Built-in Tools

import { LlmAgent, GoogleSearch, HttpRequestTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "research_agent",
  description:
    "An agent that helps users research topics using web search and HTTP requests.",
  instruction: "Help users research topics using web search and HTTP requests",
  tools: [new GoogleSearch(), new HttpRequestTool()],
});

import { LlmAgent, GoogleSearch } from "@iqai/adk";

const agent = new LlmAgent({
  name: "research_agent",
  description: "A research assistant that searches the web for information",
  tools: [new GoogleSearch()],
});

// User: "What are the latest updates about AI in 2024?"
// Agent internally decides it needs current information, so it calls:
// google_search({ query: "latest AI updates 2024", num_results: 5 })
// Agent receives search results and summarizes them for the user

import { LlmAgent, HttpRequestTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "api_agent",
  description: "An agent that integrates with external APIs and services",
  tools: [new HttpRequestTool()],
});

// User: "Get the weather from the API"
// Agent calls:
// http_request({
//   url: "https://api.weather.com/forecast?city=london",
//   method: "GET",
//   headers: { "Authorization": "Bearer YOUR_API_KEY" }
// })
// Agent receives the response and processes it

import { LlmAgent, FileOperationsTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "file_agent",
  description: "An agent that manages file operations on the local filesystem",
  tools: [
    new FileOperationsTool({
      basePath: "/safe/directory", // Optional, defaults to cwd
    }),
  ],
});

// User: "Save this data to a file called results.txt"
// Agent calls:
// file_operations({
//   operation: "write",
//   path: "results.txt",
//   content: "The data to save"
// })
// Agent: "Saved data to results.txt"

// User: "Read the contents of config.json"
// Agent calls:
// file_operations({
//   operation: "read",
//   path: "config.json"
// })
// Agent reads and displays the content

import { LlmAgent, UserInteractionTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "approval_agent",
  description: "An agent that handles user approvals and confirmations",
  tools: [new UserInteractionTool()],
});

// User: "I want to delete my account"
// Agent internally decides it needs confirmation, so it calls user_interaction:

// The agent LLM generates a call like:
// user_interaction({
//   prompt: "Are you absolutely sure you want to delete your account? This cannot be undone.",
//   options: ["Yes, delete it", "No, keep it"]
// })

// User sees: "Are you absolutely sure you want to delete your account? This cannot be undone?"
//            1. Yes, delete it
//            2. No, keep it
// User chooses: 1
// Agent receives: "Yes, delete it" and proceeds with deletion

import { LlmAgent, LoadMemoryTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "context_agent",
  description: "An agent that maintains context across conversations",
  tools: [new LoadMemoryTool()],
});

// User: "What did I ask you about last time?"
// Agent calls:
// load_memory({ query: "previous conversation topics" })
// Agent retrieves relevant memories and responds with the information

// User: "I have that preference set, right?"
// Agent calls:
// load_memory({ query: "user preferences" })
// Agent confirms based on retrieved memory

import { LlmAgent, LoadArtifactsTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "document_analyzer_agent",
  description: "An agent that analyzes and processes uploaded documents",
  tools: [new LoadArtifactsTool()],
});

// User uploads files and asks: "Analyze my resume"
// Agent calls:
// load_artifacts({ artifact_names: ["resume.pdf"] })
// Agent retrieves the uploaded resume and analyzes it

// User: "What's in the contract?"
// Agent calls:
// load_artifacts({ artifact_names: ["contract.pdf"] })
// Agent reads and analyzes the contract

import { LlmAgent, GetUserChoiceTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "choice_agent",
  description: "An agent that presents options and collects user selections",
  tools: [new GetUserChoiceTool()],
});

// User: "I want to choose a subscription plan"
// Agent calls:
// get_user_choice({
//   question: "Which plan would you like?",
//   options: ["Basic - $9/month", "Pro - $29/month", "Enterprise - $99/month"]
// })
// User sees numbered options and selects one
// Agent receives the selected option and proceeds

import { LlmAgent, TransferToAgentTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "router_agent",
  description: "An agent that routes requests to specialized agents",
  tools: [new TransferToAgentTool()],
});

// User: "I need help with my payment"
// Router agent recognizes this is a payment issue and calls:
// transfer_to_agent({ agent_name: "payment_specialist_agent" })
// Control transfers to the payment specialist agent

// User: "Can you check my order status?"
// Router agent calls:
// transfer_to_agent({ agent_name: "order_tracking_agent" })
// Control transfers to the order tracking agent

import { LlmAgent, ExitLoopTool } from "@iqai/adk";

const agent = new LlmAgent({
  name: "loop_agent",
  description: "An agent that processes items in loops with exit control",
  tools: [new ExitLoopTool()],
});

// Agent is processing items in a loop
// When instructed to exit, agent calls:
// exit_loop()
// Loop execution terminates and control returns to parent workflow

// Example workflow:
// Agent: Processing item 1... done
// Agent: Processing item 2... done
// Agent: Processing item 3... done
// Agent: All items processed, calling exit_loop()
// Workflow exits loop successfully

const researchAgent = new LlmAgent({
  name: "researcher_agent",
  description:
    "A research assistant that searches the web for current information and recalls relevant details from previous conversations to provide comprehensive, context-aware answers",
  instruction:
    "Use web search to find current information, then check memory for related previous discussions to provide complete context",
  tools: [new GoogleSearch(), new LoadMemoryTool()],
});

const documentAgent = new LlmAgent({
  name: "document_processor_agent",
  description:
    "An agent that analyzes uploaded documents, extracts key information, and saves processed results or reports to the filesystem",
  instruction:
    "Load and analyze uploaded documents, then save your findings, summaries, or processed data to files for future reference",
  tools: [
    new LoadArtifactsTool(),
    new FileOperationsTool({ basePath: "/output" }),
  ],
});

const apiAgent = new LlmAgent({
  name: "api_integration_agent",
  description:
    "An agent that calls external APIs to fetch data, processes the responses, and saves important information to files for later analysis or caching",
  instruction:
    "Make API calls to retrieve data, process the responses, and save relevant information to files for future reference or analysis",
  tools: [new HttpRequestTool(), new FileOperationsTool()],
});

const interactiveAgent = new LlmAgent({
  name: "interactive_workflow_agent",
  description:
    "An agent that guides users through multi-step processes, collects their input and confirmations, and manages files as part of the workflow",
  instruction:
    "Interact with users to gather requirements and approvals, then perform file operations based on their input and decisions",
  tools: [new UserInteractionTool(), new FileOperationsTool()],
});