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README.md

@@ -1,20 +1,12 @@
 ---
-title: Textbook Complex Public
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
+title: Website Public
+emoji: ⚡
+colorFrom: pink
+colorTo: purple
+sdk: streamlit
+sdk_version: 1.43.0
+app_file: app.py
 pinned: false
-short_description: Streamlit template space
-license: mit
 ---
 
-# Welcome to Streamlit!
-
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
-
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,154 @@
+from huggingface_hub import hf_hub_download, snapshot_download, login
+import pandas as pd
+import importlib
+import importlib.util
+import streamlit as st
+import sys
+import os
+import shutil
+from pathlib import Path
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+# #___________ cache issue 03_08
+# if os.path.exists("private_space_cache"):
+#     shutil.rmtree("private_space_cache")  # Forcefully remove corrupted cache folder
+# incomplete_files = Path(".").rglob("*.incomplete")
+# for file in incomplete_files:
+#     try:
+#         file.unlink()
+#     except Exception as e:
+#         print(f"Could not delete {file}: {e}")
+# #____________________________________
+
+# HF_TOKEN_LLAMA = os.environ.get("HF_TOKEN_LLAMA")
+# login(token=HF_TOKEN_LLAMA)
+
+# HF_TOKEN = os.environ.get("HF_TOKEN") #get HF_TOKEN 
+# login(token=HF_TOKEN)
+
+
+# USER_NAME = os.getenv("USER_NAME", "").strip().strip('"')
+# PRIVATE_SPACE_NAME = os.getenv("PRIVATE_SPACE_NAME", "").strip().strip('"')
+
+# #Construct the repo ID
+# REPO_ID = f"{USER_NAME}/{PRIVATE_SPACE_NAME}"
+
+# REPO_TYPE = "space"
+
+# # sys.path.append(repo_dir)
+
+# # Download the entire space, including the fine-tuned model folder
+# repo_dir = snapshot_download(
+#     repo_id=REPO_ID,
+#     repo_type=REPO_TYPE,
+#     token=HF_TOKEN,
+#     cache_dir="private_space_cache",
+#     force_download=True  # Forces redownload
+# )
+
+
+# # Change the working directory to the downloaded snapshot directory
+# # This step is very imporptant
+# os.chdir(repo_dir)
+
+# # # Add repo directory to sys.path so Python can find modules inside it
+# sys.path.append(repo_dir)
+
+
+# # Download specific files (if snapshot_download wasn't used)
+# app_path = hf_hub_download(
+#     repo_id=REPO_ID,
+#     filename="app.py",
+#     repo_type=REPO_TYPE
+# )
+
+# # Load and execute `app.py`
+# spec_app = importlib.util.spec_from_file_location("*", app_path)
+# app_module = importlib.util.module_from_spec(spec_app)
+# spec_app.loader.exec_module(app_module)
+# # Now you can use functions from utils_module
+# result = app_module.main()
+
+
+# Set page config as the FIRST command
+st.set_page_config(page_title="📐 Math Assignment Optimizer", layout="wide")
+
+# Helper function to clean up cache
+def clear_cache(cache_dir="private_space_cache"):
+    """Remove cache directory and all .incomplete files."""
+    if os.path.exists(cache_dir):
+        shutil.rmtree(cache_dir, ignore_errors=True)
+    for file in Path(".").rglob("*.incomplete"):
+        try:
+            file.unlink()
+        except Exception as e:
+            st.warning(f"Could not delete {file}: {e}")
+
+# Get environment variables
+HF_TOKEN_LLAMA = os.environ.get("HF_TOKEN_LLAMA")
+HF_TOKEN = os.environ.get("HF_TOKEN")
+USER_NAME = os.getenv("USER_NAME", "").strip().strip('"')
+PRIVATE_SPACE_NAME = os.getenv("PRIVATE_SPACE_NAME", "").strip().strip('"')
+
+
+# Log in to Hugging Face
+login(token=HF_TOKEN_LLAMA)
+login(token=HF_TOKEN)
+
+# Construct the repo ID
+REPO_ID = f"{USER_NAME}/{PRIVATE_SPACE_NAME}"
+REPO_TYPE = "space"
+
+# Always clear cache before downloading
+with st.spinner("Clearing old cache..."):
+    clear_cache()
+
+# Download the private space
+with st.spinner("Downloading private space..."):
+    try:
+        repo_dir = snapshot_download(
+            repo_id=REPO_ID,
+            repo_type=REPO_TYPE,
+            token=HF_TOKEN,
+            cache_dir="private_space_cache",
+            force_download=True,
+            local_dir_use_symlinks=False
+        )
+    except Exception as e:
+        st.error(f"Failed to download private space: {e}")
+        st.stop()
+
+# Change working directory and update sys.path
+os.chdir(repo_dir)
+sys.path.append(repo_dir)
+
+# Download and load app.py from the private space
+try:
+    app_path = hf_hub_download(
+        repo_id=REPO_ID,
+        filename="app.py",
+        repo_type=REPO_TYPE,
+        token=HF_TOKEN,
+        force_download=True
+    )
+except Exception as e:
+    st.error(f"Failed to download app.py: {e}")
+    st.stop()
+
+# Load and execute app.py
+spec_app = importlib.util.spec_from_file_location("app_module", app_path)
+app_module = importlib.util.module_from_spec(spec_app)
+spec_app.loader.exec_module(app_module)
+
+# Run the private app's main function
+try:
+    print("Public version is running!!!!")
+    result = app_module.main()
+except Exception as e:
+    st.error(f"Error running private app: {e}")
+    st.stop()
+
+# Optional: Clean up after execution
+with st.spinner("Cleaning up..."):
+    clear_cache()

requirements.txt

@@ -1,3 +1,10 @@
-altair
+streamlit
 pandas
-streamlit
+openpyxl
+pyscipopt
+transformers>=4.30.0
+torch
+peft
+gurobipy
+matplotlib
+seaborn