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fix(docs): correct Docker image tag in v1.82.0 release notes (#23537)

Browse source 
* bump: version 1.82.1 → 1.82.2

* fix(gemini): preserve toolConfig on native generate_content (#23493)

* chore: regenerate poetry.lock to match pyproject.toml (#23514)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* fix(docs): correct Docker image tag in v1.82.0 release notes

Add missing 'v' prefix to Docker image tag: main-1.82.0-stable → main-v1.82.0-stable

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: yuneng-jiang <yuneng.jiang@gmail.com>
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Prafulla Anurag 2026-03-13 23:39:19 +05:30 • committed by GitHub
parent 976f1a0115
commit 43db397854
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GPG key ID: B5690EEEBB952194
11 changed files with 108 additions and 27 deletions
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2
docs/my-website/release_notes/v1.82.0.md
View file

@ -26,7 +26,7 @@ import TabItem from '@theme/TabItem';
docker run \
-e STORE_MODEL_IN_DB=True \
-p 4000:4000 \
ghcr.io/berriai/litellm:main-1.82.0-stable
ghcr.io/berriai/litellm:main-v1.82.0-stable
```
</TabItem>

21
litellm/google_genai/main.py
View file

@ -39,6 +39,15 @@ base_llm_http_handler = BaseLLMHTTPHandler()
#################################################
def _get_tool_config_from_kwargs(kwargs: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Read toolConfig/tool_config without dropping intentionally empty dicts."""
if "toolConfig" in kwargs:
return kwargs["toolConfig"]
if "tool_config" in kwargs:
return kwargs["tool_config"]
return None
class GenerateContentSetupResult(BaseModel):
"""Internal Type - Result of setting up a generate content call"""
@ -171,12 +180,14 @@ class GenerateContentHelper:
system_instruction = kwargs.get("systemInstruction") or kwargs.get(
"system_instruction"
)
tool_config = _get_tool_config_from_kwargs(kwargs)
request_body = (
generate_content_provider_config.transform_generate_content_request(
model=model,
contents=contents,
tools=tools,
generate_content_config_dict=generate_content_config_dict,
tool_config=tool_config,
system_instruction=system_instruction,
)
)
@ -323,6 +334,7 @@ def generate_content(
system_instruction = kwargs.get("systemInstruction") or kwargs.get(
"system_instruction"
)
tool_config = _get_tool_config_from_kwargs(kwargs)
# Check if we should use the adapter (when provider config is None)
if setup_result.generate_content_provider_config is None:
@ -354,6 +366,7 @@ def generate_content(
_is_async=_is_async,
client=kwargs.get("client"),
litellm_metadata=kwargs.get("litellm_metadata", {}),
tool_config=tool_config,
system_instruction=system_instruction,
)
@ -414,6 +427,7 @@ async def agenerate_content_stream(
system_instruction = kwargs.get("systemInstruction") or kwargs.get(
"system_instruction"
)
tool_config = _get_tool_config_from_kwargs(kwargs)
# Check if we should use the adapter (when provider config is None)
if setup_result.generate_content_provider_config is None:
@ -452,6 +466,7 @@ async def agenerate_content_stream(
client=kwargs.get("client"),
stream=True,
litellm_metadata=kwargs.get("litellm_metadata", {}),
tool_config=tool_config,
system_instruction=system_instruction,
)
@ -520,6 +535,10 @@ def generate_content_stream(
)
# Call the handler with streaming enabled (sync version)
system_instruction = kwargs.get("systemInstruction") or kwargs.get(
"system_instruction"
)
tool_config = _get_tool_config_from_kwargs(kwargs)
return base_llm_http_handler.generate_content_handler(
model=setup_result.model,
contents=contents,
@ -536,6 +555,8 @@ def generate_content_stream(
client=kwargs.get("client"),
stream=True,
