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* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci: rename fork-flag to unit-flag now that it applies on every event * test: move tests/test_litellm root and small trees into tests/unit Pure renames, no content changes. Follow-up commits in this PR fix references, merge the three files that already existed in tests/unit, keep live-provider tests in tests/test_litellm and wire CI. * test: carry tests/test_litellm conftest isolation into tests/unit Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS, proxy-URL and keychain env, and session-end client cleanup now reset for unit tests too. The environment isolation owns its MonkeyPatch so a test's own monkeypatch is undone before the model-cost teardown runs. * test: merge, split and prune the moved root and small-tree tests Merge batches/test_batch_utils.py and the chat_completions and messages dispatch tests into the files that already existed in tests/unit. Keep the live Gemini interactions tests, the async image-fetch format test and the OpenAI embedding scorer test in tests/test_litellm since they need real network or keys. Put test_router.py under tests/unit/test_router so the existing package no longer shadows it. Delete eight tests the audit found superseded by stronger ones kept in this move. * ci: run the moved root and small-tree tests under their legacy flags Add the misc and responses-caching-types flags to unit_selection.sh and CircleCI, extend enterprise-routing and mcp-integration, and point the legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest and change classifier at the new paths. * test: make the new tests/unit directories packages tests/unit/test_package_layout.py requires every directory to carry an __init__.py, and without one the moved and retained test_litellm_responses_bridge.py modules collide on import. * test: scope the unit socket block to tests/unit in shared sessions The GHA shards collect the legacy test-path and the unit selection in one pytest session. The unit conftest's loopback-only block leaked into legacy modules that reach the network at import. The legacy conftest now lifts the restriction at collect and setup time, and the unit conftest re-applies it when collecting its own modules. * test: move tests/test_litellm/llms into tests/unit/llms Rename-only. Moves the provider tests and the fine-tuning fixtures they load, mirroring the old paths. Follow-up commits merge, split and wire them. * test: merge, split and prune the moved llms tests Merges the Databricks chat transformation tests into the existing unit file, keeps the tests that need real keys or the network in tests/test_litellm, deletes the audited tests a stronger unit test already covers, and points imports at tests.unit.llms. * ci: run the moved llms tests under their legacy flags The Vertex AI and All Other Providers shards keep their legacy test-path for the retained files and add the llm-vertex-ai and llm-other-providers unit selections. CircleCI gets matching unit jobs. * test: make the tests/unit/llms directories packages Adds __init__.py to the moved dirs and drops the legacy ones whose directories no longer hold tests. * test: drop script runners and path hacks the llms split left dangling The __main__ runners in the split openai_like files and the Databricks e2e runner called tests that now live in the other half of the split or were deleted. The retained legacy halves also no longer need sys.path edits. * test: give the shard-script tests their own GITHUB_OUTPUT They only passed where the runner set it. The CircleCI unit job's env allowlist drops it, so the script's redirect failed there. * test: point the router and module-deletion checks at tests/unit router_code_coverage and code_qa_check_tests only searched tests/test_litellm, so the moved router tests no longer counted. The two silent-experiment tests the audit deleted were the only direct callers of those methods; they are replaced with tests that assert the forwarded shadow request and the recursion guard. * test: keep the Databricks manual e2e runner and fix the SageMaker Nova run path The Databricks e2e file is a manual script whose main() calls the tests that were pruned, so pruning them broke the documented run. It is back to its main version. The SageMaker Nova docstring now points at the file's real location in tests/local_testing. * test: keep the job's UNIT_FLAG out of the shard-script tests --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
260 lines
10 KiB
Python
260 lines
10 KiB
Python
import json
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import math
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from unittest.mock import MagicMock, patch
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import httpx
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import pytest
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import litellm
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from litellm import get_llm_provider
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from litellm.types.utils import ModelResponse, Usage
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NADIR_BASE = "https://api.getnadir.com/v1"
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COST_HEADER = "llm_provider-x-litellm-response-cost"
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def _transform(payload):
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raw = httpx.Response(
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200,
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content=json.dumps(payload).encode(),
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headers={"content-type": "application/json"},
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request=httpx.Request("POST", f"{NADIR_BASE}/chat/completions"),
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)
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return litellm.NadirConfig().transform_response(
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model="auto",
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raw_response=raw,
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model_response=ModelResponse(),
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logging_obj=MagicMock(),
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request_data={},
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messages=[],
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optional_params={},
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litellm_params={},
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encoding=None,
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)
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def _payload(**extra):
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return {
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"id": "req-1",
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"object": "chat.completion",
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"created": 0,
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"model": "claude-haiku-4-5",
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"choices": [{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}],
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"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
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**extra,
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}
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def _cost(response, provider):
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return litellm.completion_cost(completion_response=response, custom_llm_provider=provider)
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def _logged_cost(response):
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return litellm.response_cost_calculator(
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response_object=response,
