src/graph/rag_graph.py

from langgraph.graph import StateGraph, END
from langgraph.checkpoint.memory import MemorySaver
from langchain_core.prompts import ChatPromptTemplate
from core.state import GraphState
from config.config import Config

class ProjectRAGGraph:
    def __init__(self, llm, vector_store):
        self.llm = llm
        self.vector_store = vector_store
        self.memory = MemorySaver()
        self.workflow = self._build_graph()

    # -------- Nodes --------
    def retrieve(self, state: GraphState):
        try:
            retriever = self.vector_store.as_retriever(
                search_type=Config.SEARCH_TYPE,
                search_kwargs={
                    "k": Config.TOP_K,
                    "lambda_mult": Config.LAMBDA_MULT
                }
            )
            docs = retriever.invoke(state["question"])
            return {"context": docs}

        except Exception as e:
            raise RuntimeError(f"Retrieval failed: {e}")

    def generate(self, state: GraphState):
        try:
            prompt = ChatPromptTemplate.from_template(
                """
                You are a professional Project Analyst.
                Context:
                {context}

                Question:
                {question}

                Answer strictly using the context. Cite sources.
                """
            )

            formatted_context = "\n\n".join(
                doc.page_content for doc in state["context"]
            )

            chain = prompt | self.llm
            response = chain.invoke({
                "context": formatted_context,
                "question": state["question"]
            })

            return {"answer": response.content}

        except Exception as e:
            raise RuntimeError(f"Answer generation failed: {e}")

    # -------- Graph --------
    def _build_graph(self):
        graph = StateGraph(GraphState)

        graph.add_node("retrieve", self.retrieve)
        graph.add_node("generate", self.generate)

        graph.set_entry_point("retrieve")
        graph.add_edge("retrieve", "generate")
        graph.add_edge("generate", END)

        return graph.compile(checkpointer=self.memory)

    def query(self, question: str, thread_id: str):
        try:
            config = {"configurable": {"thread_id": thread_id}}
            result = self.workflow.invoke({"question": question}, config=config)
            return result["answer"]

        except Exception as e:
            raise RuntimeError(f"Graph execution failed: {e}")