scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-10-07 02:59:05 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 103

Merge pull request #21357 from BerriAI/release_feb16_copy

Browse source 
[Infra] v1.81.13-nightly Change Copy to main
This commit is contained in:
yuneng-jiang 2026-02-16 20:15:57 -08:00 • committed by GitHub
commit 3b5096d142
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
9 changed files with 94 additions and 130 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

1
docs/my-website/docs/proxy/config_settings.md
View file

@ -450,6 +450,7 @@ router_settings:
| BATCH_STATUS_POLL_INTERVAL_SECONDS | Interval in seconds for polling batch status. Default is 3600 (1 hour)
| BATCH_STATUS_POLL_MAX_ATTEMPTS | Maximum number of attempts for polling batch status. Default is 24 (for 24 hours)
| BEDROCK_MAX_POLICY_SIZE | Maximum size for Bedrock policy. Default is 75
| BEDROCK_MIN_THINKING_BUDGET_TOKENS | Minimum thinking budget in tokens for Bedrock reasoning models. Bedrock returns a 400 error if budget_tokens is below this value. Requests with lower values are clamped to this minimum. Default is 1024
| BERRISPEND_ACCOUNT_ID | Account ID for BerriSpend service
| BRAINTRUST_API_KEY | API key for Braintrust integration
| BRAINTRUST_API_BASE | Base URL for Braintrust API. Default is https://api.braintrustdata.com/v1

60
litellm/proxy/management_endpoints/key_management_endpoints.py
View file

@ -3277,6 +3277,14 @@ async def _execute_virtual_key_regeneration(
update_data.update(non_default_values)
update_data = prisma_client.jsonify_object(data=update_data)
# If grace period set, insert deprecated key so old key remains valid
await _insert_deprecated_key(
prisma_client=prisma_client,
old_token_hash=hashed_api_key,
new_token_hash=new_token_hash,
grace_period=data.grace_period if data else None,
)
updated_token = await prisma_client.db.litellm_verificationtoken.update(
where={"token": hashed_api_key},
data=update_data, # type: ignore
@ -3474,58 +3482,6 @@ async def regenerate_key_fn( # noqa: PLR0915
)
verbose_proxy_logger.debug("key_in_db: %s", _key_in_db)
new_token = get_new_token(data=data)
new_token_hash = hash_token(new_token)
new_token_key_name = f"sk-...{new_token[-4:]}"
# Prepare the update data
update_data = {
"token": new_token_hash,
"key_name": new_token_key_name,
}
non_default_values = {}
if data is not None:
# Update with any provided parameters from GenerateKeyRequest
non_default_values = await prepare_key_update_data(
data=data, existing_key_row=_key_in_db
)
verbose_proxy_logger.debug("non_default_values: %s", non_default_values)
update_data.update(non_default_values)
update_data = prisma_client.jsonify_object(data=update_data)
# If grace period set, insert deprecated key so old key remains valid
await _insert_deprecated_key(
prisma_client=prisma_client,
old_token_hash=hashed_api_key,
new_token_hash=new_token_hash,
grace_period=data.grace_period if data else None,
)
# Update the token in the database
updated_token = await prisma_client.db.litellm_verificationtoken.update(
where={"token": hashed_api_key},
data=update_data, # type: ignore
)
updated_token_dict = {}
if updated_token is not None:
updated_token_dict = dict(updated_token)
updated_token_dict["key"] = new_token
updated_token_dict["token_id"] = updated_token_dict.pop("token")
### 3. remove existing key entry from cache
######################################################################
if hashed_api_key or key:
await _delete_cache_key_object(
hashed_token=hash_token(key),
user_api_key_cache=user_api_key_cache,
proxy_logging_obj=proxy_logging_obj,
)
# Normalize litellm_changed_by: if it's a Header object or not a string, convert to None
if litellm_changed_by is not None and not isinstance(litellm_changed_by, str):
litellm_changed_by = None

4
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm"
version = "1.81.12"
version = "1.81.13"
description = "Library to easily interface with LLM API providers"
authors = ["BerriAI"]
license = "MIT"
@ -182,7 +182,7 @@ requires = ["poetry-core", "wheel"]
build-backend = "poetry.core.masonry.api"
[tool.commitizen]
version = "1.81.12"
version = "1.81.13"
version_files = [
"pyproject.toml:^version"
]

2
tests/llm_responses_api_testing/base_responses_api.py
View file

@ -74,7 +74,7 @@ def validate_responses_api_response(response, final_chunk: bool = False):
"top_p": (int, float, type(None)),
"max_output_tokens": (int, type(None)),
"previous_response_id": (str, type(None)),
"reasoning": dict,
"reasoning": (dict, type(None)),
"status": str,
"text": dict,
"truncation": (str, type(None)),

