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

This version

0.4.4

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-0.4.4.tar.gz (42.7 kB view details)

Uploaded Source

Built Distribution

neural_rag-0.4.4-py310-none-any.whl (55.8 kB view details)

Uploaded Python 3.10

File details

Details for the file neural_rag-0.4.4.tar.gz.

File metadata

  • Download URL: neural_rag-0.4.4.tar.gz
  • Upload date:
  • Size: 42.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for neural_rag-0.4.4.tar.gz
Algorithm Hash digest
SHA256 8aaf0926598af8647b4fce53a63d3ba963d58deb99189d2b8a87b3bb78aac048
MD5 b5806d44af477c6fa26561c94eebddc2
BLAKE2b-256 6c0e74419d49be9c90b1efeafadaebdc300ecacd4762892e6c9f7f0825934dba

See more details on using hashes here.

File details

Details for the file neural_rag-0.4.4-py310-none-any.whl.

File metadata

  • Download URL: neural_rag-0.4.4-py310-none-any.whl
  • Upload date:
  • Size: 55.8 kB
  • Tags: Python 3.10
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for neural_rag-0.4.4-py310-none-any.whl
Algorithm Hash digest
SHA256 7a7ea28c2636b1d687f8781c88aeaff8c0e9a87147c93f89fbf6ef926356e29b
MD5 4d8fdf04a2d5a166db3a6691866ebeeb
BLAKE2b-256 ba64bad93aea8b2633e3c79adbb3a4cec9da1830ce2375278f7292387c1d076d

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