Local-Rag

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local-rag is an open-source AI Agents & Automation tool that ingests files for retrieval augmented generation (RAG) with open-source LLMs. It operates offline, ensuring data privacy without third parties.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is local-rag?

local-rag is an open-source tool designed for Retrieval Augmented Generation (RAG) using open-source Large Language Models (LLMs). It allows users to ingest various file types, including local files, GitHub repositories, and websites, all without relying on third-party services or sending sensitive data outside their network. A key differentiator is its support for offline embeddings and LLMs, eliminating the need for external APIs like OpenAI. The tool features streaming responses, conversational memory, and chat export capabilities, making it suitable for secure, local RAG implementations.

Best used for

Ideal for developers and data scientists who need to build secure, private RAG applications, process sensitive internal documents, and experiment with open-source LLMs without external dependencies. Especially valuable for environments requiring strict data sovereignty and offline capabilities.

Common actions

ingest files

generate responses

process data locally

build RAG applications

face swappingautomated workflowcollaborationworkflowsdeepfakelow-code/no-code"AI Agents"open-sourcegithub copilot

Capabilities

Key features

Offline Embeddings & LLMs
Multiple Source Support
Streaming Responses
Conversational Memory
Chat Export

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

Does local-rag require an internet connection to function?

No, local-rag is designed for offline operation. It supports offline embeddings and Large Language Models, meaning you can ingest files and perform retrieval augmented generation without any external internet connection or reliance on third-party APIs like OpenAI.

What types of data sources can local-rag ingest?

local-rag supports ingesting data from multiple sources. You can use it to process local files stored on your system, content from GitHub repositories, and information directly from websites. This flexibility allows for a broad range of RAG applications.

Does local-rag store my sensitive data externally?

No, a core principle of local-rag is to ensure data privacy. It is built to operate without third parties, meaning sensitive data never leaves your network. All processing and storage occur locally, giving you full control over your information.

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Subcategories trending in AI Agents & Automation

AI Frameworks & Infra Chatbots & Conversational AI Workflow Agents Personal Assistants RAG & Document AI Voice Agents

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