Update app.py

app.py

@@ -2,142 +2,153 @@ import os
 import gradio as gr
 import requests
 import json
+import random
 
-# 🌍 Hugging Face DeepSeek Model Token
+# Hugging Face API token
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-# 🧠 Memory
-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 with Hugging Face
-def ai_response(message, history, context, file_input=None):
-    if not isinstance(history, list):
+# =========================
+# AI response via DeepSeek
+# =========================
+def ai_response(message, history=None):
+    if history is None:
         history = []
 
-    if file_input:
-        message += f"\n\n📎 (User uploaded file '{file_input.name}')"
-
-    conversation = [
-        {"role":"system", "content":(
-            "You are EduAI, a multilingual educational AI assistant. "
-            "Explain answers like a professional tutor, use Markdown/LaTeX for math, "
-            "and keep answers neat and student-friendly."
-        )}
-    ]
+    conversation = [{"role": "system", "content": (
+        "You are EduAI, a professional multilingual educational assistant. "
+        "Explain clearly with examples, use step-by-step for math, and Markdown/LaTeX for equations."
+    )}]
 
     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})
+        conversation.append({"role": "user", "content": past_user})
+        conversation.append({"role": "assistant", "content": past_bot})
+
+    conversation.append({"role": "user", "content": message})
 
     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/v1/chat/completions",
+            headers={
+                "Authorization": f"Bearer {HF_TOKEN}",
+                "Content-Type": "application/json"
+            },
+            json={
+                "model": "deepseek-ai/DeepSeek-V3.2-Exp:novita",
+                "messages": conversation
+            }
         )
         data = response.json()
         reply = data["choices"][0]["message"]["content"]
         history.append((message, reply))
-        save_memory(history)
-        return history, history
+        return history, reply
     except Exception as e:
         history.append((message, f"❌ Error contacting model: {e}"))
-        return history, history
-
-# 🧠 MCQ generator (dynamic)
-def generate_mcq(topic):
-    prompt = f"Create a 3-question multiple-choice quiz about '{topic}' with 4 options each and indicate the correct answer."
+        return history, history[-1][1]
+
+# =========================
+# MCQ Generator (AI-based)
+# =========================
+def generate_mcq(subject):
+    prompt = f"Create 3 multiple-choice questions with 4 options each and the correct answer for {subject}. Return as JSON like: [{{'question':'...','options':['..'],'answer':'..'}}, ...]"
+    history, reply = ai_response(prompt)
     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":[{"role":"user","content":prompt}]}
-        )
-        data = response.json()
-        reply = data["choices"][0]["message"]["content"]
-        # Simple formatting: each question as separate div
-        quiz_html = "<div style='color:white; font-family:Poppins, sans-serif;'>"
-        for i, line in enumerate(reply.split("\n")):
-            quiz_html += f"{line}<br>"
+        mcqs = json.loads(reply)
+    except:
+        return f"❌ Error generating MCQs: {reply}"
+
+    quiz_html = "<div style='font-family:Poppins, sans-serif; color:#EEE;'>"
+    for i, q in enumerate(mcqs, 1):
+        quiz_html += f"<div style='margin-bottom:15px; padding:12px; border-radius:10px; background:#2a2a2a;'>"
+        quiz_html += f"<b style='color:#7C3AED;'>{i}. {q['question']}</b><br>"
+        for opt in q['options']:
+            quiz_html += f"<label style='display:block; margin:5px 0;'><input type='checkbox' value='{opt}' style='accent-color:#7C3AED;'> {opt}</label>"
+        quiz_html += f"<details style='color:#fff;'><summary>Show Answer</summary>Answer: {q['answer']}</details>"
         quiz_html += "</div>"
-        return quiz_html
-    except Exception as e:
-        return f"❌ Error generating MCQs: {e}"
-
-# 📘 Sidebar context
-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
-def clear_memory():
-    if os.path.exists(MEMORY_FILE):
-        os.remove(MEMORY_FILE)
-    return [], "🧹 Chat memory cleared! Start fresh."
-
-# 🎨 UI Custom CSS
+    quiz_html += "</div>"
+    return quiz_html
+
+# =========================
+# Study Adviser
+# =========================
+def study_adviser(question):
+    history, answer = ai_response(f"Give a professional study advice: {question}")
+    return answer
+
+# =========================
+# Study Planner
+# =========================
+planner_tasks = []
+
+def add_task(task):
+    planner_tasks.append(task)
+    return "\n".join([f"- {t}" for t in planner_tasks])
+
+def view_plan():
+    if not planner_tasks:
+        return "No tasks added yet."
+    return "\n".join([f"- {t}" for t in planner_tasks])
+
+# =========================
+# Gradio UI
+# =========================
 custom_css = """
-.gradio-container {background: #1e1e2f; font-family:'Poppins', sans-serif; color:white;}
-#chatbot {background: rgba(30,30,47,0.8); border-radius: 16px; backdrop-filter: blur(10px);}
-button.primary {background: linear-gradient(90deg,#7c3aed,#a855f7); color:white; border:none; border-radius:8px;}
-button.primary:hover {background: linear-gradient(90deg,#6d28d9,#9333ea);}
-input[type=checkbox] {accent-color:#a855f7;}
+body {background:#121212; color:#EEE; font-family:Poppins, sans-serif;}
+button.primary {background:#7C3AED; color:white; border-radius:8px; padding:5px 12px;}
+button.primary:hover {background:#6D28D9;}
+.gradio-container {background:#121212;}
 """
 
