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 links

Data verified by PyPI on
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.1.35)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for phenobarbital from gravatar.com phenobarbital

Credits

Author: Jesus Lara

GitHub Statistics

Data verified by PyPI on 
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.11

Provides Extra

huggingface google openai pgvector milvus arango bigquery faiss chroma reranker-local reranker-llm multimodal all

Tags

ai rag embeddings vector-store rerankers

Classifiers

Report project as malware

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-0.1.34.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-0.1.34-py3-none-any.whl (82.1 kB view details)

Uploaded Python 3

File details

Details for the file ai_parrot_embeddings-0.1.34.tar.gz.

File metadata

  • Download URL: ai_parrot_embeddings-0.1.34.tar.gz
  • Upload date:
  • Size: 81.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for ai_parrot_embeddings-0.1.34.tar.gz
Algorithm Hash digest
SHA256 fe996c0388648a22389d6e01d9dd8a9bd55c47ba950ad7a79b3ab4112c1ba0dd
MD5 b9bd0a1cf93b3a05e3c9ad97f5d551ae
BLAKE2b-256 d90a40da96bfb70c881485932ba964e097244775fa5021fd529c2418158c788e

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_embeddings-0.1.34.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-0.1.34-py3-none-any.whl.

File metadata

File hashes

Hashes for ai_parrot_embeddings-0.1.34-py3-none-any.whl
Algorithm Hash digest
SHA256 0970f8500057a3b89730181821a8f567f939ff4d2f4b930ed2f6cc060c85e253
MD5 599e7a0680fb01a466a5e6ed26dd32ff
BLAKE2b-256 f4aac1eb02901e6d8886ff0f192751dd1d03c44ab723a9e0d9afa9e261f3b80f

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_embeddings-0.1.34-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