LiteLLM's StreamHandlers output to stderr by default. In cloud environments like GCP, stderr output is treated as ERROR severity regardless of actual log level, causing INFO-level logs to be incorrectly classified as errors.
This change redirects LiteLLM loggers to stdout in two places:
- In `lite_llm.py`: Immediately after litellm import
- In `logs.py`: When `setup_adk_logger()` is called (with guard to check if litellm is imported)
Close#3824
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 843393874
LiteLLM's `ollama_chat` provider does not accept array-based content in messages. This change flattens multipart content by joining text parts or JSON-serializing non-text parts before sending the request to the LiteLLM completion API. This ensures compatibility with Ollama's chat endpoint.
Close#3727
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 843382361
The `_to_litellm_response_format` function now adapts the output format based on the provided model. Gemini models continue to use the "response_schema" key, while OpenAI-compatible models (including Azure OpenAI and Anthropic) now use the "json_schema" key as per LiteLLM's documentation for JSON mode. The schema name is also included in the "json_schema" format.
Close#3713Close#3890
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 843326850
Explicitly resolve the GCP project from arguments or environment variables before calling `spanner.Client`. This avoids redundant calls to `google.auth.default()` that newer versions of the Spanner library might make.
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 843320305
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 change introduces an add_session_to_memory method to both CallbackContext and ToolContext, allowing agents and tools to explicitly trigger the saving of the current session to the memory service. This enables more fine-grained control over when session data is persisted for memory generation. A ValueError is raised if the memory service is not configured.
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 843021899
Merge https://github.com/google/adk-python/pull/3875
# Problem
The example in `contributing/samples/human_in_loop/README.md` shows:
```python
await runner.run_async(...)
```
However, `run_async` returns an **async generator**, so awaiting it raises:
```
TypeError: object async_generator can't be used in 'await' expression
```
Additionally, the example payload uses `"ticket-id"` while ADK tools and other examples use `"ticketId"`, creating a mismatch that breaks copy/paste usage.
# Solution
- Updated the snippet to consume the async generator correctly:
```python
async for event in runner.run_async(...):
...
```
- Aligned the payload key from `"ticket-id"` → `"ticketId"` for consistency with ADK schema and other examples.
These changes make the example runnable and consistent with the API’s actual behavior.
# Testing Plan
This PR is a **small documentation correction**, so no unit tests are required per contribution guidelines.
- Verified the corrected snippet manually to ensure it no longer raises `TypeError`.
# Checklist
- [x] I have read the CONTRIBUTING.md document.
- [x] I have performed a self-review of my own code.
- [ ] I have commented my code, particularly in hard-to-understand areas. *(N/A – docs only)*
- [ ] I have added tests that prove my fix is effective or that my feature works. *(N/A – docs only)*
- [ ] New and existing unit tests pass locally with my changes. *(N/A – docs only)*
- [x] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules. *(N/A)*
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3875 from krishna-dhulipalla:docs/fix-adk-run_async-example 83fc5b430690b63b8b7bf1025ef03b0761264751
PiperOrigin-RevId: 842952362
When users instantiate LlmAgent directly (not subclassed), the origin inference incorrectly detected ADK's internal google/adk/agents/ path as a mismatch.
Use metadata from AgentLoader when available
Skip inference for google.adk.* module
Close#3143
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 842774292
Context: many issues related to local mult-agent system is tagged with a2a
Co-authored-by: Xiang (Sean) Zhou <seanzhougoogle@google.com>
PiperOrigin-RevId: 842397159
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
This change introduces a `verify` parameter to `RestApiTool` and `OpenAPIToolset`. This parameter allows users to configure how SSL certificates are verified when making API calls using the `requests` library. Options include providing a path to a CA bundle, disabling verification, or using a custom `ssl.SSLContext`. New methods `configure_verify` and `configure_verify_all` are added to update this setting after initialization. This is useful for environments with TLS-intercepting proxies.
Fixes: https://github.com/google/adk-python/issues/3720
Co-authored-by: Xuan Yang <xygoogle@google.com>
PiperOrigin-RevId: 840809727
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
Update fastapi constraint from <0.119.0 to <0.124.0
Update starlette minimum version from >=0.46.2 to >=0.49.1
Closes#3822
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 840372879
When converting `types.Content` with a `function_response` to LiteLLM's `ChatCompletionToolMessage`, if the response is already a string, use it directly. Otherwise, serialize the response to JSON. This prevents double-serialization of string payloads
Close#3676
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 840013822
This change refactors how session, memory, and artifact services are created in the fast_api server, using the shared service_factory.
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 839997110
This change introduces `Gemma3Ollama`, a new LLM model class for running Gemma 3 models locally via Ollama, leveraging LiteLLM. The function calling logic previously in the `Gemma` class has been refactored into a `GemmaFunctionCallingMixin` and is now used by both `Gemma` and `Gemma3Ollama`. A new sample application, `hello_world_gemma3_ollama`, is added to demonstrate using `Gemma3Ollama` with an agent. Unit tests for `Gemma3Ollama` are also included.
Merge: https://github.com/google/adk-python/pull/3120
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 839996879
This change expands the supported file MIME types and introduces provider-specific handling for file uploads. For providers like OpenAI and Azure, inline file data is now uploaded via `litellm.acreate_file` to obtain a `file_id`, which is then used in the message content. Other providers continue to use base64 encoded file data. Affected functions have been updated to be asynchronous
Merge:https://github.com/google/adk-python/pull/2863
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 839996848
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
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 839996774
The warning message shows that ADK Web is for development purposes only and should not be used in production, as it has access to all data. This warning is displayed when the `--with-ui` flag is used with `adk deploy` and `adk deploy to-gke`
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 839795361
Merge https://github.com/google/adk-python/pull/3583
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #3582
**2. Or, if no issue exists, describe the change:**
_If applicable, please follow the issue templates to provide as much detail as
possible._
**Problem:**
Currently, the BigQuery tool in ADK does not provide a way for developers to add custom labels to BigQuery jobs created by their agents. This makes it difficult to:
Track and monitor BigQuery costs associated with specific agents or use cases
Organize and filter BigQuery jobs in the Google Cloud Console
Implement billing attribution and resource organization strategies
Differentiate between jobs from different environments (dev, staging, production)
While the tool automatically adds an internal adk-bigquery-tool label with the caller_id, there's no mechanism for users to add their own custom labels for tracking and monitoring purposes.
**Solution:**
Add a labels configuration field to BigQueryToolConfig that allows users to specify custom key-value pairs to be applied to all BigQuery jobs executed by the agent. The solution should:
Configuration Option: Add an optional labels parameter to BigQueryToolConfig accepting a dictionary of string key-value pairs
Validation: Ensure labels follow BigQuery's requirements (non-empty string keys, string values)
Job Application: Automatically apply configured labels to all BigQuery jobs alongside the existing internal labels Documentation: Provide clear documentation on how to use labels for tracking and monitoring
### Testing Plan
_Please describe the tests that you ran to verify your changes. This is required
for all PRs that are not small documentation or typo fixes._
**Unit Tests:**
- [x] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
```
pytest tests/unittests/tools/bigquery/test_bigquery_tool_config.py -v --tb=line -W ignore::UserWarning
========================================= test session starts ==========================================
platform darwin -- Python 3.11.14, pytest-9.0.1, pluggy-1.6.0 -- *****redacted******
cachedir: .pytest_cache
rootdir: *****redacted******
configfile: pyproject.toml
plugins: mock-3.15.1, anyio-4.11.0, xdist-3.8.0, langsmith-0.4.43, asyncio-1.3.0
asyncio: mode=Mode.AUTO, debug=False, asyncio_default_fixture_loop_scope=function, asyncio_default_test_loop_scope=function
collected 14 items
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_experimental_warning PASSED [ 7%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_invalid_property PASSED [ 14%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_invalid_application_name PASSED [ 21%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_max_query_result_rows_default PASSED [ 28%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_max_query_result_rows_custom PASSED [ 35%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_valid_maximum_bytes_billed PASSED [ 42%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_invalid_maximum_bytes_billed PASSED [ 50%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_valid_labels PASSED [ 57%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_empty_labels PASSED [ 64%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_none_labels PASSED [ 71%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_invalid_labels_type PASSED [ 78%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_invalid_label_key_type PASSED [ 85%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_invalid_label_value_type PASSED [ 92%]
tests/unittests/tools/bigquery/test_bigquery_tool_config.py::test_bigquery_tool_config_empty_label_key PASSED [100%]
==================================================================================================== 14 passed in 2.02s ====================================================================================================
```
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### 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.
### Additional context
_Add any other context or screenshots about the feature request here._
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3583 from Faraaz1994:feature/bq_label 0fd7fe6a3b1ee20a36f73562e425d007b8d7dc9d
PiperOrigin-RevId: 839523588
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
The Gemini API may not always send an explicit transcription finished signal. This change ensures that any buffered input or output transcription text is yielded as a finished transcription when a turn is completed, generation is complete, or the session is interrupted.
Also, refined the check for `event.partial` in runners.py to be more explicit.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 839008606
LlmAgentConfig.model now accepts either a plain model string or a CodeConfig. This lets YAML configs pass a LiteLLM instance with managed API settings (e.g., api_base and fallbacks) so agents can hit KimiK2’s managed endpoint instead of only the default modelID.
Close#3579
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 838978654
This change adds new `POST` endpoint `/apps/{app_name}/users/{user_id}/sessions/{session_id}/artifacts` to the ADK web server. This endpoint lets clients to save new artifacts associated with a specific session. The endpoint uses `SaveArtifactRequest` and returns `SaveArtifactResponse`, including the version and canonical URI of the saved artifact.
Close#1975
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 838977880
Default CLI session storage to SQLite instead of in-memory
Previously, adk run and adk web used in-memory session storage by default, causing sessions to be lost on restart. Now sessions persist to .adk/session.db automatically. To use in-memory storage, pass --session-service-uri memory://
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 838975328
Merge https://github.com/google/adk-python/pull/3700
### Description
This PR refactors the `adk_stale_agent` to address `429 RESOURCE_EXHAUSTED` errors encountered during workflow execution. The previous implementation was inefficient in fetching issue history (using pagination over the REST API) and lacked server-side filtering, causing excessive API calls and huge token consumption that breached Gemini API quotas.
The new implementation switches to a **GraphQL-first approach**, implements server-side filtering via the Search API, adds robust concurrency controls, and significantly improves code maintainability through modular refactoring.
### Root Cause of Failure
The previous workflow failed with the following error due to passing too much context to the LLM and processing too many irrelevant issues:
```text
google.genai.errors.ClientError: 429 RESOURCE_EXHAUSTED.
Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_paid_tier_input_token_count
```
### Key Changes
#### 1. Optimization: REST → GraphQL (`agent.py`)
* **Old:** Fetched issue comments and timeline events using multiple paginated REST API calls (`/timeline`).
* **New:** Implemented `get_issue_state` using a single **GraphQL** query. This fetches comments, `userContentEdits`, and specific timeline events (Labels, Renames) in one network request.
* **Refactoring:** The complex analysis logic has been decomposed into focused helper functions (_fetch_graphql_data, _build_history_timeline, _replay_history_to_find_state) for better readability and testing.
* **Configurable:** Added GRAPHQL_COMMENT_LIMIT and GRAPHQL_TIMELINE_LIMIT settings to tune context depth
* **Impact:** Drastically reduces the data payload size and eliminates multiple API round-trips, significantly lowering the token count sent to the LLM.
#### 2. Optimization: Server-Side Filtering (`utils.py`)
* **Old:** Fetched *all* open issues via REST and filtered them in Python memory.
* **New:** Uses the GitHub Search API (`get_old_open_issue_numbers`) with `created:<DATE` syntax.
* **Impact:** Only fetches issue numbers that actually meet the age threshold, preventing the agent from wasting cycles and tokens on brand-new issues.
#### 3. Concurrency & Rate Limiting (`main.py` & `settings.py`)
* **Old:** Sequential execution loop.
* **New:** Implemented `asyncio.gather` with a configurable `CONCURRENCY_LIMIT` (set to 3).
* **New:** Added `urllib3` retry strategies (exponential backoff) in `utils.py` to handle GitHub API rate limits (HTTP 429) gracefully.
#### 4. Logic Improvements ("Ghost Edits")
* **New Feature:** The agent now detects "Ghost Edits" (where an author updates the issue description without posting a new comment).
* **Action:** If a silent edit is detected on a stale candidate, the agent now alerts maintainers instead of marking it stale, preventing false positives.
### File Comparison Summary
| File | Change |
| :--- | :--- |
| `main.py` | Switched from `InMemoryRunner` loop to `asyncio` chunked processing. Added execution timing and API usage logging. |
| `agent.py` | Replaced REST logic with GraphQL query. Added logic to handle silent body edits. Decomposed giant get_issue_state into helper functions with docstrings. Added _format_days helper. |
| `utils.py` | Added `HTTPAdapter` with Retries. Added `get_old_open_issue_numbers` using Search API. |
| `settings.py` | Removed `ISSUES_PER_RUN`; added configuration for CONCURRENCY_LIMIT, SLEEP_BETWEEN_CHUNKS, and GraphQL limits. |
| `PROMPT_INSTRUCTIONS.txt` | Simplified decision tree; removed date calculation responsibility from LLM. |
### Verification
The new logic minimizes token usage by offloading date calculations to Python and strictly limiting the context passed to the LLM to semantic intent analysis (e.g., "Is this a question?").
* **Metric Check:** The workflow now tracks API calls per issue to ensure we stay within limits.
* **Safety:** Silent edits by users now correctly reset the "Stale" timer.
* **Maintainability:** All complex logic is now isolated in typed helper functions with comprehensive docstrings.
Co-authored-by: Xuan Yang <xygoogle@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3700 from ryanaiagent:feat/improve-stale-agent 888064eff125ae74f7c3a9ad6c74f98de80243a2
PiperOrigin-RevId: 838885530
This change introduces an `AnthropicLlm` base class for direct Anthropic API calls using `AsyncAnthropic`. The existing `Claude` class now inherits from `AnthropicLlm` and is specialized to use `AsyncAnthropicVertex` for models hosted on Vertex AI. The `messages.create` call is now properly awaited
Merge: https://github.com/google/adk-python/pull/2904
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 838851026
This change updates the docstring for `agent_engine_id` to clarify that only the resource ID is expected. It also adds a warning log if the provided `agent_engine_id` contains a '/' character, suggesting it might be a full resource path, and provides guidance on how to extract the ID. Unit tests are added to verify the warning behavior.
