agent.py

from langchain_core.messages import SystemMessage
from langgraph.graph import START, StateGraph, MessagesState
from langgraph.prebuilt import ToolNode, tools_condition
from langchain_openai import ChatOpenAI
from typing import Optional, TypedDict, Annotated
from langgraph.graph.message import add_messages

from langfuse.langchain import CallbackHandler
from langfuse import get_client

from tools import tools

import os


class AgentState(TypedDict):
    task_id: str
    question: str
    file_name: str
    file_path: Optional[str]
    file_mime: Optional[str]
    messages: Annotated[list, add_messages]
    response: Optional[str]


langfuse = get_client()
 
# Verify connection
if langfuse.auth_check():
    print("Langfuse client is authenticated and ready!")
else:
    print("Authentication failed. Please check your credentials and host.")

langfuse_handler = CallbackHandler()

system_prompt = """You are a general AI assistant. I will ask you a question. 
Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. 
YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. 
If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. 
If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. 
If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
"""

# System message
sys_msg = SystemMessage(content=system_prompt)

class AgentIzzy:
    def __init__(self):
        llm = ChatOpenAI(
            model="gpt-4o",
            temperature=0,
            max_tokens=None,
            timeout=None,
            max_retries=2,
        )

        llm_with_tools = llm.bind_tools(tools)

        def assistant(state: MessagesState):
            response = llm_with_tools.invoke(state["messages"])
            print("LLM returned:", response)

            return {"messages": [response]}
            
        builder = StateGraph(MessagesState)
        builder.add_node("assistant", assistant)
        builder.add_node("tools", ToolNode(tools))
        builder.add_edge(START, "assistant")
        # builder.add_edge("retriever", "assistant")
        builder.add_conditional_edges(
            "assistant",
            tools_condition,
        )
        builder.add_edge("tools", "assistant")
        
        self.graph = builder.compile()

        # img_bytes = self.graph.get_graph().draw_mermaid_png()
        # with open("agent_izzy_graph.png", "wb") as f:
        #     f.write(img_bytes)


    def __call__(self, state_input: dict) -> str:
        question = state_input["question"]

        print(f"Agent received question: {question}")
        messages = [sys_msg] + state_input.get("messages", [])
        state_input["messages"] = messages

        output = self.graph.invoke(state_input,
                                   config={"callbacks": [langfuse_handler]})
        
        answer = output['messages'][-1].content
        print("Agent response (first 50 chars):", answer[:50] + "..." if len(answer) > 50 else answer)
        return answer