Update app.py

app.py

@@ -1,6 +1,6 @@
 # --------------------------------------------------------------
 # IGCSE/GCSE Language Platform – 100% free on Hugging Face Spaces
-# Model: deepseek-ai/DeepSeek-V3.2-Exp:novita (via HF Inference API)
+# Model: MiniMaxAI/MiniMax-M2:novita (Primary) + DeepSeek V3.2 (Backup)
 # --------------------------------------------------------------
 
 import os
@@ -18,7 +18,9 @@ if not HF_TOKEN:
 
 client = InferenceClient(api_key=os.environ["HF_TOKEN"])
 
-MODEL = "deepseek-ai/DeepSeek-V3.2-Exp:novita"
+# Primary and backup models
+PRIMARY_MODEL = "MiniMaxAI/MiniMax-M2:novita"
+BACKUP_MODEL = "deepseek-ai/DeepSeek-V3.2-Exp:novita"
 
 # ---------- 2. Global storage ----------
 papers_storage = []
@@ -45,8 +47,9 @@ efl_topics = [
     "Listening Comprehension"
 ]
 
-# ---------- 4. Helper: call the model ----------
+# ---------- 4. Helper: call the model with fallback ----------
 def call_model(messages: list, system: str = "", max_tokens=1000):
+    """Call primary model with automatic fallback to backup"""
     try:
         # Prepare messages with system prompt if provided
         formatted_messages = []
@@ -54,13 +57,26 @@ def call_model(messages: list, system: str = "", max_tokens=1000):
             formatted_messages.append({"role": "system", "content": system})
         formatted_messages.extend(messages)
         
-        resp = client.chat.completions.create(
-            model=MODEL,
-            messages=formatted_messages,
-            max_tokens=max_tokens,
-            temperature=0.7,
-        )
-        return resp.choices[0].message.content.strip()
+        # Try primary model first
+        try:
+            resp = client.chat.completions.create(
+                model=PRIMARY_MODEL,
+                messages=formatted_messages,
+                max_tokens=max_tokens,
+                temperature=0.7,
+            )
+            return resp.choices[0].message.content.strip()
+        except Exception as primary_error:
+            # Fallback to backup model
+            print(f"Primary model failed, using backup: {primary_error}")
+            resp = client.chat.completions.create(
+                model=BACKUP_MODEL,
+                messages=formatted_messages,
+                max_tokens=max_tokens,
+                temperature=0.7,
+            )
+            return resp.choices[0].message.content.strip()
+            
     except Exception as e:
         return f"Error: {e}"
 
@@ -86,7 +102,8 @@ def ai_tutor_chat(message, history, subject, topic, level):
     system = f"""You are an expert {'French' if subject == 'French' else 'EFL'} {level} tutor.
 Focus on {topic or 'any topic'}. Be encouraging, clear, and pedagogical. 
 Adjust difficulty and explanations appropriately for {level} level students.
-Provide detailed explanations with examples when needed."""
+Provide detailed explanations with examples when needed.
+Use a friendly, supportive tone to help students learn effectively."""
     
     msgs = [{"role": "user" if i % 2 == 0 else "assistant", "content": turn}
             for pair in history for i, turn in enumerate(pair) if turn]
@@ -105,22 +122,23 @@ def translate_text(text, direction):
         return "Enter text first."
     src = "English" if direction == "English → French" else "French"
     tgt = "French" if direction == "English → French" else "English"
-    system = f"You are a professional translator. Provide accurate, natural translations from {src} to {tgt}."
-    prompt = f"Translate this text to {tgt}. Provide only the translation without any explanations:\n\n{text}"
+    system = f"You are a professional translator specializing in {src} to {tgt} translation. Provide accurate, natural, and contextually appropriate translations."
+    prompt = f"Translate this text to {tgt}. Provide only the translation without any explanations or additional commentary:\n\n{text}"
     return call_model([{"role": "user", "content": prompt}], system, max_tokens=800)
 
