This enables to re-use the ADK web interface in other contexts more easily.
For example, when having an own run-time the web interface can be exposed
for visualization during development.
Also add documentation for function.
PiperOrigin-RevId: 868848338
Adds a logger.exception call to capture traceback and error details when an exception occurs during the execution of a coroutine within an MCP session, before re-raising it as a ConnectionError.
PiperOrigin-RevId: 868253547
This CL enhances asyncio event loop management and test isolation.
- **BigQuery Analytics Plugin:** Ensure the asyncio event loop is consistently closed within the BigQuery analytics plugin. This prevents potential resource leaks. Add checks to handle potential deadlocks in Python 3.13+ when creating loops during interpreter shutdown.
- **Test Thread Pool Cleanup:** Introduce a pytest fixture (`cleanup_thread_pools`) to automatically shut down and clear all tool-related thread pools after each test run in `test_functions_thread_pool.py`. This improves test isolation and prevents order-dependent test failures.
- **Streaming Test Loop Restoration:** Refactor event loop handling in `test_streaming.py`. A new `_run_with_loop` method is introduced in the custom test runners to create a temporary event loop for each test execution, run the coroutine, and crucially, restore the original event loop afterwards. This prevents tests from interfering with each other's loop state.
- **Resource Closure:** Ensure services are closed properly in tests by adding `await service.close()` in `test_service_factory.py` and using `async with session_service` in `test_session_service.py`.
PiperOrigin-RevId: 863305565
Improves test reliability by guaranteeing the BigQueryAgentAnalyticsPlugin is shut down after each test execution. This is achieved by wrapping test logic in try/finally blocks, using a yield fixture, or employing a new asynccontextmanager to ensure the plugin.shutdown() method is always called, preventing potential resource leaks between tests.
PiperOrigin-RevId: 862951816
This change updates the feature request issue template to include required and recommended sections. New questions are added to gather more details on the problem, impact, willingness to contribute, and potential API/implementation ideas. Existing questions are rephrased for clarity
PiperOrigin-RevId: 860199885
This change introduces a `flush` method to the `BigQueryAgentAnalyticsPlugin`. This ensures that all pending log events are written to BigQuery before the agent's run completes.
Key changes:
- Added `flush()` method to `BigQueryAgentAnalyticsPlugin` to force write of pending events.
PiperOrigin-RevId: 859263853
Bug: In live streaming mode, when function_call and function_response events
arrive during active transcription, they are correctly buffered but never
yielded to the caller. This causes callers to miss these events even though
they are saved to the session.
Fix: Add yield buffered_event after appending buffered events to the session
when transcription ends.
Testing:
- Added unit test: test_live_streaming_buffered_function_call_yielded_during_transcription
- Test verifies buffered events are yielded by:
1. Simulating partial transcription (triggers buffering)
2. Sending function_call during transcription (gets buffered)
3. Ending transcription (should yield buffered events)
4. Asserting both function_call and function_response are in yielded events
Test results:
- With fix: PASSED
- Without fix (yield commented out): FAILED with "Buffered function_call event was not yielded"
- Example event flow after fix:
EVENT: partial=True, input_transcription="Show me the weather"
EVENT: function_call=get_weather, args={'location': 'NYC'} <- Now yielded
EVENT: function_response=get_weather, response={...} <- Now yielded
EVENT: partial=False, input_transcription="Show me the weather for today"
PiperOrigin-RevId: 859158546
This refactors the BigQueryAgentAnalyticsPlugin to use the standard OpenTelemetry API for trace and span ID generation and propagation, replacing the custom ContextVar implementation.
Key changes:
- Utilizes `opentelemetry.trace` for starting/ending spans.
- Correctly uses `opentelemetry.context` for context attachment and detachment.
- Span information is now derived from the OpenTelemetry context when available.
- Added a fallback mechanism to ensure span_id and parent_span_id are still populated if the OpenTelemetry SDK is not initialized.
To get standard OpenTelemetry trace information in BigQuery logs, users should install `opentelemetry-sdk` and initialize a global `TracerProvider` in their application *before* initializing ADK components.
