使用样例 - Mint Starter Kit

单轮对话：

单模态模型：

{
    "model": "DeepSeek-R1",
    "messages": [{
        "role": "user",
        "content": "You are a helpful assistant."
    }],
    "stream": false,
    "presence_penalty": 1.03,
    "frequency_penalty": 1.0,
    "repetition_penalty": 1.0,
    "temperature": 0.5,
    "top_p": 0.95,
    "top_k": 0,
    "seed": null,
    "stop": ["stop1", "stop2"],
    "stop_token_ids": [2, 13],
    "include_stop_str_in_output": false,
    "skip_special_tokens": true,
    "ignore_eos": false,
    "max_tokens": 20
}

多模态模型：

说明: “image_url”参数的取值请根据实际情况进行修改。

{
    "model": "DeepSeek-R1",
    "messages": [{
        "role": "user",
        "content": [
           {"type": "text", "text": "My name is Olivier and I"},
           {"type": "image_url", "image_url": "/xxxx/test.png"}
        ]
    }],
    "stream": false,
    "presence_penalty": 1.03,
    "frequency_penalty": 1.0,
    "repetition_penalty": 1.0,
    "temperature": 0.5,
    "top_p": 0.95,
    "top_k": 0,
    "seed": null,
    "stop": ["stop1", "stop2"],
    "stop_token_ids": [2, 13],
    "include_stop_str_in_output": false,
    "skip_special_tokens": true,
    "ignore_eos": false,
    "max_tokens": 20
}

多轮对话

请求样例1：

{
    "model": "DeepSeek-R1",
    "messages": [{
        "role": "system",
        "content": "You are a helpful customer support assistant. Use the supplied tools to assist the user."
        },
        {
        "role": "user",
        "content": "Hi, can you tell me the delivery date for my order? my order id is 12345."
        }
    ],
    "stream": false,
    "presence_penalty": 1.03,
    "frequency_penalty": 1.0,
    "repetition_penalty": 1.0,
    "temperature": 0.5,
    "top_p": 0.95,
    "top_k": 0,
    "seed": null,
    "stop": ["stop1", "stop2"],
    "stop_token_ids": [2],
    "ignore_eos": false,
    "max_tokens": 1024,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "get_delivery_date",
                "strict": true,
                "description": "Get the delivery date for a customer's order. Call this whenever you need to know the delivery date, for example when a customer asks 'Where is my package'",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string",
                            "description": "The customer's order ID."
                        }
                    },
                    "required": [
                        "order_id"
                    ],
                    "additionalProperties": false
                }
            }
        }
    ],
   "tool_choice": "auto"
}

请求样例2：

{
    "model": "DeepSeek-R1",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful customer support assistant. Use the supplied tools to assist the user."
        },
        {
            "role": "user",
            "content": "Hi, can you tell me the delivery date for my order? my order id is 12345."
        },
        {
            "role": "assistant",
            "tool_calls": [
                {
                    "function": {
                        "arguments": "{\"order_id\": \"12345\"}",
                        "name": "get_delivery_date"
                    },
                    "id": "tool_call_8p2Nk",
                    "type": "function"
                }
            ]
        },
        {
            "role": "tool",
            "content": "the delivery date is 2024.09.10.",
            "tool_call_id": "tool_call_8p2Nk"
        }
    ],
    "stream": false,
    "repetition_penalty": 1.1,
    "temperature": 0.9,
    "top_p": 1,
    "max_tokens": 1024,
    "tools": [
        {
            "type": "function",
            "function": {
                "name": "get_delivery_date",
                "strict": true,
                "description": "Get the delivery date for a customer's order. Call this whenever you need to know the delivery date, for example when a customer asks 'Where is my package'",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "order_id": {
                            "type": "string",
                            "description": "The customer's order ID."
                        }
                    },
                    "required": [
                        "order_id"
                    ],
                    "additionalProperties": false
                }
            }
        }
    ],
    "tool_choice": "auto"
}

响应样例：

文本推理（“stream”=false）：

单轮对话：

{
    "id": "chatcmpl-123",
    "object": "chat.completion",
    "created": 1677652288,
    "model": "DeepSeek-R1",
    "choices": [
        {
            "index": 0,
            "message": {
                "role": "assistant",
                "content": "\n\nHello there, how may I assist you today?"
            },
            "finish_reason": "stop"
        }
    ],
    "usage": {
        "prompt_tokens": 9,
        "completion_tokens": 12,
        "total_tokens": 21
    },
    "prefill_time": 200,
    "decode_time_arr": [56, 28, 28]
}

多轮对话：

响应样例1：

{
    "id": "chatcmpl-123",
    "object": "chat.completion",
    "created": 1677652288,
    "model": "DeepSeek-R1",
    "choices": [
        {
            "index": 0,
            "message": {
                "role": "assistant",
                "content": "",
                "tool_calls": [
                    {
                        "function": {
                            "arguments": "{\"order_id\": \"12345\"}",
                            "name": "get_delivery_date"
                        },
                        "id": "call_JwmTNF3O",
                        "type": "function"
                    }
                ]
            },
            "finish_reason": "tool_calls"
        }
    ],
    "usage": {
        "prompt_tokens": 226,
        "completion_tokens": 122,
        "total_tokens": 348
    },
    "prefill_time": 200,
    "decode_time_arr": [56, 28, 28]
}

