Web Search

Include real-time information in answers (market data, news, weather, fact-checking). The Turing Platform offers two paths suited to different scenarios:

Path	Typical use	What you write
Path A: Model built-in search	A single LLM call that returns a final answer with search results already integrated	Add tools or enable_search to a /chat/completions, /messages, or /responses request
Path B: Standalone search endpoint	You control the pipeline: search first, then feed results to any LLM / RAG system	Call /proxy/<provider>/search directly and compose the prompt yourself

Not sure which to use? Choose A when you need the model to decide when to search and automatically inject citations into the answer. Choose B when search results need to go through embedding / retrieval / or integration with your own systems.

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Path A: Model Built-in Search

For per-provider usage, see Model Built-in Search.

Path B: Standalone Search Endpoints

The platform proxies multiple third-party search engines, suitable for custom RAG pipelines: retrieve results first, then perform embedding / reranking / feeding to any LLM.

• Baidu (China region only)
• Tavily (Global, LLM-optimized)
• Firecrawl (Global, Search & Page Scraping)
• Cloudsway (Search, China Region)
• Legacy Bing Proxy (Auto-routes to Baidu/Google)

Notes

• Keep your API key secure; do not expose it in client-side code.
• The availability and accuracy of search results depend on the search engine provider.
• Some search results contain third-party content; please be mindful of copyright when using them.

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See also

• Billing & Usage — Billing dimensions for web_search_requests and vertex_ai_grounding_metadata lift logic
• Chat Completions API — How to use web search on the OpenAI-compatible API
• Messages API — web_search_tool_result block structure on the Claude native API