsx | 21 +- .../components/bulk_create_users_button.tsx | 30 +- .../cache_settings/CacheFieldGroup.tsx | 11 +- .../src/components/chat/ChatMessages.tsx | 155 +- .../src/components/chat/ChatPage.tsx | 723 ++++-- .../src/components/chat/ConversationList.tsx | 51 +- .../src/components/chat/MCPAppsPanel.tsx | 307 ++- .../src/components/chat/MCPConnectPicker.tsx | 21 +- .../src/components/chat/MCPCredentialsTab.tsx | 35 +- .../src/components/chat/useChatHistory.ts | 142 +- .../src/components/claude_code_plugins.tsx | 21 +- .../MakeSkillPublicForm.tsx | 35 +- .../add_plugin_form.test.tsx | 20 +- .../claude_code_plugins/add_plugin_form.tsx | 82 +- .../claude_code_plugins/helpers.test.ts | 6 +- .../components/claude_code_plugins/helpers.ts | 48 +- .../claude_code_plugins/plugin_info.tsx | 66 +- .../claude_code_plugins/plugin_table.tsx | 124 +- .../claude_code_plugins/skill_detail.tsx | 74 +- .../components/claude_code_plugins/types.ts | 14 +- .../common_components/AccessGroupSelector.tsx | 14 +- .../DefaultProxyAdminTag.tsx | 4 +- .../DeleteResourceModal.test.tsx | 12 +- .../common_components/FilterTeamDropdown.tsx | 7 +- .../KeyLifecycleSettings.test.tsx | 72 +- .../KeyLifecycleSettings.tsx | 4 +- .../common_components/LabeledField.test.tsx | 16 +- .../common_components/MemberTable.tsx | 6 +- .../components/common_components/NewBadge.tsx | 8 +- .../PassThroughGuardrailsSection.tsx | 69 +- .../PassThroughRoutesSelector.tsx | 15 +- .../common_components/ProjectDropdown.tsx | 13 +- .../RateLimitTypeFormItem.test.tsx | 14 +- .../RouterSettingsAccordion.tsx | 16 +- .../TableHeaderSortDropdown.tsx | 5 +- .../common_components/simple_table.tsx | 1 - .../common_components/team_dropdown.tsx | 14 +- .../common_components/team_multi_select.tsx | 14 +- .../src/components/general_settings.tsx | 20 +- .../src/components/guardrails.tsx | 7 +- .../guardrails/GuardrailTestPanel.test.tsx | 3 +- .../guardrails/GuardrailTestPanel.tsx | 20 +- .../guardrails/GuardrailTestPlayground.tsx | 34 +- .../guardrails/GuardrailTestResults.test.tsx | 1 - .../guardrails/GuardrailTestResults.tsx | 22 +- .../guardrails/TeamGuardrailsTab.tsx | 290 +-- .../guardrails/add_guardrail_form.tsx | 51 +- .../content_filter/CategoryTable.tsx | 36 +- .../CompetitorIntentConfiguration.tsx | 55 +- .../ContentCategoryConfiguration.tsx | 76 +- .../ContentFilterConfiguration.tsx | 70 +- .../content_filter/ContentFilterDisplay.tsx | 9 +- .../ContentFilterManager.test.tsx | 74 +- .../content_filter/ContentFilterManager.tsx | 29 +- .../CustomPatternModal.test.tsx | 3 +- .../content_filter/CustomPatternModal.tsx | 19 +- .../content_filter/KeywordModal.tsx | 19 +- .../content_filter/KeywordTable.tsx | 31 +- .../content_filter/PatternModal.test.tsx | 9 +- .../content_filter/PatternModal.tsx | 21 +- .../content_filter/PatternTable.tsx | 44 +- .../custom_code/CustomCodeModal.tsx | 216 +- .../guardrails/edit_guardrail_form.tsx | 12 +- .../guardrails/guardrail_garden.tsx | 33 +- .../guardrails/guardrail_garden_card.tsx | 5 +- .../guardrails/guardrail_garden_data.ts | 18 +- .../guardrails/guardrail_garden_detail.tsx | 40 +- .../guardrails/guardrail_info.test.tsx | 21 +- .../components/guardrails/guardrail_info.tsx | 111 +- .../guardrail_info_helpers.test.tsx | 16 +- .../guardrails/guardrail_info_helpers.tsx | 2 +- .../guardrails/guardrail_optional_params.tsx | 7 +- .../guardrails/guardrail_provider_fields.tsx | 10 +- .../guardrails/llm_judge/LLMJudgeFields.tsx | 24 +- .../ToolPermissionRulesEditor.test.tsx | 4 +- .../ToolPermissionRulesEditor.tsx | 38 +- .../key_team_helpers/BudgetWindowsEditor.tsx | 27 +- .../key_team_helpers/filter_helpers.test.ts | 16 +- .../key_team_helpers/filter_logic.test.tsx | 67 +- .../src/components/leftnav.tsx | 67 +- .../src/components/logging_settings_view.tsx | 16 +- .../src/components/mcp_hub_table_columns.tsx | 17 +- .../MCPToolPermissions.tsx | 8 +- .../mcp_tools/ByokCredentialModal.tsx | 33 +- .../components/mcp_tools/MCPLogoSelector.tsx | 11 +- .../mcp_tools/MCPNetworkSettings.tsx | 17 +- .../MCPPermissionManagement.test.tsx | 63 +- .../mcp_tools/MCPPermissionManagement.tsx | 30 +- .../mcp_tools/MCPStandardsSettings.test.tsx | 10 +- .../mcp_tools/MCPSubmissionsTab.tsx | 73 +- .../mcp_tools/MCPToolArgumentsForm.tsx | 42 +- .../components/mcp_tools/MCPToolsetsTab.tsx | 113 +- .../mcp_tools/McpCrudPermissionPanel.tsx | 90 +- .../components/mcp_tools/OAuthFormFields.tsx | 72 +- .../mcp_tools/OpenAPIFormSection.tsx | 6 +- .../mcp_tools/OpenAPIQuickPicker.tsx | 13 +- .../components/mcp_tools/ToolTestPanel.tsx | 89 +- .../mcp_tools/create_mcp_server.tsx | 57 +- .../mcp_tools/mcp_connection_status.test.tsx | 30 +- .../mcp_tools/mcp_connection_status.tsx | 27 +- .../components/mcp_tools/mcp_discovery.tsx | 24 +- .../mcp_tools/mcp_server_columns.tsx | 12 +- .../components/mcp_tools/mcp_server_edit.tsx | 11 +- .../components/mcp_tools/mcp_server_view.tsx | 90 +- .../components/mcp_tools/mcp_servers.test.tsx | 10 +- .../src/components/mcp_tools/mcp_servers.tsx | 117 +- .../src/components/mcp_tools/mcp_tools.tsx | 305 ++- .../src/components/mcp_tools/utils.test.tsx | 8 +- .../components/model_add/credentials.test.tsx | 4 +- .../src/components/model_add/credentials.tsx | 4 +- .../ModelSettingsModal.test.tsx | 18 +- .../ModelSettingsModal/ModelSettingsModal.tsx | 6 +- .../model_dashboard/all_models_table.tsx | 32 +- .../src/components/model_info_view.test.tsx | 4 +- .../src/components/model_info_view.tsx | 51 +- .../molecules/models/columns.test.tsx | 40 +- .../components/molecules/models/columns.tsx | 769 +++--- .../src/components/networking.tsx | 295 +-- .../components/object_permissions_view.tsx | 6 +- .../organisms/RegenerateKeyModal.tsx | 8 +- .../organisms/create_key_button.test.tsx | 87 +- .../organisms/create_key_button.tsx | 14 +- .../organization/organization_view.tsx | 37 +- .../src/components/page_utils.test.ts | 109 +- .../src/components/page_utils.ts | 6 +- .../src/components/pass_through_info.tsx | 20 +- .../src/components/pass_through_settings.tsx | 8 +- .../permissions/AgentPermissions.tsx | 17 +- .../permissions/MCPServerPermissions.test.tsx | 25 +- .../permissions/MCPServerPermissions.tsx | 111 +- .../playground/chat_ui/A2AMetrics.tsx | 12 +- .../chat_ui/AdditionalModelSettings.test.tsx | 12 +- .../chat_ui/AdditionalModelSettings.tsx | 9 +- .../playground/chat_ui/AgentBuilderView.tsx | 77 +- .../chat_ui/ChatMessageBubble.test.tsx | 48 +- .../playground/chat_ui/ChatMessageBubble.tsx | 8 +- .../playground/chat_ui/ChatUI.test.tsx | 8 +- .../components/playground/chat_ui/ChatUI.tsx | 2136 ++++++++--------- .../chat_ui/CodeInterpreterOutput.tsx | 54 +- .../chat_ui/CodeInterpreterTool.tsx | 2 +- .../playground/chat_ui/CodeSnippets.tsx | 2 +- .../chat_ui/FilePreviewCard.test.tsx | 32 +- .../playground/chat_ui/FilePreviewCard.tsx | 4 +- .../playground/chat_ui/RealtimePlayground.tsx | 59 +- .../chat_ui/SearchResultsDisplay.tsx | 5 +- .../playground/chat_ui/useChatHistory.test.ts | 8 +- .../playground/chat_ui/useChatHistory.ts | 8 +- .../playground/chat_ui/useCodeInterpreter.ts | 2 +- .../playground/compareUI/CompareUI.test.tsx | 2 +- .../playground/compareUI/CompareUI.tsx | 15 +- .../compareUI/components/ComparisonPanel.tsx | 4 +- .../components/MessageInput.test.tsx | 8 +- .../compareUI/components/UnifiedSelector.tsx | 13 +- .../playground/compareUI/endpoint_config.ts | 16 +- .../playground/complianceUI/ComplianceUI.tsx | 1780 +++++++------- .../playground/llm_calls/a2a_send_message.tsx | 8 +- .../playground/llm_calls/chat_completion.tsx | 23 +- .../llm_calls/code_interpreter_handler.ts | 17 +- .../playground/llm_calls/fetch_agents.tsx | 8 +- .../playground/llm_calls/interactions_api.tsx | 4 +- .../policies/PolicySelector.test.tsx | 10 +- .../components/policies/PolicySelector.tsx | 4 +- .../policies/add_attachment_form.test.tsx | 5 +- .../policies/add_attachment_form.tsx | 73 +- .../components/policies/add_policy_form.tsx | 65 +- .../policies/ai_suggestion_modal.tsx | 686 +++--- .../policies/attachment_table.test.tsx | 37 +- .../policies/build_attachment_data.test.ts | 2 +- .../policies/build_attachment_data.ts | 2 +- .../policies/guardrail_selection_modal.tsx | 61 +- .../policies/impact_popover.test.tsx | 14 +- .../components/policies/impact_popover.tsx | 21 +- .../policies/impact_preview_alert.tsx | 38 +- .../src/components/policies/index.test.tsx | 13 +- .../src/components/policies/index.tsx | 58 +- .../policies/pipeline_flow_builder.tsx | 262 +- .../src/components/policies/policy_info.tsx | 25 +- .../components/policies/policy_table.test.tsx | 34 +- .../src/components/policies/policy_table.tsx | 11 +- .../policies/policy_templates.test.tsx | 20 +- .../components/policies/policy_templates.tsx | 62 +- .../components/policies/policy_test_panel.tsx | 62 +- .../policies/template_parameter_modal.tsx | 48 +- .../src/components/price_data_reload.tsx | 10 +- .../DeveloperMessageCard.tsx | 17 +- .../prompt_editor_view/DotpromptViewTab.tsx | 13 +- .../prompt_editor_view/ModelConfigCard.tsx | 13 +- .../prompt_editor_view/PromptCodeSnippets.tsx | 67 +- .../prompt_editor_view/PromptEditorHeader.tsx | 20 +- .../prompt_editor_view/PromptMessagesCard.tsx | 13 +- .../prompt_editor_view/PublishModal.tsx | 3 +- .../prompts/prompt_editor_view/ToolsCard.tsx | 23 +- .../VersionHistorySidePanel.tsx | 28 +- .../conversation_panel/EmptyState.tsx | 1 - .../conversation_panel/MessageBubble.tsx | 24 +- .../conversation_panel/MessageInput.tsx | 6 +- .../conversation_panel/MessageList.tsx | 8 +- .../conversation_panel/VariableInput.tsx | 15 +- .../conversation_panel/VariableWarning.tsx | 12 +- .../conversation_panel/index.tsx | 5 +- .../conversation_panel/types.ts | 1 - .../prompts/prompt_editor_view/index.tsx | 25 +- .../prompts/prompt_editor_view/types.ts | 1 - .../prompts/prompt_editor_view/utils.ts | 8 +- .../src/components/prompts/prompt_info.tsx | 107 +- .../src/components/prompts/prompt_table.tsx | 37 +- .../src/components/prompts/prompt_utils.tsx | 19 +- .../src/components/prompts/tool_modal.tsx | 7 +- .../components/prompts/variable_textarea.tsx | 18 +- .../src/components/public_model_hub.tsx | 6 +- .../src/components/query_param_input.tsx | 2 +- .../src/components/route_preview.tsx | 8 +- .../LatencyBasedConfiguration.test.tsx | 10 +- .../LatencyBasedConfiguration.tsx | 13 +- .../ReliabilityRetriesSection.test.tsx | 20 +- .../ReliabilityRetriesSection.tsx | 1 - .../RouterSettingsForm.test.tsx | 20 +- .../RoutingStrategySelector.test.tsx | 12 +- .../RoutingStrategySelector.tsx | 12 +- .../TagFilteringToggle.test.tsx | 44 +- .../router_settings/TagFilteringToggle.tsx | 13 +- .../components/router_settings/index.test.tsx | 32 +- .../src/components/router_settings/index.tsx | 4 +- .../routing_groups/RoutingGroupModal.tsx | 22 +- .../routing_groups/RoutingGroupsTable.tsx | 16 +- .../src/components/routing_groups/index.tsx | 24 +- .../src/components/routing_groups/types.ts | 6 +- .../components/shared/CreatedKeyDisplay.tsx | 8 +- .../components/skill_hub_table_columns.tsx | 18 +- .../survey/ClaudeCodeModal.test.tsx | 26 +- .../src/components/survey/ClaudeCodeModal.tsx | 14 +- .../survey/ClaudeCodePrompt.test.tsx | 20 +- .../components/survey/ClaudeCodePrompt.tsx | 3 +- .../src/components/survey/NudgePrompt.tsx | 19 +- .../components/survey/SurveyModal.test.tsx | 80 +- .../src/components/survey/SurveyModal.tsx | 24 +- .../components/survey/SurveyPrompt.test.tsx | 20 +- .../src/components/survey/SurveyPrompt.tsx | 1 - .../src/components/survey/index.tsx | 1 - .../src/components/team/EditMembership.tsx | 8 +- .../src/components/team/MyUserTab.tsx | 23 +- .../src/components/team/TeamInfo.test.tsx | 39 +- .../src/components/team/TeamInfo.tsx | 183 +- .../src/components/team/TeamMemberTab.tsx | 16 +- .../team/TeamVirtualKeysTable.test.tsx | 48 +- .../components/team/TeamVirtualKeysTable.tsx | 55 +- .../src/components/team/available_teams.tsx | 6 +- .../team/permission_definitions.tsx | 16 +- .../team/tabVisibilityUtils.test.ts | 6 +- .../src/components/team/tabVisibilityUtils.ts | 11 +- .../src/components/team/useMyTeamMember.ts | 15 +- .../components/templates/KeyInfoHeader.tsx | 28 +- .../key_info_view.budget_display.test.tsx | 4 +- .../templates/key_info_view.test.tsx | 102 +- .../components/templates/key_info_view.tsx | 74 +- .../components/ui/AntDLoadingSpinner.test.tsx | 7 +- .../src/components/ui_theme_settings.tsx | 71 +- .../src/components/user_dashboard.test.tsx | 12 +- .../src/components/user_edit_view.tsx | 12 +- .../CreateVectorStore.test.tsx | 4 +- .../CreateVectorStore.tsx | 28 +- .../S3VectorsConfig.test.tsx | 2 +- .../S3VectorsConfig.tsx | 14 +- .../TestVectorStoreTab.tsx | 6 +- .../VectorStoreForm.tsx | 4 +- .../VectorStoreTable.tsx | 19 +- .../vector_store_management/index.tsx | 13 +- .../AuditLogDrawer/AuditLogDrawer.tsx | 36 +- .../view_logs/CostBreakdownViewer.test.tsx | 42 +- .../view_logs/CostBreakdownViewer.tsx | 289 +-- .../components/view_logs/ErrorViewer.test.tsx | 4 +- .../view_logs/EvalViewer/EvalViewer.tsx | 31 +- .../GuardrailViewer/CompliancePanel.tsx | 22 +- .../GuardrailViewer/ContentFilterDetails.tsx | 6 +- .../GuardrailViewer/GuardrailViewer.tsx | 104 +- .../CollapsibleMessage.test.tsx | 20 +- .../LogDetailsDrawer/CollapsibleMessage.tsx | 44 +- .../LogDetailsDrawer/DrawerHeader.tsx | 10 +- .../LogDetailsDrawer/HistoryTree.test.tsx | 12 +- .../LogDetailsDrawer/HistoryTree.tsx | 38 +- .../LogDetailsDrawer/InputCard.test.tsx | 2 +- .../view_logs/LogDetailsDrawer/InputCard.tsx | 32 +- .../LogDetailsDrawer/LogDetailContent.tsx | 76 +- .../LogDetailsDrawer/LogDetailsDrawer.tsx | 123 +- .../LogDetailsDrawer/OutputCard.test.tsx | 2 +- .../view_logs/LogDetailsDrawer/OutputCard.tsx | 49 +- .../LogDetailsDrawer/PrettyMessagesView.tsx | 14 +- .../RealtimePrettyView.test.tsx | 26 +- .../LogDetailsDrawer/RealtimePrettyView.tsx | 266 +- .../LogDetailsDrawer/SectionHeader.tsx | 71 +- .../SimpleMessageBlock.test.tsx | 24 +- .../LogDetailsDrawer/SimpleMessageBlock.tsx | 37 +- .../SimpleToolCallBlock.test.tsx | 20 +- .../LogDetailsDrawer/SimpleToolCallBlock.tsx | 28 +- .../LogDetailsDrawer/prettyMessagesTypes.ts | 2 +- .../LogDetailsDrawer/prettyMessagesUtils.ts | 84 +- .../components/view_logs/LogsTableToolbar.tsx | 13 +- .../view_logs/RequestResponsePanel.test.tsx | 8 +- .../ToolsSection/FormattedToolView.tsx | 28 +- .../ToolsSection/ToolExpandedContent.tsx | 12 +- .../view_logs/ToolsSection/ToolItem.tsx | 4 +- .../view_logs/ToolsSection/ToolsSection.tsx | 2 +- .../view_logs/ToolsSection/utils.ts | 33 +- .../src/components/view_logs/TypeBadges.tsx | 36 +- .../view_logs/VectorStoreViewer.tsx | 174 +- .../src/components/view_logs/audit_logs.tsx | 96 +- .../src/components/view_logs/columns.tsx | 6 +- .../src/components/view_logs/table.tsx | 25 +- .../src/components/view_logs/utils.ts | 9 +- .../src/components/view_users.tsx | 27 +- .../src/components/view_users/columns.tsx | 3 +- .../src/components/view_users/table.test.tsx | 8 +- .../view_users/user_info_view.test.tsx | 9 +- .../components/view_users/user_info_view.tsx | 137 +- .../src/components/workflow_runs/index.tsx | 140 +- .../src/contexts/ThemeContext.tsx | 4 +- .../src/data/canadianPiiCompliancePrompts.ts | 102 +- .../src/data/claimsCompliancePrompts.ts | 104 +- .../data/codeExecutionCompliancePrompts.ts | 220 +- .../src/data/compliancePrompts.ts | 65 +- .../src/data/financialCompliancePrompts.ts | 624 +++-- .../src/data/insultsCompliancePrompts.ts | 900 ++++--- .../useDeletePolicyAttachment.test.tsx | 4 +- .../policies/useDeletePolicyAttachment.ts | 6 +- .../src/hooks/useMcpOAuthFlow.tsx | 18 +- .../src/hooks/useTestMCPConnection.tsx | 57 +- .../src/hooks/useToolsOAuthFlow.tsx | 10 +- .../src/hooks/useUserMcpOAuthFlow.tsx | 4 +- ui/litellm-dashboard/src/hooks/useWorker.ts | 3 +- .../src/utils/cookieUtils.test.ts | 24 +- ui/litellm-dashboard/src/utils/errorUtils.ts | 16 +- .../src/utils/mcpTokenStore.test.ts | 8 +- .../src/utils/mcpTokenStore.ts | 11 +- .../src/utils/proxyUtils.test.ts | 2 +- .../src/utils/returnUrlUtils.test.ts | 8 +- ui/litellm-dashboard/src/utils/roles.test.ts | 4 +- ui/litellm-dashboard/src/utils/roles.ts | 6 +- .../src/utils/secureStorage.ts | 9 +- .../tests/CreateKeyPage.expiredToken.test.tsx | 2 +- ui/litellm-dashboard/tsconfig.json | 24 +- 608 files changed, 13772 insertions(+), 16368 deletions(-) diff --git a/ui/litellm-dashboard/e2e_tests/globalSetup.ts b/ui/litellm-dashboard/e2e_tests/globalSetup.ts index 6ff5522244a..8f80f57bd78 100644 --- a/ui/litellm-dashboard/e2e_tests/globalSetup.ts +++ b/ui/litellm-dashboard/e2e_tests/globalSetup.ts @@ -14,10 +14,9 @@ async function globalSetup() { await page.getByPlaceholder("Enter your username").fill(email); await page.getByPlaceholder("Enter your password").fill(password); await page.getByRole("button", { name: "Login", exact: true }).click(); - await page.waitForURL( - (url) => url.pathname.startsWith("/ui") && !url.pathname.includes("/login"), - { timeout: 30_000 }, - ); + await page.waitForURL((url) => url.pathname.startsWith("/ui") && !url.pathname.includes("/login"), { + timeout: 30_000, + }); await expect(page.locator("a", { hasText: "Virtual Keys" })).toBeVisible({ timeout: 30_000 }); // Dismiss feedback popup if present const dismiss = page.getByText("Don't ask me again"); diff --git a/ui/litellm-dashboard/e2e_tests/helpers/navigation.ts b/ui/litellm-dashboard/e2e_tests/helpers/navigation.ts index 556e964842a..6ca18890f7a 100644 --- a/ui/litellm-dashboard/e2e_tests/helpers/navigation.ts +++ b/ui/litellm-dashboard/e2e_tests/helpers/navigation.ts @@ -20,7 +20,9 @@ export async function dismissFeedbackPopup(page: PlaywrightPage): Promise if (await dismissButton.isVisible({ timeout: 1_500 }).catch(() => false)) { await dismissButton.click(); // Wait for the popup to disappear - await expect(dismissButton).not.toBeVisible({ timeout: 2_000 }).catch(() => {}); + await expect(dismissButton) + .not.toBeVisible({ timeout: 2_000 }) + .catch(() => {}); } } diff --git a/ui/litellm-dashboard/e2e_tests/playwright.config.ts b/ui/litellm-dashboard/e2e_tests/playwright.config.ts index 6964fe52a14..8d586ce9503 100644 --- a/ui/litellm-dashboard/e2e_tests/playwright.config.ts +++ b/ui/litellm-dashboard/e2e_tests/playwright.config.ts @@ -31,7 +31,7 @@ export default defineConfig({ /* Slow down actions when SLOWMO= is set, useful for headed local debugging */ launchOptions: { - slowMo: process.env.SLOWMO ? (parseInt(process.env.SLOWMO, 10) || 0) : 0, + slowMo: process.env.SLOWMO ? parseInt(process.env.SLOWMO, 10) || 0 : 0, }, }, diff --git a/ui/litellm-dashboard/e2e_tests/tests/auth/logout.