Showcases
Real-world applications built with LangGraphGo.
DeerFlow
DeerFlow is a deep research system based on multi-agent architecture (Go port of ByteDance
DeerFlow). It orchestrates Planner, Researcher, and Reporter agents to conduct deep research
on a given topic and generate detailed reports.
Features: Modern Web Interface, Real-time SSE status updates, CLI support.
Open Deep Research
Go implementation of langchain-ai/open_deep_research. This is a hierarchical multi-agent
system where a Supervisor agent coordinates multiple parallel Researcher agents to conduct
comprehensive research on complex questions.
Features: Parallel execution, Tavily search integration, research
compression, configurable models.
DeepAgents
An example agent with file system access and sub-agent delegation capabilities. Demonstrates how to let agents use tools for file reading/writing, managing todo lists, and handling complex tasks.
Trading Agents
A multi-agent LLM-driven financial trading framework that simulates a professional trading firm.
Features specialized agents including fundamental analysts, sentiment analysts, news analysts,
technical analysts, research teams, traders, and risk management teams collaborating to analyze
stocks and make informed trading decisions.
Features: Real-time market data integration, Backend API server, CLI interface,
Web dashboard, Comprehensive logging and tracing.