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| import os | |
| import openai | |
| from utils._admin_util import create_embeddings, create_vector_store, read_pdf_data, split_data | |
| import streamlit as st | |
| from dotenv import load_dotenv | |
| def validate_api_key(api_key): | |
| """Test if the API key is valid""" | |
| try: | |
| # Make a small test request to OpenAI | |
| client = openai.OpenAI(api_key=api_key) | |
| client.embeddings.create(input="test", model="text-embedding-ada-002") | |
| return True | |
| except openai.AuthenticationError: | |
| st.error("❌ Invalid API key") | |
| return False | |
| except openai.PermissionDeniedError: | |
| st.error("❌ Permission denied. Please check your API key's permissions") | |
| return False | |
| except Exception as e: | |
| st.error(f"❌ API key validation error: {str(e)}") | |
| return False | |
| def main(): | |
| load_dotenv() | |
| # Add detailed API key verification | |
| api_key = os.getenv("OPENAI_API_KEY") | |
| if not api_key: | |
| st.error("❌ OpenAI API key not found! Please ensure it's set in the environment variables.") | |
| st.info("To set up your API key:") | |
| st.code("1. Go to Hugging Face Space settings\n2. Add OPENAI_API_KEY in Repository Secrets") | |
| st.stop() | |
| # Validate the API key | |
| # if not validate_api_key(api_key): | |
| # st.stop() | |
| #print("API KEY :",api_key) | |
| st.set_page_config(page_title="Dump PDFs to QDrant - Vector Store") | |
| st.title("Please upload your files...📁 ") | |
| try: | |
| # Upload multiple PDF files | |
| uploaded_files = st.file_uploader("Upload PDF files", type=["pdf"], accept_multiple_files=True) | |
| if uploaded_files: | |
| with st.spinner('Processing PDF files...'): | |
| all_chunks = [] | |
| # Process each PDF file | |
| for pdf in uploaded_files: | |
| st.write(f"Processing: {pdf.name}") | |
| # Extract text from PDF | |
| text = read_pdf_data(pdf) | |
| st.write(f"👉 Reading {pdf.name} done") | |
| # Create chunks for this PDF | |
| chunks = split_data(text) | |
| all_chunks.extend(chunks) | |
| st.write(f"👉 Splitting {pdf.name} into chunks done") | |
| if not all_chunks: | |
| st.error("❌ No valid chunks were created from the PDFs") | |
| st.stop() | |
| st.write("Creating embeddings...") | |
| embeddings = create_embeddings() | |
| st.write("👉 Creating embeddings instance done") | |
| # Create vector store with all chunks | |
| vector_store = create_vector_store(embeddings, all_chunks) | |
| st.session_state.vector_store = vector_store | |
| st.success(f"✅ Successfully processed {len(uploaded_files)} files and pushed embeddings to Qdrant") | |
| st.write(f"Total chunks created: {len(all_chunks)}") | |
| except Exception as e: | |
| st.error(f"❌ An unexpected error occurred: {str(e)}") | |
| if __name__ == '__main__': | |
| main() | |