Merge: https://github.com/google/adk-python/pull/2941
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 838845022
Also provide a command line tool `adk migrate session` for DB migration
Addresses https://github.com/google/adk-python/discussions/3605
Addresses https://github.com/google/adk-python/issues/3681
To verify:
```
# Start one postgres DB
docker run --name my-postgres -d -e POSTGRES_DB=agent -e POSTGRES_USER=agent -e POSTGRES_PASSWORD=agent -e PGDATA=/var/lib/postgresql/data/pgdata -v pgvolume:/var/lib/postgresql/data -p 5532:5432 postgres
# Connect to an old version of ADK and produce some query data
adk web --session_service_uri=postgresql://agent:agent@localhost:5532/agent
# Check out to the latest branch and restart ADK web
# You should see error log ask you to migrate the DB
# Start a new DB
docker run --name migration-test-db \
-d \ --rm \ -e POSTGRES_DB=agent \ -e POSTGRES_USER=agent \ -e POSTGRES_PASSWORD=agent -e PGDATA=/var/lib/postgresql/data/pgdata -v migration_test_vol:/var/lib/postgresql/data -p 5533:5432 postgres
# DB Migration
adk migrate session \
--source_db_url="postgresql://agent:agent@localhost:5532/agent" \
--dest_db_url="postgresql://agent:agent@localhost:5533/agent"
# Run ADK web with the new DB
adk web --session_service_uri=postgresql+asyncpg://agent:agent@localhost:5533/agent
# You should see the data from old DB is migrated
```
Co-authored-by: Shangjie Chen <deanchen@google.com>
PiperOrigin-RevId: 837341139
This calls the cloudapiregistry.googleapis.com API to get MCP tools from the project's registry, and adds them to ADK.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 837166909
Adds the shared adk_services_options decorator to adk run and other commands so developers can pass session/artifact URIs from the CLI
Has new warning for the unsupported memory service on adk run, and removes the legacy --session_db_url/--artifact_storage_uri flags with tests
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 836743358
This change routes adk run and the FastAPI server through the new session/artifact service factory, keeps the default experience backed by per-agent .adk storage
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 836733234
Previously, image parts were always filtered out when converting content to Anthropic message parameters. This change updates the logic to only filter out image parts and log a warning when the content role is not "user". This enables sending image data as part of user prompts to Claude models
Merges: https://github.com/google/adk-python/pull/3286
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 836725196
Merge https://github.com/google/adk-python/pull/3284
**Problem:**
When debugging agents that utilize the `VertexAiSearchTool`, it's currently difficult to inspect the specific configuration parameters (datastore ID, engine ID, filter, max_results, etc.) being passed to the underlying Vertex AI Search API via the `LlmRequest`. This lack of visibility can hinder troubleshooting efforts related to tool configuration.
**Solution:**
This PR enhances the `VertexAiSearchTool` by adding a **debug-level log statement** within the `process_llm_request` method. This log precisely records the parameters being used for the Vertex AI Search configuration just before it's appended to the `LlmRequest`.
This provides developers with crucial visibility into the tool's runtime behavior when debug logging is enabled, significantly improving the **debuggability** of agents using this tool. Corresponding unit tests were updated to rigorously verify this new logging output using `caplog`. Additionally, minor fixes were made to the tests to resolve Pydantic validation errors.
Co-authored-by: Xuan Yang <xygoogle@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3284 from omkute10:feat/add-logging-vertex-search-tool 199c12bf00a57abe202401591088c0423b39b928
PiperOrigin-RevId: 836419886
Merge https://github.com/google/adk-python/pull/2588
## Description
Fixes an issue in `base_llm_flow.py` where, in Bidi-streaming (live) mode, the multi-agent structure causes duplicated responses after tool calling.
## Problem
In Bidi-streaming (live) mode, when utilizing a multi-agent structure, the leaf-level sub-agent and its parent agent both process the same function call response, leading to duplicate replies. This duplication occurs because the parent agent's live connection remains open while initiating a new connection with the child agent.
## Root Cause
The issue originated from the placement of agent transfer logic in the `_postprocess_live` method at lines 547-557. When a `transfer_to_agent` function call was made:
1. The function response was processed in `_postprocess_live`
2. A recursive call to `agent_to_run.run_live` was initiated
3. This prevented the closure of the parent agent's connection at line 175 of the `run_live` method, as that code path was never reached
4. Both the parent and child agents remained active, causing both to process subsequent function responses
## Solution
This PR addresses the issue by ensuring the parent agent's live connection is closed before initiating a new one with the child agent. Changes made:
**Connection Management**: Moved the agent transfer logic from `_postprocess_live` method to the `run_live` method, specifically:
- Removed agent transfer handling from lines 547-557 in `_postprocess_live`
- Added agent transfer handling after connection closure at lines 176-184 in `run_live`
**Code Refactoring**: The agent transfer now occurs in the proper sequence:
1. Parent agent processes the `transfer_to_agent` function response
2. Parent agent's live connection is properly closed (line 175)
3. New connection with child agent is initiated (line 182)
4. Child agent handles subsequent function calls without duplication
**Improved Flow Control**: This ensures that each agent processes function call responses without duplication, maintaining proper connection lifecycle management in multi-agent structures.
## Testing
To verify this fix works correctly:
1. **Multi-Agent Structure Test**: Set up a multi-agent structure with a parent agent that transfers to a child agent via `transfer_to_agent` function call
2. **Bidi-Streaming Mode**: Enable Bidi-streaming (live) mode in the configuration
3. **Function Call Verification**: Trigger a function call that results in agent transfer
4. **Response Monitoring**: Verify that only one response is generated (not duplicated)
5. **Connection Management**: Confirm that parent agent's connection is properly closed before child agent starts
**Expected Behavior**:
- Single function response per call
- Clean agent handoffs without connection leaks
- Proper connection lifecycle management
## Backward Compatibility
This change is **fully backward compatible**:
- No changes to public APIs or method signatures
- Existing single-agent flows remain unaffected
- Non-live (regular async) flows continue to work as before
- Only affects the internal flow control in live multi-agent scenarios
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2588 from AlexeyChernenkoPlato:fix/double-function-response-processing-issue 3339260a4e007251137d199bdcef0ddef4487b03
PiperOrigin-RevId: 835619170
This change replaces the use of `ChatCompletionDeveloperMessage` with `ChatCompletionSystemMessage` and sets the role to "system" for providing system instructions to LiteLLM models
Close#3657
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 835388738
Merge https://github.com/google/adk-python/pull/3576
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #3557
- Related: #_issue_number_
**2. Or, if no issue exists, describe the change:**
_If applicable, please follow the issue templates to provide as much detail as
possible._
**Problem:**
When creating a BaseAgent with multiple sub-agents, there was no validation to ensure that all sub-agents have unique names. This could lead to confusion when trying to find or reference specific sub-agents by name, as duplicate names would make it ambiguous which agent is being referenced.
**Solution:**
Added a @field_validator for the sub_agents field in BaseAgent that validates all sub-agents have unique names. The validator:
Checks for duplicate names in the sub-agents list
Raises a ValueError with a clear error message listing all duplicate names found
Returns the validated list if all names are unique
Handles edge cases like empty lists gracefully
### Testing Plan
_Please describe the tests that you ran to verify your changes. This is required
for all PRs that are not small documentation or typo fixes._
**Unit Tests:**
- [x] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
Added 4 new test cases in tests/unittests/agents/test_base_agent.py:
test_validate_sub_agents_unique_names_single_duplicate: Verifies that a single duplicate name raises ValueError
test_validate_sub_agents_unique_names_multiple_duplicates: Verifies that multiple duplicate names are all reported in the error message
test_validate_sub_agents_unique_names_no_duplicates: Verifies that unique names pass validation successfully
test_validate_sub_agents_unique_names_empty_list: Verifies that empty sub-agents list passes validation
All tests pass locally. You can run with:
pytest tests/unittests/agents/test_base_agent.py::test_validate_sub_agents_unique_names_single_duplicate tests/unittests/agents/test_base_agent.py::test_validate_sub_agents_unique_names_multiple_duplicates tests/unittests/agents/test_base_agent.py::test_validate_sub_agents_unique_names_no_duplicates tests/unittests/agents/test_base_agent.py::test_validate_sub_agents_unique_names_empty_list -v
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
Test Case 1: Duplicate names should raise error
from google.adk.agents import Agent
agent1 = Agent(name="sub_agent", model="gemini-2.5-flash")
agent2 = Agent(name="sub_agent", model="gemini-2.5-flash") # Same name
# This should raise ValueError
try:
parent = Agent(
name="parent",
model="gemini-2.5-flash",
sub_agents=[agent1, agent2]
)
except ValueError as e:
print(f"Expected error: {e}")
# Output: Found duplicate sub-agent names: `sub_agent`. All sub-agents must have unique names.
Test Case 2: Unique names should work
from google.adk.agents import Agent
agent1 = Agent(name="agent1", model="gemini-2.5-flash")
agent2 = Agent(name="agent2", model="gemini-2.5-flash")
# This should work without error
parent = Agent(
name="parent",
model="gemini-2.5-flash",
sub_agents=[agent1, agent2]
)
print("Success: Unique names validated correctly")
### 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.
### Additional context
This change adds validation at the BaseAgent level, so it automatically applies to all agent types that inherit from BaseAgent (e.g., LlmAgent, LoopAgent, etc.). The validation uses Pydantic's field validator system, which runs during object initialization, ensuring the constraint is enforced early and consistently.
The error message clearly identifies which names are duplicated, making it easy for developers to fix the issue:
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3576 from sarojrout:feat/validate-unique-sub-agent-names 07adf1f9a5fc935389eb9dfa3cbc1311f551ebe3
PiperOrigin-RevId: 835358118
Merge https://github.com/google/adk-python/pull/3538
Main change from:
E(inv=2, role=user), E(inv=2, role=model), E(inv=2, role=user),
To:
E(inv=2, role=user), E(inv=2, role=model)
I think the last E(inv=2, role=user) was wrong. Also reformatted.
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3538 from adrianad:patch-1 627b933bdc3e00e45f704edf95448281e32d127c
PiperOrigin-RevId: 835346467
The `database_session_service` now updates the `update_time` of a session to the event's timestamp when an event is appended
Close#2721
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 834994070
LlmResponse/Event now keep both provider reasoning output and the raw vendor payload so callbacks and loggers can inspect hidden “thoughts” or trace bugs without rewriting adapters.
LiteLLM’s adapter and streaming loop emit reasoning chunks alongside text and aggregate them into final events -> all responses now carry a JSON-safe copy of the source payload for debug. UnsafeLocalCodeExecutor uses the documented exec(code, globals, globals) form, letting helper functions defined inside snippets call each other.
Close#1749
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 834956847
Merge https://github.com/google/adk-python/pull/3430
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #3429
**2. Or, if no issue exists, describe the change:**
_If applicable, please follow the issue templates to provide as much detail as
possible._
**Problem:**
The existing `/list-apps` endpoint only returns the name of the folder that each agent is in
**Solution:**
This adds a new endpoint `/list-apps-detailed` which will load each agent using the existing `AgentLoader.load_agent` method, and then return the folder name, display name (with underscores replaced with spaces for a more readable version), description, and the agent type.
This does introduce overhead if you had multiple agents since they all need to be loaded, but by maintaining the existing `/list-apps` endpoint, users can choose which one to hit if they don't want to load all agents. Since the existing `load_agents` method will cache results, there's only a penalty on the first hit.
### Testing Plan
Created a unit test for this, similar to the `/list-apps`. Also tested this with my own ADK instance to verify it loaded correctly.
```
curl --location "localhost:8000/list-apps-detailed"
```
```json
{
"apps": [
{
"name": "agent_1",
"displayName": "Agent 1",
"description": "A test description for a test agent",
"agentType": "package"
},
{
"name": "agent_2",
"displayName": "Agent 2",
"description": "A test description for a test agent ",
"agentType": "package"
},
{
"name": "agent_3",
"displayName": "Agent 3",
"description": "A test description for a test agent",
"agentType": "package"
}
]
}
```
**Unit Tests:**
- [X] I have added or updated unit tests for my change.
- [X] All unit tests pass locally.
3054 passed, 2383 warnings in 46.96s
### 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.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3430 from dylan-apex:more-detailed-list-apps e6864fd61a673da5fd2fb28d2d7d72cb90f5af0a
PiperOrigin-RevId: 834907771
Merge https://github.com/google/adk-python/pull/3572
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
N/A
**2. Or, if no issue exists, describe the change:**
**Problem:**
Docs fix
### Checklist
- [ ] I have read the [CONTRIBUTING.md](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) document.
- [ ] I have performed a self-review of my own code.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3572 from issacg:patch-1 b7c7ed46ff0fb018f4da1537535eff27c323daf5
PiperOrigin-RevId: 834864431
The `Parameter` class now provides default Python names based on the parameter location when the original name is empty. This prevents parameters from having an empty string as their Python name, especially for request bodies defined without a top-level name.
Close#2213
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 834850255
Make sure that the adk run --save_session writes session JSON using the Pydantic camelCase aliases (by_alias=True), matching ADK Web and keeping session files consistent
Close#3558
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 834847209
Merge https://github.com/google/adk-python/pull/3603
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #_issue_number_
- Related: #_issue_number_
**2. Or, if no issue exists, describe the change:**
_If applicable, please follow the issue templates to provide as much detail as
possible._
**Problem:**
_A clear and concise description of what the problem is._
**Solution:**
_A clear and concise description of what you want to happen and why you choose
this solution._
### Testing Plan
_Please describe the tests that you ran to verify your changes. This is required
for all PRs that are not small documentation or typo fixes._
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [ ] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### Checklist
- [ ] I have read the [CONTRIBUTING.md](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) document.
- [ ] I have performed a self-review of my own code.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
### Additional context
_Add any other context or screenshots about the feature request here._
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3603 from holtskinner:patch-1 833405898b747438e3f8a1b8c34095e25135fca3
PiperOrigin-RevId: 834805195
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.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 834514264
It also enables the ADK triaging agent to run periodically on planned but not triaged issues.
Co-authored-by: Xuan Yang <xygoogle@google.com>
PiperOrigin-RevId: 834489103
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
When this agent was built before the agent name was changed in the build script and accepted like that from the VB so changed to set into that form
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 834479335
This change introduces `input_transcription` and `output_transcription` fields to session events, enabling the storage and retrieval of transcription data in both the database and Vertex AI session services.
Closes#3172
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 834366848
Fixes https://github.com/google/adk-python/issues/3174
The event compaction process, configured via `EventsCompactionConfig`, was
previously scheduled as a background task using `asyncio.create_task`.
Because Python's `asyncio.create_task` only holds a weak reference to
the created task and no strong reference was maintained by ADK, the
compaction task could be garbage-collected before it finished executing.
This resulted in event compaction failing silently or only partially
running, preventing session history from being summarized.
### Approaches Considered
Two approaches were considered to fix this:
1. **`asyncio.create_task` + Reference:** Create the task with `create_task` and store a strong reference to it (e.g., in a `set` on the [Runner](http://_vscodecontentref_/0) instance), removing it only when complete via `task.add_done_callback()`.
* **Pros:** The [run_async](http://_vscodecontentref_/1) async generator finishes immediately after yielding the last agent event.
* **Cons:** Adds complexity to the Runner state; background task failures are silent to the [run_async](http://_vscodecontentref_/2) caller; requires enhancement to `runner.close()` to correctly manage pending tasks on shutdown.
2. **`await`:** Directly `await` the compaction coroutine at the end of [run_async](http://_vscodecontentref_/3) after all agent events have been yielded.
