Update app.py

app.py

@@ -1,90 +1,58 @@
 import streamlit as st
-import requests
+from transformers import pipeline
+import torch
 
-# STEP 1: PAGE CONFIG
+# 1. PAGE CONFIG
 st.set_page_config(page_title="SAAD AI ACADEMY", page_icon="📐", layout="centered")
 
-# STEP 2: SECURE TOKEN ACCESS
-try:
-    HF_TOKEN = st.secrets["HF_TOKEN"]
-except:
-    st.error("Error: HF_TOKEN not found in Space Secrets.")
-    st.stop()
-
-API_URL = "https://api-inference.huggingface.co/models/HuggingFaceTB/SmolLM2-1.7B-Instruct"
-headers = {"Authorization": f"Bearer {HF_TOKEN}"}
-
-# STEP 3: UI UPGRADE (Dark/Neon Glassmorphism)
+# 2. DARK MODE UI
 st.markdown("""
     <style>
-    .stApp {
-        background: linear-gradient(135deg, #0f172a 0%, #1e293b 100%);
-        color: #ffffff;
-    }
-    .stChatMessage {
-        background: rgba(255, 255, 255, 0.05) !important;
-        backdrop-filter: blur(10px);
-        border-radius: 15px !important;
-        border: 1px solid rgba(255, 255, 255, 0.1) !important;
-        margin-bottom: 15px;
-    }
-    section[data-testid="stSidebar"] {
-        background-color: #0f172a !important;
-    }
-    h1, h2, h3, p, span {
-        color: #ffffff !important;
-    }
-    .stCaption {
-        color: #3b82f6 !important;
-    }
+    .stApp { background: linear-gradient(135deg, #0f172a 0%, #1e293b 100%); color: #ffffff; }
+    .stChatMessage { background: rgba(255, 255, 255, 0.05) !important; border-radius: 15px !important; border: 1px solid rgba(255, 255, 255, 0.1) !important; }
+    h1, h2, h3, p, span { color: #ffffff !important; }
+    .stCaption { color: #3b82f6 !important; }
     </style>
     """, unsafe_allow_html=True)
 
-# STEP 4: APP TITLES
 st.title("📐 SAAD AI ACADEMY")
-st.caption("Universal B.Sc. Mathematics Engine | SUST Department of Mathematics")
+st.caption("Stable Local Mathematics Engine | SUST Logic System")
+
+# 3. LOCAL MODEL LOADING (Slow start, but 100% stable)
+@st.cache_resource
+def load_engine():
+    # We use the same model, but load it locally to avoid API errors
+    model_id = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
+    return pipeline("text-generation", model=model_id, device=-1, torch_dtype=torch.float32)
 
-# STEP 5: UNIVERSAL LOGIC ENGINE (The New Instructions)
-# These rules apply to ANY math problem you type.
+with st.spinner("⏳ Loading Math Engine into memory... This takes 1-2 minutes on first run."):
+    pipe = load_engine()
+
+# 4. UNIVERSAL LOGIC INSTRUCTIONS
 system_instruction = (
-    "You are a Senior Mathematics Professor. You must solve every problem with absolute rigor.\n\n"
-    "RULE 1 (DEFINITION): Before solving, explicitly state the mathematical domain and the key theorem or definition involved (e.g., 'In Abstract Algebra, we use the First Isomorphism Theorem...').\n"
-    "RULE 2 (VALIDATION): Check for necessary conditions or constraints before performing operations (e.g., check if a group is finite, if a function is continuous, or if a divisor is non-zero).\n"
-    "RULE 3 (DERIVATION): Show every algebraic step clearly. Do not skip intermediate simplifications. Explain the logic of each transition.\n"
-    "RULE 4 (FORMATTING): Use LaTeX ($...$ or $$...$$) for all mathematical expressions. Use bold text for final results."
+    "You are a Senior Mathematics Professor. Solve every problem with absolute rigor.\n"
+    "1. State the mathematical domain.\n"
+    "2. Check all constraints/conditions.\n"
+    "3. Show every algebraic step using LaTeX ($...$).\n"
+    "4. Bold the final result."
 )
 
-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 derive the solution step-by-step.<|im_end|>\n<|im_start|>assistant\n"
-    payload = {
-        "inputs": full_prompt,
-        "parameters": {"max_new_tokens": 1000, "temperature": 0.1, "return_full_text": False},
-        "options": {"wait_for_model": True}
-    }
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()
-
-# STEP 6: CHAT INTERFACE
-user_query = st.chat_input("Ask a B.Sc. level math question (Analysis, Algebra, Calculus...)")
+# 5. INTERFACE
+user_query = st.chat_input("Ask a B.Sc. level math question...")
 
 if user_query:
     with st.chat_message("user"):
         st.write(user_query)
 
     with st.chat_message("assistant"):
-        with st.spinner("🚀 Cloud API is analyzing mathematical logic..."):
-            data = query_api(user_query)
-            if isinstance(data, list) and len(data) > 0:
-                response = data[0]['generated_text']
-                st.markdown(response)
-                st.download_button("📩 Download Proof", response, file_name="math_solution.txt")
-            else:
-                st.error("API error or timeout. Please check your internet or try again in 10 seconds.")
+        with st.spinner("🧠 Thinking..."):
+            prompt = f"<|im_start|>system\n{system_instruction}<|im_end|>\n<|im_start|>user\n{user_query}<|im_end|>\n<|im_start|>assistant\n"
+            result = pipe(prompt, max_new_tokens=800, temperature=0.1, do_sample=True)
+            response = result[0]['generated_text'].split("<|im_start|>assistant\n")[-1]
+            st.markdown(response)
 
-# STEP 7: SIDEBAR
+# 6. SIDEBAR
 st.sidebar.markdown(f"### 🎓 Student Profile")
 st.sidebar.write("**Name:** Almuyed Saad")
 st.sidebar.write("**Inst:** SUST")
-st.sidebar.write("**Major:** Mathematics")
-st.sidebar.divider()
-st.sidebar.info("Module: Universal Logic Engine V5.1")
+st.sidebar.write("**Major:** Mathematics")