This change introduces a new `analyze_contribution` function in `query_tool.py` which uses BigQuery ML's `CREATE MODEL` with `CONTRIBUTION_ANALYSIS` type and `ML.GET_INSIGHTS` to analyze the contribution of different dimensions to a given metric. The new function is also added to the `bigquery_toolset`.
PiperOrigin-RevId: 815849281
Merge https://github.com/google/adk-python/pull/2823
Description
This change introduces a tool_name_prefix attribute to McpToolset and McpToolsetConfig. This allows for adding a prefix to the
names of all tools within the toolset, which can help avoid naming collisions and provide better organization.
The implementation involves updating the McpToolset's __init__ and from_config methods to handle the new tool_name_prefix and
adding the corresponding field to McpToolsetConfig.
Testing Plan
A new unit test file has been added to ensure the functionality works as expected.
- `tests/unittests/tools/test_mcp_toolset.py`:
- The test_mcp_toolset_with_prefix test case verifies that the tool_name_prefix is correctly applied to the tool names
retrieved from the toolset.
- All tests were run via pytest and passed.
Related Issue
- Closes#2814
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2823 from shsha4:fix/issue-2814 e8e5b0d6d5f406d3875faf2229a96701725b7a5e
PiperOrigin-RevId: 810500616
Similarity search tool supports similarity search on Spanner data by embedding a text query to a vector and run vector search with the embedded vector.
PiperOrigin-RevId: 806502499
Right now the tolls are always running against multi-region US by default. With this change the agent builder can scope the tools to data and compute in a particular BigQuery location.
PiperOrigin-RevId: 806473857
This will allow restricting BigQuery SQL executions to the specified project. The agent/LLM should resolve the `project_id` param for tools like `execute_sql` and sometimes they can resolve it to an unexpected value due to hallucination or ambiguity. This guardrail will protect against that situation.
PiperOrigin-RevId: 801039685
The existing `LongRunningTool` does not define a programmatic way to provide & validate structured input, also it relies on LLM to reason and parse the user's response.
For a quick start, annotate the function with `FunctionTool(my_function, require_confirmation=True)`. A more advanced flow is shown in the `human_tool_confirmation` sample.
The new flow is similar to the existing Auth flow:
- User request a tool confirmation by calling `tool_context.request_confirmation()` in the tool or `before_tool_callback`, or just using the `require_confirmation` shortcut in FunctionTool.
- User can provide custom validation logic before tool call proceeds.
- ADK creates corresponding RequestConfirmation FunctionCall Event to ask user for confirmation
- User needs to provide the expected tool confirmation to a RequestConfirmation FunctionResponse Event.
- ADK then checks the response and continues the tool call.
PiperOrigin-RevId: 801019917
This can help to provide more context and information about the table, like parent-child relationship, and row deletion policy etc.
PiperOrigin-RevId: 797562858
