Pytorch Docs Refactored FAQs

Question 1

How does it work?

Accepted Answer

The tool leverages ChromaDB to store embeddings of PyTorch documentation. When you enter a query, it generates an embedding for your query and searches the database for semantically similar content.

Question 2

How can I use it?

Accepted Answer

You'll need an OpenAI API key. First, create the environment with `conda env create -f environment.yml` and activate with `conda activate pytorch_docs_search`. Then set your API key with `export OPENAI_API_KEY=your_key_here` and run the `scripts/search.py` script with your query.

Question 3

What are the key features?

Accepted Answer

Key features include a command-line interface, ChromaDB integration, the ability to distinguish between code and text snippets, and an interactive mode for continuous queries.

Question 4

What is PyTorch Docs Refactored?

Accepted Answer

It's a command-line tool for performing semantic searches within the PyTorch documentation, using embeddings and a vector database for efficient results.

Question 5

Is this tool actively maintained?

Accepted Answer

Currently, the project is paused for significant redesign. While the core functionality is present, substantial improvements are needed for relevance quality and other aspects.

Pytorch Docs Refactored

概要

主な機能