Update app.py

app.py

@@ -1,29 +1,26 @@
 import os
 
-import openai
 import streamlit as st
 from dotenv import load_dotenv
 from PIL import Image
 
 from blip_model import extract_image_details
-from gpt_model import generate_response
+from qwen_model import generate_response
 
-# Load environment variables from .env file
+# Load environment variables from .env (if you have any relevant ones)
 load_dotenv()
 
-# Set OpenAI API key
-openai.api_key = os.getenv('api_key')
-
 # Initialize session state for image details
 if "image_details" not in st.session_state:
     st.session_state.image_details = ""
 
-st.title("Image to Text Response with RAG")
+st.title("Image to Text Response with RAG (Qwen)")
 
 # File uploader for image upload
 uploaded_file = st.file_uploader("Upload an Image", type=["jpg", "jpeg", "png"])
 
 if uploaded_file is not None:
+    # Check if a new file is uploaded
     if "uploaded_file" not in st.session_state or uploaded_file != st.session_state.uploaded_file:
         st.session_state.uploaded_file = uploaded_file
 
@@ -33,10 +30,12 @@ if uploaded_file is not None:
         # Show loading status while processing the image
         with st.status("Processing image...", state="running"):
             image = Image.open(uploaded_file)
+            # Extract text details from the image (using your BLIP model)
             st.session_state.image_details = extract_image_details(image)
 
         st.success("Image processed successfully.")
 else:
+    # If no file is uploaded, stop the execution
     st.stop()
 
 # Chat interface
@@ -57,7 +56,7 @@ if st.session_state.image_details:
         # Add user message to session state
         st.session_state.messages.append({"role": "user", "content": prompt})
 
-        # Generate response
+        # Generate response using Qwen
         response = generate_response([st.session_state.image_details], prompt)
         st.session_state.messages.append({"role": "assistant", "content": response})