import os
os.environ['OPENAI_API_KEY'] = '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'  # Replace with your key
from llama_index.readers.file import PDFReader
from llama_index.core import VectorStoreIndex
from llama_index.llms.openai import OpenAI
from llama_index.core.chat_engine import CondenseQuestionChatEngine

chat_engine = None

def load_resume(pdf_file):
    global chat_engine
    reader = PDFReader()
    documents = reader.load_data(file=pdf_file.name)

    index = VectorStoreIndex.from_documents(documents)
    llm = OpenAI(model="gpt-3.5-turbo")  # Uses your OpenAI API key already set

    chat_engine = index.as_chat_engine(
        chat_mode="context",
        llm=llm,
        system_prompt=(
            "You are the person whose resume has been uploaded. "
            "Answer all questions in first person, confidently and professionally."
            "Reply in Markdown"
        )
    )
    return "✅ Resume uploaded and indexed. Ask away!"

def ask_bot(user_input):
    if chat_engine is None:
        return "❌ Please upload a resume first."
    response = chat_engine.chat(user_input)
    return f"**Answer:**\n\n{response.response.strip()}"
import gradio as gr

chat_history = []  # to store (question, answer) tuples

def ask_and_update(user_input):
    global chat_history
    if chat_engine is None:
        return "❌ Please upload a resume first.", ""

    # Get bot response
    response = chat_engine.chat(user_input)
    answer = response.response.strip()

    # Append Q&A to history
    chat_history.append((user_input, answer))

    # Build Markdown display
    formatted_chat = ""
    for q, a in chat_history:
        formatted_chat += f"**You:** {q}\n\n**Bot:** {a}\n\n---\n"

    return "", formatted_chat  # clear input, update chat display

with gr.Blocks(theme=gr.themes.Base(), css="""
#title {text-align: center;}
#ask_input textarea {font-size: 16px;}
""") as demo:

    gr.Markdown("## 🧠 <span id='title'>Resume Q&A Assistant</span>")

    with gr.Group():
        gr.Markdown("### 📄 Upload Your Resume")
        with gr.Row():
            resume_input = gr.File(label="Resume (PDF only)", file_types=[".pdf"])
            upload_button = gr.Button("📤 Upload & Start")
        upload_output = gr.Textbox(label="Status", interactive=False)

    with gr.Group():
        gr.Markdown("### 💬 Ask About Your Resume")

        chat_output = gr.Markdown("👋 Ask me anything about your resume!", elem_id="chat_log")

        chat_input = gr.Textbox(
            label="Ask a Question",
            placeholder="e.g., What are my strengths?",
            lines=2,
            elem_id="ask_input"
        )

    upload_button.click(fn=load_resume, inputs=[resume_input], outputs=[upload_output])
    chat_input.submit(fn=ask_and_update, inputs=[chat_input], outputs=[chat_input, chat_output])

demo.launch()