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| import chromadb | |
| from langchain.document_loaders import PyPDFLoader | |
| from langchain.text_splitter import RecursiveCharacterTextSplitter | |
| from uuid import uuid4 | |
| import gradio as gr | |
| text_splitter = RecursiveCharacterTextSplitter( | |
| chunk_size=800, | |
| chunk_overlap=50 | |
| ) | |
| client = chromadb.PersistentClient("test") | |
| collection = client.create_collection("test_data") | |
| def upload_pdf(file_path): | |
| loader = PyPDFLoader(file_path) | |
| pages = loader.load() | |
| documents = [] | |
| for page in pages: | |
| docs = text_splitter.split_text(page.page_content) | |
| for doc in docs: | |
| documents.append({ | |
| "text": docs, "meta_data": page.metadata, | |
| }) | |
| collection.add( | |
| ids=[str(uuid4()) for _ in range(len(documents))], | |
| documents=[doc['text'][0] for doc in documents], | |
| metadatas=[doc['meta_data'] for doc in documents] | |
| ) | |
| return f"PDF Uploaded Successfully. {collection.count()} chunks stored in ChromaDB" | |
| # Define the Gradio interface | |
| iface = gr.Interface( | |
| fn=upload_pdf, | |
| inputs=["file"], # Specify a file input component | |
| outputs="textbox", # Display the output text in a textbox | |
| title="Upload PDF to ChromaDB", | |
| description="Upload a PDF file and store its text chunks in ChromaDB.", | |
| ) | |
| # Launch the Gradio app | |
| iface.launch(debug=True,share=True) |