Stream Generate Content

curl --request POST \
  --url https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent \
  --header 'Content-Type: application/json' \
  --header 'x-goog-api-key: <api-key>' \
  --data '
{
  "systemInstruction": {
    "parts": [
      {
        "text": "You are a helpful assistant."
      }
    ]
  },
  "contents": [
    {
      "role": "user",
      "parts": [
        {
          "text": "Write a short bedtime story about a unicorn."
        }
      ]
    }
  ],
  "generationConfig": {
    "maxOutputTokens": 1024
  }
}
'

import requests

url = "https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent"

payload = {
    "systemInstruction": { "parts": [{ "text": "You are a helpful assistant." }] },
    "contents": [
        {
            "role": "user",
            "parts": [{ "text": "Write a short bedtime story about a unicorn." }]
        }
    ],
    "generationConfig": { "maxOutputTokens": 1024 }
}
headers = {
    "x-goog-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-goog-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    systemInstruction: {parts: [{text: 'You are a helpful assistant.'}]},
    contents: [
      {role: 'user', parts: [{text: 'Write a short bedtime story about a unicorn.'}]}
    ],
    generationConfig: {maxOutputTokens: 1024}
  })
};

fetch('https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'systemInstruction' => [
        'parts' => [
                [
                                'text' => 'You are a helpful assistant.'
                ]
        ]
    ],
    'contents' => [
        [
                'role' => 'user',
                'parts' => [
                                [
                                                                'text' => 'Write a short bedtime story about a unicorn.'
                                ]
                ]
        ]
    ],
    'generationConfig' => [
        'maxOutputTokens' => 1024
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-goog-api-key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

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

func main() {

	url := "https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent"

	payload := strings.NewReader("{\n  \"systemInstruction\": {\n    \"parts\": [\n      {\n        \"text\": \"You are a helpful assistant.\"\n      }\n    ]\n  },\n  \"contents\": [\n    {\n      \"role\": \"user\",\n      \"parts\": [\n        {\n          \"text\": \"Write a short bedtime story about a unicorn.\"\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"maxOutputTokens\": 1024\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-goog-api-key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent")
  .header("x-goog-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"systemInstruction\": {\n    \"parts\": [\n      {\n        \"text\": \"You are a helpful assistant.\"\n      }\n    ]\n  },\n  \"contents\": [\n    {\n      \"role\": \"user\",\n      \"parts\": [\n        {\n          \"text\": \"Write a short bedtime story about a unicorn.\"\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"maxOutputTokens\": 1024\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-goog-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"systemInstruction\": {\n    \"parts\": [\n      {\n        \"text\": \"You are a helpful assistant.\"\n      }\n    ]\n  },\n  \"contents\": [\n    {\n      \"role\": \"user\",\n      \"parts\": [\n        {\n          \"text\": \"Write a short bedtime story about a unicorn.\"\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"maxOutputTokens\": 1024\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "candidates": [
    {
      "index": 0,
      "content": {
        "role": "model",
        "parts": [
          {
            "text": "Once upon a time, a magic backpack..."
          }
        ]
      },
      "finishReason": "STOP"
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 10,
    "candidatesTokenCount": 12,
    "totalTokenCount": 22
  },
  "modelVersion": "gemini-2.0-flash"
}

POST

https://api.tikway.ai

v1beta

models

{model}

:streamGenerateContent

Stream Generate Content

curl --request POST \
  --url https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent \
  --header 'Content-Type: application/json' \
  --header 'x-goog-api-key: <api-key>' \
  --data '
{
  "systemInstruction": {
    "parts": [
      {
        "text": "You are a helpful assistant."
      }
    ]
  },
  "contents": [
    {
      "role": "user",
      "parts": [
        {
          "text": "Write a short bedtime story about a unicorn."
        }
      ]
    }
  ],
  "generationConfig": {
    "maxOutputTokens": 1024
  }
}
'

import requests

url = "https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent"

payload = {
    "systemInstruction": { "parts": [{ "text": "You are a helpful assistant." }] },
    "contents": [
        {
            "role": "user",
            "parts": [{ "text": "Write a short bedtime story about a unicorn." }]
        }
    ],
    "generationConfig": { "maxOutputTokens": 1024 }
}
headers = {
    "x-goog-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-goog-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    systemInstruction: {parts: [{text: 'You are a helpful assistant.'}]},
    contents: [
      {role: 'user', parts: [{text: 'Write a short bedtime story about a unicorn.'}]}
    ],
    generationConfig: {maxOutputTokens: 1024}
  })
};

fetch('https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'systemInstruction' => [
        'parts' => [
                [
                                'text' => 'You are a helpful assistant.'
                ]
        ]
    ],
    'contents' => [
        [
                'role' => 'user',
                'parts' => [
                                [
                                                                'text' => 'Write a short bedtime story about a unicorn.'
                                ]
                ]
        ]
    ],
    'generationConfig' => [
        'maxOutputTokens' => 1024
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-goog-api-key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

