Update app.py

app.py

@@ -1,201 +1,70 @@
-import os
 import gradio as gr
 import requests
-import json
+import os
 import random
 
-# 🌍 Web search function
-def search_web(query):
-    try:
-        url = "https://api.duckduckgo.com/"
-        params = {"q": query, "format": "json", "no_html": 1, "skip_disambig": 1}
-        response = requests.get(url, params=params)
-        data = response.json()
-
-        if data.get("AbstractText"):
-            return data["AbstractText"]
-        elif data.get("RelatedTopics"):
-            topics = [t.get("Text", "") for t in data["RelatedTopics"] if "Text" in t]
-            return " ".join(topics[:3])
-        else:
-            return "No useful information found."
-    except Exception as e:
-        return f"Search error: {e}"
-
-# 🧠 Memory setup
+# 🧠 Function to call a Hugging Face model (or any LLM endpoint)
 HF_TOKEN = os.getenv("HF_TOKEN")
-MEMORY_FILE = "memory.json"
-
-def load_memory():
-    if os.path.exists(MEMORY_FILE):
-        with open(MEMORY_FILE, "r") as f:
-            return json.load(f)
-    return []
-
-def save_memory(memory):
-    with open(MEMORY_FILE, "w") as f:
-        json.dump(memory, f)
-
-memory = load_memory()
 
-# 💬 Chat function
-def chat_with_model(message, history, context, file_input=None):
-    if not isinstance(history, list):
-        history = []
-
-    if message.lower().startswith("search "):
-        query = message[7:]
-        search_result = search_web(query)
-        history.append((message, f"🔎 Here's what I found online:\n\n{search_result}"))
-        save_memory(history)
-        return history, history
-
-    if file_input:
-        file_name = file_input.name
-        message += f"\n\n📎 (User uploaded a file named '{file_name}')"
-
-    conversation = [
-        {"role": "system", "content": (
-            "You are EduAI, a multilingual educational AI assistant created by a Sri Lankan student named Wafa Fazly. "
-            "When solving math, explain step-by-step like a professional tutor. "
-            "Use Markdown and LaTeX formatting for equations (use \\[ and \\]). "
-            "Keep answers neat, structured, and student-friendly."
-        )}
-    ]
-
-    for past_user, past_bot in history[-5:]:
-        conversation.append({"role": "user", "content": past_user})
-        conversation.append({"role": "assistant", "content": past_bot})
-
-    conversation.append({"role": "user", "content": message})
+def generate_mcqs(topic="science", num_questions=3):
+    """Generate MCQs using a model API"""
+    prompt = f"Create {num_questions} multiple-choice questions on {topic}. " \
+             f"Each question should have 4 options (A–D) and specify the correct answer."
 
