agent.py

from langgraph.graph.message import add_messages
from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
from langgraph.prebuilt import ToolNode
from langgraph.graph import START, StateGraph
from langgraph.prebuilt import tools_condition
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from tools import extract_text
from langchain_community.tools import DuckDuckGoSearchRun


class AgentState(TypedDict):
    messages: Annotated[list[AnyMessage], add_messages]


class Agent():
    def __init__(self, llm):
        chat = ChatHuggingFace(llm=llm, verbose=True)
        
        search_tool = DuckDuckGoSearchRun()
        vision_llm = ChatOpenAI(model="gpt-4o")

        chat_with_tools = chat.bind_tools([extract_text,search_tool])
        self._initialize_graph()

    def _initialize_graph(self):
        builder = StateGraph(AgentState)

        # Define nodes
        builder.add_node("assistant", self.assistant)
        builder.add_node("tools", ToolNode(self.tools))

        # Define edges
        builder.add_edge(START, "assistant")
        builder.add_conditional_edges("assistant",tools_condition)
        builder.add_edge("tools", "assistant")

        # Compile the graph
        self.agent = builder.compile()

    def call_agent(self, messages):
        self.agent.invoke({"messages":messages})

    def assistant(state: AgentState):
        return {
            "messages": [chat_with_tools.invoke(state["messages"])],
        }