Update app.py

app.py

@@ -1,49 +1,256 @@
-import json
-import os
-import logging
-from datetime import datetime
+import gradio as gr
+from transformers import pipeline
+import numpy as np
+from PIL import Image
+import io
+import base64
 
-# Configure logging
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] %(message)s",
-    handlers=[
-        logging.FileHandler("/home/pi5/horrorvidmaker/test_write_json.log"),
-        logging.StreamHandler()
-    ]
-)
-logger = logging.getLogger(__name__)
+# Initialize sentiment analysis pipeline (lightweight for CPU)
+sentiment_analyzer = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
 
-# Path to horror.json
-JSON_PATH = "/var/www/html/horror.json"
+# Mock text-to-image function (CPU-friendly)
+def generate_mock_image(text_prompt, width=200, height=200):
+    img_array = np.zeros((height, width, 3), dtype=np.uint8)
+    for i in range(height):
+        for j in range(width):
+            img_array[i, j] = [(i % 255), (j % 255), ((i + j) % 255)]  # RGB gradient
+    img = Image.fromarray(img_array)
+    buffered = io.BytesIO()
+    img.save(buffered, format="PNG")
+    img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+    return f"data:image/png;base64,{img_str}"
 
-def write_test_json():
-    try:
-        # Test data to write
-        test_entry = [
-            {
-                "video_web_url": "test_horror_video.mp4",
-                "web_url": "test_horror_thumbnail.png",
-                "title": "TEST VIDEO ENTRY",
-                "theme": "horror",
-                "timestamp": datetime.now().isoformat()
-            }
-        ]
+# Sentiment analysis function
+def analyze_sentiment(text):
+    if not text.strip():
+        return "Please enter some text."
+    result = sentiment_analyzer(text)[0]
+    label = result['label']
+    score = result['score']
+    return f"Sentiment: {label} (Confidence: {score:.2%})"
 
-        # Write to horror.json
-        logger.info(f"Attempting to write to {JSON_PATH}")
-        with open(JSON_PATH, "w") as f:
-            json.dump(test_entry, f, indent=4)
-        logger.info(f"✅ Successfully wrote test entry to {JSON_PATH}")
+# Chatbot feedback function
+def chatbot_response(user_feedback, chat_history):
+    if not user_feedback.strip():
+        return chat_history, "Please provide feedback."
+    chat_history.append((
+        f"**You**: {user_feedback}", 
+        f"**Bot**: Thanks for your feedback! I understood: '{user_feedback}'."
+    ))
+    return chat_history, ""
 
-        # Verify the write by reading back
-        with open(JSON_PATH, "r") as f:
-            data = json.load(f)
-        logger.info(f"Read back JSON data: {json.dumps(data, indent=2)}")
+# Custom CSS for a dark grey, minimalist UI
+custom_css = """
+body, .gradio-container {
+    background: #2d2d2d !important;
+    color: #d4d4d4 !important;
+    font-family: 'Inter', -apple-system, sans-serif;
+    margin: 0;
+    padding: 20px;
+}
+.tab-nav button {
+    background: #3a3a3a !important;
+    color: #a3a3a3 !important;
+    border: none !important;
+    padding: 12px 20px !important;
+    border-radius: 8px 8px 0 0 !important;
+    transition: background 0.3s, color 0.3s;
+}
+.tab-nav button:hover, .tab-nav button[aria-selected="true"] {
+    background: #4a4a4a !important;
+    color: #e0e0e0 !important;
+}
+.block, .gr-panel {
+    background: #353535 !important;
+    border-radius: 10px !important;
+    padding: 20px !important;
+    box-shadow: 0 4px 10px rgba(0, 0, 0, 0.25);
+    margin-bottom: 20px;
+}
+input, textarea, .gr-textbox {
+    background: #2a2a2a !important;
+    color: #d4d4d4 !important;
+    border: 1px solid #4a4a4a !important;
+    border-radius: 8px !important;
+    padding: 12px !important;
+    transition: border-color 0.2s;
+}
+input:focus, textarea:focus {
+    border-color: #6b6b6b !important;
+    outline: none;
+}
+button {
+    background: #4a4a4a !important;
+    color: #e0e0e0 !important;
+    border: none !important;
+    border-radius: 8px !important;
+    padding: 12px 24px !important;
+    font-weight: 600;
+    transition: background 0.2s, transform 0.2s;
+}
+button:hover {
+    background: #5a5a5a !important;
+    transform: scale(1.03);
+}
+.gr-image img {
+    border-radius: 8px !important;
+    border: 2px solid #4a4a4a !important;
+    max-width: 100%;
+}
+.gr-chatbot .message {
+    border-radius: 8px !important;
+    padding: 12px !important;
+    margin: 8px 0 !important;
+}
+.gr-chatbot .message:nth-child(odd) {
+    background: #3a3a3a !important; /* User messages */
+}
+.gr-chatbot .message:nth-child(even) {
+    background: #2a2a2a !important; /* Bot messages */
+}
+h1, h2, h3 {
+    color: #b3b3b3 !important;
+    font-weight: 600;
+}
+.loading {
+    display: flex;
+    justify-content: center;
+    align-items: center;
+    height: 100px;
+}
+.loading::after {
+    content: '';
+    width: 24px;
+    height: 24px;
+    border: 4px solid #6b6b6b;
+    border-top: 4px solid transparent;
+    border-radius: 50%;
+    animation: spin 1s linear infinite;
+}
+@keyframes spin {
+    0% { transform: rotate(0deg); }
+    100% { transform: rotate(360deg); }
+}
+@media (max-width: 768px) {
+    .gradio-container {
+        padding: 10px;
+    }
+    .block {
+        padding: 15px !important;
+    }
+    button {
+        padding: 10px 20px !important;
+    }
+    .tab-nav button {
+        padding: 10px 15px !important;
+        font-size: 14px;
+    }
+}
+"""
 
