A CLI Application to interact with PDF's semantically, primarily a demo app built to learn llm and embedding fundamentals.
Built with using:
Step 1. Clone the repository
git clone https://github.com/filipkujawa/pdfchat.git
Step 2. Install requirements
cd pdfchat
pip install -r requirements.txt
Step 3. Add API Key to config
Open config.ini and add an api key to the open_ai_api_key property.
You can obtain an api key here.
Step 4. Run the program
py chat.py
And follow the instructions given.
Usage: chat.py [OPTIONS]
| Options | Description |
|---|---|
--path TEXT |
Path to the pdf |
--clear_db BOOLEAN |
Clear the chroma db |
--chunk_size INTEGER |
Text splitter chunk size |
--max_tokens INTEGER |
LLM max token config |
--context_size INTEGER |
Number of documents to include in prompt context |
The default prompt is
Given the following sections from a text, answer the question using only that information.
If you are unsure and the answer is not explicitly written in the provided text,
say 'Sorry, I don't know how to help with that'. Answer in Markdown. Context sections: {docs} Question: '''{question}'''
You can edit and experiment with the prompt by changing the value of prompt in chat.py following LangChain's PromptTemplate structure.