agents/agent.py

"""LangGraph Agent for GAIA Benchmark"""
import os
from dotenv import load_dotenv

from langgraph.graph import START, StateGraph, MessagesState
from langgraph.prebuilt import tools_condition, ToolNode
from langchain_core.messages import SystemMessage, HumanMessage
from langchain_groq import ChatGroq
from tools.CodeToolkit import execute_code_multilang
from tools.DocumentsToolkit import (
    save_and_read_file,
    download_file_from_url,
    extract_text_from_image,
    analyze_csv_file,
    analyze_excel_file,
    analyze_word_file,
    analyze_pdf_file
)
from tools.ImagesToolkit import (
    analyze_image,
    transform_image,
    draw_on_image,
    generate_simple_image,
    combine_images
)
from tools.MathsToolkit import (
    multiply, add, subtract, divide, modulus, power, square_root
)
from tools.SearchToolkit import wiki_search, web_search, arxiv_search, vector_store

# Load environment variables
load_dotenv()

# Load system prompt
with open("system_prompt.txt", "r", encoding="utf-8") as f:
    system_prompt = f.read()
sys_msg = SystemMessage(content=system_prompt)

# Toolset
tools = [
    # SearchToolkit
    web_search,
    wiki_search,
    arxiv_search,

    # MathsToolkit
    multiply,
    add,
    subtract,
    divide,
    modulus,
    power,
    square_root,

    # DocumentsToolkit
    save_and_read_file,
    download_file_from_url,
    extract_text_from_image,
    analyze_csv_file,
    analyze_excel_file,
    analyze_word_file,
    analyze_pdf_file,

    # CodeToolkit
    execute_code_multilang,

    # ImagesToolkit
    analyze_image,
    transform_image,
    draw_on_image,
    generate_simple_image,
    combine_images,
]

# Build LangGraph workflow


def build_graph():
    llm = ChatGroq(model="qwen-qwq-32b", temperature=0)
    llm_with_tools = llm.bind_tools(tools)

    def assistant(state: MessagesState):
        return {"messages": [llm_with_tools.invoke(state["messages"])]}

    def retriever(state: MessagesState):
        similar = vector_store.similarity_search(state["messages"][0].content)
        if similar:
            reference = HumanMessage(
                content=f"Here is a similar Q&A that might help: \n\n{similar[0].page_content}"
            )
            return {"messages": [sys_msg] + state["messages"] + [reference]}
        else:
            return {"messages": [sys_msg] + state["messages"]}

    builder = StateGraph(MessagesState)
    builder.add_node("retriever", retriever)
    builder.add_node("assistant", assistant)
    builder.add_node("tools", ToolNode(tools))
    builder.add_edge(START, "retriever")
    builder.add_edge("retriever", "assistant")
    builder.add_conditional_edges("assistant", tools_condition)
    builder.add_edge("tools", "assistant")

    return builder.compile()