-    except Exception as e:
-        logger.error(f"❌ Failed to write to {JSON_PATH}: {str(e)}")
-        raise
+# Main Gradio app with Tabs
+with gr.Blocks(css=custom_css) as demo:
+    gr.Markdown(
+        """
+        # 🛠️ Interactive AI Dashboard
+        Explore **Sentiment Analysis**, **Text-to-Image Generation**, and **Feedback Chatbot** in a sleek grey interface.
+        Built for Hugging Face Spaces (free tier, CPU-only).
+        """
+    )
+    
+    with gr.Tabs():
+        # Sentiment Analysis Tab
+        with gr.Tab("Sentiment Analysis"):
+            with gr.Row():
+                with gr.Column(scale=3):
+                    gr.Markdown("### 📝 Analyze Text Sentiment")
+                    sentiment_input = gr.Textbox(
+                        label="Your Text",
+                        placeholder="Enter text like 'This app is awesome!'",
+                        lines=4,
+                        show_label=False
+                    )
+                    sentiment_button = gr.Button("Analyze", variant="primary")
+                    sentiment_output = gr.Textbox(
+                        label="Result",
+                        interactive=False,
+                        placeholder="Sentiment result will appear here..."
+                    )
+                with gr.Column(scale=2):
+                    gr.Markdown("### Example Prompts")
+                    gr.Examples(
+                        examples=[
+                            "I’m thrilled about this project!",
+                            "Today feels a bit gloomy.",
+                            "Programming is tough but rewarding!"
+                        ],
+                        inputs=sentiment_input
+                    )
+            sentiment_button.click(
+                fn=analyze_sentiment,
+                inputs=sentiment_input,
+                outputs=sentiment_output,
+                _js="() => { document.querySelector('.loading').style.display = 'block'; setTimeout(() => document.querySelector('.loading').style.display = 'none', 1000); }"
+            )
+        
+        # Text-to-Image Tab
+        with gr.Tab("Text-to-Image"):
+            with gr.Row():
+                with gr.Column(scale=3):
+                    gr.Markdown("### 🖼️ Generate Mock Images")
+                    image_prompt = gr.Textbox(
+                        label="Image Prompt",
+                        placeholder="Describe an image, e.g., 'Abstract colorful pattern'",
+                        lines=3,
+                        show_label=False
+                    )
+                    image_button = gr.Button("Generate", variant="primary")
+                    image_output = gr.Image(
+                        label="Generated Image",
+                        type="pil",
+                        interactive=False
+                    )
+                with gr.Column(scale=2):
+                    gr.Markdown("### Info")
+                    gr.Markdown(
+                        "This mock generator creates gradient images to stay lightweight for the free tier."
+                    )
+            image_button.click(
+                fn=generate_mock_image,
+                inputs=image_prompt,
+                outputs=image_output,
+                _js="() => { document.querySelector('.loading').style.display = 'block'; setTimeout(() => document.querySelector('.loading').style.display = 'none', 1000); }"
+            )
+        
+        # Chatbot Tab
+        with gr.Tab("Feedback Chatbot"):
+            with gr.Row():
+                with gr.Column():
+                    gr.Markdown("### 💬 Share Your Thoughts")
+                    chatbot = gr.Chatbot(
+                        label="Conversation",
+                        bubble_full_width=False,
+                        height=400
+                    )
+                    feedback_input = gr.Textbox(
+                        label="Your Message",
+                        placeholder="Type your feedback here...",
+                        lines=2,
+                        show_label=False
+                    )
+                    feedback_button = gr.Button("Send", variant="primary")
+                    feedback_output = gr.Textbox(
+                        label="Status",
+                        interactive=False,
+                        placeholder="Bot response status..."
+                    )
+            feedback_button.click(
+                fn=chatbot_response,
+                inputs=[feedback_input, chatbot],
+                outputs=[chatbot, feedback_output],
+                _js="() => { document.querySelector('.loading').style.display = 'block'; setTimeout(() => document.querySelector('.loading').style.display = 'none', 500); }"
+            )
 
+# Launch the app
 if __name__ == "__main__":
-    write_test_json()
+    demo.launch()