Debate with judge

import requests
import json

API_BASE_URL = "https://api.swarms.world"
API_KEY = "your_api_key_here"

headers = {
    "x-api-key": API_KEY,
    "Content-Type": "application/json"
}

swarm_config = {
    "name": "Work Policy Debate",
    "description": "Structured debate on workplace policy with judge evaluation",
    "swarm_type": "DebateWithJudge",
    "task": "Should companies adopt a mandatory 4-day work week? Consider productivity impact, employee wellbeing, competitive dynamics, and implementation challenges.",
    "agents": [
        {
            "agent_name": "Pro Advocate",
            "description": "Argues in favor of the proposition with evidence-based reasoning",
            "system_prompt": "You are an expert debater arguing IN FAVOR of the proposition. Present compelling, well-structured arguments supported by evidence, data, and concrete examples. Anticipate counterarguments and address them proactively. If this is a refinement round, strengthen your arguments based on the judge feedback.",
            "model_name": "gpt-4o",
            "max_loops": 1,
            "temperature": 0.5
        },
        {
            "agent_name": "Con Advocate",
            "description": "Argues against the proposition with evidence-based reasoning",
            "system_prompt": "You are an expert debater arguing AGAINST the proposition. Present compelling counter-arguments, identify weaknesses, risks, and unintended consequences. Challenge assumptions with data and real-world examples. If this is a refinement round, strengthen your opposition based on the judge feedback.",
            "model_name": "gpt-4o",
            "max_loops": 1,
            "temperature": 0.5
        },
        {
            "agent_name": "Impartial Judge",
            "description": "Evaluates arguments from both sides and provides synthesis",
            "system_prompt": "You are an impartial judge evaluating a structured debate. Objectively assess the strength of arguments from both sides based on logical coherence, evidence quality, and persuasiveness. Identify the strongest points from each side and synthesize them into a balanced, well-reasoned conclusion. Provide a clear final verdict with justification.",
            "model_name": "gpt-4o",
            "max_loops": 1,
            "temperature": 0.3
        }
    ],
    "max_loops": 1
}

response = requests.post(
    f"{API_BASE_URL}/v1/swarm/completions",
    headers=headers,
    json=swarm_config
)

if response.status_code == 200:
    result = response.json()
    print(json.dumps(result["output"], indent=2))
else:
    print(f"Error: {response.status_code} - {response.text}")

const API_BASE_URL = "https://api.swarms.world";
const API_KEY = "your_api_key_here";

const headers = {
    "x-api-key": API_KEY,
    "Content-Type": "application/json"
};

const swarmConfig = {
    name: "Work Policy Debate",
    description: "Structured debate on workplace policy with judge evaluation",
    swarm_type: "DebateWithJudge",
    task: "Should companies adopt a mandatory 4-day work week? Consider productivity impact, employee wellbeing, competitive dynamics, and implementation challenges.",
    agents: [
        {
            agent_name: "Pro Advocate",
            description: "Argues in favor of the proposition with evidence-based reasoning",
            system_prompt: "You are an expert debater arguing IN FAVOR of the proposition. Present compelling, well-structured arguments supported by evidence, data, and concrete examples. Anticipate counterarguments and address them proactively. If this is a refinement round, strengthen your arguments based on the judge feedback.",
            model_name: "gpt-4o",
            max_loops: 1,
            temperature: 0.5
        },
        {
            agent_name: "Con Advocate",
            description: "Argues against the proposition with evidence-based reasoning",
            system_prompt: "You are an expert debater arguing AGAINST the proposition. Present compelling counter-arguments, identify weaknesses, risks, and unintended consequences. Challenge assumptions with data and real-world examples. If this is a refinement round, strengthen your opposition based on the judge feedback.",
            model_name: "gpt-4o",
            max_loops: 1,
            temperature: 0.5
        },
        {
            agent_name: "Impartial Judge",
            description: "Evaluates arguments from both sides and provides synthesis",
            system_prompt: "You are an impartial judge evaluating a structured debate. Objectively assess the strength of arguments from both sides based on logical coherence, evidence quality, and persuasiveness. Identify the strongest points from each side and synthesize them into a balanced, well-reasoned conclusion. Provide a clear final verdict with justification.",
            model_name: "gpt-4o",
            max_loops: 1,
            temperature: 0.3
        }
    ],
    max_loops: 1
};

fetch(`${API_BASE_URL}/v1/swarm/completions`, {
    method: "POST",
    headers: headers,
    body: JSON.stringify(swarmConfig)
})
.then(response => response.json())
.then(result => {
    if (result.status === "success") {
        console.log("DebateWithJudge swarm completed successfully!");
        result.output.forEach(output => {
            console.log(`\n${output.role}: ${output.content}`);
        });
    }
})
.catch(error => console.error("Error:", error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

type Agent struct {
    AgentName    string  `json:"agent_name"`
    Description  string  `json:"description"`
    SystemPrompt string  `json:"system_prompt"`
    ModelName    string  `json:"model_name"`
    MaxLoops     int     `json:"max_loops"`
    Temperature  float64 `json:"temperature"`
}

