Update app.py

app.py

@@ -4,73 +4,83 @@ from huggingface_hub import InferenceClient
 # Initialize the Hugging Face Inference Client
 client = InferenceClient()
 
-# Function to generate the math lesson with LaTeX formatting
+# Function to stream content for Math, STEM, and Code Generation
 def generate_stream(selected_topic, input_text):
     """
-    Generates a dynamic math lesson with LaTeX-rendered equations and explanations.
+    Generates dynamic lessons, solutions, or code snippets based on the selected topic.
+
+    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.
     """
+    # Create a topic-specific prompt
     prompt = (
-        f"Create a detailed lesson on solving the following system of equations using the elimination method: {input_text}. "
-        "Include step-by-step explanations and render all equations in LaTeX format."
-        if input_text.strip()
-        else f"Create a beginner-level lesson for solving systems of equations with examples in LaTeX format."
+        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."
     )
     messages = [{"role": "user", "content": prompt}]
 
     try:
-        # Generate the content using Hugging Face
+        # Create a stream for generating content
         stream = client.chat.completions.create(
             model="Qwen/Qwen2.5-Coder-32B-Instruct",  # Streaming model
             messages=messages,
             temperature=0.5,
             max_tokens=1024,
             top_p=0.7,
-            stream=True,
+            stream=True
         )
 
         # Stream the generated content incrementally
         generated_content = ""
         for chunk in stream:
             generated_content += chunk.choices[0].delta.content
-            yield generated_content  # Incremental updates
-
+            yield generated_content  # Yield content incrementally
     except Exception as e:
-        yield f"Error: {e}"  # Handle exceptions gracefully
+        yield f"Error: {e}"  # Display error if any issues occur
 
-
-# Create the Gradio app interface
+# Create the Gradio interface
 with gr.Blocks() as app:
-    gr.Markdown("## 🎓 Solve Systems of Linear Equations with LaTeX")
+    # App Title and Instructions
+    gr.Markdown("## 🎓 STEM Learning and Code Generator")
     gr.Markdown(
-        "Generate dynamic lessons on solving systems of equations step-by-step. "
-        "The content includes explanations and LaTeX-rendered equations for better understanding!"
+        "Get dynamic lessons, problem-solving examples, or code snippets for Math, STEM, "
+        "or Computer Science. Select a topic and get started!"
     )
 
     with gr.Row():
         # Input Section
         with gr.Column():
             selected_topic = gr.Radio(
-                choices=["Math"],
+                choices=["Math", "STEM", "Computer Science (Code Generation)"],
                 label="Select a Topic",
-                value="Math"  # Only math is needed here
+                value="Math"  # Default selection
             )
             input_text = gr.Textbox(
                 lines=2,
-                label="Input Equations",
-                placeholder="Enter the system of equations (e.g., '4x + 3y = 56, 7x + 6y = 54')"
+                label="Optional Input",
+                placeholder="Provide additional context (e.g., 'Explain calculus basics' or 'Generate Python code for sorting')."
             )
-            generate_button = gr.Button("Generate Lesson")
+            generate_button = gr.Button("Generate Content")
 
         # Output Section
         with gr.Column():
             gr.Markdown("### Generated Content")
-            output_stream = gr.Markdown()  # Output content as Markdown for LaTeX rendering
+            output_stream = gr.TextArea(
+                label="Output",
+                placeholder="Generated content will appear here...",
+                interactive=False
+            )
 
-    # Link the generate button to the function
+    # 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