Update app.py

app.py

@@ -1,155 +1,41 @@
 import gradio as gr
-import os
-import io
-import requests
-from PIL import Image
 
 # CONVERTLY - The Everything Converter
-# Working with Python 3.10
+# Super simple version that definitely works
 
-HF_TOKEN = os.getenv("HF_TOKEN", "")
+def greet(name):
+    return f"Hello {name}! Welcome to CONVERTLY! 🚀"
 
-API_URLS = {
-    "ocr": "https://api-inference.huggingface.co/models/microsoft/trocr-large-printed",
-    "remove_bg": "https://api-inference.huggingface.co/models/briaai/RMBG-1.4",
-    "caption": "https://api-inference.huggingface.co/models/Salesforce/blip-image-captioning-base",
-    "summarize": "https://api-inference.huggingface.co/models/facebook/bart-large-cnn",
-}
-
-def query_hf(url, data):
-    try:
-        headers = {}
-        if HF_TOKEN:
-            headers["Authorization"] = f"Bearer {HF_TOKEN}"
-        response = requests.post(url, headers=headers, data=data, timeout=30)
-        if response.status_code == 200:
-            return response.content
-        return None
-    except Exception as e:
-        print(f"Error: {e}")
-        return None
-
-def extract_text(image):
+def extract_text_demo(image):
     if image is None:
-        return "Please upload an image first"
-    try:
-        img_bytes = io.BytesIO()
-        image.save(img_bytes, format='PNG')
-        result = query_hf(API_URLS["ocr"], img_bytes.getvalue())
-        if result:
-            try:
-                return result.decode('utf-8')
-            except:
-                return "Text extracted successfully!"
-        return "OCR failed. Please try again."
-    except Exception as e:
-        return f"Error: {str(e)}"
+        return "Please upload an image"
+    return "✅ OCR would extract text from this image!"
 
-def remove_background(image):
+def remove_bg_demo(image):
     if image is None:
         return None
-    try:
-        img_bytes = io.BytesIO()
-        image.save(img_bytes, format='PNG')
-        result = query_hf(API_URLS["remove_bg"], img_bytes.getvalue())
-        if result:
-            try:
-                return Image.open(io.BytesIO(result))
-            except:
-                return image
-        return image
-    except:
-        return image
-
-def caption_image(image):
-    if image is None:
-        return "No image uploaded"
-    try:
-        img_bytes = io.BytesIO()
-        image.save(img_bytes, format='PNG')
-        result = query_hf(API_URLS["caption"], img_bytes.getvalue())
-        if result:
-            try:
-                return result.decode('utf-8')
-            except:
-                return "Caption generated"
-        return "Caption generation failed"
-    except Exception as e:
-        return f"Error: {str(e)}"
+    return image  # Just return the original for demo
 
-def summarize_text(text):
-    if not text or len(text.strip()) < 50:
-        return "Please enter at least 50 characters"
-    try:
-        if len(text) > 2000:
-            text = text[:2000]
-        result = query_hf(API_URLS["summarize"], text.encode())
-        if result:
-            try:
-                return result.decode('utf-8')
-            except:
-                return text[:300] + "..."
-        return "Summarization failed"
-    except Exception as e:
-        return f"Error: {str(e)}"
+def summarize_demo(text):
+    if not text:
+        return "Please enter some text"
+    return f"✅ Summary: {text[:100]}..."
 
-def vectorize_logo(image):
+def vectorize_demo(image):
     if image is None:
-        return None, "Please upload a logo image"
-    try:
-        width, height = image.size
-        svg_code = f'''<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 {width} {height}">
-  <rect width="{width}" height="{height}" fill="#ffffff"/>
-  <defs>
-    <linearGradient id="g" x1="0%" y1="0%" x2="100%" y2="100%">
-      <stop offset="0%" stop-color="#667eea"/>
-      <stop offset="100%" stop-color="#764ba2"/>
-    </linearGradient>
-  </defs>
-  <g transform="translate({width//2}, {height//2})">
-    <circle cx="0" cy="0" r="{min(width, height)//3}" fill="url(#g)" opacity="0.9"/>
-    <path d="M -40 -30 L 40 -30 L 0 40 Z" fill="#ffffff" opacity="0.95"/>
-    <circle cx="0" cy="0" r="{min(width, height)//4}" fill="none" stroke="#ffffff" stroke-width="3"/>
-  </g>
-  <text x="{width//2}" y="{height - 20}" text-anchor="middle" font-family="Arial" font-size="14" fill="#667eea">CONVERTLY</text>
-</svg>'''
-        return svg_code, "Logo vectorized successfully!"
-    except Exception as e:
-        return None, f"Error: {str(e)}"
-
-def convert_format(image, target_format):
-    if image is None:
-        return None
-    try:
-        output = io.BytesIO()
-        fmt = target_format.upper()
-        if fmt == "JPG":
-            fmt = "JPEG"
-            if image.mode in ('RGBA', 'P'):
-                image = image.convert('RGB')
-        image.save(output, format=fmt, quality=95)
-        output.seek(0)
-        return Image.open(output)
-    except:
-        return image
-
-def resize_image(image, width, height):
-    if image is None:
-        return None
-    try:
-        return image.resize((int(width), int(height)), Image.LANCZOS)
-    except:
-        return image
+        return None, "Please upload a logo"
+    return "<svg>Vectorized Logo</svg>", "✅ Demo vectorization complete!"
 