type SwarmConfig struct {
    Name        string  `json:"name"`
    Description string  `json:"description"`
    SwarmType   string  `json:"swarm_type"`
    Task        string  `json:"task"`
    Agents      []Agent `json:"agents"`
    MaxLoops    int     `json:"max_loops"`
}

func main() {
    API_BASE_URL := "https://api.swarms.world"
    API_KEY := "your_api_key_here"

    swarmConfig := SwarmConfig{
        Name:        "Work Policy Debate",
        Description: "Structured debate on workplace policy with judge evaluation",
        SwarmType:   "DebateWithJudge",
        Task:        "Should companies adopt a mandatory 4-day work week? Consider productivity impact, employee wellbeing, competitive dynamics, and implementation challenges.",
        Agents: []Agent{
            {
                AgentName:    "Pro Advocate",
                Description:  "Argues in favor of the proposition with evidence-based reasoning",
                SystemPrompt: "You are an expert debater arguing IN FAVOR of the proposition. Present compelling, well-structured arguments supported by evidence, data, and concrete examples. Anticipate counterarguments and address them proactively. If this is a refinement round, strengthen your arguments based on the judge feedback.",
                ModelName:    "gpt-4o",
                MaxLoops:     1,
                Temperature:  0.5,
            },
            {
                AgentName:    "Con Advocate",
                Description:  "Argues against the proposition with evidence-based reasoning",
                SystemPrompt: "You are an expert debater arguing AGAINST the proposition. Present compelling counter-arguments, identify weaknesses, risks, and unintended consequences. Challenge assumptions with data and real-world examples. If this is a refinement round, strengthen your opposition based on the judge feedback.",
                ModelName:    "gpt-4o",
                MaxLoops:     1,
                Temperature:  0.5,
            },
            {
                AgentName:    "Impartial Judge",
                Description:  "Evaluates arguments from both sides and provides synthesis",
                SystemPrompt: "You are an impartial judge evaluating a structured debate. Objectively assess the strength of arguments from both sides based on logical coherence, evidence quality, and persuasiveness. Identify the strongest points from each side and synthesize them into a balanced, well-reasoned conclusion. Provide a clear final verdict with justification.",
                ModelName:    "gpt-4o",
                MaxLoops:     1,
                Temperature:  0.3,
            },
        },
        MaxLoops: 1,
    }

    jsonData, _ := json.Marshal(swarmConfig)

    req, _ := http.NewRequest("POST", API_BASE_URL+"/v1/swarm/completions", bytes.NewBuffer(jsonData))
    req.Header.Set("x-api-key", API_KEY)
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        fmt.Printf("Error: %v\n", err)
        return
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Printf("Response: %s\n", string(body))
}

use reqwest::Client;
use serde_json::{json, Value};
use std::error::Error;

#[tokio::main]
async fn main() -> Result<(), Box<dyn Error>> {
    let api_base_url = "https://api.swarms.world";
    let api_key = "your_api_key_here";

    let swarm_config = json!({
        "name": "Work Policy Debate",
        "description": "Structured debate on workplace policy with judge evaluation",
        "swarm_type": "DebateWithJudge",
        "task": "Should companies adopt a mandatory 4-day work week? Consider productivity impact, employee wellbeing, competitive dynamics, and implementation challenges.",
        "agents": [
            {
                "agent_name": "Pro Advocate",
                "description": "Argues in favor of the proposition with evidence-based reasoning",
                "system_prompt": "You are an expert debater arguing IN FAVOR of the proposition. Present compelling, well-structured arguments supported by evidence, data, and concrete examples. Anticipate counterarguments and address them proactively. If this is a refinement round, strengthen your arguments based on the judge feedback.",
                "model_name": "gpt-4o",
                "max_loops": 1,
                "temperature": 0.5
            },
            {
                "agent_name": "Con Advocate",
                "description": "Argues against the proposition with evidence-based reasoning",
                "system_prompt": "You are an expert debater arguing AGAINST the proposition. Present compelling counter-arguments, identify weaknesses, risks, and unintended consequences. Challenge assumptions with data and real-world examples. If this is a refinement round, strengthen your opposition based on the judge feedback.",
                "model_name": "gpt-4o",
                "max_loops": 1,
                "temperature": 0.5
            },
            {
                "agent_name": "Impartial Judge",
                "description": "Evaluates arguments from both sides and provides synthesis",
                "system_prompt": "You are an impartial judge evaluating a structured debate. Objectively assess the strength of arguments from both sides based on logical coherence, evidence quality, and persuasiveness. Identify the strongest points from each side and synthesize them into a balanced, well-reasoned conclusion. Provide a clear final verdict with justification.",
                "model_name": "gpt-4o",
                "max_loops": 1,
                "temperature": 0.3
            }
        ],
        "max_loops": 1
    });

    let client = Client::new();
    let response = client
        .post(&format!("{}/v1/swarm/completions", api_base_url))
        .header("x-api-key", api_key)
        .header("Content-Type", "application/json")
        .json(&swarm_config)
        .send()
        .await?;

    if response.status().is_success() {
        let result: Value = response.json().await?;
        println!("DebateWithJudge swarm completed successfully!");
        println!("Response: {:?}", result);
    } else {
        println!("Error: {}", response.status());
    }

    Ok(())
}