What is Argilla?#
Argilla is an open-source data curation platform for LLMs. Using Argilla, everyone can build robust language models through faster data curation using both human and machine feedback. We provide support for each step in the MLOps cycle, from data labeling to model monitoring.
📄 About The Docs#
Install Argilla and end-to-end toy examples
Brief code snippets for our main functionalities
Everything deployment: Docker, Kubernetes, Cloud and way more
User management and deployment tweaking
Generative AI, ChatGPT and friends
Conceptual overview of our main functionalities
Specific applied end-to-end examples
Itemized information and API docs
Everything about for developers and contributing
Our future plans
🛠️ Project Architecture#
Argilla is built on 5 core components:
Python SDK: A Python SDK which is installable with
pip install argilla. To interact with the Argilla Server and the Argilla UI. It provides an API to manage the data, configuration, and annotation workflows.
FastAPI Server: The core of Argilla is a Python FastAPI server that manages the data, by pre-processing it and storing it in the vector database. Also, it stores application information in the relational database. It provides a REST API to interact with the data from the Python SDK and the Argilla UI. It also provides a web interface to visualize the data.
Relational Database: A relational database to store the metadata of the records and the annotations. SQLite is used as the default built-in option and is deployed separately with the Argilla Server but a separate PostgreSQL can be used too.
Vector Database: A vector database to store the records data and perform scalable vector similarity searches and basic document searches. We currently support ElasticSearch and AWS OpenSearch and they can be deployed as separate Docker images.
Vue.js UI: A web application to visualize and annotate your data, users, and teams. It is built with Vue.js and is directly deployed alongside the Argilla Server within our Argilla Docker image.
Open: Argilla is free, open-source, and 100% compatible with major NLP libraries (Hugging Face transformers, spaCy, Stanford Stanza, Flair, etc.). In fact, you can use and combine your preferred libraries without implementing any specific interface.
End-to-end: Most annotation tools treat data collection as a one-off activity at the beginning of each project. In real-world projects, data collection is a key activity of the iterative process of ML model development. Once a model goes into production, you want to monitor and analyze its predictions and collect more data to improve your model over time. Argilla is designed to close this gap, enabling you to iterate as much as you need.
User and Developer Experience: The key to sustainable NLP solutions is to make it easier for everyone to contribute to projects. Domain experts should feel comfortable interpreting and annotating data. Data scientists should feel free to experiment and iterate. Engineers should feel in control of data pipelines. Argilla optimizes the experience for these core users to make your teams more productive.
Beyond hand-labeling: Classical hand-labeling workflows are costly and inefficient, but having humans in the loop is essential. Easily combine hand-labeling with active learning, bulk-labeling, zero-shot models, and weak supervision in novel data annotation workflows**.
We love contributors and have launched a collaboration with JustDiggit to hand out our very own bunds and help the re-greening of sub-Saharan Africa. To help our community with the creation of contributions, we have created our developer and contributor docs. Additionally, you can always schedule a meeting with our Developer Advocacy team so they can get you up to speed.
🙋♀️ Join the Argilla community on Slack and get direct support from the community.
⭐ Argilla Github repo to stay updated about new releases and tutorials.
🎁 We’ve just printed stickers! Would you like some? Order stickers for free.
We continuously work on updating our plans and our roadmap and we love to discuss those with our community. Feel encouraged to participate.