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/auth/logout.spec.ts index fefadf27548..d8644babfe3 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/auth/logout.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/auth/logout.spec.ts @@ -13,9 +13,12 @@ test.describe("Logout", () => { // is declared with trigger={["click"]}, so a plain click opens the popup. await page.getByRole("button", { name: /Account menu/i }).click(); - const popup = page.locator(".ant-dropdown:visible").filter({ - has: page.locator(".bg-white.rounded-lg.shadow-lg"), - }).first(); + const popup = page + .locator(".ant-dropdown:visible") + .filter({ + has: page.locator(".bg-white.rounded-lg.shadow-lg"), + }) + .first(); await expect(popup).toBeVisible({ timeout: 5_000 }); // Click Logout — the handler clears the auth cookie and navigates via diff --git a/ui/litellm-dashboard/e2e_tests/tests/auth/proxyLogoutUrl.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/auth/proxyLogoutUrl.spec.ts index 4a233ed1bb1..6358fcf438e 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/auth/proxyLogoutUrl.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/auth/proxyLogoutUrl.spec.ts @@ -38,10 +38,9 @@ test.describe("PROXY_LOGOUT_URL redirect", () => { // fetch (/sso/get/ui_settings) resolves. Clicking Logout before that lands // runs `window.location.href = ""` — a same-origin reload, not a redirect — // so gate the click on the settings response, not just on first paint. - const settingsLoaded = page.waitForResponse( - (r) => r.url().includes("/sso/get/ui_settings") && r.ok(), - { timeout: 30_000 }, - ); + const settingsLoaded = page.waitForResponse((r) => r.url().includes("/sso/get/ui_settings") && r.ok(), { + timeout: 30_000, + }); await page.goto("/ui"); await expect(page.getByText("Virtual Keys")).toBeVisible({ timeout: 15_000 }); await settingsLoaded; @@ -59,10 +58,7 @@ test.describe("PROXY_LOGOUT_URL redirect", () => { // handleLogout clears cookies/local storage, then assigns window.location.href. // Arm the navigation wait before the click so we never miss the redirect. - await Promise.all([ - page.waitForURL((url) => url.origin === target.origin, { timeout: 15_000 }), - logout.click(), - ]); + await Promise.all([page.waitForURL((url) => url.origin === target.origin, { timeout: 15_000 }), logout.click()]); // The browser landed on exactly the configured logout URL. Compare normalized // hrefs (both sides through URL()) so trailing-slash / default-port rewrites the @@ -74,9 +70,7 @@ test.describe("PROXY_LOGOUT_URL redirect", () => { // ...and the client-side session cookie is gone (clearTokenCookies ran before // the redirect). HttpOnly cookies set server-side can't be cleared from JS, // so scope the check to the JS-managed token the UI is responsible for. - const clientTokensAfter = (await page.context().cookies()).filter( - (c) => c.name === "token" && !c.httpOnly, - ); + const clientTokensAfter = (await page.context().cookies()).filter((c) => c.name === "token" && !c.httpOnly); expect(clientTokensAfter, "client token cookie should be cleared on logout").toHaveLength(0); }); }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUser.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUser.spec.ts index c706ae0aefc..07a75dc007d 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUser.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUser.spec.ts @@ -22,9 +22,9 @@ test.describe("Internal User", () => { const teamSelect = page.locator(".ant-select", { hasText: "Search or select a team" }); await teamSelect.click(); await page.keyboard.type(E2E_TEAM_CRUD_ALIAS); - await expect( - page.locator(".ant-select-dropdown:visible").getByText(E2E_TEAM_CRUD_ALIAS).first(), - ).toBeVisible({ timeout: 5_000 }); + await expect(page.locator(".ant-select-dropdown:visible").getByText(E2E_TEAM_CRUD_ALIAS).first()).toBeVisible({ + timeout: 5_000, + }); }); test("Team info page omits the Settings tab for non-admin members", async ({ page }) => { @@ -44,9 +44,9 @@ test.describe("Internal User", () => { // Anchor on the user's own seeded key so the absence check below cannot // pass vacuously against an empty table. - await expect( - page.locator("table tbody").getByText(E2E_INTERNAL_USER_KEY_ALIAS).first(), - ).toBeVisible({ timeout: 10_000 }); + await expect(page.locator("table tbody").getByText(E2E_INTERNAL_USER_KEY_ALIAS).first()).toBeVisible({ + timeout: 10_000, + }); // The litellm-dashboard team is the proxy's internal bookkeeping team — // its keys must never leak into an internal user's Virtual Keys table. diff --git a/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUserWithTeams.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUserWithTeams.spec.ts index f6b60f411b4..7d5058a8140 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUserWithTeams.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/internal-user/internalUserWithTeams.spec.ts @@ -1,9 +1,5 @@ import { test, expect } from "@playwright/test"; -import { - INTERNAL_USER_STORAGE_PATH, - E2E_TEAM_CRUD_ALIAS, - E2E_TEAM_ORG_ALIAS, -} from "../../constants"; +import { INTERNAL_USER_STORAGE_PATH, E2E_TEAM_CRUD_ALIAS, E2E_TEAM_ORG_ALIAS } from "../../constants"; import { Page } from "../../fixtures/pages"; import { navigateToPage } from "../../helpers/navigation"; diff --git a/ui/litellm-dashboard/e2e_tests/tests/internal-viewer/internalViewer.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/internal-viewer/internalViewer.spec.ts index f5ab3c00503..4de86c46398 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/internal-viewer/internalViewer.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/internal-viewer/internalViewer.spec.ts @@ -1,9 +1,5 @@ import { test, expect } from "@playwright/test"; -import { - E2E_TEAM_CRUD_ID, - E2E_VIEWER_KEY_ALIAS, - INTERNAL_VIEWER_STORAGE_PATH, -} from "../../constants"; +import { E2E_TEAM_CRUD_ID, E2E_VIEWER_KEY_ALIAS, INTERNAL_VIEWER_STORAGE_PATH } from "../../constants"; import { Page } from "../../fixtures/pages"; import { navigateToPage } from "../../helpers/navigation"; diff --git a/ui/litellm-dashboard/e2e_tests/tests/login/internalUserIdentity.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/login/internalUserIdentity.spec.ts index cbe95276929..6008049a2aa 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/login/internalUserIdentity.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/login/internalUserIdentity.spec.ts @@ -22,9 +22,7 @@ test.describe("Navbar identity scoping", () => { await expect(accountButton).toHaveAttribute("aria-label", /Internal User/, { timeout: 5_000 }); await expect(accountButton).toHaveAttribute( "aria-label", - new RegExp( - `signed in as (${escapeRegExp(E2E_INTERNAL_USER_EMAIL)}|${escapeRegExp(E2E_INTERNAL_USER_ID)})`, - ), + new RegExp(`signed in as (${escapeRegExp(E2E_INTERNAL_USER_EMAIL)}|${escapeRegExp(E2E_INTERNAL_USER_ID)})`), { timeout: 5_000 }, ); diff --git a/ui/litellm-dashboard/e2e_tests/tests/login/login.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/login/login.spec.ts index 994d211cc18..d1b64f37156 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/login/login.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/login/login.spec.ts @@ -21,9 +21,12 @@ test("user can log in", async ({ page }) => { // Filter by the popupRender wrapper class to disambiguate from other // ant-dropdown popups. - const popup = page.locator(".ant-dropdown:visible").filter({ - has: page.locator(".bg-white.rounded-lg.shadow-lg"), - }).first(); + const popup = page + .locator(".ant-dropdown:visible") + .filter({ + has: page.locator(".bg-white.rounded-lg.shadow-lg"), + }) + .first(); await expect(popup).toBeVisible({ timeout: 5_000 }); await expect(popup.getByText("Admin", { exact: true })).toBeVisible({ timeout: 5_000 }); await expect(popup.getByText("default_user_id", { exact: true })).toBeVisible({ timeout: 5_000 }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/mcp/mcpServers.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/mcp/mcpServers.spec.ts index f953a82daaa..22ba85956da 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/mcp/mcpServers.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/mcp/mcpServers.spec.ts @@ -54,9 +54,7 @@ test.describe("MCP Servers", () => { // the MCP servers table so the form modal's `server_name` input — which // still holds the timestamped value during its close animation — can't // satisfy the assertion before the server actually lands in the list. - await expect(page.getByText("MCP Server created successfully").first()) - .toBeVisible({ timeout: 15_000 }); - await expect(page.locator("table tbody").getByText(uniqueName).first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText("MCP Server created successfully").first()).toBeVisible({ timeout: 15_000 }); + await expect(page.locator("table tbody").getByText(uniqueName).first()).toBeVisible({ timeout: 10_000 }); }); }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/modelHub/modelHub.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/modelHub/modelHub.spec.ts index ada4dfb735e..ca9c35ce722 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/modelHub/modelHub.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/modelHub/modelHub.spec.ts @@ -31,8 +31,9 @@ test.describe("AI Hub (internal admin view)", () => { // Submit await modal.getByRole("button", { name: "Make Public" }).click(); - await expect(page.getByText(/Successfully made .* model group\(s\) public/i).first()) - .toBeVisible({ timeout: 15_000 }); + await expect(page.getByText(/Successfully made .* model group\(s\) public/i).first()).toBeVisible({ + timeout: 15_000, + }); }); test("AI Hub tab list renders Model Hub, Agent Hub, MCP Hub and Skill Hub", async ({ page }) => { diff --git a/ui/litellm-dashboard/e2e_tests/tests/modelsPage/addModel.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/modelsPage/addModel.spec.ts index bb53fb7a23b..17ff1fc3f83 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/modelsPage/addModel.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/modelsPage/addModel.spec.ts @@ -154,10 +154,7 @@ test.describe("Add Model", () => { // The Team-BYOK switch is gated on `premiumUser` — without a license set // for the proxy under test, the toggle is disabled and this manual-QA // step cannot be exercised. - test.skip( - !process.env.LITELLM_LICENSE, - "LITELLM_LICENSE not set in test env — Team-BYOK switch is disabled", - ); + test.skip(!process.env.LITELLM_LICENSE, "LITELLM_LICENSE not set in test env — Team-BYOK switch is disabled"); // Make the test idempotent across retries and local reruns: delete any // Cohere model already scoped to the e2e team before we start, and again @@ -170,10 +167,11 @@ test.describe("Add Model", () => { const res = await request.get("/v2/model/info", { headers: auth }); if (!res.ok()) return; const body = await res.json(); - const matches: Array<{ id: string }> = (body?.data ?? []).filter((m: any) => - typeof m?.model_name === "string" && - m.model_name.startsWith("cohere") && - m?.model_info?.team_id === E2E_TEAM_CRUD_ID, + const matches: Array<{ id: string }> = (body?.data ?? []).filter( + (m: any) => + typeof m?.model_name === "string" && + m.model_name.startsWith("cohere") && + m?.model_info?.team_id === E2E_TEAM_CRUD_ID, ); for (const m of matches) { await request.post("/model/delete", { headers: auth, data: { id: m.id } }); @@ -208,9 +206,7 @@ test.describe("Add Model", () => { const teamDropdown = page.getByTestId("team-dropdown"); await expect(teamDropdown).toBeVisible({ timeout: 5_000 }); await teamDropdown.click(); - const teamOption = page.locator(".ant-select-dropdown:visible") - .getByText(E2E_TEAM_CRUD_ID) - .first(); + const teamOption = page.locator(".ant-select-dropdown:visible").getByText(E2E_TEAM_CRUD_ID).first(); await expect(teamOption).toBeVisible({ timeout: 5_000 }); await teamOption.click(); @@ -219,8 +215,9 @@ test.describe("Add Model", () => { // Scope the success toast to antd's notification container so a stale // success message from an earlier test in the same context can't satisfy // the assertion. - await expect(page.locator(".ant-notification").getByText("created successfully").last()) - .toBeVisible({ timeout: 15_000 }); + await expect(page.locator(".ant-notification").getByText("created successfully").last()).toBeVisible({ + timeout: 15_000, + }); // Verify the model is now in All Models with the team_id attached. The // Models table renders team-scoped models with the team id in the row. @@ -237,16 +234,16 @@ test.describe("Add Model", () => { // Confirm the search returned at least one result — gives a clear // failure message when the table is empty instead of timing out on a // row assertion. - await expect(page.getByTestId("models-results-count")).toHaveText( - /Showing \d+ - \d+ of \d+ results/, - { timeout: 15_000 }, - ); + await expect(page.getByTestId("models-results-count")).toHaveText(/Showing \d+ - \d+ of \d+ results/, { + timeout: 15_000, + }); // Stronger than "alias appears somewhere in tbody" — pin the assertion // to a single row that has BOTH the cohere model_name AND the seeded // team alias, so a stale cohere row from "Add wildcard route" (no team) // can't satisfy the check. - const teamCohereRow = page.locator("table tbody tr") + const teamCohereRow = page + .locator("table tbody tr") .filter({ hasText: "cohere/" }) .filter({ hasText: E2E_TEAM_CRUD_ALIAS }); await expect(teamCohereRow).toHaveCount(1, { timeout: 15_000 }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/modelsPage/clearCustomPricing.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/modelsPage/clearCustomPricing.spec.ts index d21192d237d..877c7f8c555 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/modelsPage/clearCustomPricing.