Skip to main content

Lightweight, LLM-agnostic RAG pipeline with pluggable corpora. Works with Claude, OpenAI, Gemini, or any LLM.

Project description

attune-rag

Lightweight, LLM-agnostic RAG pipeline with pluggable corpora. Works with Claude, OpenAI, Gemini, or any LLM.

  • No LLM SDK at install time. All provider deps are optional extras.
  • Pluggable corpus. Use attune-help (the default), any markdown directory, or your own CorpusProtocol.
  • Returns a prompt string by default — send it to whatever LLM you like. Optional provider adapters ship convenience wrappers.

Install

pip install attune-rag                     # core only
pip install 'attune-rag[attune-help]'      # + bundled help corpus
pip install 'attune-rag[claude]'           # + Claude adapter
pip install 'attune-rag[openai]'           # + OpenAI adapter
pip install 'attune-rag[gemini]'           # + Gemini adapter
pip install 'attune-rag[all]'              # everything

Quick start — Claude

pip install 'attune-rag[attune-help,claude]'
import asyncio
from attune_rag import RagPipeline

async def main():
    pipeline = RagPipeline()  # defaults to AttuneHelpCorpus
    response, result = await pipeline.run_and_generate(
        "How do I run a security audit with attune?",
        provider="claude",
    )
    print(response)
    print("\nSources:", [h.entry.path for h in result.citation.hits])

asyncio.run(main())

Quick start — OpenAI

pip install 'attune-rag[attune-help,openai]'
response, result = await pipeline.run_and_generate(
    "...", provider="openai", model="gpt-4o",
)

Quick start — Gemini

pip install 'attune-rag[attune-help,gemini]'
response, result = await pipeline.run_and_generate(
    "...", provider="gemini", model="gemini-1.5-pro",
)

Quick start — custom corpus, any LLM

from pathlib import Path
from attune_rag import RagPipeline, DirectoryCorpus

pipeline = RagPipeline(corpus=DirectoryCorpus(Path("./my-docs")))
result = pipeline.run("How do I...?")

# Send result.augmented_prompt to whatever LLM you use.
# The pipeline itself does NOT call an LLM unless you use
# run_and_generate or call a provider adapter yourself.

Status

v0.1.0 — initial release. Part of the attune ecosystem (attune-ai, attune-help, attune-author).

License

Apache 2.0. See LICENSE.

Project details


Download files

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

Source Distribution

attune_rag-0.1.2.tar.gz (19.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

attune_rag-0.1.2-py3-none-any.whl (23.8 kB view details)

Uploaded Python 3

File details

Details for the file attune_rag-0.1.2.tar.gz.

File metadata

  • Download URL: attune_rag-0.1.2.tar.gz
  • Upload date:
  • Size: 19.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for attune_rag-0.1.2.tar.gz
Algorithm Hash digest
SHA256 f2f7095a5ca148b0cd98520167089139e0f6b5b2b3316bddd62f1f97369477ef
MD5 03cbc61332a0eb855dcae77830555ab2
BLAKE2b-256 4a089be0435ea2f0242b762ebc811ba494214fea1e114f629faf05762f370873

See more details on using hashes here.

Provenance

The following attestation bundles were made for attune_rag-0.1.2.tar.gz:

Publisher: publish.yml on Smart-AI-Memory/attune-rag

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file attune_rag-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: attune_rag-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 23.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for attune_rag-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 3b2997e95e8b6da896f0d32fe7c3d832cee9da937c927e40ea9fa8ecd86e593c
MD5 2a236f7bcb679c392109cc5b7a7951c0
BLAKE2b-256 e072d23cf5c98699f76652e64632e398d293e213c084e0e3ec64a096bdc41eda

See more details on using hashes here.

Provenance

The following attestation bundles were made for attune_rag-0.1.2-py3-none-any.whl:

Publisher: publish.yml on Smart-AI-Memory/attune-rag

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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