Update app.py

app.py

@@ -13,7 +13,6 @@ import networkx as nx
 from collections import Counter
 import json
 from datetime import datetime
-from transformers import pipeline
 
 @dataclass
 class ChatMessage:
@@ -33,8 +32,6 @@ class XylariaChat:
             model="Qwen/QwQ-32B-Preview",
             token=self.hf_token
         )
-        
-        self.image_captioning_pipe = pipeline("image-text-to-text", model="llava-onevision-qwen2-0.5b-si-hf")
 
         self.image_api_url = "https://api-inference.huggingface.co/models/Salesforce/blip-image-captioning-large"
         self.image_api_headers = {"Authorization": f"Bearer {self.hf_token}"}
@@ -404,29 +401,6 @@ class XylariaChat:
             print(f"Error resetting API client: {e}")
 
         return None
-    
-    def caption_image_llava(self, image_path, prompt):
-        try:
-            with open(image_path, "rb") as img_file:
-                image_data = base64.b64encode(img_file.read()).decode("utf-8")
-
-            messages = [
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "image", "url": image_path},
-                        {"type": "text", "text": prompt},
-                    ],
-                },
-            ]
-            
-            caption_result = self.image_captioning_pipe(text=messages, max_new_tokens=50)
-            
-            caption = caption_result[0]['generated_text'] if caption_result else "No caption generated"
-            
-            return caption
-        except Exception as e:
-            return f"Error captioning image with llava: {str(e)}"
 
     def caption_image(self, image):
         try:
@@ -510,9 +484,8 @@ class XylariaChat:
                 messages.append(msg)
 
             if image:
-                image_caption_prompt = "Can you describe this image for me?"
-                caption = self.caption_image_llava(image, image_caption_prompt)
-                user_input = f"Here is a description of an image: {caption}\n\n{user_input}"
+                image_caption = self.caption_image(image)
+                user_input = f"description of an image: {image_caption}\n\nUser's message about it: {user_input}"
 
             messages.append(ChatMessage(
                 role="user",