Data Labeling Agent API Service

LLMs

Run a data-labeling agent API on your own machine with Docker Compose, bound to 127.0.0.1; labeling needs your own OpenAI key. Derived from a frozen snapshot of an Apache-2.0 open-source project.

Subscribe & download See how to start

SubscriptionUS$49 per month

Last run2026-11-13

In practice

Readiness3 / 5

What you need

Few changes needed3 / 5

Who it is for

Developers and data teams who want to call a large language model for data labeling through an API on their own machine, and who have or will get an OpenAI key.

How to start

$ cp .env.example .env
$ docker compose up -d --build

Browse the files

Files in the product repository at the pinned commit. A few house files are left out of the zip.

File overview181 paths

▸adala49

__init__.py
agents/
environments/
memories/
runtimes/
skills/
utils/

▸docs16

README.md
mkdocs.yml
src/

▸examples15

classification_skill.ipynb
classification_skill_with_CoT.ipynb
code_generation.ipynb
gsm8k_test.ipynb
ontology_creator.ipynb
question_answering_skill.ipynb
quickstart.ipynb
skillsets_sequence_of_skills.ipynb
summarization_skill.ipynb
templates/
…

▸server17

README.md
__init__.py
api_codegen.sh
app.py
handlers/
log_middleware.py
tasks/
utils.py
worker_pool/

▸tests58

cassettes/
conftest.py
test_agent_basics.py
test_agent_with_rag.py
test_analysis_skill.py
test_cost_estimation.py
test_environments.py
test_label_studio_skill.py
test_llm.py
test_llm_utils.py
…

▫ATTRIBUTION.md

▫CONTRIBUTION.md

▫Dockerfile

▫Dockerfile.app

▫LICENSE

▫PRODUCT.md

▫QUICKSTART.md

▫README.md

▫SECURITY.md

▫codecov.yml

▫compass.yml

▫delivery-manifest.txt

▫docker-compose.native.yml

▫docker-compose.yml

▫docker-entrypoint.sh

▫poetry.lock

▫pyproject.toml

▫Config and hidden files 9

Latest passing run

Clone → Checkout → Toolchain → Run api

Pre-purchase Disclosure

What you are buying

A data-labeling agent API service brought up with Docker Compose on your own machine, callable from an interactive docs page; the labeling features use your own OpenAI key.

Derived from an open-source project under the Apache-2.0 licence, and not the original project itself.

Delivery is a frozen snapshot: one zip, taken from the product repository at revision 2c57ef5.

Known limitations

The service speaks plain HTTP and is bound to the local machine only (port 30001); TLS and a reverse proxy are yours to bring for any wider access
The model features need your own OpenAI key; without one, labeling and other calls that need a model cannot be used, while the home page still opens
Kafka data lives in a Docker volume, and docker compose down -v deletes it
The first build needs internet access to download dependencies
Pinned to the delivered snapshot; it does not follow upstream.

The liability cap, the scope of what is promised and the statutory floor are governed by the Terms of Service.

Vetting record

Everything below was checked against the pinned commit 1b57923. Every verdict carries its full reasoning, an evidence link and the checker; failures are published, not hidden — do not take our word for it, verify it yourself.

2 PASS3 WARN0 FAIL

Source ReviewWARN

Read: docker-compose.yml, Dockerfile, .env.example, QUICKSTART.md and the top of README.md. The upstream Python source was not read file by file.

Script SafetyPASS

The Dockerfile and compose file were read: images are pinned by digest, dependencies install from a lock file, and no download-and-pipe-to-shell pattern was seen there. docker-entrypoint.sh and other upstream scripts were not read in detail.

RecencyWARN

This is a frozen snapshot that does not follow upstream. The date of the pinned upstream commit was not checked.

LicensePASS

SPDX:Apache-2.0

The LICENSE file in the repository is the Apache License 2.0 text. The upstream copy was not compared against it.

Dependency LicensesWARN

Dependencies are declared in the Poetry project files and fetched at build time. They were not scanned for licenses.