Update app.py

app.py

@@ -3,120 +3,141 @@ import gradio as gr
 import requests
 import json
 
+# 🌍 Hugging Face DeepSeek Model Token
 HF_TOKEN = os.getenv("HF_TOKEN")
-MODEL_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-V3.2-Exp:novita"
 
-# 🧠 AI Response function
+# 🧠 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):
         history = []
 
     if file_input:
-        message += f"\n\n📎 (User uploaded a file named '{file_input.name}')"
+        message += f"\n\n📎 (User uploaded file '{file_input.name}')"
 
     conversation = [
-        {"role": "system", "content": (
-            "You are EduAI, a professional educational AI assistant. "
-            "Explain clearly and step-by-step. Generate MCQs dynamically when requested. "
-            "Use Markdown and LaTeX for math."
+        {"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."
         )}
     ]
+
     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(
-            MODEL_URL,
-            headers={"Authorization": f"Bearer {HF_TOKEN}", "Content-Type": "application/json"},
-            json={"inputs": conversation, "parameters":{"max_new_tokens":512}}
+            "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}
         )
         data = response.json()
-        if isinstance(data, dict) and "error" in data:
-            reply = "❌ Error contacting model: " + data["error"]
-        else:
-            reply = data[0]["generated_text"] if isinstance(data, list) else str(data)
+        reply = data["choices"][0]["message"]["content"]
         history.append((message, reply))
+        save_memory(history)
         return history, history
     except Exception as e:
         history.append((message, f"❌ Error contacting model: {e}"))
         return history, history
 
-# 🧹 Clear Chat Memory
-MEMORY_FILE = "memory.json"
-def clear_memory():
-    if os.path.exists(MEMORY_FILE):
-        os.remove(MEMORY_FILE)
-    return [], "🧹 Chat memory cleared! Start fresh."
-
-# 📘 Sidebar context
-def update_context(choice):
-    if not choice:
-        return "📘 **General Mode.** Ask EduAI anything!"
-    return f"📘 **You selected {choice}.**"
-
-# 🧩 Dynamic MCQ generator via AI
+# 🧠 MCQ generator (dynamic)
 def generate_mcq(topic):
-    prompt = f"Create a short 3-question MCQ quiz about {topic} with 4 options each and indicate the correct answer."
+    prompt = f"Create a 3-question multiple-choice quiz about '{topic}' with 4 options each and indicate the correct answer."
     try:
         response = requests.post(
-            MODEL_URL,
-            headers={"Authorization": f"Bearer {HF_TOKEN}", "Content-Type": "application/json"},
-            json={"inputs": prompt, "parameters":{"max_new_tokens":400}}
+            "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()
-        text = data[0]["generated_text"] if isinstance(data, list) else str(data)
-        return f"<div style='color:white'>{text.replace(chr(10), '<br>')}</div>"
+        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>"
+        quiz_html += "</div>"
+        return quiz_html
     except Exception as e:
         return f"❌ Error generating MCQs: {e}"
 
-# 🎨 Gradio UI
+# 📘 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
 custom_css = """
-body {background-color:#1e1e2f; color:white; font-family:'Poppins', sans-serif;}
-#chatbot {background: rgba(30,30,50,0.85); border-radius:12px; backdrop-filter: blur(8px);}
+.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;}
 """
 
-with gr.Blocks(css=custom_css) as iface:
-    gr.Markdown("<h1 style='text-align:center; color:#a855f7'>🎓 EduAI — Smart Study Companion</h1>")
+# 🎨 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.Row():
-        with gr.Column(scale=1, min_width=220):
-            gr.Markdown("### 🧭 Main Menu")
-
+        # 🌈 Left Sidebar
+        with gr.Column(scale=1, min_width=250):
+            gr.Markdown("### 🧭 **Main Menu**")
             with gr.Accordion("📚 Study Tutor", open=False):
-                tutor_sub = gr.Radio(["Math", "Science", "ICT", "English"], label="Select Subject")
+                tutor_subj = gr.Radio(["Mathematics ➗","Science 🧪","ICT 💻","English 📘"], label="Select Subject")
 
             with gr.Accordion("🧠 MCQ Generator", open=False):
-                mcq_topic = gr.Textbox(label="Topic for Quiz")
-                gen_mcq_btn = gr.Button("Generate MCQ", elem_classes="primary")
-                mcq_output = gr.HTML("<i>Enter a topic and click 'Generate MCQ'</i>")
+                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>")
 
             with gr.Accordion("🗓 Study Planner", open=False):
-                planner_opt = gr.Radio(["View Plan", "Add Task", "Study Tips"], label="Planner Options")
+                planner_choice = gr.Radio(["View Plan 📅","Add Task ✏️","Study Tips 💡"], label="Planner Options")
 
-            with gr.Accordion("📖 Study Advisor", open=False):
-                advisor_txt = gr.Textbox(label="Ask for Study Advice")
-                advisor_btn = gr.Button("Get Advice", elem_classes="primary")
-                advisor_output = gr.HTML("<i>Ask your study question here</i>")
+            with gr.Accordion("💡 Study Adviser", open=False):
+                adviser_input = gr.Textbox(label="Ask for study 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 Chat Memory")
+                clear_btn = gr.Button("🧹 Clear Memory")
 
-        with gr.Column(scale=4):
-            context_display = gr.Markdown("📘 **General Mode**")
-            chatbot = gr.Chatbot(label="💬 EduAI Chat", elem_id="chatbot", height=480, type="messages")
-            user_input = gr.Textbox(label="Type your message")
+        # 💬 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")
+            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 bindings
-    send_btn.click(ai_response, inputs=[user_input, chatbot, context_display, gr.File(visible=False)], outputs=[chatbot, chatbot])
+    # ⚙️ 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])
-    gen_mcq_btn.click(generate_mcq, inputs=[mcq_topic], outputs=mcq_output)
-    advisor_btn.click(ai_response, inputs=[advisor_txt, chatbot, context_display, gr.File(visible=False)], outputs=[chatbot, chatbot])
-    tutor_sub.change(update_context, inputs=tutor_sub, outputs=context_display)
-    planner_opt.change(update_context, inputs=planner_opt, outputs=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])
 
 iface.launch()