創建補全

POST

api

completions

創建補全

curl --request POST \
  --url https://api.example.com/api/v1/completions \
  --header 'Content-Type: application/json' \
  --data '
{
  "prompt": "<string>",
  "mode": "<string>",
  "stream": true,
  "conversation_id": "<string>",
  "skills": [
    "<string>"
  ],
  "tools": [
    {
      "name": "<string>",
      "description": "<string>",
      "input_schema": {}
    }
  ],
  "persona": {},
  "temperature": 123,
  "max_iterations": 123,
  "model_overrides": {},
  "format": "<string>",
  "metadata": {},
  "component_library": "<string>",
  "memory": true,
  "conversation": {},
  "response_style": {},
  "personality_config": {},
  "theo_branding": true,
  "brand_soul": true,
  "attachments": [
    {}
  ],
  "image_model": "<string>",
  "image_quality": "<string>",
  "stealth_model": "<string>",
  "stealth_aspect": "<string>",
  "stealth_duration": "<string>"
}
'

import requests

url = "https://api.example.com/api/v1/completions"

payload = {
    "prompt": "<string>",
    "mode": "<string>",
    "stream": True,
    "conversation_id": "<string>",
    "skills": ["<string>"],
    "tools": [
        {
            "name": "<string>",
            "description": "<string>",
            "input_schema": {}
        }
    ],
    "persona": {},
    "temperature": 123,
    "max_iterations": 123,
    "model_overrides": {},
    "format": "<string>",
    "metadata": {},
    "component_library": "<string>",
    "memory": True,
    "conversation": {},
    "response_style": {},
    "personality_config": {},
    "theo_branding": True,
    "brand_soul": True,
    "attachments": [{}],
    "image_model": "<string>",
    "image_quality": "<string>",
    "stealth_model": "<string>",
    "stealth_aspect": "<string>",
    "stealth_duration": "<string>"
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    prompt: '<string>',
    mode: '<string>',
    stream: true,
    conversation_id: '<string>',
    skills: ['<string>'],
    tools: [{name: '<string>', description: '<string>', input_schema: {}}],
    persona: {},
    temperature: 123,
    max_iterations: 123,
    model_overrides: {},
    format: '<string>',
    metadata: {},
    component_library: '<string>',
    memory: true,
    conversation: {},
    response_style: {},
    personality_config: {},
    theo_branding: true,
    brand_soul: true,
    attachments: [{}],
    image_model: '<string>',
    image_quality: '<string>',
    stealth_model: '<string>',
    stealth_aspect: '<string>',
    stealth_duration: '<string>'
  })
};

fetch('https://api.example.com/api/v1/completions', 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.example.com/api/v1/completions",
  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([
    'prompt' => '<string>',
    'mode' => '<string>',
    'stream' => true,
    'conversation_id' => '<string>',
    'skills' => [
        '<string>'
    ],
    'tools' => [
        [
                'name' => '<string>',
                'description' => '<string>',
                'input_schema' => [
                                
                ]
        ]
    ],
    'persona' => [
        
    ],
    'temperature' => 123,
    'max_iterations' => 123,
    'model_overrides' => [
        
    ],
    'format' => '<string>',
    'metadata' => [
        
    ],
    'component_library' => '<string>',
    'memory' => true,
    'conversation' => [
        
    ],
    'response_style' => [
        
    ],
    'personality_config' => [
        
    ],
    'theo_branding' => true,
    'brand_soul' => true,
    'attachments' => [
        [
                
