* **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
Fix discovery engine search tool, bigquery agent analytics plugin, and application integration tool to correctly handle the ADC quota project override -- the x-goog-user-project should be set based on the ADC quota project, per gcloud auth team's requirements.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 853841124
When truncating conversation history, make sure function_response messages always have their corresponding function_call included
Close#4027
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 852377919
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
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
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
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
SaveFilesAsArtifactsPlugin now resolves the canonical URI for each saved artifact. When the URI is model-accessible (`gs://`, `https://`, `http://`), we add a `Part(file_data=...)` so the LLM can fetch the filedirectly while still emitting the placeholder. If no model-accessible URI exists, we retain the original inline blob alongside the placeholder to preserve access to the uploaded bytes.
Close#2016
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 828786519
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
Merge #3163
END_PUBLIC
Hello,
Since global_instruction has been deprecated, I’m migrating to GlobalInstructionPlugin.
During the migration, I encountered an error and am submitting this PR to fix it.
In [df05ed6](https://github.com/google/adk-python/commit/df05ed6b3b7b218d85fddc1acd6617802cdf6f2a) ,
GlobalInstructionPlugin references invocation_context, but CallbackContext actually contains _invocation_context.
This mismatch always causes an error during execution.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3180 from UlookEE:fix_global_instruction_plugin e289a12d69812f0abcfe77db0114fdb2045b31bc
PiperOrigin-RevId: 827682501
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
Introduces the `BigQueryLoggingPlugin` for capturing and sending ADK lifecycle events to Google BigQuery. This allows for persistent storage and analysis of agent and tool interactions. The plugin supports asynchronous logging, automatic dataset/table creation, and comprehensive event capture.
Also refactors common formatting utilities (_format_content, _format_args) for shared use.
PiperOrigin-RevId: 824703739
Update plugin manager and built-in plugins to prioritize CallbackContext. Keep InvocationContext access for legacy plugins with adapter. Change callback docs/tests to cover the new context.
PiperOrigin-RevId: 818822267
Update plugin manager and built-in plugins to prioritize CallbackContext. Keep InvocationContext access for legacy plugins with adapter. Change callback docs/tests to cover the new context.
PiperOrigin-RevId: 818798087
This plugin intercepts tool failures, provides structured guidance to the LLM for reflection and correction, and retries the operation up to a configurable limit.
**Key Features:**
- **Concurrency Safe:** Uses locking to safely handle parallel tool
executions
- **Configurable Scope:** Tracks failures per-invocation (default) or globally
using the `TrackingScope` enum.
- **Extensible Scoping:** The `_get_scope_key` method can be overridden to
implement custom tracking logic (e.g., per-user or per-session).
- **Granular Tracking:** Failure counts are tracked per-tool within the
defined scope. A success with one tool resets its counter without affecting
others.
- **Custom Error Extraction:** Supports detecting errors in normal tool
responses
that
don't throw exceptions, by overriding the `extract_error_from_result`
method.
**Example:**
```python
from my_project.plugins import ReflectAndRetryToolPlugin, TrackingScope
# Example 1: (MOST COMMON USAGE):
# Track failures only within the current agent invocation (default).
error_handling_plugin = ReflectAndRetryToolPlugin(max_retries=3)
# Example 2:
# Track failures globally across all turns and users.
global_error_handling_plugin = ReflectAndRetryToolPlugin(max_retries=5,
scope=TrackingScope.GLOBAL)
# Example 3:
# Retry on failures but do not throw exceptions.
error_handling_plugin =
ReflectAndRetryToolPlugin(max_retries=3,
throw_exception_if_retry_exceeded=False)
# Example 4:
# Track failures in successful tool responses that contain errors.
class CustomRetryPlugin(ReflectAndRetryToolPlugin):
async def extract_error_from_result(self, *, tool, tool_args,tool_context,
result):
# Detect error based on response content
if result.get('status') == 'error':
return result
return None # No error detected
error_handling_plugin = CustomRetryPlugin(max_retries=5)
```
PiperOrigin-RevId: 816456549
The root cause is an unsafe in-memory mutation. The `SaveFilesAsArtifactsPlugin` was saving a direct reference to the message part and then modifying the message list in-place. This created a race condition where downstream code could alter the original part *after* it had been saved as an artifact, leading to a corrupted state.
This CL saves a `copy.copy()` of the artifact, which create a snapshot of the data.
Also Changes the plugin to return a new `types.Content` object instead of modifying the original message in-place
PiperOrigin-RevId: 814308070
