Update app.py

app.py

@@ -1,6 +1,6 @@
 # --------------------------------------------------------------
-# IGCSE/GCSE Language Platform – Multi-AI System (Z.ai + Cohere + MiniMax + Gemini)
-# Models: Z.ai GLM-4.6 (Primary) → Cohere → MiniMax → Gemini (Fallbacks)
+# IGCSE/GCSE Language Platform – Multi-AI System (Gemini + Cohere + Z.ai + MiniMax)
+# Models: Gemini 2.5 (Primary) → Cohere → Z.ai → MiniMax (Fallbacks)
 # --------------------------------------------------------------
 
 import os
@@ -11,69 +11,70 @@ import PyPDF2
 import time
 
 # ---------- 1. Configure ALL AI Systems ----------
-# Z.ai (Primary)
+# Gemini (Primary)
 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")
+    import google.generativeai as genai
+    genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
+    gemini_model = genai.GenerativeModel('gemini-2.5')
+    print(" Gemini AI initialized successfully (PRIMARY)")
 except Exception as e:
-    print(f" Error initializing Z.ai: {e}")
-    zai_client = None
+    print(f" Error initializing Gemini: {e}")
+    gemini_model = None
 
 # Cohere (Secondary)
 try:
     import cohere
     cohere_client = cohere.Client(os.getenv("COHERE_API_KEY"))
-    print(" Cohere initialized successfully")
+    print(" Cohere initialized successfully (SECONDARY)")
 except Exception as e:
     print(f" Error initializing Cohere: {e}")
     cohere_client = None
 
-# MiniMax (Tertiary)
+# Z.ai (Tertiary)
 try:
-    minimax_client = InferenceClient(
+    from huggingface_hub import InferenceClient
+    zai_client = InferenceClient(
         provider="novita",
         api_key=os.environ.get("HF_TOKEN"),
     )
-    print(" MiniMax AI initialized successfully")
+    print(" Z.ai GLM-4.6 initialized successfully (TERTIARY)")
 except Exception as e:
-    print(f" Error initializing MiniMax: {e}")
-    minimax_client = None
+    print(f" Error initializing Z.ai: {e}")
+    zai_client = None
 
-# Gemini (Final Fallback)
+# MiniMax (Final Fallback)
 try:
-    import google.generativeai as genai
-    genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
-    gemini_model = genai.GenerativeModel('gemini-2.5')
-    print(" Gemini AI initialized successfully")
+    minimax_client = InferenceClient(
+        provider="novita",
+        api_key=os.environ.get("HF_TOKEN"),
+    )
+    print(" MiniMax AI initialized successfully (FINAL FALLBACK)")
 except Exception as e:
-    print(f" Error initializing Gemini: {e}")
-    gemini_model = None
+    print(f" Error initializing MiniMax: {e}")
+    minimax_client = None
 
 # ---------- 2. Unified AI Function with Smart Fallback ----------
 def ask_ai(prompt, temperature=0.7, max_retries=2):
     """
-    Try models in order: Z.ai → Cohere → MiniMax → Gemini
+    Try models in order: Gemini → Cohere → Z.ai → MiniMax
     Returns: (response_text, source_name)
     """
     last_error = None
     
-    # Try Z.ai first (Primary)
-    if zai_client:
+    # Try Gemini first (Primary)
+    if gemini_model:
         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
+                response = gemini_model.generate_content(
+                    prompt,
+                    generation_config=genai.types.GenerationConfig(
+                        temperature=temperature,
+                    )
                 )
-                return completion.choices[0].message.content, "zai"
+                return response.text, "gemini"
             except Exception as e:
                 last_error = e
-                print(f" Z.ai attempt {attempt+1} failed: {str(e)}")
+                print(f" Gemini attempt {attempt+1} failed: {str(e)}")
                 if attempt < max_retries - 1:
                     time.sleep(1)
     
@@ -93,35 +94,34 @@ def ask_ai(prompt, temperature=0.7, max_retries=2):
                 if attempt < max_retries - 1:
                     time.sleep(1)
     
-    # Try MiniMax (Tertiary)
-    if minimax_client:
+    # Try Z.ai (Tertiary)
+    if zai_client:
         for attempt in range(max_retries):
             try:
-                completion = minimax_client.chat.completions.create(
-                    model="MiniMaxAI/MiniMax-M2",
+                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, "minimax"
+                return completion.choices[0].message.content, "zai"
             except Exception as e:
                 last_error = e
-                print(f" MiniMax attempt {attempt+1} failed: {str(e)}")
+                print(f" Z.ai attempt {attempt+1} failed: {str(e)}")
                 if attempt < max_retries - 1:
                     time.sleep(1)
     