        ]
    ],
    'image_model' => '<string>',
    'image_quality' => '<string>',
    'stealth_model' => '<string>',
    'stealth_aspect' => '<string>',
    'stealth_duration' => '<string>'
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($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.example.com/api/v1/completions"

	payload := strings.NewReader("{\n  \"prompt\": \"<string>\",\n  \"mode\": \"<string>\",\n  \"stream\": true,\n  \"conversation_id\": \"<string>\",\n  \"skills\": [\n    \"<string>\"\n  ],\n  \"tools\": [\n    {\n      \"name\": \"<string>\",\n      \"description\": \"<string>\",\n      \"input_schema\": {}\n    }\n  ],\n  \"persona\": {},\n  \"temperature\": 123,\n  \"max_iterations\": 123,\n  \"model_overrides\": {},\n  \"format\": \"<string>\",\n  \"metadata\": {},\n  \"component_library\": \"<string>\",\n  \"memory\": true,\n  \"conversation\": {},\n  \"response_style\": {},\n  \"personality_config\": {},\n  \"theo_branding\": true,\n  \"brand_soul\": true,\n  \"attachments\": [\n    {}\n  ],\n  \"image_model\": \"<string>\",\n  \"image_quality\": \"<string>\",\n  \"stealth_model\": \"<string>\",\n  \"stealth_aspect\": \"<string>\",\n  \"stealth_duration\": \"<string>\"\n}")

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

	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.example.com/api/v1/completions")
  .header("Content-Type", "application/json")
  .body("{\n  \"prompt\": \"<string>\",\n  \"mode\": \"<string>\",\n  \"stream\": true,\n  \"conversation_id\": \"<string>\",\n  \"skills\": [\n    \"<string>\"\n  ],\n  \"tools\": [\n    {\n      \"name\": \"<string>\",\n      \"description\": \"<string>\",\n      \"input_schema\": {}\n    }\n  ],\n  \"persona\": {},\n  \"temperature\": 123,\n  \"max_iterations\": 123,\n  \"model_overrides\": {},\n  \"format\": \"<string>\",\n  \"metadata\": {},\n  \"component_library\": \"<string>\",\n  \"memory\": true,\n  \"conversation\": {},\n  \"response_style\": {},\n  \"personality_config\": {},\n  \"theo_branding\": true,\n  \"brand_soul\": true,\n  \"attachments\": [\n    {}\n  ],\n  \"image_model\": \"<string>\",\n  \"image_quality\": \"<string>\",\n  \"stealth_model\": \"<string>\",\n  \"stealth_aspect\": \"<string>\",\n  \"stealth_duration\": \"<string>\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/completions")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"prompt\": \"<string>\",\n  \"mode\": \"<string>\",\n  \"stream\": true,\n  \"conversation_id\": \"<string>\",\n  \"skills\": [\n    \"<string>\"\n  ],\n  \"tools\": [\n    {\n      \"name\": \"<string>\",\n      \"description\": \"<string>\",\n      \"input_schema\": {}\n    }\n  ],\n  \"persona\": {},\n  \"temperature\": 123,\n  \"max_iterations\": 123,\n  \"model_overrides\": {},\n  \"format\": \"<string>\",\n  \"metadata\": {},\n  \"component_library\": \"<string>\",\n  \"memory\": true,\n  \"conversation\": {},\n  \"response_style\": {},\n  \"personality_config\": {},\n  \"theo_branding\": true,\n  \"brand_soul\": true,\n  \"attachments\": [\n    {}\n  ],\n  \"image_model\": \"<string>\",\n  \"image_quality\": \"<string>\",\n  \"stealth_model\": \"<string>\",\n  \"stealth_aspect\": \"<string>\",\n  \"stealth_duration\": \"<string>\"\n}"

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

{
  "id": "<string>",
  "object": "<string>",
  "created": "<string>",
  "content": "<string>",
  "mode": "<string>",
  "resolved_mode": "<string>",
  "model": {
    "id": "<string>",
    "label": "<string>",
    "engine": "<string>"
  },
  "tools_used": [
    {
      "name": "<string>",
      "status": "<string>",
      "description": "<string>"
    }
  ],
  "artifacts": [
    {}
  ],
  "follow_ups": [
    {
      "label": "<string>",
      "prompt": "<string>"
    }
  ],
  "usage": {
    "cost_cents": 123,
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123,
    "cached": true
  },
  "metadata": {},
  "conversation_id": {},
  "request_id": "<string>"
}

Theo API 的核心端點。讓提示詞經過完整的編排流水線，並返回完整的響應。

如需實時令牌傳輸，請設置 stream: true，或參閱流式補全。

認證

需要 Bearer 令牌。參閱認證。

Authorization: Bearer theo_sk_...

