Update app.py

app.py

@@ -1,89 +1,111 @@
 import gradio as gr
 from groq import Groq
 import os
+import json
+import logging
+from typing import Dict, Any, Tuple
+
+# Set up logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
 # Initialize Groq client
-client = Groq(api_key=os.environ["GROQ_API_KEY"])
+try:
+    client = Groq(api_key=os.environ["GROQ_API_KEY"])
+except KeyError:
+    logging.error("GROQ_API_KEY not found in environment variables")
+    raise EnvironmentError("Please set the GROQ_API_KEY environment variable")
 
-def generate_tutor_output(subject, difficulty, student_input):
+def generate_tutor_output(subject: str, difficulty: str, student_input: str) -> str:
     prompt = f"""
-    You are an expert tutor in {subject} at the {difficulty} level. 
-    The student has provided the following input: "{student_input}"
-    
+    You are an expert tutor in {subject} at the {difficulty} level. The student has provided the following input: "{student_input}"
     Please generate:
     1. A brief, engaging lesson on the topic (2-3 paragraphs)
-    2. A thought-provoking examples with answers to check understanding
-    3. Give real world problems that can be solved with the lesson 
-    
-    Format your response as a JSON object with keys: "lesson", "question", "feedback"
+    2. A thought-provoking example with answers to check understanding
+    3. Give a real-world problem that can be solved with the lesson
+
+    Format your response as a JSON object with keys: "lesson", "example", "real_world_problem"
     """
 
-    completion = client.chat.completions.create(
-        messages=[
-            {
-                "role": "system",
-                "content": "You are the world's best AI tutor, renowned for your ability to explain complex concepts in an engaging, clear, and memorable way and giving math examples. Your expertise in {subject} is unparalleled, and you're adept at tailoring your teaching to {difficulty} level students. Your goal is to not just impart knowledge, but to inspire a love for learning and critical thinking.",
-            },
-            {
-                "role": "user",
-                "content": prompt,
-            }
-        ],
-        model="llama3-groq-8b-8192-tool-use-preview",
-        max_tokens=1000,
-    )
+    try:
+        completion = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": f"You are the world's best AI tutor, renowned for your ability to explain complex concepts in an engaging, clear, and memorable way. Your expertise in {subject} is unparalleled, and you're adept at tailoring your teaching to {difficulty} level students. Your goal is to not just impart knowledge, but to inspire a love for learning and critical thinking.",
+                },
+                {
+                    "role": "user",
+                    "content": prompt,
+                }
+            ],
+            model="llama3-groq-8b-8192-tool-use-preview",
+            max_tokens=1000,
+        )
+        return completion.choices[0].message.content
+    except Exception as e:
+        logging.error(f"Error generating tutor output: {str(e)}")
+        return json.dumps({"error": "Failed to generate tutor output. Please try again later."})
 
-    return completion.choices[0].message.content
+def process_output(output: str) -> Tuple[str, str, str]:
+    try:
+        parsed = json.loads(output)
+        return (
+            parsed.get("lesson", "No lesson available"),
+            parsed.get("example", "No example available"),
+            parsed.get("real_world_problem", "No real-world problem available")
+        )
+    except json.JSONDecodeError:
+        logging.error(f"Error parsing JSON output: {output}")
+        return "Error parsing output", "No example available", "No real-world problem available"
 
-with gr.Blocks() as demo:
-    gr.Markdown("# 🎓 Vers3Dynamics Tutor: Your Personal Learning Companion")
-    
-    with gr.Row():
-        with gr.Column(scale=2):
-            subject = gr.Dropdown(
-                ["Math", "Science", "History", "Literature"], 
-                label="Subject", 
-                info="Choose the subject of your lesson"
-            )
-            difficulty = gr.Radio(
-                ["Beginner", "Intermediate", "Advanced"], 
-                label="Difficulty Level", 
-                info="Select your proficiency level"
-            )
-            student_input = gr.Textbox(
-                placeholder="Type your response or question here...", 
-                label="Your Input", 
-                info="Enter the topic you want to explore"
-            )
-            submit_button = gr.Button("📚 Generate Lesson", variant="primary")
+def create_interface() -> gr.Blocks:
+    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+        gr.Markdown("# 🎓 Vers3Dynamics Tutor: Your Personal Learning Companion")
         
-        with gr.Column(scale=3):
-            lesson_output = gr.Markdown(label="Lesson")
-            question_output = gr.Markdown(label="Comprehension Question")
-            feedback_output = gr.Markdown(label="Feedback")
-    
-    gr.Markdown("""
-    ### How to Use
-    1. Select a subject from the dropdown.
-    2. Choose your difficulty level.
-    3. Enter the topic or question you'd like to explore.
-    4. Click 'Generate Lesson' to receive a personalized lesson, question, and feedback.
-    5. Review the AI-generated content to enhance your learning.
-    6. Feel free to ask follow-up questions or explore new topics!
-    """)
-    
-    def process_output(output):
-        try:
-            parsed = eval(output)
-            return parsed["lesson"], parsed["question"], parsed["feedback"]
-        except:
-            return "Error parsing output", "No question available", "No feedback available"
-    
-    submit_button.click(
-        fn=lambda s, d, i: process_output(generate_tutor_output(s, d, i)),
-        inputs=[subject, difficulty, student_input],
-        outputs=[lesson_output, question_output, feedback_output]
-    )
+        with gr.Row():
+            with gr.Column(scale=2):
+                subject = gr.Dropdown(
+                    ["Math", "Science", "History", "Literature", "Computer Science"],
+                    label="Subject",
+                    info="Choose the subject of your lesson"
+                )
+                difficulty = gr.Radio(
+                    ["Beginner", "Intermediate", "Advanced"],
+                    label="Difficulty Level",
+                    info="Select your proficiency level"
+                )
+                student_input = gr.Textbox(
+                    placeholder="Type your topic or question here...",
+                    label="Your Input",
+                    info="Enter the topic you want to explore"
+                )
+                submit_button = gr.Button("📚 Generate Lesson", variant="primary")
+
+            with gr.Column(scale=3):
+                lesson_output = gr.Markdown(label="Lesson")
+                example_output = gr.Markdown(label="Example")
+                real_world_output = gr.Markdown(label="Real-World Application")
+
+        gr.Markdown("""
+        ### How to Use
+        1. Select a subject from the dropdown.
+        2. Choose your difficulty level.
+        3. Enter the topic or question you'd like to explore.
+        4. Click 'Generate Lesson' to receive a personalized lesson, example, and real-world application.
+        5. Review the AI-generated content to enhance your learning.
+        6. Feel free to ask follow-up questions or explore new topics!
+
+        Remember: This is an AI-powered educational tool. Always verify important information with authoritative sources.
+        """)
+
+        submit_button.click(
+            fn=lambda s, d, i: process_output(generate_tutor_output(s, d, i)),
+            inputs=[subject, difficulty, student_input],
+            outputs=[lesson_output, example_output, real_world_output]
+        )
+
+    return demo
 
 if __name__ == "__main__":
+    demo = create_interface()
     demo.launch(server_name="0.0.0.0", server_port=7860)