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/modelsPage/clearCustomPricing.spec.ts @@ -62,9 +62,7 @@ test.describe("Clear custom pricing on a deployment", () => { } }); - test("UI sends null for cleared pricing and backend removes the override", async ({ - page, - }) => { + test("UI sends null for cleared pricing and backend removes the override", async ({ page }) => { // Navigate to the model detail view. await page.goto("/ui"); await page.getByText("Models + Endpoints").click(); @@ -97,34 +95,24 @@ test.describe("Clear custom pricing on a deployment", () => { // Capture the outgoing PATCH so we can assert the UI sends explicit nulls. const patchPromise = page.waitForRequest( - (req) => - req.method() === "PATCH" && - req.url().includes(`/model/${createdModelId}/update`) + (req) => req.method() === "PATCH" && req.url().includes(`/model/${createdModelId}/update`), ); await page.getByRole("button", { name: "Save Changes" }).click(); const patchReq = await patchPromise; const patchBody = JSON.parse(patchReq.postData() ?? "{}"); - expect( - patchBody.litellm_params.input_cost_per_token, - "UI sends explicit null for cleared input cost" - ).toBeNull(); - expect( - patchBody.litellm_params.output_cost_per_token, - "UI sends explicit null for cleared output cost" - ).toBeNull(); + expect(patchBody.litellm_params.input_cost_per_token, "UI sends explicit null for cleared input cost").toBeNull(); + expect(patchBody.litellm_params.output_cost_per_token, "UI sends explicit null for cleared output cost").toBeNull(); expect( patchBody.litellm_params.cache_read_input_token_cost, - "UI sends explicit null for cleared cache_read cost" + "UI sends explicit null for cleared cache_read cost", ).toBeNull(); expect( patchBody.litellm_params.cache_creation_input_token_cost, - "UI sends explicit null for cleared cache_write cost" + "UI sends explicit null for cleared cache_write cost", ).toBeNull(); // Success toast confirms the save was accepted. - await expect( - page.getByText("Model settings updated successfully") - ).toBeVisible({ timeout: 10_000 }); + await expect(page.getByText("Model settings updated successfully")).toBeVisible({ timeout: 10_000 }); // Verify via the management API: the user-set rate is gone from both blobs. // The cost-map may synthesize a default for known providers in the response, @@ -132,46 +120,40 @@ test.describe("Clear custom pricing on a deployment", () => { // undefined. const infoRes = await page.request.get( `/v2/model/info?include_team_models=true&page=1&size=100&modelId=${createdModelId}`, - { headers: { Authorization: `Bearer ${masterKey}` } } + { headers: { Authorization: `Bearer ${masterKey}` } }, ); expect(infoRes.ok()).toBe(true); const infoBody = await infoRes.json(); - const row = (infoBody.data ?? infoBody).find?.( - (m: any) => m?.model_info?.id === createdModelId - ); + const row = (infoBody.data ?? infoBody).find?.((m: any) => m?.model_info?.id === createdModelId); expect(row, "model info row").toBeTruthy(); - expect( - "input_cost_per_token" in row.litellm_params, - "litellm_params.input_cost_per_token key removed" - ).toBe(false); - expect( - "output_cost_per_token" in row.litellm_params, - "litellm_params.output_cost_per_token key removed" - ).toBe(false); + expect("input_cost_per_token" in row.litellm_params, "litellm_params.input_cost_per_token key removed").toBe(false); + expect("output_cost_per_token" in row.litellm_params, "litellm_params.output_cost_per_token key removed").toBe( + false, + ); expect( "cache_read_input_token_cost" in row.litellm_params, - "litellm_params.cache_read_input_token_cost key removed" + "litellm_params.cache_read_input_token_cost key removed", ).toBe(false); expect( "cache_creation_input_token_cost" in row.litellm_params, - "litellm_params.cache_creation_input_token_cost key removed" + "litellm_params.cache_creation_input_token_cost key removed", ).toBe(false); expect( row.model_info.input_cost_per_token, - "model_info.input_cost_per_token no longer the seeded override" + "model_info.input_cost_per_token no longer the seeded override", ).not.toBe(SEED_INPUT_PER_TOKEN); expect( row.model_info.output_cost_per_token, - "model_info.output_cost_per_token no longer the seeded override" + "model_info.output_cost_per_token no longer the seeded override", ).not.toBe(SEED_OUTPUT_PER_TOKEN); expect( row.model_info.cache_read_input_token_cost, - "model_info.cache_read_input_token_cost no longer the seeded override" + "model_info.cache_read_input_token_cost no longer the seeded override", ).not.toBe(SEED_CACHE_READ_PER_TOKEN); expect( row.model_info.cache_creation_input_token_cost, - "model_info.cache_creation_input_token_cost no longer the seeded override" + "model_info.cache_creation_input_token_cost no longer the seeded override", ).not.toBe(SEED_CACHE_WRITE_PER_TOKEN); }); }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/navigation/sidebar.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/navigation/sidebar.spec.ts index f56b5875dc6..b8fb95b764d 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/navigation/sidebar.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/navigation/sidebar.spec.ts @@ -6,15 +6,7 @@ import { menuLabelToPage } from "../../fixtures/menuMappings"; import { navigateToPage } from "../../helpers/navigation"; const sidebarButtons = { - [Role.ProxyAdmin]: [ - "Virtual Keys", - "Playground", - "Models", - "Usage", - "Teams", - "Internal Users", - "AI Hub", - ], + [Role.ProxyAdmin]: ["Virtual Keys", "Playground", "Models", "Usage", "Teams", "Internal Users", "AI Hub"], }; const roles = [{ role: Role.ProxyAdmin, storage: ADMIN_STORAGE_PATH }]; diff --git a/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/keys.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/keys.spec.ts index 1e44d9a25a0..644228c5ff9 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/keys.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/keys.spec.ts @@ -89,12 +89,8 @@ test.describe("Proxy Admin - Keys", () => { await page.getByRole("spinbutton", { name: "RPM Limit" }).fill("456"); await page.getByRole("button", { name: "Save Changes" }).click(); - await expect( - page.getByRole("paragraph").filter({ hasText: "TPM: 123" }) - ).toBeVisible({ timeout: 10_000 }); - await expect( - page.getByRole("paragraph").filter({ hasText: "RPM: 456" }) - ).toBeVisible({ timeout: 10_000 }); + await expect(page.getByRole("paragraph").filter({ hasText: "TPM: 123" })).toBeVisible({ timeout: 10_000 }); + await expect(page.getByRole("paragraph").filter({ hasText: "RPM: 456" })).toBeVisible({ timeout: 10_000 }); }); test("Delete key", async ({ page }) => { diff --git a/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/license.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/license.spec.ts index 579b3cede7c..37a0e324f27 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/license.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/license.spec.ts @@ -14,10 +14,7 @@ import { ADMIN_STORAGE_PATH } from "../../constants"; */ test.describe("Premium license wiring", () => { test("admin session JWT carries premium_user=true when LITELLM_LICENSE is set", () => { - test.skip( - !process.env.LITELLM_LICENSE, - "LITELLM_LICENSE not set in test env — proxy is running unlicensed", - ); + test.skip(!process.env.LITELLM_LICENSE, "LITELLM_LICENSE not set in test env — proxy is running unlicensed"); const storage = JSON.parse(fs.readFileSync(ADMIN_STORAGE_PATH, "utf-8")); const tokenCookie = storage.cookies?.find((c: { name: string }) => c.name === "token"); @@ -28,9 +25,7 @@ test.describe("Premium license wiring", () => { const jwtParts = tokenCookie.value.split("."); expect(jwtParts.length, "token cookie is not a 3-part JWT").toBe(3); const [, payloadB64] = jwtParts; - const payload = JSON.parse( - Buffer.from(payloadB64, "base64url").toString("utf-8"), - ); + const payload = JSON.parse(Buffer.from(payloadB64, "base64url").toString("utf-8")); expect(payload.premium_user).toBe(true); }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/teams.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/teams.spec.ts index 4774b50dbc5..b30bb8aca7b 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/teams.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/proxy-admin/teams.spec.ts @@ -19,7 +19,10 @@ test.describe("Proxy Admin - Teams", () => { const uniqueAlias = `e2e-created-team-${Date.now()}`; // Click the Create Team button — accessible name includes "Create Team" - await page.getByRole("button", { name: /Create Team/i }).first().click(); + await page + .getByRole("button", { name: /Create Team/i }) + .first() + .click(); // Wait for the Create Team modal const dialog = page.locator(".ant-modal:visible"); @@ -157,8 +160,9 @@ test.describe("Proxy Admin - Teams", () => { await page.getByRole("button", { name: "Save Changes" }).click(); - await expect(page.getByText(/Team settings updated|updated successfully/i).first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText(/Team settings updated|updated successfully/i).first()).toBeVisible({ + timeout: 10_000, + }); } finally { // Leave the team in its seeded state for any subsequent test or rerun. await restore(); diff --git a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts index 8dd5571f7af..98b86ec9b11 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts @@ -86,17 +86,16 @@ test.describe("Router Settings - Fallbacks", () => { await modal.getByRole("button", { name: /Save All Configurations/i }).click(); // Success toast - await expect(page.getByText(/fallback configuration\(s\) added successfully/i).first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText(/fallback configuration\(s\) added successfully/i).first()).toBeVisible({ + timeout: 10_000, + }); // Modal closes, and a single row contains BOTH the primary and the fallback // model — stronger than asserting each name appears somewhere in tbody, // which could be satisfied by leftover rows from prior runs. await expect(modal).not.toBeVisible({ timeout: 5_000 }); - const newRow = page.locator("table tbody tr") - .filter({ hasText: PRIMARY }) - .filter({ hasText: FALLBACK }); + const newRow = page.locator("table tbody tr").filter({ hasText: PRIMARY }).filter({ hasText: FALLBACK }); await expect(newRow).toHaveCount(1, { timeout: 10_000 }); }); }); diff --git a/ui/litellm-dashboard/e2e_tests/tests/team-admin/teamAdmin.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/team-admin/teamAdmin.spec.ts index 1612e6929bd..18b43ec89b2 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/team-admin/teamAdmin.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/team-admin/teamAdmin.spec.ts @@ -28,13 +28,11 @@ test.describe("Team Admin", () => { await clickTeamId(page, E2E_TEAM_CRUD_ID); await page.getByRole("tab", { name: "Virtual Keys" }).click(); - await expect(page.getByText(E2E_INTERNAL_USER_KEY_ALIAS).first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText(E2E_INTERNAL_USER_KEY_ALIAS).first()).toBeVisible({ timeout: 10_000 }); // And from the global Virtual Keys page, the same key should be visible. await navigateToPage(page, Page.ApiKeys); - await expect(page.getByText(E2E_INTERNAL_USER_KEY_ALIAS).first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText(E2E_INTERNAL_USER_KEY_ALIAS).first()).toBeVisible({ timeout: 10_000 }); }); test("Team admin can add a member to their team", async ({ page }) => { @@ -60,8 +58,7 @@ test.describe("Team Admin", () => { await modal.getByRole("button", { name: /Add Member/i }).click(); - await expect(page.getByText("Team member added successfully").first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText("Team member added successfully").first()).toBeVisible({ timeout: 10_000 }); }); test("Team admin can remove a member from their team", async ({ page }) => { @@ -82,8 +79,7 @@ test.describe("Team Admin", () => { await expect(modal).toBeVisible({ timeout: 5_000 }); await modal.getByRole("button", { name: /^Delete$/ }).click(); - await expect(page.getByText("Team member removed successfully").first()) - .toBeVisible({ timeout: 10_000 }); + await expect(page.getByText("Team member removed successfully").first()).toBeVisible({ timeout: 10_000 }); }); test("Team admin can create a team key with All Team Models", async ({ page }) => { diff --git a/ui/litellm-dashboard/knip.json b/ui/litellm-dashboard/knip.json index e93d1997d62..9971ed779ee 100644 --- a/ui/litellm-dashboard/knip.json +++ b/ui/litellm-dashboard/knip.json @@ -1,18 +1,9 @@ { "$schema": "https://unpkg.com/knip@5/schema.json", "entry": ["scripts/**/*.ts"], - "project": [ - "src/**/*.{ts,tsx}", - "tests/**/*.{ts,tsx}", - "scripts/**/*.ts", - "e2e_tests/**/*.ts" - ], + "project": ["src/**/*.{ts,tsx}", "tests/**/*.{ts,tsx}", "scripts/**/*.ts", "e2e_tests/**/*.ts"], "playwright": { "config": "e2e_tests/playwright.config.ts", - "entry": [ - "e2e_tests/**/*.spec.ts", - "e2e_tests/**/*.setup.ts", - "e2e_tests/globalSetup.ts" - ] + "entry": ["e2e_tests/**/*.spec.ts", "e2e_tests/**/*.setup.ts", "e2e_tests/globalSetup.ts"] } } diff --git a/ui/litellm-dashboard/src/app/(dashboard)/README.md b/ui/litellm-dashboard/src/app/(dashboard)/README.md index c913431fc5b..920ea5b4258 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/README.md +++ b/ui/litellm-dashboard/src/app/(dashboard)/README.md @@ -2,7 +2,7 @@ The LiteLLM UI is currently being refactored/rewritten to reduce development friction. Please read this document to understand what's expected for new contributions. -The project follows strict NextJS file structure. All pages on the site (determined by the sidebar) are contained in their own folder, and routing is automatically handled by NextJS based on the file structure. +The project follows strict NextJS file structure. All pages on the site (determined by the sidebar) are contained in their own folder, and routing is automatically handled by NextJS based on the file structure. For example, NextJS will automatically render the admin settings page when the user visits `/settings/admin-settings` @@ -16,7 +16,9 @@ For example, NextJS will automatically render the admin settings page when the u You can use parenthesis around directory names to hide them from the user route, for example `(dashboard)`, while still getting the benefits of `layout` and file structure. ### File Structure + Every page must follow the following file structure pattern. + ``` ├── teams │   ├── TeamsView.tsx @@ -34,11 +36,11 @@ Every page must follow the following file structure pattern. │   └── page.tsx ``` -### Component Files +### Component Files All component files should ideally be as dumb as possible. Their only job should be to take the data they need from hooks or props and render them to the UI. If a component file becomes too large (over `300` lines or so), **please break it down** into smaller components. -A component should only be placed where it will be used. For example, if a component will only be used by the `teams` page, it should belong in the `teams/components` folder. +A component should only be placed where it will be used. For example, if a component will only be used by the `teams` page, it should belong in the `teams/components` folder. **Common components should be moved to the lowest common ancestor components folder.** diff --git a/ui/litellm-dashboard/src/app/(dashboard)/components/Sidebar2.tsx b/ui/litellm-dashboard/src/app/(dashboard)/components/Sidebar2.tsx index 27a6e6c13be..90f498912a8 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/components/Sidebar2.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/components/Sidebar2.tsx @@ -464,7 +464,6 @@ const Sidebar2: React.FC = ({ accessToken, userRole, defaultSelect /> {isAdminRole(userRole) && !collapsed && } - ); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/components/SidebarProvider.tsx b/ui/litellm-dashboard/src/app/(dashboard)/components/SidebarProvider.tsx index 49e6569f1a7..1e091314ecd 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/components/SidebarProvider.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/components/SidebarProvider.tsx @@ -31,13 +31,15 @@ const SidebarProvider = ({ setPage, defaultSelectedKey, sidebarCollapsed }: Side console.log("[SidebarProvider] Fetching UI settings from /get/ui_settings"); const settings = await getUISettings(accessToken); console.log("[SidebarProvider] UI settings response:", settings); - + // API returns 'values' not 'settings' if (settings?.values?.enabled_ui_pages_internal_users !