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-0.3.6.tar.gz (40.8 kB view details)

Uploaded Source

Built Distribution

neural_rag-0.3.6-py310-none-any.whl (53.9 kB view details)

Uploaded Python 3.10

File details

Details for the file neural_rag-0.3.6.tar.gz.

File metadata

  • Download URL: neural_rag-0.3.6.tar.gz
  • Upload date:
  • Size: 40.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for neural_rag-0.3.6.tar.gz
Algorithm Hash digest
SHA256 47d35f56dfc76552bb791e81dc239f5e5f35cb0ee2753fc6fee90d9d4bf509d8
MD5 0da173f4d9c2f560d990831cc590669f
BLAKE2b-256 4688ceb48732db1dc63c1aab22ac59b5ffc7254afb5afbaa142dd1ec33d0195c

See more details on using hashes here.

File details

Details for the file neural_rag-0.3.6-py310-none-any.whl.

File metadata

  • Download URL: neural_rag-0.3.6-py310-none-any.whl
  • Upload date:
  • Size: 53.9 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-0.3.6-py310-none-any.whl
Algorithm Hash digest
SHA256 adbb60312d90117ccc9e0ef59b2f39e538411f534711340bde65107b5f24be3f
MD5 a296ded4078d74dcc47cd2631af654d2
BLAKE2b-256 f3a61de311b442edf3b83aa5e2935658aab6f1685341b746b2b06358cf2780fa

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