Update app.py

app.py

@@ -2,12 +2,49 @@ import gradio as gr
 from groq import Groq
 import os
 import json
+import random
+import sqlite3
 
 # Initialize Groq client
 client = Groq(api_key=os.environ["GROQ_API_KEY"])
 print("API Key:", os.environ.get("GROQ_API_KEY"))  # Debug print
 
+# Initialize or connect to SQLite database for points
+conn = sqlite3.connect("student_points.db", check_same_thread=False)
+cursor = conn.cursor()
+cursor.execute('''CREATE TABLE IF NOT EXISTS points (student_id TEXT, points INTEGER, timestamp TEXT)''')
+conn.commit()
+
 def generate_tutor_output(subject, grade, student_input, model):
+    # List of supported Groq models (based on your provided list)
+    valid_models = [
+        "distil-whisper-large-v3-en",
+        "gemma2-9b-it",
+        "llama-3.3-70b-versatile",
+        "llama-3.1-8b-instant",
+        "llama-guard-3-8b",
+        "llama3-70b-8192",
+        "llama3-8b-8192",
+        "mixtral-8x7b-32768",
+        "whisper-large-v3",
+        "whisper-large-v3-turbo",
+        "qwen-qwq-32b",
+        "mistral-saba-24b",
+        "qwen-2.5-coder-32b",
+        "qwen-2.5-32b",
+        "deepseek-r1-distill-qwen-32b",
+        "deepseek-r1-distill-llama-70b-specdec",
+        "deepseek-r1-distill-llama-70b",
+        "llama-3.3-70b-specdec",
+        "llama-3.2-1b-preview",
+        "llama-3.2-3b-preview",
+        "llama-3.2-11b-vision-preview",
+        "llama-3.2-90b-vision-preview"
+    ]
+    if model not in valid_models:
+        model = "mixtral-8x7b-32768"  # Fallback model
+        print(f"Invalid model selected: {model}. Using fallback: mixtral-8x7b-32768")
+
     prompt = f"""
     You are an expert tutor in {subject} for a {grade} grade student. 
     The student has provided the following input: "{student_input}"
@@ -37,7 +74,7 @@ def generate_tutor_output(subject, grade, student_input, model):
         )
         return completion.choices[0].message.content
     except Exception as e:
-        print(f"Groq API Error: {str(e)}")  # Debug print
+        print(f"Groq API Error: {str(e)}")
         return json.dumps({
             "lesson": f"Error: Could not generate lesson. API error: {str(e)}",
             "question": "No question available",
@@ -46,11 +83,44 @@ def generate_tutor_output(subject, grade, student_input, model):
             "feedback": "No feedback available due to API error"
         })
 
-def check_answer(selected_answer, correct_answer):
+def check_answer(selected_answer, correct_answer, current_points, student_id="student1"):
     if selected_answer == correct_answer:
-        return "🎉 Awesome job! You got it right! Keep rocking it!", 10
+        feedback = "🎉 Awesome job! You got it right! Keep rocking it!"
+        new_points = current_points + 10
     else:
-        return f"😅 Not quite! The correct answer was '{correct_answer}'. Try again next time!", 0
+        feedback = f"😅 Not quite! The correct answer was '{correct_answer}'. Try again next time!"
+        new_points = current_points
+    # Save points to database
+    cursor.execute("INSERT INTO points (student_id, points, timestamp) VALUES (?, ?, ?)", 
+                   (student_id, new_points, "2025-03-08 04:25"))
+    conn.commit()
+    return feedback, new_points
+
+def process_output(output):
+    print(f"Raw API Output: {output}")
+    try:
+        parsed = json.loads(output)
+        # Shuffle options for variety
+        options_list = list(zip(["a", "b", "c", "d"], parsed["options"]))
+        random.shuffle(options_list)
+        options = [f"{k}. {v}" for k, v in options_list]
+        correct_key = [k for k, v in options_list if v == parsed["correct_answer"]][0]
+        return (
+            parsed["lesson"],
+            parsed["question"],
+            options,
+            correct_key,
+            parsed["feedback"]
+        )
+    except Exception as e:
+        print(f"JSON Parsing Error: {str(e)}")
+        return (
+            f"Error parsing response: {str(e)}",
+            "No question available",
+            [],
+            "",
+            "No feedback available"
+        )
 
 with gr.Blocks(title="Learn & Practice 🚀") as demo:
     gr.Markdown("# 🚀 Learn & Practice Zone (Grades 5-10)")
@@ -69,11 +139,7 @@ with gr.Blocks(title="Learn & Practice 🚀") as demo:
                 info="Select your grade level"
             )
             model_select = gr.Dropdown(
-                [
-                    "mixtral-8x7b-32768",
-                    "llama3-8b-8192",  # Fallback model
-                    "qwen-2.5-32b"
-                ],
+                valid_models,
                 label="AI Tutor Model",
                 value="mixtral-8x7b-32768",
                 info="Choose your AI tutor"
@@ -104,30 +170,8 @@ with gr.Blocks(title="Learn & Practice 🚀") as demo:
     5. Earn points for correct answers and keep learning!
     """)
 
-    def process_output(output):
-        print(f"Raw API Output: {output}")  # Debug print
-        try:
-            parsed = json.loads(output)
-            options = [f"{k}. {v}" for k, v in zip(["a", "b", "c", "d"], parsed["options"])]
-            return (
-                parsed["lesson"],
-                parsed["question"],
-                options,
-                parsed["correct_answer"],
-                parsed["feedback"]
-            )
-        except Exception as e:
-            print(f"JSON Parsing Error: {str(e)}")  # Debug print
-            return (
-                f"Error parsing response: {str(e)}",
-                "No question available",
-                [],
-                "",
-                "No feedback available"
-            )
-
     def update_interface(subject, grade, student_input, model):
-        print(f"Selected Model: {model}")  # Debug print
+        print(f"Selected Model: {model}")
         output = generate_tutor_output(subject, grade, student_input, model)
         lesson, question, options, correct_answer, feedback = process_output(output)
         return (
@@ -136,7 +180,7 @@ with gr.Blocks(title="Learn & Practice 🚀") as demo:
             gr.update(choices=options, visible=True),
             feedback,
             "",  # Clear answer feedback
-            gr.update(value=0)  # Reset points
+            gr.update(value=0)  # Reset points for new session
         ), correct_answer
 
     # State to store correct answer
@@ -154,9 +198,12 @@ with gr.Blocks(title="Learn & Practice 🚀") as demo:
 
     options_output.change(
         fn=check_answer,
-        inputs=[options_output, correct_answer_state],
+        inputs=[options_output, correct_answer_state, points],
         outputs=[answer_feedback, points]
     )
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    try:
+        demo.launch(server_name="0.0.0.0", server_port=7860)
+    finally:
+        conn.close()  # Close database connection on shutdown