* **Pros:** Simple to implement; ensures compaction runs to completion; failures during compaction propagate immediately to the [run_async](http://_vscodecontentref_/4) caller, making them visible and easier to debug.
* **Cons:** The `async for` loop iterating over [run_async](http://_vscodecontentref_/5) will not terminate until compaction finishes.
### Decision
This change implements the `await` approach. Although it means the `async for` loop takes longer to terminate when compaction occurs, it was chosen for its **simplicity and robustness**. Ensuring that compaction either succeeds or fails visibly is preferable to silent background failures.
All agent response events are yielded *before* compaction starts, so there is **no user-perceived delay in receiving the agent's answer** for the current turn.
### Integration Note for Users
Because compaction is now awaited, code consuming events via `async for event in runner.run_async(...)` will only finish iterating *after* compaction is complete (if compaction is triggered for that invocation).
If your application only needs the agent's response to proceed (e.g., displaying a message in a UI and allowing the user to reply), you can process events as they arrive and initiate the next turn without waiting for the `async for` loop to fully terminate. A new call to [run_async](http://_vscodecontentref_/6) for the next user query can be made immediately and will execute concurrently.
**Example:**
```python
async def handle_agent_turn(runner, message):
print("Agent is thinking...")
async for event in runner.run_async(user_id='...', session_id='...', new_message=message):
# Stream events to UI, log, etc.
if event.author == 'model' and event.content and event.content.parts[0].text:
print(f"Agent response: {event.content.parts[0].text}")
# The agent has provided a text response.
# The application can now enable user input for the next turn,
# even though this async for loop might not finish immediately
# if compaction is running.
print("Invocation complete (including compaction if any).")
# In your application:
# A new call to handle_agent_turn(runner, next_message) can be made
# as soon as the user provides the next input, without waiting for
# the previous call's generator to be exhausted.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 833885375
this creates service_factory to handle .adk folder changes (including per-agent .adk defaults and in-memory/custom URI handling)
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 833875524
This change loads the agent or app from the specified directory before creating the session. This allows using the correct application name (from the `App` object if applicable) when initializing the session, rather than always defaulting to the folder name. The variable `root_agent` is also renamed to `agent_or_app` to better reflect that it can be either an Agent or an App
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 833839070
Currently logic to check for a disconnected session only checks for certain headers but doesn't detect all cases, leading to situations where it tries to connect to a session that is down. This adds logic so that we ping the server to check if it is disconnected. Fixes https://github.com/google/adk-python/issues/3321.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 833487825
Updates type annotations to use built-in types like `list` and `dict`, and uses `| None` for optional types, along with adding `from __future__ import annotations`
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 832522395
Currently logic to check for a disconnected session only checks for certain headers but doesn't detect all cases, leading to situations where it tries to connect to a session that is down. This adds logic so that we ping the server to check if it is disconnected. Fixes https://github.com/google/adk-python/issues/3321.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 832460068
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
In order to make evals more resilient to temporary model failures, we add retry options to llm_requests that are made during evals.
Note that this is a fall back option, if the developer has already specified their own retry options, then those will be honored.
Co-authored-by: Ankur Sharma <ankusharma@google.com>
PiperOrigin-RevId: 832383755
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
This is ~27% of the current cold start latency after previous changes are submitted. This change refactors `google.adk.tools/__init__.py` to use `__getattr__` for lazy loading of all tools and related classes. Previously, all modules were imported directly upon `google.adk.tools` import, leading to potentially long initial import times. With lazy loading, modules are only imported when they are first accessed, improving the initial startup performance.
Co-authored-by: Liang Wu <wuliang@google.com>
PiperOrigin-RevId: 831537187
This change:
* Deprecates the `save_live_audio` configuration option in `RunConfig`, introducing `save_live_blob` as its replacement. A warning is issued if `save_live_audio` is used.
* Updates `base_llm_flow.py` to use the new `save_live_blob` flag.
* Ensures that audio events generated by `audio_cache_manager.py` are properly appended to the session service.
* Adds a utility script `pcm_audio_player.py` for playing raw PCM audio files.
Input sample event: 14a5859f-6b6c-46ed-9f28-e5008793b1c6|live_bidi_streaming_multi_agent|user|1e867c7f-dbe1-4268-a7bc-7a9fa5fbd16c|e-7a28a060-29bf-4483-bc5c-17248698a897|1762916981.5932|{"content":{"parts":[{"file_data":{"file_uri":"artifact://live_bidi_streaming_multi_agent/user/1e867c7f-dbe1-4268-a7bc-7a9fa5fbd16c/_adk_live/adk_live_audio_storage_input_audio_1762916981593.pcm#0","mime_type":"audio/pcm"}}],"role":"user"},"invocation_id":"e-7a28a060-29bf-4483-bc5c-17248698a897","author":"user","actions":{"state_delta":{},"artifact_delta":{},"requested_auth_configs":{},"requested_tool_confirmations":{}},"id":"14a5859f-6b6c-46ed-9f28-e5008793b1c6","timestamp":1762916981.5932002}
output sample event:
506c9df4-e143-4ebc-90a5-2f5b2eb26754|live_bidi_streaming_multi_agent|user|1e867c7f-dbe1-4268-a7bc-7a9fa5fbd16c|e-7a28a060-29bf-4483-bc5c-17248698a897|1762916986.10579|{"content":{"parts":[{"file_data":{"file_uri":"artifact://live_bidi_streaming_multi_agent/user/1e867c7f-dbe1-4268-a7bc-7a9fa5fbd16c/_adk_live/adk_live_audio_storage_output_audio_1762916986105.pcm;rate=24000#0","mime_type":"audio/pcm;rate=24000"}}],"role":"model"},"invocation_id":"e-7a28a060-29bf-4483-bc5c-17248698a897","author":"model","actions":{"state_delta":{},"artifact_delta":{},"requested_auth_configs":{},"requested_tool_confirmations":{}},"id":"506c9df4-e143-4ebc-90a5-2f5b2eb26754","timestamp":1762916986.105794}
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 831512074
pin crew ai to 3.13 at highest version as it uses chromadb and that uses onnxruntime which does not work yet with 3.14
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 831508884
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 CL adds debug logs to show the history being sent to the live connection and the live connect config used.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 831473597
This changes how content parts are converted for LiteLLM, treating all "text/" mime types as plain text and only "application/pdf" as a file
Close#1940
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 831418696
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
This change introduces a mechanism for users to register their own custom backend services for sessions, memory, and artifacts without modifying the ADK framework. This enhances the extensibility of ADK.
Two methods of registration are supported, both by placing a file in the parent directory of the agents.
**YAML Configuration (services.yaml or .yml)**
This is the recommended approach for simple services that can be instantiated with a constructor like MyService(uri="...", **kwargs).
Example services.yaml:
```
services:
- scheme: mysession
type: session
class: my_package.my_module.MyCustomSessionService
```
**Python Registration (services.py)**
For services requiring more complex initialization logic, users can define factory functions in a services.py file.
Example services.py
```
from google.adk.cli.service_registry import get_service_registry
from my_package.my_module import MyCustomSessionService
def my_session_factory(uri: str, **kwargs):
# custom initialization logic
return MyCustomSessionService(...)
get_service_registry().register_session_service("mysession", my_session_factory)
```
ADK will load services from services.yaml/.yml first, and then from services.py. If the same service scheme is defined in both, the registration in services.py will take precedence.
To use a registered service, specify its URI via the corresponding command-line flag, e.g., `--session_service_uri=mysession://....`
Co-authored-by: Shangjie Chen <deanchen@google.com>
PiperOrigin-RevId: 831211371
Creates AdkFolderManager for creating/resetting the .adk layout, helper builders that return SQLite- and filesystembacked services for each agent
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 831206377
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
The `google.cloud.storage` module is now imported within the `__init__` method of `GCSArtifactService`, rather than at the top level. This avoids importing the potentially heavy `storage` module unless an instance of `GCSArtifactService` is actually created.
Co-authored-by: Liang Wu <wuliang@google.com>
PiperOrigin-RevId: 831124463
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.
Co-authored-by: Liang Wu <wuliang@google.com>
PiperOrigin-RevId: 831124329
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.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 831123085
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
The agent's instructions are updated to guide it to guess a positive integer, starting from 50 and decreasing, using the `guess_number_tool` until the target is found. The maximum number of retries for the `CustomRetryPlugin` is increased from 6 to 10.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 830984481
Merge https://github.com/google/adk-python/pull/2167, during which:
- Let the already added `max_query_result_rows` field cover for `max_downloaded_rows` field added in the PR
- Revert `max_rows` parameter added to execute_sql function, the tool config control should serve most practical use cases
- Keep the relevant tests for tool config
🤖 Generated with [Claude Code](https://claude.ai/code)
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2167 from lupuletic:feature/configurable-max-downloaded-rows 23c56905c297d7aec2be4f1eb86ea23c8178bf21
PiperOrigin-RevId: 830701093
Enhanced `save_artifact` in `callback_context.py` to accept `custom_metadata` and added `get_artifact_version` to retrieve artifact details.
Introduced a new sample, `context_offloading_with_artifact`, demonstrating how to use ADK artifacts to offload large data from the LLM context. The sample includes:
- `QueryLargeDataTool`: Generates mock sales reports, saves them as artifacts with custom metadata, and injects the artifact content into the LLM request immediately after creation.
- `CustomLoadArtifactsTool`: Provides summaries of available artifacts to the LLM based on metadata and loads artifact content on demand when `load_artifacts` is called.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 830592786
Merge https://github.com/google/adk-python/pull/2889
# Implement Full async DatabaseSessionService
**Target Issue:** #1005
## Overview
This PR introduces an asynchronous implementation of the `DatabaseSessionService` with minimal breaking changes. The primary goal is to enable effective use of ADK in fully async environments and API endpoints while avoiding event loop blocking during database I/O operations.
## Changes
- Converted `DatabaseSessionService` to use async/await patterns throughout
## Testing Plan
The implementation has been tested following the project's contribution guidelines:
### Unit Tests
- All existing unit tests pass successfully
- Minor update to test requirements added to support `aiosqlite`
### Manual End-to-End Testing
- E2E tests performed using:
- **LLM Provider:** LiteLLM
- **Database:** PostgreSQL with `asyncpg` driver
```python
from google.adk.sessions.database_session_service import DatabaseSessionService
connection_string: str = (
"postgresql+asyncpg://PG_USER:PG_PSWD@PG_HOST:5432/PG_DB"
)
session_service: DatabaseSessionService = DatabaseSessionService(
db_url=connection_string
)
session = await session_service.create_session(
app_name="test_app", session_id="test_session", user_id="test_user"
)
assert session is not None
sessions = await session_service.list_sessions(app_name="test_app", user_id="test_user")
assert len(sessions.sessions) > 0
session = await session_service.get_session(
app_name="test_app", session_id="test_session", user_id="test_user"
)
assert session is not None
await session_service.delete_session(
app_name="test_app", session_id="test_session", user_id="test_user"
)
assert (
await session_service.get_session(
app_name="test_app", session_id="test_session", user_id="test_user"
)
is None
)
```
The implementation have been also tested using the following configurations for llm provider and Runner:
```python
def get_azure_openai_model(deployment_id: str | None = None) -> LiteLlm:
...
if not deployment_id:
deployment_id = os.getenv("AZURE_OPENAI_DEPLOYMENT_ID")
logger.info(f"Using Azure OpenAI deployment ID: {deployment_id}")
return LiteLlm(
model=f"azure/{os.getenv('AZURE_OPENAI_DEPLOYMENT_ID')}",
stream=True,
)
...
@staticmethod
def _get_runner(agent: Agent) -> Runner:
storage=DatabaseSessionService(db_url=get_pg_connection_string())
return Runner(
agent=agent,
app_name=APP_NAME,
session_service=storage,
)
...
async for event in self.runner.run_async(
user_id=user_id,
session_id=session_id,
new_message=content,
run_config=(
RunConfig(
streaming_mode=StreamingMode.SSE, response_modalities=["TEXT"]
)
if stream
else RunConfig()
),
):
last_event = event
if stream:
yield event
...
```
## Breaking Changes
- Database connection string format may need updates for async drivers
Co-authored-by: Shangjie Chen <deanchen@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2889 from GitMarco27:feature/async_database_session_service e1b1b14934c1fb7975a6832cdd1549e94acab985
PiperOrigin-RevId: 830525148
The tool description now clarifies that `load_artifacts` should be called when a user uploads files, to make those artifacts accessible within the session.
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 830469802
The upper bound for the `fastapi` dependency is adjusted from `<1.119.0` to `<0.119.0`.
Close#3422
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 830465681
Update `_function_declaration_to_tool_param` to use `getattr` when accessing the `required` field within `function_declaration.parameters`. This prevents `AttributeError` when a `FunctionDeclaration`'s parameters schema does not include a `required` attribute
Close#2891
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 830225582
Merge https://github.com/google/adk-python/pull/3352
Replace send() method with send_realtime_input() to fix DeprecationWarning
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #2393
### Testing Plan
Have run unit test for test_live_request_queue.py
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
Summary :
tests/unittests/agents/test_live_request_queue.py::test_send_realtime PASSED [100%]
**Manual End-to-End (E2E) Tests:**
### 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.
- [ ] 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.
- [ ] Any dependent changes have been merged and published in downstream modules.
Tested both API variants.
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3352 from SanjaySiddharth:fix-dep-session.send b23b641a63ff20d1f2dbd9abd519f8facf0aab77
PiperOrigin-RevId: 830182844
Merge https://github.com/google/adk-python/pull/2875
related: https://github.com/google/adk-python/issues/2876
## Reason for this change:
Currently, there is no direct way to access the user_id from within agent contexts, plugins, or callbacks. This limitation prevents several important use cases:
1. **User-specific logging and tracing**: When debugging or monitoring agent behavior, it's crucial to associate actions with specific users for better observability.
2. **User-scoped operations**: Plugins and callbacks often need to perform user-specific operations, such as accessing user-specific resources or applying user-level configurations.
3. **Session management**: The user_id is a key component of session identification, but it's not accessible through the ReadonlyContext interface, requiring workarounds to access it.
## Changes made:
- Added a `user_id` property to the `ReadonlyContext` class in `src/google/adk/agents/readonly_context.py`
- The property exposes the user_id from the underlying invocation context as a readonly field
## Impact:
This change will:
- Enable plugins and callbacks to access the current user's ID directly through the context
- Improve logging and tracing capabilities by allowing user-specific tracking
- Simplify code that needs to perform user-scoped operations without requiring access to internal implementation details
- Maintain backward compatibility as this is an additive change
### Before:
- No direct way to access user_id from ReadonlyContext
### After:
```python
@property
def user_id(self) -> str:
"""The id of the user. READONLY field."""
return self._invocation_context.user_id
```
This is a non-breaking change that adds a new readonly property to the existing ReadonlyContext interface.
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2875 from ammmr:ammmr-add-user_id-property-to-readonly-context 771734ebf39cb0748a5dc826436236268fbb58f8
PiperOrigin-RevId: 830170908
The new Sqlite version has fixed schema and use a single column to store Event data, this should avoid DB migration for future add to the Event object.
