Update app.py

app.py

@@ -1,84 +1,21 @@
 import gradio as gr
-from transformers import pipeline, AutoTokenizer
-from transformers import AutoModelForCausalLM
+import openai
 from langdetect import detect
-from huggingface_hub import login
 import os
-import base64
 from PIL import Image
 from transformers import BlipProcessor, BlipForConditionalGeneration
 import requests
 from bs4 import BeautifulSoup
 import cv2
-from io import BytesIO
 import torch
-from sentence_transformers import SentenceTransformer
-import numpy as np
-import faiss
 
+# Set up OpenAI API key
+openai.api_key = os.getenv("OPENAI_API_KEY")
 
-login(token=os.getenv("chatbot"))
-generator = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1")
+# Translation pipelines (keeping these for language support)
+from transformers import pipeline
 bg_to_en = pipeline("translation", model="Helsinki-NLP/opus-mt-bg-en")
 en_to_bg = pipeline("translation", model="Helsinki-NLP/opus-mt-en-bg")
-tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
-
-def load_chunks(path, chunk_size=300):
-    with open(path, "r", encoding="utf-8") as f:
-        text = f.read()
-
-    sentences = text.split(". ")
-    chunks, chunk = [], ""
-
-    for sentence in sentences:
-        if len(chunk.split()) + len(sentence.split()) < chunk_size:
-            chunk += sentence + ". "
-        else:
-            chunks.append(chunk.strip())
-            chunk = sentence + ". "
-
-    if chunk:
-        chunks.append(chunk.strip())
-
-    return chunks
-
-# Load your document chunks
-chunks = load_chunks("MasterBrand Explanation.txt")
-
-# Create embeddings
-embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
-embeddings = embedding_model.encode(chunks)
-
-# Build FAISS index
-dimension = embeddings[0].shape[0]
-index = faiss.IndexFlatL2(dimension)
-index.add(np.array(embeddings))
-
-def search_similar_chunks(query, k=3):
-    query_embedding = embedding_model.encode([query])
-    distances, indices = index.search(np.array(query_embedding), k)
-    return [chunks[i] for i in indices[0]]
-
-def generate_answer_with_context(question):
-    top_chunks = search_similar_chunks(question)
-    context = "\n\n".join(top_chunks)
-
-    prompt = f"""<s>
-You are a helpful assistant trained on e-commerce and branding content.
-
-Use the context below to answer the question.
-
-Context:
-{context}
-
-Question: {question}
-Answer:"""
-
-    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-    outputs = model.generate(**inputs, max_new_tokens=300)
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    return response.replace(prompt, "").strip()
 
 # Load BLIP for image captioning
 blip_processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
@@ -86,12 +23,14 @@ blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image
 blip_model.to("cuda" if torch.cuda.is_available() else "cpu")
 
 def describe_image(image):
+    """Generate description for uploaded images"""
     inputs = blip_processor(images=image, return_tensors="pt").to(blip_model.device)
     out = blip_model.generate(**inputs)
     caption = blip_processor.decode(out[0], skip_special_tokens=True)
     return caption
 
 def describe_video(video_path):
+    """Extract first frame from video and describe it"""
     cap = cv2.VideoCapture(video_path)
     success, frame = cap.read()
     cap.release()
@@ -102,6 +41,7 @@ def describe_video(video_path):
         return "Could not read video frame."
 
 def extract_text_from_url(url):
+    """Extract text content from provided URL"""
     try:
         response = requests.get(url, timeout=5)
         soup = BeautifulSoup(response.text, 'html.parser')
@@ -111,7 +51,24 @@ def extract_text_from_url(url):
     except Exception as e:
         return f"Failed to fetch URL: {str(e)}"
 
+def generate_chatgpt_response(messages, temperature=0.7):
+    """Generate response using OpenAI's ChatGPT API"""
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",  # You can change this to "gpt-4" if you have access
+            messages=messages,
+            temperature=temperature,
+            max_tokens=500,
+            top_p=1.0,
+            frequency_penalty=0.0,
+            presence_penalty=0.0
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"Error generating response: {str(e)}"
+
 def generate_response(user_input, top_p, temperature, chat_counter, chatbot, history, image=None, video=None, url=None, request: gr.Request = None):
+    """Main function to generate AI responses"""
     lang = detect(user_input)
     print(f"Detected language: {lang}")
 
@@ -121,39 +78,44 @@ def generate_response(user_input, top_p, temperature, chat_counter, chatbot, his
     else:
         user_input_translated = user_input
 
