add tracing cookbook
This commit is contained in:
remy
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#!/usr/bin/env python3
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"""
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Async example demonstrating PocketFlow tracing with Langfuse.
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This example shows how to use the @trace_flow decorator with AsyncFlow
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and AsyncNode to trace asynchronous workflows.
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"""
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import asyncio
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import sys
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import os
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Add parent directory to path to import pocketflow and tracing
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", ".."))
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sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
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from pocketflow import AsyncNode, AsyncFlow
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from tracing import trace_flow, TracingConfig
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class AsyncDataFetchNode(AsyncNode):
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"""An async node that simulates fetching data."""
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async def prep_async(self, shared):
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"""Extract the query from shared data."""
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query = shared.get("query", "default")
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return query
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async def exec_async(self, query):
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"""Simulate async data fetching."""
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print(f"🔍 Fetching data for query: {query}")
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# Simulate async operation
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await asyncio.sleep(1)
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# Return mock data
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data = {
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"query": query,
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"results": [f"Result {i} for {query}" for i in range(3)],
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"timestamp": "2024-01-01T00:00:00Z",
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}
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return data
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async def post_async(self, shared, prep_res, exec_res):
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"""Store the fetched data."""
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shared["fetched_data"] = exec_res
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return "process"
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class AsyncDataProcessNode(AsyncNode):
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"""An async node that processes the fetched data."""
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async def prep_async(self, shared):
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"""Get the fetched data."""
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return shared.get("fetched_data", {})
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async def exec_async(self, data):
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"""Process the data asynchronously."""
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print("⚙️ Processing fetched data...")
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# Simulate async processing
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await asyncio.sleep(0.5)
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# Process the results
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processed_results = []
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for result in data.get("results", []):
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processed_results.append(f"PROCESSED: {result}")
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return {
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"original_query": data.get("query"),
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"processed_results": processed_results,
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"result_count": len(processed_results),
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}
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async def post_async(self, shared, prep_res, exec_res):
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"""Store the processed data."""
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shared["processed_data"] = exec_res
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return "default"
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@trace_flow(flow_name="AsyncDataProcessingFlow")
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class AsyncDataProcessingFlow(AsyncFlow):
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"""An async flow that fetches and processes data."""
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def __init__(self):
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# Create async nodes
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fetch_node = AsyncDataFetchNode()
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process_node = AsyncDataProcessNode()
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# Connect nodes
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fetch_node - "process" >> process_node
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# Initialize async flow
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super().__init__(start=fetch_node)
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async def main():
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"""Run the async tracing example."""
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print("🚀 Starting PocketFlow Async Tracing Example")
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print("=" * 50)
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# Create the async flow
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flow = AsyncDataProcessingFlow()
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# Prepare shared data
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shared = {"query": "machine learning tutorials"}
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print(f"📥 Input: {shared}")
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# Run the async flow (this will be automatically traced)
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try:
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result = await flow.run_async(shared)
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print(f"📤 Output: {shared}")
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print(f"🎯 Result: {result}")
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print("✅ Async flow completed successfully!")
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# Print the processed data
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if "processed_data" in shared:
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processed = shared["processed_data"]
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print(
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f"🎉 Processed {processed['result_count']} results for query: {processed['original_query']}"
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)
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for result in processed["processed_results"]:
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print(f" - {result}")
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except Exception as e:
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print(f"❌ Async flow failed with error: {e}")
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raise
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print("\n📊 Check your Langfuse dashboard to see the async trace!")
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langfuse_host = os.getenv("LANGFUSE_HOST", "your-langfuse-host")
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print(f" Dashboard URL: {langfuse_host}")
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -0,0 +1,110 @@
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#!/usr/bin/env python3
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"""
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Basic example demonstrating PocketFlow tracing with Langfuse.
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This example shows how to use the @trace_flow decorator to automatically
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trace a simple PocketFlow workflow.
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"""
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import sys
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import os
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Add parent directory to path to import pocketflow and tracing
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", ".."))
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sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
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from pocketflow import Node, Flow
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from tracing import trace_flow, TracingConfig
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class GreetingNode(Node):
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"""A simple node that creates a greeting message."""
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def prep(self, shared):
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"""Extract the name from shared data."""
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name = shared.get("name", "World")
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return name
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def exec(self, name):
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"""Create a greeting message."""
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greeting = f"Hello, {name}!"
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return greeting
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def post(self, shared, prep_res, exec_res):
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"""Store the greeting in shared data."""
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shared["greeting"] = exec_res
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return "default"
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class UppercaseNode(Node):
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"""A node that converts the greeting to uppercase."""
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def prep(self, shared):
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"""Get the greeting from shared data."""
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return shared.get("greeting", "")
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def exec(self, greeting):
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"""Convert to uppercase."""
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return greeting.upper()
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def post(self, shared, prep_res, exec_res):
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"""Store the uppercase greeting."""
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shared["uppercase_greeting"] = exec_res
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return "default"
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@trace_flow(flow_name="BasicGreetingFlow")
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class BasicGreetingFlow(Flow):
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"""A simple flow that creates and processes a greeting."""
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def __init__(self):
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# Create nodes
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greeting_node = GreetingNode()
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uppercase_node = UppercaseNode()
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# Connect nodes
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greeting_node >> uppercase_node
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# Initialize flow
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super().__init__(start=greeting_node)
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def main():
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"""Run the basic tracing example."""
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print("🚀 Starting PocketFlow Tracing Basic Example")
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print("=" * 50)
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# Create the flow
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flow = BasicGreetingFlow()
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# Prepare shared data
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shared = {"name": "PocketFlow User"}
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print(f"📥 Input: {shared}")
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# Run the flow (this will be automatically traced)
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try:
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result = flow.run(shared)
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print(f"📤 Output: {shared}")
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print(f"🎯 Result: {result}")
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print("✅ Flow completed successfully!")
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# Print the final greeting
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if "uppercase_greeting" in shared:
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print(f"🎉 Final greeting: {shared['uppercase_greeting']}")
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except Exception as e:
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print(f"❌ Flow failed with error: {e}")
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raise
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print("\n📊 Check your Langfuse dashboard to see the trace!")
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langfuse_host = os.getenv("LANGFUSE_HOST", "your-langfuse-host")
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print(f" Dashboard URL: {langfuse_host}")
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if __name__ == "__main__":
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main()
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