From 5110607dbd8debf7469471952dfce5d418f71f3a Mon Sep 17 00:00:00 2001 From: Fabian Schindler Date: Fri, 10 Oct 2025 14:44:31 +0200 Subject: [PATCH] feat: adding pydantic-ai tests --- test-pydantic-ai/README.md | 132 ++ test-pydantic-ai/agents.py | 185 +++ test-pydantic-ai/main.py | 126 ++ test-pydantic-ai/main_async.py | 240 ++++ test-pydantic-ai/pyproject.toml | 13 + test-pydantic-ai/run.sh | 12 + test-pydantic-ai/run_async.sh | 12 + test-pydantic-ai/uv.lock | 2290 +++++++++++++++++++++++++++++++ 8 files changed, 3010 insertions(+) create mode 100644 test-pydantic-ai/README.md create mode 100644 test-pydantic-ai/agents.py create mode 100644 test-pydantic-ai/main.py create mode 100644 test-pydantic-ai/main_async.py create mode 100644 test-pydantic-ai/pyproject.toml create mode 100755 test-pydantic-ai/run.sh create mode 100755 test-pydantic-ai/run_async.sh create mode 100644 test-pydantic-ai/uv.lock diff --git a/test-pydantic-ai/README.md b/test-pydantic-ai/README.md new file mode 100644 index 0000000..74f7c05 --- /dev/null +++ b/test-pydantic-ai/README.md @@ -0,0 +1,132 @@ +# Pydantic AI Sentry Integration Tests + +Clean, focused tests for the Sentry Pydantic AI integration. + +## Prerequisites + +You need to have Python and `curl` installed. + +## Configure + +Set the following environment variables: +- `SENTRY_DSN` +- `OPENAI_API_KEY` +- `ANTHROPIC_API_KEY` (for Anthropic provider tests) + +## Run Tests + +### Synchronous Tests +```bash +./run.sh +``` + +### Asynchronous Tests +```bash +./run_async.sh +``` + +## Test Structure + +The tests are organized into three main scenarios, each tested in both sync/async and streaming/non-streaming modes: + +### 1. **Simple Agent** +- Basic agent without tools +- Tests fundamental agent functionality +- Demonstrates simple Q&A interactions + +### 2. **Agent with Tools** +- Mathematical agent with calculation tools +- Tools: `add()`, `multiply()`, `calculate_percentage()` +- Tests tool integration and structured output +- Returns `CalculationResult` with explanation + +### 3. **Two-Agent Workflow** +- **Data Collector Agent**: Extracts and organizes data +- **Data Analyzer Agent**: Analyzes data and provides insights +- Demonstrates agent handoff and workflow patterns +- Returns `AnalysisResult` with findings and recommendations + +### 4. **Anthropic Provider Tests** +- **Anthropic Simple Agent**: Basic Claude agent without tools +- **Anthropic Math Agent**: Claude agent with calculation tools +- Tests both OpenAI and Anthropic providers for comparison +- Uses `anthropic:claude-3-5-haiku-20241022` model + +## Test Modes + +Each scenario is tested in four different modes: + +| Mode | Sync/Async | Streaming | Description | +|------|------------|-----------|-------------| +| 1 | Sync | No | `agent.run_sync()` | +| 2 | Sync | Yes | `agent.run_stream_sync()` | +| 3 | Async | No | `await agent.run()` | +| 4 | Async | Yes | `async with agent.run_stream()` | + +## Additional Features + +### Parallel Processing (Async Only) +- Demonstrates running multiple agents concurrently +- Uses `asyncio.gather()` for parallel execution +- Shows scalable multi-agent patterns + +### Model Settings +All agents use optimized model settings: +- **Simple Agent**: Balanced settings (temp: 0.3) +- **Math Agent**: Low temperature for precision (temp: 0.1) +- **Data Collector**: Focused extraction (temp: 0.2) +- **Data Analyzer**: Creative analysis (temp: 0.4) +- **Anthropic Simple Agent**: Balanced settings (temp: 0.3) +- **Anthropic Math Agent**: Low temperature for precision (temp: 0.1) + +## Sentry Integration + +The integration automatically creates Sentry spans for: +- `gen_ai.pipeline` - Agent workflow execution (root span) +- `gen_ai.invoke_agent` - Individual agent invocations +- `gen_ai.chat` - Model requests (AI client calls) +- `gen_ai.execute_tool` - Tool executions + +## File Structure + +``` +test-pydantic-ai/ +├── agents.py # Agent definitions and tools +├── main.py # Synchronous tests +├── main_async.py # Asynchronous tests +├── run.sh # Run sync tests +├── run_async.sh # Run async tests +├── pyproject.toml # Dependencies +└── README.md # This file +``` + +## Output Example + +``` +🚀 Running Pydantic AI Synchronous Tests +================================================== + +=== SIMPLE AGENT (Non-Streaming) === +Question: What is the capital of France? +Answer: The capital of France is Paris. + +=== SIMPLE AGENT (Streaming) === +Question: Tell me a short story about a robot. +Answer (streaming): Once upon a time, a curious robot named Zara discovered... + +=== AGENT WITH TOOLS (Non-Streaming) === +Task: Multi-step calculation +Result: CalculationResult(result=126, operation='multi-step', explanation='...') + +=== TWO-AGENT WORKFLOW (Non-Streaming) === +Step 1: Data Collection +Data Collector Result: Extracted sales data: [150, 200, 175, 225] + +Step 2: Data Analysis +Data Analyzer Result: AnalysisResult(summary='...', key_findings=[...], recommendation='...') + +================================================== +✅ All synchronous tests completed! +``` + +This clean structure focuses on the core functionality while thoroughly testing all aspects of the Pydantic AI integration with Sentry. \ No newline at end of file diff --git a/test-pydantic-ai/agents.py b/test-pydantic-ai/agents.py new file mode 100644 index 0000000..6a69563 --- /dev/null +++ b/test-pydantic-ai/agents.py @@ -0,0 +1,185 @@ +""" +Simple, focused agents for testing Pydantic AI integration with Sentry. +""" + +from pydantic_ai import Agent +from pydantic import BaseModel + + +class CalculationResult(BaseModel): + """Result from mathematical calculations.""" + result: int + operation: str + explanation: str + + +class AnalysisResult(BaseModel): + """Result from data analysis.""" + summary: str + key_findings: list[str] + recommendation: str + + +# Simple agent without tools +simple_agent = Agent( + "openai:gpt-4o-mini", + name="simple_agent", + instructions="You are a helpful assistant. Provide clear, concise answers.", + model_settings={ + "temperature": 0.3, + "max_tokens": 200, + }, +) + + +# Agent with mathematical tools +math_agent = Agent( + "openai:gpt-4o-mini", + name="math_agent", + instructions="You are a mathematical assistant. Use the available tools to perform calculations and return structured results.", + output_type=CalculationResult, + model_settings={ + "temperature": 0.1, + "max_tokens": 300, + }, +) + + +@math_agent.tool_plain +def add(a: int, b: int) -> int: + """Add two numbers together.""" + return a + b + + +@math_agent.tool_plain +def multiply(a: int, b: int) -> int: + """Multiply two numbers together.""" + return a * b + + +@math_agent.tool_plain +def calculate_percentage(part: float, total: float) -> float: + """Calculate what percentage 'part' is of 'total'.""" + if total == 0: + return 0.0 + return (part / total) * 100 + + +# First agent in two-agent setup - data collector +data_collector_agent = Agent( + "openai:gpt-4o-mini", + name="data_collector", + instructions="You collect and prepare data for analysis. Extract key numbers and organize information clearly.", + model_settings={ + "temperature": 0.2, + "max_tokens": 400, + }, +) + + +@data_collector_agent.tool_plain +def extract_numbers(text: str) -> list[int]: + """Extract all numbers from a text string.""" + import re + numbers = re.findall(r'\d+', text) + return [int(n) for n in numbers] + + +@data_collector_agent.tool_plain +def organize_data(items: list[str]) -> dict: + """Organize a list of items into categories.""" + return { + "total_items": len(items), + "items": items, + "categories": list(set(item.split()[0] if item.split() else "unknown" for item in items)) + } + + +# Second agent in two-agent setup - data analyzer +data_analyzer_agent = Agent( + "openai:gpt-4o-mini", + name="data_analyzer", + instructions="You analyze data provided by the data collector and provide insights and recommendations.", + output_type=AnalysisResult, + model_settings={ + "temperature": 0.4, + "max_tokens": 500, + }, +) + + +@data_analyzer_agent.tool_plain +def calculate_statistics(numbers: list[int]) -> dict: + """Calculate basic statistics for a list of numbers.""" + if not numbers: + return {"error": "No numbers provided"} + + return { + "count": len(numbers), + "sum": sum(numbers), + "average": sum(numbers) / len(numbers), + "min": min(numbers), + "max": max(numbers), + } + + +@data_analyzer_agent.tool_plain +def identify_trends(numbers: list[int]) -> str: + """Identify trends in a sequence of numbers.""" + if len(numbers) < 2: + return "Not enough data to identify trends" + + differences = [numbers[i+1] - numbers[i] for i in range(len(numbers)-1)] + + if all(d > 0 for d in differences): + return "Increasing trend" + elif all(d < 0 for d in differences): + return "Decreasing trend" + elif all(d == 0 for d in differences): + return "Constant values" + else: + return "Mixed trend" + + +# Anthropic agents for provider testing +anthropic_simple_agent = Agent( + "anthropic:claude-3-5-haiku-20241022", + name="anthropic_simple_agent", + instructions="You are a helpful assistant using Claude. Provide clear, concise answers.", + model_settings={ + "temperature": 0.3, + "max_tokens": 200, + }, +) + + +anthropic_math_agent = Agent( + "anthropic:claude-3-5-haiku-20241022", + name="anthropic_math_agent", + instructions="You are a mathematical assistant using Claude. Use the available tools to perform calculations and return structured results.", + output_type=CalculationResult, + model_settings={ + "temperature": 0.1, + "max_tokens": 300, + }, +) + + +@anthropic_math_agent.tool_plain +def anthropic_add(a: int, b: int) -> int: + """Add two numbers together (Anthropic version).""" + return a + b + + +@anthropic_math_agent.tool_plain +def anthropic_multiply(a: int, b: int) -> int: + """Multiply two numbers together (Anthropic version).""" + return a * b + + +@anthropic_math_agent.tool_plain +def anthropic_calculate_percentage(part: float, total: float) -> float: + """Calculate what percentage 'part' is of 'total' (Anthropic version).""" + if total == 0: + return 0.0 + return (part / total) * 100 diff --git a/test-pydantic-ai/main.py b/test-pydantic-ai/main.py new file mode 100644 index 0000000..e1d9f11 --- /dev/null +++ b/test-pydantic-ai/main.py @@ -0,0 +1,126 @@ +""" +Synchronous Pydantic AI tests with Sentry integration. +Tests: simple agent, agent with tools, two-agent workflow. +Includes both streaming and non-streaming tests. +""" + +import os +import sentry_sdk +from sentry_sdk.integrations.pydantic_ai import PydanticAIIntegration +from sentry_sdk.integrations.stdlib import StdlibIntegration + +from agents import ( + simple_agent, + math_agent, + data_collector_agent, + data_analyzer_agent, + anthropic_simple_agent, + anthropic_math_agent, +) + + +def test_simple_agent(): + """Test simple agent without tools.""" + print("\n=== SIMPLE AGENT ===") + + result = simple_agent.run_sync("What is the capital of France? Keep it brief.") + print(f"Question: What is the capital of France?") + print(f"Answer: {result.output}") + + + + +def test_agent_with_tools(): + """Test agent with mathematical tools.""" + print("\n=== AGENT WITH TOOLS ===") + + result = math_agent.run_sync( + "Calculate 15 + 27, then multiply the result by 3. " + "Also calculate what percentage 42 is of 100. " + "Explain your work step by step." + ) + print(f"Task: Multi-step calculation") + print(f"Result: {result.output}") + + + + +def test_two_agent_workflow(): + """Test two-agent workflow.""" + print("\n=== TWO-AGENT WORKFLOW ===") + + # Step 1: Data Collector + print("Step 1: Data Collection") + raw_data = "Sales report: January 150 units, February 200 units, March 