Serve

praisonai serve agents.yaml

# Start server with default settings (port 8005, host 127.0.0.1)
praisonai serve agents.yaml

📄 Loading agents from: agents.yaml
  ✓ Loaded: Researcher
  ✓ Loaded: Writer
  ✓ Loaded: Editor

🚀 Starting PraisonAI API server...
   Host: 127.0.0.1
   Port: 8005
   Agents: 3
🚀 Multi-Agent HTTP API available at http://127.0.0.1:8005/agents
📊 Available agents for this endpoint (3): Researcher, Writer, Editor
🔗 Per-agent endpoints: /agents/researcher, /agents/writer, /agents/editor
✅ FastAPI server started at http://127.0.0.1:8005
📚 API documentation available at http://127.0.0.1:8005/docs

# Custom port
praisonai serve agents.yaml --port 9000

# Custom host (allow external connections)
praisonai serve agents.yaml --host 0.0.0.0

# Both custom
praisonai serve agents.yaml --port 8080 --host 0.0.0.0

# Using --serve flag instead of serve command
praisonai agents.yaml --serve

# With options
praisonai agents.yaml --serve --port 8005

curl -X POST http://127.0.0.1:8005/agents \
  -H "Content-Type: application/json" \
  -d '{"query": "Research AI trends and write a summary"}'

{
  "query": "Research AI trends and write a summary",
  "results": [
    {"agent": "Researcher", "response": "...research findings..."},
    {"agent": "Writer", "response": "...written summary..."},
    {"agent": "Editor", "response": "...edited content..."}
  ],
  "final_response": "...final edited content..."
}

# Run only the researcher agent
curl -X POST http://127.0.0.1:8005/agents/researcher \
  -H "Content-Type: application/json" \
  -d '{"query": "What are the latest AI trends?"}'

{
  "agent": "Researcher",
  "query": "What are the latest AI trends?",
  "response": "...research findings..."
}

curl http://127.0.0.1:8005/agents/list

{
  "agents": [
    {"name": "Researcher", "id": "researcher"},
    {"name": "Writer", "id": "writer"},
    {"name": "Editor", "id": "editor"}
  ]
}

name: Content Creation Pipeline
description: Research, write, and edit content

agents:
  researcher:
    name: Researcher
    role: Research Specialist
    goal: Find accurate and relevant information
    backstory: Expert at finding and synthesizing information
    llm: gpt-4o-mini

  writer:
    name: Writer
    role: Content Writer
    goal: Create engaging content from research
    backstory: Skilled writer who transforms research into readable content
    llm: gpt-4o-mini

  editor:
    name: Editor
    role: Content Editor
    goal: Polish and improve written content
    backstory: Meticulous editor ensuring quality and clarity
    llm: gpt-4o-mini

# Terminal 1: Start the API server
praisonai serve agents.yaml --port 8005

# Terminal 2: Create n8n workflow
praisonai agents.yaml --n8n

from praisonaiagents import Agent, PraisonAIAgents
import yaml

# Load agents from YAML
with open('agents.yaml', 'r') as f:
    config = yaml.safe_load(f)

agents = []
for agent_id, cfg in config['agents'].items():
    agent = Agent(
        name=cfg.get('name', agent_id),
        role=cfg.get('role', ''),
        goal=cfg.get('goal', ''),
        llm=cfg.get('llm', 'gpt-4o-mini')
    )
    agents.append(agent)

# Start server
praison = PraisonAIAgents(agents=agents)
praison.launch(port=8005, host='127.0.0.1')