Academic Idea Proposal System - Copilot Instructions

This is a Python project that builds an academic idea proposal system using LangGraph. The system uses multiple agents to search for research threads and combine ideas from different domains.

Project Context

Language: Python 3.8+
Framework: LangGraph (built on LangChain)
Purpose: Generate A+B type academic research ideas by combining insights from different fields
Architecture: Multi-agent system with state management

Code Style Guidelines

Use type hints for all function parameters and return values
Follow PEP 8 style guidelines
Use async/await patterns where appropriate for API calls
Create clear, descriptive variable and function names
Add comprehensive docstrings for all classes and functions

Key Patterns to Follow

Use LangGraph's StateGraph for building agent workflows
Implement proper state management with TypedDict and Annotated types
Use the add_messages pattern for state updates
Create modular agents that can be composed into larger workflows
Handle API errors gracefully with proper exception handling

Project Structure

```
/agents/
```
- Individual agent implementations
```
/tools/
```
- External API integrations (arXiv, Google Scholar, etc.)
```
/models/
```
- Data models and state definitions
```
/utils/
```
- Helper functions and utilities

When suggesting code:

Always include proper error handling
Use environment variables for API keys
Implement rate limiting for external API calls
Create comprehensive logging for debugging
Write modular, testable code
Consider performance implications of concurrent operations

Academic Idea Proposal System - Copilot Instructions

This is a Python project that builds an academic idea proposal system using LangGraph. The system uses multiple agents to search for research threads and combine ideas from different domains.

Project Context

Language: Python 3.8+
Framework: LangGraph (built on LangChain)
Purpose: Generate A+B type academic research ideas by combining insights from different fields
Architecture: Multi-agent system with state management

Code Style Guidelines

Use type hints for all function parameters and return values
Follow PEP 8 style guidelines
Use async/await patterns where appropriate for API calls
Create clear, descriptive variable and function names
Add comprehensive docstrings for all classes and functions

Key Patterns to Follow

Use LangGraph's StateGraph for building agent workflows
Implement proper state management with TypedDict and Annotated types
Use the add_messages pattern for state updates
Create modular agents that can be composed into larger workflows
Handle API errors gracefully with proper exception handling

Project Structure

```
/agents/
```
- Individual agent implementations
```
/tools/
```
- External API integrations (arXiv, Google Scholar, etc.)
```
/models/
```
- Data models and state definitions
```
/utils/
```
- Helper functions and utilities

When suggesting code:

Always include proper error handling
Use environment variables for API keys
Implement rate limiting for external API calls
Create comprehensive logging for debugging
Write modular, testable code
Consider performance implications of concurrent operations

<!-- Use this file to provide workspace-specific custom instructions to Copilot. For more details, visit https://code.visualstudio.com/docs/copilot/copilot-customization#_use-a-githubcopilotinstructio

Academic Idea Proposal System - Copilot Instructions

Project Context

Code Style Guidelines

Key Patterns to Follow

Project Structure

When suggesting code:

Related Skills

Markdown Converter

Nano Banana Pro

1password

Academic Idea Proposal System - Copilot Instructions

Project Context

Code Style Guidelines

Key Patterns to Follow

Project Structure

When suggesting code: