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Each integration takes an API key, your API base URL (https://api.answerline.dev) and the engines to offer. Leave engines at their default or set them to the engines available to you, ["CHATGPT","GEMINI","PERPLEXITY","COPILOT","GROK","AIMODE","GOOGLE","GOOGLE_NEWS"] today.

n8n

Install the community node n8n-nodes-answerline, then create its credentials; n8n tests them with GET /v1/credits. Operations:

• Run Monitor: an engine's prompt or query, country and additional request fields as JSON, answered synchronously. For Google, a url in the additional fields replaces the query and country.
• Create Task: the same request as an async task, with priority, idempotency key and webhook URL.
• Get Task: status and result of a task.
• Get Credits: your remaining balance in dollars.

With Continue On Fail, a failed item outputs the error message, its description and the HTTP status.

Zapier

Connect the app with the same three settings; engines are a comma-separated list of task types.

• Run Monitor: an engine's request, run as an async task; the Zap continues with the answer, charged at the task price.
• Create Task: queues the request with the Zap's callback URL as its webhook; the Zap pauses and continues with the finished task, completed or failed.

Zapier limits how long an action may run, so both actions queue a task instead of waiting on a synchronous call.

LangChain

The LangChain packages build tools on the SDKs: one synchronous monitor tool per engine (for example monitor_chatgpt), plus create_async_task, get_task_status and get_credits. A task's payload is validated as the request of its taskType. In JavaScript, API errors are thrown with the response body in the message; in Python, errors are returned to the model as the tool result.

npm install @answerline/sdk @answerline/langchain

import { Client } from "@answerline/sdk";
import { createTools } from "@answerline/langchain";

const client = new Client({ apiKey: process.env.API_KEY!, baseUrl: "https://api.answerline.dev" });
const tools = createTools(client, { engines: ["CHATGPT","GEMINI","PERPLEXITY","COPILOT","GROK","AIMODE","GOOGLE","GOOGLE_NEWS"] });

pip install answerline answerline_langchain

import os
from answerline import Client
from answerline_langchain import create_tools

tools = create_tools(Client(os.environ["API_KEY"], base_url="https://api.answerline.dev"), engines=["CHATGPT","GEMINI","PERPLEXITY","COPILOT","GROK","AIMODE","GOOGLE","GOOGLE_NEWS"])

Bind tools to a chat model or agent like any other LangChain tools.