Jaroslav PantsjohaandCopybara-Service
34d9b53f37
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**: β 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
Agent Development Kit (ADK)
An open-source, code-first Python framework for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Important Links: Docs, Samples, Java ADK & ADK Web.
</html>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.
π₯ What's new
-
Custom Service Registration: Add a service registry to provide a generic way to register custom service implementations to be used in FastAPI server. See short instruction here. (391628f)
-
Rewind: Add the ability to rewind a session to before a previous invocation (9dce06f).
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New CodeExecutor: Introduces a new AgentEngineSandboxCodeExecutor class that supports executing agent-generated code using the Vertex AI Code Execution Sandbox API (ee39a89)
β¨ Key Features
-
Rich Tool Ecosystem: Utilize pre-built tools, custom functions, OpenAPI specs, MCP tools or integrate existing tools to give agents diverse capabilities, all for tight integration with the Google ecosystem.
-
Code-First Development: Define agent logic, tools, and orchestration directly in Python for ultimate flexibility, testability, and versioning.
-
Agent Config: Build agents without code. Check out the Agent Config feature.
-
Tool Confirmation: A tool confirmation flow(HITL) 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.
π Installation
Stable Release (Recommended)
You can install the latest stable version of ADK using pip:
pip install google-adk
The release cadence is roughly bi-weekly.
This version is recommended for most users as it represents the most recent official release.
Development Version
Bug fixes and new features are merged into the main branch on GitHub first. If you need access to changes that haven't been included in an official PyPI release yet, you can install directly from the main branch:
pip install git+https://github.com/google/adk-python.git@main
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.
π€ Agent2Agent (A2A) Protocol and ADK Integration
For remote agent-to-agent communication, ADK integrates with the A2A protocol. See this example for how they can work together.
π Documentation
Explore the full documentation for detailed guides on building, evaluating, and deploying agents:
π Feature Highlight
Define a single agent:
from google.adk.agents import Agent
from google.adk.tools import google_search
root_agent = Agent(
name="search_assistant",
model="gemini-2.5-flash", # Or your preferred Gemini model
instruction="You are a helpful assistant. Answer user questions using Google Search when needed.",
description="An assistant that can search the web.",
tools=[google_search]
)
Define a multi-agent system:
Define a multi-agent system with coordinator agent, greeter agent, and task execution agent. Then ADK engine and the model will guide the agents works together to accomplish the task.
from google.adk.agents import LlmAgent, BaseAgent
# Define individual agents
greeter = LlmAgent(name="greeter", model="gemini-2.5-flash", ...)
task_executor = LlmAgent(name="task_executor", model="gemini-2.5-flash", ...)
# Create parent agent and assign children via sub_agents
coordinator = LlmAgent(
name="Coordinator",
model="gemini-2.5-flash",
description="I coordinate greetings and tasks.",
sub_agents=[ # Assign sub_agents here
greeter,
task_executor
]
)
Development UI
A built-in development UI to help you test, evaluate, debug, and showcase your agent(s).
Evaluate Agents
adk eval \
samples_for_testing/hello_world \
samples_for_testing/hello_world/hello_world_eval_set_001.evalset.json
π€ Contributing
We welcome contributions from the community! Whether it's bug reports, feature requests, documentation improvements, or code contributions, please see our
- General contribution guideline and flow.
- Then if you want to contribute code, please read Code Contributing Guidelines to get started.
Vibe Coding
If you are to develop agent via vibe coding the llms.txt and the 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 to get access to the recording, and deck.
π License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Happy Agent Building!