11
tests/test_litellm/containers/test_container_integration.py
View file

@ -385,6 +385,15 @@ class TestContainerIntegration:
@pytest.mark.parametrize("provider", ["openai"])
def test_provider_support(self, provider):
"""Test that the container API works with supported providers."""
import importlib
import litellm.containers.main as containers_main_module
# Reload the module to ensure it has a fresh reference to base_llm_http_handler
# after conftest reloads litellm (same pattern as test_error_handling_integration)
importlib.reload(containers_main_module)
from litellm.containers.main import create_container as create_container_fresh
mock_response = ContainerObject(
id="cntr_provider_test",
object="container",
@ -398,7 +407,7 @@ class TestContainerIntegration:
with patch('litellm.containers.main.base_llm_http_handler') as mock_handler:
mock_handler.container_create_handler.return_value = mock_response
response = create_container(
response = create_container_fresh(
name="Provider Test Container",
custom_llm_provider=provider
)

82
tests/test_litellm/llms/meta_llama/test_meta_llama_chat_transformation.py
View file

@ -1,6 +1,5 @@
import os
import sys
from unittest.mock import AsyncMock, patch
import pytest
@ -47,67 +46,26 @@ def test_map_openai_params():
assert "response_format" in result
@pytest.mark.asyncio
async def test_llama_api_streaming_no_307_error():
"""Test that streaming works without 307 redirect errors due to follow_redirects=True"""
def test_llama_api_streaming_no_307_error():
"""
Test that the OpenAI-compatible httpx clients use follow_redirects=True.
# Mock the httpx client to simulate a successful streaming response
with patch(
"litellm.llms.custom_httpx.http_handler.get_async_httpx_client"
) as mock_get_client:
# Create a mock client
mock_client = AsyncMock()
mock_get_client.return_value = mock_client
meta_llama routes through the OpenAI SDK path (BaseOpenAILLM), so the
follow_redirects setting on that SDK's underlying httpx client is what
actually prevents 307 redirect errors for LLaMA API streaming.
"""
from litellm.llms.openai.common_utils import BaseOpenAILLM
# Mock a successful streaming response (not a 307 redirect)
mock_response = AsyncMock()
mock_response.status_code = 200
mock_response.headers = {"content-type": "text/plain; charset=utf-8"}
# Verify the async httpx client has follow_redirects enabled
async_client = BaseOpenAILLM._get_async_http_client()
assert async_client is not None
assert (
async_client.follow_redirects is True
), "Async httpx client should set follow_redirects=True to prevent 307 errors"
# Mock streaming data that would come from a successful request
async def mock_aiter_lines():
yield 'data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"meta_llama/Llama-4-Maverick-17B-128E-Instruct-FP8","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello"},"finish_reason":null}]}'
yield 'data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"meta_llama/Llama-4-Maverick-17B-128E-Instruct-FP8","choices":[{"index":0,"delta":{"content":" there"},"finish_reason":null}]}'
yield 'data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"meta_llama/Llama-4-Maverick-17B-128E-Instruct-FP8","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}'
yield "data: [DONE]"
mock_response.aiter_lines.return_value = mock_aiter_lines()
mock_client.stream.return_value.__aenter__.return_value = mock_response
# Test the streaming completion
try:
response = await litellm.acompletion(
model="meta_llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
messages=[{"role": "user", "content": "Tell me about yourself"}],
stream=True,
temperature=0.0,
)
# Verify we get a CustomStreamWrapper (streaming response)
from litellm.utils import CustomStreamWrapper
assert isinstance(response, CustomStreamWrapper)
# Verify the HTTP client was called with follow_redirects=True
mock_client.stream.assert_called_once()
call_kwargs = mock_client.stream.call_args[1]
assert (
call_kwargs.get("follow_redirects") is True
), "follow_redirects should be True to prevent 307 errors"
# Verify the response status is 200 (not 307)
assert (
mock_response.status_code == 200
), "Should get 200 response, not 307 redirect"
except Exception as e:
# If there's an exception, make sure it's not a 307 error
error_str = str(e)
assert (
"307" not in error_str
), f"Should not get 307 redirect error: {error_str}"
# Still verify that follow_redirects was set correctly
if mock_client.stream.called:
call_kwargs = mock_client.stream.call_args[1]
assert call_kwargs.get("follow_redirects") is True
# Verify the sync httpx client has follow_redirects enabled
sync_client = BaseOpenAILLM._get_sync_http_client()
assert sync_client is not None
assert (
sync_client.follow_redirects is True
), "Sync httpx client should set follow_redirects=True to prevent 307 errors"

16
tests/test_litellm/llms/publicai/test_publicai_chat_transformation.py
View file

