Note: This is a readable copy of the .cursorrules file maintained for legibility. The actual rules are implemented from the .cursorrules file in the root directory.

GPT-Researcher Cursor Rules

Project Overview

This project, named GPT-Researcher, is an LLM-based autonomous agent that conducts local and web research on any topic and generates a comprehensive report with citations. It is built using Next.js and TypeScript, integrating various libraries for their strengths.

Your primary goal is to help with:

Next.js app router patterns
TypeScript type safety
Tailwind CSS best practices
Code quality standards
Python/FastAPI backend optimizations

Key URLs

Project Home Page: https://gptr.dev/
GitHub Repository: https://github.com/assafelovic/gpt-researcher
Documentation: https://docs.gptr.dev/

Project Structure

Frontend user interface built with Next.js, TypeScript, and Tailwind CSS in /frontend
- Static FastAPI version for lightweight deployments
- Next.js version for production use with enhanced features
Multi-agent research system using LangChain and LangGraph in /backend/multi_agents
- Browser, Editor, Researcher, Reviewer, Revisor, Writer, and Publisher agents
- Task configuration and agent coordination
Document processing using Unstructured and PyMuPDF in /backend/document_processing
- PDF, DOCX, and web content parsing
- Text extraction and preprocessing
Report generation using LangChain and Jinja2 templates in /backend/report_generation
- Template-based report structuring
- Dynamic content formatting
Multiple output formats in /backend/output_formats
- PDF via md2pdf
- Markdown via mistune
- DOCX via python-docx
- Format conversion utilities
- Export functionality
GPT Researcher core functionality in /gpt_researcher
- Web scraping and content aggregation
- Research planning and execution
- Source validation and tracking
- Query processing and response generation
Testing infrastructure in /tests
- Unit tests for individual components
- Integration tests for agent interactions
- End-to-end research workflow tests
- Mock data and fixtures for testing

Language Model Configuration

Default model: gpt-4-turbo
Alternative models: gpt-3.5-turbo, claude-3-opus
Temperature settings for different tasks
Context window management
Token limit handling
Cost optimization strategies

Error Handling

Research failure recovery
API rate limiting
Network timeout handling
Invalid input management
Source validation errors
Report generation failures

Performance

Parallel processing strategies
Caching mechanisms
Memory management
Response streaming
Resource allocation
Query optimization

Development Workflow

Branch naming conventions
Commit message format
PR review process
Testing requirements
Documentation updates
Version control guidelines

API Documentation

REST endpoints
WebSocket events
Request/Response formats
Authentication methods
Rate limits
Error codes

Monitoring

Performance metrics
Error tracking
Usage statistics
Cost monitoring
Research quality metrics
User feedback tracking

Frontend Components

Static FastAPI version for lightweight deployments
Next.js version for production use with enhanced features

Backend Components

Multi-agent system architecture
Document processing pipeline
Report generation system
Output format handlers

Core Research Components

Web scraping and aggregation
Research planning and execution
Source validation
Query processing

Testing

Unit tests
Integration tests
End-to-end tests
Performance testing

Rule Violation Monitoring

Alert developer when changes conflict with project structure
Warn about deviations from coding standards
Flag unauthorized framework or library additions
Monitor for security and performance anti-patterns
Track API usage patterns that may violate guidelines
Report TypeScript strict mode violations
Identify accessibility compliance issues

Development Guidelines

Use TypeScript with strict mode enabled
Follow ESLint and Prettier configurations
Ensure components are responsive and accessible
Use Tailwind CSS for styling, following the project's design system
Minimize AI-generated comments, prefer self-documenting code
Follow React best practices and hooks guidelines
Validate all user inputs and API responses
Use existing components as reference implementations

Important Scripts

npm run dev: Start development server
npm run build: Build for production
npm run test: Run test suite
python -m pytest: Run Python tests
python -m uvicorn backend.server.server:app --host=0.0.0.0 --port=8000: Start FastAPI server
python -m uvicorn backend.server.server:app --reload: Start FastAPI server with auto-reload for development
python main.py: Run the main application directly
docker-compose up: Start all services
docker-compose run gpt-researcher-tests: Run test suite in container

AI Integration Guidelines

Prioritize type safety in all AI interactions
Follow LangChain and LangGraph best practices
Implement proper error handling for AI responses
Maintain context window limits
Handle rate limiting and API quotas
Validate AI outputs before processing
Log AI interactions for debugging

Lexicon

GPT Researcher: Autonomous research agent system
Multi-Agent System: Coordinated AI agents for research tasks
Research Pipeline: End-to-end research workflow
Agent Roles: Browser, Editor, Researcher, Reviewer, Revisor, Writer, Publisher
Source Validation: Verification of research sources
Report Generation: Process of creating final research output

Additional Resources

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