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model="auto",
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custom_llm_provider="nadir",
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call_type="completion",
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optional_params={},
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)
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class TestNadirProviderResolution:
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def test_model_prefix_resolves_to_nadir(self):
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model, provider, _, _ = get_llm_provider(model="nadir/auto", api_key="sk-test")
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assert (model, provider) == ("auto", "nadir")
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def test_default_api_base(self):
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_, _, _, api_base = get_llm_provider(model="nadir/auto", api_key="sk-test")
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assert api_base == NADIR_BASE
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def test_api_base_override(self):
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_, _, _, api_base = get_llm_provider(
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model="nadir/auto",
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api_key="sk-test",
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api_base="https://gateway.internal/v1",
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)
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assert api_base == "https://gateway.internal/v1"
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def test_endpoint_reverse_maps_to_nadir_with_the_env_key(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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_, provider, dynamic_api_key, _ = get_llm_provider(model="auto", api_base=NADIR_BASE)
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assert (provider, dynamic_api_key) == ("nadir", "sk-server-secret")
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def test_plaintext_endpoint_never_loads_the_env_key(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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_, provider, dynamic_api_key, _ = get_llm_provider(model="auto", api_base="http://api.getnadir.com/v1")
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assert provider == "nadir"
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assert dynamic_api_key is None
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class TestNadirCredentialScoping:
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def test_env_key_used_for_default_endpoint(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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_, _, dynamic_api_key, _ = get_llm_provider(model="nadir/auto")
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assert dynamic_api_key == "sk-server-secret"
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def test_env_key_used_when_base_matches_default(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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_, _, dynamic_api_key, _ = get_llm_provider(model="nadir/auto", api_base=f"{NADIR_BASE}/")
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assert dynamic_api_key == "sk-server-secret"
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def test_env_key_not_leaked_to_custom_base(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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_, _, dynamic_api_key, _ = get_llm_provider(model="nadir/auto", api_base="https://attacker.example/v1")
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assert dynamic_api_key is None
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def test_caller_key_used_for_custom_base(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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_, _, dynamic_api_key, _ = get_llm_provider(
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model="nadir/auto",
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api_base="https://self-hosted.internal/v1",
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api_key="sk-caller-own",
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)
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assert dynamic_api_key == "sk-caller-own"
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def test_env_key_used_for_operator_configured_base(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-server-secret")
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monkeypatch.setenv("NADIR_API_BASE", "https://nadir.mycorp.internal/v1")
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_, _, dynamic_api_key, _ = get_llm_provider(model="nadir/auto", api_base="https://nadir.mycorp.internal/v1")
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assert dynamic_api_key == "sk-server-secret"
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class TestNadirParamMapping:
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def test_supported_params_are_mapped(self):
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params = litellm.get_optional_params(
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model="auto",
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custom_llm_provider="nadir",
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temperature=0.5,
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max_tokens=64,
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)
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assert params["temperature"] == 0.5
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assert params["max_tokens"] == 64
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def test_streaming_is_advertised_and_tools_are_not(self):
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params = litellm.get_supported_openai_params(model="auto", custom_llm_provider="nadir")
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assert "stream" in params
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assert "tools" not in params
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@pytest.mark.parametrize(
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"unsupported",
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[
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{"tools": [{"type": "function", "function": {"name": "f", "parameters": {}}}]},
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{"stop": ["\n"]},
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{"seed": 7},
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{"n": 2},
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],
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)
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def test_params_nadir_would_silently_drop_are_rejected(self, unsupported):
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with pytest.raises(litellm.UnsupportedParamsError):
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litellm.get_optional_params(model="auto", custom_llm_provider="nadir", **unsupported)
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def test_unsupported_params_are_dropped_when_asked(self):
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params = litellm.get_optional_params(
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model="auto",
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custom_llm_provider="nadir",
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drop_params=True,
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seed=7,
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temperature=0.2,
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)
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assert "seed" not in params
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assert params["temperature"] == 0.2
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class TestNadirEnvValidation:
