Chat with Your GitHub Repository
Build a chatbot to talk to your Github repository.
Why it matters
Build a conversational interface to query and understand the content of any GitHub repository. Get instant answers and insights directly from your code and documentation.
Outcomes
What it gets done
Download and index a specified GitHub repository.
Create a chat engine that retrieves context from the indexed repository.
Provide a user-friendly Panel ChatInterface for interactive querying.
Stream answers from the chat engine directly to the user.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/li-pack-packs-panel-chatbot | bash Steps
Steps in the chain
Downloads and indexes a Github repository using the `llama_index` `GithubRepositoryReader`. The default repository is holoviz/panel.
Creates a VectorStoreIndex powered chat engine that will retrieve context from the indexed data to respond to each user query.
Creates a Panel ChatInterface UI that will stream each answer from the chat engine.
Overview
Panel ChatBot Pack
What it does
This pack builds a chatbot that allows you to interact with a GitHub repository. It leverages LlamaIndex to index the repository's content and OpenAI's ChatGPT to generate responses, all presented through a HoloViz Panel chat interface.
How it connects
Use this pack when you need to quickly create a conversational interface to query the contents of a GitHub repository. Do not use this pack if you require advanced multi-user support, custom service context configurations (like specific models or temperatures), or if you need to manage multiple repositories simultaneously, as these features are listed as potential improvements.
Source README
Description pending for li-pack-packs-panel-chatbot.
Step 1: Download and index Github repository
Downloads and indexes a Github repository using the `llama_index` `GithubRepositoryReader`. The default repository is holoviz/panel.
Step 2: Create VectorStoreIndex chat engine
Creates a VectorStoreIndex powered chat engine that will retrieve context from the indexed data to respond to each user query.
Step 3: Create Panel ChatInterface UI
Creates a Panel ChatInterface UI that will stream each answer from the chat engine.
Discussion
Questions & comments · 0
Sign In Sign in to leave a comment.