Update app.py

app.py

@@ -3,21 +3,19 @@ import os
 import streamlit as st
 import pandas as pd
 import openpyxl
-import io
 import torch
 from reportlab.lib.pagesizes import letter
 from reportlab.pdfgen import canvas
 from huggingface_hub import InferenceClient
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 
-# Load API key securely
-with open("secrets.json", "r") as file:
-    secrets = json.load(file)
-HF_API_KEY = secrets["HF_API_KEY"]
+# ✅ Load API Key Securely from Hugging Face Secrets
+HF_API_KEY = os.getenv("HF_API_KEY")
 
+# ✅ Initialize Hugging Face API Client
 client = InferenceClient(api_token=HF_API_KEY)
 
-# Load Local Model with Device Optimization
+# ✅ Load Local Model with Device Optimization
 MODEL_NAME = "mistralai/Mistral-7B-Instruct-v0.3"
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -25,67 +23,50 @@ tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(device)
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if device == "cuda" else -1)
 
-# Initialize session state for uploaded files
-if "uploaded_files" not in st.session_state:
-    st.session_state.uploaded_files = {}
-
-# Streamlit UI Setup
+# ✅ Streamlit UI Setup
 st.set_page_config(page_title="AI-Powered Timetable", layout="wide")
 st.markdown("<h1 style='text-align: center; color: #4CAF50;'>📅 AI-Powered Timetable</h1>", unsafe_allow_html=True)
 
-# File Upload Section
+# ✅ File Upload Section
 st.sidebar.markdown("## 📂 Upload Your Timetable Files")
 uploaded_master = st.sidebar.file_uploader("Upload Master Timetable", type=["xlsx"])
 uploaded_lab = st.sidebar.file_uploader("Upload Lab Timetable", type=["xlsx"])
 uploaded_classroom = st.sidebar.file_uploader("Upload Classroom Timetable", type=["xlsx"])
 uploaded_individual = st.sidebar.file_uploader("Upload Individual Timetable", type=["xlsx"])
 
-# Save uploaded files locally
-if uploaded_master:
-    st.session_state.uploaded_files["Master Timetable"] = uploaded_master
-if uploaded_lab:
-    st.session_state.uploaded_files["Lab Timetable"] = uploaded_lab
-if uploaded_classroom:
-    st.session_state.uploaded_files["Classroom Timetable"] = uploaded_classroom
-if uploaded_individual:
-    st.session_state.uploaded_files["Individual Timetable"] = uploaded_individual
-
-# Define paths for uploaded files
-TIMETABLE_FILES = {name: file for name, file in st.session_state.uploaded_files.items()}
-
-# Load Timetable Data
-def load_timetable(sheet_name):
-    if sheet_name not in TIMETABLE_FILES:
+uploaded_files = {
+    "Master Timetable": uploaded_master,
+    "Lab Timetable": uploaded_lab,
+    "Classroom Timetable": uploaded_classroom,
+    "Individual Timetable": uploaded_individual,
+}
+
+# ✅ Load Timetable Data (Directly from Uploaded File)
+def load_timetable(file):
+    if not file:
         return None
-    file = TIMETABLE_FILES[sheet_name]
     wb = openpyxl.load_workbook(file)
     sheet = wb.active
     return [row for row in sheet.iter_rows(values_only=True)]
 
-# Ask Mistral AI a question using API
+# ✅ Ask Mistral AI via API
 def ask_mistral_api(query):
     response = client.text_generation(model=MODEL_NAME, inputs=query, max_new_tokens=500)
     return response
 
-# Ask Mistral AI a question using local model
+# ✅ Ask Mistral AI Locally
 def ask_mistral_local(query):
     inputs = tokenizer(query, return_tensors="pt").to(device)
     outputs = model.generate(**inputs, max_new_tokens=200)
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
-# Auto-Schedule Missing Slots
-def auto_schedule(sheet_name):
-    if sheet_name not in TIMETABLE_FILES:
+# ✅ Auto-Schedule Missing Slots
+def auto_schedule(file):
+    if not file:
         return "No timetable uploaded."
 
-    file = TIMETABLE_FILES[sheet_name]
-    local_path = f"temp_{sheet_name.replace(' ', '_')}.xlsx"
-    
-    with open(local_path, "wb") as f:
-        f.write(file.getbuffer())
-
-    wb = openpyxl.load_workbook(local_path)
+    wb = openpyxl.load_workbook(file)
     sheet = wb.active
 
     empty_slots = []
@@ -99,17 +80,14 @@ def auto_schedule(sheet_name):
 
         try:
             subject, faculty = suggestion.split(", Faculty: ")
-            subject = subject.replace("Subject: ", "").strip()
-            faculty = faculty.strip()
-            sheet.cell(row=row_idx, column=4, value=subject)
-            sheet.cell(row=row_idx, column=5, value=faculty)
+            sheet.cell(row=row_idx, column=4, value=subject.strip())
+            sheet.cell(row=row_idx, column=5, value=faculty.strip())
         except:
             continue  
 
-    wb.save(local_path)
     return f"Auto-scheduling completed for {len(empty_slots)} slots."
 
-# AI Query Section
+# ✅ AI Query Section
 st.markdown("## 🤖 Ask Mistral AI About Your Timetable")
 user_query = st.text_input("Type your question here (e.g., 'Who is free at 10 AM on Monday?')")
 
@@ -120,5 +98,3 @@ if st.button("Ask AI via API"):
 if st.button("Ask AI via Local Model"):
     ai_response = ask_mistral_local(user_query)
     st.write("🧠 **Mistral AI Suggests:**", ai_response)
-
-# 🚀 Now Your App is Fully Functional & Optimized! 🚀