https://github.com/badlogic/doxie

RAG/LLM info retrieval
https://github.com/badlogic/doxie

Last synced: about 1 month ago
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RAG/LLM info retrieval

• Host: GitHub
• URL: https://github.com/badlogic/doxie
• Owner: badlogic
• License: bsd-2-clause
• Created: 2024-01-04T14:39:30.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-05-14T08:21:15.000Z (about 1 month ago)
• Last Synced: 2024-05-14T09:35:28.863Z (about 1 month ago)
• Language: TypeScript
• Size: 1.08 MB
• Stars: 17
• Watchers: 2
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-stars - badlogic/doxie - RAG/LLM info retrieval (TypeScript)

README

        
# Doxie

Doxie is an experiment in LLM-based information retrieval. Or in plain words: Doxie uses ChatGPT to answer questions based on the content of one or more websites, documents, or whatever other text content you want to feed it. It exposes a simple, ChatGPT like interface.

Doxie implements the most basic RAG loop imaginable, with simple context management. Have a look at these source files:

-   Srapping and preparing data from a specific source [src/server/berufslexikon.ts](src/server/berufslexikon.ts)

-   Embedding data

    -   [src/server/embedder.ts](src/server/embedder.ts) chunking, embedding

    -   [src/server/embedder-cli.ts](src/server/embedder.ts) takes the output of the scrapper and converts it into a `xxx.embeddings.bin` file to be loaded into the vector database

-   Vector database, loads a file generated by `embedder-cli.ts` into a collection and lets you query it [src/server/rag.ts](src/server/rag.ts)

-   Chat session management, keeps track of chat sessions, expands queries for RAG, and submits user queries + RAG context to GPT 3.5-turbo to get hopefully meaningful answers with source citations. [src/server/chatsessions.ts]

To run Doxie you need the following software installed on your system:

-   [NodeJs +20](https://nodejs.org/en)

-   [Docker](https://www.docker.com/)

Doxie currently does not have a proper ingestion pipeline, and is hard coded for the test use case. This will probably, maybe amended in the coming days/weeks, depending on my mood.

If you want to play around with Doxie on some real-world data, run the `./download-testdata.sh` script in the root folder. It will download a data set with embeddings generated from [AMS Berufslexikon](https://www.berufslexikon.at/) to `./docker/data/berufslexikon.embeddings.bin`. You can then follow the instructions in the `Development` section below.

### Development

```

npm run dev

```

In VS Code run the `dev` launch configurations, which will attach the debugger to the server, spawn a browser window, and also attach to that for frontend debugging.

### Deployment

1. Deploy backend & frontend: `./publish.sh server`

1. Deploy just the frontend: `./publish.sh`