== undefined) { console.log("[SidebarProvider] Setting enabled pages:", settings.values.enabled_ui_pages_internal_users); setEnabledPagesInternalUsers(settings.values.enabled_ui_pages_internal_users); } else { - console.log("[SidebarProvider] No enabled_ui_pages_internal_users in response (all pages visible by default)"); + console.log( + "[SidebarProvider] No enabled_ui_pages_internal_users in response (all pages visible by default)", + ); } if (settings?.values?.enable_projects_ui !== undefined) { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroupDetails.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroupDetails.ts index c0379b25321..3dcf73388a5 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroupDetails.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroupDetails.ts @@ -1,20 +1,12 @@ import { useQuery, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import { all_admin_roles } from "@/utils/roles"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { AccessGroupResponse, accessGroupKeys } from "./useAccessGroups"; // ── Fetch function ─────────────────────────────────────────────────────────── -const fetchAccessGroupDetails = async ( - accessToken: string, - accessGroupId: string, -): Promise => { +const fetchAccessGroupDetails = async (accessToken: string, accessGroupId: string): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/v1/access_group/${encodeURIComponent(accessGroupId)}`; @@ -45,17 +37,13 @@ export const useAccessGroupDetails = (accessGroupId?: string) => { return useQuery({ queryKey: accessGroupKeys.detail(accessGroupId!), queryFn: async () => fetchAccessGroupDetails(accessToken!, accessGroupId!), - enabled: - Boolean(accessToken && accessGroupId) && - all_admin_roles.includes(userRole || ""), + enabled: Boolean(accessToken && accessGroupId) && all_admin_roles.includes(userRole || ""), // Seed from the list cache when available initialData: () => { if (!accessGroupId) return undefined; - const groups = queryClient.getQueryData( - accessGroupKeys.list({}), - ); + const groups = queryClient.getQueryData(accessGroupKeys.list({})); return groups?.find((g) => g.access_group_id === accessGroupId); }, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroups.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroups.ts index 215b555fcf9..9f306c21459 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroups.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroups.ts @@ -1,11 +1,6 @@ import { useQuery } from "@tanstack/react-query"; import { createQueryKeys } from "../common/queryKeysFactory"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import { all_admin_roles } from "@/utils/roles"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; @@ -32,9 +27,7 @@ export const accessGroupKeys = createQueryKeys("accessGroups"); // ── Fetch function ─────────────────────────────────────────────────────────── -const fetchAccessGroups = async ( - accessToken: string, -): Promise => { +const fetchAccessGroups = async (accessToken: string): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/v1/access_group`; @@ -64,7 +57,6 @@ export const useAccessGroups = () => { return useQuery({ queryKey: accessGroupKeys.list({}), queryFn: async () => fetchAccessGroups(accessToken!), - enabled: - Boolean(accessToken) && all_admin_roles.includes(userRole || ""), + enabled: Boolean(accessToken) && all_admin_roles.includes(userRole || ""), }); }; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useCreateAccessGroup.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useCreateAccessGroup.ts index 7ea5a813462..5efa2da6557 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useCreateAccessGroup.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useCreateAccessGroup.ts @@ -1,10 +1,5 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { AccessGroupResponse, accessGroupKeys } from "./useAccessGroups"; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useDeleteAccessGroup.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useDeleteAccessGroup.ts index 5df5960ce0a..01e317f6613 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useDeleteAccessGroup.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useDeleteAccessGroup.ts @@ -1,19 +1,11 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { accessGroupKeys } from "./useAccessGroups"; // ── Fetch function ─────────────────────────────────────────────────────────── -const deleteAccessGroup = async ( - accessToken: string, - accessGroupId: string, -): Promise => { +const deleteAccessGroup = async (accessToken: string, accessGroupId: string): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/v1/access_group/${encodeURIComponent(accessGroupId)}`; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useEditAccessGroup.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useEditAccessGroup.ts index 5dc2252f640..7dd85ae93dc 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useEditAccessGroup.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useEditAccessGroup.ts @@ -1,10 +1,5 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { AccessGroupResponse, accessGroupKeys } from "./useAccessGroups"; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroCreate.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroCreate.test.ts index 8334aea56e7..f370e4d6d6e 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroCreate.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroCreate.test.ts @@ -4,27 +4,22 @@ import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; import React, { ReactNode } from "react"; import { useCloudZeroCreate } from "./useCloudZeroCreate"; -const { - mockProxyBaseUrl, - mockAccessToken, - mockHeaderName, - mockGetProxyBaseUrl, - mockGetGlobalLitellmHeaderName, -} = vi.hoisted(() => { - const mockProxyBaseUrl = "https://proxy.example.com"; - const mockAccessToken = "test-access-token"; - const mockHeaderName = "X-LiteLLM-API-Key"; - const mockGetProxyBaseUrl = vi.fn(() => mockProxyBaseUrl); - const mockGetGlobalLitellmHeaderName = vi.fn(() => mockHeaderName); +const { mockProxyBaseUrl, mockAccessToken, mockHeaderName, mockGetProxyBaseUrl, mockGetGlobalLitellmHeaderName } = + vi.hoisted(() => { + const mockProxyBaseUrl = "https://proxy.example.com"; + const mockAccessToken = "test-access-token"; + const mockHeaderName = "X-LiteLLM-API-Key"; + const mockGetProxyBaseUrl = vi.fn(() => mockProxyBaseUrl); + const mockGetGlobalLitellmHeaderName = vi.fn(() => mockHeaderName); - return { - mockProxyBaseUrl, - mockAccessToken, - mockHeaderName, - mockGetProxyBaseUrl, - mockGetGlobalLitellmHeaderName, - }; -}); + return { + mockProxyBaseUrl, + mockAccessToken, + mockHeaderName, + mockGetProxyBaseUrl, + mockGetGlobalLitellmHeaderName, + }; + }); vi.mock("@/components/networking", () => ({ getProxyBaseUrl: mockGetProxyBaseUrl, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroDryRun.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroDryRun.test.ts index 74d657b3e85..b5b903ea620 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroDryRun.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroDryRun.test.ts @@ -4,27 +4,22 @@ import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; import React, { ReactNode } from "react"; import { useCloudZeroDryRun } from "./useCloudZeroDryRun"; -const { - mockProxyBaseUrl, - mockAccessToken, - mockHeaderName, - mockGetProxyBaseUrl, - mockGetGlobalLitellmHeaderName, -} = vi.hoisted(() => { - const mockProxyBaseUrl = "https://proxy.example.com"; - const mockAccessToken = "test-access-token"; - const mockHeaderName = "X-LiteLLM-API-Key"; - const mockGetProxyBaseUrl = vi.fn(() => mockProxyBaseUrl); - const mockGetGlobalLitellmHeaderName = vi.fn(() => mockHeaderName); +const { mockProxyBaseUrl, mockAccessToken, mockHeaderName, mockGetProxyBaseUrl, mockGetGlobalLitellmHeaderName } = + vi.hoisted(() => { + const mockProxyBaseUrl = "https://proxy.example.com"; + const mockAccessToken = "test-access-token"; + const mockHeaderName = "X-LiteLLM-API-Key"; + const mockGetProxyBaseUrl = vi.fn(() => mockProxyBaseUrl); + const mockGetGlobalLitellmHeaderName = vi.fn(() => mockHeaderName); - return { - mockProxyBaseUrl, - mockAccessToken, - mockHeaderName, - mockGetProxyBaseUrl, - mockGetGlobalLitellmHeaderName, - }; -}); + return { + mockProxyBaseUrl, + mockAccessToken, + mockHeaderName, + mockGetProxyBaseUrl, + mockGetGlobalLitellmHeaderName, + }; + }); vi.mock("@/components/networking", () => ({ getProxyBaseUrl: mockGetProxyBaseUrl, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroExport.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroExport.test.ts index 72a1cfd24aa..3c44d75dd06 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroExport.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/cloudzero/useCloudZeroExport.test.ts @@ -4,27 +4,22 @@ import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; import React, { ReactNode } from "react"; import { useCloudZeroExport } from "./useCloudZeroExport"; -const { - mockProxyBaseUrl, - mockAccessToken, - mockHeaderName, - mockGetProxyBaseUrl, - mockGetGlobalLitellmHeaderName, -} = vi.hoisted(() => { - const mockProxyBaseUrl = "https://proxy.example.com"; - const mockAccessToken = "test-access-token"; - const mockHeaderName = "X-LiteLLM-API-Key"; - const mockGetProxyBaseUrl = vi.fn(() => mockProxyBaseUrl); - const mockGetGlobalLitellmHeaderName = vi.fn(() => mockHeaderName); +const { mockProxyBaseUrl, mockAccessToken, mockHeaderName, mockGetProxyBaseUrl, mockGetGlobalLitellmHeaderName } = + vi.hoisted(() => { + const mockProxyBaseUrl = "https://proxy.example.com"; + const mockAccessToken = "test-access-token"; + const mockHeaderName = "X-LiteLLM-API-Key"; + const mockGetProxyBaseUrl = vi.fn(() => mockProxyBaseUrl); + const mockGetGlobalLitellmHeaderName = vi.fn(() => mockHeaderName); - return { - mockProxyBaseUrl, - mockAccessToken, - mockHeaderName, - mockGetProxyBaseUrl, - mockGetGlobalLitellmHeaderName, - }; -}); + return { + mockProxyBaseUrl, + mockAccessToken, + mockHeaderName, + mockGetProxyBaseUrl, + mockGetGlobalLitellmHeaderName, + }; + }); vi.mock("@/components/networking", () => ({ getProxyBaseUrl: mockGetProxyBaseUrl, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/common/queryKeysFactory.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/common/queryKeysFactory.test.ts index 39afd044097..2c1fd29f61c 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/common/queryKeysFactory.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/common/queryKeysFactory.test.ts @@ -13,11 +13,7 @@ describe("createQueryKeys", () => { }); it("should generate a list key with params", () => { - expect(keys.list({ page: 1, limit: 10 })).toEqual([ - "books", - "list", - { params: { page: 1, limit: 10 } }, - ]); + expect(keys.list({ page: 1, limit: 10 })).toEqual(["books", "list", { params: { page: 1, limit: 10 } }]); }); it("should generate a list key with undefined params when none provided", () => { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/configOverrides/hashicorpVaultApi.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/configOverrides/hashicorpVaultApi.ts index edf18860ec1..2af0f118500 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/configOverrides/hashicorpVaultApi.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/configOverrides/hashicorpVaultApi.ts @@ -2,9 +2,7 @@ import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage } from export const getHashicorpVaultConfig = async (accessToken: string) => { const proxyBaseUrl = getProxyBaseUrl(); - const url = proxyBaseUrl - ? `${proxyBaseUrl}/config_overrides/hashicorp_vault` - : `/config_overrides/hashicorp_vault`; + const url = proxyBaseUrl ? `${proxyBaseUrl}/config_overrides/hashicorp_vault` : `/config_overrides/hashicorp_vault`; const response = await fetch(url, { method: "GET", headers: { @@ -20,14 +18,9 @@ export const getHashicorpVaultConfig = async (accessToken: string) => { return data; }; -export const updateHashicorpVaultConfig = async ( - accessToken: string, - config: Record, -) => { +export const updateHashicorpVaultConfig = async (accessToken: string, config: Record) => { const proxyBaseUrl = getProxyBaseUrl(); - const url = proxyBaseUrl - ? `${proxyBaseUrl}/config_overrides/hashicorp_vault` - : `/config_overrides/hashicorp_vault`; + const url = proxyBaseUrl ? `${proxyBaseUrl}/config_overrides/hashicorp_vault` : `/config_overrides/hashicorp_vault`; const response = await fetch(url, { method: "POST", headers: { @@ -47,9 +40,7 @@ export const updateHashicorpVaultConfig = async ( export const deleteHashicorpVaultConfig = async (accessToken: string) => { const proxyBaseUrl = getProxyBaseUrl(); - const url = proxyBaseUrl - ? `${proxyBaseUrl}/config_overrides/hashicorp_vault` - : `/config_overrides/hashicorp_vault`; + const url = proxyBaseUrl ? `${proxyBaseUrl}/config_overrides/hashicorp_vault` : `/config_overrides/hashicorp_vault`; const response = await fetch(url, { method: "DELETE", headers: { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useGuardrails.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useGuardrails.test.ts index b1896eda0e6..8db520eecd0 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useGuardrails.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useGuardrails.test.ts @@ -289,11 +289,7 @@ describe("useGuardrails", () => { expect(result.current.isSuccess).toBe(true); }); - expect(result.current.data?.globalGuardrailNames).toEqual( - new Set(["global-guard-a", "global-guard-b"]), - ); - expect(result.current.data?.optionalGuardrailNames).toEqual( - new Set(["optional-guard-a", "optional-guard-b"]), - ); + expect(result.current.data?.globalGuardrailNames).toEqual(new Set(["global-guard-a", "global-guard-b"])); + expect(result.current.data?.optionalGuardrailNames).toEqual(new Set(["optional-guard-a", "optional-guard-b"])); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useRegisterGuardrail.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useRegisterGuardrail.ts index 3135e8326fc..edbcbdfe170 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useRegisterGuardrail.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/guardrails/useRegisterGuardrail.ts @@ -1,10 +1,5 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { createQueryKeys } from "../common/queryKeysFactory"; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/healthReadiness/useHealthReadinessDetails.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/healthReadiness/useHealthReadinessDetails.ts index 5838dbd0ee6..3b79e5c7643 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/healthReadiness/useHealthReadinessDetails.