1.概述

Google 推出的多模态人工智能模型，旨在处理多种数据类型，包括文本、图像、音频、视频和代码。

模型列表：

  • gemini-1.5-pro
  • gemini-1.5-pro-001
  • gemini-1.5-pro-002
  • gemini-1.5-flash-001
  • gemini-1.5-flash-002
  • gemini-1.5-flash-8b
  • gemini-1.5-pro-latest
  • gemini-2.0-flash
  • gemini-2.0-flash-lite-preview-02-05
  • gemini-2.5-flash-preview-04-17(2025/07/15停用)
  • gemini-2.5-flash-preview-05-20(2025/07/15停用)
  • gemini-2.5-flash
  • gemini-2.5-pro-preview-05-06(2025/07/15停用)
  • gemini-2.5-pro-preview-06-05(2025/07/15停用)
  • gemini-2.5-pro
  • gemini-2.5-flash-lite-preview-06-17
  • gemini-2.5-flash-thinking (输出思考过程)
  • gemini-2.5-pro-thinking (输出思考过程)

2.请求说明

  • 请求方法: POST
  • 请求地址
  https://gateway.theturbo.ai/v1/chat/completions

3.请求参数

3.1 Head参数

参数名称 类型 必填 说明 示例值
Content-Type string 是 设置请求头类型，必须为application/json application/json
Accept string 是 设置响应类型，建议统一为application/json application/json
Authorization string 是 身份验证所需的 API_KEY，格式Bearer $YOUR_API_KEY Bearer $YOUR_API_KEY

3.2 Body 参数 (application/json)

参数名称 类型 必填 说明 示例
model string 是 要使用的模型 ID。详见概述列出的可用版本，如 gemini-1.5-pro。 gemini-1.5-pro
messages array 是 聊天消息列表。数组中的每个对象包含role (角色) 与 content (内容)。 [{"role": "user","content": "你好"}]
role string 否 消息角色，可选值: system、user、assistant。 user
content string 否 消息的具体内容。 你好，请给我讲个笑话。
temperature number 否 采样温度，取值0~2。数值越大，输出越随机；数值越小，输出越集中和确定。 0.7
top_p number 否 另一种调节采样分布的方式，取值 0~1。和 temperature 通常二选一设置。 0.9
n number 否 为每条输入消息生成多少条回复。 1
stream boolean 否 是否开启流式输出。设置为 true 时，返回类似 ChatGPT 的流式数据。 false
stop string 否 最多可指定 4 个字符串，一旦生成的内容出现这几个字符串之一，就停止生成更多 tokens。 \n
max_tokens number 否 单次回复可生成的最大 token 数量，受模型上下文长度限制。 1024
presence_penalty number 否 -2.0 ~ 2.0，正值会鼓励模型输出更多新话题，负值会降低输出新话题的概率。 0
frequency_penalty number 否 -2.0 ~ 2.0，正值会降低模型重复字句的频率，负值会提高重复字句出现的概率。 0
reasoning_effort string 否 用来控制模型在推理任务中投入多少“计算精力”。目前只有gemini-2.5-flash-preview-04-17支持。支持low medium high none。默认为low。 low
web_search_options object 否 用来控制是否开启google搜索提示依据。 {}

4.请求示例

4.1聊天对话 

  POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
    "model": "gemini-1.5-pro",
    "messages": [
        {
            "role": "user",
            "content": "你好，给我科普一下量子力学吧"
        }
    ],
    "temperature": 0.7,
    "max_tokens": 1024
}
  
  curl https://gateway.theturbo.ai/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "Accept: application/json" \
    -H "Authorization: Bearer $YOUR_API_KEY" \
    -d "{
    \"model\": \"gemini-1.5-pro\",
    \"messages\": [{
        \"role\": \"user\",
        \"content\": \"你好，给我科普一下量子力学吧\"
    }]
}"
  
  package main

import (
    "fmt"
    "io/ioutil"
    "net/http"
    "strings"
)

const (
    YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
    REQUEST_PAYLOAD = `{
    "model": "gemini-1.5-pro",
    "messages": [{
        "role": "user",
        "content": "你好，给我科普一下量子力学吧"
    }],
    "temperature": 0.7,
    "max_tokens": 1024
}`
)

func main() {

    requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
    requestMethod := "POST"
    requestPayload := strings.NewReader(REQUEST_PAYLOAD)

    req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
    if err != nil {
        fmt.Println("Create request failed, err: ", err)
        return
    }

    req.Header.Add("Content-Type", "application/json")
    req.Header.Add("Accept", "application/json")
    req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

    client := &http.Client{}

    resp, err := client.Do(req)
    if err != nil {
        fmt.Println("Do request failed, err: ", err)
        return
    }
    defer resp.Body.Close()

    respBodyBytes, err := ioutil.ReadAll(resp.Body)
    if err != nil {
        fmt.Println("Read response body failed, err: ", err)
        return
    }
    fmt.Println(string(respBodyBytes))
}

