vault-ai: Custom Knowledgebase Query Tool

Project Overview

Introduction

Vault-AI leverages the OP Stack (OpenAI + Pinecone Vector Database) to empower users to upload custom knowledgebase files and query their contents. This Golang server, paired with a React frontend, offers a quick setup for creating a personalized question-answering system focused on human-readable content like books and letters. Users can upload extensive libraries and receive precise answers, complete with the file name and specific section referenced. This makes Vault-AI a practical tool for efficient knowledge extraction and information retrieval.

Key Features

‘Vault-AI’ leverages the OP Stack (OpenAI + Pinecone Vector Database) to enable users to upload custom knowledgebase files and query their contents. Key features include a quick setup with a Golang server and React frontend, support for various document types, and the ability to handle large libraries. Users can retrieve accurate answers with context snippets and filenames. The system processes files into embeddings stored in Pinecone, facilitating efficient question-answering. Dependencies include Go, Node.js, and Poppler, and the setup involves configuring API keys and running the server and frontend locally.

Real-World Applications

1. Academic Research: Upload a collection of academic papers, books, and research documents to create a comprehensive knowledge base. Use OP Vault to quickly retrieve specific information or answers, including context and source references, aiding in research and study.

2. Business Document Management: Store and manage business documents, such as contracts, reports, and communications. Ask questions to get precise information from these documents, enhancing decision-making and efficiency.

3. Personal Library Organization: Upload personal book collections and documents. Easily search for specific content or quotes, making it a useful tool for avid readers and researchers.

Conclusion

‘Vault-AI’ leverages the OP Stack (OpenAI + Pinecone Vector Database) to enable users to upload and query custom knowledge bases. With a user-friendly React frontend and Golang server, it supports various document types, providing accurate, context-aware answers. Its potential lies in scalable knowledge extraction and question-answering for extensive libraries, enhancing information accessibility and utility.

For further insights and to explore the project further, check out the original pashpashpash/vault-ai repository.

Attributions

Content derived from the pashpashpash/vault-ai repository on GitHub. Original materials are licensed under their respective terms.