react_agent.py

from basic_tools import *

from langgraph.prebuilt import create_react_agent
from utils import *
from langchain_core.messages import SystemMessage, HumanMessage


# Initial System message
system_message = SystemMessage(content="You are a helpful assistant. You are free to utilize the tools present and give back proper answer")


def main(search_query: str = "What is the capital of France?") -> None:
    # Initialize the LLM (loaded from the lmstudio server running on localhost:1234)
    llm = get_llm(provider="openai_local")
    if llm:
        web_search_tools = [multiply,
                            multiply, add, subtract, divide, modulus,
                            wiki_search, web_search, arxiv_search,
                            python_repl, analyze_image,
                            date_filter, analyze_content,
                            step_by_step_reasoning, translate_text
                            ]
        # Create a langgraph react agent with the LLM and tools.
        web_search_agent = create_react_agent(
            name="Web Search Agent",
            model=llm.bind(system_message=system_message),
            tools=web_search_tools,
            response_format={
                "title": "SearchResults",
                "description": "Structured JSON object with search results",
                "type": "object",
                "properties": {
                    "results": {
                        "type": "array",
                        "items": {"type": "string"}
                    }
                },
                "required": ["results"]
            }
        )

        # Provide a complete conversation history containing both a system and an initial user message.
        # This allows the agent to have a valid first user message. But the message can't be in the form of messages but should be in the form of a dict.
        # input_payload = {
        #     "messages": [
        #         {"role": "system", "content": system_message.content},
        #         {"role": "user", "content": f"{search_query}"}
        #     ]
        # }
        input_payload = {"messages": [
            system_message, HumanMessage(content=f"{search_query}")]}
        results = web_search_agent.invoke(input_payload)
        print(results)


if __name__ == "__main__":
    main("can you find out what is the best place to visit in  France")