124 lines
4.6 KiB
Python
124 lines
4.6 KiB
Python
"""
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File: llamaVisionApp.py
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Author: Martin Rattensberger
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Description: A GUI application for interacting with a local Llama vision model.
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Users can upload images or PDFs and ask questions about them.
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Date: 11.11.2024 # Replace with actual date
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Version: 1.0
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Development Environment: Visual Studio Code with Continue.ai (Claude Sonnet 3.5)
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This script creates a tkinter-based GUI for uploading images or PDFs,
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sending them to a local Llama 3.2 vision model, and displaying the results.
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"""
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import tkinter as tk
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from tkinter import filedialog, scrolledtext
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import ollama
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from PIL import Image
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import fitz # PyMuPDF library for handling PDFs
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import io
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import base64
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import threading
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import time
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class LlamaVisionApp:
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def __init__(self, master):
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self.master = master
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master.title("Llama Vision Interface")
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# File upload button
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self.upload_button = tk.Button(master, text="Upload File", command=self.upload_file)
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self.upload_button.pack(pady=10)
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# Display selected filename
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self.filename_label = tk.Label(master, text="No file selected")
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self.filename_label.pack()
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# Question input - now larger
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self.question_entry = tk.Text(master, width=50, height=3) # Changed from Entry to Text
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self.question_entry.pack(pady=10)
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self.question_entry.insert(tk.END, "What is in this image?")
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# Submit button
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self.submit_button = tk.Button(master, text="Submit", command=self.submit_question)
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self.submit_button.pack()
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# Response display
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self.response_text = scrolledtext.ScrolledText(master, width=60, height=30)
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self.response_text.pack(pady=10)
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self.file_path = None
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self.image_data = None
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self.processing = False
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def upload_file(self):
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self.file_path = filedialog.askopenfilename(filetypes=[("Image files", "*.png *.jpg *.jpeg *.gif"), ("PDF files", "*.pdf")])
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if self.file_path:
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self.filename_label.config(text=f"Selected file: {self.file_path}")
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self.load_file()
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def load_file(self):
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if self.file_path.lower().endswith(('.png', '.jpg', '.jpeg', '.gif')):
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with open(self.file_path, "rb") as image_file:
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self.image_data = base64.b64encode(image_file.read()).decode('utf-8')
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elif self.file_path.lower().endswith('.pdf'):
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pdf_document = fitz.open(self.file_path)
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first_page = pdf_document[0]
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image = first_page.get_pixmap()
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img = Image.frombytes("RGB", [image.width, image.height], image.samples)
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buffer = io.BytesIO()
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img.save(buffer, format="PNG")
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self.image_data = base64.b64encode(buffer.getvalue()).decode('utf-8')
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pdf_document.close()
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def submit_question(self):
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if not self.image_data:
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self.response_text.delete('1.0', tk.END) # Clear previous response
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self.response_text.insert(tk.END, "Please upload an image or PDF first.\n")
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return
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question = self.question_entry.get('1.0', tk.END).strip() # Get text from Text widget
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# Clear previous response
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self.response_text.delete('1.0', tk.END)
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# Start processing animation
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self.processing = True
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threading.Thread(target=self.processing_animation).start()
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# Run the Llama model in a separate thread
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threading.Thread(target=self.run_llama_model, args=(question,)).start()
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def processing_animation(self):
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animation = "|/-\\"
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i = 0
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while self.processing:
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self.response_text.delete('1.0', tk.END)
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self.response_text.insert(tk.END, f"Processing {animation[i % len(animation)]}")
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self.master.update_idletasks()
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time.sleep(0.1)
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i += 1
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def run_llama_model(self, question):
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try:
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response = ollama.chat(
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model='llama3.2-vision',
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messages=[{
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'role': 'user',
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'content': question,
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'images': [self.image_data]
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}]
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)
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self.processing = False
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self.master.after(0, self.update_response, question, response['message']['content'])
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except Exception as e:
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self.processing = False
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self.master.after(0, self.update_response, question, f"Error: {str(e)}")
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def update_response(self, question, answer):
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self.response_text.delete('1.0', tk.END)
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self.response_text.insert(tk.END, f"Q: {question}\nA: {answer}\n\n")
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root = tk.Tk()
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app = LlamaVisionApp(root)
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root.mainloop()
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