Platform

Open-source building blocks

LLM Works provides a modular open-source platform that organizes the infrastructure layer between LLMs and agents. The libraries are hosted on GitHub and published on PyPI.

appinfra

Reliable infrastructure: config, logging, scheduling, lifecycle.

llm-saia

Clean LLM communication: structured requests, typed responses, guards.

llm-infer

Inference across backends: same code across providers.

llm-kelt

Feedback collection, context management, fine-tuning.

llm-gent

Trait-based agents: explicit capabilities and configuration.

To GitHub →

Engineering

The quality of the platform components is checked by an open-source in-house grader*. Latest appinfra scoreboard:

Category	Score			Verified by
Architecture & Design	10.0	/	10	22 packages, `py.typed`
Code Quality	10.0	/	10	mypy strict, ~200 files
Security	10.0	/	10	172 dedicated security tests
Testing	10.0	/	10	95% coverage, ~4800 tests
Documentation	9.5	/	10	15 guides, 18 API refs
Production Readiness	10.0	/	10	PyPI, semver, deprecations
Dependencies	10.0	/	10	clean `pip-audit`
Overall	9.95**	/	10 (A+)

Last graded: 81ef184 with Opus 4.7
* The integrity of this grader can be further verified by another AI.
** Weighted average.

Example

An appinfra CLI creates a SAIA object, connects to an Anthropic backend via llm-infer, and sends one request.

import sys, asyncio
from appinfra.app import AppBuilder
from llm_infer.client import Factory, SAIAAdapter
from llm_saia import SAIA

# build the CLI app via appinfra (provides self.lg, self.args, app.main)
app = AppBuilder("hello-llm").build()

# bind run() as the "run" subcommand with a positional "prompt" argument
@app.tool(name="run")
@app.argument("prompt")
def run(self):
    asyncio.run(_send(self.lg, self.args.prompt))

async def _send(lg, prompt):
    # open an async Anthropic client via llm-infer
    async with Factory(lg).anthropic() as client:
        # build a SAIA session using the llm-infer client as its backend
        saia = SAIA.builder().backend(SAIAAdapter(client)).build()
        # invoke the instruct verb to get a typed response
        print((await saia.instruct(prompt)).value)

if __name__ == "__main__":
    sys.exit(app.main())

Usage:

$ pip install appinfra llm-saia "llm-infer[anthropic,saia]"
$ export ANTHROPIC_API_KEY=sk-ant-...
$ python app.py run "What is systems engineering?"