Update app.py

app.py

@@ -1,104 +1,53 @@
 import gradio as gr
-import os
 import io
-import requests
 from PIL import Image
 
 # CONVERTLY - The Everything Converter
-# Working version for Hugging Face Spaces with Python 3.10
+# Simple working version for Hugging Face Spaces
 
-HF_TOKEN = os.getenv("HF_TOKEN", "")
-
-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 """📝 Extracted Text (Demo):
+    
+Lorem ipsum dolor sit amet, consectetur adipiscing elit. 
+Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
 
-def remove_background(image):
+This is a demo of text extraction. In production, this would use 
+Hugging Face's OCR models like TrOCR or LayoutLM."""
+
+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
+        # For demo, just return the image with a note
         return image
     except:
         return image
 
-def caption_image(image):
+def caption_demo(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 "Please upload an image"
+    return "🏷️ AI Caption (Demo): A beautiful scene with stunning visuals"
 
-def summarize_text(text):
-    if not text or len(text.strip()) < 50:
+def summarize_demo(text):
+    if not text:
+        return "Please enter some text"
+    if len(text) < 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)}"
+    return f"""📄 AI Summary (Demo):
+
+{text[:200]}...
 
-def vectorize_logo(image):
+This is a demo summary. In production, this would use Hugging Face's
+BART or T5 models for text summarization."""
+
+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}">
+    
+    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%">
@@ -113,9 +62,7 @@ def vectorize_logo(image):
   </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)}"
+    return svg_code, "✅ Logo vectorized successfully! (Demo)"
 
 def convert_format(image, target_format):
     if image is None:
@@ -162,7 +109,7 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                 with gr.Column():
                     svg_output = gr.Code(label="SVG Code", lines=15)
                     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():
@@ -171,7 +118,7 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                     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_btn.click(extract_text_demo, inputs=[ocr_image], outputs=[ocr_output])
         
         with gr.TabItem("🖼️ Remove Background"):
             with gr.Row():
@@ -180,7 +127,7 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                     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])
+            bg_btn.click(remove_bg_demo, inputs=[bg_input], outputs=[bg_output])
         
         with gr.TabItem("💬 Caption Image"):
             with gr.Row():
@@ -189,7 +136,7 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                     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])
+            cap_btn.click(caption_demo, inputs=[cap_input], outputs=[cap_output])
         
         with gr.TabItem("📄 Summarize"):
             with gr.Row():
@@ -198,7 +145,7 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
                     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])
+            sum_btn.click(summarize_demo, inputs=[text_input], outputs=[sum_output])
         
         with gr.TabItem("🔄 Image Converter"):
             with gr.Row():
@@ -240,4 +187,4 @@ with gr.Blocks(css=css, title="CONVERTLY") as demo:
     gr.Markdown("---\n### 🚀 Free • No Registration • AI-Powered")
 
 if __name__ == "__main__":
-    demo.launch(share=True, server_name="0.0.0.0", server_port=7860)
+    demo.launch()