LaVague is an open-source project designed to automate automation for devs!
We use advanced AI techniques (RAG, Few-shot learning, Chain of Thought) to turn natural language instructions into Python code leveraging Selenium. LaVague is designed to make it easy for users to automate web workflows and execute them on a browser.
Here's an example to show how LaVague can execute natural language instructions on a browser to automate interactions with a website:
LaVague interacting with Hugging Face's website.
You can get started with LaVague in 2 steps:
- Install LaVague & dependencies
wget https://raw.githubusercontent.com/lavague-ai/LaVague/main/setup.sh &&
sudo bash setup.sh
- Run your LaVague command!
You can either launch an interactive demo, where LaVague will execute and show you the results of the automation code it generates for your instruction.
lavague-launch --file_path tests/hf.txt --config_path examples/api/openai_api.py
Or you can use the lavague-build to directly get the Python code leveraging Selenium in a file, which you can then inspect & execute locally.
lavague-build --file_path tests/hf.txt --config_path examples/api/openai_api.py
For a step-by-step guide or to run LaVague in a Google Colab, see our quick-tour which will walk you through how to get set-up and launch LaVague with our CLI tool.
We would love your help in making La Vague a reality.
To avoid having multiple people working on the same things & being unable to merge your work, we have outlined the following contribution process:
- 📢 We outline tasks on our
backlog: we recommend you check out issues with thehelp-wantedlabels &good first issuelabels - 🙋♀️ If you are interested in working on one of these tasks, comment on the issue!
- 🤝 We will discuss with you and assign you the task with a
community assignedlabel - 💬 We will then be available to discuss this task with you
- ⬆️ You should submit your work as a PR
- ✅ We will review & merge your code or request changes/give feedback
Please check out our contributing guide for a more detailed guide.
If you want to ask questions, contribute, or have proposals, please come on our Discord to chat!
TO keep up to date with our project backlog here.
This project executes LLM-generated code using exec. This is not considered a safe practice. We therefore recommend taking extra care when using LaVague (such as running LaVague in a sandboxed environment)!