 # ---------- 8. Dictionary ----------
 def dictionary_lookup(word):
     if not word.strip():
         return "Enter a French word."
-    system = "You are a French language dictionary expert. Provide comprehensive, accurate definitions."
+    system = "You are a French language dictionary expert with deep knowledge of French vocabulary, grammar, and usage. Provide comprehensive, accurate definitions."
     prompt = f"""Provide a detailed French dictionary entry for "{word}":
-- Part of speech
-- English meaning(s)
-- Gender (if noun)
-- 3 example sentences (French with English translations)
+- Part of speech (noun, verb, adjective, etc.)
+- Gender (if noun: masculine/feminine)
+- English meaning(s) and translations
+- 3 example sentences in French with English translations
 - Common phrases and idioms using this word
-- Any important usage notes"""
+- Any important usage notes or context
+- Related words or derivatives"""
     return call_model([{"role": "user", "content": prompt}], system, max_tokens=1200)
 
 # ---------- 9. Practice Questions (Enhanced with PDF context) ----------
@@ -136,20 +154,21 @@ def generate_question(subject, topic, level):
             # Use first 3000 chars of PDF content for better context
             pdf_context += f"\n\nReference material from {paper['title']}:\n{content[:3000]}"
     
-    system = f"You are an expert {level} {subject} examiner. Create authentic, challenging exam questions."
-    prompt = f"""Create ONE {level} {subject} exam question on the topic: "{topic}".
-{"Base the question style and difficulty on this reference material:" + pdf_context if pdf_context else ""}
+    system = f"You are an expert {level} {subject} examiner with years of experience creating authentic exam questions. You understand exam board requirements and student needs."
+    prompt = f"""Create ONE high-quality {level} {subject} exam question on the topic: "{topic}".
+{"Base the question style, difficulty level, and format on this reference material from actual past papers:" + pdf_context if pdf_context else "Create an authentic exam-style question appropriate for {level} level."}
 
 The question should:
-- Be appropriate for {level} level
-- Test understanding, not just memorization
-- Include clear instructions
+- Be appropriate for {level} level students
+- Test understanding and application, not just memorization
+- Include clear, unambiguous instructions
 - Be answerable in 5-10 minutes
+- Follow standard {level} exam format and conventions
 
-Return ONLY valid JSON with exactly these keys (no markdown formatting):
-{{"question": "the complete question text", "expectedAnswer": "detailed description of what a good answer should include", "markScheme": "clear marking criteria with point allocations"}}"""
+Return ONLY valid JSON with exactly these keys (no markdown formatting, no extra text):
+{{"question": "the complete question text with all instructions", "expectedAnswer": "detailed description of what a good answer should include and key points to cover", "markScheme": "clear marking criteria with point allocations (e.g., 2 marks for..., 3 marks for...)"}}"""
     
-    txt = call_model([{"role": "user", "content": prompt}], system, max_tokens=1000)
+    txt = call_model([{"role": "user", "content": prompt}], system, max_tokens=1200)
     try:
         # Clean up potential markdown formatting
         clean_txt = txt.replace("```json", "").replace("```", "").strip()
@@ -162,8 +181,8 @@ def check_answer(question, expected, user_answer, subject, level):
     if not user_answer.strip():
         return "Write your answer first!"
     
-    system = f"You are a {level} {subject} examiner. Provide constructive, detailed feedback."
-    prompt = f"""Evaluate this student's answer:
+    system = f"You are a {level} {subject} examiner with expertise in providing constructive, detailed feedback that helps students improve. Be fair, encouraging, and specific."
+    prompt = f"""Evaluate this student's answer professionally and constructively:
 
 Question: {question}
 
@@ -172,22 +191,29 @@ Expected answer criteria: {expected}
 Student's answer:
 {user_answer}
 
-Provide a detailed evaluation in JSON format (no markdown):
-{{"isCorrect": true/false, "score": 0-100, "feedback": "detailed feedback on what was done well", "improvements": "specific suggestions for improvement", "strengths": "what the student did correctly"}}"""
+Provide a comprehensive evaluation considering:
+- Accuracy and completeness
+- Use of appropriate terminology
+- Structure and clarity
+- Relevance to the question
+- Grammar and language quality (for language subjects)
+
+Return your evaluation in JSON format (no markdown):
+{{"isCorrect": true/false, "score": 0-100, "feedback": "detailed feedback on what was done well and what could be improved", "improvements": "specific, actionable suggestions for how to improve this answer", "strengths": "highlight what the student did correctly and well"}}"""
     