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

func main() {

	url := "https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent"

	payload := strings.NewReader("{\n  \"systemInstruction\": {\n    \"parts\": [\n      {\n        \"text\": \"You are a helpful assistant.\"\n      }\n    ]\n  },\n  \"contents\": [\n    {\n      \"role\": \"user\",\n      \"parts\": [\n        {\n          \"text\": \"Write a short bedtime story about a unicorn.\"\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"maxOutputTokens\": 1024\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-goog-api-key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent")
  .header("x-goog-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"systemInstruction\": {\n    \"parts\": [\n      {\n        \"text\": \"You are a helpful assistant.\"\n      }\n    ]\n  },\n  \"contents\": [\n    {\n      \"role\": \"user\",\n      \"parts\": [\n        {\n          \"text\": \"Write a short bedtime story about a unicorn.\"\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"maxOutputTokens\": 1024\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.tikway.ai/v1beta/models/{model}:streamGenerateContent")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-goog-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"systemInstruction\": {\n    \"parts\": [\n      {\n        \"text\": \"You are a helpful assistant.\"\n      }\n    ]\n  },\n  \"contents\": [\n    {\n      \"role\": \"user\",\n      \"parts\": [\n        {\n          \"text\": \"Write a short bedtime story about a unicorn.\"\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"maxOutputTokens\": 1024\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "candidates": [
    {
      "index": 0,
      "content": {
        "role": "model",
        "parts": [
          {
            "text": "Once upon a time, a magic backpack..."
          }
        ]
      },
      "finishReason": "STOP"
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 10,
    "candidatesTokenCount": 12,
    "totalTokenCount": 22
  },
  "modelVersion": "gemini-2.0-flash"
}

授权

x-goog-api-key

string

header

必填

Tikway API Key。按 Gemini 原生协议通过 x-goog-api-key 请求头传递。

路径参数

model

string

必填

请求体

application/json

contents

object[]

必填

当前对话内容。单轮请求通常只有一个 Content；多轮对话按顺序包含历史与最新请求。

Minimum array length: 1

Hide child attributes

contents.parts

object[]

必填

内容部分列表。

Minimum array length: 1

Hide child attributes

contents.parts.text

string

文本输入。

contents.parts.inline_data

object

内联 Base64 文件数据。

Hide child attributes

contents.parts.inline_data.mime_type

string

MIME 类型，例如 image/jpeg。

contents.parts.inline_data.data

string

Base64 编码的数据。

contents.parts.file_data

object

File API 中已上传文件的引用。

Hide child attributes

contents.parts.file_data.mime_type

string

文件 MIME 类型。

contents.parts.file_data.file_uri

string

文件 URI。

contents.parts.function_call

object

上一轮模型生成的函数调用。

Hide child attributes

contents.parts.function_call.name

string

函数名称。

contents.parts.function_call.args

object

函数参数。

contents.parts.function_response

object

客户端对函数调用的执行结果。

Hide child attributes

contents.parts.function_response.name

string

函数名称。

contents.parts.function_response.response

object

函数执行返回值。

contents.parts.executable_code

object

可执行代码。

Hide child attributes

contents.parts.executable_code.language

string

编程语言。

contents.parts.executable_code.code

string

代码内容。

contents.parts.code_execution_result

object

代码执行结果。

Hide child attributes

contents.parts.code_execution_result.outcome

string

执行结果状态。

contents.parts.code_execution_result.output

string

执行输出。

contents.parts.thought

boolean

该部分是否属于模型思考内容。

contents.parts.thought_signature

string

思考内容签名；回传时保持原样。

contents.role

enum<string>

内容角色。省略时通常视为 user。

可用选项:

user,

model

systemInstruction

object

开发者设定的系统指令，目前应使用纯文本部分。

Hide child attributes

systemInstruction.parts

object[]

必填

Hide child attributes

systemInstruction.parts.text

string

系统指令文本。

tools

object[]

模型可使用的工具列表，例如函数调用或代码执行。

Hide child attributes

tools.function_declarations

object[]

函数声明列表。

Hide child attributes

tools.function_declarations.name

string

函数名称。

tools.function_declarations.description

string

函数用途说明。

tools.function_declarations.parameters

object

函数参数 JSON Schema。

tools.function_declarations.response

object

函数响应 JSON Schema。

tools.code_execution

object

启用代码执行工具。

tools.google_search

object

启用 Google 搜索工具。

tools.url_context

object

启用 URL 上下文工具。

toolConfig

object

工具调用配置。

Hide child attributes

toolConfig.functionCallingConfig

object

Hide child attributes

toolConfig.functionCallingConfig.mode

enum<string>

函数调用模式。

可用选项:

AUTO,

ANY,

NONE,

VALIDATED

toolConfig.functionCallingConfig.allowedFunctionNames

string[]

允许自动调用的函数名。

safetySettings

object[]

安全过滤规则；同一类别最多配置一次，覆盖该类别的默认阈值。

Hide child attributes

safetySettings.category

enum<string>

安全类别。

可用选项:

