Quick Start

runagent run --id agent_abc123 --local --tag minimal \
  --message "Explain why the sky is blue" \
  --role user

🚀 RunAgent Configuration:
   Agent ID: agent_abc123
   Tag: minimal
   Local: Yes
🔍 Auto-resolved address: 127.0.0.1:8000
🤖 Executing agent: agent_abc123
✅ Agent execution completed!

The sky appears blue due to a phenomenon called Rayleigh scattering...

from runagent import RunAgentClient

# Connect to your agent (replace with your actual agent_id)
ra = RunAgentClient(
    agent_id="agent_abc123",
    entrypoint_tag="minimal",
    local=True
)

# Call your agent like it's a local function
result = ra.run(
    message="Analyze the benefits of remote work for software teams",
    role="user"
)
print(result)

npm install runagent

import { RunAgentClient } from 'runagent';

const ra = new RunAgentClient({
  agentId: "agent_abc123",
  entrypointTag: "minimal", 
  local: true
});

await ra.initialize();

const result = await ra.run({
  message: 'What makes a great engineering team?',
  role: 'user'
});

console.log(result);

from runagent import RunAgentClient

ra = RunAgentClient(
    host="localhost",
    port=8000,
    entrypoint_tag="minimal",
    local=True
)

result = ra.run(message="Hello from any language!")
print(result)

runagent run --id agent_abc123 --local --tag minimal_stream \
  --message "Write a creative story about AI agents"

🚀 RunAgent Configuration:
   Agent ID: agent_abc123
   Tag: minimal_stream
   Local: Yes
🔍 Auto-resolved address: 127.0.0.1:8000

Once
 upon
 a
 time,
 in
 a
 digital
 realm
 far
 beyond
 the
 clouds...
[STREAM COMPLETE]

from runagent import RunAgentClient

# Connect to streaming entrypoint (note the '_stream' tag)
ra = RunAgentClient(
    agent_id="agent_abc123", 
    entrypoint_tag="minimal_stream",
    local=True
)

# Stream responses as they generate
for chunk in ra.run(
    message="Explain quantum computing step by step"
):
    print(chunk, end="", flush=True)

import { RunAgentClient } from 'runagent';

const ra = new RunAgentClient({
  agentId: "agent_abc123",
  entrypointTag: "minimal_stream",  // The magic '_stream' suffix
  local: true
});

await ra.initialize();

const stream = await ra.run({
  message: 'Write a poem about coding'
});

// Modern JavaScript async iteration
for await (const chunk of stream) {
  process.stdout.write(chunk);
}

use runagent::client::RunAgentClient;
use serde_json::json;
use futures::StreamExt;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let client = RunAgentClient::new("agent_abc123", "minimal_stream", true).await?;
    
    let mut stream = client.run_stream(&[
        ("message", json!("Explain machine learning concepts"))
    ]).await?;
    
    while let Some(chunk) = stream.next().await {
        print!("{}", chunk?);
    }
    
    Ok(())
}

runagent init my_langgraph_agent --langgraph
cd my_langgraph_agent

# Add your AI power
echo "OPENAI_API_KEY=your-key-here" > .env

# Install and activate
pip install -r requirements.txt
runagent serve .

runagent init my_crew_agent --crewai
cd my_crew_agent

# Configure your AI crew
echo "OPENAI_API_KEY=your-key-here" > .env
pip install -r requirements.txt
runagent serve .

runagent init my_custom_agent
cd my_custom_agent

# Edit main.py with your framework
# Update runagent.config.json with your entrypoints
runagent serve .