Create app.py

app.py

@@ -0,0 +1,54 @@
+import gradio as gr
+import os
+from learning_platform import LearningPlatform
+import asyncio
+import nest_asyncio
+nest_asyncio.apply()
+
+# Initialize the platform with environment variable
+platform = LearningPlatform(os.environ.get('OPENAI_API_KEY'))
+
+async def create_course(topic, difficulty):
+    try:
+        learning_path = await platform.create_course(topic, difficulty)
+        
+        # Format the output
+        output = f"Course: {learning_path.topic}\n"
+        output += f"Difficulty: {learning_path.difficulty_level}\n\n"
+        
+        for i, module in enumerate(learning_path.modules, 1):
+            output += f"Module {i}: {module.title}\n"
+            output += f"Content:\n{module.content}\n\n"
+            output += "Quiz Questions:\n"
+            for j, question in enumerate(module.quiz_questions, 1):
+                output += f"Q{j}: {question['question']}\n"
+                output += f"Options: {', '.join(question['options'])}\n"
+                output += f"Answer: {question['correct_answer']}\n\n"
+        
+        return output
+    except Exception as e:
+        return f"Error generating course: {str(e)}"
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=create_course,
+    inputs=[
+        gr.Textbox(label="Enter topic", placeholder="e.g., Python Programming"),
+        gr.Dropdown(
+            choices=["beginner", "intermediate", "advanced"], 
+            label="Select difficulty",
+            value="beginner"
+        )
+    ],
+    outputs="text",
+    title="AI Learning Platform",
+    description="Generate personalized learning paths for any topic",
+    examples=[
+        ["Python Programming", "beginner"],
+        ["Machine Learning", "intermediate"],
+        ["Web Development", "beginner"]
+    ]
+)
+
+if __name__ == "__main__":
+    demo.launch()