請求體

string

必填

提示詞文本。必須為非空字符串。

string

預設值:"auto"

執行模式。設置為 auto 時，Theo 會對提示詞進行分類並自動選擇最優引擎。可用模式：

auto — 對提示詞分類並路由到最佳引擎（默認）
fast — 面向簡單查詢的低延遲響應
think — 面向複雜分析的深度推理
code — 代碼生成（Theo Code 引擎，擴展輸出預算）
image — 圖像生成（Theo Create）
video — 異步。 請使用 POST /api/v1/video 並輪詢任務狀態，而不是本端點。
research — 異步。 請使用 POST /api/v1/research 並輪詢任務狀態，而不是本端點。
roast — 幽默、不拘一格的語氣
genui — 生成交互式 UI 組件（OpenUI Lang）

research 和 video 是異步的，不得發送給 /completions（或 stream()）。它們以後台任務形式運行；在此處調用會導致工作被內聯執行，請求會在完成前觸發超時。請通過 POST /api/v1/research / POST /api/v1/video 將其加入隊列，並使用獲取任務狀態進行輪詢。@hitheo/sdk 在你把這些模式傳給 complete() / stream() 時會立即拋出 TheoUsageError。參閱異步任務指南。

boolean

預設值:"false"

啓用 SSE 流式傳輸。為 true 時，返回 text/event-stream 響應而非 JSON。參閱流式傳輸。

string

延續一段已有的對話。傳入對話 ID 以保持多輪上下文。

string[]

本次請求要激活的技能 slug。這些技能會與用戶已安裝的技能合併。每個 slug 會為本次補全激活相應技能的提示擴展、工具和模型偏好。你可以在控制台（每張技能卡片上的複製圖標）、GET /api/v1/skills，或技能構建器的 Input 節點中找到 slug。完整指南參閱通過 API 激活技能。

object[]

代理循環期間模型可調用的內聯工具定義。

顯示 Tool object

string

必填

工具名稱（例如 check_inventory）。

string

必填

工具的作用 — 模型會據此判斷何時調用它。

object

描述工具輸入參數的 JSON Schema。

string | object

預設值:"theo"

為本次請求覆蓋 Theo 的人格設定。

"theo" — 默認的 Theo 角色
"none" — 不使用角色（原始模型輸出）
{ "system_prompt": "You are..." } — 自定義系統提示詞

number

採樣温度（0–2）。數值越高，輸出越具創造性。

integer

預設值:"8"

代理循環的最大迭代次數（1–20）。每次迭代為一個「思考 → 行動 → 觀察」循環。

object

為特定模式覆蓋所用引擎。鍵為模式名稱（例如 "code"、"think"），值為 Theo 引擎 ID（例如 "theo-1-reason"、"theo-1-flash"）。有效引擎 ID 參閱列出模型。

string

預設值:"theo"

響應格式。"theo" 為默認格式，"openai" 為兼容 OpenAI 的格式。

object

附加在此次補全上的任意鍵值元數據。會在響應中原樣返回，並記錄在審計日誌中。

string

GenUI 模式下的組件庫標識符。供 E.V.I. 調用方用於自定義 UI 渲染。

boolean

預設值:"true"

設為 false 可跳過本次請求的長期記憶檢索與注入。適用於無狀態 / 對隱私敏感的調用場景，即不希望歷史記憶影響本次回答。

object

面向無狀態調用方的內聯對話信封 — 當未提供 conversation_id 時，服務器會使用其中最近的 messages（最多 20 條），使「再寫長一點」這類追問能夠正確解析上下文。

object

按請求覆蓋的響應風格配置（格式、精確度、意圖），疊加在該密鑰的默認設置之上。

object

按請求覆蓋的人格 / 特質配置疊加層。

boolean

預設值:"true"

