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vector-store

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

Cuda
870
2 天前

Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions

TypeScript
857
4 个月前
Python
146
2 年前

The official Elasticsearch .NET Vector Store Connector for Microsoft Semantic Kernel.

C#
14
1 个月前

A Question Generation Application leveraging RAG and Weaviate vector store to be able to retrieve relative contexts and generate a more useful answer-aware questions

Jupyter Notebook
11
3 个月前

AgriGenius: AI-Powered Agriculture Chatbot is a Python web application designed to empower farmers with information accessibility. AgriGenius leverages a Retrieval-Augmented Generation model to address farmer's agricultural queries with precise answers.

JavaScript
9
7 个月前

The AI Assistant uses OpenAI's GPT models and Langchain for agent management and memory handling. With a Streamlit interface, it offers interactive responses and supports efficient document search with FAISS. Users can upload and search pdf, docx, and txt files, making it a versatile tool for answering questions and retrieving content.

Python
9
1 年前

A command-line tool that ingests documents and generates instant answers to your questions about those documents using ChatGPT, giving you the Sheldon Cooper you never had at your fingertips.

TypeScript
8
2 年前

A simple way to convert and manage files in vector storage.

Python
6
5 个月前

In this we implements a Retrieval-Augmented Generation (RAG) based conversational AI agent designed for intelligent knowledge extraction from PDF documents. Leveraging LangChain and Google’s Gemini LLM

Jupyter Notebook
5
7 个月前

AI Data Assistant empowers data professionals by speaking both human language and machine langauges (SQL/Python)

Python
4
3 个月前