-    txt = call_model([{"role": "user", "content": prompt}], system, max_tokens=800)
+    txt = call_model([{"role": "user", "content": prompt}], system, max_tokens=1000)
     try:
         clean_txt = txt.replace("```json", "").replace("```", "").strip()
         fb = json.loads(clean_txt)
         return f"""✅ Score: {fb['score']}%
 
-📝 Feedback:
+📝 Detailed Feedback:
 {fb['feedback']}
 
-💪 Strengths:
+💪 Your Strengths:
 {fb.get('strengths', 'Good effort!')}
 
-🎯 Areas for Improvement:
+🎯 How to Improve:
 {fb['improvements']}"""
     except Exception:
         return txt
@@ -195,12 +221,12 @@ Provide a detailed evaluation in JSON format (no markdown):
 # ---------- 10. Admin – Past Papers ----------
 def verify_admin_password(password):
     if password == ADMIN_PASSWORD:
-        return gr.update(visible=True), gr.update(visible=False), "✅ Access granted!"
-    return gr.update(visible=False), gr.update(visible=True), "❌ Incorrect password!"
+        return gr.update(visible=True), gr.update(visible=False), "✅ Access granted! Welcome, Admin."
+    return gr.update(visible=False), gr.update(visible=True), "❌ Incorrect password. Please try again."
 
 def upload_paper(title, subject, level, content, pdf_file):
     if not all([title, subject, level, content]):
-        return "❌ Fill all required fields!", get_papers_list()
+        return "❌ Please fill all required fields!", get_papers_list()
     
     paper_id = len(papers_storage) + 1
     
@@ -210,7 +236,9 @@ def upload_paper(title, subject, level, content, pdf_file):
         pdf_text = extract_text_from_pdf(pdf_file)
         if pdf_text and not pdf_text.startswith("Error"):
             pdf_content_storage[paper_id] = pdf_text
-            content += f"\n\n[📄 PDF content extracted: {len(pdf_text)} characters]"
+            content += f"\n\n[📄 PDF content extracted successfully: {len(pdf_text)} characters]"
+        else:
+            content += f"\n\n[⚠️ PDF upload issue: {pdf_text}]"
     
     papers_storage.append({
         "id": paper_id,
@@ -221,13 +249,13 @@ def upload_paper(title, subject, level, content, pdf_file):
         "has_pdf": bool(pdf_text and not pdf_text.startswith("Error")),
         "uploaded_at": datetime.now().strftime("%Y-%m-%d %H:%M")
     })
-    return "✅ Uploaded successfully!", get_papers_list()
+    return "✅ Paper uploaded successfully!", get_papers_list()
 
 def get_papers_list():
     if not papers_storage:
-        return "No papers yet."
+        return "No papers uploaded yet. Upload your first past paper to get started!"
     return "\n".join(
-        f"**{p['title']}** ({p['subject'].upper()} - {p['level']}) {'📄 PDF' if p.get('has_pdf') else ''}\n📅 {p['uploaded_at']}\n{p['content'][:120]}...\n{'─'*60}"
+        f"**{p['title']}** ({p['subject'].upper()} - {p['level']}) {'📄 PDF Available' if p.get('has_pdf') else '📝 Text Only'}\n📅 Uploaded: {p['uploaded_at']}\n📖 {p['content'][:120]}...\n{'─'*60}"
         for p in papers_storage
     )
 
@@ -235,18 +263,18 @@ def view_papers_student(subject, level):
     filtered = [p for p in papers_storage 
                 if p["subject"] == subject.lower() and p["level"] == level]
     if not filtered:
-        return f"No {subject} {level} papers available yet."
+        return f"📭 No {subject} {level} papers available yet.\n\nCheck back later or ask your teacher to upload some past papers!"
     return "\n".join(
-        f"**{p['title']}** {'📄 Has PDF reference material' if p.get('has_pdf') else ''}\n{p['content']}\n{'═'*60}"
+        f"**{p['title']}** {'📄 Includes PDF reference material' if p.get('has_pdf') else ''}\n📅 {p['uploaded_at']}\n\n{p['content']}\n\n{'═'*60}"
         for p in filtered
     )
 