- This change introduces `SqliteSessionService`, an asynchronous session service using `aiosqlite` that stores event data as JSON within SQLite.
- A migration script, `migrate_from_sqlalchemy_sqlite.py`, is included to transition data from the older SQLAlchemy-based SQLite schema to this new format.
- The CLI service registry is updated to use SqliteSessionService for sqlite:// URIs.
- Throw error when user trying to access a legacy DB and advice the user to do the migration.
Co-authored-by: Shangjie Chen <deanchen@google.com>
PiperOrigin-RevId: 829971174
NOTE:
- This is the expected behavior, so that SSE streaming and non-streaming behaviors are idential to each other in the persisted session.
- The underlying google_llm.py hasn't been fully comply with this behavior, which will be addressed in future changes.
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
PiperOrigin-RevId: 829878175
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
Merge https://github.com/google/adk-python/pull/2600
**Reason for this change:**
Currently, the detailed llm_request object is logged at the info level when connecting to the live API. This causes two main issues:
1. Excessive log output with large instructions: When instructions are large, the unstructured log output becomes problematic. Since the logs are not structured, any
newline characters in the instruction content cause each line to be output as a separate log entry, resulting in massive log output that floods the logging system.
2. Unnecessary verbosity in production: The detailed request information is primarily useful for debugging purposes and should not appear in standard info-level logs,
especially when connections are established frequently.
**Changes made:**
- Changed logger.info to logger.debug in src/google/adk/models/google_llm.py at line 294 for the live connection logging statement.
**Impact:**
This change will:
- Reduce log noise in production environments where info-level logging is enabled
- Keep the detailed connection information available when debug-level logging is needed for troubleshooting
- Improve log readability by showing only essential information at the info level
**Before:**
logger.info('Connecting to live with llm_request:%s', llm_request)
**After:**
logger.debug('Connecting to live with llm_request:%s', llm_request)
This is a non-breaking change that only affects logging verbosity.
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2600 from ammmr:ammmr-info-to-debug-connect-log 36eab157f5d5ca00b44ee6ad8a4e1aeec871600c
PiperOrigin-RevId: 829596092
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 trimmed schema includes only the fields relevant to agent shells, tool wiring, and common generation parameters, improving efficiency and focus.
The default model for the assistant has also been updated to "gemini-2.5-pro"
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 829513627
Merge https://github.com/google/adk-python/pull/3127
# What this PR does
This PR fixes a bug in the `execute_sql function` within `bigquery/query_tool.py`. The bug caused an error when executing queries that do not return a result set, such as a `CREATE TEMP FUNCTION` statement.
# The problem
Within `execute_sql,` when a user executed a query that doesn't produce a result set, like the following:
```sql
CREATE TEMP FUNCTION f() AS (0); SELECT f();
```
The corresponding BigQuery job object would have its `destination` property set to `None`. This caused an error because the code was written with the expectation of a valid destination table.
# The solution
The fix modifies `execute_sql` to check if the `query_job.destination` is None. If it is, the function correctly identifies the query as a statement that doesn't require a destination and allows it to complete successfully.
This ensures that `execute_sql` can robustly handle these types of queries.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3127 from na0fu3y:patch-1 69218a8d25699dfa2e18bb305087f01192e91e91
PiperOrigin-RevId: 829270885
This change adds a debug log statement to output the function response IDs and the event list when a matching function call event is not found, which helps in debugging.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 829059186
Capture the function call ID from events and use it to populate the `function_response.id` in subsequent user messages, enabling recording and replaying of test cases involving long-running tools.
Co-authored-by: Liang Wu <wuliang@google.com>
PiperOrigin-RevId: 829042356
Add `_to_litellm_response_format` to convert ADK's `response_schema` types (Pydantic models, JSON schema dicts) into the format needed by LiteLLM for JSON object/schema constraints
Close#1967
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 829037987
In `gemini_llm_connection.py`, accumulate partial transcription texts and emit `LlmResponse` with `partial=True` for each chunk. When the transcription is marked as `finished`, emit a final `LlmResponse` with the full accumulated text and `partial=False`.
In `runners.py`, modify `_should_append_to_history` to only add transcription events to the history when they are fully finished, preventing partial transcriptions from being added.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 829029715
This is about 35% decrease. This change refactors several ADK modules to import `vertexai` and its submodules only when they are first used, rather than at the top of the file. This improves module load times by avoiding unnecessary imports of large dependencies. Imports are also placed within `if TYPE_CHECKING:` blocks where appropriate.
Co-authored-by: Liang Wu <wuliang@google.com>
PiperOrigin-RevId: 829017293
This accounts for about 8% of latency in cold start, because DatabaseSessionService imports from sqlalchemy. After the change, DatabaseSessionService is only imported if it's really needed by the program. The other objects in this file are not affected because they contribute to a small fraction of the latency.
Co-authored-by: Liang Wu <wuliang@google.com>
PiperOrigin-RevId: 829009868
Merge https://github.com/google/adk-python/pull/3324
**Problem:**
ADK seems to not pass output/input transcription `finished` flag from the Gemini.
**Solution:**
Relaxation of checking conditions of valid llm_response for input/output transcription.
### Testing Plan
Unit test `test_receive_transcript_finished` checks if input/output transcription message with no text but `finished` flag is received.
**Unit Tests:**
- [x] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
<img width="785" height="373" alt="image" src="https://github.com/user-attachments/assets/6d870e9f-1372-4808-91a9-38578c1b3729" />
**Manual End-to-End (E2E) Tests:**
Configure Gemini Agent to produce input & output transcriptions. Observe incoming transcript messages - to see if the finished flag appears at the end agents & users statement.
### 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.
### Additional context
The mentioned `finished` flag can be obtained in native Gemini APIs like via Websocket but not via ADK.
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3324 from ChrisQlasty:fix/transcript_finish e7b8e5e5f5fac1d2dfd495f2dbadb19ed4328b0c
PiperOrigin-RevId: 828987996
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
The `_run_compaction_default` method is no longer called and can be safely removed.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 828760157
Merge https://github.com/google/adk-python/pull/3403
This PR corrects misspellings identified by the [check-spelling action](https://github.com/marketplace/actions/check-spelling)
Note: while I use tooling to identify errors, the tooling doesn't _actually_ provide the corrections, I'm picking them on my own. I'm a human, and I may make mistakes.
### Testing Plan
The misspellings have been reported at https://github.com/jsoref/adk-python/actions/runs/19056081305/attempts/1#summary-54426435973
The action reports that the changes in this PR would make it happy: https://github.com/jsoref/adk-python/actions/runs/19056081446/attempts/1#summary-54426436321
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [ ] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### 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.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
### Additional context
- https://github.com/google/adk-python/pull/3382#issuecomment-3488654110
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3403 from jsoref:spelling-markdown 432b7ded3bddfe4a1d8127c50fd7a001f19bda83
PiperOrigin-RevId: 828754459
Merge https://github.com/google/adk-python/pull/2582
Relate to #3306
## Description
Fixes issues #6 and #1785 where ADK commands crash on Windows due to symlink creation requiring admin privileges.
## Problem
On Windows, running ADK commands (like `adk run`) fails with `OSError: [WinError 1314] A required privilege is not held by the client: ...` because the logging system attempts to create a symlink for the latest log file. Windows requires administrator privileges for symlink creation by default (unless Developer Mode is enabled), causing crashes for non-admin users.
## Root Cause
The issue was in [`logs.py`](https://github.com/google/adk-python/blob/main/src/google/adk/cli/utils/logs.py#L72) where `os.symlink()` was called unconditionally without error handling, causing the entire CLI to crash when symlink creation failed.
## Solution
This PR implements graceful symlink handling. Changes made:
- Extracted symlink creation into separate function with error handling
- Added graceful fallback when symlink creation fails
- Replaced crashes with warnings to keep CLI functional
- Improved user messaging about log file locations
This solution follows a similar pattern to the one used in [ROS2](https://github.com/ros2) in its [logging module](https://github.com/ros2/launch/blob/rolling/launch/launch/logging/__init__.py#L93).
## Testing
### Before (broken)
```bash
> adk run my_agent
Log setup complete: C:\Users\username\AppData\Local\Temp\agents_log\agent.20250817_215119.log
Traceback (most recent call last):
File "google\adk\cli\utils\logs.py", line 72, in log_to_tmp_folder
os.symlink(log_filepath, latest_log_link)
OSError: [WinError 1314] A required privilege is not held by the client
```
### After (fixed)
```bash
> adk run my_agent
Log setup complete: C:\Users\username\AppData\Local\Temp\agents_log\agent.20250817_215319.log
UserWarning: Cannot create symlink for latest log file: [WinError 1314] A required privilege is not held by the client
To access latest log: tail -F C:\Users\username\AppData\Local\Temp\agents_log\agent.20250817_215319.log
Running agent my_agent, type exit to exit.
```
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2582 from lorenzofavaro:fix/windows-symlink-permissions 1e99a6287994f1bfd9ac11550d3dc06205998df5
PiperOrigin-RevId: 828690483
Merge https://github.com/google/adk-python/pull/3382
This PR corrects misspellings identified by the [check-spelling action](https://github.com/marketplace/actions/check-spelling)
Note: while I use tooling to identify errors, the tooling doesn't _actually_ provide the corrections, I'm picking them on my own. I'm a human, and I may make mistakes.
### Testing Plan
The misspellings have been reported at https://github.com/jsoref/adk-python/actions/runs/19056081305/attempts/1#summary-54426435973
The action reports that the changes in this PR would make it happy: https://github.com/jsoref/adk-python/actions/runs/19056081446/attempts/1#summary-54426436321
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [ ] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### 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.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
### Additional context
- follow-up to #2447
Co-authored-by: Hangfei Lin <hangfei@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3382 from jsoref:spelling 3df5932e97391c437e1638d7163e5e3d5c52d5c3
PiperOrigin-RevId: 828686941
Merge https://github.com/google/adk-python/pull/3394
This PR corrects misspellings identified by the [check-spelling action](https://github.com/marketplace/actions/check-spelling)
Note: while I use tooling to identify errors, the tooling doesn't _actually_ provide the corrections, I'm picking them on my own. I'm a human, and I may make mistakes.
### Testing Plan
The misspellings have been reported at https://github.com/jsoref/adk-python/actions/runs/19056081305/attempts/1#summary-54426435973
The action reports that the changes in this PR would make it happy: https://github.com/jsoref/adk-python/actions/runs/19056081446/attempts/1#summary-54426436321
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [ ] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### 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.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
### Additional context
- https://github.com/google/adk-python/pull/3382#issuecomment-3488654110
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3394 from jsoref:spelling-contributing c3d5e342c4350f7cae9f8f0c6638b176f2e30e80
PiperOrigin-RevId: 828659867
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
Merge https://github.com/google/adk-python/pull/3411
## Summary
Fixes AgentTool cleanup to prevent MCP session errors by calling `runner.close()` after sub-agent execution.
## Problem
When using AgentTool with MCP tools, the runner cleanup happened during garbage collection in a different async task context, causing:
```
RuntimeError: Attempted to exit cancel scope in a different task than it was entered in
```
## Solution
- Call `await runner.close()` immediately after sub-agent execution in AgentTool
- This ensures MCP sessions and other resources are cleaned up in the correct async task context
- Updated test mock to include the close() method
## Demo Agents
Added two comprehensive demo agents showing how to use AgentTool with MCP tools:
### mcp_in_agent_tool_remote (SSE mode)
- Uses HTTP/SSE connection to remote MCP server
- Zero-installation setup with `uvx`
- Demonstrates server-side MCP deployment pattern
### mcp_in_agent_tool_stdio (stdio mode)
- Uses subprocess connection with automatic server launch
- Fully automatic setup with `uvx` subdirectory syntax
- Demonstrates embedded MCP deployment pattern
Both demos:
- Use Gemini 2.5 Flash
- Include example prompts for JSON Schema exploration
- Have comprehensive READMEs with architecture diagrams
- Follow ADK agent structure conventions
## Testing
- ✅ All existing unit tests pass
- ✅ Manual testing with both SSE and stdio modes
- ✅ Verified cleanup happens in correct async context
- ✅ No more cancel scope errors with MCP tools
## Related
- Fixes#1112
- Related to #929
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3411 from google:fix/agent-tool-mcp-cleanup 9ae753b5a4
PiperOrigin-RevId: 828651896
Currently ADK web hangs and logs "AGSI callable returned without completing response" when the server is unreachable. To fix, set timeouts for connecting to server.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 828648928
- add FileArtifactService that persists artifacts to the local filesystem
- adjust BaseArtifactService and exports so callers can wire in the filebacked implementation
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 828629298
Replace the full JSON schema dump with a compact text summary of key AgentConfig components like LlmAgent, ToolConfig, and GenerateContentConfig
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 828627911
Merge https://github.com/google/adk-python/pull/3407
This PR corrects misspellings identified by the [check-spelling action](https://github.com/marketplace/actions/check-spelling)
Note: while I use tooling to identify errors, the tooling doesn't _actually_ provide the corrections, I'm picking them on my own. I'm a human, and I may make mistakes.
### Testing Plan
The misspellings have been reported at https://github.com/jsoref/adk-python/actions/runs/19056081305/attempts/1#summary-54426435973
The action reports that the changes in this PR would make it happy: https://github.com/jsoref/adk-python/actions/runs/19056081446/attempts/1#summary-54426436321
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [ ] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### 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.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
### Additional context
- https://github.com/google/adk-python/pull/3382#issuecomment-3488654110
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3407 from jsoref:spelling-issue-template ce8febc6ab5368640c0ec2ae5d6a2c8ac5bf8ed6
PiperOrigin-RevId: 828610865
The blob content is often large and binary, which makes the logs unreadable and can cause excessive logging.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 828523413
The sample agent now uses updated model names for Gemini Live, including a new Vertex model as the default and a new AI Studio model option.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 828515811
Merge https://github.com/google/adk-python/pull/3381
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #3363
- This PR sets a max column width for the table printed in detailed output of agent evaluations.
**Problem:**
The detailed output of agent evaluations is not readable due to rows in the table getting wrapped. This happens when there are long text values in cells.
<img width="1904" height="717" alt="508807185-9e8fe1c3-d04a-43dd-acf9-0befaa1b247d" src="https://github.com/user-attachments/assets/61526ad2-8a9e-4c18-83e2-51a3b9b32d2b" />
**Solution:**
Existing code uses `tabulate` python package to format the table. We can set a maximum column width using `maxcolwidths` parameter. I have set it to `25`.
After the fix:
<img width="1882" height="711" alt="508810179-b91c5bca-fb43-480b-90ff-bca2e909417c" src="https://github.com/user-attachments/assets/b653f825-719e-4101-9acb-e28a52694cf8" />
### Testing Plan
I have manually tested if the output is properly displayed after changes. Please let me know if any unit tests can be added for this.
