This repository contains the code and instructions needed to build a sophisticated answer engine that leverages the capabilities of Groq, Mixtral, Langchain.JS, Brave Search, and OpenAI. Designed to efficiently return sources, answers, and follow-up questions based on user queries, this project is an ideal starting point for developers interested in natural language processing and search technologies.

Watch the tutorial here for a detailed guide on setting up and running this project. The video covers every step of the process, from API key acquisition to server deployment.

• Express.js: A web application framework for Node.js, used to create server-side applications.
• Body-Parser: A middleware for Express.js, it's used to parse incoming request bodies before your handlers.
• Groq & Mixtral: Technologies for processing and understanding user queries.
• Langchain.JS: A JavaScript library focused on text operations, such as text splitting and embeddings.
• Brave Search: A privacy-focused search engine used for sourcing relevant content.
• OpenAI: Leveraged for generating coherent and contextually relevant answers and follow-up questions.
• Cheerio: Utilized for HTML parsing, allowing the extraction of content from web pages.

• Ensure Node.js and npm are installed on your machine.
• Obtain API keys from Groq, OpenAI, and Brave Search.

• Groq API Key: Get your Groq API key here.
• OpenAI API Key: Generate your OpenAI API key here.
• Brave Search API Key: Obtain your Brave Search API key here.

1. Clone the repository: git clone https://github.com/developersdigest/llm-answer-engine
2. Install the required dependencies: npm install or bun install
3. Create a .env file in the root of your project and add your API keys:

   GROQ_API_KEY=<your_groq_api_key>
   BRAVE_SEARCH_API_KEY=<your_brave_search_api_key>
   OPENAI_API_KEY=<your_openai_api_key>
   

To start the server, execute: npm start The server will be listening on port 3005.

Make a POST request to localhost:3005 with a JSON body containing your query and the desired parameters:

{
  "message": "Tell me the Anthropic's Claude 3",
  "returnSources": true,
  "returnFollowUpQuestions": true,
  "embedSourcesInLLMResponse": false,
  "textChunkSize": 800,
  "textChunkOverlap": 200,
  "numberOfSimilarityResults": 2,
  "numberOfPagesToScan": 4
}

The engine will process your query and return a comprehensive answer along with sources and, if requested, follow-up questions.

Contributions to the project are welcome. Feel free to fork the repository, make your changes, and submit a pull request. You can also open issues to suggest improvements or report bugs.

This project is licensed under the MIT License - see the LICENSE file for more details.

I'm the developer behind Developers Digest. If you find my work helpful or enjoy what I do, consider supporting me. Here are a few ways you can do that:

• Patreon: Support me on Patreon at patreon.com/DevelopersDigest
• Buy Me A Coffee: You can buy me a coffee at buymeacoffee.com/developersdigest
• Website: Check out my website at developersdigest.tech
• Github: Follow me on GitHub at github.com/developersdigest
• Twitter: Follow me on Twitter at twitter.com/dev__digest