# Yandex Alice AI Text Generation API — Fast & Multilingual LLM (`dev00/yandex-alice-api`) Actor

Generate AI text responses, creative writing, translations, code snippets, and multi-turn conversations using Yandex Alice (YandexGPT 3/4). Built-in procedural device fingerprinting anti-blocking.

- **URL**: https://apify.com/dev00/yandex-alice-api.md
- **Developed by:** [dev00](https://apify.com/dev00) (community)
- **Categories:** AI, Agents, MCP servers
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / 1,000 yandex alice ai queries

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Yandex Alice AI Text Generation API — Fast & Multilingual LLM

Generate AI text responses, creative writing, translations, code snippets, and multi-turn conversations using Yandex Alice (YandexGPT 3/4). Built-in procedural device fingerprinting anti-blocking.

***

### ✨ Key Features

- 🧠 **Powerful YandexGPT Engine** — Powered by Yandex Alice (YandexGPT 3/4) web standalone scenario architecture.
- 🌐 **Multilingual Support** — High quality outputs in English (`en`), Russian (`ru`), Turkish (`tr`), German (`de`), Spanish (`es`), and French (`fr`).
- 💬 **Multi-Turn Conversation Memory** — Pass `prev_req_id` to continue multi-turn dialogues seamlessly across runs.
- 🛡️ **Anti-Blocking Device Randomization** — Every call procedurally generates authentic user-agent, OS version, platform, and browser scale factor fingerprints.
- 🔐 **Zero Setup Overhead** — No cookies, no personal API keys, no complex session tokens to manage.

***

### 📥 Input Parameters

| Parameter | Type | Required | Default | Description |
| :--- | :--- | :--- | :--- | :--- |
| `prompt` | String | Yes | `Explain quantum computing simply` | The text prompt or question to send to Alice AI. |
| `lang` | String | No | `en` | Target response language code: `en`, `ru`, `tr`, `de`, `es`, `fr`. |
| `prev_req_id` | String | No | — | Request ID of the previous message to maintain multi-turn dialogue context. |

#### Input Example (JSON):

```json
{
  "prompt": "Explain quantum computing simply",
  "lang": "en"
}
```

***

### 📤 Output Format Example

```json
{
  "success": true,
  "text": "Quantum computing is a rapidly-emerging technology that harnesses the laws of quantum mechanics to solve complex problems faster than on classical computers...",
  "status": "ok",
  "lang": "en",
  "request_id": "fbb422bc-e76d-4552-99b6-83b3ada850eb"
}
```

***

### 🆚 Why Yandex Alice AI API vs. Standard OpenAI/Claude APIs

| Feature | Yandex Alice AI API | Standard OpenAI/Claude APIs |
| :--- | :--- | :--- |
| **User Sign-up / API Key** | ⚡ Zero Sign-up Required | ❌ Mandatory API key & credit card |
| **Response Latency** | 🚀 Sub-second Edge WebSocket | 🐢 2–5 seconds connection overhead |
| **Multilingual Capabilities** | ✅ Native English, Russian, Turkish, European | ⚠️ Variable quality across non-English |
| **Fingerprint Rotation** | ✅ Procedurally Randomized per Call | ❌ Fixed client IP / Key tracking |

***

### 💡 How To Use — Multi-Turn Dialogue Workflow

1. **First Message** → Run with `"prompt": "My favorite color is cyan."` → Copy the returned `request_id`.
2. **Follow-Up Message** → Run with `"prompt": "What is my favorite color?"` and `"prev_req_id": "YOUR_REQUEST_ID"`.

***

### 🙋 Frequently Asked Questions (FAQ)

**Q: Do I need a Yandex account or API key?**\
A: No! The backend transparently negotiates guest authentication over WebSockets server-side.

**Q: How do I maintain dialogue context?**\
A: Pass the `request_id` returned in the previous run output into the `prev_req_id` input parameter for your next run.

***

### 🎯 Use Cases

- 🤖 **AI Chatbots & Conversational Agents** — Power AI assistants with sub-second multilingual response times.
- ✍️ **Content Generation & Copywriting** — Generate blog posts, emails, and social media captions.
- 🌐 **Multilingual Translation** — High accuracy translations across English, Russian, Turkish, and European languages.
- 🧪 **Automated Testing & QA** — Test conversational flows and LLM outputs in Apify pipelines.

***

### 🔍 Keywords & Tags

`yandex alice api`, `yandexgpt api`, `ai text generator`, `llm api`, `chatgpt alternative`, `ai writer api`, `multilingual ai`, `ai chatbot api`

# Actor input Schema

## `prompt` (type: `string`):

Enter the question or instruction for Alice AI.

## `lang` (type: `string`):

Target language code for the response (default: en). Supported: en, ru, tr, de, es, fr.

## `prev_req_id` (type: `string`):

Request ID of the previous message to maintain multi-turn dialogue context.

## Actor input object example

```json
{
  "prompt": "Explain quantum computing simply",
  "lang": "en"
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `keyValueStoreResult` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "prompt": "Explain quantum computing simply",
    "lang": "en"
};

// Run the Actor and wait for it to finish
const run = await client.actor("dev00/yandex-alice-api").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "prompt": "Explain quantum computing simply",
    "lang": "en",
}

# Run the Actor and wait for it to finish
run = client.actor("dev00/yandex-alice-api").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "prompt": "Explain quantum computing simply",
  "lang": "en"
}' |
apify call dev00/yandex-alice-api --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=dev00/yandex-alice-api",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/Dml30PTSd8niO1Dkl/builds/kUDkS3xLWGId1sxeL/openapi.json