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
<img width="1627" height="39" alt="image" src="https://github.com/user-attachments/assets/59a70619-3669-4113-8ab7-dcff130ee241" />
**Manual End-to-End (E2E) Tests:**
1. Create a simple agent using adk (preferably an agent that outputs a long text).
2. Create an evalset for this agent.
3. Run the evalset with `print_detailed_results` option and check if the output is properly displayed.
If you want a quick setup for testing this, I have a sample repo with an agent and an evalset [here](https://github.com/nimanthadilz/adk-test/tree/reproduce-print-detailed-results). You will have to manually build & install the fixed adk version to test it.
### 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.
- [ ] 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.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3381 from nimanthadilz:fix-eval-output-rows-wrapping-issue f6d40121f621df60c4596a1c62e0c54e4da309d3
PiperOrigin-RevId: 828265715
Merge https://github.com/google/adk-python/pull/2651
### Summary
Correct a misspelling in the build configuration:
- "swtich" → "switch" in `pyproject.toml`.
### Rationale
This is a spelling fix only. It improves readability and avoids potential confusion in configuration.
There is no impact on runtime behavior, tests, or public APIs.
### Notes
- Follows Conventional Commits style for build/config changes (`build:`).
- CLA status should be green via the Google CLA bot.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2651 from marsboy02:docs/fix-type-pyproject b78c014c864b1a143ffc157c7a8c807f5f19d31d
PiperOrigin-RevId: 828221776
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
Add support for MCP prompts via the McpInstructionProvider class, which can be specified as an agent's instruction.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 828166051
Users were getting spammed with this log even though their tools didn't require authentication. To fix, reduce the log level to DEBUG so that it doesn't show up by default.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 828161281
This change introduces a new section in the README.md to highlight the `adk-python-community` GitHub repository, describing it as a place for community-contributed tools and integrations.
Co-authored-by: Hangfei Lin <hangfei@google.com>
PiperOrigin-RevId: 828155205
Populate the usage_metadata field for live events with the metadata provided by the Gemini live API.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 828124232
This lets users to specify `drop_params` when initializing `LiteLlm`, which will be forwarded to LiteLLM's `acompletion` or `completion` calls
Close#1718
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 828058105
LiteLLM providers can extract the MIME type from the data URI. Removing the separate `format` field avoids redundancy and potential issues with backends that may reject requests containing this field.
Close#2017
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 828014286
ARIMA supports both historical data and future data anomaly detection. This CL add how the tool support future table anomaly detection.
PiperOrigin-RevId: 827803748
Merge https://github.com/google/adk-python/pull/3365
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
fix typo for several files.
### 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.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] 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.
### Additional context
_Add any other context or screenshots about the feature request here._
Co-authored-by: Liang Wu <wuliang@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3365 from UlookEE:fix_typo 1469de4ea354d1c205268b999183ee86c9d6a1d5
PiperOrigin-RevId: 827724001
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
Merge https://github.com/google/adk-python/pull/2326
`adk run --help` (adk 1.9.0)
```
--resume FILE The json file that contains a previously saved session
(by--save_session option). The previous session will be
re-displayed. And user can continue to interact with the
agent.
```
## testing plan
N/A (because this is a simple string correction)
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2326 from ftnext:fix-typo-run-help-resume a896fa38e223b13e7edd8125d7b38139f1ca3712
PiperOrigin-RevId: 827311506
This fixes MCP authentication for gcloud service accounts. Previously it was failing to authenticate tool calls.
Co-authored-by: Kathy Wu <wukathy@google.com>
PiperOrigin-RevId: 826639044
Merge https://github.com/google/adk-python/pull/3345
Add run_debug() helper method to InMemoryRunner that reduces agent execution boilerplate from 7-8 lines to just 2 lines, making it ideal for quick experimentation, notebooks, and getting started with ADK.
**Key changes:**
• Introduce run_debug() to reduce boilerplate from 7-8 lines to 2 lines
• Enable quick testing in notebooks, REPL, and during development
• Support single or multiple messages with automatic session management
• Add verbose flag to show/hide tool calls and intermediate processing
• Add quiet flag to suppress console output while capturing events
• Extract event printing logic to reusable utility (utils/_debug_output.py)
• Include comprehensive test suite with 21 test cases covering all part types
• Provide complete working example with 8 usage patterns
• **This is a convenience method for experimentation, not a replacement for run_async()**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
* N/A - New feature to improve developer experience
**2. Or, if no issue exists, describe the change:**
**Problem:**
Developers need to write 7-8 lines of boilerplate code just to test a simple agent interaction during development. This creates friction for:
* New developers getting started with ADK
* Quick experimentation in Jupyter notebooks or Python REPL
* Debugging agent behavior during development
* Writing examples and tutorials
* Rapid prototyping of agent capabilities
**Solution:**
Introduce `run_debug()` as a convenience helper method specifically designed for quick experimentation and getting started scenarios. This method:
* **Is NOT a replacement for `run_async()`** - it's a developer convenience tool
* **Reduces boilerplate** from 7-8 lines to just 2 lines for simple testing
* **Handles session management automatically** with sensible defaults
* **Provides debugging visibility** with optional verbose flag for tool calls
* **Supports common patterns** like multiple messages and event capture
* **Type-safe implementation** using direct attribute access instead of getattr()
### Before vs After Comparison
**BEFORE - Current approach requires 7-8 lines of boilerplate:**
```python
from google.adk import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.genai import types
# Define a simple agent
agent = Agent(
model="gemini-2.5-flash",
instruction="You are a helpful assistant"
)
# Need all this boilerplate just to test the agent
APP_NAME = "default"
USER_ID = "default"
session_service = InMemorySessionService()
runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service)
session = await session_service.create_session(
app_name=APP_NAME, user_id=USER_ID, session_id="default"
)
content = types.Content(role="user", parts=[types.Part.from_text("Hello")])
async for event in runner.run_async(
user_id=USER_ID, session_id=session.id, new_message=content
):
if event.content and event.content.parts:
print(event.content.parts[0].text)
```
**AFTER - With run_debug() helper, just 2 lines:**
```python
from google.adk import Agent
from google.adk.runners import InMemoryRunner
# Define the same agent
agent = Agent(
model="gemini-2.5-flash",
instruction="You are a helpful assistant"
)
# Test it with just 2 lines!
runner = InMemoryRunner(agent=agent)
await runner.run_debug("Hello")
```
### API Design
```python
async def run_debug(
self,
user_messages: str | list[str],
*,
user_id: str = 'debug_user_id',
session_id: str = 'debug_session_id',
run_config: RunConfig | None = None,
quiet: bool = False,
verbose: bool = False,
) -> list[Event]:
```
**Parameters:**
* `user_messages`: Single message string or list of messages (required)
* `user_id`: User identifier (default: 'debug_user_id')
* `session_id`: Session identifier for conversation continuity (default: 'debug_session_id')
* `run_config`: Optional advanced configuration
* `quiet`: Suppress console output (default: False)
* `verbose`: Show detailed tool calls and responses (default: False)
**Key Features:**
* **Always returns events** - Simplifies API, no conditional return type
* **Type-safe implementation** - Uses direct attribute access on Pydantic models
* **Text buffering** - Consecutive text parts printed without repeated author prefix
* **Smart truncation** - Long tool args/responses truncated for readability
* **Clean session management** - Get-then-create pattern, no try/except
* **Reusable printing logic** - Extracted to utils/_debug_output.py for other tools
### Implementation Highlights
**1. Event Printing Utility (utils/_debug_output.py):**
* Modular print_event() function for displaying events
* Text buffering to combine consecutive text parts
* Configurable truncation for different content types:
- Function args: 50 chars max
- Function responses: 100 chars max
- Code output: 100 chars max
* Supports all ADK part types (text, function_call, executable_code, inline_data, file_data)
**2. Session Management:**
```python
# Clean get-then-create pattern (no try/except)
session = await self.session_service.get_session(
app_name=self.app_name, user_id=user_id, session_id=session_id
)
if not session:
session = await self.session_service.create_session(
app_name=self.app_name, user_id=user_id, session_id=session_id
)
```
**3. Type-Safe Event Processing:**
* Direct attribute access on Pydantic models (no getattr() or hasattr())
* Proper handling of all part types
* Leverages `from __future__ import annotations` for duck typing
### Important Note on Scope
`run_debug()` is a **convenience method for experimentation only**. For production applications requiring:
* Custom session services (Spanner, Cloud SQL)
* Fine-grained event processing control
* Error recovery and resumability
* Performance optimization
* Complex authentication flows
Continue using the standard `run_async()` method. The `run_debug()` helper is specifically designed to lower the barrier to entry and speed up the development/testing cycle.
### Testing Plan
**Unit Tests (21 test cases in tests/unittests/runners/test_runner_debug.py):**
**Core functionality (7 tests):**
* ✅ Single message execution and event return
* ✅ Multiple messages in sequence
* ✅ Quiet mode (suppresses output)
* ✅ Custom session_id configuration
* ✅ Custom user_id configuration
* ✅ RunConfig passthrough
* ✅ Session persistence across calls
**Part type handling (8 tests):**
* ✅ Tool calls and responses (verbose mode)
* ✅ Executable code parts
* ✅ Code execution result parts
* ✅ Inline data (images)
* ✅ File data references
* ✅ Mixed part types in single event
* ✅ Long output truncation
* ✅ Verbose flag behavior (show/hide tools)
**Edge cases (6 tests):**
* ✅ None text filtering
* ✅ Existing session handling
* ✅ Empty parts list
* ✅ None event content
* ✅ Verbose=False hides tool calls
* ✅ Verbose=True shows tool calls
**All 21 tests passing in 3.8s** ✓
**Manual End-to-End (E2E) Tests:**
Tested all 8 example patterns in contributing/samples/runner_debug_example/main.py:
1. ✅ Minimal 2-line usage
2. ✅ Multiple sequential messages
3. ✅ Session persistence across calls
4. ✅ Multiple user sessions (Alice & Bob)
5. ✅ Verbose mode for tool visibility
6. ✅ Event capture with quiet mode
7. ✅ Custom RunConfig integration
8. ✅ Before/after comparison
### Files Changed
**Core implementation:**
* src/google/adk/runners.py - Added run_debug() method (~60 lines)
* src/google/adk/utils/_debug_output.py - Event printing utility (~106 lines)
**Tests:**
* tests/unittests/runners/test_runner_debug.py - Comprehensive test suite (21 tests)
**Examples:**
* contributing/samples/runner_debug_example/agent.py - Sample agent with tools
* contributing/samples/runner_debug_example/main.py - 8 usage examples
* contributing/samples/runner_debug_example/README.md - Complete documentation
### 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 (21/21 passing)
- [x] I have manually tested my changes end-to-end (8 examples tested)
- [x] Code follows ADK style guide (relative imports, type hints, 2-space indentation)
- [x] Ran ./autoformat.sh before committing
- [x] Any dependent changes have been merged and published in downstream modules
### Additional Context
**Example with Tools (verbose mode):**
```python
# Create agent with tools
agent = Agent(
model="gemini-2.5-flash",
instruction="You can check weather and do calculations",
tools=[get_weather, calculate]
)
# Test with verbose to see tool calls
runner = InMemoryRunner(agent=agent)
await runner.run_debug("What's the weather in SF?", verbose=True)
# Output:
# User > What's the weather in SF?
# agent > [Calling tool: get_weather({'city': 'San Francisco'})]
# agent > [Tool result: {'result': 'Foggy, 15°C (59°F)'}]
# agent > The weather in San Francisco is foggy, 15°C (59°F).
```
**Complete Example Included:**
The PR includes a full working example in `contributing/samples/runner_debug_example/` with:
* Agent with weather and calculator tools
* 8 different usage patterns
* Comprehensive README with troubleshooting
* Safe AST-based expression evaluation
**Breaking Changes:** None - this is purely additive.
**Security:** Example uses AST-based expression evaluation instead of eval().
**Code Quality:**
* Type-safe implementation (no getattr() or hasattr())
* Modular design (printing logic separated into utility)
* Follows ADK conventions (relative imports, from __future__ import annotations)
* Comprehensive error handling (gracefully handles None content, empty parts)
* Well-documented with docstrings and inline comments
END_PUBLIC
```
---
## Key Changes from Original:
1. ✅ Updated parameter name: `user_queries` → `user_messages`
2. ✅ Updated parameter name: `session_name` → `session_id`
3. ✅ Updated parameter name: `print_output` → `quiet`
4. ✅ Removed `return_events` parameter
5. ✅ Updated test count: 23 → 21
6. ✅ Changed "queries" → "messages" throughout
7. ✅ Added implementation highlights section
8. ✅ Added details about utils/_debug_output.py
9. ✅ Updated default values to debug_user_id/debug_session_id
10. ✅ Noted type-safe implementation
11. ✅ Added Code Quality section
12. ✅ Updated API signature to match final refactored version
13. ✅ Removed optional return type (always returns list[Event])
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3345 from lavinigam-gcp:adk-runner-helper e0050b9f152d0f0e49e6501610d2c59a754fc571
PiperOrigin-RevId: 826607817
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
This change adds an optional `runner` parameter to the `to_a2a` function, enabling users to provide a pre-configured `Runner` instance instead of always using the default in-memory services. A new test case has been added to verify this functionality.
closes#3104
Co-authored-by: Dongyu Jia <dongyuj@google.com>
PiperOrigin-RevId: 826526861
This change introduces a sample (`migration_session_db`) demonstrating how to load a session database created with an older version of ADK (e.g., 1.15.0) and make it compatible with the current version. It includes a script (`db_migration.sh`) to alter the SQLite schema automatically. to_event is updated to handle potential discrepancies in pickled `EventActions` by using `model_copy` to ensure compatibility with the latest `EventActions` model definition.
Related to #3272#3197, Closes#3197#3272
Co-authored-by: Dongyu Jia <dongyuj@google.com>
PiperOrigin-RevId: 826524368
It is common for expected response and expected tool calls column to be empty for user simulated conversations. So, we don't render those.
Co-authored-by: Ankur Sharma <ankusharma@google.com>
PiperOrigin-RevId: 826202867
Previously we only do a simple prefix string matching, thus `agent_00` will match with `agent_0`
With this new change, we either check directly equality, or must expect seeing `agent_0.`. See added test for branches we now match / skip.
TBF `.` is also not a perfect delimiter (I would imagine users might put dot in agent names). We might consider a follow up that bans such agent names.
Tested with script in the linked issue (I updated prompt so we see which agent they see from):
Before:
```
[agent_8]: 73
[agent_0]: 97
[agent_1]: 73
[agent_5]: 97
[agent_4]: 73
[agent_2]: 73
[agent_3]: 73
[agent_9]: 93
[agent_6]: 73
[agent_7]: 1
[agent_70]: 1 (agent_7)
[agent_20]: 73 (agent_2)
[agent_30]: 73 (agent_3)
[agent_00]: 97 (agent_0)
[agent_40]: 73 (agent_4)
[agent_80]: 73 (agent_8)
[agent_50]: 97 (agent_5)
[agent_90]: 93 (agent_9)
[agent_10]: 73 (agent_1)
[agent_60]: 73 (agent_6)
```
After:
```
[agent_9]: 73
[agent_6]: 73
[agent_2]: 73
[agent_7]: 93
[agent_4]: 73
[agent_1]: 73
[agent_3]: 73
[agent_5]: 97
[agent_0]: 73
[agent_8]: 87
[agent_50]: 0
[agent_80]: 0
[agent_10]: 0
[agent_90]: 0
[agent_30]: 0
[agent_20]: 0
[agent_60]: 0
[agent_00]: 0
[agent_40]: 0
[agent_70]: 0
```
Closes#2948
Co-authored-by: Kevin Qian <kqian@google.com>
PiperOrigin-RevId: 826187198
Merge https://github.com/google/adk-python/pull/3219
## Summary
Enhance error messages for tool and agent not found errors to provide actionable guidance and reduce developer debugging time from hours to minutes.
