Copied GitHub project to Hugging Face Space

backend/api/main.py

@@ -26,7 +26,7 @@ async def root():
 @app.post("/upload/")
 async def upload_pdfs(user_id: str = Form(...), files: List[UploadFile] = File(...)):
     # Create directories for the user
-    base_dir = os.path.join("docs", user_id)
+    base_dir = os.path.join("/tmp/docs", user_id)
     pdf_dir = os.path.join(base_dir, "pdfs")
     image_dir = os.path.join(base_dir,"images")
     faiss_dir = os.path.join(base_dir, "faiss_index")

backend/models/app.py

@@ -14,7 +14,7 @@ llm = ChatGroq(model='llama-3.3-70b-versatile')
 
 #Funtion for load Vector data
 def load_user_vectorstore(user_id: str):
-    faiss_path = os.path.join("docs", user_id, "faiss_index")
+    faiss_path = os.path.join("/tmp/docs", user_id, "faiss_index")
     if not os.path.exists(faiss_path):
         raise ValueError(f"No FAISS index found for user '{user_id}'")
     

backend/models/embed.py

@@ -12,7 +12,7 @@ import pytesseract
 # Funtion for load Documents and Save it into Vector Stores
 def embed_and_store(user_id: str):
     # Setup user directories
-    base_dir = os.path.join("docs", user_id)
+    base_dir = os.path.join("/tmp/docs", user_id)
     pdf_dir = os.path.join(base_dir, "pdfs")
     image_dir = os.path.join(base_dir,"images")
     faiss_dir = os.path.join(base_dir, "faiss_index")