import gradio as gr
import pandas as pd
import os
import requests

# Get Hugging Face API token from secret
HF_TOKEN = os.getenv("HF_TOKEN")
MODEL_ID = "deepset/tinyroberta-squad2"
file_data = {"text": None}
headers = {"Authorization": f"Bearer {HF_TOKEN}"}

# Handle file upload
def upload_file(file):
    if file is None or not hasattr(file, "name"):
        return [], "❌ No file uploaded."

    try:
        if file.name.endswith(".csv"):
            df = pd.read_csv(file.name)
            file_data["text"] = df.to_string(index=False)
        elif file.name.endswith(".txt"):
            file_data["text"] = file.read().decode("utf-8")
        else:
            return [], "❌ Please upload a .txt or .csv file."
        return [], "✅ File uploaded. Now ask your question."
    except Exception as e:
        return [], f"❌ Error reading file: {e}"

# Handle user question
def ask_question(message, history):
    if not message or not file_data["text"]:
        return "", history + [[message, "📄 Please upload a file and type a question."]]

    context = file_data["text"][:1500]  # truncate long content

    payload = {
        "inputs": {
            "question": message,
            "context": context
        }
    }

    try:
        response = requests.post(
            f"https://api-inference.huggingface.co/models/{MODEL_ID}",
            headers=headers,
            json=payload
        )
        result = response.json()
        answer = result.get("answer", "🤷 No answer found.")
    except Exception as e:
        answer = f"❌ API error: {e}"

    return "", history + [[message, answer]]

# Build the Gradio UI
with gr.Blocks() as demo:
    chatbot = gr.Chatbot(label="Chat with Your File")
    file_input = gr.File(label="Upload .txt or .csv")
    msg = gr.Textbox(label="Your Question")
    send = gr.Button("Send")
    status = gr.Textbox(label="Status", interactive=False)

    file_input.change(upload_file, inputs=file_input, outputs=[chatbot, status])
    send.click(ask_question, inputs=[msg, chatbot], outputs=[msg, chatbot])
    gr.ClearButton([msg, file_input, chatbot])

demo.launch()