Fixes#3217
## Changes
### Modified Files
1. **`src/google/adk/flows/llm_flows/functions.py`**
- Enhanced `_get_tool()` error message with:
- Available tools list (formatted, truncated to 20 for readability)
- Possible causes
- Suggested fixes
- Fuzzy matching suggestions
2. **`src/google/adk/agents/llm_agent.py`**
- Enhanced `__get_agent_to_run()` error message with:
- Available agents list (formatted, truncated to 20 for readability)
- Timing/ordering issue explanation
- Fuzzy matching for agent names
- Added `_get_available_agent_names()` helper method
### New Test Files
3. **`tests/unittests/flows/llm_flows/test_functions_error_messages.py`**
- Tests for enhanced tool not found error messages
- Fuzzy matching validation
- Edge cases (no close matches, empty tools dict, 100+ tools)
4. **`tests/unittests/agents/test_llm_agent_error_messages.py`**
- Tests for enhanced agent not found error messages
- Agent tree traversal validation
- Fuzzy matching for agents
- Long list truncation
## Testing Plan
### Unit Tests
```bash
pytest tests/unittests/flows/llm_flows/test_functions_error_messages.py -v
pytest tests/unittests/agents/test_llm_agent_error_messages.py -v
```
**Results**: ✅ 8/8 tests passing
```
tests/unittests/flows/llm_flows/test_functions_error_messages.py::test_tool_not_found_enhanced_error PASSED
tests/unittests/flows/llm_flows/test_functions_error_messages.py::test_tool_not_found_fuzzy_matching PASSED
tests/unittests/flows/llm_flows/test_functions_error_messages.py::test_tool_not_found_no_fuzzy_match PASSED
tests/unittests/flows/llm_flows/test_functions_error_messages.py::test_tool_not_found_truncates_long_list PASSED
tests/unittests/agents/test_llm_agent_error_messages.py::test_agent_not_found_enhanced_error PASSED
tests/unittests/agents/test_llm_agent_error_messages.py::test_agent_not_found_fuzzy_matching PASSED
tests/unittests/agents/test_llm_agent_error_messages.py::test_agent_tree_traversal PASSED
tests/unittests/agents/test_llm_agent_error_messages.py::test_agent_not_found_truncates_long_list PASSED
8 passed, 1 warning in 4.38s
```
### Example Enhanced Error Messages
#### Before (Current Error)
```
ValueError: Function get_equipment_specs is not found in the tools_dict: dict_keys(['get_equipment_details', 'query_vendor_catalog', 'score_proposals'])
```
#### After (Enhanced Error)
```
Function 'get_equipment_specs' is not found in available tools.
Available tools: get_equipment_details, query_vendor_catalog, score_proposals
Possible causes:
1. LLM hallucinated the function name - review agent instruction clarity
2. Tool not registered - verify agent.tools list
3. Name mismatch - check for typos
Suggested fixes:
- Review agent instruction to ensure tool usage is clear
- Verify tool is included in agent.tools list
- Check for typos in function name
Did you mean one of these?
- get_equipment_details
```
## Community Impact
- **Addresses 3 active issues**: #2050, #2933 (12 comments), #2164
- **Reduces debugging time** from 3+ hours to < 5 minutes (validated in production multi-agent RFQ solution for recent partner nanothon initiative)
- **Improves developer experience** for new ADK users
## Implementation Details
- Uses standard library `difflib` for fuzzy matching (no new dependencies)
- Error path only (no performance impact on happy path)
- Measured performance: < 0.03ms per error
- Truncates long lists to first 20 items to prevent log overflow
- Fully backward compatible (same exception types)
## Checklist
- [x] Unit tests added and passing (8/8 tests)
- [x] Code formatted with `./autoformat.sh` (isort + pyink)
- [x] No new dependencies (uses standard library `difflib`)
- [x] Docstrings updated
- [x] Tested with Python 3.11
- [x] Issue #3217 created and linked
## Related Issues
- Fixes#3217
- Addresses #2050 - Tool verification callback request
- Addresses #2933 - How to handle "Function is not found in the tools_dict" Error
- Addresses #2164 - ValueError: {agent} not found in agent tree
---
**Note**: For production scenarios where LLM tool hallucinations occur, ADK's built-in [`ReflectAndRetryToolPlugin`](https://github.com/google/adk-python/blob/main/src/google/adk/plugins/reflect_retry_tool_plugin.py) can automatically retry failed tool calls (available since v1.16.0). This PR's enhanced error messages complement that by helping developers quickly identify and fix configuration issues during development.
Cheers, JP
Co-authored-by: Yvonne Yu <yyyu@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3219 from jpantsjoha:feat/better-error-messages a4df8bfb031685dce9e528d8eb7006f53447b75b
PiperOrigin-RevId: 826132579
Make sure _add_instructions_to_user_content skips over user messages that carry function_response parts so tool_use/tool_result blocks stay together
Close#3229
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 826076141
Include a manual mode for testing first and will remove after verifying it works.
When a commit with `Merge https://github.com/google/adk-python/pull/3333` in description is pushed by copybara, the workflow will automatically close the PR.
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
PiperOrigin-RevId: 826058313
Remove validation for output_schema and agent transfer flags.
The check that prevented `output_schema` from co-existing with agent transfer capabilities (`disallow_transfer_to_parent` or `disallow_transfer_to_peers` being False) has been removed. The agent will no longer automatically set these transfer flags to True when `output_schema` is present.
Co-authored-by: Ieva Grublyte <ievagrublyte@google.com>
PiperOrigin-RevId: 825998224
Merge https://github.com/google/adk-python/pull/3282
The `process_bind_param` and `process_result_value` methods in the `DynamicPickleType` class have been modified to handle MySQL dialect in addition to Spanner. This change ensures that pickled values are correctly processed for both database types.
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #3283
**2. Or, if no issue exists, describe the change:**
_If applicable, please follow the issue templates to provide as much detail as
possible._
**Problem:**
When using `DatabaseSessionService` with MySQL backend in google-adk v1.17.0, the application crashes with the following error: app.resources.runner:event_generator:260 - Error in event_generator: (builtins.TypeError) 'tuple' object cannot be interpreted as an integer
<img width="1237" height="129" alt="image" src="https://github.com/user-attachments/assets/0a5fc223-600a-4a92-8443-4d37fb1267f6" />
Root cause: The `DynamicPickleType` class in `database_session_service.py` configures MySQL dialect to use `LONGBLOB` for storing pickled data (line 117-118), but the `process_bind_param` and `process_result_value` methods only handle pickle serialization/deserialization for Spanner dialect, not MySQL. This causes MySQL to attempt storing raw Python objects instead of pickled bytes, leading to serialization errors and potential data corruption.
**Solution:**
Added MySQL to the pickle serialization logic in both `process_bind_param` and `process_result_value` methods, treating it the same way as Spanner dialect. This ensures that:
- Data is properly pickled to bytes before being stored in MySQL's LONGBLOB column
- Data is properly unpickled when retrieved from the database
- No breaking changes to existing functionality for other dialects (SQLite, PostgreSQL)
### Testing Plan
_Please describe the tests that you ran to verify your changes. This is required
for all PRs that are not small documentation or typo fixes._
**Unit Tests:**
- [x] I have added or updated unit tests for my change.
- [x] All unit tests pass locally.
**Summary of `pytest` results:**
<img width="929" height="306" alt="image" src="https://github.com/user-attachments/assets/3d548b96-ac49-4101-8405-a289a722293c" />
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### 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.
### Additional context
_Add any other context or screenshots about the feature request here._
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3282 from hung12ct:fix/mysql-pickle-serialization d9df37adb7dfbbfd8502a0fe65c4f8bca3d0d978
PiperOrigin-RevId: 825834360
This CL introduces a new tool, get_job_info, to the BigQuery toolset. This tool allows retrieving metadata about a BigQuery job, such as slot usage, job configuration, statistics, and job status.
Closes#2928
Co-authored-by: Dongyu Jia <dongyuj@google.com>
PiperOrigin-RevId: 825762399
Session input file contains fields that are needed to run evals and later be able retrieve the session generated by them.
Co-authored-by: Ankur Sharma <ankusharma@google.com>
PiperOrigin-RevId: 825742522
We also change VertexAiSessionService and VertexAiMemoryBankService to both use keyword arguments for project, location, agent engine id, and express mode api key
PiperOrigin-RevId: 825719331
Merge https://github.com/google/adk-python/pull/3333
## Summary
Add ignore patterns for popular AI coding assistant configuration files to prevent committing developer-specific settings. This aligns with the project's approach of providing `AGENTS.md` as a general starting point that developers can symlink or copy and customize locally.
## Changes
Added `.gitignore` patterns for 10 popular AI coding tools:
- **Claude Code** - `.claude/`, `CLAUDE.md`
- **Cursor** - `.cursor/`, `.cursorrules`, `.cursorignore`
- **Windsurf** - `.windsurfrules`
- **Aider** - `.aider*`
- **Continue.dev** - `.continue/`
- **Codeium** - `.codeium/`
- **GitHub Next** - `.githubnext/`
- **Roo Code** - `.roo/`, `.rooignore`
- **Bolt** - `.bolt/`
- **v0** - `.v0/`
## Rationale
Each developer may want different AI tool configurations and personal instructions. By ignoring these files, we:
- Prevent accidental commits of personal AI assistant settings
- Keep the repository clean of developer-specific configurations
- Allow developers to customize their AI tools without affecting others
- Maintain consistency with the project's `AGENTS.md` approach
Co-authored-by: Yvonne Yu <yyyu@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3333 from google:chore/ignore-ai-tool-configs 0abe4ccdf130ac93c3d2c353556f0ce7c305c429
PiperOrigin-RevId: 825682646
Usage: you can create symlink to AGENTS.md with the file name required by the specific AI coding tool.
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
PiperOrigin-RevId: 825627185
Previously this will return true for events yielded from before_agent_callback when there are state changes.
Note with this change, it will also return false for state delta only callbacks even after main response, but this is fine as long as the actual final response event has it to be true.
Closes#2992
PiperOrigin-RevId: 825313208
Previously this will return true for events yielded from before_agent_callback when there are state changes.
Note with this change, it will also return false for state delta only callbacks even after main response, but this is fine as long as the actual final response event has it to be true.
Closes#2992
PiperOrigin-RevId: 825279439
Merge https://github.com/google/adk-python/pull/3037
fix: [#3036](https://github.com/google/adk-python/issues/3036)
- Fix FunctionTool parameter filtering to support CrewAI-style tools
- Functions with **kwargs now receive all parameters except 'self' and 'tool_context'
- Maintains backward compatibility with explicit parameter functions
- Add comprehensive tests for **kwargs functionality
Fixes parameter filtering issue where CrewAI tools using **kwargs pattern would receive empty parameter dictionaries, causing search_query and other parameters to be None.
#non-breaking
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3037 from omarcevi:fix/function-tool-kwargs-parameter-filtering 012bbfcfd68e83a29635ac74718a1bd1323c5187
PiperOrigin-RevId: 825275686
This change introduces a powerful pattern for customizing code execution environments by extending a base `CodeExecutor`. It showcases how to inject setup code to prepare the environment before a user's code is run, enabling advanced use cases that require specific configurations.
As a practical example, this change implements `CustomCodeExecutor`, a subclass of `VertexAiCodeExecutor`, to solve the problem of rendering non-standard characters in `matplotlib` plots (Issue #2993). The custom executor programmatically adds a Japanese font to the `matplotlib` font manager at runtime.
This is achieved by overriding the `execute_code` method to add font files to execution input and prepend the necessary font-loading logic. This approach is not limited to fonts and can be adapted for other setup tasks.
Fixes: #2993
PiperOrigin-RevId: 825240143
This change introduces a new sample agent and documentation to demonstrate the usage of the `VertexAiCodeExecutor`.
The new agent, located at `vertex_code_execution/agent.py`, is a direct counterpart to the existing sample at `code_execution/agent.py`. The key difference is that this new agent uses `VertexAiCodeExecutor` to execute code within the Vertex AI Code Interpreter Extension, whereas the original sample uses `BuiltInCodeExecutor` to run code in the model's built-in sandbox.
A `README.md` file is also included to provide an overview, setup instructions, and sample usage for the new agent.
Related: #2993
PiperOrigin-RevId: 825239758
This change introduces a new `detect_anomalies` tool in `query_tool.py` which uses BigQuery ML's `CREATE MODEL` with `ARIMA_PLUS` type and `ML.DETECT_ANOMALIES` to detect anomalies. The new function is also added to the `bigquery_toolset`.
PiperOrigin-RevId: 825181489
* feat: Added support for enums as arguments for function tools
* feat: Add default value support for function tools
fix: Add more test cases inside `test_build_function_declaration.py` for passing Enums as arguments
* fix: format code with pyink
---------
Co-authored-by: Wei Sun (Jack) <weisun@google.com>
Co-authored-by: Yvonne Yu <150068659+yyyu-google@users.noreply.github.com>
ADK already has a set of metrics that don't rely expected_invocations. Also, for eval cases with conversation scenario, this would be the main line case.
PiperOrigin-RevId: 825101481
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
This CL refactors VertexAiSessionService to use the asynchronous aio client for all Vertex AI API calls. This ensures that the service methods are non-blocking and can be used effectively in an asyncio environment.
PiperOrigin-RevId: 824573356
The computer_use sample now supports launching with a `user_data_dir` to maintain browser state across runs. The sample agent is updated to use a shared temporary directory for the browser profile, preserving login sessions and other data.
PiperOrigin-RevId: 823749082
While testing the bidi streaming sample agent, I noticed that the import was erroring and I think it's a typo -- the other bidi sample agents all import `from google.adk.agents.llm_agent`.
PiperOrigin-RevId: 823662586
Details:
- Adds the `LlmBackedUserSimulator` which uses an LLM to generate user prompts until it decides that the conversation is complete.
- Adds unit tests for the new functionality.
PiperOrigin-RevId: 823557910
This change adds a new section to the README.md, detailing past community events. The first entry is for the completed ADK's 1st community meeting, with links to the recording and deck.
PiperOrigin-RevId: 823322924
Right now the failure eats up the traceback information and there is no clear way for the developer to know what went wrong. Adding this traceback info could give them the needed debugging information.
