Update app.py

app.py

@@ -1,63 +1,75 @@
 import streamlit as st
-from transformers import pipeline
-import torch
+import requests
 
-# 1. Page Configuration for a Professional Academic Interface
-st.set_page_config(page_title="B.Sc. Math Engine V5", page_icon="📐", layout="centered")
+# 1. Page Configuration
+st.set_page_config(page_title="SAAD AI ACADEMY: Math Engine", page_icon="📐", layout="centered")
+
+# SECURE TOKEN ACCESS (This pulls from the Settings/Secrets you just saved)
+try:
+    HF_TOKEN = st.secrets["HF_TOKEN"]
+except:
+    st.error("Error: HF_TOKEN not found in Space Secrets. Please add it in Settings.")
+    st.stop()
+
+API_URL = "https://api-inference.huggingface.co/models/HuggingFaceTB/SmolLM2-1.7B-Instruct"
+headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 
 st.markdown("""
     <style>
     .stApp { background-color: #f0f2f6; }
-    .stChatMessage { border-radius: 15px; border: 1px solid #d1d5db; }
+    .stChatMessage { border-radius: 15px; border: 1px solid #d1d5db; box-shadow: 2px 2px 5px rgba(0,0,0,0.05); }
     </style>
     """, unsafe_allow_html=True)
 
-st.title("📐 B.Sc. Mathematics Engine")
-st.caption("Advanced Logic & Proof System | Optimized for SUST 3rd Year")
-
-@st.cache_resource
-def load_engine():
-    # SmolLM2-1.7B is the best logic engine for Free CPU spaces
-    model_id = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
-    return pipeline(
-        "text-generation", 
-        model=model_id, 
-        device=-1, 
-        torch_dtype=torch.float32
-    )
+st.title("📐 SAAD AI ACADEMY")
+st.caption("High-Speed Mathematics Engine | SUST Department of Mathematics")
 
-pipe = load_engine()
-
-# 2. THE LOGIC CONTROLLER (Prevents common B.Sc. Math errors)
+# 2. MASTER LOGIC PROMPT
 system_instruction = (
     "You are a Senior Mathematics Professor. You must follow a 'Verify-then-Solve' protocol.\n\n"
     "RULE 1 (DIVISIBILITY): For ax ≡ b (mod n), you MUST check if d = gcd(a, n) divides b. "
     "If it divides, divide the entire congruence by d: (a/d)x ≡ (b/d) (mod n/d) BEFORE finding the inverse.\n\n"
     "RULE 2 (GROUPS): To prove H is normal where [G:H]=2, use the fact that gH and Hg are both "
     "the complement G\\H when g is not in H. Do not assume gh=hg.\n\n"
-    "RULE 3 (REASONING): Think step-by-step. State the theorem you are using (e.g., Lagrange, Fermat, Cauchy-Riemann) "
-    "before applying it.\n\n"
+    "RULE 3 (REASONING): Think step-by-step. State the theorem you are using before applying it.\n\n"
     "RULE 4 (FORMAT): Use LaTeX ($...$ or $$...$$) for all math. Never skip algebraic steps."
 )
 
+def query_api(prompt_text):
+    full_prompt = f"<|im_start|>system\n{system_instruction}<|im_end|>\n<|im_start|>user\n{prompt_text}\nLet's think step by step.<|im_end|>\n<|im_start|>assistant\n"
+    
+    payload = {
+        "inputs": full_prompt,
+        "parameters": {
+            "max_new_tokens": 800,
+            "temperature": 0.1,
+            "return_full_text": False
+        }
+    }
+    
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
 # 3. User Interface
-user_query = st.chat_input("Enter your problem (e.g., Prove H is normal if [G:H]=2)")
+user_query = st.chat_input("Enter your problem (e.g., Solve 14x ≡ 30 mod 44)")
 
 if user_query:
     with st.chat_message("user"):
         st.write(user_query)
 
     with st.chat_message("assistant"):
-        with st.spinner("⏳ Analyzing mathematical structures and verifying logic..."):
-            # We add "Let's think step by step" to the prompt to trigger Chain-of-Thought
-            prompt = f"<|im_start|>system\n{system_instruction}<|im_end|>\n<|im_start|>user\n{user_query}\nLet's think step by step.<|im_end|>\n<|im_start|>assistant\n"
-            
-            # Increased max_new_tokens for longer, detailed proofs
-            result = pipe(prompt, max_new_tokens=900, temperature=0.1, do_sample=True, top_p=0.9)
-            response = result[0]['generated_text'].split("<|im_start|>assistant\n")[-1]
-            
-            st.markdown(response)
-            st.download_button("📩 Download Proof", response, file_name="math_solution.txt")
-
-st.sidebar.markdown("### 🎓 Academic Modules")
-st.sidebar.info("• Abstract Algebra\n• Real Analysis\n• Number Theory\n• Complex Variables")
+        with st.spinner("🚀 Cloud API is solving..."):
+            try:
+                data = query_api(user_query)
+                
+                if isinstance(data, dict) and "error" in data:
+                    st.warning("Model is starting up. Please wait 10-20 seconds and try again.")
+                else:
+                    response = data[0]['generated_text']
+                    st.markdown(response)
+                    st.download_button("📩 Download Proof", response, file_name="math_solution.txt")
+            except Exception as e:
+                st.error("Connection error. Ensure your HF_TOKEN is correctly set in Secrets.")
+
+st.sidebar.markdown(f"### 🎓 Student Profile\n**Name:** Almuyed Saad\n**Inst:** SUST\n**Major:** Mathematics")
+st.sidebar.info("Module: B.Sc. Math Engine V5 (API Edition)")