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/healthReadiness/useHealthReadinessDetails.ts @@ -1,8 +1,5 @@ import { useQuery, UseQueryResult } from "@tanstack/react-query"; -import { - getGlobalLitellmHeaderName, - getProxyBaseUrl, -} from "@/components/networking"; +import { getGlobalLitellmHeaderName, getProxyBaseUrl } from "@/components/networking"; import { createQueryKeys } from "../common/queryKeysFactory"; const healthReadinessDetailsKeys = createQueryKeys("healthReadinessDetails"); @@ -18,9 +15,7 @@ export interface HealthReadinessDetailsResponse { is_detailed_debug?: boolean; } -const fetchHealthReadinessDetails = async ( - accessToken: string, -): Promise => { +const fetchHealthReadinessDetails = async (accessToken: string): Promise => { const baseUrl = getProxyBaseUrl(); const response = await fetch(`${baseUrl}/health/readiness/details`, { method: "GET", @@ -30,9 +25,7 @@ const fetchHealthReadinessDetails = async ( }, }); if (!response.ok) { - throw new Error( - `Failed to fetch health readiness details: ${response.statusText}`, - ); + throw new Error(`Failed to fetch health readiness details: ${response.statusText}`); } return response.json(); }; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.test.ts index 1e1190b12c8..e0140c6a63a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.test.ts @@ -128,9 +128,7 @@ describe("useInfiniteKeyAliases", () => { }); it("should fetch the next page when fetchNextPage is called", async () => { - mockKeyAliasesCall - .mockResolvedValueOnce(mockPage1) - .mockResolvedValueOnce(mockPage2); + mockKeyAliasesCall.mockResolvedValueOnce(mockPage1).mockResolvedValueOnce(mockPage2); const wrapper = createWrapper(); const { result } = renderHook(() => useInfiniteKeyAliases(2), { wrapper }); @@ -151,10 +149,10 @@ describe("useInfiniteKeyAliases", () => { it("should include search in query key so search changes refetch from page 1", async () => { const wrapper = createWrapper(); - const { result, rerender } = renderHook( - ({ search }: { search?: string }) => useInfiniteKeyAliases(50, search), - { wrapper, initialProps: { search: undefined } }, - ); + const { result, rerender } = renderHook(({ search }: { search?: string }) => useInfiniteKeyAliases(50, search), { + wrapper, + initialProps: { search: undefined }, + }); await waitFor(() => { expect(result.current.isSuccess).toBe(true); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.ts index 03e96fe73c4..2b4583ad6b3 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeyAliases.ts @@ -5,11 +5,7 @@ import useAuthorized from "../useAuthorized"; const infiniteKeyAliasKeys = createQueryKeys("infiniteKeyAliases"); -export const useInfiniteKeyAliases = ( - size: number = 50, - search?: string, - team_id?: string, -) => { +export const useInfiniteKeyAliases = (size: number = 50, search?: string, team_id?: string) => { const { accessToken } = useAuthorized(); return useInfiniteQuery({ queryKey: infiniteKeyAliasKeys.list({ @@ -20,13 +16,7 @@ export const useInfiniteKeyAliases = ( }, }), queryFn: async ({ pageParam }) => { - return await keyAliasesCall( - accessToken!, - pageParam as number, - size, - search, - team_id, - ); + return await keyAliasesCall(accessToken!, pageParam as number, size, search, team_id); }, initialPageParam: 1, getNextPageParam: (lastPage) => { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.test.ts index 80cb69495da..1e700e572d0 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.test.ts @@ -410,10 +410,7 @@ describe("useKeys", () => { }), }); - const { result } = renderHook( - () => useKeys(1, 10, { projectID: "project-1" }), - { wrapper }, - ); + const { result } = renderHook(() => useKeys(1, 10, { projectID: "project-1" }), { wrapper }); await waitFor(() => { expect(result.current.isLoading).toBe(false); @@ -436,10 +433,7 @@ describe("useKeys", () => { }), }); - const { result } = renderHook( - () => useKeys(1, 10, { projectID: "project-1", teamID: "team-1" }), - { wrapper }, - ); + const { result } = renderHook(() => useKeys(1, 10, { projectID: "project-1", teamID: "team-1" }), { wrapper }); await waitFor(() => { expect(result.current.isLoading).toBe(false); @@ -456,10 +450,7 @@ describe("useKeys", () => { json: async () => mockKeysResponse, }); - const { result } = renderHook( - () => useKeys(1, 10, { projectID: null }), - { wrapper }, - ); + const { result } = renderHook(() => useKeys(1, 10, { projectID: null }), { wrapper }); await waitFor(() => { expect(result.current.isLoading).toBe(false); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts index fbe5eccb75a..4a04c541d1a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts @@ -1,11 +1,6 @@ import { keepPreviousData, useQuery, UseQueryResult } from "@tanstack/react-query"; import { createQueryKeys } from "../common/queryKeysFactory"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import { KeyResponse } from "@/components/key_team_helpers/key_list"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; @@ -43,18 +38,13 @@ export interface KeyListCallOptions { status?: string | null; } -const keyListCall = async ( - accessToken: string, - page: number, - pageSize: number, - options: KeyListCallOptions = {}, -) => { +const keyListCall = async (accessToken: string, page: number, pageSize: number, options: KeyListCallOptions = {}) => { /** * Get all available keys on proxy */ try { const baseUrl = getProxyBaseUrl(); - + const params = new URLSearchParams( Object.entries({ team_id: options.teamID, @@ -134,4 +124,4 @@ export const useDeletedKeys = ( staleTime: 30000, // 30 seconds placeholderData: keepPreviousData, }); -}; \ No newline at end of file +}; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useResetKeySpend.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useResetKeySpend.ts index a845fc5881a..0265b4dc402 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useResetKeySpend.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useResetKeySpend.ts @@ -1,10 +1,5 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { keyKeys } from "./useKeys"; @@ -20,10 +15,7 @@ export interface ResetKeySpendResponse { // ── Fetch function ──────────────────────────────────────────────────────────── -export const resetKeySpend = async ( - accessToken: string, - keyToken: string, -): Promise => { +export const resetKeySpend = async (accessToken: string, keyToken: string): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl ? `${baseUrl}/key/${keyToken}/reset_spend` : `/key/${keyToken}/reset_spend`}`; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/logDetails/useLogDetails.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/logDetails/useLogDetails.ts index 6c0f95d5995..5e4757bdb2f 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/logDetails/useLogDetails.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/logDetails/useLogDetails.ts @@ -10,11 +10,7 @@ import { uiSpendLogDetailsCall } from "@/components/networking"; * @param startTime - The formatted start time for the query * @param enabled - Whether the query should be enabled (e.g., drawer is open) */ -export const useLogDetails = ( - requestId: string | undefined, - startTime: string | undefined, - enabled: boolean, -) => { +export const useLogDetails = (requestId: string | undefined, startTime: string | undefined, enabled: boolean) => { const { accessToken } = useAuthorized(); return useQuery({ diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useMCPSemanticFilterSettings.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useMCPSemanticFilterSettings.ts index e91f5aa670b..ad9880d8cac 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useMCPSemanticFilterSettings.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useMCPSemanticFilterSettings.ts @@ -3,9 +3,7 @@ import { useQuery } from "@tanstack/react-query"; import { createQueryKeys } from "../common/queryKeysFactory"; import useAuthorized from "../useAuthorized"; -const mcpSemanticFilterSettingsKeys = createQueryKeys( - "mcpSemanticFilterSettings" -); +const mcpSemanticFilterSettingsKeys = createQueryKeys("mcpSemanticFilterSettings"); export const useMCPSemanticFilterSettings = () => { const { accessToken } = useAuthorized(); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useUpdateMCPSemanticFilterSettings.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useUpdateMCPSemanticFilterSettings.ts index 2062b4f4c29..bc7406599b1 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useUpdateMCPSemanticFilterSettings.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpSemanticFilterSettings/useUpdateMCPSemanticFilterSettings.ts @@ -2,9 +2,7 @@ import { updateMCPSemanticFilterSettings } from "@/components/networking"; import { useMutation, useQueryClient } from "@tanstack/react-query"; import { createQueryKeys } from "../common/queryKeysFactory"; -const mcpSemanticFilterSettingsKeys = createQueryKeys( - "mcpSemanticFilterSettings" -); +const mcpSemanticFilterSettingsKeys = createQueryKeys("mcpSemanticFilterSettings"); export const useUpdateMCPSemanticFilterSettings = (accessToken: string) => { const queryClient = useQueryClient(); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPAccessGroups.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPAccessGroups.test.ts index 9c555ff1234..65dfd6bf4f2 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPAccessGroups.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPAccessGroups.test.ts @@ -121,4 +121,4 @@ describe("useMCPAccessGroups", () => { expect(result.current.data).toEqual([]); }); -}); \ No newline at end of file +}); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerHealth.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerHealth.ts index 681bf4161ad..9ad8a6f43fa 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerHealth.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServerHealth.ts @@ -24,32 +24,32 @@ export const useMCPServerHealth = () => { refetchInterval: 30000, }); - const recheckServerHealth = useCallback(async (serverId: string) => { - if (!accessToken) return; + const recheckServerHealth = useCallback( + async (serverId: string) => { + if (!accessToken) return; - setRecheckingServerIds((prev) => new Set(prev).add(serverId)); + setRecheckingServerIds((prev) => new Set(prev).add(serverId)); - try { - const result: MCPServerHealth[] = await fetchMCPServerHealth(accessToken, [serverId]); + try { + const result: MCPServerHealth[] = await fetchMCPServerHealth(accessToken, [serverId]); - queryClient.setQueriesData( - { queryKey: mcpServerHealthKeys.lists() }, - (oldData) => { + queryClient.setQueriesData({ queryKey: mcpServerHealthKeys.lists() }, (oldData) => { if (!oldData) return result; return oldData.map((h) => { const updated = result.find((r) => r.server_id === h.server_id); return updated ?? h; }); - }, - ); - } finally { - setRecheckingServerIds((prev) => { - const next = new Set(prev); - next.delete(serverId); - return next; - }); - } - }, [accessToken, queryClient]); + }); + } finally { + setRecheckingServerIds((prev) => { + const next = new Set(prev); + next.delete(serverId); + return next; + }); + } + }, + [accessToken, queryClient], + ); return { ...query, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServers.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServers.test.ts index ee03a0ab7c3..52b58f9e318 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServers.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpServers/useMCPServers.test.ts @@ -131,4 +131,4 @@ describe("useMCPServers", () => { expect(result.current.data).toEqual([]); }); -}); \ No newline at end of file +}); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/models/useModels.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/models/useModels.ts index fe1afdcc39f..c997f679b2e 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/models/useModels.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/models/useModels.ts @@ -28,7 +28,15 @@ const allProxyModelsKeys = createQueryKeys("allProxyModels"); const selectedTeamModelsKeys = createQueryKeys("selectedTeamModels"); const infiniteModelKeys = createQueryKeys("infiniteModels"); -export const useModelsInfo = (page: number = 1, size: number = 50, search?: string, modelId?: string, teamId?: string, sortBy?: string, sortOrder?: string) => { +export const useModelsInfo = ( + page: number = 1, + size: number = 50, + search?: string, + modelId?: string, + teamId?: string, + sortBy?: string, + sortOrder?: string, +) => { const { accessToken, userId, userRole } = useAuthorized(); return useQuery({ queryKey: modelKeys.list({ @@ -44,7 +52,8 @@ export const useModelsInfo = (page: number = 1, size: number = 50, search?: stri ...(sortOrder && { sortOrder }), }, }), - queryFn: async () => await modelInfoCall(accessToken!, userId!, userRole!, page, size, search, modelId, teamId, sortBy, sortOrder), + queryFn: async () => + await modelInfoCall(accessToken!, userId!, userRole!, page, size, search, modelId, teamId, sortBy, sortOrder), enabled: Boolean(accessToken && userId && userRole), }); }; @@ -76,10 +85,7 @@ export const useSelectedTeamModels = (teamID: string | null) => { }); }; -export const useInfiniteModelInfo = ( - size: number = 50, - search?: string, -) => { +export const useInfiniteModelInfo = (size: number = 50, search?: string) => { const { accessToken, userId, userRole } = useAuthorized(); return useInfiniteQuery({ queryKey: infiniteModelKeys.list({ @@ -91,14 +97,7 @@ export const useInfiniteModelInfo = ( }, }), queryFn: async ({ pageParam }) => { - return await modelInfoCall( - accessToken!, - userId!, - userRole!, - pageParam as number, - size, - search, - ); + return await modelInfoCall(accessToken!, userId!, userRole!, pageParam as number, size, search); }, initialPageParam: 1, getNextPageParam: (lastPage) => { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.test.ts index 64d950d59ee..110a704725a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.test.ts @@ -103,9 +103,7 @@ describe("useCreateProject", () => { const { result } = renderHook(() => useCreateProject(), { wrapper: makeWrapper(queryClient), }); - await expect(result.current.mutateAsync({ team_id: "team-1" })).rejects.toThrow( - "Access token is required" - ); + await expect(result.current.mutateAsync({ team_id: "team-1" })).rejects.toThrow("Access token is required"); expect(global.fetch).not.toHaveBeenCalled(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.ts index e206c770b19..2e67e626936 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useCreateProject.ts @@ -1,10 +1,5 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { ProjectResponse, projectKeys } from "./useProjects"; @@ -25,10 +20,7 @@ export interface ProjectCreateParams { // ── Fetch function ─────────────────────────────────────────────────────────── -const createProject = async ( - accessToken: string, - params: ProjectCreateParams, -): Promise => { +const createProject = async (accessToken: string, params: ProjectCreateParams): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/project/new`; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.test.ts index 85a9f3e0b10..beaad13ce2a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.test.ts @@ -80,9 +80,7 @@ describe("useDeleteProject", () => { const { result } = renderHook(() => useDeleteProject(), { wrapper: makeWrapper(queryClient), }); - await expect(result.current.mutateAsync(["proj-1"])).rejects.toThrow( - "Access token is required" - ); + await expect(result.current.mutateAsync(["proj-1"])).rejects.toThrow("Access token is required"); expect(global.fetch).not.toHaveBeenCalled(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.ts index 5abf9e03be2..04f2c547eef 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useDeleteProject.ts @@ -1,19 +1,11 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { projectKeys } from "./useProjects"; // ── Fetch function ─────────────────────────────────────────────────────────── -const deleteProjects = async ( - accessToken: string, - projectIds: string[], -): Promise => { +const deleteProjects = async (accessToken: string, projectIds: string[]): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/project/delete`; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjectDetails.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjectDetails.ts index 1d35ac1bf70..037baa18692 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjectDetails.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjectDetails.ts @@ -1,20 +1,12 @@ import { useQuery, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import { all_admin_roles } from "@/utils/roles"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { ProjectResponse, projectKeys } from "./useProjects"; // ── Fetch function ─────────────────────────────────────────────────────────── -const fetchProjectDetails = async ( - accessToken: string, - projectId: string, -): Promise => { +const fetchProjectDetails = async (accessToken: string, projectId: string): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/project/info?project_id=${encodeURIComponent(projectId)}`; @@ -45,17 +37,13 @@ export const useProjectDetails = (projectId?: string) => { return useQuery({ queryKey: projectKeys.detail(projectId!), queryFn: async () => fetchProjectDetails(accessToken!, projectId!), - enabled: - Boolean(accessToken && projectId) && - all_admin_roles.includes(userRole || ""), + enabled: Boolean(accessToken && projectId) && all_admin_roles.includes(userRole || ""), // Seed from the list cache when available initialData: () => { if (!projectId) return undefined; - const projects = queryClient.getQueryData( - projectKeys.list({}), - ); + const projects = queryClient.getQueryData(projectKeys.list({})); return projects?.find((p) => p.project_id === projectId); }, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjects.