This repository contains some selected examples on building powerful chat services using QvikChat. These examples range from beginner to advanced level and cover a wide range of topics like working with chat history, response caching, RAG, and more.
All examples are present in the examples directory. Each example is a self-contained project that you can run on your local machine. These examples were built using the QvikChat Starter Template, hence they come pre-configured with support for TypeScript, ESLint, Prettier, Jest, SWC, and more.
Simply clone this repository and navigate to the example you want to run. Each example folder contains a README.md file that contains the step-by-step guide for that example.
Below is a list of currently available examples. If you wish to add a new example, please create a pull request following the guidelines in the CONTRIBUTING.md file.
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Building a simple open-ended chatbot in under 5 minutes
This example will guide you through building a simple open-ended chatbot using QvikChat. The chatbot will be able to return an LLM generated response to any user input. Good example for getting started with QvikChat.
Keywords: open ended chat, getting started, beginner
QvikChat version: 1.0.7
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Build chatbot for any webpage in under 5 minutes
Learn how to quickly build a reliable and accurate chatbot that can answer questions using data from a webpage. This example also demonstrates how to use data loaders available in LangChain to load data and use it in building a RAG-enabled chat endpoint with QvikChat.
Keywords: webpage chatbot, data loading, langchain, intermediate
QvikChat version: 1.0.9
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Build a Chatbot on Your Own Data in under 10 minutes with History, Cache, and RAG
This example will guide you through building a chatbot that can answer questions on your data, with support for continuing conversations using chat history and caching responses to frequent queries, all in under ten minutes!
Keywords: RAG, chat history, response caching, intermediate
QvikChat version: 1.0.7
QvikChat is a Firebase Genkit and LangChain based framework that provides you with a solid foundation to build powerful AI-powered chat service endpoints quickly and efficiently. It includes support for multiple types of conversations (open-ended, close-ended), chat history, response caching, authentication, and information retrieval using Retrieval Augmented Generation (RAG).
This project is licensed under the MIT License. See the LICENSE file for more details.
QvikChat is a project by Oconva. Oconva is an initiative to make conversational AI more open and accessible to all. Oconva's vision is to create a future where any developer, regardless of their available resources, can empower their apps with the power of conversational AI. Whether it's adding an AI assistant to their app or integrating a translation service, Oconva aims to provide developers with open-source tools and frameworks to support them on this journey.