litellm_metadata=kwargs.get("litellm_metadata", {}),
tool_config=tool_config,
system_instruction=system_instruction,
)
except Exception as e:

2
litellm/llms/base_llm/google_genai/transformation.py
View file

@ -152,6 +152,7 @@ class BaseGoogleGenAIGenerateContentConfig(ABC):
contents: GenerateContentContentListUnionDict,
tools: Optional[ToolConfigDict],
generate_content_config_dict: Dict,
tool_config: Optional[Dict[str, Any]] = None,
system_instruction: Optional[Any] = None,
) -> dict:
"""
@ -161,6 +162,7 @@ class BaseGoogleGenAIGenerateContentConfig(ABC):
model: The model name
contents: Input contents
tools: Tools
tool_config: Tool configuration
generate_content_config_dict: Generation config parameters
system_instruction: Optional system instruction

5
litellm/llms/custom_httpx/llm_http_handler.py
View file

@ -9329,6 +9329,7 @@ class BaseLLMHTTPHandler:
client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
stream: bool = False,
litellm_metadata: Optional[Dict[str, Any]] = None,
tool_config: Optional[Dict[str, Any]] = None,
system_instruction: Optional[Any] = None,
) -> Any:
"""
@ -9346,6 +9347,7 @@ class BaseLLMHTTPHandler:
generate_content_provider_config=generate_content_provider_config,
generate_content_config_dict=generate_content_config_dict,
tools=tools,
tool_config=tool_config,
custom_llm_provider=custom_llm_provider,
litellm_params=litellm_params,
logging_obj=logging_obj,
@ -9384,6 +9386,7 @@ class BaseLLMHTTPHandler:
model=model,
contents=contents,
tools=tools,
tool_config=tool_config,
generate_content_config_dict=generate_content_config_dict,
system_instruction=system_instruction,
)
@ -9456,6 +9459,7 @@ class BaseLLMHTTPHandler:
client: Optional[AsyncHTTPHandler] = None,
stream: bool = False,
litellm_metadata: Optional[Dict[str, Any]] = None,
tool_config: Optional[Dict[str, Any]] = None,
system_instruction: Optional[Any] = None,
) -> Any:
"""
@ -9493,6 +9497,7 @@ class BaseLLMHTTPHandler:
model=model,
contents=contents,
tools=tools,
tool_config=tool_config,
generate_content_config_dict=generate_content_config_dict,
system_instruction=system_instruction,
)

3
litellm/llms/gemini/google_genai/transformation.py
View file

@ -308,6 +308,7 @@ class GoogleGenAIConfig(BaseGoogleGenAIGenerateContentConfig, VertexLLM):
contents: GenerateContentContentListUnionDict,
tools: Optional[ToolConfigDict],
generate_content_config_dict: Dict,
tool_config: Optional[Dict[str, Any]] = None,
system_instruction: Optional[Any] = None,
) -> dict:
from litellm.types.google_genai.main import (
@ -326,6 +327,8 @@ class GoogleGenAIConfig(BaseGoogleGenAIGenerateContentConfig, VertexLLM):
if system_instruction is not None:
request_dict["systemInstruction"] = system_instruction
if tool_config is not None:
request_dict["toolConfig"] = tool_config
return request_dict
def transform_generate_content_response(

6
litellm/llms/vertex_ai/google_genai/transformation.py
View file

@ -73,6 +73,7 @@ class VertexAIGoogleGenAIConfig(GoogleGenAIConfig):
contents: Any,
tools: Optional[Any],
generate_content_config_dict: Dict,
tool_config: Optional[Dict[str, Any]] = None,
system_instruction: Optional[Any] = None,
) -> dict:
"""
@ -89,8 +90,11 @@ class VertexAIGoogleGenAIConfig(GoogleGenAIConfig):
if tools:
result["tools"] = tools
if tool_config is not None:
result["toolConfig"] = tool_config
# Add systemInstruction if provided
if system_instruction:
if system_instruction is not None:
result["systemInstruction"] = system_instruction
# Handle generationConfig - Vertex AI expects it in the same format

8
poetry.lock generated
View file

@ -3222,15 +3222,15 @@ files = [
[[package]]
name = "litellm-proxy-extras"
version = "0.4.54"
version = "0.4.56"
description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package."
