Update app.py

app.py

@@ -1,64 +1,166 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-
+#!/usr/bin/env python3
 """
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+Hockey Mind AI Chatbot - Fixed Gradio Interface for Hugging Face Spaces
 """
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
+import gradio as gr
+import asyncio
+import os
+from dotenv import load_dotenv
+from OpenAPI_DB import agentic_hockey_chat
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+# Load environment variables
+load_dotenv()
 
-        response += token
-        yield response
+# Global variable to track if resources are loaded
+resources_loaded = False
 
+async def chat_interface(user_role, user_team, user_prompt):
+    """Interface function for Gradio"""
+    global resources_loaded
+    
+    try:
+        # Load resources on first use to save memory
+        if not resources_loaded:
+            try:
+                from OpenAPI_DB import load_resources
+                load_resources()
+                resources_loaded = True
+            except ImportError as import_err:
+                return f"Import Error: {str(import_err)}. Please check if all required packages are installed.", "Unable to load ML models."
+        
+        # Call the main chat function
+        result = await agentic_hockey_chat(user_role, user_team, user_prompt)
+        
+        # Format response for Gradio
+        ai_response = result.get('ai_response', 'Sorry, no response generated.')
+        recommendations = result.get('recommended_content_details', [])
+        
+        # Format recommendations as HTML
+        rec_html = ""
+        if recommendations:
+            rec_html = "<h3>🏒 Recommended Videos:</h3><ul>"
+            for rec in recommendations[:5]:
+                title = rec.get('title', 'No title')
+                url = rec.get('url', '#')
+                similarity = rec.get('similarity', 0)
+                rec_html += f"<li><a href='{url}' target='_blank'>{title}</a> (Similarity: {similarity:.3f})</li>"
+            rec_html += "</ul>"
+        
+        return ai_response, rec_html
+        
+    except Exception as e:
+        import traceback
+        error_details = traceback.format_exc()
+        return f"Error: {str(e)}\n\nDetails:\n{error_details}", "No recommendations available due to error."
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+def sync_chat_interface(user_role, user_team, user_prompt):
+    """Synchronous wrapper for Gradio"""
+    return asyncio.run(chat_interface(user_role, user_team, user_prompt))
 
+# Gradio Interface
+with gr.Blocks(
+    title="🏒 Hockey Mind AI Chatbot",
+    theme=gr.themes.Soft(),
+    css="""
+    .gradio-container {max-width: 800px !important; margin: auto !important;}
+    .main-header {text-align: center; margin-bottom: 2rem;}
+    """
+) as demo:
+    
+    gr.HTML("""
+    <div class="main-header">
+        <h1>🏒 Hockey Mind AI Chatbot</h1>
+        <p>Get personalized hockey advice and video recommendations!</p>
+        <p><i>Optimized for field hockey coaching, training, and player development</i></p>
+    </div>
+    """)
+    
+    with gr.Row():
+        with gr.Column():
+            user_role = gr.Dropdown(
+                choices=["le Trainer", "le Coach", "Speler"],
+                label="Your Role 👤",
+                value="Coach"
+            )
+            
+            user_team = gr.Textbox(
+                label="Team/Level 🏒",
+                placeholder="e.g., U8C, Toronto Maple Leafs, Beginner",
+                value="U10"
+            )
+            
+            user_prompt = gr.Textbox(
+                label="Your Question ❓",
+                placeholder="Ask about drills, techniques, strategies, rules...",
+                lines=3
+            )
+            
+            submit_btn = gr.Button("Get Hockey Advice 🚀", variant="primary", size="lg")
+    
+    with gr.Row():
+        ai_response = gr.Textbox(
+            label="🤖 AI Response",
+            lines=8,
+            interactive=False
+        )
+    
+    with gr.Row():
+        recommendations = gr.HTML()
+    
+    # Examples section
+    gr.HTML("<br><h3>💡 Example Questions:</h3>")
+    
+    examples = gr.Examples(
+        examples=[
+            ["Coach", "U8C", "What are the best backhand shooting drills for young players?"],
+            ["Player", "Intermediate", "How can I improve my penalty corner technique?"],
+            ["le Coach", "U10", "Geef me oefeningen voor backhandschoten"],
+            ["Parent", "Beginner", "What equipment does my child need to start playing hockey?"],
+            ["Coach", "Advanced", "What are effective small-sided games for skill development?"],
+        ],
+        inputs=[user_role, user_team, user_prompt],
+        outputs=[ai_response, recommendations],
+        fn=sync_chat_interface,
+    )
+    
+    # Event handler
+    submit_btn.click(
+        fn=sync_chat_interface,
+        inputs=[user_role, user_team, user_prompt],
+        outputs=[ai_response, recommendations],
+        api_name="chat"
+    )
+    
+    user_prompt.submit(
+        fn=sync_chat_interface,
+        inputs=[user_role, user_team, user_prompt],
+        outputs=[ai_response, recommendations]
+    )
+    
+    # Footer
+    gr.HTML("""
+    <br>
+    <div style="text-align: center; color: #666; font-size: 0.9em;">
+        <p>🏒 Hockey Mind AI - Powered by OpenRouter & Sentence Transformers</p>
+        <p>Supports English & Dutch | Built for field hockey community</p>
+    </div>
+    """)
 
+# Launch configuration for Hugging Face Spaces
 if __name__ == "__main__":
-    demo.launch()
+    # Check if running on Hugging Face Spaces
+    if os.getenv("SPACE_ID"):
+        # Production mode on HF Spaces
+        demo.launch(
+            server_name="0.0.0.0",
+            server_port=7860,
+            share=False,
+            show_error=True,
+            quiet=False
+        )
+    else:
+        # Local development mode
+        demo.launch(
+            share=True,
+            show_error=True
+        )