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https://github.com/togethercomputer/llamaindex-chatbot
A RAG Chatbot with Next.js, Together.ai and Llama Index
https://github.com/togethercomputer/llamaindex-chatbot
Last synced: about 1 month ago
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A RAG Chatbot with Next.js, Together.ai and Llama Index
- Host: GitHub
- URL: https://github.com/togethercomputer/llamaindex-chatbot
- Owner: togethercomputer
- Created: 2024-01-25T07:18:57.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-10-17T22:28:29.000Z (about 2 months ago)
- Last Synced: 2024-10-28T21:37:21.817Z (about 1 month ago)
- Language: TypeScript
- Size: 399 KB
- Stars: 54
- Watchers: 3
- Forks: 12
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome - togethercomputer/llamaindex-chatbot - A RAG Chatbot with Next.js, Together.ai and Llama Index (TypeScript)
README
# Open source AI RAG Chatbot
This is a [LlamaIndex](https://www.llamaindex.ai/) and [Together.ai](https://www.together.ai/) RAG chatbot using [Next.js](https://nextjs.org/) bootstrapped with [`create-llama`](https://github.com/run-llama/LlamaIndexTS/tree/main/packages/create-llama).
It's powered by Llama Index, Mixtral (through Together AI Inference) and Together Embeddings. It'll embed the PDF file in `data`, generate embeddings stored locally, then give you a RAG chatbot to ask questions to.
## Getting Started
Copy your `.example.env` file into a `.env` and replace the TOGETHER_API_KEY with your API key from [together.ai](https://www.together.ai).
1. Install the dependencies.
```
npm install
```
2. Generate the embeddings and store them locally in the `cache` folder. You can also provide a PDF in the `data` folder instead of the default one.
```
npm run generate
```
3. Run the app and send messages to your chatbot. It will use context from the embeddings to answer questions.
```
npm run dev
```
## Common Issues
- Ensure your environment file is called `.env`
- Specify a dummy `OPENAI_API_KEY` value in this `.env` to make sure it works (temporary hack, Llama index is patching this)
## Learn More
To learn more about LlamaIndex and Together AI, take a look at the following resources:
- [Together AI Documentation](https://docs.together.ai/docs) - learn about Together.ai (inference, finetuning, embeddings)
- [LlamaIndex Documentation](https://docs.llamaindex.ai) - learn about LlamaIndex (Python features).
- [LlamaIndexTS Documentation](https://ts.llamaindex.ai) - learn about LlamaIndex (Typescript features).