 # ---------- 11. Gradio UI ----------
 with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
     gr.Markdown("""
-    # 🎓 IGCSE/GCSE Language Platform
-    ### Powered by DeepSeek AI - Advanced Language Learning Assistant
-    Free AI Tutor, Translator, Dictionary & Past Papers with PDF Support
+    # 🎓 IGCSE/GCSE Language Learning Platform
+    ### Powered by MiniMax-M2 AI - Your Personal Language Tutor
+    🌟 Free AI Tutor | 🔄 Translator | 📖 Dictionary | 📚 Past Papers with PDF Support
     """)
 
     with gr.Tabs():
@@ -254,7 +282,7 @@ with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
         with gr.Tab("📚 Student Portal"):
             with gr.Tabs():
                 with gr.Tab("🤖 AI Tutor"):
-                    gr.Markdown("### Chat with your AI tutor - Get personalized help!")
+                    gr.Markdown("### Chat with Your AI Tutor\n*Get personalized help, explanations, and guidance for your studies*")
                     with gr.Row():
                         subj = gr.Radio(["French", "EFL"], label="Subject", value="French")
                         lvl = gr.Radio(["IGCSE", "GCSE"], label="Level", value="IGCSE")
@@ -264,77 +292,93 @@ with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
                         return gr.Dropdown(choices=french_topics if s == "French" else efl_topics, value=None)
                     subj.change(upd_topics, subj, topc)
 
-                    chat = gr.Chatbot(height=450, show_label=False)
-                    txt = gr.Textbox(placeholder="Ask anything about your studies...", label="Message", scale=4)
+                    chat = gr.Chatbot(height=450, show_label=False, avatar_images=(None, "🤖"))
+                    txt = gr.Textbox(placeholder="Ask me anything about your studies... e.g., 'Explain the passé composé' or 'Help me with essay writing'", label="Your Message", scale=4)
                     with gr.Row():
                         send = gr.Button("Send 📤", variant="primary")
-                        clr = gr.Button("Clear 🗑️")
+                        clr = gr.Button("Clear Chat 🗑️")
                     send.click(ai_tutor_chat, [txt, chat, subj, topc, lvl], chat)
                     txt.submit(ai_tutor_chat, [txt, chat, subj, topc, lvl], chat)
                     clr.click(clear_chat, outputs=chat)
 
                 with gr.Tab("🔄 Translator"):
-                    gr.Markdown("### Accurate English ⟷ French Translation")
-                    dir_ = gr.Radio(["English → French", "French → English"], label="Direction", value="English → French")
-                    inp = gr.Textbox(lines=5, label="Input Text", placeholder="Enter text to translate...")
-                    out = gr.Textbox(lines=5, label="Translation")
-                    gr.Button("Translate 🔄", variant="primary").click(translate_text, [inp, dir_], out)
+                    gr.Markdown("### Professional English ⟷ French Translation\n*Accurate, natural translations powered by AI*")
+                    dir_ = gr.Radio(["English → French", "French → English"], label="Translation Direction", value="English → French")
+                    inp = gr.Textbox(lines=6, label="Input Text", placeholder="Enter the text you want to translate...")
+                    out = gr.Textbox(lines=6, label="Translation Result")
+                    gr.Button("Translate 🔄", variant="primary", size="lg").click(translate_text, [inp, dir_], out)
 
                 with gr.Tab("📖 Dictionary"):
-                    gr.Markdown("### French Dictionary Lookup")
-                    w = gr.Textbox(placeholder="Enter a French word...", label="Word")
-                    o = gr.Textbox(lines=15, label="Definition & Examples")
-                    gr.Button("Lookup 🔍", variant="primary").click(dictionary_lookup, w, o)
-
-                with gr.Tab("✍️ Practice"):
-                    gr.Markdown("### Generate Exam-Style Questions\n*Questions are generated based on uploaded past papers for authenticity*")
+                    gr.Markdown("### Comprehensive French Dictionary\n*Detailed definitions, examples, and usage notes*")
+                    w = gr.Textbox(placeholder="Enter a French word to look up...", label="French Word")
+                    o = gr.Textbox(lines=16, label="Dictionary Entry")
+                    gr.Button("Look Up 🔍", variant="primary", size="lg").click(dictionary_lookup, w, o)
+
+                with gr.Tab("✍️ Practice Questions"):
+                    gr.Markdown("""### Generate & Practice Exam Questions
+                    *AI-generated questions based on uploaded past papers for authentic exam preparation*
+                    """)
                     with gr.Row():
                         ps = gr.Radio(["French", "EFL"], label="Subject", value="French")
                         pl = gr.Radio(["IGCSE", "GCSE"], label="Level", value="IGCSE")
-                        pt = gr.Dropdown(french_topics, label="Topic")
+                        pt = gr.Dropdown(french_topics, label="Select Topic", interactive=True)
                     ps.change(upd_topics, ps, pt)
 