4.2媒体文件理解

媒体文件理解功能，支持理解文档、图像、音频、视频，详细支持类型请参照下方“支持的媒体类型”。

  POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-1.5-pro",
	"messages": [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "这张图片里有什么？"
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "data:image/jpeg;base64,${base64_image}"
					}
				}
			]
		}
	],
	"temperature": 0.7,
	"max_tokens": 1024
}
  
  base64_image=$(base64 -i "Path/to/agi/image.jpeg");
curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-1.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": [{
				\"type\": \"text\",
				\"text\": \"这张图片里有什么？\"
			},
			{
				\"type\": \"image_url\",
				\"image_url\": {
					\"url\": \"data:image/jpeg;base64,${base64_image}\"
				}
			}
		]
	}]
}"
  
  package main

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	REQUEST_PAYLOAD = `{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "你好，给我科普一下量子力学吧"
	}],
	"temperature": 0.7,
	"max_tokens": 1024
}`
)

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"
	requestPayload := strings.NewReader(REQUEST_PAYLOAD)

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

支持的媒体格式

图片类型:

image/png image/jpeg image/webp image/heic image/heif

音频类型:

audio/wav audio/mp3 audio/aiff audio/aac audio/ogg audio/flac

视频类型:

video/mp4 video/mpeg video/mov video/avi video/x-flv video/mpg video/webm video/wmv video/3gpp

文档类型:

application/pdf application/x-javascript text/javascript application/x-python text/x-python text/plain text/html text/css text/md text/csv text/xml text/rtf

4.3函数调用 

  POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "What's the weather like in Boston today?"
	}],
	"tools": [{
		"type": "function",
		"function": {
			"name": "get_current_weather",
			"description": "Get the current weather in a given location",
			"parameters": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					},
					"unit": {
						"type": "string",
						"enum": ["celsius", "fahrenheit"]
					}
				},
				"required": ["location"]
			}
		}
	}],
	"tool_choice": "auto"
}
  
  curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-1.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"What's the weather like in Boston today?\"
	}],
	\"tools\": [{
		\"type\": \"function\",
		\"function\": {
			\"name\": \"get_current_weather\",
			\"description\": \"Get the current weather in a given location\",
			\"parameters\": {
				\"type\": \"object\",
				\"properties\": {
					\"location\": {
						\"type\": \"string\",
						\"description\": \"The city and state, e.g. San Francisco, CA\"
					},
					\"unit\": {
						\"type\": \"string\",
						\"enum\": [\"celsius\", \"fahrenheit\"]
					}
				},
				\"required\": [\"location\"]
			}
		}
	}],
	\"tool_choice\": \"auto\"
}"
  
  package main

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	REQUEST_PAYLOAD = `{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "What's the weather like in Boston today?"
	}],
	"tools": [{
		"type": "function",
		"function": {
			"name": "get_current_weather",
			"description": "Get the current weather in a given location",
			"parameters": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					},
					"unit": {
						"type": "string",
						"enum": ["celsius", "fahrenheit"]
					}
				},
				"required": ["location"]
			}
		}
	}],
	"tool_choice": "auto"
}`
)

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"
	requestPayload := strings.NewReader(REQUEST_PAYLOAD)

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

将 Gemini 模型与实时网络内容相关联，并且适用于所有可用语言。这样一来，Gemini 就可以提供更准确的回答，并引用其知识断点之外的可验证来源。

  POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gemini-2.5-pro",
	"messages": [
		{
			"role": "user",
			"content": "你好，波士顿最近天气怎么样"
		}
	],
	"temperature": 0.7,
	"max_tokens": 1024,
	"web_search_options": {}
}
  
  curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gemini-2.5-pro\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"你好，波士顿最近天气怎么样\"
	}],
	\"temperature\": 0.7,
	\"max_tokens\": 1024,
	\"web_search_options\": {}
}
  
  package main

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"strings"
)

const (
	YOUR_API_KEY    = "sk-123456789012345678901234567890123456789012345678"
	REQUEST_PAYLOAD = `{
	"model": "gemini-1.5-pro",
	"messages": [{
		"role": "user",
		"content": "What's the weather like in Boston today?"
	}],
	"tools": [{
		"type": "function",
		"function": {
			"name": "get_current_weather",
			"description": "Get the current weather in a given location",
			"parameters": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					},
					"unit": {
						"type": "string",
						"enum": ["celsius", "fahrenheit"]
					}
				},
				"required": ["location"]
			}
		}
	}],
	"tool_choice": "auto"
}`
)

func main() {

	requestURL := "https://gateway.theturbo.ai/v1/chat/completions"
	requestMethod := "POST"
	requestPayload := strings.NewReader(REQUEST_PAYLOAD)

	req, err := http.NewRequest(requestMethod, requestURL, requestPayload)
	if err != nil {
		fmt.Println("Create request failed, err: ", err)
		return
	}

	req.Header.Add("Content-Type", "application/json")
	req.Header.Add("Accept", "application/json")
	req.Header.Add("Authorization", "Bearer "+YOUR_API_KEY)

	client := &http.Client{}

	resp, err := client.Do(req)
	if err != nil {
		fmt.Println("Do request failed, err: ", err)
		return
	}
	defer resp.Body.Close()

	respBodyBytes, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		fmt.Println("Read response body failed, err: ", err)
		return
	}
	fmt.Println(string(respBodyBytes))
}

5.响应示例 

  {
    "id": "chatcmpl-1234567890",
    "object": "chat.completion",
    "created": 1699999999,
    "model": "gemini-1.5-pro",
    "choices": [
        {
            "message": {
                "role": "assistant",
                "content": "量子力学是研究微观世界的物理学分支……"
            },
            "finish_reason": "stop"
        }
    ],
    "usage": {
        "prompt_tokens": 10,
        "completion_tokens": 30,
        "total_tokens": 40
    }
}