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| 1 | +import os |
| 2 | +from langchain_openai import ChatOpenAI |
| 3 | +from langchain.agents import create_agent |
| 4 | +from langchain_core.tools import tool |
| 5 | +from dotenv import load_dotenv |
| 6 | +from agentkit.apps import AgentkitSimpleApp |
| 7 | +import logging |
| 8 | +import asyncio |
| 9 | +import json |
| 10 | + |
| 11 | + |
| 12 | +# Load environment variables (especially OPENAI_API_KEY) |
| 13 | +load_dotenv() |
| 14 | +logger = logging.getLogger(__name__) |
| 15 | +logger.setLevel(logging.INFO) |
| 16 | + |
| 17 | +# 1. Define tools |
| 18 | +@tool |
| 19 | +def get_word_length(word: str) -> int: |
| 20 | + """Returns the length of a word.""" |
| 21 | + return len(word) |
| 22 | + |
| 23 | +@tool |
| 24 | +def add_numbers(a: int, b: int) -> int: |
| 25 | + """Adds two numbers together.""" |
| 26 | + return a + b |
| 27 | + |
| 28 | +# Create the agent |
| 29 | +# Fix: Ensure environment variables are mapped to the correct arguments |
| 30 | +agent = create_agent( |
| 31 | + model=ChatOpenAI( |
| 32 | + model=os.getenv("MODEL_NAME", "gpt-4o-mini"), |
| 33 | + api_key=os.getenv("OPENAI_API_KEY"), |
| 34 | + base_url=os.getenv("OPENAI_API_BASE", "https://api.openai.com/v1"), |
| 35 | + temperature=0 |
| 36 | + ), |
| 37 | + tools=[get_word_length, add_numbers], |
| 38 | + system_prompt="You are a helpful assistant. You have access to tools to help answer questions." |
| 39 | +) |
| 40 | + |
| 41 | + |
| 42 | +app = AgentkitSimpleApp() |
| 43 | +@app.entrypoint |
| 44 | +async def run(payload: dict, headers: dict): |
| 45 | + prompt = payload.get("prompt") |
| 46 | + user_id = headers.get("user_id") |
| 47 | + session_id = headers.get("session_id") |
| 48 | + |
| 49 | + # Default values if still missing |
| 50 | + user_id = user_id or "default_user" |
| 51 | + session_id = session_id or "default_session" |
| 52 | + |
| 53 | + logger.info( |
| 54 | + f"Running agent with prompt: {prompt}, user_id: {user_id}, session_id: {session_id}" |
| 55 | + ) |
| 56 | + |
| 57 | + inputs = {"messages": [{"role": "user", "content": prompt}]} |
| 58 | + |
| 59 | + # stream returns an iterator of updates |
| 60 | + # To get the final result, we can just iterate or use invoke |
| 61 | + async for chunk in agent.astream(inputs, stream_mode="updates"): |
| 62 | + # chunk is a dict with node names as keys and state updates as values |
| 63 | + for node, state in chunk.items(): |
| 64 | + logger.debug(f"--- Node: {node} ---") |
| 65 | + |
| 66 | + if "messages" in state: |
| 67 | + last_msg = state["messages"][-1] |
| 68 | + |
| 69 | + for block in last_msg.content_blocks: |
| 70 | + # 返回的event_data数据结构要求符合 adk event规范： https://google.github.io/adk-docs/events/#identifying-event-origin-and-type |
| 71 | + event_data = { |
| 72 | + "content": { |
| 73 | + "parts": [ |
| 74 | + {"text": block.get("text") or block.get("reasoning")} |
| 75 | + ] |
| 76 | + } |
| 77 | + } |
| 78 | + yield json.dumps(event_data) |
| 79 | + |
| 80 | +@app.ping |
| 81 | +def ping() -> str: |
| 82 | + return "pong!" |
| 83 | + |
| 84 | +async def local_test(): |
| 85 | + """Helper to run the agent locally without server""" |
| 86 | + print("Running local test...") |
| 87 | + query = "What is the length of the word 'LangChain' and what is that length plus 5?" |
| 88 | + print(f"Query: {query}") |
| 89 | + async for event in run({"prompt": query}, {"user_id": "1", "session_id": "1"}): |
| 90 | + print(f"Received event: {event}") |
| 91 | + |
| 92 | +if __name__ == "__main__": |
| 93 | + app.run(host="0.0.0.0", port=8000) |
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