Update app.py

app.py

@@ -1,94 +1,98 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import os
 
-# Use Qwen 2.5 Coder 32B (Excellent for code & JSON)
-# We will access it via the Chat API to avoid "Task not supported" errors.
-REPO_ID = "Qwen/Qwen2.5-Coder-32B-Instruct"
-client = InferenceClient()
+# 1. SETUP: Get the token from the Space secrets
+# This fixes the "Auth" error by using your private key
+hf_token = os.getenv("HF_TOKEN")
+
+# Initialize the client with your token
+# We use Qwen 2.5 Coder 32B. It is the best open model for this task.
+model_id = "Qwen/Qwen2.5-Coder-32B-Instruct"
+client = InferenceClient(api_key=hf_token)
 
 def generate_seo(code_snippet, file_type):
     """
-    Analyzes code and generates SEO metadata + JSON-LD using Chat API.
+    Generates SEO and JSON-LD using the Authenticated Client.
     """
     if not code_snippet.strip():
-        return "Please paste some code first."
+        return "⚠️ Error: Please paste some code first."
 
-    # 1. Define the System Prompt (The instructions)
+    # SEO Prompt
     system_instruction = f"""
-    You are an expert SEO specialist and Software Engineer. 
-    Analyze the user's {file_type} code.
-    
-    Output Format requirements:
-    1. Title: A clickable, SEO-optimized title tag (max 60 chars).
-    2. Meta Description: A summary for search engines (max 160 chars).
-    3. Keywords: 5-8 comma-separated high-value keywords.
-    4. JSON-LD: A valid <script type="application/ld+json"> block. 
-       - If Python: use Schema.org 'SoftwareSourceCode'.
-       - If HTML: use Schema.org 'WebPage' or 'TechArticle'.
+    You are an expert Technical SEO Specialist. Analyze the user's {file_type} code.
     
-    Strictly follow this output format (Markdown):
+    Your Goal: Generate Google-compliant JSON-LD structured data and SEO meta tags.
     
+    Output Format (Strict Markdown):
     ## SEO Metadata
-    **Title:** [Title Here]
-    **Description:** [Description Here]
-    **Keywords:** [Keywords Here]
+    **Title:** [Engaging Title, max 60 chars]
+    **Description:** [Summary including keywords, max 160 chars]
+    **Keywords:** [5-8 comma-separated keywords]
     
     ## JSON-LD Structured Data
     ```json
-    [Insert strictly valid JSON code here, no comments]
+    [Insert VALID JSON-LD here. 
+     - If Python: Use schema.org/SoftwareSourceCode
+     - If HTML: Use schema.org/WebPage or schema.org/TechArticle]
     ```
     """
 
-    # 2. Define the User Message (The Code)
-    user_message = f"Here is the {file_type} code:\n\n{code_snippet}"
+    user_message = f"Analyze this {file_type} code:\n\n{code_snippet}"
 
     try:
-        # 3. Use chat_completion (matches 'conversational' task)
+        # Chat Completion API (Reliable with Token)
         response = client.chat_completion(
-            model=REPO_ID,
+            model=model_id,
             messages=[
                 {"role": "system", "content": system_instruction},
                 {"role": "user", "content": user_message}
             ],
-            max_tokens=1024,
-            temperature=0.3
+            max_tokens=1500,
+            temperature=0.2  # Low temp for precise JSON
         )
-        
-        # Extract the actual message content
         return response.choices[0].message.content
 
     except Exception as e:
-        # Fallback error handling
-        return f"Error: {str(e)}\n\nTry switching the model in the code to 'meta-llama/Meta-Llama-3-8B-Instruct' if this persists."
+        # detailed error logging for the UI
+        error_msg = str(e)
+        if "401" in error_msg:
+            return "🔒 Authentication Error: Please check that you added 'HF_TOKEN' to your Space Secrets."
+        elif "429" in error_msg:
+            return "⏳ Rate Limit: The free model is busy. Please wait 1 minute and try again."
+        elif "504" in error_msg:
+            return "⏱️ Timeout: The code snippet might be too long. Try a shorter piece of code."
+        else:
+            return f"❌ System Error: {error_msg}"
 
-# Design the UI
+# UI Layout
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown(
         """
-        # 🚀 AI Code-to-SEO Generator
-        Paste your **Python** or **HTML** code below to generate optimized meta tags and JSON-LD Schema.
+        # ⚡ SEO & JSON-LD Generator (Authenticated)
+        **Status:** ✅ Connected to Qwen 2.5 Coder
         """
     )
     
     with gr.Row():
-        with gr.Column():
-            input_type = gr.Radio(["python", "html"], label="File Type", value="python")
-            code_input = gr.Code(language="python", label="Paste Code Here", lines=10)
-            submit_btn = gr.Button("Generate SEO & JSON-LD", variant="primary")
+        with gr.Column(scale=1):
+            input_type = gr.Radio(["python", "html"], label="Select File Type", value="python")
+            code_input = gr.Code(language="python", label="Paste Code Here", lines=15)
+            submit_btn = gr.Button("✨ Generate SEO Data", variant="primary", size="lg")
         
-        with gr.Column():
-            output_markdown = gr.Markdown(label="Generated SEO Strategy")
+        with gr.Column(scale=1):
+            # This component displays the result
+            output_markdown = gr.Markdown(label="Results will appear here...")
 
-    # Update syntax highlighting dynamically
+    # Dynamic syntax highlighting
     input_type.change(lambda x: gr.Code(language=x), inputs=input_type, outputs=code_input)
     
-    # Run logic
+    # Button Click Action
     submit_btn.click(
         fn=generate_seo,
         inputs=[code_input, input_type],
         outputs=output_markdown
     )
 
-# Launch
 if __name__ == "__main__":
     demo.launch()