PlanningCopilot
Tool-augmented LLM system for the full PDDL planning pipeline, improving reliability without domain-specific training.
Installation
Les étapes d'installation sont dans la documentation ci-dessous. Documentation
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Toward PDDL Planning Copilot
Getting Started
We present the Planning Copilot, a chatbot that brings together multiple planning tools and lets users run them using natural language instructions. It’s built on the Model Context Protocol (MCP), which makes it easy for language models to interact with external tools and systems.
The Planning Copilot is modular, so each part can be swapped out, upgraded, or extended without affecting the rest of the system. In the current implementation, Solve uses FastDownward for classical planning and Metric-FF for numeric planning, Verify uses VAL to validate plans, and Execute relies on PDDL_Plus_Parser to simulate and track plan execution.
Dependencies
- Make sure that Python 3.10 is installed and active (via virtual environment or conda environment).
- Install the latest version of Ollama to run it locally.
- Install all project requirements:
python -m pip install -r requirements.txt
Usage
How to use the environment:
- Update all the paths and settings in the config.py file.
- Run the LLM chat with:
python app.py - To change the LLM, edit the llm_with_tools.py file.
- To add new tools, modify the MCP server in solvers_server.py.
Citations
If you find our work interesting or the repo useful, please consider citing this paper:
@article{benyamin2025toward,
title={Toward PDDL Planning Copilot},
author={Benyamin, Yarin and Mordoch, Argaman and Shperberg, Shahaf S and Stern, Roni},
journal={arXiv preprint arXiv:2509.12987},
year={2025}
}
Questions fréquentes
Qu'est-ce que PlanningCopilot ?
Tool-augmented LLM system for the full PDDL planning pipeline, improving reliability without domain-specific training.
Comment installer PlanningCopilot ?
Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.
PlanningCopilot est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient PlanningCopilot ?
Il est publié par SPL-BGU. AI.tn le référence sans le maintenir ni le recommander.
Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.