Large language model services supported by AI Search Open Platform - OpenSearch

AI Search Open Platform lets you call large language model (LLM) services via an API. These services include Retrieval-Augmented Generation (RAG) specific large language models that are fine-tuned based on Alibaba's proprietary foundation models. You can use these models in RAG scenarios in combination with document processing and retrieval services to improve answer accuracy and reduce the hallucination rate.

Service	Service ID (service_id)	Description	QPS limit (for both Alibaba Cloud accounts and RAM users)
Qwen3-235B-A22B	qwen3-235b-a22b	A next-generation large language model (LLM) in the Qwen series. Based on extensive training, Qwen3 achieves breakthroughs in inference, instruction following, agent capabilities, and multilingual support. It supports over 100 languages and dialects, demonstrating powerful multilingual understanding, reasoning, and generation.	3 Note To request a higher API QPS limit, submit a ticket to technical support.
OpenSearch-Qwen-Turbo	ops-qwen-turbo	This model uses the Qwen-Turbo large language model as its foundation. It is fine-tuned using supervised learning to enhance retrieval capabilities and reduce harmful content generation.
Qwen-Turbo	qwen-turbo	The fastest and most cost-effective model in the Qwen series. It is suitable for simple tasks.
Qwen-Plus	qwen-plus	A balanced model offering performance, cost, and speed between Qwen-Max and Qwen-Turbo. It is suitable for moderately complex tasks.
Qwen-Max	qwen-max	The highest-performing model in the Qwen series. It is suitable for complex, multi-step tasks.
DeepSeek-R1	deepseek-r1	A large language model that specializes in complex reasoning tasks. It excels at understanding complex instructions, ensuring result accuracy, and supporting the web search feature.
DeepSeek-V3	deepseek-v3	DeepSeek-V3 is a Mixture-of-Experts (MoE) model that excels in processing long texts, code, mathematics, and encyclopedic knowledge, with outstanding proficiency in Chinese.
DeepSeek-R1-distill-qwen-7b	deepseek-r1-distill-qwen-7b	A model created by using knowledge distillation to fine-tune Qwen-7B with training samples generated by DeepSeek-R1.
DeepSeek-R1-distill-qwen-14b	deepseek-r1-distill-qwen-14b	A model created by using knowledge distillation to fine-tune Qwen-14B with training samples generated by DeepSeek-R1.
DeepSeek-V4-Pro	deepseek-v4-pro	A flagship Mixture-of-Experts (MoE) large model with 1.6T total parameters and 49B activated parameters, natively supporting an ultra-long context of millions of tokens. Built on massive high-quality training data, it possesses top-tier capabilities in mathematical logic, complex reasoning, professional coding, and deep analysis of long texts. It is ideal for advanced scenarios such as high-level scientific research, complex office tasks, and deep intelligent agents.
DeepSeek-V4-Flash	deepseek-v4-flash	An efficient and lightweight Mixture-of-Experts (MoE) model with 284B total parameters and 13B activated parameters, natively supporting an ultra-long context of millions of tokens. It features fast inference, low latency, and low cost. With balanced overall capabilities, it is designed for high-concurrency, lightweight tasks and is suitable for general-purpose scenarios like daily conversation, content creation, basic RAG, and batch text processing.

Prerequisites

Get authentication credentials

The AI Search open platform requires an API key for authentication. For instructions, see Get an API key.
Get the service endpoint

You can call the service via the public network or a VPC. For details, see Get the service endpoint.

Request

General notes

The request body cannot exceed 8 MB.

HTTP method

POST

URL

{host}/v3/openapi/workspaces/{workspace_name}/text-generation/{service_id}

Path parameters

host: The endpoint for the service. You can call the API over the internet or from within a VPC. For more information, see Obtain a service endpoint.

On the API keys page, in the Access Domain Names section, you can find the Public API Domain Name and Private API Domain Name (VPC). Select the appropriate domain name as the host. You can switch to the target workspace by using the drop-down list at the top of the page.
workspace_name: The name of the workspace. Example: default.
service_id: The ID of the built-in service. Example: ops-qwen-turbo.

Request parameters

Header parameters

API key authentication

Parameter	Type	Required	Description	Example
Content-Type	String	Yes	The request format. Must be `application/json`.	application/json
Authorization	String	Yes	The API key for authentication.	Bearer OS-d1**2a

Body parameters

Parameter	Type	Required	Description	Example
messages	List	Yes	The conversation history between the user and the model. Each element in the list is an object with a `role` and `content` key. The available roles are `system`, `user`, and `assistant`. `system`: A system-level message. This role can only be used for the first message in the history (`messages[0]`). Using the `system` role is optional, but if present, it must be at the start of the list. `user` and `assistant`: Represent the dialogue between the user and the model. These roles should alternate to simulate a conversation. The `role` of the last message must be `user`.
stream	Boolean	No	Specifies whether to return a streaming response. The default is `false`. If set to `true`, the response is streamed, with each chunk containing the cumulative text generated up to that point.	false
enable_search	Boolean	No	Specifies whether to enable web search. The default is `false`. When set to `true`, the large language model uses an internal prompt to determine whether a web search is needed. Note This feature is currently supported only by the deepseek-r1 model.	false
csi_level	String	No	The content moderation level. Default: `strict`. Valid values: `none`: No content moderation. `loose`: Loose filtering. `strict`: Strict filtering. `rigorous`: Rigorous filtering.	strict
parameters	Map	No	A map of adjustable parameters for the large language model.	N/A
parameters.search_return_result	Boolean	No	This parameter takes effect only when `enable_search` is `true`. `true`: Returns the web search results. `false`: Does not return the web search results.	false
parameters.search_top_k	Integer	No	The number of web search results to return. Note This parameter takes effect only when `enable_search` is `true`. It is supported only by the deepseek-r1 model.	5
parameters.search_way	String	No	The web search strategy, which is the same as that of the web search API. `normal` (Default): The model rewrites the query, performs a web search, and filters the results using vectorization. `fast`: The model rewrites the query and performs a web search. The search results are not filtered. `full`: The model rewrites the query, performs a web search, and then uses the model to evaluate and filter the results. Note This parameter takes effect only when `enable_search` is `true`. It is supported only by the deepseek-r1 model.	normal
parameters.seed	Integer	No	A random number seed for generation. It controls the randomness of the model's output. The seed must be a 64-bit unsigned integer. When a seed is provided, the model attempts to produce the same or similar results, but deterministic output is not guaranteed.	"parameters":{"seed":666}
parameters.max_tokens	Integer	No	The maximum number of tokens to generate. For Qwen-Turbo, the maximum and default value is 1,500. For Qwen-Max and Qwen-Plus, the maximum and default value is 2,000.	"parameters":{"max_tokens":1500}
parameters.top_p	Float	No	The probability threshold for nucleus sampling. For example, a value of `0.8` means that only tokens from the smallest set that has a cumulative probability of 80% or higher are considered for sampling. The value must be in the range (0, 1.0). A higher value increases randomness, while a lower value decreases it.	"parameters":{"top_p":0.7}
parameters.top_k	Integer	No	The size of the candidate set for sampling. For example, a value of `50` means that only the top 50 most likely tokens are used as the candidate set for random sampling. A higher value increases randomness, while a lower value increases determinism. Note: If `top_k` is not specified or its value is greater than 100, this policy is disabled, and only the `top_p` policy takes effect.	"parameters":{"top_k":50}
parameters.repetition_penalty	Float	No	Controls the penalty for repeating tokens in a sequence. Higher values reduce repetition. A value of `1.0` means no penalty. The value must be greater than 0.	"parameters":{"repetition_penalty":1.0}
parameters.presence_penalty	Float	No	Controls the penalty for repeating tokens anywhere in the entire output. Higher values reduce repetition. The value must be in the range [-2.0, 2.0].	"parameters":{"presence_penalty":1.0}
parameters.temperature	Float	No	Controls the degree of randomness and diversity in the output. A higher temperature value smooths the probability distribution of candidate tokens, making less likely words more probable and increasing diversity. A lower value sharpens the peak of the distribution, making high-probability words more likely and increasing determinism. The value must be in the range [0, 2). A value of 0 is not recommended.	"parameters":{"temperature":0.85}
parameters.stop	string/array	No	Provides precise control by stopping generation before the model produces a specified string or token ID. The generated content will not include the stop sequence. The value can be a string or an array. string type The model stops when it is about to generate the specified stop word. For example, if `stop` is "Hello", generation stops just before outputting "Hello". array type The elements can be strings, token IDs, or an array of token IDs. Generation stops when the next token to be generated (or its corresponding ID) is in the stop array. For example, if you set `stop` to `["hello","weather"]` or `[108386,104307]`, the model will stop when it is about to generate "hello" or "weather". If you set `stop` to `[[108386, 103924],[35946, 101243]]`, the model will stop when it is about to generate "hello there" or "I'm fine". Note When `stop` is an array, you cannot mix strings and token IDs in the same top-level array. For example, `["Hello", 104307]` is invalid.	"parameters":{"stop":["Hello","Weather"]}

Note

The maximum token limit for ops-qwen-turbo is 4,000.

Response parameters

Parameter	Type	Description	Example
result.text	String	The text generated by the model.	Zhengzhou is a...
result.search_results	List<SearchResult>	If `enable_search` is `true` and `parameters.search_return_result` is `true`, this field contains the web search results.	[]
result.search_results[].title	String	The title of the search result.	Today's weather in Zhengzhou
result.search_results[].url	String	The URL of the search result.	https://xxxx.com
result.search_results[].snippet	String	A brief snippet from the content of the search result web page.	The weather in Zhengzhou is sunny today.
usage.output_tokens	Integer	The number of tokens in the generated text.	100
usage.input_tokens	Integer	The number of tokens in the input prompt.	100
usage.total_tokens	Integer	The total number of tokens for the request (input and output).	200

cURL request example

curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
"http://xxxx-hangzhou.opensearch.aliyuncs.com/v3/openapi/workspaces/default/text-generation/qwen-max" \
-d '{
      "messages":[
      {
          "role":"system",
          "content":"You are a helpful assistant."
      },
      {
          "role":"user",
          "content":"What is the capital of Henan Province?"
      },
      {
          "role":"assistant",
          "content":"Zhengzhou"
      },
      {
          "role":"user",
          "content":"What is the weather like in Zhengzhou today?"
      }
      ],
      "parameters":{
          "search_return_result":true,
          "search_top_k":5,
          "search_way":"normal"
      },
       "stream":false,
       "enable_search":true
}'

Response examples

Sample success response

{
  "request_id": "450fcb80-f796-****-8d69-e1e86d29aa9f",
  "latency": 564.903929,
  "result": {
    "text":"According to the latest weather forecast, it will be cloudy in Zhengzhou today, with temperatures between 9°C and 19°C, and a light northeasterly breeze...",
     "search_results":[
      {
        "url":"https://xxxxx.com",
        "title":"xxxx",
        "snippet":"The weather in Zhengzhou is sunny today."
      }
    ]
   },
  "usage": {
      "output_tokens": 934,
      "input_tokens": 798,
      "total_tokens": 1732
  }
}

Sample error response

If an error occurs, the response includes a code and message that explain the error.

{
    "request_id": "45C8C9E5-6BCB-****-80D3-E298F788512B",
    "latency": 0,
    "code": "InvalidParameter",
    "message": "JSON parse error: Unexpected character ..."
}

Status codes

For more information, see Status codes for AI Search Open Platform.