Skip to main content

Concrete embedding, vector-store, and reranker backends for AI-Parrot

Project description

ai-parrot-embeddings

Concrete backend implementations for the AI-Parrot retrieval stack: embedding models, vector stores, and rerankers.

What's in this package

This satellite contributes modules to three subsystems of the parrot.* namespace:

  • parrot.embeddings.{google, huggingface, openai} — embedding backends
  • parrot.stores.{postgres, pgvector, milvus, arango, bigquery, faiss_store} — vector stores
  • parrot.rerankers.{local, llm} — rerankers

The abstract base classes (EmbeddingModel, AbstractStore, AbstractReranker), the registries (EmbeddingRegistry), the dispatch maps (supported_embeddings, supported_stores), and all shared types (parrot.stores.models.Document, SearchResult, etc.) remain in the ai-parrot core package.

Import contract

This package uses PEP 420 implicit namespace packages. Its modules ship directly under the existing parrot.* namespace — no separate top-level. Existing imports continue to work unchanged once installed:

from parrot.embeddings.huggingface import SentenceTransformerModel  # from satellite
from parrot.stores.pgvector import PgVectorStore                    # from satellite
from parrot.embeddings import EmbeddingRegistry                     # from core
from parrot.stores import AbstractStore, supported_stores           # from core

No code changes are needed in user projects after upgrading from ai-parrot[embeddings] to ai-parrot-embeddings[...].

Install

Goal Command
Core framework only (no backends) pip install ai-parrot
One backend pip install ai-parrot-embeddings[pgvector]
Multiple backends pip install ai-parrot-embeddings[pgvector,milvus,huggingface]
Embeddings + vector stores pip install ai-parrot-embeddings[huggingface,pgvector]
Rerankers pip install ai-parrot-embeddings[reranker-local]
Everything pip install ai-parrot-embeddings[all]
Legacy all-in-one (unchanged) pip install ai-parrot[all]

Extras

Extra Pulls in Enables
huggingface sentence-transformers, tokenizers, safetensors, einops, accelerate, peft, xformers, simsimd, bm25s, rank_bm25, sentencepiece parrot.embeddings.huggingface.SentenceTransformerModel
google google-genai, google-cloud-aiplatform parrot.embeddings.google.GoogleEmbeddingModel
openai openai, tiktoken parrot.embeddings.openai.OpenAIEmbeddingModel
pgvector pgvector==0.4.1 parrot.stores.postgres.PgVectorStore, parrot.stores.pgvector.PgVectorStore
milvus pymilvus, milvus-lite parrot.stores.milvus.MilvusStore
arango python-arango-async parrot.stores.arango.ArangoDBStore
bigquery google-cloud-bigquery parrot.stores.bigquery.BigQueryStore
faiss (no extra deps; faiss-cpu ships with ai-parrot core) parrot.stores.faiss_store.FAISSStore
chroma chromadb (reserved for future ChromaStore)
reranker-local sentence-transformers, tokenizers, safetensors parrot.rerankers.local.LocalCrossEncoderReranker
reranker-llm (no extra deps; uses existing LLM clients) parrot.rerankers.llm.LLMReranker
all All of the above Full retrieval stack

Development

git clone https://github.com/phenobarbital/ai-parrot
cd ai-parrot
source .venv/bin/activate
uv pip install -e packages/ai-parrot -e packages/ai-parrot-embeddings
uv run pytest packages/ai-parrot-embeddings/tests/

Or for the full workspace (if no pre-existing dependency conflicts):

uv sync --all-packages

Architecture

This package uses PEP 420 implicit namespace packages (not the parrot_<name>.* + sys.meta_path redirector pattern used by ai-parrot-tools, -loaders, -pipelines). The satellite ships no __init__.py files at parrot/, parrot/embeddings/, parrot/stores/, or parrot/rerankers/. Python's import machinery merges the satellite's directory entries with the host's regular packages at import time, because the host's sub-package __init__.py files call pkgutil.extend_path.

Design rationale

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

ai_parrot_embeddings-0.1.19.tar.gz (81.0 kB view details)

Uploaded Source

Built Distribution

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

ai_parrot_embeddings-0.1.19-py3-none-any.whl (82.1 kB view details)

Uploaded Python 3

File details

Details for the file ai_parrot_embeddings-0.1.19.tar.gz.

File metadata

  • Download URL: ai_parrot_embeddings-0.1.19.tar.gz
  • Upload date:
  • Size: 81.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for ai_parrot_embeddings-0.1.19.tar.gz
Algorithm Hash digest
SHA256 31ff0679a9af09d9f875cad022c65a03adeb0757308928c08c93a08bc427ac39
MD5 2b5253f8d998247154eafafd47aeda3e
BLAKE2b-256 f01d6017093bbb6bbd0f6d215b1fdbbe46de70bc67b4c2ea800413172caced29

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_embeddings-0.1.19.tar.gz:

Publisher: release.yml on phenobarbital/ai-parrot

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

File details

Details for the file ai_parrot_embeddings-0.1.19-py3-none-any.whl.

File metadata

File hashes

Hashes for ai_parrot_embeddings-0.1.19-py3-none-any.whl
Algorithm Hash digest
SHA256 273f352e9fbd92c286da69341508824180b3b1bea21efa5169b5c393de35127f
MD5 d6cda093cdc46c36d9de6857c4feeb82
BLAKE2b-256 093a8ff0f7b637bc3555646921538cb1821db224452e798e267836a901644655

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_embeddings-0.1.19-py3-none-any.whl:

Publisher: release.yml on phenobarbital/ai-parrot

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