Update app.py

app.py

@@ -5,11 +5,9 @@ import os  # For environment variables
 # Initialize the Hugging Face Inference Client
 client = InferenceClient()
 
-# Generic function to generate AI response with streaming
+# Generator function for streaming AI response
 def generate_response(prompt_template, **kwargs):
-    # Format the prompt with provided arguments
     prompt = os.getenv(prompt_template).format(**kwargs)
-    # Stream the response from the model
     stream = client.chat.completions.create(
         model="Qwen/QwQ-32B-Preview",
         messages=[{"role": "user", "content": prompt}],
@@ -18,22 +16,23 @@ def generate_response(prompt_template, **kwargs):
         top_p=0.8,
         stream=True
     )
-    # Stream chunks as they are generated
     response = ""
     for chunk in stream:
         response += chunk.choices[0].delta.content
-        yield response
+        yield response  # Yield incrementally
+
+# Wrapper function for Gradio compatibility
+def stream_response(prompt_template, **kwargs):
+    return "".join(generate_response(prompt_template, **kwargs))
 
 # Gradio app interface
 with gr.Blocks() as app:
     gr.Markdown("## Mathematical Insight Tutor")
     gr.Markdown("An advanced AI-powered tutor to help you master math concepts.")
 
-    # Function to create a reusable tab with inputs and outputs
     def create_tab(tab_name, prompt_template, inputs):
         with gr.Tab(tab_name):
             input_fields = []
-            # Create input components dynamically
             for inp in inputs:
                 if inp["type"] == "textbox":
                     input_fields.append(
@@ -49,16 +48,15 @@ with gr.Blocks() as app:
                     )
             # Button and output
             button = gr.Button(f"{tab_name} Execute")
-            output = gr.Markdown()
-            # Link button to the response generator
+            output = gr.Textbox(lines=10, label="Output", placeholder="Generated response will appear here.")
+            # Link button to the response wrapper
             button.click(
-                fn=lambda *args: generate_response(prompt_template, **dict(zip([inp["key"] for inp in inputs], args))),
+                fn=lambda *args: stream_response(prompt_template, **dict(zip([inp["key"] for inp in inputs], args))),
                 inputs=input_fields,
-                outputs=output,
-                stream=True  # Enable streaming for Gradio
+                outputs=output
             )
 
-    # Tabs for various functionalities
+    # Tabs for functionalities
     create_tab(
         "Solve a Problem",
         "PROMPT_SOLVE",