Update gitignore and cleanup files

.gitignore

@@ -35,6 +35,7 @@ MANIFEST
 *.zip
 *.pt 
 *.pptx 
+*.pdf
 
 
 # PyInstaller
@@ -169,3 +170,4 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+OshoBooks-all-books/

README.md.bak

@@ -0,0 +1,37 @@
+# Ask Osho - Question Answering System
+
+This is a Streamlit application that allows users to ask questions and receive answers from Osho's teachings. The application uses a vector database of Osho's books to find relevant passages and provide meaningful answers.
+
+## Features
+
+- Ask questions about Osho's teachings
+- Choose from example questions or ask your own
+- Get answers with references to specific books
+- Clean and intuitive user interface
+- Additional book recommendations for further reading
+
+## How it Works
+
+The application uses:
+- Sentence transformers for text embeddings
+- ChromaDB for vector similarity search
+- Streamlit for the user interface
+
+## Usage
+
+1. Select an example question or type your own
+2. Click "Please Answer Osho"
+3. View the answer and book references
+
+## Development
+
+To run this application locally:
+
+```bash
+pip install -r requirements.txt
+streamlit run streamlit_app.py
+```
+
+## Deployment
+
+This application is deployed on Hugging Face Spaces.

hf_login.py

@@ -0,0 +1,2 @@
+from huggingface_hub import login
+login()

upload_to_hub.py

@@ -0,0 +1,41 @@
+from huggingface_hub import HfApi, create_repo
+import os
+import shutil
+
+def upload_to_hub():
+    # Initialize the Hugging Face API
+    api = HfApi()
+    
+    # Your Hugging Face info
+    repo_id = "harithapliyal/osho-vector-db"
+    
+    # Create the dataset repository if it doesn't exist
+    try:
+        print("Creating dataset repository...")
+        create_repo(
+            repo_id=repo_id,
+            repo_type="dataset",
+            private=False
+        )
+        print("Dataset repository created successfully!")
+    except Exception as e:
+        print(f"Note: {str(e)}")
+    
+    # Local vector database path
+    local_db_path = os.path.join(os.getcwd(), "vector_db")
+    
+    print(f"Uploading vector database from {local_db_path}")
+    
+    try:
+        # Upload the entire directory
+        api.upload_folder(
+            folder_path=local_db_path,
+            repo_id=repo_id,
+            repo_type="dataset"
+        )
+        print("Successfully uploaded vector database to Hugging Face!")
+    except Exception as e:
+        print(f"Error uploading to Hugging Face: {str(e)}")
+
+if __name__ == "__main__":
+    upload_to_hub()