响应样例2：

{
    "id": "endpoint_common_25",
    "object": "chat.completion",
    "created": 1728959154,
    "model": "DeepSeek-R1",
    "choices": [
        {
            "index": 0,
            "message": {
                "role": "assistant",
                "content": "\n Your order with ID 12345 is scheduled for delivery on September 10th, 2024.",
                "tool_calls": null
            },
            "finish_reason": "stop"
        }
    ],
    "usage": {
        "prompt_tokens": 265,
        "completion_tokens": 30,
        "total_tokens": 295
    },
    "prefill_time": 200,
    "decode_time_arr": [56, 28, 28]
}

流式推理：

流式推理1

（“stream”=true，使用sse格式返回）：

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"\t"},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"\t"},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"endpoint_common_8","object":"chat.completion.chunk","created":1729614610,"model":"DeepSeek-R1","usage":{"prompt_tokens":54,"completion_tokens":17,"total_tokens":71},"choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":"stop"}]}

data: [DONE]

流式推理2

（“stream”=true，配置项“fullTextEnabled”=true，使用sse格式返回）：

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello!"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can I"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can I assist"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can I assist you"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can I assist you today"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can I assist you today?"},"finish_reason":null}]}

data: {"id":"endpoint_common_11","object":"chat.completion.chunk","created":1730184192,"model":"DeepSeek-R1","full_text":"Hello! How can I assist you today?","usage":{"prompt_tokens":31,"completion_tokens":10,"total_tokens":41},"choices":[{"index":0,"delta":{"role":"assistant","content":"Hello! How can I assist you today?"},"finish_reason":"length"}]}

data: [DONE]

输出说明

表1

文本推理结果说明

参数名					类型	说明
id					string	请求ID。
object					string	返回结果类型目前都返回”chat.completion”。
created					integer	推理请求时间戳，精确到秒。
model					string	使用的推理模型。
choices					list	推理结果列表。
-	index				integer	choices消息index，当前只能为0。
	message				object	推理消息。
	-	role			string	角色，目前都返回”assistant”。
		content			string	推理文本结果。
		tool_calls			list	模型工具调用输出。
		-	function		dict	函数调用说明。
			-	arguments	string	调用函数的参数，JSON格式的字符串。
			-	name	string	调用的函数名。
			id		string	模型调用工具的ID。
			type		string	工具的类型，目前仅支持function。
	finish_reason				string	结束原因。 stop：请求被CANCEL或STOP，用户不感知，丢弃响应。请求执行中出错，响应输出为空，err_msg非空。请求输入校验异常，响应输出为空，err_msg非空。请求遇eos结束符正常结束。 length：请求因达到最大序列长度而结束，响应为最后一轮迭代输出。请求因达到最大输出长度（包括请求和模型粒度）而结束，响应为最后一轮迭代输出。 tool_calls：表示模型调用了工具。
usage					object	推理结果统计数据。
-	prompt_tokens				int	用户输入的prompt文本对应的token长度。
	completion_tokens				int	推理结果token数量。PD场景下统计P和D推理结果的总token数量。当一个请求的推理长度上限取maxIterTimes的值时，D节点响应中completion_tokens数量为maxIterTimes+1，即增加了P推理结果的首token数量。
	total_tokens				int	请求和推理的总token数。
prefill_time					float	推理首token时延。
decode_time_arr					list	推理Decode时延数组。

表2

流式推理结果说明

参数名				类型	说明
data				object	一次推理返回的结果。
-	id			string	请求ID。
	object			string	目前都返回”chat.completion.chunk”。
	created			integer	推理请求时间戳，精确到秒。
	model			string	使用的推理模型。
	full_text			string	全量文本结果，配置项“fullTextEnabled”=true时才有此返回值。
	usage			object	推理结果统计数据。
	-	prompt_tokens		int	用户输入的prompt文本对应的token长度。
		completion_tokens		int	推理结果token数量。PD场景下统计P和D推理结果的总token数量。当一个请求的推理长度上限取maxIterTimes的值时，D节点响应中completion_tokens数量为maxIterTimes+1，即增加了P推理结果的首token数量。
		total_tokens		int	请求和推理的总token数。
	choices			list	流式推理结果。
	-	index		integer	choices消息index，当前只能为0。
		delta		object	推理返回结果，最后一个响应为空。
		-	role	string	角色，目前都返回”assistant”。
		-	content	string	推理文本结果。
		finish_reason		string	结束原因，只在最后一次推理结果返回。 stop：请求被CANCEL或STOP，用户不感知，丢弃响应。请求执行中出错，响应输出为空，err_msg非空。请求输入校验异常，响应输出为空，err_msg非空。请求遇eos结束符正常结束。 length：请求因达到最大序列长度而结束，响应为最后一轮迭代输出。请求因达到最大输出长度（包括请求和模型粒度）而结束，响应为最后一轮迭代输出。

​单轮对话：

​单模态模型：

​多模态模型：

​多轮对话

​请求样例1：

​请求样例2：

​响应样例：

​单轮对话：

​多轮对话：

​响应样例1：

​响应样例2：

​流式推理：

​流式推理1

​流式推理2

​输出说明

​表1

​表2

单轮对话：

单模态模型：

多模态模型：

多轮对话

请求样例1：

请求样例2：

响应样例：

单轮对话：

多轮对话：

响应样例1：

响应样例2：

流式推理：

流式推理1

流式推理2

输出说明

表1

表2