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def test_validate_environment_detects_key(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-live-xyz")
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result = litellm.validate_environment(model="nadir/auto")
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assert result["keys_in_environment"] is True
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def test_validate_environment_flags_missing_key(self, monkeypatch):
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monkeypatch.delenv("NADIR_API_KEY", raising=False)
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result = litellm.validate_environment(model="nadir/auto")
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assert "NADIR_API_KEY" in result["missing_keys"]
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class TestNadirCostAttribution:
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def test_reported_cost_wins_over_model_pricing(self):
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res = _transform(_payload(nadir_metadata={"cost": {"total_cost_usd": 0.00123}}))
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assert _logged_cost(res) == pytest.approx(0.00123)
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assert _logged_cost(res) != _cost(res, "anthropic")
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def test_routed_model_is_preserved(self):
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res = _transform(_payload(nadir_metadata={"cost": {"total_cost_usd": 0.001}}))
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assert res.model == "claude-haiku-4-5"
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def test_missing_cost_prices_the_routed_model_from_its_own_entry(self):
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res = _transform(_payload())
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assert res.choices[0].message.content == "hi"
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assert COST_HEADER not in res._hidden_params.get("additional_headers", {})
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assert _cost(res, "nadir") == _logged_cost(res) == _cost(res, "anthropic") > 0
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def test_streamed_routed_model_prices_from_its_own_entry(self):
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res = ModelResponse(
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model="gemini-3.5-flash-lite",
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usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150),
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)
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assert _cost(res, "nadir") == _cost(res, "gemini") > 0
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@pytest.mark.parametrize("bad", [-0.001, math.nan, math.inf, -math.inf, True, "0.001", None])
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def test_invalid_reported_cost_falls_back_to_model_pricing(self, bad):
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res = _transform(_payload(nadir_metadata={"cost": {"total_cost_usd": bad}}))
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assert COST_HEADER not in res._hidden_params.get("additional_headers", {})
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assert _cost(res, "nadir") == _cost(res, "anthropic") > 0
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@pytest.mark.parametrize("metadata", ["oops", {"cost": "free"}, {"cost": None}, {}])
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def test_malformed_metadata_falls_back_to_model_pricing(self, metadata):
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res = _transform(_payload(nadir_metadata=metadata))
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assert COST_HEADER not in res._hidden_params.get("additional_headers", {})
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assert _cost(res, "nadir") == _cost(res, "anthropic") > 0
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class TestNadirCompletionDispatch:
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def _call(self, **kwargs):
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captured = {}
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def fake_completion(**call_kwargs):
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captured.update(call_kwargs)
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return ModelResponse()
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with patch( # test-quality-ok: these tests assert the dispatch wiring itself (nadir must reach base_llm_http_handler, and which credentials it is handed); faking HTTP would not observe that
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"litellm.main.base_llm_http_handler.completion", side_effect=fake_completion
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):
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litellm.completion(
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model="nadir/auto",
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messages=[{"role": "user", "content": "hi"}],
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**kwargs,
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)
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return captured
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def test_routes_through_the_http_handler_as_nadir(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-env")
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captured = self._call()
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assert captured["custom_llm_provider"] == "nadir"
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assert captured["api_base"] == NADIR_BASE
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def test_env_key_is_used_for_the_default_endpoint(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-env")
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assert self._call()["api_key"] == "sk-env"
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def test_caller_key_wins(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-env")
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assert self._call(api_key="sk-caller")["api_key"] == "sk-caller"
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def test_env_key_is_not_forwarded_to_a_caller_supplied_host(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-env")
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captured = self._call(api_base="https://attacker.example/v1")
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assert captured["api_key"] != "sk-env"
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assert captured["api_base"] == "https://attacker.example/v1"
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def test_global_key_is_not_forwarded_to_a_caller_supplied_host(self, monkeypatch):
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monkeypatch.delenv("NADIR_API_KEY", raising=False)
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monkeypatch.setattr(litellm, "api_key", "sk-global")
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captured = self._call(api_base="https://attacker.example/v1")
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assert captured["api_key"] != "sk-global"
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def test_custom_api_base_is_honoured(self, monkeypatch):
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monkeypatch.setenv("NADIR_API_KEY", "sk-env")
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captured = self._call(api_base="https://nadir.internal/v1", api_key="sk-own")
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assert captured["api_base"] == "https://nadir.internal/v1"
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assert captured["api_key"] == "sk-own"
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