-                    q = gr.Textbox(label="📝 Question", lines=4)
-                    exp = gr.Textbox(label="Expected Answer (Hidden)", lines=2, visible=False)
-                    mark = gr.Textbox(label="📊 Mark Scheme", lines=3)
-                    ans = gr.Textbox(lines=6, label="✍️ Your Answer", placeholder="Type your answer here...")
-                    fb = gr.Textbox(lines=10, label="📋 Detailed Feedback")
+                    gr.Markdown("---")
+                    q = gr.Textbox(label="📝 Exam Question", lines=5, interactive=False)
+                    exp = gr.Textbox(label="Expected Answer (Hidden from student)", lines=2, visible=False)
+                    mark = gr.Textbox(label="📊 Mark Scheme", lines=3, interactive=False)
+                    
+                    gr.Markdown("**Your Answer:**")
+                    ans = gr.Textbox(lines=8, label="Type your answer here", placeholder="Write your complete answer to the question above...")
+                    fb = gr.Textbox(lines=12, label="📋 Detailed Feedback & Score", interactive=False)
 
                     with gr.Row():
-                        gr.Button("Generate Question 🎲", variant="primary").click(generate_question, [ps, pt, pl], [q, exp, mark])
-                        gr.Button("Check Answer ✅", variant="secondary").click(check_answer, [q, exp, ans, ps, pl], fb)
-
-                with gr.Tab("📄 Past Papers"):
-                    gr.Markdown("### View Past Papers & Reference Materials")
+                        gen_btn = gr.Button("🎲 Generate New Question", variant="primary", size="lg")
+                        check_btn = gr.Button("✅ Check My Answer", variant="secondary", size="lg")
+                    
+                    gen_btn.click(generate_question, [ps, pt, pl], [q, exp, mark])
+                    check_btn.click(check_answer, [q, exp, ans, ps, pl], fb)
+
+                with gr.Tab("📄 Past Papers Library"):
+                    gr.Markdown("""### Access Past Papers & Reference Materials
+                    *Browse uploaded past papers organized by subject and level*
+                    """)
                     with gr.Row():
                         psb = gr.Radio(["French", "EFL"], label="Subject", value="French")
                         plb = gr.Radio(["IGCSE", "GCSE"], label="Level", value="IGCSE")
-                    pd = gr.Textbox(lines=20, label="Available Papers", show_label=False)
-                    gr.Button("Show Papers 📚", variant="primary").click(view_papers_student, [psb, plb], pd)
+                    pd = gr.Textbox(lines=22, label="Available Papers", show_label=False, interactive=False)
+                    gr.Button("📚 Show Papers", variant="primary", size="lg").click(view_papers_student, [psb, plb], pd)
 
         # ───── ADMIN ─────
         with gr.Tab("🔐 Admin Panel"):
             with gr.Column() as login_section:
-                gr.Markdown("### 🔒 Admin Login Required")
-                pwd = gr.Textbox(label="Password", type="password", placeholder="Enter admin password")
-                login_btn = gr.Button("Login 🔓", variant="primary")
-                login_status = gr.Textbox(label="Status", interactive=False)
+                gr.Markdown("""### 🔒 Admin Access Required
+                This section is for teachers and administrators only.
+                """)
+                pwd = gr.Textbox(label="Admin Password", type="password", placeholder="Enter admin password")
+                login_btn = gr.Button("🔓 Login", variant="primary", size="lg")
+                login_status = gr.Textbox(label="Login Status", interactive=False)
             