Example minimal initialization:
```python
# Install: pip install opentelemetry-sdk
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
trace.set_tracer_provider(TracerProvider())
```
PiperOrigin-RevId: 858965562
### Description of Change
**Problem:**
The `ToolboxToolset` was relying on the legacy `toolbox-core` package. Users wanting to use the Toolbox features were forced to install the heavy `[extensions]` group, lacking a granular installation option. Additionally, `ToolboxToolset` had a validation check enforcing either `toolset_name` or `tool_names` to be present, preventing the default behavior of loading all tools (which `toolbox-adk` supports).
**Solution:**
* Refactored `ToolboxToolset` to delegate to `toolbox-adk`.
* Added a new `toolbox` optional dependency group in `pyproject.toml`.
* Users can now run `pip install google-adk[toolbox]` to install only the necessary dependencies.
* Updated the `extensions` dependency group to replace `toolbox-core` with `toolbox-adk`.
* This ensures existing users of `[extensions]` are not broken upon upgrade.
* Removed the restrictive validation check to allow default loading of all tools.
* Updated the `ImportError` message to guide users toward the new granular installation command.
### Testing Plan
**Unit Tests:**
- [x] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
**Manual End-to-End (E2E) Tests:**
- Verified that the sample agent runs correctly with `toolbox-adk` locally.
- Verified that `ToolboxToolset` can now be instantiated without arguments to load all tools.
### Checklist
- [x] I have read the [CONTRIBUTING.md](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) document.
- [x] I have performed a self-review of my own code.
- [x] I have commented my code, particularly in hard-to-understand areas.
- [x] I have added tests that prove my fix is effective or that my feature works.
- [x] New and existing unit tests pass locally with my changes.
- [x] I have manually tested my changes end-to-end.
- [x] Any dependent changes have been merged and published in downstream modules.
PiperOrigin-RevId: 857171811
1. Convert A2A responses containing a DataPart to ADK events. By default, this is done by serializing the DataPart to JSON and embedding it within the inline_data field of a GenAI Part, wrapped with custom tags (<a2a_datapart_json> and </a2a_datapart_json>).
2. Convert ADK events back to A2A requests. Specifically, messages stored in inline_data with the text/plain mime type and content wrapped within the custom tags (<a2a_datapart_json> and </a2a_datapart_json>) are deserialized from JSON back into an A2A DataPart
PiperOrigin-RevId: 856426615
### Description of Change
**Problem:**
The `ToolboxToolset` was implemented directly within `adk-python`, leading to code duplication and potential drift from the core `toolbox-adk` implementation.
**Solution:**
Refactored `ToolboxToolset` to act as a rigorous wrapper around the `toolbox-adk` package, which delegates all functionality to `toolbox_adk.ToolboxToolset`.
### Testing Plan
**Unit Tests:**
- [x] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
Summary:
- Verified initialization flows through to `toolbox-adk`.
- Verified `auth_token_getters` are correctly propagated.
- Verified type hints are static-analysis friendly.
**Manual End-to-End (E2E) Tests:**
Manually verified standard toolbox loading and execution with the new wrapper:
```python
from google.adk.tools import ToolboxToolset
from toolbox_adk import CredentialStrategy
# Loading with toolset_name
ts = ToolboxToolset(
server_url='http://localhost:8080',
toolset_name='calculator',
credentials=CredentialStrategy.toolbox_identity()
)
tools = await ts.get_tools()
print(f'Loaded {len(tools)} tools')
```
### Checklist
- [x] I have read the [CONTRIBUTING.md](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) document.
- [x] I have performed a self-review of my own code.
- [x] I have commented my code, particularly in hard-to-understand areas.
- [x] I have added tests that prove my fix is effective or that my feature works.
- [x] New and existing unit tests pass locally with my changes.
- [x] I have manually tested my changes end-to-end.
- [x] Any dependent changes have been merged and published in downstream modules.
PiperOrigin-RevId: 855798474
* **Async Safety:** Improved TraceManager context variable handling to ensure correct context isolation in concurrent asynchronous operations. This was achieved by using immutable tuples for the span stack and making copies of context dictionaries before modification.
* **Enhanced Logging:** The BigQueryAgentAnalyticsPlugin now captures richer metadata, including:
* Root agent name (via a new context variable).
* LLM model name and version.
* Usage metadata from LLM requests and responses.
* **Serialization Fix:** Updated BigQueryAgentAnalyticsPlugin to prevent JSON serialization errors when logging custom objects (e.g., Dataclasses). These are now automatically converted to dictionaries or string representations to ensure successful insertion into BigQuery.
