For Vertex model backend, we send response back. This doesn't work for streaming tools that the return type is AsyncGenerator. So the fix here is to ignore the return type when it's AsyncGenerator.
We can't distinguish streaming vs non-streaming tool with AsyncGenerator though as LiveRequestQueue is optional in streaming tool.
Adds an `ignore_response` option to `build_function_declaration` to skip including the return type in the function declaration. This is enabled for tools that return `AsyncGenerator`, as the model does not yet support understanding these return types, while streaming tools can still handle them. Also, removes redundant return statements in `_get_mandatory_params`.
PiperOrigin-RevId: 794392846
Mainly it's due to GenAI sdk changed their header of genai SDK versions, we have UT to verify that ADK or ADK users won't override their headers. Updated the header accordingly in the UT.
PiperOrigin-RevId: 786334741
Merge https://github.com/google/adk-python/pull/1130
This enables the use of the `model-optimizer-*` family of models in vertex, as per the [documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/vertex-ai-model-optimizer#using-vertex-ai-model-optimizer).
To use this, ensure your location is set to `global` and pass a model optimizer model to an agent:
```python
root_agent = Agent(
model="model-optimizer-exp-04-09",
name="fast_and_slow_agent",
instruction="Answer any question the user gives you - easy or hard.",
generate_content_config=types.GenerateContentConfig(
temperature=0.01,
model_selection_config=ModelSelectionConfig(
feature_selection_preference=FeatureSelectionPreference.BALANCED
# Options: PRIORITIZE_QUALITY, BALANCED, PRIORITIZE_COST
)
),
)
```
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/1130 from calvingiles:feat-model-optimizer 1a76bfa22420edb07d83415dcea6dd0114084e8e
PiperOrigin-RevId: 784921913
- Allow run_async to break on partial events instead of raising ValueError
- Generate aggregated streaming content regardless of finish_reason
- Add error_code and error_message to final streaming responses if model response is interrupted.
PiperOrigin-RevId: 781377328
Merge https://github.com/google/adk-python/pull/1451
## Description
Fixes https://github.com/google/adk-python/issues/1306 by using `async for` with `await self.llm_client.acompletion()` instead of synchronous `for` loop.
## Changes
- Updated test mocks to properly handle async streaming by creating an async generator
- Ensured proper parameter handling to avoid duplicate stream parameter
## Testing Plan
- All unit tests now pass with the async streaming implementation
- Verified with `pytest tests/unittests/models/test_litellm.py` that all streaming tests pass
- Manually tested with a sample agent using LiteLLM to confirm streaming works properly
# Test Evidence:
https://youtu.be/hSp3otI79DM
Let me know if you need anything else from me for this PR
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/1451 from avidelatm:fix/litellm-async-streaming d35b9dc90b2fd6fad44c3869de0fda2514e50055
PiperOrigin-RevId: 774835130
#non-breaking
The correct conversion from 25 degrees Celsius is 77 degrees Fahrenheit. The previous value of 41 was wrong.
PiperOrigin-RevId: 772528757
