Chat with your personal PDF docs.

Highlevel overview of this streamlit app by file.

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The main() function is responsible for handling the user interface and processing the uploaded PDF file. Here's a breakdown of the code:

1. The render_header() function is called to display the header section of the application. It includes the title, description, and an image.

2. The sidebar() function is called to display the sidebar section of the application. It includes information about HuxleyPDF, instructions on how to use it, and input fields for the OpenAI API key.

3. The setup_environment() function is called to set up the environment. Currently, it only prints a message indicating that the setup is in progress.

4. The st.file_uploader() function is used to upload a PDF file. The user is prompted to select a file with the description "Upload your PDF" and the file type filter set to "pdf".

5. The code then fetches a remote PDF file using the OnlinePDFLoader class from the Unstructured library. This is commented out for now.

6. If a PDF file is uploaded, the code extracts the text from the PDF using the PdfReader class from the PyMuPDF library.

7. The extracted text is split into chunks using the CharacterTextSplitter class from the LangChain library. The chunk size is set to 400 characters, and the overlap between chunks is set to 80 characters.

8. The OpenAIEmbeddings class is used to create embeddings for the chunks of text.

9. The FAISS.from_texts() function is used to create a FAISS index from the chunks of text and their embeddings. This is commented out for now.

10. The user is prompted to enter a question about the PDF using the st.text_input() function.

11. If a question is entered, the code retrieves the documents from the FAISS index that are most similar to the user's question using the similarity_search() method.

12. The OpenAI() class is used to create an instance of the OpenAI API.

13. The load_qa_chain() function is used to create a question-answering chain using the OpenAI API and the "stuff" chain type.

14. The get_openai_callback() context manager is used to capture the callback information from the OpenAI API.

15. The chain.run() method is used to run the question-answering chain on the input documents and the user's question. The response is printed.

16. The response is displayed using the st.write() function.

Overall, the code within the main() function handles the user interface, processes the uploaded PDF file, and performs a question-answering task using the OpenAI API and the LangChain library.

References (1)

1. huxley.py - 268-313