-    # Try Gemini (Final Fallback)
-    if gemini_model:
+    # Try MiniMax (Final Fallback)
+    if minimax_client:
         try:
-            response = gemini_model.generate_content(
-                prompt,
-                generation_config=genai.types.GenerationConfig(
-                    temperature=temperature,
-                )
+            completion = minimax_client.chat.completions.create(
+                model="MiniMaxAI/MiniMax-M2",
+                messages=[{"role": "user", "content": prompt}],
+                temperature=temperature
             )
-            return response.text, "gemini"
+            return completion.choices[0].message.content, "minimax"
         except Exception as e:
             last_error = e
-            print(f" Gemini fallback failed: {str(e)}")
+            print(f" MiniMax fallback failed: {str(e)}")
     
     # All failed
     error_msg = f" Error: All AI services failed. Last error: {str(last_error)}"
@@ -184,7 +184,7 @@ Use a friendly, supportive tone to help students learn effectively."""
             conversation += f"Student: {user_msg}\n"
         if bot_msg:
             # Remove source indicators from history
-            clean_msg = bot_msg.replace("[Cohere] ", "").replace("[MiniMax] ", "").replace("[Gemini] ", "")
+            clean_msg = bot_msg.replace("[Cohere] ", "").replace("[Z.ai] ", "").replace("[MiniMax] ", "")
             conversation += f"Tutor: {clean_msg}\n"
     
     conversation += f"Student: {message}\nTutor:"
@@ -192,13 +192,13 @@ 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 Z.ai
+    # Add source indicator if not from Gemini
     if source == "cohere":
-        bot_response = f" {bot_response}"
+        bot_response = f"🔵 {bot_response}"
+    elif source == "zai":
+        bot_response = f"🟢 {bot_response}"
     elif source == "minimax":
-        bot_response = f" {bot_response}"
-    elif source == "gemini":
-        bot_response = f" {bot_response}"
+        bot_response = f"🟣 {bot_response}"
     elif source == "error":
         pass  # Error already formatted
     
@@ -224,8 +224,8 @@ Provide only the translation without explanations:
     
     response, source = ask_ai(prompt, temperature=0.3)
     
-    # Add subtle source indicator
-    if source in ["cohere", "minimax", "gemini"]:
+    # Add subtle source indicator if not primary
+    if source in ["cohere", "zai", "minimax"]:
         response = f"{response}\n\n_[Translated using {source.title()}]_"
     
     return response
@@ -246,7 +246,7 @@ def dictionary_lookup(word):
     
     response, source = ask_ai(prompt, temperature=0.3)
     
-    if source in ["cohere", "minimax", "gemini"]:
+    if source in ["cohere", "zai", "minimax"]:
         response = f"{response}\n\n_[Dictionary powered by {source.title()}]_"
     
     return response
@@ -315,7 +315,7 @@ Return JSON (no markdown):
  How to Improve:
 {fb['improvements']}"""
         
-        if source in ["cohere", "minimax", "gemini"]:
+        if source in ["cohere", "zai", "minimax"]:
             result += f"\n\n_[Graded by {source.title()}]_"
         
         return result
@@ -339,7 +339,7 @@ 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 extracted: {len(pdf_text)} characters]"
+            content += f"\n\n[📄 PDF extracted: {len(pdf_text)} characters]"
     
     papers_storage.append({
         "id": paper_id,
@@ -356,7 +356,7 @@ def get_papers_list():
     if not papers_storage:
         return "No papers yet."
     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' if p.get('has_pdf') else ''}\n {p['uploaded_at']}\n{p['content'][:120]}...\n{'─'*60}"
         for p in papers_storage
     )
 
@@ -374,15 +374,16 @@ def view_papers_student(subject, level):
 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
+    Justice AI Tutor |  Translator |  Dictionary |  Past Papers
+    _Powered by Gemini AI with intelligent fallback system_
     """)
 
     with gr.Tabs():
         # ───── STUDENT ─────
         with gr.Tab(" Student Portal"):
             with gr.Tabs():
-                with gr.Tab(" AI Tutor"):
-                    gr.Markdown("### Chat with Your AI Tutor\n*Powered by Z.ai with automatic fallback*")
+                with gr.Tab("Justice AI Tutor"):
+                    gr.Markdown("### Chat with Your AI Tutor\n*Powered by Gemini 2.5 with automatic fallback*")
                     with gr.Row():
                         subj = gr.Radio(["French", "EFL"], label="Subject", value="French")
                         lvl = gr.Radio(["IGCSE", "GCSE"], label="Level", value="IGCSE")