-    prompt = ""
-
-    top_chunks = search_similar_chunks(user_input_translated)
-    rag_context = "\n\n".join(top_chunks)
-
-    prompt += f"[Context from your e-commerce training document]:\n{rag_context}\n\n"
+    # Build the conversation context for ChatGPT
+    messages = [
+        {"role": "system", "content": "You are a helpful AI assistant. Provide clear, friendly, and informative responses to user questions."}
+    ]
+    
+    # Add conversation history
+    for msg in history:
+        messages.append(msg)
 
+    # Prepare the current user message
+    current_message = user_input_translated
 
     # Multimodal additions
     if image is not None:
         try:
             img_desc = describe_image(image)
-            prompt += f"[Image Description]: {img_desc}\n"
+            current_message += f"\n[Image Description]: {img_desc}"
         except Exception as e:
-            prompt += f"[Image Error]: {str(e)}\n"
+            current_message += f"\n[Image Error]: {str(e)}"
 
     if video is not None:
         try:
             vid_desc = describe_video(video)
-            prompt += f"[Video Description]: {vid_desc}\n"
+            current_message += f"\n[Video Description]: {vid_desc}"
         except Exception as e:
-            prompt += f"[Video Error]: {str(e)}\n"
+            current_message += f"\n[Video Error]: {str(e)}"
 
     if url:
         url_content = extract_text_from_url(url)
-        prompt += f"[URL Content]: {url_content}\n"
+        current_message += f"\n[URL Content]: {url_content}"
 
-    # Append user message to prompt
-    prompt += f"User said:\n{user_input_translated}\n\nGive simple, friendly, clear advice:\n"
+    # Add current user message
+    messages.append({"role": "user", "content": current_message})
 
-    # Generate response
-    response_text = generator(prompt, max_length=200, top_p=top_p, temperature=temperature, do_sample=True)[0]["generated_text"]
+    # Generate response using ChatGPT
+    response_text = generate_chatgpt_response(messages, temperature)
 
+    # Translate back if needed
     if lang == "bg":
         response_text = en_to_bg(response_text)[0]["translation_text"]
 
@@ -165,21 +127,19 @@ def generate_response(user_input, top_p, temperature, chat_counter, chatbot, his
     return history, history, chat_counter, "✅ Success", gr.update(value=''), gr.update(interactive=True)
 
 def reset_textbox():
+    """Reset the input textbox"""
     return gr.update(value='')
 
