Update app.py

app.py

@@ -1,6 +1,6 @@
 # --------------------------------------------------------------
-# IGCSE/GCSE Language Platform – Multi-AI System (Gemini + Cohere + Z.ai + MiniMax)
-# Models: Gemini 2.5 (Primary) → Cohere → Z.ai → MiniMax (Fallbacks)
+# IGCSE/GCSE Language Platform – Multi-AI System (Z.ai + Gemini + Cohere + MiniMax)
+# Models: Z.ai (Primary) → Gemini → Cohere → MiniMax (Fallbacks)
 # --------------------------------------------------------------
 
 import os
@@ -11,39 +11,37 @@ import PyPDF2
 import time
 
 # ---------- 1. Configure ALL AI Systems ----------
-# Gemini (Primary)
+# Z.ai (Primary) - Using Z.ai SDK
+try:
+    import zai
+    zai_client = zai.Client(api_key=os.getenv("ZAI_API_KEY"))
+    print("✅ Z.ai SDK initialized successfully (PRIMARY)")
+except Exception as e:
+    print(f"❌ Error initializing Z.ai SDK: {e}")
+    zai_client = None
+
+# Gemini (Secondary)
 try:
     import google.generativeai as genai
     genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
     gemini_model = genai.GenerativeModel('gemini-2.5-pro')
-    print("✅ Gemini AI initialized successfully (PRIMARY)")
+    print("✅ Gemini AI initialized successfully (SECONDARY)")
 except Exception as e:
     print(f"❌ Error initializing Gemini: {e}")
     gemini_model = None
 
-# Cohere (Secondary)
+# Cohere (Tertiary)
 try:
     import cohere
     cohere_client = cohere.Client(os.getenv("COHERE_API_KEY"))
-    print("✅ Cohere initialized successfully (SECONDARY)")
+    print("✅ Cohere initialized successfully (TERTIARY)")
 except Exception as e:
     print(f"❌ Error initializing Cohere: {e}")
     cohere_client = None
 
-# Z.ai (Tertiary)
-try:
-    from huggingface_hub import InferenceClient
-    zai_client = InferenceClient(
-        provider="novita",
-        api_key=os.environ.get("HF_TOKEN"),
-    )
-    print("✅ Z.ai GLM-4.6 initialized successfully (TERTIARY)")
-except Exception as e:
-    print(f"❌ Error initializing Z.ai: {e}")
-    zai_client = None
-
 # MiniMax (Final Fallback)
 try:
+    from huggingface_hub import InferenceClient
     minimax_client = InferenceClient(
         provider="novita",
         api_key=os.environ.get("HF_TOKEN"),
@@ -56,12 +54,28 @@ except Exception as e:
 # ---------- 2. Unified AI Function with Smart Fallback ----------
 def ask_ai(prompt, temperature=0.7, max_retries=2):
     """
-    Try models in order: Gemini → Cohere → Z.ai → MiniMax
+    Try models in order: Z.ai → Gemini → Cohere → MiniMax
     Returns: (response_text, source_name)
     """
     last_error = None
     
-    # Try Gemini first (Primary)
+    # Try Z.ai first (Primary) - Using Z.ai SDK
+    if zai_client:
+        for attempt in range(max_retries):
+            try:
+                response = zai_client.chat.completions.create(
+                    model="glm-4.6",  # Replace with actual model name
+                    messages=[{"role": "user", "content": prompt}],
+                    temperature=temperature
+                )
+                return response.choices[0].message.content, "zai"
+            except Exception as e:
+                last_error = e
+                print(f"⚠ Z.ai attempt {attempt+1} failed: {str(e)}")
+                if attempt < max_retries - 1:
+                    time.sleep(1)
+    
+    # Try Gemini (Secondary)
     if gemini_model:
         for attempt in range(max_retries):
             try:
@@ -78,7 +92,7 @@ def ask_ai(prompt, temperature=0.7, max_retries=2):
                 if attempt < max_retries - 1:
                     time.sleep(1)
     
