"""
File: llamaVisionApp.py
Author: Martin Rattensberger
Description: A GUI application for interacting with a local Llama vision model.
             Users can upload images or PDFs and ask questions about them.
Date: 11.11.2024 # Replace with actual date
Version: 1.0
Development Environment: Visual Studio Code with Continue.ai (Claude Sonnet 3.5)

This script creates a tkinter-based GUI for uploading images or PDFs,
sending them to a local Llama 3.2 vision model, and displaying the results.
"""

import tkinter as tk
from tkinter import filedialog, scrolledtext
import ollama
from PIL import Image
import fitz  # PyMuPDF library for handling PDFs
import io
import base64
import threading
import time

class LlamaVisionApp:
    def __init__(self, master):
        self.master = master
        master.title("Llama Vision Interface")

        # File upload button
        self.upload_button = tk.Button(master, text="Upload File", command=self.upload_file)
        self.upload_button.pack(pady=10)

        # Display selected filename
        self.filename_label = tk.Label(master, text="No file selected")
        self.filename_label.pack()

        # Question input - now larger
        self.question_entry = tk.Text(master, width=50, height=3)  # Changed from Entry to Text
        self.question_entry.pack(pady=10)
        self.question_entry.insert(tk.END, "What is in this image?")

        # Submit button
        self.submit_button = tk.Button(master, text="Submit", command=self.submit_question)
        self.submit_button.pack()

        # Response display
        self.response_text = scrolledtext.ScrolledText(master, width=60, height=30)
        self.response_text.pack(pady=10)

        self.file_path = None
        self.image_data = None
        self.processing = False

    def upload_file(self):
        self.file_path = filedialog.askopenfilename(filetypes=[("Image files", "*.png *.jpg *.jpeg *.gif"), ("PDF files", "*.pdf")])
        if self.file_path:
            self.filename_label.config(text=f"Selected file: {self.file_path}")
            self.load_file()

    def load_file(self):
        if self.file_path.lower().endswith(('.png', '.jpg', '.jpeg', '.gif')):
            with open(self.file_path, "rb") as image_file:
                self.image_data = base64.b64encode(image_file.read()).decode('utf-8')
        elif self.file_path.lower().endswith('.pdf'):
            pdf_document = fitz.open(self.file_path)
            first_page = pdf_document[0]
            image = first_page.get_pixmap()
            img = Image.frombytes("RGB", [image.width, image.height], image.samples)
            buffer = io.BytesIO()
            img.save(buffer, format="PNG")
            self.image_data = base64.b64encode(buffer.getvalue()).decode('utf-8')
            pdf_document.close()

    def submit_question(self):
        if not self.image_data:
            self.response_text.delete('1.0', tk.END)  # Clear previous response
            self.response_text.insert(tk.END, "Please upload an image or PDF first.\n")
            return

        question = self.question_entry.get('1.0', tk.END).strip()  # Get text from Text widget
        # Clear previous response
        self.response_text.delete('1.0', tk.END)
            
        # Start processing animation
        self.processing = True
        threading.Thread(target=self.processing_animation).start()

        # Run the Llama model in a separate thread
        threading.Thread(target=self.run_llama_model, args=(question,)).start()

    def processing_animation(self):
        animation = "|/-\\"
        i = 0
        while self.processing:
            self.response_text.delete('1.0', tk.END)
            self.response_text.insert(tk.END, f"Processing {animation[i % len(animation)]}")
            self.master.update_idletasks()
            time.sleep(0.1)
            i += 1

    def run_llama_model(self, question):
        try:
            response = ollama.chat(
                model='llama3.2-vision',
                messages=[{
                    'role': 'user',
                    'content': question,
                    'images': [self.image_data]
                }]
            )
            self.processing = False
            self.master.after(0, self.update_response, question, response['message']['content'])
        except Exception as e:
            self.processing = False
            self.master.after(0, self.update_response, question, f"Error: {str(e)}")

    def update_response(self, question, answer):
        self.response_text.delete('1.0', tk.END)
        self.response_text.insert(tk.END, f"Q: {question}\nA: {answer}\n\n")

root = tk.Tk()
app = LlamaVisionApp(root)
root.mainloop()