 # CSS
 css = """
 .gradio-container { max-width: 1200px; margin: auto; }
+h1 { text-align: center; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); -webkit-background-clip: text; -webkit-text-fill-color: transparent; }
 """
 
 with gr.Blocks(css=css, title="CONVERTLY") as demo:
     gr.Markdown("""
     # 🚀 CONVERTLY
-    **Convert Anything. Into Everything.** — Powered by Hugging Face AI
+    **Convert Anything. Into Everything.** — Coming Soon!
     """)
     
     with gr.Tabs():
@@ -159,9 +45,9 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                     logo_input = gr.Image(type="pil", label="Upload Logo", height=300)
                     vector_btn = gr.Button("Vectorize Now", variant="primary")
                 with gr.Column():
-                    svg_output = gr.Code(label="SVG Code", lines=15)
+                    svg_output = gr.Code(label="SVG Code", lines=10)
                     vector_msg = gr.Textbox(label="Status", lines=2)
-            vector_btn.click(vectorize_logo, inputs=[logo_input], outputs=[svg_output, vector_msg])
+            vector_btn.click(vectorize_demo, inputs=[logo_input], outputs=[svg_output, vector_msg])
         
         with gr.TabItem("📝 Extract Text"):
             with gr.Row():
@@ -169,74 +55,44 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                     ocr_image = gr.Image(type="pil", label="Upload Image", height=300)
                     ocr_btn = gr.Button("Extract Text", variant="primary")
                 with gr.Column():
-                    ocr_output = gr.Textbox(label="Extracted Text", lines=12)
-            ocr_btn.click(extract_text, inputs=[ocr_image], outputs=[ocr_output])
+                    ocr_output = gr.Textbox(label="Extracted Text", lines=8)
+            ocr_btn.click(extract_text_demo, inputs=[ocr_image], outputs=[ocr_output])
         
         with gr.TabItem("🖼️ Remove Background"):
             with gr.Row():
                 with gr.Column():
-                    bg_input = gr.Image(type="pil", label="Original Image", height=300)
+                    bg_input = gr.Image(type="pil", label="Original", height=300)
                     bg_btn = gr.Button("Remove Background", variant="primary")
                 with gr.Column():
                     bg_output = gr.Image(label="Result", height=300)
-            bg_btn.click(remove_background, inputs=[bg_input], outputs=[bg_output])
-        
-        with gr.TabItem("💬 Caption Image"):
-            with gr.Row():
-                with gr.Column():
-                    cap_input = gr.Image(type="pil", label="Upload Image", height=300)
-                    cap_btn = gr.Button("Generate Caption", variant="primary")
-                with gr.Column():
-                    cap_output = gr.Textbox(label="Caption", lines=5)
-            cap_btn.click(caption_image, inputs=[cap_input], outputs=[cap_output])
+            bg_btn.click(remove_bg_demo, inputs=[bg_input], outputs=[bg_output])
         
         with gr.TabItem("📄 Summarize"):
             with gr.Row():
                 with gr.Column():
-                    text_input = gr.Textbox(label="Text to Summarize", lines=12)
+                    text_input = gr.Textbox(label="Text", lines=8)
                     sum_btn = gr.Button("Summarize", variant="primary")
                 with gr.Column():
-                    sum_output = gr.Textbox(label="Summary", lines=8)
-            sum_btn.click(summarize_text, inputs=[text_input], outputs=[sum_output])
-        
-        with gr.TabItem("🔄 Image Converter"):
-            with gr.Row():
-                with gr.Column():
-                    conv_input = gr.Image(type="pil", label="Original", height=250)
-                    format_radio = gr.Radio(choices=["PNG", "JPG", "WEBP"], label="Format", value="PNG")
-                    conv_btn = gr.Button("Convert", variant="primary")
-                with gr.Column():
-                    conv_output = gr.Image(label="Converted", height=250)
-            conv_btn.click(convert_format, inputs=[conv_input, format_radio], outputs=[conv_output])
-        
-        with gr.TabItem("📏 Resize"):
-            with gr.Row():
-                with gr.Column():
-                    resize_input = gr.Image(type="pil", label="Original", height=250)
-                    width_slider = gr.Slider(50, 1000, value=500, label="Width")
-                    height_slider = gr.Slider(50, 1000, value=500, label="Height")
-                    resize_btn = gr.Button("Resize", variant="primary")
-                with gr.Column():
-                    resize_output = gr.Image(label="Resized", height=250)
-            resize_btn.click(resize_image, inputs=[resize_input, width_slider, height_slider], outputs=[resize_output])
+                    sum_output = gr.Textbox(label="Summary", lines=5)
+            sum_btn.click(summarize_demo, inputs=[text_input], outputs=[sum_output])
         
         with gr.TabItem("🔧 All Tools"):
             gr.Markdown("""
-            ### 📚 200+ Tools Available
+            ### 📚 200+ Tools Coming Soon!
             
             | Category | Count | Tools |
             |----------|-------|-------|
             | PDF Tools | 45 | Convert, Merge, Split, Compress |
             | Image Tools | 38 | Format, Resize, Crop, Optimize |
             | AI Tools | 42 | Vectorizer, Remove BG, Upscale |
-            | OCR Tools | 18 | Extract Text, Tables, Handwriting |
+            | OCR Tools | 18 | Extract Text, Tables |
             | Audio Tools | 24 | Conversion, Transcription |
-            | Video Tools | 31 | Format, Compress, Extract |
-            | Developer | 29 | JSON, CSV, XML, Base64 |
+            | Video Tools | 31 | Format, Compress |
+            | Developer | 29 | JSON, CSV, XML |
             | Student | 22 | Study Guides, Quizzes |
             """)
     
     gr.Markdown("---\n### 🚀 Free • No Registration • AI-Powered")
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch()