# DeepSeek Search: One Chinese Citation Query

**Use case:** 

Run one Chinese-language query, inspect cited domains and literal brand mentions, and compare with the saved baseline. Review source annotations before using the findings.

## Input

```json
{
  "queries": [
    "中国企业有哪些开源大语言模型可用于部署？请引用官方资料。"
  ],
  "models": [
    "deepseek/deepseek-v4-flash:online"
  ],
  "brand": "DeepSeek",
  "brandAliases": [],
  "competitors": [
    "Qwen"
  ],
  "language": "zh",
  "stateStoreName": "chinese-ai-search-citation-baseline",
  "comparePrevious": true,
  "maxItems": 1,
  "baseUrl": "https://openrouter.ai/api/v1",
  "model": "deepseek/deepseek-v4-flash",
  "reasoningMode": "off",
  "maxOutputTokens": 1200,
  "maxTotalTokens": 40000,
  "temperature": 0.2,
  "maxConcurrency": 1
}
```

## Output

```json
{
  "query": {
    "label": "query",
    "format": "text"
  },
  "model": {
    "label": "model",
    "format": "text"
  },
  "provider": {
    "label": "provider",
    "format": "text"
  },
  "answer": {
    "label": "answer",
    "format": "text"
  },
  "citations": {
    "label": "citations",
    "format": "text"
  },
  "citedDomains": {
    "label": "citedDomains",
    "format": "text"
  },
  "mentioned": {
    "label": "mentioned",
    "format": "boolean"
  },
  "position": {
    "label": "position",
    "format": "number"
  },
  "competitorsAhead": {
    "label": "competitorsAhead",
    "format": "text"
  },
  "domainClasses": {
    "label": "domainClasses",
    "format": "text"
  },
  "newDomains": {
    "label": "newDomains",
    "format": "text"
  },
  "lostDomains": {
    "label": "lostDomains",
    "format": "text"
  },
  "tokensIn": {
    "label": "tokensIn",
    "format": "number"
  },
  "tokensOut": {
    "label": "tokensOut",
    "format": "number"
  },
  "reasoningTokens": {
    "label": "reasoningTokens",
    "format": "number"
  },
  "costUsd": {
    "label": "costUsd",
    "format": "number"
  },
  "costSource": {
    "label": "costSource",
    "format": "text"
  },
  "priceDate": {
    "label": "Model price date",
    "format": "text"
  },
  "latencyMs": {
    "label": "latencyMs",
    "format": "number"
  },
  "baselineReset": {
    "label": "baselineReset",
    "format": "boolean"
  },
  "stateKey": {
    "label": "stateKey",
    "format": "text"
  },
  "schemaVersion": {
    "label": "schemaVersion",
    "format": "text"
  },
  "type": {
    "label": "type",
    "format": "text"
  },
  "sourceUrl": {
    "label": "sourceUrl",
    "format": "text"
  },
  "found": {
    "label": "found",
    "format": "boolean"
  },
  "status": {
    "label": "status",
    "format": "text"
  },
  "resultCount": {
    "label": "resultCount",
    "format": "number"
  },
  "partial": {
    "label": "partial",
    "format": "boolean"
  },
  "error": {
    "label": "error",
    "format": "text"
  },
  "warnings": {
    "label": "warnings",
    "format": "text"
  },
  "checkedAt": {
    "label": "checkedAt",
    "format": "text"
  },
  "evidence": {
    "label": "evidence",
    "format": "text"
  },
  "confidence": {
    "label": "confidence",
    "format": "text"
  },
  "action": {
    "label": "action",
    "format": "text"
  },
  "successfulPairs": {
    "label": "Successful pairs",
    "format": "number"
  },
  "requestedPairs": {
    "label": "Requested pairs",
    "format": "number"
  },
  "coverage": {
    "label": "Coverage (0–1)",
    "format": "number"
  },
  "domains": {
    "label": "Domain counts and shares",
    "format": "array"
  }
}
```

## About this Actor

This example demonstrates how to use [Chinese AI Search Citation Analyzer DeepSeek Kimi](https://apify.com/zinin/chinese-ai-search-citation-analyzer.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/zinin/chinese-ai-search-citation-analyzer.md) to learn more, explore other use cases, and run it yourself.


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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/zinin/chinese-ai-search-citation-analyzer.md

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).