Skip to main content

No project description provided

Project description

# Neural RAG

Neural Rag is a LLM framework to build Vector RAG and Graph RAG knowledge base. It provides the foundation to quickly build agents.

## What is RAG?

RAG stands for Retrieval Augmented Generation.

It was introduced in the paper [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://arxiv.org/abs/2005.11401).

Each step can be roughly broken down to:

  • Retrieval - Seeking relevant information from a source given a query. For example, getting relevant passages of Wikipedia text from a database given a question.

  • Augmented - Using the relevant retrieved information to modify an input to a generative model (e.g. an LLM).

  • Generation - Generating an output given an input. For example, in the case of an LLM, generating a passage of text given an input prompt.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

neural_rag-0.3.18.tar.gz (42.4 kB view details)

Uploaded Source

Built Distribution

neural_rag-0.3.18-py310-none-any.whl (55.6 kB view details)

Uploaded Python 3.10

File details

Details for the file neural_rag-0.3.18.tar.gz.

File metadata

  • Download URL: neural_rag-0.3.18.tar.gz
  • Upload date:
  • Size: 42.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for neural_rag-0.3.18.tar.gz
Algorithm Hash digest
SHA256 3c1df0d1bad430e93f3e30f32df29a2ca750973aef9a462cf0d4348408d7fdcb
MD5 c7b708ba563a4bb0e061916a5cb83464
BLAKE2b-256 3f2c0b4c689615d356dfb92da6dcd35d702d9be19d57662970b748f190c211fa

See more details on using hashes here.

File details

Details for the file neural_rag-0.3.18-py310-none-any.whl.

File metadata

File hashes

Hashes for neural_rag-0.3.18-py310-none-any.whl
Algorithm Hash digest
SHA256 62079f86725efc179773a97069bc47115e01689f8fd73c8357b2e8936fa08e3b
MD5 a20c1acc35d1c723f4a7590359e4c0ba
BLAKE2b-256 d6ff3e5d53a49dabf28fa16714bb678d461db74e5be9fa375da4171733404cc5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page