how-to-setup-a-multi-agent-system-bookmark-it-the-trading

CloudAI-X (@cloudxdev)

2025-12-29 | ❤️ 601 | 🔁 51

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How to setup a multi agent system? Bookmark it 📂

“The Trading Floor”

Multi-Agent Market Analysis Council to analyze a stock ticker

@Zai_org GLM-4.7 🤝 @opencode

Agent framework: @crewAIInc

How it works?

1. User enters a stock ticker to analyze
2. 5 AI agents wake up, each with distinct expertise:
   • Quant Analyst — technical indicators & price patterns
   • Sentiment Scout — market mood & crowd psychology
   • Macro Strategist — sector dynamics & economic context
   • Risk Manager — volatility, drawdowns & position sizing
   • Portfolio Chief — synthesizes all perspectives
3. Agents analyze independently using real market data
4. They debate, challenge assumptions, and identify disagreements
5. Portfolio Chief resolves conflicts and delivers a consensus recommendation
6. Final output: buy/hold/sell rating with confidence level, position size, and key risks

How to built The Trading Floor?

1. Chose CrewAI as the agent framework — handles multi-agent orchestration out of the box
2. Defined 5 agents with distinct roles, goals, and backstories in Python
3. Built custom tools wrapping yfinance for real market data (prices, indicators, volatility)
4. Configured sequential workflow — specialists analyze first, Portfolio Chief synthesizes last
5. Set up FastAPI backend with SSE to stream agent thoughts in real-time
6. Built Next.js frontend to visualize the “board of directors” deliberating live
7. One environment variable (MODEL=openai/gpt-5.2) powers all agents
8. Generated unique agent icons with AI image tools Total cost: $0 for the framework, pay only for LLM API calls

Tech stack:

• GLM-4.7 with opencode to build the app
• CrewAI (open source) for agent orchestration
• GPT-5.2 powering each agent
• FastAPI + SSE for real-time streaming
• Next.js frontend showing live agent deliberations

미디어

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Tags

3D AI-ML LLM