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from langchain_openai import ChatOpenAI
from langchain.schema import SystemMessage, HumanMessage
from langgraph.prebuilt import create_react_agent
from tools import (
wikipedia_search_tool, arxiv_search_tool,
audio_transcriber_tool, excel_tool, analyze_code_tool, image_tool,
add_tool, subtract_tool, multiply_tool, divide_tool, web_search_tool
)
# ──────────────────────────────── Config ────────────────────────────────
SYSTEM_PROMPT = """
You are a helpful AI assistant. You will answer questions by thinking step-by-step, taking actions using tools when necessary, and finishing with a final answer.
When you want to use a tool, respond *exactly* in the following format:
Thought: [your reasoning]
Action: [tool_name]
Action Input: [input]
When you receive an observation, continue reasoning. Write:
Thought: [final reasoning]
FINAL ANSWER: [your answer]
IMPORTANT:
- If using tools that require a `task_id`, only use the value provided.
- Do not make up tool names.
- Do not loop unnecessarily.
- Provide FINAL ANSWER fast.
- Try to use the web search tool first before using wiki and arxiv tools.
- If wiki tool doesnt give you enough information, try again with a shorter query, or a more genral query. Dont use a query that is too specific.
- DOnt user wiki tool more than 3 times.
"""
TOOLS = [
wikipedia_search_tool, arxiv_search_tool,
audio_transcriber_tool, excel_tool, analyze_code_tool, image_tool,
add_tool, subtract_tool, multiply_tool, divide_tool, web_search_tool
]
# ───────────────────────────── Agent Wrapper ─────────────────────────────
class SimpleLangGraphAgent:
def __init__(self, model_name="gpt-4o-mini"):
self.agent = create_react_agent(
model=ChatOpenAI(model_name=model_name, temperature=0.3),
tools=TOOLS,
)
def run(self, question: str, task_id: str = None, max_steps: int = 10) -> str:
messages = [SystemMessage(content=SYSTEM_PROMPT)]
if task_id:
messages[0].content += f"\n\nYour task_id is: {task_id}. Use it only with the tools that require it."
messages.append(HumanMessage(content=question))
state = {"messages": messages}
final_state = self.agent.invoke(state)
for msg in final_state["messages"][::-1]:
if "FINAL ANSWER:" in msg.content.upper():
print(f"\n\n thoughts = {msg.content.split('Thought:')[-1].strip()} \n\n")
return msg.content.split("FINAL ANSWER:")[-1].strip()
return "No FINAL ANSWER found."
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