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

0.4.6

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-0.4.6.tar.gz (42.7 kB view details)

Uploaded Source

Built Distribution

neural_rag-0.4.6-py310-none-any.whl (55.8 kB view details)

Uploaded Python 3.10

File details

Details for the file neural_rag-0.4.6.tar.gz.

File metadata

  • Download URL: neural_rag-0.4.6.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-0.4.6.tar.gz
Algorithm Hash digest
SHA256 2999f3f17c9d378fc9b921a7a77f8398d266e299bde78ce1e3e03ad58d221202
MD5 fb95a93c1ecd6dd9aa8c0e6019c47b48
BLAKE2b-256 5675ba2a19147c9c1dc0009c9049a959f85b4a4b7349a8d31c3305f84c93bdef

See more details on using hashes here.

File details

Details for the file neural_rag-0.4.6-py310-none-any.whl.

File metadata

  • Download URL: neural_rag-0.4.6-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-0.4.6-py310-none-any.whl
Algorithm Hash digest
SHA256 c3e60fb5aaadf8dfca41a15e8a8386bdeea65aac8f12daeb41796cde82f1fe73
MD5 2f2205df213474e6b90b99943ee6803f
BLAKE2b-256 0125d9c100ca39b2a45db4f789380da2a63fc59dde42ad019c97aa5de1505f92

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