 # ==== Enhanced Custom CSS with Masterbrand Styling ====
 custom_css = f""" 
 @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800;900&display=swap');
-
 * {{
     font-family: 'Inter', sans-serif !important;
 }}
-
 .gradio-container {{
     background: linear-gradient(135deg, #0a0a0a 0%, #1a0a0a 50%, #2a1a1a 100%) !important;
     min-height: 100vh !important;
 }}
-
 .main-header {{
     background: linear-gradient(135deg, #0a0a0a 0%, #1a0a0a 50%, #2a1a1a 100%) !important;
     padding: 2rem 0 3rem 0 !important;
@@ -189,7 +149,6 @@ custom_css = f"""
     position: relative !important;
     overflow: hidden !important;
 }}
-
 .main-header::before {{
     content: '';
     position: absolute;
@@ -200,7 +159,6 @@ custom_css = f"""
     background: radial-gradient(circle at 50% 50%, rgba(255, 0, 0, 0.1) 0%, transparent 70%);
     pointer-events: none;
 }}
-
 .logo-container {{
     display: flex !important;
     justify-content: center !important;
@@ -208,7 +166,6 @@ custom_css = f"""
     margin-bottom: 1.5rem !important;
     gap: 1rem !important;
 }}
-
 .logo-image {{
     width: 50px !important;
     height: 50px !important;
@@ -217,11 +174,9 @@ custom_css = f"""
     animation: pulse-glow 2s ease-in-out infinite alternate !important;
     transition: transform 0.3s ease !important;
 }}
-
 .logo-image:hover {{
     transform: scale(1.1) !important;
 }}
-
 .brand-text {{
     background: linear-gradient(135deg, #00ff41 0%, #ffffff 50%, #ff0000 100%) !important;
     -webkit-background-clip: text !important;
@@ -232,7 +187,6 @@ custom_css = f"""
     letter-spacing: 2px !important;
     text-shadow: 0 0 20px rgba(0, 255, 65, 0.3) !important;
 }}
-
 .main-header h1 {{
     color: #ffffff !important;
     font-size: 3.5rem !important;
@@ -244,14 +198,12 @@ custom_css = f"""
     background-clip: text !important;
     margin: 0 !important;
 }}
-
 .main-header p {{
     color: #cccccc !important;
     font-size: 1.3rem !important;
     font-weight: 500 !important;
     margin-top: 0.5rem !important;
 }}
-
 .chatbot-container {{
     background: rgba(26, 26, 26, 0.95) !important;
     border: 2px solid #ff0000 !important;
@@ -260,7 +212,6 @@ custom_css = f"""
     margin-bottom: 2rem !important;
     backdrop-filter: blur(10px) !important;
 }}
-
 .input-section {{
     background: rgba(26, 26, 26, 0.8) !important;
     border: 2px solid #333333 !important;
@@ -271,20 +222,16 @@ custom_css = f"""
     backdrop-filter: blur(10px) !important;
     transition: all 0.3s ease !important;
 }}
-
 .input-section:hover {{
     border-color: #ff0000 !important;
     box-shadow: 0 15px 40px rgba(255, 0, 0, 0.2) !important;
 }}
-
 .input-group {{
     margin-bottom: 1.5rem !important;
 }}
-
 .input-group:last-child {{
     margin-bottom: 0 !important;
 }}
-
 .input-label {{
     color: #ffffff !important;
     font-size: 1.1rem !important;
@@ -294,12 +241,10 @@ custom_css = f"""
     align-items: center !important;
     gap: 0.5rem !important;
 }}
-
 .input-icon {{
     font-size: 1.2rem !important;
     color: #ff0000 !important;
 }}
-
 .enhanced-textbox textarea {{
     background: linear-gradient(135deg, #1a1a1a 0%, #2a2a1a 100%) !important;
     border: 2px solid #444444 !important;
@@ -311,19 +256,16 @@ custom_css = f"""
     transition: all 0.3s ease !important;
     box-shadow: 0 5px 15px rgba(0, 0, 0, 0.3) !important;
 }}
-
 .enhanced-textbox textarea:focus {{
     border-color: #ff0000 !important;
     box-shadow: 0 0 25px rgba(255, 0, 0, 0.4), 0 5px 15px rgba(0, 0, 0, 0.3) !important;
     outline: none !important;
     transform: translateY(-2px) !important;
 }}
-
 .enhanced-textbox textarea::placeholder {{
     color: #888888 !important;
     font-style: italic !important;
 }}
-
 .enhanced-image-input, .enhanced-video-input {{
     background: rgba(42, 42, 42, 0.8) !important;
     border: 2px dashed #444444 !important;
@@ -336,12 +278,10 @@ custom_css = f"""
     align-items: center !important;
     justify-content: center !important;
 }}
-
 .enhanced-image-input:hover, .enhanced-video-input:hover {{
     border-color: #ff0000 !important;
     background: rgba(255, 0, 0, 0.05) !important;
 }}
-
 .enhanced-url-input input {{
     background: linear-gradient(135deg, #1a1a1a 0%, #2a2a1a 100%) !important;
     border: 2px solid #444444 !important;
@@ -352,19 +292,16 @@ custom_css = f"""
     transition: all 0.3s ease !important;
     box-shadow: 0 5px 15px rgba(0, 0, 0, 0.3) !important;
 }}
-
 .enhanced-url-input input:focus {{
     border-color: #ff0000 !important;
     box-shadow: 0 0 25px rgba(255, 0, 0, 0.4), 0 5px 15px rgba(0, 0, 0, 0.3) !important;
     outline: none !important;
     transform: translateY(-2px) !important;
 }}
-
 .enhanced-url-input input::placeholder {{
     color: #888888 !important;
     font-style: italic !important;
 }}
-
 .submit-button {{
     background: linear-gradient(135deg, #ff0000 0%, #cc0000 100%) !important;
     border: none !important;
@@ -380,34 +317,28 @@ custom_css = f"""
     width: 100% !important;
     margin-top: 1rem !important;
 }}
-
 .submit-button:hover {{
     background: linear-gradient(135deg, #cc0000 0%, #aa0000 100%) !important;
     transform: translateY(-3px) !important;
     box-shadow: 0 12px 30px rgba(255, 0, 0, 0.4) !important;
 }}
-
 .submit-button:active {{
     transform: translateY(-1px) !important;
 }}
-
 .accordion-container {{
     background: rgba(26, 26, 26, 0.8) !important;
     border: 1px solid #333333 !important;
     border-radius: 15px !important;
     margin-top: 2rem !important;
 }}
-
 .slider-container label {{
     color: #ffffff !important;
     font-weight: 600 !important;
     font-size: 1rem !important;
 }}
-
 .slider-container input[type="range"] {{
     accent-color: #ff0000 !important;
 }}
-
 .status-container textarea {{
     background: transparent !important;
     border: none !important;
@@ -415,24 +346,20 @@ custom_css = f"""
     font-weight: 600 !important;
     text-align: center !important;
 }}
-
 .footer {{
     display: none !important;
 }}
-
 /* Enhanced chat styling */
 .message.user {{
     background: linear-gradient(135deg, #2a2a2a 0%, #3a3a2a 100%) !important;
     border-left: 4px solid #ff0000 !important;
     margin-left: 2rem !important;
 }}
-
 .message.bot {{
     background: linear-gradient(135deg, #1a2a1a 0%, #2a3a2a 100%) !important;
     border-left: 4px solid #cc0000 !important;
     margin-right: 2rem !important;
 }}
-
 /* Responsive design */
 @media (max-width: 768px) {{
     .main-header h1 {{
@@ -452,7 +379,6 @@ custom_css = f"""
         font-size: 2rem !important;
     }}
 }}
-
 /* Animations */
 @keyframes pulse-glow {{
     0% {{ 
@@ -468,12 +394,10 @@ custom_css = f"""
         transform: scale(1);
     }}
 }}
-
 @keyframes float {{
     0%, 100% {{ transform: translateY(0px); }}
     50% {{ transform: translateY(-10px); }}
 }}
-
 .floating {{
     animation: float 3s ease-in-out infinite;
 }}
@@ -497,13 +421,13 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
     logo_html = f"""
     <div class="main-header">
         <div class="logo-container">
-            <img src="https://huggingface.co/spaces/Yordann/MasterBrand_ChatBot/resolve/main/logo.png" alt="MasterBrand Logo" class="logo-image floating style="height:100px;">
+            <img src="https://huggingface.co/spaces/Yordann/MasterBrand_ChatBot/resolve/main/logo.png" alt="MasterBrand Logo" class="logo-image floating" style="height:100px;">
             <div class="brand-text">MASTERBRAND</div>
         </div>
         <h1>AI ASSISTANT</h1>
-        <p>Your Personal E-commerce Business Expert - Available in English & Bulgarian</p>
+        <p>Your Personal AI Assistant - Powered by ChatGPT - Available in English & Bulgarian</p>
         <p style="font-size: 1rem; color: #ff0000; font-weight: 600; margin-top: 1rem;">
-            🚀 Powered by Advanced AI • 🌍 Multilingual Support • 💼 Expert Business Guidance
+            🚀 Powered by ChatGPT • 🌍 Multilingual Support • 💼 General AI Assistance
         </p>
     </div>
     """
@@ -526,7 +450,7 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
             with gr.Column(elem_classes=["input-section"]):
                 gr.HTML('<div class="input-label"><span class="input-icon">💬</span>Ask Your Question</div>')
                 inputs = gr.Textbox(
-                    placeholder="Ask me anything about your e-commerce business please... 💡",
+                    placeholder="Ask me anything... 💡",
                     label="",
                     lines=3,
                     elem_classes=["enhanced-textbox"],
@@ -538,7 +462,7 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
                         gr.HTML('<div class="input-label"><span class="input-icon">🖼️</span>Upload Image (Optional)</div>')
                         image_input = gr.Image(
                             label="", 
-                            type="pil", 
+                            type="pil",
                             elem_classes=["enhanced-image-input"],
                             show_label=False
                         )
@@ -560,7 +484,7 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
                 )
 
