Fixes#423
Related to #1670
- This avoids the `GeneratorExit` error thrown, which would crash OTel metric collection and cause `Failed to detach context` error.
- This also allows all function calls are processed when exit_loop is called together with other tools in the same LLmResponse.
A sample agent for testing:
```
from google.adk import Agent
from google.adk.agents.loop_agent import LoopAgent
from google.adk.tools.exit_loop_tool import exit_loop
worker_1 = Agent(
name='worker_1',
description='Worker 1',
instruction="""\
Just say job #1 is done.
If job #1 is said to be done. Call exit_loop tool.""",
tools=[exit_loop],
)
worker_2 = Agent(
name='worker_2',
description='Worker 2',
instruction="""\
Just say job #2 is done.
If job #2 is said to be done. Call exit_loop tool.""",
tools=[exit_loop],
)
work_agent = LoopAgent(
name='work_agent',
description='Do all work.',
sub_agents=[worker_1, worker_2],
max_iterations=5,
)
root_agent = Agent(
model='gemini-2.0-flash',
name='hello_world_agent',
description='hello world agent that can roll a check prime',
instruction="""Hand off works to sub agents.""",
sub_agents=[work_agent],
)
```
PiperOrigin-RevId: 785538101
Merge https://github.com/google/adk-python/pull/1195
## Summary
Updated the Toolbox Agent documentation to address a critical missing dependency that prevents the agent from running successfully.
## Changes Made
- **Added missing dependency**: Documented that `toolbox-core` must be installed via `pip install toolbox-core`
- **Improved documentation structure**: Added clear section numbering and better organization
- **Enhanced readability**: Fixed grammar, capitalization, and formatting throughout
- **Added Prerequisites section**: Set clear expectations before installation begins
- **Clarified optional steps**: Made it clearer when database creation can be skipped
## Problem Solved
The original documentation was missing a crucial step - installing the `toolbox-core` package. Without this dependency, users encounter an `ImportError: No module named 'toolbox-core'` when trying to use the `ToolboxToolset` class in ADK. This fix ensures users can successfully set up and run the agent without encountering import errors.
## Testing
- Verified the installation steps work correctly with the added dependency
- Confirmed the agent runs successfully after following the updated documentation
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/1195 from designcomputer:patch-1 b90c71fe95aa09a3dca069e91f14791f557ab2e3
PiperOrigin-RevId: 785487495
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
Now the LangchainTool can wrap:
* Langchain StructuredTool (sync and async).
* Langchain @Tool (sync and async).
This enhance the flexibility for user and enables async functionalities.
PiperOrigin-RevId: 784728061
