Update app.py

app.py

@@ -4,23 +4,23 @@ from huggingface_hub import InferenceClient
 # Initialize the Hugging Face Inference Client
 client = InferenceClient()
 
-# Function to stream content for Math, STEM, and Code Generation
+# Function to stream content with Math, STEM, or Code Generation, including LaTeX
 def generate_stream(selected_topic, input_text):
     """
-    Generates dynamic lessons, solutions, or code snippets based on the selected topic.
-
+    Generates dynamic lessons, solutions, or code snippets with LaTeX-style formatting.
+    
     Args:
         selected_topic (str): The selected subject (e.g., Math, STEM, or Code Generation).
         input_text (str): Additional input for contextual content generation.
 
     Yields:
-        str: Incremental output content.
+        str: Incremental content, including Markdown/LaTeX math formatting.
     """
     # Create a topic-specific prompt
     prompt = (
-        f"Generate a {selected_topic.lower()} lesson, problem, or example based on the following input: {input_text}"
-        if input_text.strip() else
-        f"Generate a beginner-level {selected_topic.lower()} lesson with examples."
+        f"Generate a {selected_topic.lower()} lesson, problem, or example with step-by-step explanations and LaTeX math formatting based on the following input: {input_text}"
+        if input_text.strip()
+        else f"Generate a beginner-level {selected_topic.lower()} lesson with examples and LaTeX math formatting."
     )
     messages = [{"role": "user", "content": prompt}]
 
@@ -32,7 +32,7 @@ def generate_stream(selected_topic, input_text):
             temperature=0.5,
             max_tokens=1024,
             top_p=0.7,
-            stream=True
+            stream=True,
         )
 
         # Stream the generated content incrementally
@@ -40,16 +40,18 @@ def generate_stream(selected_topic, input_text):
         for chunk in stream:
             generated_content += chunk.choices[0].delta.content
             yield generated_content  # Yield content incrementally
+
     except Exception as e:
         yield f"Error: {e}"  # Display error if any issues occur
 
+
 # Create the Gradio interface
 with gr.Blocks() as app:
     # App Title and Instructions
-    gr.Markdown("## 🎓 STEM Learning and Code Generator")
+    gr.Markdown("## 🎓 STEM Learning and Code Generator with LaTeX")
     gr.Markdown(
         "Get dynamic lessons, problem-solving examples, or code snippets for Math, STEM, "
-        "or Computer Science. Select a topic and get started!"
+        "or Computer Science. Includes LaTeX support for equations and step-by-step breakdowns!"
     )
 
     with gr.Row():
@@ -58,29 +60,28 @@ with gr.Blocks() as app:
             selected_topic = gr.Radio(
                 choices=["Math", "STEM", "Computer Science (Code Generation)"],
                 label="Select a Topic",
-                value="Math"  # Default selection
+                value="Math",  # Default selection
             )
             input_text = gr.Textbox(
                 lines=2,
                 label="Optional Input",
-                placeholder="Provide additional context (e.g., 'Explain calculus basics' or 'Generate Python code for sorting')."
+                placeholder="Provide additional context (e.g., 'Explain calculus basics' or 'Generate Python code for sorting').",
             )
             generate_button = gr.Button("Generate Content")
 
         # Output Section
         with gr.Column():
             gr.Markdown("### Generated Content")
-            output_stream = gr.Textbox(
-                lines=15,
-                label="Output",
-                interactive=False
+            output_stream = gr.Markdown(
+                placeholder="Generated content will appear here, with support for LaTeX math equations...",
+                interactive=False,
             )
 
     # Link the generate button to the streaming function
     generate_button.click(
         fn=generate_stream,
         inputs=[selected_topic, input_text],
-        outputs=output_stream
+        outputs=output_stream,
     )
 
 # Launch the Gradio app