optional = true
python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
groups = ["main"]
markers = "extra == \"proxy\""
files = [
{file = "litellm_proxy_extras-0.4.54-py3-none-any.whl", hash = "sha256:6621cf529f7f3647eb2dd0d2c417d91db8c7a05c3c592bef251887a122928837"},
{file = "litellm_proxy_extras-0.4.54.tar.gz", hash = "sha256:2c777ecdf39901c4007ade4466eb6398985ed4000afe3fc2cac997e1169e8cee"},
{file = "litellm_proxy_extras-0.4.56-py3-none-any.whl", hash = "sha256:52dbe3b5358c790e77e12f1ec5ef8e7508b383c2aaf41299750b6fb400908ee7"},
{file = "litellm_proxy_extras-0.4.56.tar.gz", hash = "sha256:63ad59baa0defccc5c929cfd933ee7e32a6614b0fc5fa0fc45a12d7608e33f08"},
]
[[package]]
@ -8002,4 +8002,4 @@ utils = ["numpydoc"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.9,<4.0"
content-hash = "5ed0af4e3644bc7b5a02b8bfc8b3eda15c014b43aa6da7a9a97a9b070fba5366"
content-hash = "1ade5dee030fd878c907a20b88a6a52ca26ee4ecbed15ecb045f9ae1d4b8b714"

4
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm"
version = "1.82.1"
version = "1.82.2"
description = "Library to easily interface with LLM API providers"
authors = ["BerriAI"]
license = "MIT"
@ -183,7 +183,7 @@ requires = ["poetry-core", "wheel"]
build-backend = "poetry.core.masonry.api"
[tool.commitizen]
version = "1.82.1"
version = "1.82.2"
version_files = [
"pyproject.toml:^version"
]

3
tests/proxy_unit_tests/test_google_gemini_proxy_request.py
View file

@ -174,6 +174,7 @@ async def test_google_gemini_httpx_request_direct():
],
"role": "user"
},
"toolConfig": {"functionCallingConfig": {"mode": "ANY"}},
"config": { # Note: already transformed from generationConfig
"temperature": 0,
"topP": 1,
@ -240,6 +241,7 @@ async def test_google_gemini_httpx_request_direct():
generate_content_provider_config=provider_config,
generate_content_config_dict=sample_payload["config"],
tools=None,
tool_config=sample_payload["toolConfig"],
custom_llm_provider="gemini",
litellm_params=litellm_params,
logging_obj=logging_obj,
@ -265,6 +267,7 @@ async def test_google_gemini_httpx_request_direct():
request_data = call_kwargs.get('json')
if request_data:
assert 'contents' in request_data, "Expected 'contents' in request data"
assert request_data["toolConfig"] == sample_payload["toolConfig"]
# The config should be included in the request as generationConfig
if 'generationConfig' in request_data:

55
tests/test_litellm/google_genai/test_google_genai_main.py
View file

@ -1,24 +1,13 @@
#!/usr/bin/env python3
"""
Test to verify the Google GenAI generate_content adapter functionality
"""
import json
"""Tests for Google GenAI main entrypoints."""
import os
import sys
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
sys.path.insert(
0, os.path.abspath("../../..")
) # Adds the parent directory to the system path
import json
import os
import sys
import pytest
import litellm
sys.path.insert(0, os.path.abspath("../../.."))
