# app/graph/nodes/synthesizer.py

from app.core.llm_engine import llm
from app.core.prompts.rag_prompt import rag_prompt
from app.core.prompts.hybrid_prompt import hybrid_prompt
from langchain_core.output_parsers import StrOutputParser


def synthesizer_node(state):
    route = state.get("route")
    general_answer = state.get("general_answer")

    # ✅ FIX: Use 'in' operator
    if route == "general":
        return {
            **state,
            "final_answer": general_answer or "I couldn't find relevant information."
        }
    
    # Prepare common inputs
    query = state["query"]
    context = state.get("context", "")
    history = state.get("history", "")
    
    # ✅ Route-specific prompt selection
    if route == "hybrid":
        chain = hybrid_prompt | llm | StrOutputParser()
        print("🔀 Using HYBRID prompt (doc snippet + general knowledge)")
    else:  # route == "rag"
        chain = rag_prompt | llm | StrOutputParser()
        print("📚 Using RAG prompt (document-only)")
    
    answer = chain.invoke({
        "context": context,
        "query": query,
        "history": history
    })

    return {
        **state,
        "final_answer": answer.strip()
    }