PiperOrigin-RevId: 823179833
## What's Added
- **PostgreSQL MCP Agent** ([mcp_postgres_agent/agent.py](cci:7://file:///Users/admin/git%20repos/adk-python/contributing/samples/mcp_postgres_agent/agent.py:0:0-0:0)): A fully functional agent that connects to PostgreSQL databases via the `postgres-mcp` MCP server
- **Comprehensive README** ([mcp_postgres_agent/README.md](cci:7://file:///Users/admin/git%20repos/adk-python/contributing/samples/mcp_postgres_agent/README.md:0:0-0:0)): Documentation with setup instructions, configuration details, and example queries
- **Environment Configuration**: Support for secure credential management via `.env` files
## Key Features
- **MCP Integration**: Demonstrates proper use of `MCPToolset` with `StdioConnectionParams`
- **Zero Installation**: Uses `uvx` to run the MCP server without manual installation
- **Secure Credentials**: Database connection strings passed via environment variables
- **Production-Ready**: Uses Gemini 2.0 Flash with unrestricted access mode for full database operations
## Technical Details
- **Model**: Gemini 2.0 Flash
- **MCP Server**: `postgres-mcp` (via `uvx`)
- **Connection**: StdioConnectionParams with 60-second timeout
- **Environment Variable**: Maps `POSTGRES_CONNECTION_STRING` to `DATABASE_URI`
## Testing
The agent has been tested with:
- PostgreSQL database connections (local and remote)
- Schema inspection queries
- Data querying operations
- Table listing and management
## Example Queries
Users can interact with the agent using natural language queries like:
- "What tables are in the database?"
- "Show me the schema for the users table"
- "Query the first 10 rows from the products table"
This sample serves as a reference implementation for developers looking to integrate PostgreSQL databases with ADK agents using MCP.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3182 from Vrajesh-Babu:postgres-mcp f3b3846abae37ae376d3554624ac2b1be82f7adc
PiperOrigin-RevId: 822865931
The "What's new" section has been updated to highlight: Custom API Registration, Rewind functionality, and a new CodeExecutor utilizing the Vertex AI Code Execution Sandbox API. Previous updates on context compaction, resumability, ReflectRetryToolPlugin, and search tool support have been removed.
PiperOrigin-RevId: 822848112
The section detailing the first ADK community call scheduled for Oct 15, 2025, including date, time, meeting links, and agenda, has been removed.
The section detailing the first ADK community call scheduled for Oct 15, 2025, including date, time, meeting links, and agenda, has been removed.
PiperOrigin-RevId: 822843889
This release includes updates to the changelog with new features across Core, Evals, Integrations, Observability, Services, Tools, and UI, along with various bug fixes and improvements. The base CL number has also been updated.
PiperOrigin-RevId: 822730595
Since it appears in the same bubble as the rest of the LLM's response text, make it more human readable so it doesn't look out of place.
PiperOrigin-RevId: 822729061
The `BaseTool` expects the run_async to return a json-serializable object. By model_dump the McpTool result explicitly can allow what ADK runtime sees is identical to what is persisted in the session event list.
Before the change, runtime sees CallToolResult instance and Session persists its serialized dict.
https://github.com/modelcontextprotocol/python-sdk/blob/main/src/mcp/types.py#L916-L922
PiperOrigin-RevId: 822465432
From
```
You are an agent. Your internal name is "agent".
The description about you is "test description"
```
to
```
You are an agent. Your internal name is "agent". The description about you is "test description".
```
PiperOrigin-RevId: 822358196
To register a custom service:
- Create a factory function that takes a URI and returns an instance of your custom service. This function will parse any details it needs from the URI.
- Register your factory with the global service registry. You need to define a unique URI scheme for your service (e.g., custom).
PiperOrigin-RevId: 822310466
Merge https://github.com/google/adk-python/pull/3170
Addresses Feature Request: #3116
This PR adds a `speech_config` to the **LLM Agent configuration** for the **live use case**. When an **asynchronous LLM** call is made to the **Gemini Live API**, it prioritizes the most specific agent configuration's speech_config. If that is null, it then uses the run configuration's speech_config. Unit tests have been added to verify this behavior.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3170 from qyuo:bidi_agent_speech_config af1bd277d4f95c4a7d9aa0b16828ba3de826ce08
PiperOrigin-RevId: 822305427
Merge https://github.com/google/adk-python/pull/3194
Allow Google API toolsets to accept optional per-request headers
#3105
## Testing Plan
### Unit Tests
- ✅ Added `test_init_with_additional_headers` in `test_google_api_tool.py` to verify headers are passed to RestApiTool
- ✅ Added `test_prepare_request_params_merges_default_headers` in `test_rest_api_tool.py` to verify custom headers are merged into requests
- ✅ Added `test_prepare_request_params_preserves_existing_headers` in `test_rest_api_tool.py` to verify critical headers (Content-Type, User-Agent) are not overridden by additional_headers
- ✅ Updated `test_init` and `test_get_tools` in `test_google_api_toolset.py` to verify the parameter is properly stored and passed through
### Manual Testing
Tested with Google Ads API scenario (the original use case from issue #3105):
```python
import os
from google.adk.tools.google_api_tool import GoogleApiToolset
# Create toolset with developer-token header required by Google Ads API
google_ads_toolset = GoogleApiToolset(
client_id=os.environ["CLIENT_ID"],
client_secret=os.environ["CLIENT_SECRET"],
api_name="googleads",
api_version="v21",
additional_headers={"developer-token": os.environ["GOOGLE_ADS_DEV_TOKEN"]}
)
# Verify headers are included in API requests
tools = await google_ads_toolset.get_tools()
# Successfully made requests with the developer-token header
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3194 from Prhmma:feature/google-api-toolset-additional-headers-3105 e10489e82bfde5cf2bfd3f1bced3e1f5cea1f8b2
PiperOrigin-RevId: 822273582
Previously BuiltInCodeExecutor was missing the logic to save output files from executed code as artifacts, so images/visualizations wouldn't show up in the UI. This fix will iterate through all parts of the LlmResponse, and if any of them are images, it will save the image data using artifact_service (similar to what is done in VertexAICodeExecutor).
This fixes the backend, but there are still UI bugs that should be fixed -- events without content are currently ignored, so the image doesn't appear even though it is saved. We will add the UI fix in a separate change.
PiperOrigin-RevId: 822245140
- let _enforce_app_name_alignment warn instead of raising while caching the hint that now augments the existing “Session not found …” error
- tighten _infer_agent_origin so it ignores hidden folders (like .venv)
- make AgentTool reuse the parent runner’s app_name, stopping internal runners from conflicting in multi-agent setups
PiperOrigin-RevId: 822205860
Details:
- Adds the `StaticUserSimulator` which implements the current functionality of supplying a fixed set of user prompts for an EvalCase.
- Adds the `UserSimulatorProvider` which determines the type of user simulator required for an EvalCase (StaticUserSimulator or LlmBackedUserSimulator).
- Integrates the UserSimulatorProvider and UserSimulator into the CLI and evaluation infrastructure.
- Updates and adds unit tests for the new functionality.
- Miscellaneous updates to lay groundwork for a full implementation of the LlmBackedUserSimulator in the future.
PiperOrigin-RevId: 822198401
Merge https://github.com/google/adk-python/pull/3196
## Summary
Enhances the `AgentLoader` error message to provide clear guidance when users run `adk web` from incorrect directories.
## Motivation
During internal workshops, multiple teams encountered confusion when starting `adk web` from the wrong directory. This often happened when:
- Running `adk web my_agent/` instead of `adk web .`
- Being inside an agent directory when executing the command
- Configuring incorrect start paths during development
## Changes
- **Smart detection**: Checks if `agent.py` or `root_agent.yaml` exists in the current directory
- **Visual diagram**: Shows expected directory structure with actual agent name
- **Explicit command**: Includes `adk web <agents_dir>` usage example
- **Conditional hint**: Provides targeted guidance when user is detected to be inside an agent directory
## Example Error Message
### Before
```
ValueError: No root_agent found for 'my_agent'. Searched in 'my_agent.agent.root_agent', 'my_agent.root_agent' and 'my_agent/root_agent.yaml'. Ensure 'path/my_agent' is structured correctly, an .env file can be loaded if present, and a root_agent is exposed.
```
### After
```
ValueError: No root_agent found for 'my_agent'. Searched in 'my_agent.agent.root_agent', 'my_agent.root_agent' and 'my_agent/root_agent.yaml'.
Expected directory structure:
<agents_dir>/
my_agent/
agent.py (with root_agent) OR
root_agent.yaml
Then run: adk web <agents_dir>
Ensure 'path/my_agent' is structured correctly, an .env file can be loaded if present, and a root_agent is exposed.
HINT: It looks like you might be running 'adk web' from inside an agent directory. Try running 'adk web .' from the parent directory that contains your agent folder, not from within the agent folder itself.
```
## Testing
- ✅ Existing unit tests pass (17/22, with 5 pre-existing failures unrelated to this change)
- ✅ `test_agent_not_found_error` passes, confirming error message enhancement works correctly
- ✅ Code follows ADK contribution guidelines
## Type
- [x] Bug fix (improved error messaging)
- [ ] Feature
- [ ] Breaking change
- [ ] Documentation
## Related
Fixes#3195
---
**Tags**: #non-breaking
🤖 Generated with [Claude Code](https://claude.com/claude-code)
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3196 from jpantsjoha:fix/improve-adk-web-error-message a73b190f5b021dbe0afa8426172696ee9eeae8da
PiperOrigin-RevId: 822186700
Merge https://github.com/google/adk-python/pull/3060
## Description
Fixes#3059
This PR fixes two endpoints in `adk web` that fail when using App objects instead of bare agents.
## Changes
- **Eval execution endpoint** (line ~969): Extract root_agent from App objects before passing to LocalEvalService
- **Graph visualization endpoint** (line ~1308): Extract root_agent from App objects before graph operations
Both endpoints now properly handle both BaseAgent and App objects by checking the type and extracting `.root_agent` when needed.
## Testing Plan
### Manual E2E Testing with ADK Web
Tested with an App object that includes context caching:
```python
from google.adk.apps import App
from google.adk.agents import LlmAgent
root_agent = LlmAgent(name="MyAgent", model="gemini-1.5-pro-002")
app = App(
name="my_agent",
root_agent=root_agent,
context_cache_config=ContextCacheConfig(...)
)
```
**Before fix:**
- Graph visualization failed (tried to call agent methods on App object)
- Eval execution failed (LocalEvalService received App instead of agent)
**After fix:**
- Graph visualization works correctly
- Eval execution works correctly
- Both endpoints properly extract root_agent from App objects
## Checklist
- [x] Code follows project style (autoformat.sh passed)
- [x] Changes are focused and minimal
- [x] Issue #3059 created and referenced
- [x] Manual E2E testing completed
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3060 from ejfn:ejfn/bugfix-app-object-endpoints 01c30191bfd9487a8c8463ccf24b297cb9a4ce37
PiperOrigin-RevId: 821746910
Add a header_provider param which is a callable[ReadonlyContext, Dict[str, Any]] for users to build headers in MCPToolset
fix: https://github.com/google/adk-python/issues/3156
PiperOrigin-RevId: 820412372
This change introduces type aliases for request and event conversion functions:
- `A2ARequestToADKRunArgsConverter`: For converting A2A `RequestContext` to an `ADKRunArgs` Pydantic model.
- `AdkEventToA2AEventsConverter`: For converting ADK `Event` to a list of A2A `A2AEvent` objects.
The `convert_a2a_request_to_adk_run_args` function now returns a structured `ADKRunArgs` model instead of a generic dictionary, improving type safety.
These converter types can now be provided via the `A2aAgentExecutorConfig` to customize the conversion logic used by the `A2aAgentExecutor`. The executor defaults to the existing `convert_a2a_request_to_adk_run_args` and `convert_event_to_a2a_events` functions if no custom converters are specified.
This allows users to inject their own logic for handling request and event conversions, for example, to add custom metadata or transform data types, without modifying the core executor.
PiperOrigin-RevId: 819934960
Merge https://github.com/google/adk-python/pull/2884closes: #2883
# Fix
When put leage data into event and load it. the _pickle.UnpicklingError was occurred.
The root caurse is `DynamicPickleType` mapping `BLOB` as default in case of MySql, not `LONGBLOB`. And learge data will be able to cut off tail of data. And raise pickle error.
# What todo
Defined `LONFBLOB` as default explicitly.
# Question
Where should we code the test code like this case? I cannot found the test code the DB and table was created expectedly.
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2884 from Lin-Nikaido:fix/#2883-mysql-datatype-fix 2be9b38fc3f5d5083b0b6715a2bf7b4eff5d947b
PiperOrigin-RevId: 819891727
Merge https://github.com/google/adk-python/pull/2206
### Summary
This PR adds support for `ContextWindowCompressionConfig` in `RunConfig`.
This enables context window compression using a `trigger_tokens` threshold and a sliding window with a `target_tokens` limit.
This feature is useful for managing long-running audio inputs.
### Related Issue
Closes#2188
### Testing Plan
- Added new unit test: `test_streaming_with_context_window_compression_config`
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2206 from ac-machache:support/add-context-compression-config c8a5b15cae2d2b72f331797d07ae0bbaf977ed3c
PiperOrigin-RevId: 819855786
This change removes the `convert_session_to_eval_format` function and its associated unit tests. New tests for `create_gcs_eval_managers_from_uri` are also added.
PiperOrigin-RevId: 819576620
- add a shared --structured_logs flag to adk web and adk api_server so users can opt into JSON-formatted output
- introduce CloudTraceJSONFormatter that emits structured entries and attaches current Cloud Trace/Span IDs when an OpenTelemetry context is active
- update CLI logging setup to clear duplicate stdout handlers when Cloud Logging is enabled and to reconfigure existing handlers (like from Uvicorn) so they also pick up the structured format and requested log level
With the flag disabled the CLIs keep their existing text logs; when enabled, the services now produce Cloud Logging–friendly JSON that can be correlated with distributed traces.
PiperOrigin-RevId: 818823818
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 is so we don't need to worry about side effect of Loop in all agent type. Custom agent should do the same if there exists loop inside.
PiperOrigin-RevId: 818766305
This change removes the `run_evals` function and its helper `_get_evaluator` from `cli_eval.py`, as they were marked as deprecated. Corresponding test mocks and patches in `test_fast_api.py` are also removed.
PiperOrigin-RevId: 818719422
changed the LiteLLM content conversion so Part.file_data.file_uri (like the gs://…) becomes a file object with file_id, making sure GCS-backed files reach LiteLLM proxies instead of being dropped add unit tests covering both _get_content and _content_to_message_param paths for file URIs
PiperOrigin-RevId: 817658432
This change removes the `evaluate`, `_evaluate_row`, `are_tools_equal`, `_remove_tool_outputs`, `_report_failures`, and `_print_results` static methods from `TrajectoryEvaluator`, along with their corresponding unit tests. These methods were previously marked as deprecated.
PiperOrigin-RevId: 817477494
This CL updates the "What's new" section to include Resumability, ReflectRetryToolPlugin, Context compaction, and Search tool support. It also moves "Agent Config" and "Tool Confirmation" from "What's new" to "Key Features".