-# 🎨 Gradio Blocks
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft(primary_hue="violet")) as iface:
-    gr.Markdown("<h1 style='text-align:center; color:#A855F7;'>🎓 EduAI — Smart Study Companion</h1>")
+with gr.Blocks(css=custom_css, theme=gr.themes.Dark()) as iface:
+    gr.Markdown("<h1 style='text-align:center; color:#7C3AED;'>🎓 EduAI — Smart Study Companion</h1>")
 
     with gr.Row():
-        # 🌈 Left Sidebar
         with gr.Column(scale=1, min_width=250):
-            gr.Markdown("### 🧭 **Main Menu**")
+            gr.Markdown("### 🧭 Main Menu")
+
             with gr.Accordion("📚 Study Tutor", open=False):
-                tutor_subj = gr.Radio(["Mathematics ➗","Science 🧪","ICT 💻","English 📘"], label="Select Subject")
+                subject_tutor = gr.Radio(["Math", "Science", "ICT", "English"], label="Select Subject")
+                tutor_input = gr.Textbox(label="Ask your question:")
+                tutor_output = gr.Textbox(label="Answer:")
+                tutor_btn = gr.Button("Get Answer", elem_classes="primary")
 
             with gr.Accordion("🧠 MCQ Generator", open=False):
-                mcq_topic = gr.Textbox(label="Enter topic for quiz:")
-                mcq_btn = gr.Button("Generate Quiz 🎯", elem_classes="primary")
-                mcq_output = gr.HTML("<i>Quiz will appear here...</i>")
+                mcq_subject = gr.Radio(["Math", "Science", "ICT", "English"], label="Select Subject")
+                mcq_output = gr.HTML("<i>Click 'Generate Quiz' to start!</i>")
+                mcq_btn = gr.Button("Generate Quiz", elem_classes="primary")
 
-            with gr.Accordion("🗓 Study Planner", open=False):
-                planner_choice = gr.Radio(["View Plan 📅","Add Task ✏️","Study Tips 💡"], label="Planner Options")
-
-            with gr.Accordion("💡 Study Adviser", open=False):
-                adviser_input = gr.Textbox(label="Ask for study advice")
+            with gr.Accordion("📋 Study Adviser", open=False):
+                adviser_input = gr.Textbox(label="Ask for study advice:")
+                adviser_output = gr.Textbox(label="Advice:")
                 adviser_btn = gr.Button("Get Advice", elem_classes="primary")
-                adviser_output = gr.HTML("<i>Advice will appear here...</i>")
 
-            with gr.Accordion("⚙️ Settings", open=False):
-                clear_btn = gr.Button("🧹 Clear Memory")
+            with gr.Accordion("🗓 Study Planner", open=False):
+                task_input = gr.Textbox(label="Add a Task:")
+                add_task_btn = gr.Button("Add Task", elem_classes="primary")
+                view_plan_btn = gr.Button("View Plan", elem_classes="primary")
+                planner_output = gr.Textbox(label="Planner Tasks:")
 
-        # 💬 Main Chat
-        with gr.Column(scale=3):
-            context_display = gr.Markdown("📘 **General Mode.** Ask EduAI anything!")
-            chatbot = gr.Chatbot(label="EduAI Chat", elem_id="chatbot", height=450, type="messages")
+        with gr.Column(scale=4):
+            chatbot_display = gr.Chatbot(label="💬 EduAI Chat", height=480, type="messages")
             user_input = gr.Textbox(label="Type your question:")
-            send_btn = gr.Button("Send ✈️", elem_classes="primary")
-            file_input = gr.File(label="📂 Upload optional file")
-
-    # ⚙️ Event handlers
-    tutor_subj.change(update_context, inputs=tutor_subj, outputs=context_display)
-    planner_choice.change(update_context, inputs=planner_choice, outputs=context_display)
-    send_btn.click(ai_response, inputs=[user_input, chatbot, context_display, file_input], outputs=[chatbot, chatbot])
-    clear_btn.click(clear_memory, outputs=[chatbot, context_display])
-    mcq_btn.click(generate_mcq, inputs=mcq_topic, outputs=mcq_output)
-    adviser_btn.click(ai_response, inputs=[adviser_input, chatbot, context_display, None], outputs=[adviser_output, adviser_output])
+            send_btn = gr.Button("Send", elem_classes="primary")
+
+    # =========================
+    # Event Bindings
+    # =========================
+    # Study Tutor
+    tutor_btn.click(ai_response, inputs=[tutor_input, gr.State(value=[])], outputs=[gr.State(value=[]), tutor_output])
+
+    # MCQ Generator
+    mcq_btn.click(generate_mcq, inputs=[mcq_subject], outputs=[mcq_output])
+
+    # Study Adviser
+    adviser_btn.click(study_adviser, inputs=[adviser_input], outputs=[adviser_output])
+
+    # Study Planner
+    add_task_btn.click(add_task, inputs=[task_input], outputs=[planner_output])
+    view_plan_btn.click(view_plan, outputs=[planner_output])
+
+    # Chatbot
+    send_btn.click(ai_response, inputs=[user_input, gr.State(value=[])], outputs=[gr.State(value=[]), chatbot_display])
 
 iface.launch()