Next.js RAG (Retrieval-Augmented Generation)
Next.js RAG is an open-source project that implements a Retrieval-Augmented Generation (RAG) feature using Next.js, Langchain, and Ollama. This project is designed to help developers integrate RAG capabilities into their Next.js applications, offering real-time, data-driven insights powered by language models.
This project is an extraction of a core feature embedded in Rebackk to enhance AI capabilities in customer interactions and security incident management. While the embedded version remains private, we are excited to offer this open-source version to help others leverage RAG in their own applications.
Features
- Retrieval-Augmented Generation: Integrates external data sources to enrich language model responses.
- Next.js-based: Fully server-side and API routes support for efficient querying and responses.
- Langchain integration: Handles retrieval and orchestration of large language models (LLMs) and external data.
- Ollama-powered: Utilizes Ollama for generating responses based on retrieved data.
- Extensible: Easily customizable and extendable to support additional data sources or LLMs.
- Open-source: Available to the developer community to build intelligent chatbots, dynamic FAQs, automated customer support, etc.
Use Cases
- Customer Support: Build an intelligent FAQ or support system to answer customer queries based on real-time data.
- Knowledge Base: Provide accurate, up-to-date information from a dynamic knowledge base, including documentation or stored articles.
- Security Incident Management: Use RAG to manage security incidents, retrieve historical data, and provide recommended solutions based on past incidents. (As Used By Rebackk)
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License
This project is licensed under the MIT License.