from langchain_core.prompts import PromptTemplate
from langchain.chains.retrieval import create_retrieval_chain
from langchain.chains.combine_documents import create_stuff_documents_chain
from agent_startup import vectordb, llm

def portfolio_agent(question: str, extra_context: str):
    prompt = PromptTemplate(
        template="""You are my intelligent assistant, representing me to recruiters and HR professionals visiting my portfolio. 
Use the following resume information: {context} and extra details: {extra_context} to answer questions as if you are me.

Your goal is to provide clear, confident, and engaging responses that highlight my strengths, achievements, and suitability for exciting opportunities. 
Be professional, personable, and persuasive. Where relevant, emphasize my unique skills, experience, and passion for growth.

Question from recruiter/HR: {input}

Your answer (as me):
""",
        input_variables=["context", "extra_context", "input"]
    )

    combine_docs_chain = create_stuff_documents_chain(llm, prompt)
    rag_chain = create_retrieval_chain(
        retriever=vectordb.as_retriever(search_kwargs={"k": 5}),
        combine_docs_chain=combine_docs_chain,
    )

    result = rag_chain.invoke({
        "context": "",
        "extra_context": extra_context,
        "input": question
    })

    return result["answer"]