PiperOrigin-RevId: 855415320
Introduces `full_history_when_stateless` to RemoteA2aAgent. When True, stateless agents will receive all session events on each request, instead of only events since their last reply. This allows stateless agents to have access to the complete conversation history.
PiperOrigin-RevId: 854400798
These changes add extra hint for the LLM in the `execute_tool` SQL examples to always use back-ticks around BQ project, dataset and table names in the generated SQL, to save the SQL parsing error when the name has special characters.
PiperOrigin-RevId: 852418943
Previously, the warning check occurred after "plugins" could be populated from "app.plugins". This caused the deprecation warning to trigger incorrectly even when plugins were properly provided via the app argument. Moving the check ensures it only triggers when the deprecated plugins argument is explicitly used.
The change also enhanced the condition that would trigger the warning to cover the empty list case.
PiperOrigin-RevId: 845746847
Performance: Switched to BigQuery Storage Write API with async batching, reducing agent latency.
Multimodal: Native support for GCS offloading (ObjectRef) for images, video, and large text.
Reliability: Added connection pooling, retries, and a "rescue flush" for safe shutdown on Cloud Run.
Observability: Fixed distributed tracing hierarchy with ContextVars support.
PiperOrigin-RevId: 843062561
Add using the execute sql query return result as list of dictionaries.
In each dictionary the key is the column name and the value is the value of
the that column in a given row.
PiperOrigin-RevId: 840909555
The RemoteA2aAgent now extracts a "task_id" from the custom metadata of the last agent event in the session, alongside the existing "context_id". This task_id is then included in the A2AMessage sent to the remote A2A service.
Close#3765
PiperOrigin-RevId: 840375992
The vector_store_similarity_search tool performs similarity search against data in a Spanner vector store table, using the provided Spanner tool settings for configuration.
PiperOrigin-RevId: 839352057
This change will help the tools user identify per agent job usage in BQ console and INFORMATION_SCHEMA views. This change fulfills the feature request #3582. Here is a demo after change: screen/C6YB4ge2FM2ZREi.
PiperOrigin-RevId: 834480140
This update enhances the BigQuery agent analytics plugin:
* **Schema Field Descriptions:** The recommended BigQuery table schema now includes descriptions for each field, improving data understandability.
* **Optimized Table Structure:** The plugin now creates the table with daily partitioning on `timestamp` and clustering on `event_type`, `agent`, and `user_id` by default.
* **Truncation Flag:** A new boolean field `is_truncated` is added to the schema to show if the `content` was truncated.
PiperOrigin-RevId: 832436799
Two tools - detect_anomalies and analyze_contribution are modifying the settings passed to them, which is not right as the settings are held and passed by the top level, which means several tools share the same settings.
PiperOrigin-RevId: 832081738
The change adds an extension point for controlling which request metadata gets attached to A2A requests made by a RemoteAgent.
Instead of taking metadata from custom_metadata of session events users can construct payloads using a2a_request_meta_provider.
request_meta feature was added in v0.3.11 of the a2a-sdk library: https://github.com/a2aproject/a2a-python/releases/tag/v0.3.11
PiperOrigin-RevId: 831506364
This is targeting the Client import mostly, but also prevents future latency increase if the other modules in genai adds more 3p dependencies. This change will make ADK only import `live`, `Client` and `_transformers` just-in-time, therefore cutting down cold start latency.
PiperOrigin-RevId: 831244349
This update improves the `BigQueryAgentAnalyticsPlugin` in several ways:
* Corrects the PyArrow schema generation to accurately reflect BigQuery field nullability based on the `mode` attribute.
* Introduces a configurable `shutdown_timeout` in `BigQueryLoggerConfig` to manage how long the plugin waits for pending logs to flush during shutdown.
* Adds more robust error handling within the `shutdown` method and background write tasks, particularly for event loop closure issues.
* Improves internal logging to provide better diagnostics.
* Ensures consistent use of safe content formatting.
PiperOrigin-RevId: 831225837
Retrying only on closed_resource error is not enough to be reliable for production environments due to the other network errors that may occur -- remote protocol error, read timeout, etc. We will update this to retry on all errors. Since it is only a one-time retry, it should not affect latency significantly. Fixes https://github.com/google/adk-python/issues/2561.
