adj-ai 0.1.0

A multi-provider LLM orchestrator using a analyse-delegate-judge strategy.

adj-ai

adj-ai is a multi-provider LLM orchestrator. It generates several candidate responses to a task from one or more model providers (Anthropic, OpenAI, DeepSeek), then uses a "judge" model to adjudicate the candidates and return the best one.

The core idea is analyse-delegate-judge: by producing multiple candidates and scoring them against a judging rubric, you get higher-quality outputs than a single one-shot completion.

Status: Early development. The Anthropic, OpenAI, and DeepSeek generation/judging paths are all implemented.

How it works

1. Model selection – A lightweight model (e.g. Anthropic Haiku) inspects the task prompt and picks the most appropriate generation model, balancing cost and performance.
2. Candidate generation – The chosen model produces candidates responses to the task_prompt.
3. Judging – A stronger model (e.g. Anthropic Sonnet) ranks the candidates using the judge_prompt and returns them in order of preference.
4. Result – The top-ranked candidate is returned.

When multiple clients are configured, judging falls back in priority order: Anthropic → OpenAI → DeepSeek.

Installation

pip install adj-ai

This pulls in the official provider SDKs (anthropic, openai) automatically.

DeepSeek and OpenAI share the openai SDK (DeepSeek exposes an OpenAI-compatible API).

Usage

from anthropic import Anthropic
from openai import OpenAI

from adj_ai import Orchestrator

anthropic_client = Anthropic(api_key="...")
openai_client = OpenAI(api_key="...")
deepseek_client = OpenAI(api_key="...", base_url="https://api.deepseek.com")

orch = Orchestrator(
    task_prompt="Write a concise product description for a smart water bottle.",
    judge_prompt="Pick the description that is clearest and most persuasive.",
    anthropic_client=anthropic_client,
    openai_client=openai_client,
    deepseek_client=deepseek_client,
    candidate_number=5,
    max_task_tokens=1000,
)

best = orch.run_task()
print(best)

At least one of anthropic_client, openai_client, or deepseek_client must be provided, otherwise an OrchestratorError is raised.

Configuration

Parameter	Type	Default	Description
task_prompt	str	—	The task to generate candidate responses for.
judge_prompt	str	—	The rubric used to rank candidates.
anthropic_client	Anthropic	—	Optional Anthropic client.
openai_client	OpenAI	—	Optional OpenAI client.
deepseek_client	OpenAI	—	Optional DeepSeek (OpenAI-compatible) client.
candidate_number	int	1	Number of candidate responses to generate.
max_task_tokens	int	1000	Maximum tokens per generated candidate.

TODO

• Package the project for distribution

License

Released under the MIT License.