RAG With NextJS, Langchain and Ollama

[0xsarwagya]

Project Suggestion Title

RAG With NextJS, Langchain, and Ollama

Description

This project aims to integrate Retrieval-Augmented Generation (RAG) capabilities into a Next.js application using Langchain and Ollama. By combining these technologies, we can create a robust, scalable, and interactive system capable of retrieving relevant data from external sources and generating responses using advanced language models. This can be utilized in a variety of use cases, such as a highly intelligent chatbot, dynamic FAQs, or an automated customer support system that adapts based on user queries.

Benefits

This project would benefit the community by providing a powerful, customizable, and efficient solution for building conversational AI applications with integrated data retrieval. It offers flexibility in scaling knowledge-driven responses by leveraging both the latest advancements in language models and efficient API handling in Next.js. This could be an ideal solution for teams looking to build conversational agents, customer support tools, or knowledge bases for their products.

It would also help Rebackk by enhancing user engagement through a more dynamic, responsive AI assistant or help desk tool.

Implementation Ideas

• Next.js as the framework for building the web app, providing fast and flexible server-side rendering (SSR) and API routes.
• Langchain to handle the orchestration of LLMs and the retrieval-augmented generation process, including linking to data sources and retrieval of documents.
• Ollama for language model generation, fine-tuned for specific tasks such as question answering or summarization.
• Vercel to deploy the Next.js application, leveraging serverless functions for handling the API requests and ensuring efficient handling of RAG tasks.
• Potential features: chat interface, file/document search, custom LLM responses based on user input, automatic knowledge base expansion.

Additional Context

We are building this for Rebackk to enhance our product's AI capabilities, specifically in customer interactions and security incident management. The integration of RAG could greatly improve our response accuracy and ensure that users have real-time, data-driven insights at their disposal.

Relevant Links:

• Langchain Documentation
• Ollama GitHub
• Next.js Documentation

Suggested Contributors

• @0xsarwagya
• @king04aman

[github-actions[bot]]

👋 @0xsarwagya 👋

We're thrilled to see you opening an issue! Your input is valuable to us. Don’t forget to fill out our issue template for the best experience. We will look into it soon.

[0xsarwagya]

Completed :)

[github-actions[bot]]

👋 @0xsarwagya 👋

Thanks for closing the issue! We appreciate your updates.