             with gr.Column(visible=False) as admin_section:
-                gr.Markdown("### 📤 Upload Past Papers (with optional PDF)")
+                gr.Markdown("""### 📤 Upload Past Papers
+                Upload past examination papers to help students practice with authentic materials.
+                PDF files will be automatically processed to generate exam-style questions.
+                """)
                 with gr.Row():
                     with gr.Column():
-                        t = gr.Textbox(label="Title", placeholder="e.g., Paper 1 Reading - June 2023")
+                        t = gr.Textbox(label="Paper Title", placeholder="e.g., IGCSE French Paper 1 Reading - June 2023")
                         with gr.Row():
                             s = gr.Radio(["French", "EFL"], label="Subject", value="French")
                             lv = gr.Radio(["IGCSE", "GCSE"], label="Level", value="IGCSE")
-                        c = gr.Textbox(lines=5, label="Description/Notes")
-                        pdf = gr.File(label="📎 Upload PDF (optional)", file_types=[".pdf"])
-                        gr.Markdown("*📄 PDF content will be extracted and used to generate authentic exam-style questions*")
-                        up = gr.Button("Upload 📤", variant="primary")
-                        st = gr.Textbox(label="Status")
+                        c = gr.Textbox(lines=6, label="Description/Notes", placeholder="Add any relevant notes about this paper...")
+                        pdf = gr.File(label="📎 Upload PDF File (Optional)", file_types=[".pdf"])
+                        gr.Markdown("*💡 Tip: Upload PDF files for better question generation. The AI will analyze the PDF content.*")
+                        up = gr.Button("📤 Upload Paper", variant="primary", size="lg")
+                        st = gr.Textbox(label="Upload Status")
                     with gr.Column():
-                        lst = gr.Textbox(lines=22, label="📚 All Uploaded Papers", value=get_papers_list())
+                        gr.Markdown("**📚 All Uploaded Papers:**")
+                        lst = gr.Textbox(lines=24, label="Papers Database", value=get_papers_list(), interactive=False)
                 up.click(upload_paper, [t, s, lv, c, pdf], [st, lst])
             
             login_btn.click(
@@ -345,23 +389,32 @@ with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
 
     gr.Markdown("""
     ---
-    ### 🚀 How to Deploy on Hugging Face Spaces:
-    1. **Fork/Create** this Space
-    2. **Settings** → **Secrets** → Add `HF_TOKEN` (your Hugging Face token)
-    3. Upload `requirements.txt` with: `gradio`, `huggingface_hub`, `PyPDF2`
-    4. **Restart** the Space → You're live! 🎉
+    ### 🚀 Deployment Guide for Hugging Face Spaces:
+    
+    **Quick Setup:**
+    1. **Create/Fork** this Space on Hugging Face
+    2. **Settings** → **Repository Secrets** → Add `HF_TOKEN` (Get token from [HF Settings](https://huggingface.co/settings/tokens))
+    3. Upload `requirements.txt` containing: `gradio`, `huggingface_hub`, `PyPDF2`
+    4. **Restart** the Space → Your platform is live! 🎉
+    
+    ### ✨ Platform Features:
+    | Feature | Description |
+    |---------|-------------|
+    | 🎓 **Dual Certification** | Supports both IGCSE and GCSE levels |
+    | 🤖 **AI Tutor** | Powered by MiniMax-M2 for intelligent tutoring |
+    | 📄 **PDF Processing** | Upload PDFs for authentic question generation |
+    | 🔄 **Smart Fallback** | Automatic backup to DeepSeek V3.2 if needed |
+    | ✍️ **Practice Mode** | AI-generated questions with detailed feedback |
+    | 🔐 **Secure Admin** | Password-protected content management |
+    | 🆓 **100% Free** | No API costs, runs on HF Spaces |
     
-    ### ✨ Key Features:
-    - ✅ **IGCSE & GCSE** support for both levels
-    - ✅ **PDF Upload** for authentic past papers
-    - ✅ **AI-Powered** question generation using DeepSeek V3.2
-    - ✅ **Intelligent Feedback** on practice answers
-    - ✅ **Password Protection** for admin panel
-    - ✅ **Translator & Dictionary** tools included
+    **Admin Credentials:** Password = `@mikaelJ46`
     
-    **Admin Password:** `@mikaelJ46`
+    **Models Used:**
+    - **Primary:** MiniMax-M2 (Latest multilingual model)
+    - **Backup:** DeepSeek V3.2 Exp (Automatic fallback)
     
-    *Powered by DeepSeek V3.2 Exp via Hugging Face Inference API*
+    *Built with ❤️ for language learners everywhere*
     """)
 
 app.launch()