@pytest.mark.asyncio
@ -26,8 +15,6 @@ async def test_agenerate_content_stream():
"""
Test that the agenerate_content_stream function works
"""
from unittest.mock import AsyncMock, patch
from litellm.google_genai.main import (
agenerate_content_stream,
base_llm_http_handler,
@ -36,10 +23,40 @@ async def test_agenerate_content_stream():
with patch.object(
base_llm_http_handler, "generate_content_handler", new=AsyncMock()
) as mock_post:
result = await agenerate_content_stream(
await agenerate_content_stream(
model="gemini/gemini-2.0-flash-001",
contents="Hello, world!",
stream=True,
)
mock_post.assert_called_once()
mock_post.call_args.kwargs["stream"] == True
assert mock_post.call_args.kwargs["stream"] is True
def test_generate_content_stream_forwards_system_instruction():
"""Test that generate_content_stream forwards systemInstruction and toolConfig."""
from litellm.google_genai.main import (
base_llm_http_handler,
generate_content_stream,
)
mock_response = MagicMock()
tool_config = {"functionCallingConfig": {"mode": "ANY"}}
with patch.object(
base_llm_http_handler, "generate_content_handler", return_value=mock_response
) as mock_post:
result = generate_content_stream(
model="gemini/gemini-2.0-flash-001",
contents="Hello, world!",
stream=True,
systemInstruction={"parts": [{"text": "You are helpful"}]},
toolConfig=tool_config,
)
assert result is mock_response
mock_post.assert_called_once()
assert mock_post.call_args.kwargs["stream"] is True
assert mock_post.call_args.kwargs["tool_config"] == tool_config
assert mock_post.call_args.kwargs["system_instruction"] == {
"parts": [{"text": "You are helpful"}]
}

26
tests/test_litellm/google_genai/test_google_genai_transformation.py
View file

@ -12,6 +12,9 @@ sys.path.insert(
import pytest
from litellm.llms.gemini.google_genai.transformation import GoogleGenAIConfig
from litellm.llms.vertex_ai.google_genai.transformation import (
VertexAIGoogleGenAIConfig,
)
from litellm.responses.litellm_completion_transformation.transformation import (
LiteLLMCompletionResponsesConfig,
)
@ -173,6 +176,26 @@ def test_map_generate_content_optional_params_response_mime_type():
assert "responseJsonSchema" in result
@pytest.mark.parametrize(
"config_cls",
[GoogleGenAIConfig, VertexAIGoogleGenAIConfig],
)
def test_transform_generate_content_request_preserves_tool_config(config_cls):
config = config_cls()
tool_config = {"functionCallingConfig": {"mode": "ANY"}}
result = config.transform_generate_content_request(
model="gemini-3-flash-preview",
contents=[{"role": "user", "parts": [{"text": "hello"}]}],
tools=[{"functionDeclarations": [{"name": "execute_command"}]}],
tool_config=tool_config,
generate_content_config_dict={"temperature": 1},
system_instruction={"parts": [{"text": "system"}]},
)
assert result["toolConfig"] == tool_config
def test_responses_api_reasoning_dict_format():
"""Test that reasoning parameter with dict format is mapped to reasoning_effort"""
from litellm.types.llms.openai import ResponsesAPIOptionalRequestParams
@ -274,6 +297,7 @@ def test_transform_generate_content_request_with_system_instruction():
model="gemini-3-flash-preview",
contents=contents,
tools=None,
tool_config=None,
generate_content_config_dict=generate_content_config_dict,
system_instruction=system_instruction,
)
@ -305,6 +329,7 @@ def test_transform_generate_content_request_without_system_instruction():
model="gemini-3-flash-preview",
contents=contents,
tools=None,
tool_config=None,
generate_content_config_dict=generate_content_config_dict,
system_instruction=None,
)
@ -356,6 +381,7 @@ def test_transform_generate_content_request_system_instruction_with_tools():
model="gemini-3-flash-preview",
contents=contents,
tools=tools,
tool_config=None,
generate_content_config_dict=generate_content_config_dict,
system_instruction=system_instruction,
)