import os
from groq import Groq
import gradio as gr
import pandas as pd
from PyPDF2 import PdfReader
from docx import Document

# -------------------------------
# Get your API key from environment
# -------------------------------
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
if not GROQ_API_KEY:
    raise ValueError("Please set your GROQ_API_KEY environment variable!")

# Initialize Groq client
client = Groq(api_key=GROQ_API_KEY)

# -------------------------------
# Helper function: extract text from uploaded files
# -------------------------------
def extract_file_text(uploaded_file):
    if not uploaded_file:
        return ""
    
    filename = uploaded_file.name.lower()
    try:
        if filename.endswith(".txt"):
            with open(uploaded_file.name, "r", encoding="utf-8") as f:
                return f.read()
        elif filename.endswith(".pdf"):
            reader = PdfReader(uploaded_file.name)
            return "\n".join([page.extract_text() for page in reader.pages if page.extract_text()])
        elif filename.endswith(".docx"):
            doc = Document(uploaded_file.name)
            return "\n".join([p.text for p in doc.paragraphs])
        elif filename.endswith(".csv"):
            df = pd.read_csv(uploaded_file.name)
            return df.to_string()
        elif filename.endswith(".xlsx"):
            df = pd.read_excel(uploaded_file.name)
            return df.to_string()
        else:
            return "[Unsupported file type]"
    except Exception as e:
        return f"[Error reading file: {str(e)}]"

# -------------------------------
# Chatbot logic
# -------------------------------
def healthcare_assistant(message, history, uploaded_file):
    # Extract file text
    file_text = extract_file_text(uploaded_file)

    # System prompt
    messages = [
        {
            "role": "system",
            "content": "You are a helpful Professional Role Pathway Bot — turns a Job Description or uploaded file content into a personalized, step-by-step upskilling plan."
        }
    ]

    # Add previous chat history
    for user_msg, bot_msg in history:
        messages.append({"role": "user", "content": user_msg})
        if bot_msg:
            messages.append({"role": "assistant", "content": bot_msg})

    # Combine user message + file content
    combined_message = message
    if file_text:
        combined_message += "\n\nFile content:\n" + file_text
    messages.append({"role": "user", "content": combined_message})

    # Call Groq API
    response = client.chat.completions.create(
        model="llama-3.1-8b-instant",
        messages=messages
    )

    return response.choices[0].message.content

# -------------------------------
# Gradio UI
# -------------------------------
with gr.Blocks() as demo:
    history = gr.State([])  # store chat history

    gr.Markdown("## Professional Role Pathway Bot 🤖\nPaste JD, answer prompts, or upload a file to get personalized learning roadmap.")

    chatbox = gr.Chatbot()

    with gr.Row():
        txt = gr.Textbox(label="Type your message", placeholder="Enter text here...")
        file_input = gr.File(label="Upload file (optional)", file_types=[".txt", ".pdf", ".docx", ".csv", ".xlsx"])
        submit_btn = gr.Button("Send")

    # Respond function
    def respond(message, history, uploaded_file):
        response = healthcare_assistant(message, history, uploaded_file)
        history.append((message, response))
        return history, ""

    submit_btn.click(respond, inputs=[txt, history, file_input], outputs=[chatbox, txt])

# -------------------------------
# Launch
# -------------------------------
if __name__ == "__main__":
    demo.launch()