175 units, April 225 units" + + collection_result = data_collector_agent.run_sync( + f"Extract and organize the numerical data from this text: {raw_data}" + ) + print(f"Data Collector Result: {collection_result.output}") + + # Step 2: Data Analyzer (using the collected data) + print("\nStep 2: Data Analysis") + analysis_result = data_analyzer_agent.run_sync( + f"Analyze this sales data and provide insights: {collection_result.output}. " + "The data represents monthly sales units. Identify trends and make recommendations." + ) + print(f"Data Analyzer Result: {analysis_result.output}") + + +def test_anthropic_simple_agent(): + """Test Anthropic simple agent without tools.""" + print("\n=== ANTHROPIC SIMPLE AGENT ===") + + result = anthropic_simple_agent.run_sync("What is the capital of Italy? Keep it brief.") + print(f"Question: What is the capital of Italy?") + print(f"Answer: {result.output}") + + +def test_anthropic_agent_with_tools(): + """Test Anthropic agent with mathematical tools.""" + print("\n=== ANTHROPIC AGENT WITH TOOLS ===") + + result = anthropic_math_agent.run_sync( + "Calculate 12 + 18, then multiply the result by 4. " + "Also calculate what percentage 25 is of 80. " + "Show your work step by step." + ) + print(f"Task: Multi-step calculation with Claude") + print(f"Result: {result.output}") + + +def main(): + """Run all synchronous tests.""" + # Initialize Sentry + sentry_sdk.init( + dsn=os.environ.get("SENTRY_DSN"), + environment=os.environ.get("ENV", "test-sync"), + traces_sample_rate=1.0, + send_default_pii=True, + integrations=[PydanticAIIntegration()], + disabled_integrations=[StdlibIntegration()], + debug=True, + ) + + # Set user context + sentry_sdk.set_user({"id": "test-user", "email": "test@example.com"}) + sentry_sdk.set_tag("test_type", "pydantic_ai_sync") + + print("🚀 Running Pydantic AI Synchronous Tests") + print("=" * 50) + + # Run all tests + test_simple_agent() + test_agent_with_tools() + test_two_agent_workflow() + + # Run Anthropic provider tests + test_anthropic_simple_agent() + test_anthropic_agent_with_tools() + + print("\n" + "=" * 50) + print("✅ All synchronous tests completed!") + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/test-pydantic-ai/main_async.py b/test-pydantic-ai/main_async.py new file mode 100644 index 0000000..55d51d6 --- /dev/null +++ b/test-pydantic-ai/main_async.py @@ -0,0 +1,240 @@ +""" +Asynchronous Pydantic AI tests with Sentry integration. +Tests: simple agent, agent with tools, two-agent workflow. +Includes both streaming and non-streaming tests. +""" + +import asyncio +import os +import sentry_sdk +from sentry_sdk.integrations.pydantic_ai import PydanticAIIntegration +from sentry_sdk.integrations.stdlib import StdlibIntegration + +from agents import ( + simple_agent, + math_agent, + data_collector_agent, + data_analyzer_agent, + anthropic_simple_agent, + anthropic_math_agent, +) + + +async def test_simple_agent(): + """Test simple agent without tools - non-streaming.""" + print("\n=== SIMPLE AGENT (Non-Streaming) ===") + + result = await simple_agent.run("What is the capital of Germany? Keep it brief.") + print(f"Question: What is the capital of Germany?") + print(f"Answer: {result.output}") + + +async def test_simple_agent_streaming(): + """Test simple agent without tools - streaming.""" + print("\n=== SIMPLE AGENT (Streaming) ===") + + print("Question: Explain photosynthesis in simple terms.") + print("Answer (streaming): ", end="", flush=True) + + async with simple_agent.run_stream("Explain photosynthesis in simple terms, 2-3 sentences.") as result: + async for chunk in result.stream_output(): + if hasattr(chunk, 'output') and chunk.output: + print(chunk.output, end="", flush=True) + print() # New line after streaming + + +async def test_agent_with_tools(): + """Test agent with mathematical tools - non-streaming.""" + print("\n=== AGENT WITH TOOLS (Non-Streaming) ===") + + result = await math_agent.run( + "Calculate 23 + 17, then multiply the result by 2. " + "Also calculate what percentage 30 is of 120. " + "Show your work clearly." + ) + print(f"Task: Multi-step calculation") + print(f"Result: {result.output}") + + +async def test_agent_with_tools_streaming(): + """Test agent with tools - streaming.""" + print("\n=== AGENT WITH TOOLS (Streaming) ===") + + print("Task: Calculate 18 * 6 and show the process") + print("Result (streaming): ", end="", flush=True) + + async with math_agent.run_stream("Calculate 18 multiplied by 6 and show your calculation steps.") as result: + async for chunk in result.stream_output(): + if hasattr(chunk, 'output') and chunk.output: + print(chunk.output, end="", flush=True) + print() # New line after streaming + + +async def test_two_agent_workflow(): + """Test two-agent workflow - non-streaming.""" + print("\n=== TWO-AGENT WORKFLOW (Non-Streaming) ===") + + # Step 1: Data Collector + print("Step 1: Data Collection") + raw_data = "Quarterly revenue: Q1 $450K, Q2 $520K, Q3 $480K, Q4 $610K" + + collection_result = await data_collector_agent.run( + f"Extract and organize the financial data from this text: {raw_data}" + ) + print(f"Data Collector Result: {collection_result.output}") + + # Step 2: Data Analyzer (using the collected data) + print("\nStep 2: Data Analysis") + analysis_result = await data_analyzer_agent.run( + f"Analyze this quarterly revenue data: {collection_result.output}. " + "Identify trends and provide business recommendations." + ) + print(f"Data Analyzer Result: {analysis_result.output}") + + +async def test_two_agent_workflow_streaming(): + """Test two-agent workflow - streaming.""" + print("\n=== TWO-AGENT WORKFLOW (Streaming) ===") + + # Step 1: Data Collector (streaming) + print("Step 1: Data Collection (streaming)") + raw_data = "Website traffic: Monday 1200 visits, Tuesday 1350 visits, Wednesday 980 visits, Thursday 1450 visits" + + print("Data Collector (streaming): ", end="", flush=True) + collection_output = "" + + async with data_collector_agent.run_stream( + f"Extract and organize this website traffic data: {raw_data}" + ) as collection_result: + async for chunk in collection_result.stream_output(): + if hasattr(chunk, 'output') and chunk.output: + print(chunk.output, end="", flush=True) + collection_output += chunk.output + print() # New line + + # Step 2: Data Analyzer (streaming) + print("\nStep 2: Data Analysis (streaming)") + print("Data Analyzer (streaming): ", end="", flush=True) + + async with data_analyzer_agent.run_stream( + f"Analyze this website traffic data: {collection_output}. " + "Calculate daily patterns and suggest optimization strategies." + ) as analysis_result: + async for chunk in analysis_result.stream_output(): + if hasattr(chunk, 'output') and chunk.output: + print(chunk.output, end="", flush=True) + print() # New line + + +async def test_parallel_agents(): + """Test running multiple agents in parallel.""" + print("\n=== PARALLEL AGENTS ===") + + print("Running multiple agents in parallel...") + + # Run multiple agents concurrently + tasks = [ + simple_agent.run("What is 2+2?"), + math_agent.run("Calculate 5 * 8 and explain the result."), + data_collector_agent.run("Extract numbers from: 'We sold 100 apples, 50 oranges, and 75 bananas.'"), + ] + + results = await asyncio.gather(*tasks) + + print("Parallel Results:") + print(f"1. Simple Agent: {results[0].output}") + print(f"2. Math Agent: {results[1].output}") + print(f"3. Data Collector: {results[2].output}") + + +async def test_anthropic_simple_agent(): + """Test Anthropic simple agent without tools - non-streaming.""" + print("\n=== ANTHROPIC SIMPLE AGENT (Non-Streaming) ===") + + result = await anthropic_simple_agent.run("What is the capital of Spain? Keep it brief.") + print(f"Question: What is the capital of Spain?") + print(f"Answer: {result.output}") + + +async def test_anthropic_simple_agent_streaming(): + """Test Anthropic simple agent without tools - streaming.""" + print("\n=== ANTHROPIC SIMPLE AGENT (Streaming) ===") + + print("Question: Explain gravity in simple terms.") + print("Answer (streaming): ", end="", flush=True) + + async with anthropic_simple_agent.run_stream("Explain gravity in simple terms, 2-3 sentences.") as result: + async for chunk in result.stream_output(): + if hasattr(chunk, 'output') and chunk.output: + print(chunk.output, end="", flush=True) + print() # New line after streaming + + +async def test_anthropic_agent_with_tools(): + """Test Anthropic agent with mathematical tools - non-streaming.""" + print("\n=== ANTHROPIC AGENT WITH TOOLS (Non-Streaming) ===") + + result = await anthropic_math_agent.run( + "Calculate 19 + 31, then multiply the result by 2. " + "Also calculate what percentage 15 is of 60. " + "Show your work clearly using Claude." + ) + print(f"Task: Multi-step calculation with Claude") + print(f"Result: {result.output}") + + +async def test_anthropic_agent_with_tools_streaming(): + """Test Anthropic agent with tools - streaming.""" + print("\n=== ANTHROPIC AGENT WITH TOOLS (Streaming) ===") + + print("Task: Calculate 14 * 9 with Claude and show the process") + print("Result (streaming): ", end="", flush=True) + + async with anthropic_math_agent.run_stream("Calculate 14 multiplied by 9 and show your calculation steps using Claude.") as result: + async for chunk in result.stream_output(): + if hasattr(chunk, 'output') and chunk.output: + print(chunk.output, end="", flush=True) + print() # New line after streaming + + +async def main(): + """Run all asynchronous tests.""" + # Initialize Sentry + sentry_sdk.init( + dsn=os.environ.get("SENTRY_DSN"), + environment=os.environ.get("ENV", "test-async"), + traces_sample_rate=1.0, + send_default_pii=True, + integrations=[PydanticAIIntegration()], + disabled_integrations=[StdlibIntegration()], + debug=True, + ) + + # Set user context + sentry_sdk.set_user({"id": "test-user-async", "email": "test-async@example.com"}) + sentry_sdk.set_tag("test_type", "pydantic_ai_async") + + print("🚀 Running Pydantic AI Asynchronous Tests") + print("=" * 50) + + # Run all tests + await test_simple_agent() + await test_simple_agent_streaming() + await test_agent_with_tools() + await test_agent_with_tools_streaming() + await test_two_agent_workflow() + await test_two_agent_workflow_streaming() + await test_parallel_agents() + + # Run Anthropic provider tests + await test_anthropic_simple_agent() + await test_anthropic_simple_agent_streaming() + await test_anthropic_agent_with_tools() + await test_anthropic_agent_with_tools_streaming() + + print("\n" + "=" * 50) + print("✅ All asynchronous tests completed!") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/test-pydantic-ai/pyproject.toml b/test-pydantic-ai/pyproject.toml new file mode 100644 index 0000000..5b97442 --- /dev/null +++ b/test-pydantic-ai/pyproject.toml @@ -0,0 +1,13 @@ +[project] +name = "test" +version = "0" +requires-python = ">=3.12" + +dependencies = [ + "ipdb>=0.13.13", + "pydantic-ai>=0.0.14", + "sentry-sdk", +] + +[tool.uv.sources] +sentry-sdk = { path = "../../sentry-python", editable = true } diff --git a/test-pydantic-ai/run.sh b/test-pydantic-ai/run.sh new file mode 100755 index 0000000..3ca4a02 --- /dev/null +++ b/test-pydantic-ai/run.sh @@ -0,0 +1,12 @@ +#!/usr/bin/env bash + +# exit on first error +set -euo pipefail + +# Install uv if it's not installed +if ! command -v uv &> /dev/null; then + curl -LsSf https://astral.sh/uv/install.sh | sh +fi + +echo "🔄 Running Synchronous Pydantic AI Tests..." +uv run python main.py \ No newline at end of file diff --git a/test-pydantic-ai/run_async.sh b/test-pydantic-ai/run_async.sh new file mode 100755 index 0000000..e6208e1 --- /dev/null +++ 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