Files
adk-python/contributing/samples/runner_debug_example/agent.py
T
Lavi Nigam 0487eea2ab feat: add run_debug() helper method for quick agent experimentation
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
2025-10-31 13:28:02 -07:00

128 lines
3.9 KiB
Python

# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Example agent for demonstrating run_debug helper method."""
from google.adk import Agent
from google.adk.tools.tool_context import ToolContext
def get_weather(city: str, tool_context: ToolContext) -> str:
"""Get weather information for a city.
Args:
city: Name of the city to get weather for.
tool_context: Tool context for session state.
Returns:
Weather information as a string.
"""
# Store query history in session state
if "weather_queries" not in tool_context.state:
tool_context.state["weather_queries"] = [city]
else:
tool_context.state["weather_queries"] = tool_context.state[
"weather_queries"
] + [city]
# Mock weather data for demonstration
weather_data = {
"San Francisco": "Foggy, 15°C (59°F)",
"New York": "Sunny, 22°C (72°F)",
"London": "Rainy, 12°C (54°F)",
"Tokyo": "Clear, 25°C (77°F)",
"Paris": "Cloudy, 18°C (64°F)",
}
return weather_data.get(
city, f"Weather data not available for {city}. Try a major city."
)
def calculate(expression: str) -> str:
"""Safely evaluate a mathematical expression.
This tool demonstrates how function calls are displayed in run_debug().
Args:
expression: Mathematical expression to evaluate.
Returns:
Result of the calculation as a string.
"""
import ast
import operator
# Supported operators for safe evaluation
operators = {
ast.Add: operator.add,
ast.Sub: operator.sub,
ast.Mult: operator.mul,
ast.Div: operator.truediv,
ast.Pow: operator.pow,
ast.USub: operator.neg,
}
def _eval(node):
"""Recursively evaluate an AST node."""
if isinstance(node, ast.Expression):
return _eval(node.body)
elif isinstance(node, ast.Constant): # Python 3.8+
return node.value
elif isinstance(node, ast.Num): # For older Python versions
return node.n
elif isinstance(node, ast.BinOp):
op = operators.get(type(node.op))
if op:
return op(_eval(node.left), _eval(node.right))
else:
raise ValueError(f"Unsupported operation: {type(node.op).__name__}")
elif isinstance(node, ast.UnaryOp):
op = operators.get(type(node.op))
if op:
return op(_eval(node.operand))
else:
raise ValueError(f"Unsupported operation: {type(node.op).__name__}")
else:
raise ValueError(f"Unsupported expression type: {type(node).__name__}")
try:
# Parse the expression into an AST
tree = ast.parse(expression, mode="eval")
# Safely evaluate the AST
result = _eval(tree)
return f"Result: {result}"
except (SyntaxError, ValueError) as e:
return f"Error: {str(e)}"
except ZeroDivisionError:
return "Error: Division by zero"
except Exception as e:
return f"Error: {str(e)}"
root_agent = Agent(
model="gemini-2.5-flash-lite",
name="agent",
description="A helpful assistant demonstrating run_debug() helper method",
instruction="""You are a helpful assistant that can:
1. Provide weather information for major cities
2. Perform mathematical calculations
3. Remember previous queries in the conversation
When users ask about weather, use the get_weather tool.
When users ask for calculations, use the calculate tool.
Be friendly and conversational.""",
tools=[get_weather, calculate],
)