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjects.ts index 79976f54626..7bdc8a4fe6d 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjects.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useProjects.ts @@ -1,11 +1,6 @@ import { useQuery } from "@tanstack/react-query"; import { createQueryKeys } from "../common/queryKeysFactory"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { all_admin_roles } from "@/utils/roles"; @@ -49,9 +44,7 @@ export const projectKeys = createQueryKeys("projects"); // ── Fetch function ─────────────────────────────────────────────────────────── -const fetchProjects = async ( - accessToken: string, -): Promise => { +const fetchProjects = async (accessToken: string): Promise => { const baseUrl = getProxyBaseUrl(); const url = `${baseUrl}/project/list`; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.test.ts index 31d1a5fb352..9e752ac098a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.test.ts @@ -108,9 +108,9 @@ describe("useUpdateProject", () => { const { result } = renderHook(() => useUpdateProject(), { wrapper: makeWrapper(queryClient), }); - await expect( - result.current.mutateAsync({ projectId: "proj-1", params: {} }) - ).rejects.toThrow("Access token is required"); + await expect(result.current.mutateAsync({ projectId: "proj-1", params: {} })).rejects.toThrow( + "Access token is required", + ); expect(global.fetch).not.toHaveBeenCalled(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.ts index 2042c8fc7cd..6d8c2d9d4f8 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/projects/useUpdateProject.ts @@ -1,10 +1,5 @@ import { useMutation, useQueryClient } from "@tanstack/react-query"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { ProjectResponse, projectKeys } from "./useProjects"; @@ -58,11 +53,7 @@ export const useUpdateProject = () => { const { accessToken } = useAuthorized(); const queryClient = useQueryClient(); - return useMutation< - ProjectResponse, - Error, - { projectId: string; params: ProjectUpdateParams } - >({ + return useMutation({ mutationFn: async ({ projectId, params }) => { if (!accessToken) { throw new Error("Access token is required"); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.test.ts index 6ff784ebd90..dd69e8c8791 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.test.ts @@ -54,7 +54,7 @@ describe("useStoreModelInDB", () => { field_value: true, config_type: "general_settings", }), - }) + }), ); }); @@ -80,15 +80,12 @@ describe("useStoreModelInDB", () => { field_value: false, config_type: "general_settings", }), - }) + }), ); }); it("should throw error when access token is missing", async () => { - vi.spyOn( - await import("../useAuthorized"), - "default" - ).mockReturnValue({ + vi.spyOn(await import("../useAuthorized"), "default").mockReturnValue({ accessToken: null, userRole: null, userId: null, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.ts index e6efbd724cd..27e375c265d 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeModelInDB/useStoreModelInDB.ts @@ -12,7 +12,7 @@ export interface StoreModelInDBResponse { const performStoreModelInDB = async ( accessToken: string, - params: StoreModelInDBParams + params: StoreModelInDBParams, ): Promise => { const proxyBaseUrl = getProxyBaseUrl(); const url = proxyBaseUrl ? `${proxyBaseUrl}/config/field/update` : `/config/field/update`; @@ -41,11 +41,7 @@ const performStoreModelInDB = async ( return data; }; -export const useStoreModelInDB = (): UseMutationResult< - StoreModelInDBResponse, - Error, - StoreModelInDBParams -> => { +export const useStoreModelInDB = (): UseMutationResult => { const { accessToken } = useAuthorized(); return useMutation({ diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeRequestInSpendLogs/useStoreRequestInSpendLogs.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeRequestInSpendLogs/useStoreRequestInSpendLogs.ts index 67b52997a01..88a37b30291 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeRequestInSpendLogs/useStoreRequestInSpendLogs.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/storeRequestInSpendLogs/useStoreRequestInSpendLogs.ts @@ -14,7 +14,7 @@ export interface StoreRequestInSpendLogsResponse { const performStoreRequestInSpendLogs = async ( accessToken: string, - params: StoreRequestInSpendLogsParams + params: StoreRequestInSpendLogsParams, ): Promise => { const proxyBaseUrl = getProxyBaseUrl(); const url = proxyBaseUrl ? `${proxyBaseUrl}/config/update` : `/config/update`; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts index 217ca426c25..20f034ada36 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts @@ -423,7 +423,7 @@ describe("useTeam", () => { // This tests the defensive error path in queryFn (lines 111-112) // The enabled check prevents queryFn from running, but we can test the defensive code // by manually constructing and calling the queryFn logic - + // Set up mocks mockUseAuthorized.mockReturnValue({ accessToken: null, // Missing accessToken @@ -438,24 +438,24 @@ describe("useTeam", () => { // Import useQueryClient to get access to query client const { useQueryClient } = await import("@tanstack/react-query"); - + // Manually test the queryFn logic by calling it directly // This simulates what would happen if enabled check was bypassed const testQueryFn = async () => { const { accessToken } = mockUseAuthorized(); const teamId = "team-1"; - + // This is the defensive check from lines 111-112 if (!accessToken || !teamId) { throw new Error("Missing auth or teamId"); } - + return teamInfoCall(accessToken, teamId); }; // Test that the error is thrown await expect(testQueryFn()).rejects.toThrow("Missing auth or teamId"); - + // Also test with missing teamId mockUseAuthorized.mockReturnValue({ accessToken: "test-access-token", @@ -471,11 +471,11 @@ describe("useTeam", () => { const testQueryFnMissingTeamId = async () => { const { accessToken } = mockUseAuthorized(); const teamId = undefined; // Missing teamId - + if (!accessToken || !teamId) { throw new Error("Missing auth or teamId"); } - + return teamInfoCall(accessToken, teamId); }; @@ -736,13 +736,10 @@ describe("useDeletedTeams", () => { json: async () => ({ teams: mockDeletedTeams }), }); - const { result, rerender } = renderHook( - ({ page }) => useDeletedTeams(page, 10, {}), - { - wrapper, - initialProps: { page: 1 }, - }, - ); + const { result, rerender } = renderHook(({ page }) => useDeletedTeams(page, 10, {}), { + wrapper, + initialProps: { page: 1 }, + }); await waitFor(() => { expect(result.current.isSuccess).toBe(true); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts index b25b6ce393a..c356434ba04 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts @@ -4,12 +4,7 @@ import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { fetchTeams } from "@/app/(dashboard)/networking"; import { createQueryKeys } from "@/app/(dashboard)/hooks/common/queryKeysFactory"; import { teamInfoCall } from "@/components/networking"; -import { - getProxyBaseUrl, - getGlobalLitellmHeaderName, - deriveErrorMessage, - handleError, -} from "@/components/networking"; +import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking"; export interface TeamsResponse { teams: Team[]; @@ -24,7 +19,6 @@ export interface DeletedTeam extends Team { deleted_by: string; } - export interface TeamListCallOptions { organizationID?: string | null; teamID?: string | null; @@ -47,7 +41,7 @@ export const teamListCall = async ( */ try { const baseUrl = getProxyBaseUrl(); - + const params = new URLSearchParams( Object.entries({ team_id: options.teamID, @@ -128,11 +122,7 @@ export const useTeam = (teamId?: string) => { const infiniteTeamKeys = createQueryKeys("infiniteTeams"); -export const useInfiniteTeams = ( - pageSize: number = 50, - search?: string, - organizationId?: string | null, -) => { +export const useInfiniteTeams = (pageSize: number = 50, search?: string, organizationId?: string | null) => { const { accessToken, userId, userRole } = useAuthorized(); const isAdmin = userRole === "Admin" || userRole === "Admin Viewer"; @@ -174,7 +164,7 @@ const deletedTeamListCall = async ( */ try { const baseUrl = getProxyBaseUrl(); - + const params = new URLSearchParams( Object.entries({ team_id: options.teamID, @@ -211,10 +201,10 @@ const deletedTeamListCall = async ( const data = await response.json(); console.log("/team/list?status=deleted API Response:", data); - + // Extract teams array from response if it's wrapped in a response object // Otherwise return the data directly if it's already an array - if (data && typeof data === 'object' && 'teams' in data) { + if (data && typeof data === "object" && "teams" in data) { return data.teams as DeletedTeam[]; } return data as DeletedTeam[]; @@ -239,4 +229,4 @@ export const useDeletedTeams = ( staleTime: 30000, // 30 seconds placeholderData: keepPreviousData, }); -}; \ No newline at end of file +}; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/useAuthorized.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/useAuthorized.test.ts index 5178aca0790..94f9d9173f0 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/useAuthorized.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/useAuthorized.test.ts @@ -8,7 +8,15 @@ import useAuthorized from "./useAuthorized"; // Unmock useAuthorized to test the actual implementation vi.unmock("@/app/(dashboard)/hooks/useAuthorized"); -const { replaceMock, clearTokenCookiesMock, getProxyBaseUrlMock, getUiConfigMock, decodeTokenMock, checkTokenValidityMock, buildLoginUrlWithReturnMock } = vi.hoisted(() => ({ +const { + replaceMock, + clearTokenCookiesMock, + getProxyBaseUrlMock, + getUiConfigMock, + decodeTokenMock, + checkTokenValidityMock, + buildLoginUrlWithReturnMock, +} = vi.hoisted(() => ({ replaceMock: vi.fn(), clearTokenCookiesMock: vi.fn(), getProxyBaseUrlMock: vi.fn(() => "http://proxy.example"), @@ -102,7 +110,7 @@ describe("useAuthorized", () => { admin_ui_disabled: false, sso_configured: false, }); - + const decodedPayload = { key: "api-key-123", user_id: "user-1", @@ -112,7 +120,7 @@ describe("useAuthorized", () => { disabled_non_admin_personal_key_creation: false, login_method: "username_password", }; - + decodeTokenMock.mockReturnValue(decodedPayload); checkTokenValidityMock.mockReturnValue(true); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.test.ts index b0a96eff0e7..537e2c5378a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.test.ts @@ -36,11 +36,7 @@ const DEFAULT_AUTH = { showSSOBanner: false, }; -const buildUserListResponse = ( - page: number, - totalPages: number, - userCount = 2, -): UserListResponse => ({ +const buildUserListResponse = (page: number, totalPages: number, userCount = 2): UserListResponse => ({ page, page_size: 50, total: totalPages * userCount, @@ -90,13 +86,7 @@ describe("useInfiniteUsers", () => { expect(result.current.data?.pages).toHaveLength(1); expect(result.current.data?.pages[0]).toEqual(mockResponse); - expect(userListCall).toHaveBeenCalledWith( - "test-access-token", - null, - 1, - 50, - null, - ); + expect(userListCall).toHaveBeenCalledWith("test-access-token", null, 1, 50, null); }); it("should use the default page size of 50", async () => { @@ -109,13 +99,7 @@ describe("useInfiniteUsers", () => { expect(result.current.isSuccess).toBe(true); }); - expect(userListCall).toHaveBeenCalledWith( - "test-access-token", - null, - 1, - 50, - null, - ); + expect(userListCall).toHaveBeenCalledWith("test-access-token", null, 1, 50, null); }); it("should use a custom page size when provided", async () => { @@ -131,13 +115,7 @@ describe("useInfiniteUsers", () => { expect(result.current.isSuccess).toBe(true); }); - expect(userListCall).toHaveBeenCalledWith( - "test-access-token", - null, - 1, - customPageSize, - null, - ); + expect(userListCall).toHaveBeenCalledWith("test-access-token", null, 1, customPageSize, null); }); it("should pass searchEmail to userListCall when provided", async () => { @@ -153,13 +131,7 @@ describe("useInfiniteUsers", () => { expect(result.current.isSuccess).toBe(true); }); - expect(userListCall).toHaveBeenCalledWith( - "test-access-token", - null, - 1, - 50, - searchEmail, - ); + expect(userListCall).toHaveBeenCalledWith("test-access-token", null, 1, 50, searchEmail); }); it("should pass null for searchEmail when not provided", async () => { @@ -174,13 +146,7 @@ describe("useInfiniteUsers", () => { expect(result.current.isSuccess).toBe(true); }); - expect(userListCall).toHaveBeenCalledWith( - "test-access-token", - null, - 1, - 50, - null, - ); + expect(userListCall).toHaveBeenCalledWith("test-access-token", null, 1, 50, null); }); it("should fetch the next page when more pages are available", async () => { @@ -209,13 +175,7 @@ describe("useInfiniteUsers", () => { expect(result.current.data?.pages[1]).toEqual(page2); expect(userListCall).toHaveBeenCalledTimes(2); - expect(userListCall).toHaveBeenLastCalledWith( - "test-access-token", - null, - 2, - 50, - null, - ); + expect(userListCall).toHaveBeenLastCalledWith("test-access-token", null, 2, 50, null); }); it("should not have a next page when on the last page", async () => { @@ -275,13 +235,7 @@ describe("useInfiniteUsers", () => { }); it("should execute query for each admin role", async () => { - const adminRoles = [ - "Admin", - "Admin Viewer", - "proxy_admin", - "proxy_admin_viewer", - "org_admin", - ]; + const adminRoles = ["Admin", "Admin Viewer", "proxy_admin", "proxy_admin_viewer", "org_admin"]; for (const role of adminRoles) { vi.clearAllMocks(); @@ -328,12 +282,6 @@ describe("useInfiniteUsers", () => { expect(result.current.isSuccess).toBe(true); }); - expect(userListCall).toHaveBeenCalledWith( - "test-access-token", - null, - 1, - 50, - null, - ); + expect(userListCall).toHaveBeenCalledWith("test-access-token", null, 1, 50, null); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.ts index cb30299f46f..9031de3cb1a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/users/useUsers.ts @@ -8,10 +8,7 @@ const infiniteUsersKeys = createQueryKeys("infiniteUsers"); const DEFAULT_PAGE_SIZE = 50; -export const useInfiniteUsers = ( - pageSize: number = DEFAULT_PAGE_SIZE, - searchEmail?: string, -) => { +export const useInfiniteUsers = (pageSize: number = DEFAULT_PAGE_SIZE, searchEmail?: string) => { const { accessToken, userRole } = useAuthorized(); return useInfiniteQuery({ queryKey: infiniteUsersKeys.list({ @@ -23,10 +20,10 @@ export const useInfiniteUsers = ( queryFn: async ({ pageParam }) => { return await userListCall( accessToken!, - null, // userIDs - pageParam as number, // page - pageSize, // page_size - searchEmail || null, // userEmail + null, // userIDs + pageParam as number, // page + pageSize, // page_size + searchEmail || null, // userEmail ); }, initialPageParam: 1, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx b/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx index 5bb55ee8d10..a611d619cc1 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx @@ -69,17 +69,13 @@ function LayoutContent({ children }: { children: React.ReactNode }) { sidebarCollapsed={sidebarCollapsed} onToggleSidebar={toggleSidebar} proxySettings={undefined} - setProxySettings={() => { }} + setProxySettings={() => {}} accessToken={accessToken} />
- +
{children}
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx index 944c56833e5..88f4382d7dd 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx @@ -518,7 +518,11 @@ const ModelsAndEndpointsView: React.FC = ({ premiumUser, te ); } return ( - +
{visibleTabs.map((t) => t.tab)}
