OpenAI SDK

import OpenAI from "openai";

const openai = new OpenAI();

const WORKSPACE_ID = "ws_123";
const ARG_API_KEY = "YOUR_API_KEY";
const ARG_BASE = "https://api.arg.ai/api";

// Define arg.ai workspace tools
const tools: OpenAI.ChatCompletionTool[] = [
  {
    type: "function",
    function: {
      name: "run_bash",
      description: "Run a shell command in the workspace sandbox",
      parameters: {
        type: "object",
        properties: { command: { type: "string" } },
        required: ["command"],
      },
    },
  },
  {
    type: "function",
    function: {
      name: "read_file",
      description: "Read a file from the workspace",
      parameters: {
        type: "object",
        properties: {
          path: { type: "string" },
          offset: { type: "integer" },
          limit: { type: "integer" },
        },
        required: ["path"],
      },
    },
  },
  {
    type: "function",
    function: {
      name: "write_file",
      description: "Write a file to the workspace",
      parameters: {
        type: "object",
        properties: {
          path: { type: "string" },
          content: { type: "string" },
        },
        required: ["path", "content"],
      },
    },
  },
  {
    type: "function",
    function: {
      name: "edit_file",
      description: "Replace a string in a file",
      parameters: {
        type: "object",
        properties: {
          path: { type: "string" },
          old_string: { type: "string" },
          new_string: { type: "string" },
        },
        required: ["path", "old_string", "new_string"],
      },
    },
  },
  {
    type: "function",
    function: {
      name: "grep",
      description: "Search file contents with a regex pattern",
      parameters: {
        type: "object",
        properties: {
          pattern: { type: "string" },
          path: { type: "string" },
          include: { type: "string" },
        },
        required: ["pattern"],
      },
    },
  },
];

// Map tool names to arg.ai endpoints
const TOOL_ENDPOINTS: Record<string, string> = {
  run_bash: "run-bash",
  read_file: "read-file",
  write_file: "write-file",
  edit_file: "edit-file",
  grep: "grep",
};

async function callTool(name: string, args: Record<string, unknown>) {
  const endpoint = TOOL_ENDPOINTS[name];
  const res = await fetch(
    `${ARG_BASE}/workspaces/${WORKSPACE_ID}/tools/${endpoint}`,
    {
      method: "POST",
      headers: {
        "X-API-Key": ARG_API_KEY,
        "Content-Type": "application/json",
      },
      body: JSON.stringify(args),
    }
  );
  return res.json();
}

// Agent loop
const messages: OpenAI.ChatCompletionMessageParam[] = [
  { role: "user", content: "List the files in /home/user/project and read the README" },
];

while (true) {
  const response = await openai.chat.completions.create({
    model: "o4-mini",
    tools,
    messages,
  });

  const choice = response.choices[0];
  messages.push(choice.message);

  if (choice.finish_reason === "tool_calls") {
    for (const call of choice.message.tool_calls!) {
      const result = await callTool(call.function.name, JSON.parse(call.function.arguments));
      messages.push({
        role: "tool",
        tool_call_id: call.id,
        content: JSON.stringify(result),
      });
    }
  } else {
    console.log(choice.message.content);
    break;
  }
}

import json
import requests
import openai

WORKSPACE_ID = "ws_123"
ARG_API_KEY = "YOUR_API_KEY"
ARG_BASE = "https://api.arg.ai/api"

# Define arg.ai workspace tools
tools = [
    {
        "type": "function",
        "function": {
            "name": "run_bash",
            "description": "Run a shell command in the workspace sandbox",
            "parameters": {
                "type": "object",
                "properties": {"command": {"type": "string"}},
                "required": ["command"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "read_file",
            "description": "Read a file from the workspace",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {"type": "string"},
                    "offset": {"type": "integer"},
                    "limit": {"type": "integer"},
                },
                "required": ["path"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "write_file",
            "description": "Write a file to the workspace",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {"type": "string"},
                    "content": {"type": "string"},
                },
                "required": ["path", "content"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "edit_file",
            "description": "Replace a string in a file",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {"type": "string"},
                    "old_string": {"type": "string"},
                    "new_string": {"type": "string"},
                },
                "required": ["path", "old_string", "new_string"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "grep",
            "description": "Search file contents with a regex pattern",
            "parameters": {
                "type": "object",
                "properties": {
                    "pattern": {"type": "string"},
                    "path": {"type": "string"},
                    "include": {"type": "string"},
                },
                "required": ["pattern"],
            },
        },
    },
]

TOOL_ENDPOINTS = {
    "run_bash": "run-bash",
    "read_file": "read-file",
    "write_file": "write-file",
    "edit_file": "edit-file",
    "grep": "grep",
}


def call_tool(name: str, args: dict) -> dict:
    endpoint = TOOL_ENDPOINTS[name]
    resp = requests.post(
        f"{ARG_BASE}/workspaces/{WORKSPACE_ID}/tools/{endpoint}",
        headers={"X-API-Key": ARG_API_KEY, "Content-Type": "application/json"},
        json=args,
    )
    return resp.json()


# Agent loop
client = openai.OpenAI()
messages = [
    {"role": "user", "content": "List the files in /home/user/project and read the README"},
]

while True:
    response = client.chat.completions.create(
        model="o4-mini",
        tools=tools,
        messages=messages,
    )

    choice = response.choices[0]
    messages.append(choice.message)

    if choice.finish_reason == "tool_calls":
        for call in choice.message.tool_calls:
            result = call_tool(call.function.name, json.loads(call.function.arguments))
            messages.append({
                "role": "tool",
                "tool_call_id": call.id,
                "content": json.dumps(result),
            })
    else:
        print(choice.message.content)
        break