HARM_CATEGORY_HATE_SPEECH,

HARM_CATEGORY_SEXUALLY_EXPLICIT,

HARM_CATEGORY_DANGEROUS_CONTENT,

HARM_CATEGORY_HARASSMENT,

HARM_CATEGORY_CIVIC_INTEGRITY,

HARM_CATEGORY_JAILBREAK

safetySettings.threshold

string

阻止阈值。

safetySettings.method

string

安全评级方法。

generationConfig

object

生成与输出配置。

Hide child attributes

generationConfig.temperature

number

采样温度。

generationConfig.topP

number

核采样阈值。

generationConfig.topK

integer

每步保留的最高概率候选数。

generationConfig.candidateCount

integer

返回候选回复数量。

必填范围: x >= 1

generationConfig.maxOutputTokens

integer

最大输出词元数。

generationConfig.stopSequences

string[]

停止序列。

generationConfig.responseMimeType

enum<string>

输出 MIME 类型。

可用选项:

text/plain,

application/json

generationConfig.responseSchema

object

application/json 输出应遵循的 JSON Schema。

generationConfig.responseJsonSchema

object

JSON 输出的原始 JSON Schema。

generationConfig.responseModalities

enum<string>[]

请求的输出模态。

可用选项:

TEXT,

IMAGE,

AUDIO

generationConfig.thinkingConfig

object

Hide child attributes

generationConfig.thinkingConfig.thinkingBudget

integer

思考词元预算。

generationConfig.thinkingConfig.includeThoughts

boolean

是否在响应中包含思考摘要。

generationConfig.mediaResolution

string

媒体输入解析度设置。

cachedContent

string

作为上下文使用的缓存内容名称，格式为 cachedContents/{cachedContent}。

serviceTier

string

请求服务层级。

store

boolean

是否记录本请求；若设置，会覆盖项目级日志配置。

响应

200 - application/json

Gemini API：models.generateContent 普通响应。完全内联，适合导入 Apifox。

candidates

object[]

模型生成的候选回复列表。

Hide child attributes

candidates.index

integer

候选回复索引。

candidates.content

object

候选回复内容。

Hide child attributes

candidates.content.role

enum<string>

角色，固定为 model。

可用选项:

model

candidates.content.parts

object[]

回复内容部分。

Hide child attributes

candidates.content.parts.text

string

生成的文本。

candidates.content.parts.inline_data

object

内联生成的媒体数据。

Hide child attributes

candidates.content.parts.inline_data.mime_type

string

candidates.content.parts.inline_data.data

string

Base64 编码数据。

candidates.content.parts.file_data

object

Hide child attributes

candidates.content.parts.file_data.mime_type

string

candidates.content.parts.file_data.file_uri

string

candidates.content.parts.function_call

object

模型请求调用函数。

Hide child attributes

candidates.content.parts.function_call.name

string

函数名称。

candidates.content.parts.function_call.args

object

函数参数。

candidates.content.parts.function_call.id

string

函数调用 ID。

candidates.content.parts.executable_code

object

Hide child attributes

candidates.content.parts.executable_code.language

string

candidates.content.parts.executable_code.code

string

candidates.content.parts.code_execution_result

object

Hide child attributes

candidates.content.parts.code_execution_result.outcome

string

candidates.content.parts.code_execution_result.output

string

candidates.content.parts.thought

boolean

是否为思考内容。

candidates.content.parts.thought_signature

string

思考签名。

candidates.finishReason

string

候选回复的结束原因。

candidates.finishMessage

string

结束原因的说明。

candidates.safetyRatings

object[]

候选回复的安全评级。

Hide child attributes

candidates.safetyRatings.category

string

candidates.safetyRatings.probability

string

candidates.safetyRatings.blocked

boolean

candidates.citationMetadata

object

引用元数据。

candidates.tokenCount

integer

候选回复词元数。

candidates.avgLogprobs

number

候选回复的平均对数概率。

candidates.logprobsResult

object

词元对数概率结果。

candidates.urlContextMetadata

object

URL 上下文元数据。

promptFeedback

object

提示词被阻止或过滤时的反馈。

Hide child attributes

promptFeedback.blockReason

string

阻止原因。

promptFeedback.blockReasonMessage

string

阻止原因说明。

promptFeedback.safetyRatings

string[]

提示词安全评级。

usageMetadata

object

词元使用统计。

Hide child attributes

usageMetadata.promptTokenCount

integer

提示词词元数。

usageMetadata.candidatesTokenCount

integer

候选回复词元数。

usageMetadata.totalTokenCount

integer

总词元数。

usageMetadata.cachedContentTokenCount

integer

缓存内容词元数。

usageMetadata.thoughtsTokenCount

integer

思考词元数。

usageMetadata.toolUsePromptTokenCount

integer

工具使用提示词词元数。

modelVersion

string

实际使用的模型版本。

responseId

string

响应唯一 ID。

对话补全

图片生成

视频生成

向量嵌入

语音转写

Stream Generate Content

授权

路径参数

请求体

响应