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.test.tsx index 32ab83ea754..045bf0a5f44 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.test.tsx @@ -21,7 +21,7 @@ vi.mock("@/components/molecules/notifications_manager", () => ({ // Mock react-query const mockInvalidateQueries = vi.fn(); vi.mock("@tanstack/react-query", async (importOriginal) => { - const actual = await importOriginal() as any; + const actual = (await importOriginal()) as any; return { ...actual, useQueryClient: () => ({ @@ -178,24 +178,30 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-accessible", - model_info: { - id: "model-1", - access_via_team_ids: ["team-456"], - access_groups: [], + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-accessible", + model_info: { + id: "model-1", + access_via_team_ids: ["team-456"], + access_groups: [], + }, }, - }, - { - model_name: "gpt-3.5-turbo-blocked", - model_info: { - id: "model-2", - access_via_team_ids: ["team-789"], - access_groups: [], + { + model_name: "gpt-3.5-turbo-blocked", + model_info: { + id: "model-2", + access_via_team_ids: ["team-789"], + access_groups: [], + }, }, - }, - ], 2, 1, 1, 50); + ], + 2, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null }); @@ -239,24 +245,30 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-sales", - model_info: { - id: "model-sales-1", - access_via_team_ids: [], - access_groups: ["sales-model-group"], + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-sales", + model_info: { + id: "model-sales-1", + access_via_team_ids: [], + access_groups: ["sales-model-group"], + }, }, - }, - { - model_name: "gpt-4-engineering", - model_info: { - id: "model-eng-1", - access_via_team_ids: [], - access_groups: ["engineering-model-group"], + { + model_name: "gpt-4-engineering", + model_info: { + id: "model-eng-1", + access_via_team_ids: [], + access_groups: ["engineering-model-group"], + }, }, - }, - ], 2, 1, 1, 50); + ], + 2, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null }); @@ -284,26 +296,32 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-personal", - model_info: { - id: "model-personal-1", - direct_access: true, - access_via_team_ids: [], - access_groups: [], + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-personal", + model_info: { + id: "model-personal-1", + direct_access: true, + access_via_team_ids: [], + access_groups: [], + }, }, - }, - { - model_name: "gpt-4-team-only", - model_info: { - id: "model-team-1", - direct_access: false, - access_via_team_ids: ["team-123"], - access_groups: [], + { + model_name: "gpt-4-team-only", + model_info: { + id: "model-team-1", + direct_access: false, + access_via_team_ids: ["team-123"], + access_groups: [], + }, }, - }, - ], 2, 1, 1, 50); + ], + 2, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null }); @@ -330,38 +348,44 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-config", - litellm_model_name: "gpt-4-config", - provider: "openai", - model_info: { - id: "model-config-1", - db_model: false, - direct_access: true, - access_via_team_ids: [], - access_groups: [], - created_by: "user-123", - created_at: "2024-01-01", - updated_at: "2024-01-01", + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-config", + litellm_model_name: "gpt-4-config", + provider: "openai", + model_info: { + id: "model-config-1", + db_model: false, + direct_access: true, + access_via_team_ids: [], + access_groups: [], + created_by: "user-123", + created_at: "2024-01-01", + updated_at: "2024-01-01", + }, }, - }, - { - model_name: "gpt-4-db", - litellm_model_name: "gpt-4-db", - provider: "openai", - model_info: { - id: "model-db-1", - db_model: true, - direct_access: true, - access_via_team_ids: [], - access_groups: [], - created_by: "user-123", - created_at: "2024-01-01", - updated_at: "2024-01-01", + { + model_name: "gpt-4-db", + litellm_model_name: "gpt-4-db", + provider: "openai", + model_info: { + id: "model-db-1", + db_model: true, + direct_access: true, + access_via_team_ids: [], + access_groups: [], + created_by: "user-123", + created_at: "2024-01-01", + updated_at: "2024-01-01", + }, }, - }, - ], 2, 1, 1, 50); + ], + 2, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null }); @@ -387,23 +411,29 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-config", - litellm_model_name: "gpt-4-config", - provider: "openai", - model_info: { - id: "model-config-1", - db_model: false, - direct_access: true, - access_via_team_ids: [], - access_groups: [], - created_by: "user-123", - created_at: "2024-01-01", - updated_at: "2024-01-01", + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-config", + litellm_model_name: "gpt-4-config", + provider: "openai", + model_info: { + id: "model-config-1", + db_model: false, + direct_access: true, + access_via_team_ids: [], + access_groups: [], + created_by: "user-123", + created_at: "2024-01-01", + updated_at: "2024-01-01", + }, }, - }, - ], 1, 1, 1, 50); + ], + 1, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null }); @@ -537,23 +567,29 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-delete-test", - litellm_model_name: "gpt-4-delete-test", - provider: "openai", - model_info: { - id: "model-to-delete", - db_model: true, - direct_access: true, - access_via_team_ids: [], - access_groups: [], - created_by: "user-123", - created_at: "2024-01-01", - updated_at: "2024-01-01", + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-delete-test", + litellm_model_name: "gpt-4-delete-test", + provider: "openai", + model_info: { + id: "model-to-delete", + db_model: true, + direct_access: true, + access_via_team_ids: [], + access_groups: [], + created_by: "user-123", + created_at: "2024-01-01", + updated_at: "2024-01-01", + }, }, - }, - ], 1, 1, 1, 50); + ], + 1, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null, refetch: vi.fn() }); @@ -581,23 +617,29 @@ describe("AllModelsTab", () => { }), ); - const modelData = createPaginatedModelData([ - { - model_name: "gpt-4-clickable", - litellm_model_name: "gpt-4-clickable", - provider: "openai", - model_info: { - id: "clickable-model-id", - db_model: true, - direct_access: true, - access_via_team_ids: [], - access_groups: [], - created_by: "user-123", - created_at: "2024-01-01", - updated_at: "2024-01-01", + const modelData = createPaginatedModelData( + [ + { + model_name: "gpt-4-clickable", + litellm_model_name: "gpt-4-clickable", + provider: "openai", + model_info: { + id: "clickable-model-id", + db_model: true, + direct_access: true, + access_via_team_ids: [], + access_groups: [], + created_by: "user-123", + created_at: "2024-01-01", + updated_at: "2024-01-01", + }, }, - }, - ], 1, 1, 1, 50); + ], + 1, + 1, + 1, + 50, + ); mockUseModelsInfo.mockReturnValue({ data: modelData, isLoading: false, error: null, refetch: vi.fn() }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx index 2626ace86d5..2aa1eb4c808 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx @@ -68,7 +68,7 @@ const AllModelsTab = ({ setCurrentPage(1); setPagination((prev: PaginationState) => ({ ...prev, pageIndex: 0 })); }, 200), - [] + [], ); useEffect(() => { @@ -100,15 +100,11 @@ const AllModelsTab = ({ return sort.desc ? "desc" : "asc"; }, [sorting]); - const { data: rawModelData, isLoading: isLoadingModelsInfo, refetch: refetchModels } = useModelsInfo( - currentPage, - pageSize, - debouncedSearch || undefined, - undefined, - teamIdForQuery, - sortBy, - sortOrder - ); + const { + data: rawModelData, + isLoading: isLoadingModelsInfo, + refetch: refetchModels, + } = useModelsInfo(currentPage, pageSize, debouncedSearch || undefined, undefined, teamIdForQuery, sortBy, sortOrder); const isLoading = isLoadingModelsInfo || isLoadingModelCostMap; const getProviderFromModel = (model: string) => { @@ -494,7 +490,7 @@ const AllModelsTab = ({ ) : ( {paginationMeta.total_count > 0 - ? `Showing ${((currentPage - 1) * pageSize) + 1} - ${Math.min(currentPage * pageSize, paginationMeta.total_count)} of ${paginationMeta.total_count} results` + ? `Showing ${(currentPage - 1) * pageSize + 1} - ${Math.min(currentPage * pageSize, paginationMeta.total_count)} of ${paginationMeta.total_count} results` : "Showing 0 results"} )} @@ -510,10 +506,9 @@ const AllModelsTab = ({ setPagination((prev: PaginationState) => ({ ...prev, pageIndex: 0 })); }} disabled={currentPage === 1} - className={`px-3 py-1 text-sm border rounded-md ${currentPage === 1 - ? "bg-gray-100 text-gray-400 cursor-not-allowed" - : "hover:bg-gray-50" - }`} + className={`px-3 py-1 text-sm border rounded-md ${ + currentPage === 1 ? "bg-gray-100 text-gray-400 cursor-not-allowed" : "hover:bg-gray-50" + }`} > Previous @@ -529,10 +524,11 @@ const AllModelsTab = ({ setPagination((prev: PaginationState) => ({ ...prev, pageIndex: 0 })); }} disabled={currentPage >= paginationMeta.total_pages} - className={`px-3 py-1 text-sm border rounded-md ${currentPage >= paginationMeta.total_pages - ? "bg-gray-100 text-gray-400 cursor-not-allowed" - : "hover:bg-gray-50" - }`} + className={`px-3 py-1 text-sm border rounded-md ${ + currentPage >= paginationMeta.total_pages + ? "bg-gray-100 text-gray-400 cursor-not-allowed" + : "hover:bg-gray-50" + }`} > Next @@ -550,8 +546,8 @@ const AllModelsTab = ({ setSelectedModelId, setSelectedTeamId, getDisplayModelName, - () => { }, - () => { }, + () => {}, + () => {}, expandedRows, setExpandedRows, setDeleteModalModelId, @@ -577,24 +573,28 @@ const AllModelsTab = ({ alertMessage="This action cannot be undone." message="Are you sure you want to delete this model?" resourceInformationTitle="Model Information" - resourceInformation={modelToDelete ? [ - { - label: "Model Name", - value: modelToDelete.model_name || "Not Set", - }, - { - label: "LiteLLM Model Name", - value: modelToDelete.litellm_model_name || "Not Set", - }, - { - label: "Provider", - value: modelToDelete.provider || "Not Set", - }, - { - label: "Created By", - value: modelToDelete.model_info?.created_by || "Not Set", - }, - ] : []} + resourceInformation={ + modelToDelete + ? [ + { + label: "Model Name", + value: modelToDelete.model_name || "Not Set", + }, + { + label: "LiteLLM Model Name", + value: modelToDelete.litellm_model_name || "Not Set", + }, + { + label: "Provider", + value: modelToDelete.provider || "Not Set", + }, + { + label: "Created By", + value: modelToDelete.model_info?.created_by || "Not Set", + }, + ] + : [] + } onCancel={() => setDeleteModalModelId(null)} onOk={handleDeleteModel} confirmLoading={deleteLoading} diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/page.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/page.tsx index 2b4b4ace491..abcbe80a382 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/playground/page.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/page.tsx @@ -36,43 +36,43 @@ export default function PlaygroundPage() { return (
- - - Chat - Compare - Compliance - Agent Builder (Experimental) - - - - - - - - - - - - - - - - + + + Chat + Compare + Compliance + Agent Builder (Experimental) + + + + + + + + + + + + + + + +
); } diff --git a/ui/litellm-dashboard/src/app/login/LoginPage.test.tsx b/ui/litellm-dashboard/src/app/login/LoginPage.test.tsx index 25233725da6..6a61f5ed85f 100644 --- a/ui/litellm-dashboard/src/app/login/LoginPage.test.tsx +++ b/ui/litellm-dashboard/src/app/login/LoginPage.test.tsx @@ -304,8 +304,7 @@ describe("LoginPage", () => { }, writable: true, }); - document.cookie = - "token=; expires=Thu, 01 Jan 1970 00:00:00 GMT; path=/; SameSite=Lax"; + document.cookie = "token=; expires=Thu, 01 Jan 1970 00:00:00 GMT; path=/; SameSite=Lax"; }); afterEach(() => { diff --git a/ui/litellm-dashboard/src/app/login/LoginPage.tsx b/ui/litellm-dashboard/src/app/login/LoginPage.tsx index 2db95947305..db3a069902a 100644 --- a/ui/litellm-dashboard/src/app/login/LoginPage.tsx +++ b/ui/litellm-dashboard/src/app/login/LoginPage.tsx @@ -50,13 +50,11 @@ function LoginPageContent() { // Validate the SSO code is a plausible OAuth authorization code (alphanumeric // plus common URL-safe chars) so that arbitrary user input cannot trigger the // exchange endpoint. - const ssoCode = - rawSsoCode && /^[a-zA-Z0-9._~+/=-]+$/.test(rawSsoCode) ? rawSsoCode : null; + const ssoCode = rawSsoCode && /^[a-zA-Z0-9._~+/=-]+$/.test(rawSsoCode) ? rawSsoCode : null; if (ssoCode) { const rawWorkerUrl = localStorage.getItem("litellm_worker_url"); // Validate the stored worker URL: only allow http(s) URLs. - const workerUrl = - rawWorkerUrl && /^https?:\/\/.+/.test(rawWorkerUrl) ? rawWorkerUrl : null; + const workerUrl = rawWorkerUrl && /^https?:\/\/.+/.test(rawWorkerUrl) ? rawWorkerUrl : null; exchangeLoginCode(ssoCode, workerUrl).then(() => { params.delete("code"); const cleanSearch = params.toString(); @@ -277,10 +275,7 @@ function LoginPageContent() { {!uiConfig?.sso_configured ? ( - + @@ -315,7 +310,13 @@ function LoginPageContent() { type="info" showIcon closable - message={Single Sign-On (SSO) is enabled. LiteLLM no longer automatically redirects to the SSO login flow upon loading this page. To re-enable auto-redirect-to-SSO, set AUTO_REDIRECT_UI_LOGIN_TO_SSO=true in your environment configuration.} + message={ + + Single Sign-On (SSO) is enabled. LiteLLM no longer automatically redirects to the SSO login flow upon + loading this page. To re-enable auto-redirect-to-SSO, set{" "} + AUTO_REDIRECT_UI_LOGIN_TO_SSO=true in your environment configuration. + + } /> )} diff --git a/ui/litellm-dashboard/src/app/mcp/oauth/callback/page.tsx b/ui/litellm-dashboard/src/app/mcp/oauth/callback/page.tsx index 3b3729c1ac9..d292925f810 100644 --- a/ui/litellm-dashboard/src/app/mcp/oauth/callback/page.tsx +++ b/ui/litellm-dashboard/src/app/mcp/oauth/callback/page.tsx @@ -80,12 +80,12 @@ const McpOAuthCallbackContent = () => {

LiteLLM MCP OAuth

-

- Authorization complete. You may close this window and return to the LiteLLM dashboard. -

-

- If the window does not close automatically, everything is still saved—you can close it manually. -

+

+ Authorization complete. You may close this window and return to the LiteLLM dashboard. +

+

+ If the window does not close automatically, everything is still saved—you can close it manually. +

); diff --git a/ui/litellm-dashboard/src/app/model_hub_table/page.tsx b/ui/litellm-dashboard/src/app/model_hub_table/page.tsx index f35a6943a63..472cea4c27e 100644 --- a/ui/litellm-dashboard/src/app/model_hub_table/page.tsx +++ b/ui/litellm-dashboard/src/app/model_hub_table/page.tsx @@ -16,9 +16,7 @@ function PublicModelHubTableContent() { setAccessToken(key); }, [key]); - return ( - - ); + return ; } export default function PublicModelHubTable() { diff --git a/ui/litellm-dashboard/src/app/onboarding/OnboardingErrorView.test.tsx b/ui/litellm-dashboard/src/app/onboarding/OnboardingErrorView.test.tsx index d7a7ffb1b15..59071f17bf6 100644 --- a/ui/litellm-dashboard/src/app/onboarding/OnboardingErrorView.test.tsx +++ b/ui/litellm-dashboard/src/app/onboarding/OnboardingErrorView.test.tsx @@ -11,9 +11,7 @@ describe("OnboardingErrorView", () => { it("should show the expiry description", () => { render(); - expect( - screen.getByText("The invitation link may be invalid or expired.") - ).toBeInTheDocument(); + expect(screen.getByText("The invitation link may be invalid or expired.")).toBeInTheDocument(); }); it("should render a Back to Login link pointing to /ui/login", () => { diff --git a/ui/litellm-dashboard/src/app/onboarding/OnboardingForm.tsx b/ui/litellm-dashboard/src/app/onboarding/OnboardingForm.tsx index add58102c57..23a8bc6725a 100644 --- a/ui/litellm-dashboard/src/app/onboarding/OnboardingForm.tsx +++ b/ui/litellm-dashboard/src/app/onboarding/OnboardingForm.tsx @@ -26,9 +26,7 @@ export function OnboardingForm({ variant }: OnboardingFormProps) { const { mutate: claimToken, isPending } = useClaimOnboardingToken(); - const decoded = credentialsData?.token - ? (jwtDecode(credentialsData.token) as { [key: string]: any }) - : null; + const decoded = credentialsData?.token ? (jwtDecode(credentialsData.token) as { [key: string]: any }) : null; const userEmail: string = decoded?.user_email ?? ""; const userId: string | null = decoded?.user_id ?? null; const accessToken: string | null = decoded?.key ?? null; @@ -53,14 +51,12 @@ export function OnboardingForm({ variant }: OnboardingFormProps) { clearTokenCookies(); storeLoginToken(data.token); const proxyBaseUrl = getProxyBaseUrl(); - window.location.href = proxyBaseUrl - ? `${proxyBaseUrl}/ui/?login=success` - : "/ui/?login=success"; + window.location.href = proxyBaseUrl ? `${proxyBaseUrl}/ui/?login=success` : "/ui/?login=success"; }, onError: (error: Error) => { setClaimError(error.message || "Failed to submit. Please try again."); }, - } + }, ); }; diff --git a/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.test.tsx b/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.test.tsx index f742176d1ba..f3286984706 100644 --- a/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.test.tsx +++ b/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.test.tsx @@ -74,16 +74,12 @@ describe("OnboardingFormBody", () => { await user.click(screen.getByRole("button", { name: /sign up/i })); await waitFor(() => { - expect(onSubmit).toHaveBeenCalledWith( - expect.objectContaining({ password: "mypassword" }) - ); + expect(onSubmit).toHaveBeenCalledWith(expect.objectContaining({ password: "mypassword" })); }); }); it("should show 'Reset Password' on the submit button for reset_password variant", () => { render(); - expect( - screen.getByRole("button", { name: /reset password/i }) - ).toBeInTheDocument(); + expect(screen.getByRole("button", { name: /reset password/i })).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.tsx b/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.tsx index c57c7328b61..4aa5e2e6138 100644 --- a/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.tsx +++ b/ui/litellm-dashboard/src/app/onboarding/OnboardingFormBody.tsx @@ -9,13 +9,7 @@ type OnboardingFormBodyProps = { onSubmit: (values: { password: string }) => void; }; -export function OnboardingFormBody({ - variant, - userEmail, - isPending, - claimError, - onSubmit, -}: OnboardingFormBodyProps) { +export function OnboardingFormBody({ variant, userEmail, isPending, claimError, onSubmit }: OnboardingFormBodyProps) { const [form] = Form.useForm(); React.useEffect(() => { @@ -28,9 +22,7 @@ export function OnboardingFormBody({ 🚅 LiteLLM - - {variant === "reset_password" ? "Reset Password" : "Sign Up"} - + {variant === "reset_password" ? "Reset Password" : "Sign Up"} {variant === "reset_password" ? "Reset your password to access Admin UI." @@ -45,12 +37,7 @@ export function OnboardingFormBody({ description={
