Chat with your PDF （Streamlit Demo)
Recently, many people have been discussing the use of LLMs, which can be basically divided into:
Fine-tuning (Training pretrained model, Transfer learning, etc.)
Applications based on LLMs, especially the very popular LangChain.
This time, I will provide a relatively advanced model of LangChain to communicate with a certain PDF file. I have shared the complete code here. If you want to understand the code, just go there directly. The process is explained based on Streamlit, as shown below:
Read the PDF file (in fact, any file type can be read).
Divide the content of each file into several documents.
Embed each document using OpenAI’s API (other API is also possible).
Establish a vector storage(Chroma) for these embeddings.
When posing a question, identify the most pertinent documents and forward them as context to GPT to solicit a well-constructed response.
When responding, supply the source documents utilized and the corresponding answer.
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