hellig 0.0.1

Multi-agent natural language orchestration programming framework.

Hellig

Multi-agent natural language orchestration programming framework.

Hellig lets you compose programs out of natural language steps that are dispatched to specialized agents. Treat prompts as instructions, agents as functions, and an orchestrator as the runtime that wires them together.

Why Hellig

Modern LLM applications quickly outgrow a single prompt. Hellig provides a tiny, opinionated core so you can:

• Describe work in natural language and let agents do the heavy lifting.
• Compose programs as ordered steps, with named outputs feeding later prompts.
• Swap agent runtimes (any LLM client, a local model, or a stub for tests) without rewriting your orchestration.
• Operate from the terminal with the hg CLI for quick experiments.

Install

pip install hellig
# or
uv add hellig

Quick start

from hellig import Agent, Orchestrator, Program

def echo_runtime(prompt: str, **_: object) -> str:
    return prompt.upper()

researcher = Agent(name="researcher", instructions="You research topics.", runtime=echo_runtime)
writer = Agent(name="writer", instructions="You write summaries.", runtime=echo_runtime)

program = (
    Program(name="brief")
    .add("researcher", "Collect facts about {topic}", output="facts")
    .add("writer", "Write a 3-bullet summary of:\n{facts}", output="summary")
)

orchestrator = Orchestrator().register(researcher).register(writer)
result = orchestrator.run(program, topic="agentic programming")
print(result["summary"])

Core concepts

Concept	Description
Agent	A named worker with optional instructions, runtime, and tools.
Program	An ordered sequence of natural language Steps with named outputs.
Orchestrator	Registers agents and executes programs, threading outputs into later prompts.

Steps use str.format substitution, so any prior step's output (and any context kwargs passed to run) is available as a placeholder.

CLI

The package installs an hg command powered by Click:

hg --help
hg version
hg hello HSPK
hg run --agent researcher --agent writer \
       --step researcher "Find facts about Hellig" \
       --step writer "Summarize the facts"

Development

uv sync
uv run hg --help
uv build

Roadmap

• Pluggable LLM runtimes (OpenAI, Anthropic, local).
• Tool calling and structured outputs.
• Parallel and conditional steps.
• Persistent traces for debugging.

License

MIT © HSPK