@ -7,6 +7,7 @@ PublicAI is an OpenAI-compatible provider with minor customizations.
import os
import sys
from unittest.mock import patch
sys.path.insert(
0, os.path.abspath("../../../../..")
@ -51,9 +52,13 @@ class TestPublicAIConfig:
assert result["Authorization"] == f"Bearer {api_key}"
assert result["Content-Type"] == "application/json"
def test_get_supported_openai_params(self, config):
@patch("litellm.utils.supports_function_calling", return_value=True)
def test_get_supported_openai_params(self, mock_supports_fc, config):
"""
Test that get_supported_openai_params returns correct params
Test that get_supported_openai_params returns correct params.
We mock supports_function_calling because the test model name
'swiss-ai-apertus' is not in the model registry; this test validates
config behaviour, not registry lookups.
"""
supported_params = config.get_supported_openai_params(model="swiss-ai-apertus")
@ -66,9 +71,12 @@ class TestPublicAIConfig:
# Note: JSON-based configs inherit from OpenAIGPTConfig which includes functions
# This is expected behavior for JSON-based providers
def test_map_openai_params_includes_functions(self, config):
@patch("litellm.utils.supports_function_calling", return_value=True)
def test_map_openai_params_includes_functions(self, mock_supports_fc, config):
"""
Test that functions parameter is mapped (JSON-based configs don't exclude functions)
Test that functions parameter is mapped (JSON-based configs don't exclude functions).
We mock supports_function_calling because the test model name
'swiss-ai-apertus' is not in the model registry.
"""
non_default_params = {
"functions": [{"name": "test_function", "description": "Test function"}],

12
tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_transformation.py
View file

@ -22,6 +22,8 @@ class TestVertexAIRerankTransform:
"GOOGLE_APPLICATION_CREDENTIALS",
"GOOGLE_CLOUD_PROJECT",
"VERTEXAI_PROJECT",
"VERTEXAI_CREDENTIALS",
"VERTEX_AI_CREDENTIALS",
"VERTEX_PROJECT",
"VERTEX_LOCATION",
"VERTEX_AI_PROJECT",
@ -471,16 +473,20 @@ class TestVertexAIRerankTransform:
}
assert headers == expected_headers
@patch('litellm.llms.vertex_ai.rerank.transformation.VertexAIRerankConfig._ensure_access_token')
def test_validate_environment_preserves_optional_params_for_get_complete_url(
self,
mock_ensure_access_token,
):
"""
Validate that calling validate_environment does not remove vertex-specific
parameters needed later by get_complete_url.
Uses instance-level mocking to avoid class-reference issues caused by
importlib.reload(litellm) in conftest.py.
"""
mock_ensure_access_token.return_value = ("test-access-token", "project-from-token")
mock_ensure_access_token = MagicMock(
return_value=("test-access-token", "project-from-token")
)
self.config._ensure_access_token = mock_ensure_access_token
optional_params = {
"vertex_credentials": "path/to/credentials.json",

36
tests/test_litellm/proxy/test_proxy_cli.py
View file

@ -446,8 +446,24 @@ class TestProxyInitializationHelpers:
mock_proxy_config_instance.get_config = mock_get_config
mock_proxy_config.return_value = mock_proxy_config_instance
# Ensure DATABASE_URL is not set in the environment
with patch.dict(os.environ, {"DATABASE_URL": ""}, clear=True):
mock_proxy_server_module = MagicMock(app=mock_app)
# Only remove DATABASE_URL and DIRECT_URL to prevent the database setup
# code path from running. Do NOT use clear=True as it removes PATH, HOME,
# etc., which causes imports inside run_server to break in CI (the real
# litellm.proxy.proxy_server import at line 820 of proxy_cli.py has heavy
# side effects that fail without a proper environment).
env_overrides = {
"DATABASE_URL": "",
"DIRECT_URL": "",
"IAM_TOKEN_DB_AUTH": "",
"USE_AWS_KMS": "",
}
with patch.dict(os.environ, env_overrides):
# Remove DATABASE_URL entirely so the DB setup block is skipped
os.environ.pop("DATABASE_URL", None)
os.environ.pop("DIRECT_URL", None)
with patch.dict(
"sys.modules",
{
@ -456,7 +472,11 @@ class TestProxyInitializationHelpers:
ProxyConfig=mock_proxy_config,
KeyManagementSettings=mock_key_mgmt,
save_worker_config=mock_save_worker_config,
)
),
# Also mock litellm.proxy.proxy_server to prevent the real
# import at line 820 of proxy_cli.py which has heavy side
# effects (FastAPI app init, logging setup, etc.)
"litellm.proxy.proxy_server": mock_proxy_server_module,
},
), patch(
"litellm.proxy.proxy_cli.ProxyInitializationHelpers._get_default_unvicorn_init_args"
@ -470,7 +490,10 @@ class TestProxyInitializationHelpers:
# Test with no config parameter (config=None)
result = runner.invoke(run_server, ["--local"])
assert result.exit_code == 0
assert result.exit_code == 0, (
f"run_server failed with exit_code={result.exit_code}, "
f"output={result.output}, exception={result.exception}"
)
# Verify that uvicorn.run was called
mock_uvicorn_run.assert_called_once()
@ -481,7 +504,10 @@ class TestProxyInitializationHelpers:
# Test with explicit --config None (should behave the same)
result = runner.invoke(run_server, ["--local", "--config", "None"])
assert result.exit_code == 0
assert result.exit_code == 0, (
f"run_server failed with exit_code={result.exit_code}, "
f"output={result.output}, exception={result.exception}"
)
# Verify that uvicorn.run was called again
mock_uvicorn_run.assert_called_once()