                 submit_btn = gr.Button(
-                    "🚀 Get Expert Advice",
+                    "🚀 Get AI Response",
                     variant="primary",
                     size="lg",
                     elem_classes=["submit-button"]
@@ -586,7 +510,7 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
             )
             temperature = gr.Slider(
                 0.1, 2.0, 
-                value=1.0, 
+                value=0.7, 
                 step=0.1, 
                 label="🌡️ Temperature", 
                 elem_classes=["slider-container"],
@@ -597,10 +521,10 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
     gr.HTML("""
     <div style="text-align: center; padding: 2rem; color: #666666; border-top: 1px solid #333333; margin-top: 3rem;">
         <p style="margin: 0; font-size: 0.9rem;">
-            © 2025 MasterBrand AI Assistant • Built with ❤️ for E-commerce Success
+            © 2025 MasterBrand AI Assistant • Powered by ChatGPT
         </p>
         <p style="margin: 0.5rem 0 0 0; font-size: 0.8rem; color: #888888;">
-            Empowering entrepreneurs worldwide with AI-driven business insights
+            Your intelligent AI companion for any task
         </p>
     </div>
     """
@@ -629,4 +553,3 @@ with gr.Blocks(theme=masterbrand_theme, css=custom_css, title="MasterBrand Assis
 # ==== Launch ====
 if __name__ == "__main__":
     demo.queue(max_size=10).launch(server_name="0.0.0.0", server_port=7860)
-