ai_api_unified 0.1.0

Unified access layer for completion and embedding services

ai_api_unified · Unified Foundation-Model Client Library

Version: 0.1.0  |  License: MIT

ai_api_unified provides a single, typed interface for calling both completion-style LLMs and text-embedding models across vendors (OpenAI, Amazon Bedrock/Titan, …).

Prerequisites

• Python 3.12.1 (only)
  We strongly recommend using pyenv to install and pin exactly 3.12.1, so that compiled wheels (e.g. tiktoken) are available and no Rust toolchain is required.

Installation

# from your internal Artifactory PyPI
pip install --index-url https://<org>.jfrog.io/artifactory/api/pypi/pypi-local/simple ai_api_unified

Supported Python ≥ 3.9 (< 4.0).

Quick start

from ai_api_unified import AIFactory

# Completions
client = AIFactory.get_ai_completions_client()           # auto-selects engine via .env
response = client.send_prompt("Say hello in German")
print(response)  # → "Hallo!"

# Embeddings
embedder = AIFactory.get_ai_embedding_client()
vector = embedder.generate_embeddings("vectorize me")

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Repository layout

src/ai_api_unified/              ← package source
└── ai_base.py           ← abstract interfaces
└── ai_factory.py        ← runtime factory
tests/                   ← pytest suite
.env_template            ← sample environment config

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Development

# create virtualenv & install runtime + dev dependencies
poetry install --with dev
pytest -q

Linting and formatting:

ruff check .
ruff format .

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Publishing to Artifactory (Poetry workflow)

poetry version 0.1.0        # bump when ready
poetry build                # builds wheel + sdist
poetry config repositories.ups-ai https://<org>.jfrog.io/artifactory/api/pypi/pypi-local
poetry publish -r ups-ai

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Roadmap

• Add more provider back-ends (Anthropic, Google).
• Provide async variants for high-throughput workloads.