Titeltext angepasst

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2025-01-13 15:22:54 +01:00
parent 9507403c46
commit c9f8c54030
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File: RAG-Demo.py File: RAG-Demo.py
Author: Martin Rattensberger Author: Martin Rattensberger
Description: A GUI application for interacting with a local Llama vision model. Description: A GUI application for interacting with a local Llama vision model.
Users can select a directory with PDF files and ask questions about them. Users can select a directory with PDF files, load them into a vector database,
and ask questions about them.
Date: 11.11.2024 # Replace with actual date Date: 11.11.2024 # Replace with actual date
Version: 1.1 Version: 1.2
Development Environment: Visual Studio Code with Continue.ai (Claude Sonnet 3.5) Development Environment: Visual Studio Code with Continue.ai (Claude Sonnet 3.5)
This script creates a tkinter-based GUI for selecting a directory with PDFs, This script creates a tkinter-based GUI for selecting a directory with PDFs,
sending them to a local Llama 3.2 vision model, and displaying the results. loading them into a LanceDB vector database, and querying them using a local Llama 3.2 vision model.
""" """
import tkinter as tk import tkinter as tk
@@ -21,11 +22,30 @@ import base64
import threading import threading
import time import time
import os import os
import lancedb
import numpy as np
import pyarrow as pa
from sentence_transformers import SentenceTransformer
class LlamaVisionApp: class LlamaVisionApp:
def __init__(self, master): def __init__(self, master):
self.master = master self.master = master
master.title("Llama Vision Interface") master.title("Llama Vision Interface RAG")
# Initialize LanceDB and sentence transformer
self.db = lancedb.connect("./lancedb")
self.db.drop_table("pdf_embeddings")
schema = pa.schema([
('id', pa.int64()),
('filename', pa.string()),
('page', pa.int64()),
('text', pa.string()),
("embedding", pa.list_(pa.float32(), 384))
])
self.table = self.db.create_table("pdf_embeddings", schema=schema)
self.model = SentenceTransformer('all-MiniLM-L6-v2')
# Directory selection button # Directory selection button
self.select_dir_button = tk.Button(master, text="Select PDF Directory", command=self.select_directory) self.select_dir_button = tk.Button(master, text="Select PDF Directory", command=self.select_directory)
@@ -35,14 +55,14 @@ class LlamaVisionApp:
self.dir_label = tk.Label(master, text="No directory selected") self.dir_label = tk.Label(master, text="No directory selected")
self.dir_label.pack() self.dir_label.pack()
# PDF file listbox # Load PDFs button
self.pdf_listbox = tk.Listbox(master, width=50, height=5) self.load_pdfs_button = tk.Button(master, text="Load PDFs into Database", command=self.load_pdfs_to_db)
self.pdf_listbox.pack(pady=10) self.load_pdfs_button.pack(pady=10)
# Question input # Question input
self.question_entry = tk.Text(master, width=50, height=3) self.question_entry = tk.Text(master, width=50, height=3)
self.question_entry.pack(pady=10) self.question_entry.pack(pady=10)
self.question_entry.insert(tk.END, "What is in this PDF?") self.question_entry.insert(tk.END, "What is in these PDFs?")
# Submit button # Submit button
self.submit_button = tk.Button(master, text="Submit", command=self.submit_question) self.submit_button = tk.Button(master, text="Submit", command=self.submit_question)
@@ -54,51 +74,79 @@ class LlamaVisionApp:
self.directory_path = None self.directory_path = None
self.pdf_files = [] self.pdf_files = []
self.image_data = None
self.processing = False self.processing = False
def select_directory(self): def select_directory(self):
self.directory_path = filedialog.askdirectory() self.directory_path = filedialog.askdirectory()
if self.directory_path: if self.directory_path:
self.dir_label.config(text=f"Selected directory: {self.directory_path}") self.dir_label.config(text=f"Selected directory: {self.directory_path}")
self.load_pdf_files()
def load_pdf_files(self):
self.pdf_files = [f for f in os.listdir(self.directory_path) if f.lower().endswith('.pdf')] self.pdf_files = [f for f in os.listdir(self.directory_path) if f.lower().endswith('.pdf')]
self.pdf_listbox.delete(0, tk.END)
for pdf in self.pdf_files:
self.pdf_listbox.insert(tk.END, pdf)
def load_selected_pdf(self): def load_pdfs_to_db(self):
selected_indices = self.pdf_listbox.curselection() if not self.directory_path:
if not selected_indices:
return None
selected_pdf = self.pdf_files[selected_indices[0]]
pdf_path = os.path.join(self.directory_path, selected_pdf)
pdf_document = fitz.open(pdf_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")
image_data = base64.b64encode(buffer.getvalue()).decode('utf-8')
pdf_document.close()
return image_data
def submit_question(self):
self.image_data = self.load_selected_pdf()
if not self.image_data:
self.response_text.delete('1.0', tk.END) self.response_text.delete('1.0', tk.END)
self.response_text.insert(tk.END, "Please select a PDF file first.\n") self.response_text.insert(tk.END, "Please select a directory first.\n")
return return
self.processing = True
threading.Thread(target=self.processing_animation).start()
threading.Thread(target=self.process_pdfs).start()
def process_pdfs(self):
data = []
id_counter = 0
for pdf_file in self.pdf_files:
pdf_path = os.path.join(self.directory_path, pdf_file)
doc = fitz.open(pdf_path)
for page_num in range(len(doc)):
page = doc[page_num]
text = page.get_text()
embedding = self.model.encode(text)
data.append({
"id": id_counter,
"filename": pdf_file,
"page": page_num,
"text": text,
"embedding": embedding.tolist()
})
id_counter += 1
doc.close()
self.table.add(data)
self.processing = False
self.master.after(0, self.update_response, "Load Complete", f"Loaded {len(data)} pages from {len(self.pdf_files)} PDFs into the database.")
def submit_question(self):
question = self.question_entry.get('1.0', tk.END).strip() question = self.question_entry.get('1.0', tk.END).strip()
self.response_text.delete('1.0', tk.END) self.response_text.delete('1.0', tk.END)
self.processing = True self.processing = True
threading.Thread(target=self.processing_animation).start() threading.Thread(target=self.processing_animation).start()
threading.Thread(target=self.run_llama_model, args=(question,)).start() threading.Thread(target=self.query_database, args=(question,)).start()
def query_database(self, question):
try:
question_embedding = self.model.encode(question)
results = self.table.search(question_embedding).limit(5).to_list()
context = "\n".join([f"From {r['filename']} (Page {r['page']+1}):\n{r['text'][:500]}..." for r in results])
response = ollama.chat(
model='llama3.2-vision',
messages=[{
'role': 'system',
'content': f"You are an AI assistant that answers questions based on the following context:\n\n{context}"
},
{
'role': 'user',
'content': question
}]
)
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 processing_animation(self): def processing_animation(self):
animation = "|/-\\" animation = "|/-\\"
@@ -110,22 +158,6 @@ class LlamaVisionApp:
time.sleep(0.1) time.sleep(0.1)
i += 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): def update_response(self, question, answer):
self.response_text.delete('1.0', tk.END) self.response_text.delete('1.0', tk.END)
self.response_text.insert(tk.END, f"Q: {question}\nA: {answer}\n\n") self.response_text.insert(tk.END, f"Q: {question}\nA: {answer}\n\n")

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