-    # Try Cohere (Secondary)
+    # Try Cohere (Tertiary)
     if cohere_client:
         for attempt in range(max_retries):
             try:
@@ -94,22 +108,6 @@ def ask_ai(prompt, temperature=0.7, max_retries=2):
                 if attempt < max_retries - 1:
                     time.sleep(1)
     
-    # Try Z.ai (Tertiary)
-    if zai_client:
-        for attempt in range(max_retries):
-            try:
-                completion = zai_client.chat.completions.create(
-                    model="zai-org/GLM-4.6",
-                    messages=[{"role": "user", "content": prompt}],
-                    temperature=temperature
-                )
-                return completion.choices[0].message.content, "zai"
-            except Exception as e:
-                last_error = e
-                print(f"⚠ Z.ai attempt {attempt+1} failed: {str(e)}")
-                if attempt < max_retries - 1:
-                    time.sleep(1)
-    
     # Try MiniMax (Final Fallback)
     if minimax_client:
         try:
@@ -166,7 +164,7 @@ def extract_text_from_pdf(pdf_file):
     except Exception as e:
         return f"Error extracting PDF: {e}"
 
-# ---------- 6. AI Tutor with Multi-Model Support (FIXED) ----------
+# ---------- 6. AI Tutor with Multi-Model Support ----------
 def ai_tutor_chat(message, history, subject, topic, level):
     if not message.strip():
         return history
@@ -183,8 +181,8 @@ Use a friendly, supportive tone to help students learn effectively."""
         if user_msg:
             conversation += f"Student: {user_msg}\n"
         if bot_msg:
-            # FIXED: Remove emoji indicators that match what we're actually adding
-            clean_msg = bot_msg.replace("🔵 ", "").replace("🟢 ", "").replace("🟣 ", "")
+            # Remove emoji indicators that match what we're actually adding
+            clean_msg = bot_msg.replace("🔵 ", "").replace("🟢 ", "").replace("🟣 ", "").replace("🟠 ", "")
             conversation += f"Tutor: {clean_msg}\n"
     
     conversation += f"Student: {message}\nTutor:"
@@ -192,11 +190,11 @@ Use a friendly, supportive tone to help students learn effectively."""
     
     bot_response, source = ask_ai(full_prompt, temperature=0.7)
     
-    # Add source indicator if not from Gemini
-    if source == "cohere":
+    # Add source indicator if not from Z.ai
+    if source == "gemini":
         bot_response = f"🔵 {bot_response}"
-    elif source == "zai":
-        bot_response = f"🟢 {bot_response}"
+    elif source == "cohere":
+        bot_response = f"🟠 {bot_response}"
     elif source == "minimax":
         bot_response = f"🟣 {bot_response}"
     elif source == "error":
@@ -225,7 +223,7 @@ Provide only the translation without explanations:
     response, source = ask_ai(prompt, temperature=0.3)
     
     # Add subtle source indicator if not primary
-    if source in ["cohere", "zai", "minimax"]:
+    if source in ["gemini", "cohere", "minimax"]:
         response = f"{response}\n\n_[Translated using {source.title()}]_"
     
     return response
@@ -246,12 +244,59 @@ def dictionary_lookup(word):
     
     response, source = ask_ai(prompt, temperature=0.3)
     
-    if source in ["cohere", "zai", "minimax"]:
+    if source in ["gemini", "cohere", "minimax"]:
         response = f"{response}\n\n_[Dictionary powered by {source.title()}]_"
     
