togethercomputer/llamaindex-chatbot
TypeScript
Captured source
source ↗togethercomputer/llamaindex-chatbot
Description: A RAG Chatbot with Next.js, Together.ai and Llama Index
Language: TypeScript
Stars: 72
Forks: 17
Open issues: 4
Created: 2024-01-25T07:18:57Z
Pushed: 2024-10-17T22:28:29Z
Default branch: main
Fork: no
Archived: no
README:
Open source AI RAG Chatbot
This is a LlamaIndex and Together.ai RAG chatbot using Next.js bootstrapped with `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.
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_KEYvalue in this.envto 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 - learn about Together.ai (inference, finetuning, embeddings)
- LlamaIndex Documentation - learn about LlamaIndex (Python features).
- LlamaIndexTS Documentation - learn about LlamaIndex (Typescript features).