35 rules available in the Cursor directory
Cursor rules for Python FastAPI projects enforcing async patterns, Pydantic v2 models, dependency injection, and proper error handling.
- Write concise, technical responses with accurate Python examples.
- Design services to be stateless; leverage external storage and caches (e.g., Redis) for state persistence.
This is the context and rules for all responses about our "Slack to FAQ" app. The app turns Slack messages into easy-to-search FAQs for teams. We're building v1 to start. Use this to guide all your answers. Always follow the rules exactly.
- NEVER hardcode `localhost` or `127.0.0.1` into the `docker-compose.yml` environment blocks. Always use dynamic variables (e.g., `${VITE_API_BASE_URL:-http://localhost:8000}`) so the configuration can adapt to production environments.
**Name:** AI Chatbot Lite
Here are some best practices and rules you must follow:- You use Python 3.12- Frameworks: - pydantic - fastapi - sqlalchemy- You use poetry for dependency management- You use alembic for database migrations- You use fastapi-users for user management- You use fastapi-jwt-auth for authentication- You
> 目标:让任意新 AI 在接手时,能稳定产出符合本项目习惯的改动。
This is an AI-powered financial technology application that uses machine learning to generate Financial Profile Scores (FPS) from transaction data. The project consists of:
project_name: "TaskPilot"
This is a dynamic form chatbot project using LangGraph + LangChain for backend, LobeChat for frontend, and Railway for deployment. The system uses JSON Schema + Pydantic for configuration and validation.
Full-stack GraphRAG application modeling **Philadelphia's** restaurant hype ecosystem. Ingests Yelp Open Dataset, builds bipartite + projected networks, computes graph metrics, loads into Neo4j, and exposes a conversational AI interface over the graph with interactive network visualizations. (Target
This is a community-driven ride-sharing application connecting Catholics who need transportation to Mass, Confession, prayer events, and church social functions with volunteer drivers.
- **One Layer, One Responsibility**: Each layer has a single, well-defined responsibility
Clear project structure with separate directories for source code, tests, docs, and config.
This is a sophisticated biblical text analysis project focused on the Documentary Hypothesis in the King James Version of the Bible. The project parses color-coded wikitext files to extract and analyze different source traditions (J, E, P, D, R) and provides multiple data formats for LLM training an
Always use type hints.
- **Backend:** FastAPI (Python 3.12+), SQLModel, SQLAlchemy, Pydantic v2.
- You are a **Python master**, a highly experienced **tutor**, a **world-renowned ML engineer**, and a **talented data scientist**.
Astroloh is a professional astrological voice skill for Yandex Alice built with FastAPI, PostgreSQL, and Kerykeion 4.x for advanced astronomical calculations.
Use the Python standard library as much as possible.
- Primary package: `src/company_researcher/`
@.cursorrules - Non-Negotiable Quality & Code Mandate
- Aviation fuel hedging optimization platform for an airline