PiperOrigin-RevId: 831153803
This change updates `RemoteA2AAgent` to extract and forward custom metadata from session events to the `a2a-sdk`'s `send_message` method. The metadata is looked for under the key `A2A_METADATA_PREFIX + "metadata"` within the `custom_metadata` of the relevant session events. The `a2a-sdk` dependency is also updated to a version that supports this feature.
This feature was added in v0.3.11 of the a2a-sdk library: https://github.com/a2aproject/a2a-python/releases/tag/v0.3.11
PiperOrigin-RevId: 831120978
This change introduces a shutdown lifecycle hook for plugins. The `PluginManager` now has an `async def shutdown()` method that will call `await plugin.shutdown()` on any registered plugins that implement the method. This is called from `Runner.close()`, allowing plugins to perform cleanup tasks like flushing logs or closing connections when the runner instance is being closed. This improves the reliability of plugins that perform background operations.
PiperOrigin-RevId: 831037737
This change updates the `BigQueryAgentAnalyticsPlugin` (formerly in `bigquery_logging_plugin.py`) to perform BigQuery writes asynchronously in background tasks, preventing blocking of the main agent execution flow. Initialization of BigQuery clients and table creation is also made asynchronous. The content logged in various callbacks has been streamlined and simplified. The plugin file has been renamed to `bigquery_agent_analytics_plugin.py` to match the class name.
PiperOrigin-RevId: 829603260
We need to set project and location parameters when we instantiate the Google GenAI library Client for VertexAi. This used to work before through environment variables but it doesn't seem to work anymore. So we are updating the `ApigeeLlm` wrapper to read from `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` environment variables and pass to the Client constructor.
PiperOrigin-RevId: 829569362
This commit refactors the `BigQueryAgentAnalyticsPlugin` to leverage the modern BigQuery Storage Write API, replacing the previous implementation that used the legacy `insert_rows_json` method (based on `tabledata.insertAll`).
**Key Changes:**
* **Switched to Storage Write API:** Event logs are now ingested using the `BigQueryWriteClient` from the `google-cloud-bigquery-storage` library.
* **Utilizes Default Stream:** We are using the `_default` stream for sending data, which is an efficient method for streaming in data without needing to manage stream lifecycles. This is ideal for continuous event logging.
* **Apache Arrow Format:** Log entries are converted to the Apache Arrow format using `pyarrow` before being sent. The BigQuery table schema is dynamically converted to an Arrow schema. This binary format is more efficient than JSON.
* **Updated Initialization:** The plugin now initializes both the standard `bigquery.Client` (for table management) and the `BigQueryWriteClient`.
* **Test Updates:** Unit tests in `test_bigquery_logging_plugin.py` have been comprehensively updated to mock the new `BigQueryWriteClient`, `bq_schema_utils`, and `pyarrow` components. Tests now verify calls to `append_rows` and the data structure passed to create the Arrow RecordBatch.
**Benefits of this change:**
* **Improved Performance:** The Storage Write API is designed for high-throughput streaming and offers better performance compared to the legacy API.
* **Reduced Cost:** Ingesting data via the Storage Write API is generally more cost-effective.
* **Enhanced Reliability:** The Storage Write API provides more robust streaming capabilities.
* **Modernization:** Aligns the plugin with the recommended best practices for BigQuery data ingestion.
This change enhances the efficiency and scalability of the BigQuery logging plugin.
PiperOrigin-RevId: 828655496
This change introduces BigQueryLoggerConfig to allow customization of the BigQueryAgentAnalyticsPlugin. Users can now enable/disable the plugin, specify event type allowlists and denylists, and provide a custom function to format or redact the content field before logging to BigQuery. The content logged for model and tool errors has also been enhanced.
PiperOrigin-RevId: 828172241
ARIMA supports both historical data and future data anomaly detection. This CL add how the tool support future table anomaly detection.
PiperOrigin-RevId: 827803748
Removes the dataset_id field from the BigQuery table schema and from each log entry created by the BigQueryAgentAnalyticsPlugin. This field is redundant, as all rows logged to a specific table belong to the same dataset.
To ensure the plugin can still target the correct dataset, dataset_id is now a required argument in the BigQueryAgentAnalyticsPlugin constructor, and its default value has been removed.
The BigQuery client user_agent is also updated with plugin version info to help identify traffic originating from this plugin. Unit tests have been updated to reflect the removal of dataset_id from log entries.
PiperOrigin-RevId: 826596499