SSO is under the Enterprise Tier. -
@@ -59,7 +46,12 @@ export function OnboardingFormBody({ /> )} -
onSubmit({ password: values.password })}> + onSubmit({ password: values.password })} + > @@ -68,18 +60,12 @@ export function OnboardingFormBody({ label="Password" name="password" rules={[{ required: true, message: "password required to sign up" }]} - help={ - variant === "reset_password" - ? "Enter your new password" - : "Create a password for your account" - } + help={variant === "reset_password" ? "Enter your new password" : "Create a password for your account"} > - {claimError && ( - - )} + {claimError && }
- } - > + Loading...}> ); diff --git a/ui/litellm-dashboard/src/app/page.tsx b/ui/litellm-dashboard/src/app/page.tsx index ce12967c911..da6a0d5a76f 100644 --- a/ui/litellm-dashboard/src/app/page.tsx +++ b/ui/litellm-dashboard/src/app/page.tsx @@ -46,7 +46,13 @@ import SpendLogsTable from "@/components/view_logs"; import ViewUserDashboard from "@/components/view_users"; import { ThemeProvider } from "@/contexts/ThemeContext"; import { useAuth } from "@/contexts/AuthContext"; -import { buildLoginUrlWithReturn, consumeReturnUrl, isValidReturnUrl, normalizeUrlForCompare, storeReturnUrl } from "@/utils/returnUrlUtils"; +import { + buildLoginUrlWithReturn, + consumeReturnUrl, + isValidReturnUrl, + normalizeUrlForCompare, + storeReturnUrl, +} from "@/utils/returnUrlUtils"; import { isAdminRole } from "@/utils/roles"; import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; import { useRouter, useSearchParams } from "next/navigation"; @@ -67,17 +73,8 @@ interface ProxySettings { const LEGACY_REDIRECTS: Record = {}; function CreateKeyPageContent() { - const { - authLoading, - token, - userID, - userRole, - userEmail, - accessToken, - premiumUser, - setUserRole, - setUserEmail, - } = useAuth(); + const { authLoading, token, userID, userRole, userEmail, accessToken, premiumUser, setUserRole, setUserEmail } = + useAuth(); const [teams, setTeams] = useState(null); const [keys, setKeys] = useState([]); @@ -129,15 +126,13 @@ function CreateKeyPageContent() { // Validate owned_by against allowed values const validOwnedByValues = ["you", "service_account", "another_user"]; - const validatedOwnedBy = ownedBy && validOwnedByValues.includes(ownedBy) - ? (ownedBy as CreateKeyPrefillData["owned_by"]) - : undefined; + const validatedOwnedBy = + ownedBy && validOwnedByValues.includes(ownedBy) ? (ownedBy as CreateKeyPrefillData["owned_by"]) : undefined; // Validate key_type against allowed values const validKeyTypes = ["default", "llm_api", "management"]; - const validatedKeyType = keyType && validKeyTypes.includes(keyType) - ? (keyType as CreateKeyPrefillData["key_type"]) - : undefined; + const validatedKeyType = + keyType && validKeyTypes.includes(keyType) ? (keyType as CreateKeyPrefillData["key_type"]) : undefined; // Sanitize key_alias (limit length, trim whitespace) const sanitizedKeyAlias = keyAlias @@ -149,8 +144,8 @@ function CreateKeyPageContent() { ? modelsParam .split(",") .slice(0, 100) // Limit number of models to prevent DoS - .map(m => m.trim().slice(0, 256)) // Limit individual model name length - .filter(m => m.length > 0) // Remove empty strings + .map((m) => m.trim().slice(0, 256)) // Limit individual model name length + .filter((m) => m.length > 0) // Remove empty strings : undefined; return { @@ -259,7 +254,9 @@ function CreateKeyPageContent() { if (accessToken && userID && userRole) { v2TeamListCall(accessToken, 1, 100, { userID: userRole !== "Admin" && userRole !== "Admin Viewer" ? userID : null, - }).then((response) => setTeams(response.teams ?? [])).catch(console.error); + }) + .then((response) => setTeams(response.teams ?? [])) + .catch(console.error); } if (accessToken) { fetchOrganizations(accessToken, setOrganizations); @@ -353,235 +350,231 @@ function CreateKeyPageContent() { return ( }> - - - {invitation_id ? ( - + + {invitation_id ? ( + + ) : ( +
+ - ) : ( -
- -
-
+
+
- {page == "api-keys" ? ( - + ) : page == "models" ? ( + + ) : page == "llm-playground" ? ( + + ) : page == "users" ? ( + + ) : page == "teams" ? ( + + ) : page == "organizations" ? ( + + ) : page == "admin-panel" ? ( + + ) : page == "api_ref" || page == "api-reference" ? ( + + ) : page == "logging-and-alerts" ? ( + + ) : page == "budgets" ? ( + + ) : page == "guardrails" ? ( + + ) : page == "policies" ? ( + + ) : page == "agents" ? ( + + ) : page == "prompts" ? ( + + ) : page == "transform-request" ? ( + + ) : page == "router-settings" ? ( + + ) : page == "ui-theme" ? ( + + ) : page == "cost-tracking" ? ( + + ) : page == "model-hub-table" ? ( + isAdminRole(userRole) ? ( + - ) : page == "models" ? ( - - ) : page == "llm-playground" ? ( - - ) : page == "users" ? ( - - ) : page == "teams" ? ( - - ) : page == "organizations" ? ( - - ) : page == "admin-panel" ? ( - - ) : page == "api_ref" || page == "api-reference" ? ( - - ) : page == "logging-and-alerts" ? ( - - ) : page == "budgets" ? ( - - ) : page == "guardrails" ? ( - - ) : page == "policies" ? ( - - ) : page == "agents" ? ( - - ) : page == "prompts" ? ( - - ) : page == "transform-request" ? ( - - ) : page == "router-settings" ? ( - - ) : page == "ui-theme" ? ( - - ) : page == "cost-tracking" ? ( - - ) : page == "model-hub-table" ? ( - isAdminRole(userRole) ? ( - - ) : ( - - ) - ) : page == "caching" ? ( - - ) : page == "pass-through-settings" ? ( - - ) : page == "logs" ? ( - - ) : page == "mcp-servers" ? ( - - ) : page == "search-tools" ? ( - - ) : page == "tag-management" ? ( - - ) : page == "skills" || page == "claude-code-plugins" ? ( - - ) : page == "access-groups" ? ( - - ) : page == "projects" ? ( - - ) : page == "vector-stores" ? ( - - ) : page == "tool-policies" ? ( - - ) : page == "workflows" ? ( - - ) : page == "memory" ? ( - - ) : page == "guardrails-monitor" ? ( - - ) : page == "new_usage" ? ( - ) : ( - - )} -
- - {/* Survey Components */} - - - - {/* Claude Code Components */} - - + + ) + ) : page == "caching" ? ( + + ) : page == "pass-through-settings" ? ( + + ) : page == "logs" ? ( + + ) : page == "mcp-servers" ? ( + + ) : page == "search-tools" ? ( + + ) : page == "tag-management" ? ( + + ) : page == "skills" || page == "claude-code-plugins" ? ( + + ) : page == "access-groups" ? ( + + ) : page == "projects" ? ( + + ) : page == "vector-stores" ? ( + + ) : page == "tool-policies" ? ( + + ) : page == "workflows" ? ( + + ) : page == "memory" ? ( + + ) : page == "guardrails-monitor" ? ( + + ) : page == "new_usage" ? ( + + ) : ( + + )}
- )} - - + + {/* Survey Components */} + + + + {/* Claude Code Components */} + + +
+ )} + + ); } diff --git a/ui/litellm-dashboard/src/components/AIHub/AgentHubTableColumns.test.tsx b/ui/litellm-dashboard/src/components/AIHub/AgentHubTableColumns.test.tsx index 083e67c297a..f980aee3c2c 100644 --- a/ui/litellm-dashboard/src/components/AIHub/AgentHubTableColumns.test.tsx +++ b/ui/litellm-dashboard/src/components/AIHub/AgentHubTableColumns.test.tsx @@ -104,12 +104,10 @@ describe("AgentHubTableColumns", () => { render(); // "In:" and "Out:" are in children; getByText with exact:false // matches against the element's full textContent across child nodes - expect(screen.getByText((_, el) => - el?.tagName === "P" && el.textContent === "In: text" - )).toBeInTheDocument(); - expect(screen.getByText((_, el) => - el?.tagName === "P" && el.textContent === "Out: text, image" - )).toBeInTheDocument(); + expect(screen.getByText((_, el) => el?.tagName === "P" && el.textContent === "In: text")).toBeInTheDocument(); + expect( + screen.getByText((_, el) => el?.tagName === "P" && el.textContent === "Out: text, image"), + ).toBeInTheDocument(); }); it("should display 'Yes' badge for public agents", () => { diff --git a/ui/litellm-dashboard/src/components/AIHub/ClaudeCodeMarketplaceTab.tsx b/ui/litellm-dashboard/src/components/AIHub/ClaudeCodeMarketplaceTab.tsx index 043077c0210..762b0836921 100644 --- a/ui/litellm-dashboard/src/components/AIHub/ClaudeCodeMarketplaceTab.tsx +++ b/ui/litellm-dashboard/src/components/AIHub/ClaudeCodeMarketplaceTab.tsx @@ -2,14 +2,8 @@ import { SearchOutlined } from "@ant-design/icons"; import { Card, Tab, TabGroup, TabList, TabPanel, TabPanels, Text } from "@tremor/react"; import { Input } from "antd"; import React, { useEffect, useMemo, useState } from "react"; -import { - extractCategories, - filterPluginsByCategory, - filterPluginsBySearch, -} from "../claude_code_plugins/helpers"; -import { - MarketplaceResponse -} from "../claude_code_plugins/types"; +import { extractCategories, filterPluginsByCategory, filterPluginsBySearch } from "../claude_code_plugins/helpers"; +import { MarketplaceResponse } from "../claude_code_plugins/types"; import { ModelDataTable } from "../model_dashboard/table"; import NotificationsManager from "../molecules/notifications_manager"; import { getClaudeCodeMarketplace } from "../networking"; @@ -19,11 +13,8 @@ interface ClaudeCodeMarketplaceTabProps { publicPage?: boolean; } -const ClaudeCodeMarketplaceTab: React.FC = ({ - publicPage = false, -}) => { - const [marketplaceData, setMarketplaceData] = - useState(null); +const ClaudeCodeMarketplaceTab: React.FC = ({ publicPage = false }) => { + const [marketplaceData, setMarketplaceData] = useState(null); const [isLoading, setIsLoading] = useState(true); const [searchTerm, setSearchTerm] = useState(""); const [selectedCategoryIndex, setSelectedCategoryIndex] = useState(0); @@ -74,18 +65,13 @@ const ClaudeCodeMarketplaceTab: React.FC = ({ return plugins; }, [marketplaceData, selectedCategory, searchTerm]); - const columns = useMemo( - () => getMarketplaceTableColumns(copyToClipboard, publicPage), - [publicPage] - ); + const columns = useMemo(() => getMarketplaceTableColumns(copyToClipboard, publicPage), [publicPage]); if (!marketplaceData && !isLoading) { return (
- - Failed to load marketplace. Please try again later. - + Failed to load marketplace. Please try again later.
); @@ -110,14 +96,8 @@ const ClaudeCodeMarketplaceTab: React.FC = ({ {categories.map((category) => { // Count plugins in this category - const categoryPlugins = filterPluginsByCategory( - marketplaceData?.plugins || [], - category - ); - const count = filterPluginsBySearch( - categoryPlugins, - searchTerm - ).length; + const categoryPlugins = filterPluginsByCategory(marketplaceData?.plugins || [], category); + const count = filterPluginsBySearch(categoryPlugins, searchTerm).length; return ( @@ -143,8 +123,7 @@ const ClaudeCodeMarketplaceTab: React.FC = ({ {/* Footer Info */}
- Showing {filteredPlugins.length} of{" "} - {marketplaceData?.plugins.length || 0} plugin + Showing {filteredPlugins.length} of {marketplaceData?.plugins.length || 0} plugin {marketplaceData?.plugins.length !== 1 ? "s" : ""} {searchTerm && ` matching "${searchTerm}"`} {selectedCategory !== "All" && ` in ${selectedCategory}`} diff --git a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx index ee59ac84ece..3a22a55298e 100644 --- a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx +++ b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx @@ -48,11 +48,7 @@ describe("ModelHubTable", () => { }); // Reusable helper function to setup mocks for auth redirect tests - const setupAuthRedirectTest = ( - requireAuth: boolean, - tokenValue: string | null, - isTokenValid: boolean - ) => { + const setupAuthRedirectTest = (requireAuth: boolean, tokenValue: string | null, isTokenValid: boolean) => { mockUseUISettings.mockReturnValue({ data: { values: { @@ -87,14 +83,12 @@ describe("ModelHubTable", () => { tokenValue: string | null, isTokenValid: boolean, shouldRedirect: boolean, - description: string + description: string, ) => { it(description, async () => { setupAuthRedirectTest(requireAuth, tokenValue, isTokenValid); - renderWithProviders( - - ); + renderWithProviders(); await waitFor(() => { if (shouldRedirect) { @@ -125,7 +119,9 @@ describe("ModelHubTable", () => { isLoading: false, }); - renderWithProviders(); + renderWithProviders( + , + ); await waitFor(() => { expect(screen.getByText("AI Hub")).toBeInTheDocument(); @@ -172,7 +168,7 @@ describe("ModelHubTable", () => { null, false, true, - "should redirect to login when requireAuth is true and there is no token" + "should redirect to login when requireAuth is true and there is no token", ); testAuthRedirect( @@ -180,7 +176,7 @@ describe("ModelHubTable", () => { "expired-token", false, true, - "should redirect to login when requireAuth is true and token is expired" + "should redirect to login when requireAuth is true and token is expired", ); testAuthRedirect( @@ -188,24 +184,18 @@ describe("ModelHubTable", () => { "malformed-token", false, true, - "should redirect to login when requireAuth is true and token is malformed" + "should redirect to login when requireAuth is true and token is malformed", ); // Test cases where requireAuth is false - should NOT redirect regardless of token state - testAuthRedirect( - false, - null, - false, - false, - "should not redirect when requireAuth is false and there is no token" - ); + testAuthRedirect(false, null, false, false, "should not redirect when requireAuth is false and there is no token"); testAuthRedirect( false, "expired-token", false, false, - "should not redirect when requireAuth is false and token is expired" + "should not redirect when requireAuth is false and token is expired", ); testAuthRedirect( @@ -213,7 +203,7 @@ describe("ModelHubTable", () => { "malformed-token", false, false, - "should not redirect when requireAuth is false and token is malformed" + "should not redirect when requireAuth is false and token is malformed", ); }); }); diff --git a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx index 75058157a65..5d171139ab5 100644 --- a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx +++ b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx @@ -526,9 +526,7 @@ const ModelHubTable: React.FC = ({ accessToken, publicPage, {publicPage == false && canModify && (
- +
)} = ({ s.description?.toLowerCase().includes(q) || s.domain?.toLowerCase().includes(q) || s.namespace?.toLowerCase().includes(q) || - s.keywords?.some((k) => k.toLowerCase().includes(q)) + s.keywords?.some((k) => k.toLowerCase().includes(q)), ); } return result; @@ -94,9 +94,7 @@ const SkillHubDashboard: React.FC = ({ {/* Search + filters + table */}
-

- All {publicPage ? "Public " : ""}Skills -

+

All {publicPage ? "Public " : ""}Skills

+ - -