Automatisation
PyScrappy
Self-healing web scraping for AI agents, plus an MCP server.
★ 260 étoilesMIT
Voir le guide →JamAIBase est un projet de automatisation open source, créé par EmbeddedLLM (EmbeddedLLM/JamAIBase sur GitHub). Il compte 1 102 étoiles sur GitHub et 48 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 24 septembre 2026.
The collaborative spreadsheet for building AI apps, cell by cell.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Retrieval-augmented generation over your own documents.
A responsive interface built with current web tech.
Automate recurring scraping and data jobs.
Built to survive site changes and bot filters.
Deploy with containers in minutes.
Inspect and extend every part of the pipeline.
Download the source and move into the project folder.
git clone https://github.com/EmbeddedLLM/JamAIBase.git
cd JamAIBaseCreate a virtual environment and install the requirements.
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtStart the app or CLI and follow the README examples.
python main.py --helpIt is an open-source project at EmbeddedLLM/JamAIBase with 48 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
Yes. It is Apache-2.0 licensed, so commercial use is allowed with attribution and license notices.
Basic setup is config-driven, but custom scrapers and pipelines benefit from some Python.
It includes stealth techniques, but no tool guarantees success against every site — respect robots.txt and terms of service.
Yes, most setups support cron-style scheduling or webhook triggers.
Self-healing web scraping for AI agents, plus an MCP server.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.