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

0.4.8

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-0.4.8.tar.gz (42.5 kB view details)

Uploaded Source

Built Distribution

neural_rag-0.4.8-py310-none-any.whl (55.6 kB view details)

Uploaded Python 3.10

File details

Details for the file neural_rag-0.4.8.tar.gz.

File metadata

  • Download URL: neural_rag-0.4.8.tar.gz
  • Upload date:
  • Size: 42.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for neural_rag-0.4.8.tar.gz
Algorithm Hash digest
SHA256 5e0d00cdb9a3996382fa22e81fcc281d4d81e35713ab20d0273f7e3a8e2be56d
MD5 d67ba485693e606133c588f9b342e03e
BLAKE2b-256 048ade08952ec5be494e3af611dd6fe7350b0f3e0149736bf3d6e98963e00964

See more details on using hashes here.

File details

Details for the file neural_rag-0.4.8-py310-none-any.whl.

File metadata

  • Download URL: neural_rag-0.4.8-py310-none-any.whl
  • Upload date:
  • Size: 55.6 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-0.4.8-py310-none-any.whl
Algorithm Hash digest
SHA256 8d16eee08f97a77b268aabfc3f0c24a7aff6a0d6dcd3b0c9250c348de135e766
MD5 2dfdbfae2c24248adae0e7ef34699294
BLAKE2b-256 71816aa3d4be066801b182e202fd4b94c51ac680987159db1b52ea34672fd9b2

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