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-0.1.6.tar.gz (77.0 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-0.1.6-py3-none-any.whl (77.6 kB view details)

Uploaded Python 3

File details

Details for the file ai_parrot_embeddings-0.1.6.tar.gz.

File metadata

  • Download URL: ai_parrot_embeddings-0.1.6.tar.gz
  • Upload date:
  • Size: 77.0 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-0.1.6.tar.gz
Algorithm Hash digest
SHA256 59fcc74a09d2ed897083d7438dc79f4979299b4fd59b7fe671bcb20f2be8be79
MD5 2148f8d8ca5ec3e56da80f8b56852e4a
BLAKE2b-256 f700f3a65635cfa04c7cf7abdbf8f03e0751c8c8969cd9739d7ba694221811ce

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_embeddings-0.1.6.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-0.1.6-py3-none-any.whl.

File metadata

File hashes

Hashes for ai_parrot_embeddings-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 115d9ce410e0f47ad937135b05d6be3a0eb8b36abf28f25346c6fdebdc31014d
MD5 fc44c2ea6b396fcdf2abffedeb2a79e6
BLAKE2b-256 ad159bb0b2c1b8f0653a260e55e8355c10c4678f3d6557b1ccf77252cd06109c

See more details on using hashes here.

Provenance

The following attestation bundles were made for ai_parrot_embeddings-0.1.6-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