swarms

from swarms import Agent, SequentialWorkflow

# Agent 1: The Researcher
researcher = Agent(
    agent_name="Researcher",
    system_prompt="Your job is to research...",
    model_name="gpt-4o-mini",
)

# Agent 2: The Writer
writer = Agent(
    agent_name="Writer",
    system_prompt="Your job is to write...",
    model_name="gpt-4o-mini",
)

# Create workflow
workflow = SequentialWorkflow(
    agents=[researcher, writer]
)
final_post = workflow.run("AI history")

import requests

payload = {
    "agent_config": {
        "agent_name": "Research Analyst",
        "description": "Expert in analyzing research data",
        "system_prompt": "You are a Research Analyst...",
        "model_name": "gpt-4o-mini",
        "max_tokens": 8192,
        "temperature": 0.7
    },
    "task": "Analyze the impact of AI on healthcare"
}

response = requests.post(
    "https://api.swarms.world/v1/agent/completions",
    headers={"x-api-key": "your-api-key"},
    json=payload
)

use swarms_rs::llm::provider::openai::OpenAI;
use swarms_rs::structs::concurrent_workflow::ConcurrentWorkflow;

#[tokio::main]
async fn main() -> Result<()> {
    let client = OpenAI::from_url(
        base_url, api_key
    ).set_model("deepseek-chat");

    let workflow = ConcurrentWorkflow::builder()
        .name("Trading Strategy")
        .agents(vec![...])
        .build();

    let result = workflow
        .run("BTC/USD").await?;
    Ok(())
}