PiperOrigin-RevId: 817469210
The added section provides details for the community call on Oct 15, 2025, including the agenda and links to join and add to calendars.
PiperOrigin-RevId: 817457276
Agent developers can now create an eval set and add eval cases through command line itself. Adding an eval case is limited only to specifying conversation scenarios.
Sample comamnds:
- Create an eval set:
adk eval_set create \
contributing/samples/hello_world \
set_01
- Add an eval case with scenario file
Content of scenarios.json file:
'{"scenarios": [{"starting_prompt": "hello", "conversation_plan": "world"}]}'
adk eval_set add_eval_case \
contributing/samples/hello_world \
set_01 \
--scenarios scenarios.json
PiperOrigin-RevId: 817456117
The `agent_loader.load_agent` method can now return an `App` object. This change unwraps the `App` to get its `root_agent` before passing it to the graph builder, makes sure a `BaseAgent` instance is always used
PiperOrigin-RevId: 817209601
Details:
- Introduces a concept of `ConversationScenario` to represent a scenario that user simulator is supposed to follow.
- Introduces a `UserSimulator` interface, that one should implement. UserSimulator interface will be integrated with LocalEvalService in subsequent PRs.
PiperOrigin-RevId: 816883699
When there are multiple intervals and compactions, the original implementation only keep the last one. The right implementation is to keep as many compaction events/summary as the requested internals.
PiperOrigin-RevId: 816516662
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
Merge https://github.com/google/adk-python/pull/2857
Adds support for invoking Gemma models via the Gemini API endpoint. To support agentic function, callbacks are added which can extract and transform function calls and responses into user and model messages in the history.
This change is intended to allow developers to explore the use of Gemma models for agentic purposes without requiring local deployment of the models. This should ease the burden of experimentation and testing for developers.
A basic "hello world" style agent example is provided to demonstrate proper functioning of Gemma 3 models inside an Agent container, using the dice roll + prime check framework of similar examples for other models.
## Testing
### Testing Plan
- add and run integration and unit tests
- manual run of example `multi_tool_agent` from quickstart using new `Gemma` model
- manual run of `hello_world_gemma` agent
### Automated Test Results:
| Test Command | Results |
|----------------|---------|
| pytest ./tests/unittests | 4386 passed, 2849 warnings in 58.43s |
| pytest ./tests/unittests/models/test_google_llm.py | 100 passed, 4 warnings in 5.83s |
| pytest ./tests/integration/models/test_google_llm.py | 5 passed, 2 warnings in 3.73s |
### Manual Testing
Here is a log of `multi_tool_agent` run with locally-built wheel and using Gemma model.
```
❯ adk run multi_tool_agent
Log setup complete: /var/folders/bg/_133c0ds2kb7cn699cpmmh_h0061bp/T/agents_log/agent.20250904_152617.log
To access latest log: tail -F /var/folders/bg/_133c0ds2kb7cn699cpmmh_h0061bp/T/agents_log/agent.latest.log
/Users/<redacted>/venvs/adk-quickstart/lib/python3.11/site-packages/google/adk/cli/cli.py:143: UserWarning: [EXPERIMENTAL] InMemoryCredentialService: This feature is experimental and may change or be removed in future versions without notice. It may introduce breaking changes at any time.
credential_service = InMemoryCredentialService()
/Users/<redacted>/venvs/adk-quickstart/lib/python3.11/site-packages/google/adk/auth/credential_service/in_memory_credential_service.py:33: UserWarning: [EXPERIMENTAL] BaseCredentialService: This feature is experimental and may change or be removed in future versions without notice. It may introduce breaking changes at any time.
super().__init__()
Running agent weather_time_agent, type exit to exit.
[user]: what's the weather like today?
[weather_time_agent]: Which city are you asking about?
[user]: new york
[weather_time_agent]: OK. The weather in New York is sunny with a temperature of 25 degrees Celsius (77 degrees Fahrenheit).
```
And here is a snippet of a log generated with DEBUG level logging of the `hello_world_gemma` sample. It demonstrates how function calls are extracted and inserted based on Gemma model interactions:
```
...
2025-09-04 15:32:41,708 - DEBUG - google_llm.py:138 -
LLM Request:
-----------------------------------------------------------
System Instruction:
None
-----------------------------------------------------------
Contents:
{"parts":[{"text":"\n You roll dice and answer questions about the outcome of the dice rolls.\n You can roll dice of different sizes...\n"}],"role":"user"}
{"parts":[{"text":"Hi, introduce yourself."}],"role":"user"}
{"parts":[{"text":"Hello! I am data_processing_agent, a hello world agent that can roll many-sided dice and check if numbers are prime. I'm ready to assist you with those tasks. Let's begin!\n\n\n\n"}],"role":"model"}
{"parts":[{"text":"Roll a die with 100 sides and check if it is prime"}],"role":"user"}
{"parts":[{"text":"{\"args\":{\"sides\":100},\"name\":\"roll_die\"}"}],"role":"model"}
{"parts":[{"text":"Invoking tool `roll_die` produced: `{\"result\": 82}`."}],"role":"user"}
{"parts":[{"text":"{\"args\":{\"nums\":[82]},\"name\":\"check_prime\"}"}],"role":"model"}
{"parts":[{"text":"Invoking tool `check_prime` produced: `{\"result\": \"No prime numbers found.\"}`."}],"role":"user"}
{"parts":[{"text":"The die roll was 82, and it is not a prime number.\n\n\n\n"}],"role":"model"}
{"parts":[{"text":"Roll it again."}],"role":"user"}
-----------------------------------------------------------
Functions:
-----------------------------------------------------------
2025-09-04 15:32:41,708 - INFO - models.py:8165 - AFC is enabled with max remote calls: 10.
2025-09-04 15:32:42,693 - INFO - google_llm.py:180 - Response received from the model.
2025-09-04 15:32:42,693 - DEBUG - google_llm.py:181 -
LLM Response:
-----------------------------------------------------------
Text:
{"args":{"sides":100},"name":"roll_die"}
-----------------------------------------------------------
...
```
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/2857 from douglas-reid:add-gemma-via-api e6d015f6a9ccbcf20ef7a7af8e4bbe1e9a5936b6
PiperOrigin-RevId: 816451001
If `EventsCompactionConfig` is provided without a `compactor`, a `SlidingWindowCompactor` is now automatically instantiated using the `root_agent`'s LLM. This simplifies configuration by providing a sensible default.
PiperOrigin-RevId: 816038579
The class is now named `LlmEventSummarizer` to better reflect that its primary function is to use an LLM to summarize events. The docstring has been updated to clarify that this class is responsible *only* for the LLM-based summarization of a given set of events, while the logic for determining *when* and *which* events form the sliding window is handled by an external component, such as an ADK Runner.
PiperOrigin-RevId: 815976264
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
before this change, we estimate the token count of the contents to cache and use it to compare with the threshold user set. but that's not precise , so we use the actual prompt token count of previous llm request.
We won't create cache for the very initial request
PiperOrigin-RevId: 814484840
We updated the one of the public methods on AgentEvaluator to take in eval metric configurations using a more formal EvalConfig data model.
We also mark "criteria" field on the method as deprecated.
Updated some integration test cases.
PiperOrigin-RevId: 814314134
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
This is allow user to update session state without running the agent. e.g. if I want to test some case when session has certain state on adk web.
PiperOrigin-RevId: 814252851
Currently, the A2A Task -> ADK event conversion is producing the same events on the last two update events (the last is a status update marking the task complete)
The change here based on A2AClientEvent(task, update):
- if the update == None: handle the non-streaming task case and also streaming case for the initial task creation event
- if the update = TaskStatusUpdateEvent AND a message is set: emit an event with that message
- if a task status update AND no message is set: don't emit event (for example, the final status update)
- if the update is ArtifactUpdateEvent and it's final artifact: emit the event
PiperOrigin-RevId: 812878869
The PR does two main things:
1) Introduces a new rubric based tool use metric
2) Given that we now have two rubric based metric, we refactor and create a new RubricBasedEvaluator interface.
PiperOrigin-RevId: 811983514
**Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.**
### Link to Issue or Description of Change
**1. Link to an existing issue (if applicable):**
- Closes: #_issue_number_
- Related: #_issue_number_
**2. Or, if no issue exists, describe the change:**
_If applicable, please follow the issue templates to provide as much detail as
possible._
**Problem:**
_A clear and concise description of what the problem is._
**Solution:**
_A clear and concise description of what you want to happen and why you choose
this solution._
### Testing Plan
_Please describe the tests that you ran to verify your changes. This is required
for all PRs that are not small documentation or typo fixes._
**Unit Tests:**
- [ ] I have added or updated unit tests for my change.
- [ ] All unit tests pass locally.
_Please include a summary of passed `pytest` results._
**Manual End-to-End (E2E) Tests:**
_Please provide instructions on how to manually test your changes, including any
necessary setup or configuration. Please provide logs or screenshots to help
reviewers better understand the fix._
### Checklist
- [ ] I have read the [CONTRIBUTING.md](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) document.
- [ ] I have performed a self-review of my own code.
- [ ] I have commented my code, particularly in hard-to-understand areas.
- [ ] I have added tests that prove my fix is effective or that my feature works.
- [ ] New and existing unit tests pass locally with my changes.
- [ ] I have manually tested my changes end-to-end.
- [ ] Any dependent changes have been merged and published in downstream modules.
### Additional context
_Add any other context or screenshots about the feature request here._
console.log(`PR #${prNumber} not found or inaccessible:`, error.message);
continue;
}
// Only close if PR is still open
if (pr.data.state !== 'open') {
console.log(`PR #${prNumber} is already ${pr.data.state}, skipping`);
continue;
}
const author = pr.data.user.login;
try {
// Add comment with commit reference
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: prNumber,
body: `Thank you @${author} for your contribution! 🎉\n\nYour changes have been successfully imported and merged via Copybara in commit ${commitSha}.\n\nClosing this PR as the changes are now in the main branch.`
[](https://github.com/google/adk-python/actions/workflows/python-unit-tests.yml)
Agent Development Kit (ADK) is a flexible and modular framework for developing and deploying AI agents. While optimized for Gemini and the Google ecosystem, ADK is model-agnostic, deployment-agnostic, and is built for compatibility with other frameworks. ADK was designed to make agent development feel more like software development, to make it easier for developers to create, deploy, and orchestrate agentic architectures that range from simple tasks to complex workflows.
Agent Development Kit (ADK) is a flexible and modular framework that applies
software development principles to AI agent creation. It is designed to
simplify building, deploying, and orchestrating agent workflows, from simple
tasks to complex systems. While optimized for Gemini, ADK is model-agnostic,
deployment-agnostic, and compatible with other frameworks.
---
## 🔥 What's new
- **Agent Config**: Build agents without code. Check out the
- **Custom Service Registration**: Add a service registry to provide ageneric way to register custom service implementations to be used in FastAPI server. See [short instruction](https://github.com/google/adk-python/discussions/3175#discussioncomment-14745120). ([391628f](https://github.com/google/adk-python/commit/391628fcdc7b950c6835f64ae3ccab197163c990))
- **Tool Confirmation**: A [tool confirmation flow(HITL)](https://google.github.io/adk-docs/tools/confirmation/) that can guard tool execution with explicit confirmation and custom input
- **Rewind**: Add the ability to rewind a session to before a previous invocation ([9dce06f](https://github.com/google/adk-python/commit/9dce06f9b00259ec42241df4f6638955e783a9d1)).
- **New CodeExecutor**: Introduces a new AgentEngineSandboxCodeExecutor class that supports executing agent-generated code using the Vertex AI Code Execution Sandbox API ([ee39a89](https://github.com/google/adk-python/commit/ee39a891106316b790621795b5cc529e89815a98))
- **Tool Confirmation**: A [tool confirmation flow(HITL)](https://google.github.io/adk-docs/tools/confirmation/) that can guard tool execution with explicit confirmation and custom input.
- **Modular Multi-Agent Systems**: Design scalable applications by composing
multiple specialized agents into flexible hierarchies.
- **Deploy Anywhere**: Easily containerize and deploy agents on Cloud Run or
scale seamlessly with Vertex AI Agent Engine.
## 🤖 Agent2Agent (A2A) Protocol and ADK Integration
For remote agent-to-agent communication, ADK integrates with the
Note: The development version is built directly from the latest code commits. While it includes the newest fixes and features, it may also contain experimental changes or bugs not present in the stable release. Use it primarily for testing upcoming changes or accessing critical fixes before they are officially released.
## 🤖 Agent2Agent (A2A) Protocol and ADK Integration
For remote agent-to-agent communication, ADK integrates with the
See this [example](https://github.com/a2aproject/a2a-samples/tree/main/samples/python/agents)
for how they can work together.
## 📚 Documentation
Explore the full documentation for detailed guides on building, evaluating, and
@@ -146,10 +156,20 @@ We welcome contributions from the community! Whether it's bug reports, feature r
- [General contribution guideline and flow](https://google.github.io/adk-docs/contributing-guide/).
- Then if you want to contribute code, please read [Code Contributing Guidelines](./CONTRIBUTING.md) to get started.
## Community Repo
We have [adk-python-community repo](https://github.com/google/adk-python-community)that is home to a growing ecosystem of community-contributed tools, third-party
service integrations, and deployment scripts that extend the core capabilities
of the ADK.
## Vibe Coding
If you are to develop agent via vibe coding the [llms.txt](./llms.txt) and the [llms-full.txt](./llms-full.txt) can be used as context to LLM. While the former one is a summarized one and the later one has the full information in case your LLM has big enough context window.
## Community Events
- [Completed] ADK's 1st community meeting on Wednesday, October 15, 2025. Remember to [join our group](https://groups.google.com/g/adk-community) to get access to the [recording](https://drive.google.com/file/d/1rpXDq5NSH8-MyMeYI6_5pZ3Lhn0X9BQf/view), and [deck](https://docs.google.com/presentation/d/1_b8LG4xaiadbUUDzyNiapSFyxanc9ZgFdw7JQ6zmZ9Q/edit?slide=id.g384e60cdaca_0_658&resourcekey=0-tjFFv0VBQhpXBPCkZr0NOg#slide=id.g384e60cdaca_0_658).
## 📄 License
This project is licensed under the Apache 2.0 License - see the [LICENSE](LICENSE) file for details.
@@ -99,7 +99,7 @@ Agent: ✅ Great news! Your reimbursement has been approved by the manager. Proc
The human-in-the-loop process follows this pattern:
1. **Initial Call**: Root agent delegates approval request to remote approval agent for amounts >$100
2. **Pending Response**: Remote approval agent returns immediate response with `status: "pending"` and ticket ID and serface the approval request to root agent
2. **Pending Response**: Remote approval agent returns immediate response with `status: "pending"` and ticket ID and surface the approval request to root agent
3. **Agent Acknowledgment**: Root agent informs user about pending approval status
4. **Human Interaction**: Human manager interacts with root agent to review and approve/reject the request
5. **Updated Response**: Root agent receives updated tool response with approval decision and send it to remote agent
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Reference in New Issue
Block a user
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.