Upload folder using huggingface_hub

app.py

@@ -1,27 +1,5 @@
-import os
-
-# Use /tmp (always writable in Hugging Face Spaces & Docker)
-os.environ["HF_HOME"] = "/tmp/huggingface"
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/transformers"
-os.environ["HF_HUB_CACHE"] = "/tmp/hfhub"
-
-# Create directories if not exist
-os.makedirs(os.environ["HF_HOME"], exist_ok=True)
-os.makedirs(os.environ["TRANSFORMERS_CACHE"], exist_ok=True)
-os.makedirs(os.environ["HF_HUB_CACHE"], exist_ok=True)
-
-
-# Redirect Hugging Face cache to writable directory
-# os.environ["HF_HOME"] = "/app/.cache/huggingface"
-# os.environ["TRANSFORMERS_CACHE"] = "/app/.cache/transformers"
-# os.environ["HF_HUB_CACHE"] = "/app/.cache/hub"
-
-# Make sure the folders exist
-# os.makedirs(os.environ["HF_HOME"], exist_ok=True)
-# os.makedirs(os.environ["TRANSFORMERS_CACHE"], exist_ok=True)
-# os.makedirs(os.environ["HF_HUB_CACHE"], exist_ok=True)
-
 import streamlit as st
+import os
 import json
 import re
 import fitz  # PyMuPDF
@@ -49,11 +27,12 @@ summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
 
 # -------------------------
 # Extract text from PDF
-# -------------------------
+# ------------------------
+
 def extract_text_from_pdf(pdf_file):
     text = ""
-    # Save the uploaded file temporarily to process it with fitz
-    temp_file_path = "temp.pdf"
+    # ✅ Save the uploaded file into /tmp (writable in Spaces/Docker)
+    temp_file_path = os.path.join("/tmp", "temp.pdf")
     with open(temp_file_path, "wb") as f:
         f.write(pdf_file.getvalue())
 
@@ -68,6 +47,7 @@ def extract_text_from_pdf(pdf_file):
 
     return text.strip()
 
+
 # Translate text to English using Google Translate
 # -------------------------
 def translate_text_google(text):

requirements.txt

@@ -2,6 +2,6 @@ streamlit==1.43.2
 PyMuPDF==1.26.4
 langdetect==1.0.9
 googletrans==4.0.0-rc1
-transformers>=4.44.2
+transformers==4.46.3
 joblib==1.4.2
 torch==2.8.0