1994f9d4c4
**Purpose** Allow arbitrary `extra_body` parameters (e.g. `cached_content`) to be forwarded into the LiteLLM call. Useful for context caching in Gemini models ([docs](https://ai.google.dev/gemini-api/docs/caching?lang=python)). **Example usage** ```python import os from agents import Agent, ModelSettings from agents.extensions.models.litellm_model import LitellmModel cache_name = "cachedContents/34jopukfx5di" # previously stored context gemini_model = LitellmModel( model="gemini/gemini-1.5-flash-002", api_key=os.getenv("GOOGLE_API_KEY") ) agent = Agent( name="Cached Gemini Agent", model=gemini_model, model_settings=ModelSettings( extra_body={"cached_content": cache_name} ) )
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
import litellm
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import pytest
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from litellm.types.utils import Choices, Message, ModelResponse, Usage
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from agents.extensions.models.litellm_model import LitellmModel
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from agents.model_settings import ModelSettings
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from agents.models.interface import ModelTracing
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@pytest.mark.allow_call_model_methods
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@pytest.mark.asyncio
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async def test_extra_body_is_forwarded(monkeypatch):
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"""
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Forward `extra_body` entries into litellm.acompletion kwargs.
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This ensures that user-provided parameters (e.g. cached_content)
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arrive alongside default arguments.
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"""
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captured: dict[str, object] = {}
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async def fake_acompletion(model, messages=None, **kwargs):
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captured.update(kwargs)
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msg = Message(role="assistant", content="ok")
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choice = Choices(index=0, message=msg)
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return ModelResponse(choices=[choice], usage=Usage(0, 0, 0))
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monkeypatch.setattr(litellm, "acompletion", fake_acompletion)
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settings = ModelSettings(
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temperature=0.1,
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extra_body={"cached_content": "some_cache", "foo": 123}
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)
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model = LitellmModel(model="test-model")
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await model.get_response(
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system_instructions=None,
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input=[],
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model_settings=settings,
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tools=[],
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output_schema=None,
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handoffs=[],
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tracing=ModelTracing.DISABLED,
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previous_response_id=None,
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)
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assert {"cached_content": "some_cache", "foo": 123}.items() <= captured.items()
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