Deploy as a Server: Agents

pip install "praisonaiagents[api]"
export OPENAI_API_KEY="your-key"

python -m praisonai --init "helpful assistant"
python -m praisonai --serve --port 8000

📄 Loading workflow from: agents.yaml
🚀 Starting PraisonAI API server...
   Host: 127.0.0.1
   Port: 8000
🚀 Multi-Agent HTTP API available at http://127.0.0.1:8000/agents
✅ FastAPI server started at http://127.0.0.1:8000
📚 API documentation available at http://127.0.0.1:8000/docs

curl http://localhost:8000/health

from praisonaiagents import Agent

agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
    llm="gpt-4o-mini"
)
agent.launch(path="/ask", port=8000)

🚀 Agent 'Assistant' available at http://0.0.0.0:8000
✅ FastAPI server started at http://0.0.0.0:8000
📚 API documentation available at http://0.0.0.0:8000/docs
🔌 Available endpoints: /ask

curl -X POST http://localhost:8000/ask \
  -H "Content-Type: application/json" \
  -d '{"query": "Hello"}'

from praisonaiagents import Agent, Agents

researcher = Agent(name="Researcher", instructions="Research topics", llm="gpt-4o-mini")
writer = Agent(name="Writer", instructions="Write content", llm="gpt-4o-mini")

agents = Agents(agents=[researcher, writer])
agents.launch(path="/content", port=8000)

🚀 Multi-Agent HTTP API available at http://0.0.0.0:8000/content
📊 Available agents for this endpoint (2): Researcher, Writer
🔗 Per-agent endpoints: /content/researcher, /content/writer
✅ FastAPI server started at http://0.0.0.0:8000
📚 API documentation available at http://0.0.0.0:8000/docs

framework: praisonai
topic: research and write content
roles:
  researcher:
    role: Researcher
    goal: Research topics thoroughly
    backstory: Expert researcher
    tasks:
      research_task:
        description: Research the topic
        expected_output: Research findings
  writer:
    role: Writer
    goal: Write engaging content
    backstory: Expert writer
    tasks:
      write_task:
        description: Write based on research
        expected_output: Written content

python -m praisonai --serve --port 8000