Use full media types (image/jpeg, video/mp4, application/pdf) instead of suffixes (jpeg/mp4/pdf) when constructing LiteLLM payloads
This fxes compatibility with providers that validate media types (Anthropic)
Updated and added unit tests to assert full MIME types for image/video/pdf
PiperOrigin-RevId: 800685204
The transcription change breaks the multi-agent transfer during live/bidi.
Updates `GeminiLlmConnection` to populate the `content` field of `LlmResponse` with `types.Content` and `types.Part` objects for both input and output transcriptions, instead of using dedicated transcription fields. Also removes a debug print from `audio_cache_manager.py`.
the transcription is not fully ready to be used yet so roll back the transcription change.
PiperOrigin-RevId: 799851950
Merge https://github.com/google/adk-python/pull/2212
This PR closes issue #2202
ADK was not parsing the required attribute when using LiteLLM, letting the LLM decide what is required vs not, not respecting function definitions.
## Test Plan
There's a fork of adk-python that is being running live for over 2 weeks in our production environment with millions of requests per day.
Below you can find a screenshot of the unit tests passing. I've also added one change to the test cases to cover this scenario
<img width="1904" height="483" alt="image" src="https://github.com/user-attachments/assets/5a6eb069-63ae-45a3-baca-6b01543f56fb" />
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2212 from thiagosalvatore:main 7de4037d8016389313f3fb22df40c12bac578523
PiperOrigin-RevId: 797393698
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
Previous implementation doesn't pass the actual handle to server. Now we cache the handle and pass it over when reconnection happens.
To enable:
run_config = RunConfig(
session_resumption=types.SessionResumptionConfig(transparent=True)
)
PiperOrigin-RevId: 791308462
Please set --log_level to DEBUG, if you are interested in having those API request and responses in logs.
NOTE: Generally it is not recommended to have DEBUG log level for services that run in a production setting. It is our recommendation to only use DEBUG log level in a debug or development setting.
PiperOrigin-RevId: 785972338
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