     try:
         response = requests.post(
-            "https://router.huggingface.co/v1/chat/completions",
-            headers={
-                "Authorization": f"Bearer {HF_TOKEN}",
-                "Content-Type": "application/json"
-            },
-            json={
-                "model": "deepseek-ai/DeepSeek-V3.2-Exp:novita",
-                "messages": conversation
-            }
+            "https://api-inference.huggingface.co/models/google/gemma-2b",
+            headers={"Authorization": f"Bearer {HF_TOKEN}"},
+            json={"inputs": prompt}
         )
-
         data = response.json()
-        reply = data["choices"][0]["message"]["content"]
-
-        reply = reply.replace("Step", "\n\n**Step")
-        reply = reply.replace(":", ":**")
-        reply = reply.replace("\\[", "\n\n\\[")
-        reply = reply.replace("\\]", "\\]\n\n")
-
-        if "\\" in reply or "log_" in reply or "^" in reply:
-            reply = f"{reply}"
-
-        history.append((message, reply))
-        save_memory(history)
-        return history, history
-
+        text = data[0]["generated_text"]
+
+        # 🪄 Simple parsing: try to split questions
+        questions = []
+        for block in text.split("\n\n"):
+            if "." in block:
+                parts = block.split("\n")
+                q_line = parts[0]
+                opts = [p.strip() for p in parts[1:5] if p.strip()]
+                ans = ""
+                for p in parts:
+                    if "Answer" in p or "Correct" in p:
+                        ans = p.split(":")[-1].strip()
+                if len(opts) == 4:
+                    questions.append({"question": q_line, "options": opts, "answer": ans})
+        return questions if questions else [{"question": "⚠️ Couldn’t parse any question.", "options": [], "answer": ""}]
     except Exception as e:
-        print("Error:", e)
-        history.append((message, "😅 EduAI is having trouble connecting right now. Please try again later!"))
-        return history, history
-
-
-# 📘 Sidebar context update
-def update_context(choice):
-    if not choice:
-        return "📘 **You are in General Mode.** Ask EduAI anything about your studies!"
-    return f"📘 **You selected {choice} mode.** Ask anything related to this topic!"
-
-
-# 🧹 Clear chat memory
-def clear_memory():
-    if os.path.exists(MEMORY_FILE):
-        os.remove(MEMORY_FILE)
-    return [], "🧹 Chat memory cleared! Start fresh."
-
-
-# 🧠 MCQ QUIZ GENERATOR
-quiz_data = [
-    {"question": "Which planet is known as the Red Planet?", "options": ["Earth", "Mars", "Venus", "Jupiter"], "answer": "Mars"},
-    {"question": "What is the chemical symbol for water?", "options": ["H2O", "O2", "CO2", "NaCl"], "answer": "H2O"},
-    {"question": "What is 5 × 6?", "options": ["11", "30", "25", "36"], "answer": "30"},
-    {"question": "Which gas do humans breathe in to survive?", "options": ["Carbon dioxide", "Oxygen", "Nitrogen", "Hydrogen"], "answer": "Oxygen"},
-    {"question": "What is the largest planet in our Solar System?", "options": ["Earth", "Mars", "Jupiter", "Saturn"], "answer": "Jupiter"}
-]
-
-def generate_quiz():
-    selected = random.sample(quiz_data, 3)
-    quiz_html = ""
-    for i, q in enumerate(selected, 1):
-        quiz_html += f"<div><b>{i}. {q['question']}</b><br>"
-        for opt in q['options']:
-            quiz_html += f"<input type='checkbox' name='q{i}' value='{opt}'> {opt}<br>"
-        quiz_html += "<br></div>"
-    quiz_html += "<br><b>✅ Select your answers and review!</b>"
-    return quiz_html
-
-
-# 🎨 Gradio Interface
-with gr.Blocks(theme=gr.themes.Soft(primary_hue="violet")) as iface:
-    gr.Markdown("# 🎓 **EduAI — Your Smart Study Companion**")
-
-    with gr.Row():
-        with gr.Column(scale=1, min_width=230):
-            gr.Markdown("### 🧭 **Main Menu**")
-
-            with gr.Accordion("📚 Subject Tutor", open=False):
-                subj = gr.Radio(
-                    ["Science 🧪", "ICT 💻", "English 📘", "Mathematics ➗"],
-                    label="Choose a subject"
-                )
-
-            with gr.Accordion("🗓 Study Planner", open=False):
-                planner = gr.Radio(
-                    ["View Plan 📅", "Add Task ✏️", "Study Tips 💡"],
-                    label="Planner Options"
-                )
-
-            with gr.Accordion("🌐 Languages", open=False):
-                lang = gr.Radio(
-                    ["Learn Sinhala 🇱🇰", "Learn Tamil 🇮🇳", "Learn English 🇬🇧", "Learn Spanish 🇪🇸"],
-                    label="Language Options"
-                )
-
-            with gr.Accordion("🧠 MCQ Quiz Generator", open=False):
-                gen_btn = gr.Button("🎯 Generate Quiz")
-                quiz_output = gr.HTML("<i>Click 'Generate Quiz' to start!</i>")
-
-            with gr.Accordion("⚙️ Settings", open=False):
-                clear_btn = gr.Button("🧹 Clear Memory")
-
-            with gr.Accordion("👩‍🎓 About", open=False):
-                gr.Markdown("""
-                EduAI – developed and fine-tuned by **Wafa Fazly** using a pre-trained AI model,  
-                to help learners understand **Science, ICT, English, and more** —  
-                in a simple and friendly way! 💬
-                """)
-
-        with gr.Column(scale=4):
-            context_display = gr.Markdown("📘 **You are in General Mode.** Ask EduAI anything about your studies!")
-            chatbot = gr.Chatbot(
-                label="EduAI Chat",
-                height=450,
-                render_markdown=True,
-                latex_delimiters=[{"left": "$$", "right": "$$", "display": True}, {"left": "\\[", "right": "\\]", "display": True}]
-            )
-            msg = gr.Textbox(label="Ask EduAI:")
-            file_input = gr.File(label="📂 Upload a study file (PDF, DOCX, or image):")
-            send = gr.Button("Send ✈️")
-
-    # 🪄 Event handlers
-    subj.change(update_context, inputs=subj, outputs=context_display)
-    planner.change(update_context, inputs=planner, outputs=context_display)
-    lang.change(update_context, inputs=lang, outputs=context_display)
-    send.click(chat_with_model, inputs=[msg, chatbot, context_display, file_input], outputs=[chatbot, chatbot])
-    clear_btn.click(clear_memory, outputs=[chatbot, context_display])
-    gen_btn.click(generate_quiz, outputs=quiz_output)
-
-iface.launch()
+        return [{"question": f"Error: {e}", "options": [], "answer": ""}]
+
+
+# 🎯 Build quiz HTML with checkboxes
+def build_quiz_html(topic):
+    mcqs = generate_mcqs(topic)
+    html = "<div style='font-family:Poppins,sans-serif;color:#222;'>"
+    for i, q in enumerate(mcqs, 1):
+        html += f"<div style='margin:15px;padding:15px;border-radius:10px;background:#fff9ff;box-shadow:0 3px 10px rgba(0,0,0,0.08);'>"
+        html += f"<b style='color:#5b21b6;'>{i}. {q['question']}</b><br><br>"
+        for opt in q["options"]:
+            html += f"<label style='display:block;margin-bottom:5px;'><input type='checkbox' name='q{i}' value='{opt}' style='accent-color:#7c3aed;'> {opt}</label>"
+        html += f"<p style='color:#7e22ce;display:none;' id='ans{i}'><b>✅ Correct Answer:</b> {q['answer']}</p>"
+        html += "</div>"
+    html += """
+    <button onclick="document.querySelectorAll('[id^=ans]').forEach(a=>a.style.display='block');" 
+            style='margin-top:10px;background:#7c3aed;color:white;border:none;padding:10px 20px;border-radius:8px;cursor:pointer;'>
+        Show Answers
+    </button>
+    </div>"""
+    return html
+
+
+# ⚙️ Gradio Interface
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="violet")) as demo:
+    gr.Markdown("<h1 style='text-align:center;color:#5b21b6;'>🧠 EduAI — Auto MCQ Quiz Generator</h1>")
+    topic = gr.Textbox(label="Enter a topic (e.g. Physics, History, Chemistry)")
+    gen_btn = gr.Button("🎯 Generate Quiz")
+    quiz_output = gr.HTML("<i>Enter a topic and click Generate to start!</i>")
+
+    gen_btn.click(build_quiz_html, inputs=topic, outputs=quiz_output)
+
+demo.launch()