     return response
 
-# ---------- 9. Practice Questions (Enhanced with PDF context) ----------
+# ---------- 9. Search Past Papers for Real Questions ----------
+def search_past_papers(subject, topic, level):
+    """Search uploaded past papers for questions matching the topic"""
+    if not topic:
+        return "⚠ Select a topic first!"
+    
+    # Find matching papers
+    matching_content = []
+    for paper_id, content in pdf_content_storage.items():
+        paper = next((p for p in papers_storage if p['id'] == paper_id), None)
+        if paper and paper['subject'].lower() == subject.lower() and paper['level'] == level:
+            matching_content.append({
+                'title': paper['title'],
+                'content': content,
+                'uploaded': paper['uploaded_at']
+            })
+    
+    if not matching_content:
+        return f"📭 No past papers found for {subject} {level}.\n\nTip: Upload past papers in the Admin Panel to enable this feature."
+    
+    # Use AI to extract relevant questions from the papers
+    combined_content = "\n\n".join([f"=== {p['title']} ===\n{p['content'][:5000]}" for p in matching_content])
+    
+    prompt = f"""You are analyzing real {level} {subject} past papers to find questions about "{topic}".
+
+PAST PAPER CONTENT:
+{combined_content}
+
+TASK: Extract and return ALL questions from these papers that relate to the topic "{topic}".
+
+For each question found, provide:
+1. The complete question text (exactly as written)
+2. The paper it came from
+3. Any mark allocations mentioned
+4. Any accompanying resources/images mentioned
+
+Format your response clearly with question numbers and paper sources.
+If no questions directly match this topic, return questions from related topics and explain the connection.
+If no relevant questions exist at all, clearly state this."""
+    
+    response, source = ask_ai(prompt, temperature=0.3)
+    
+    if source in ["gemini", "cohere", "minimax"]:
+        response = f"{response}\n\n_[Search powered by {source.title()}]_"
+    
+    return response
+
+# ---------- 10. Practice Questions (Enhanced with PDF context) ----------
 def generate_question(subject, topic, level):
     if not topic:
         return "Select a topic!", "", ""
@@ -315,14 +360,14 @@ Return JSON (no markdown):
 📈 How to Improve:
 {fb['improvements']}"""
         
-        if source in ["cohere", "zai", "minimax"]:
+        if source in ["gemini", "cohere", "minimax"]:
             result += f"\n\n_[Graded by {source.title()}]_"
         
         return result
     except Exception:
         return response
 
-# ---------- 10. Admin – Past Papers ----------
+# ---------- 11. Admin – Past Papers ----------
 def verify_admin_password(password):
     if password == ADMIN_PASSWORD:
         return gr.update(visible=True), gr.update(visible=False), "✅ Access granted!"
@@ -370,12 +415,12 @@ def view_papers_student(subject, level):
         for p in filtered
     )
 
-# ---------- 11. Gradio UI ----------
+# ---------- 12. Gradio UI ----------
 with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
     gr.Markdown("""
     # 🎓 IGCSE/GCSE Language Learning Platform
     🤖 AI Tutor | 🌐 Translator | 📖 Dictionary | 📚 Past Papers
-    _Powered by Gemini AI with intelligent fallback system_
+    _Powered by Z.ai with intelligent multi-model fallback system_
     """)
 
     with gr.Tabs():
@@ -384,7 +429,7 @@ with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
             with gr.Tabs():
                 # AI TUTOR
                 with gr.Tab("🤖 AI Tutor"):
-                    gr.Markdown("### Chat with Your AI Tutor\n*Powered by Gemini 2.5 with automatic fallback*")
+                    gr.Markdown("### Chat with Your AI Tutor\n*Powered by Z.ai with automatic fallback*")
                     with gr.Row():
                         subj = gr.Radio(["French", "EFL"], label="Subject", value="French")
                         lvl = gr.Radio(["IGCSE", "GCSE"], label="Level", value="IGCSE")
@@ -474,7 +519,7 @@ with gr.Blocks(theme=gr.themes.Soft(), title="IGCSE/GCSE Platform") as app:
 
     gr.Markdown("""
     ---
-    **System Status:** 🟢 Gemini AI (Primary) | 🔵 Cohere (Secondary) | 🟢 Z.ai (Tertiary) | 🟣 MiniMax (Fallback)
+    **System Status:** 🟢 Z.ai (Primary) | 🔵 Gemini (Secondary) | 🟠 Cohere (Tertiary) | 🟣 MiniMax (Fallback)
     """)
 
 app.launch()