品牌總開關。設為 false 會從系統提示詞中剝離 Theo 的角色 / 品牌信息（對 persona 的超集控制）。

boolean

設為 true 時，會將響應限定在該密鑰的品牌目錄（Brand Soul）範圍內 — 只推薦你自己的產品/內容，並將偏離主題的請求引導回來。

object[]

用於視覺輪次的圖片附件。每項為 { type: "image_url", url } 或 { type: "image_base64", data, mime_type }（PNG / JPEG / WebP / GIF，base64 編碼後 ≤ 15MB）。

string

為 image 模式固定圖像子引擎（否則自動選擇）。

string

為 image 模式固定圖像質量檔位。

string

隱身媒體模型固定（stealth_image / stealth_video）。

string

隱身媒體的寬高比。

string

隱身視頻片段的時長。

請求示例

curl -X POST https://www.hitheo.ai/api/v1/completions \
  -H "Authorization: Bearer $THEO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Explain microservices architecture",
    "mode": "auto",
    "temperature": 0.7
  }'

import { Theo } from "@hitheo/sdk";

const theo = new Theo({ apiKey: process.env.THEO_API_KEY! });

const res = await theo.complete({
  prompt: "Explain microservices architecture",
  mode: "auto",
  temperature: 0.7,
});

console.log(res.content);
console.log(res.model.label);     // e.g. "Theo Flash"
console.log(res.usage.cost_cents); // e.g. 0.02

結合技能與工具

curl -X POST https://www.hitheo.ai/api/v1/completions \
  -H "Authorization: Bearer $THEO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Check current inventory levels for SKU-1234",
    "mode": "auto",
    "skills": ["inventory-check"],
    "tools": [
      {
        "name": "check_stock",
        "description": "Look up current stock levels by SKU",
        "input_schema": {
          "type": "object",
          "properties": {
            "sku": { "type": "string" },
            "warehouse": { "type": "string" }
          },
          "required": ["sku"]
        }
      }
    ],
    "persona": { "system_prompt": "You are Atlas, an operations assistant." },
    "max_iterations": 5
  }'

const res = await theo.complete({
  prompt: "Check current inventory levels for SKU-1234",
  skills: ["inventory-check"],
  tools: [
    {
      name: "check_stock",
      description: "Look up current stock levels by SKU",
      input_schema: {
        type: "object",
        properties: {
          sku: { type: "string" },
          warehouse: { type: "string" },
        },
        required: ["sku"],
      },
    },
  ],
  persona: { system_prompt: "You are Atlas, an operations assistant." },
  max_iterations: 5,
});

響應

string

唯一的補全 ID（前綴為 cmpl_）。

string

固定為 "completion"。

string

ISO 8601 時間戳。

string

生成的文本內容。

string

你請求時指定的模式（例如 "auto"）。

string

Theo 在意圖分類後實際使用的模式（例如 "fast"、"think"、"code"）。

object

處理該請求的 Theo 引擎。

顯示 Model object

string

Theo 品牌化的模型 ID（例如 "theo-1-flash"、"theo-1-reason"）。

string

人類可讀的名稱（例如 "Theo Flash"、"Theo Reason"）。

string

引擎子系統（例如 "theo-core"、"theo-vision"）。

object[]

代理循環期間調用過的工具。

顯示 Tool usage object

string

工具名稱。

string

"success" 或 "error"。

string

工具描述。

object[]

在本次補全過程中生成的文件（圖片、代碼、文檔）。

object[]

建議的後續提示詞。

顯示 Follow-up object

string

建議項的簡短標籤。

string

完整的提示詞文本。

object

令牌計數與費用。

顯示 Usage object

number

費用（單位：美分）。

integer

消耗的輸入令牌數。對於非文本模式（image、video、tts、stt）始終為 0。

integer

生成的輸出令牌數。對於非文本模式始終為 0。

integer

令牌總數。

boolean

當響應來自語義緩存時，該字段存在且為 true。

對於非文本模式（image、video、tts、stt），prompt_tokens 和 completion_tokens 始終為 0 — 令牌在這些場景下不是有意義的計費單位。請以 usage.cost_cents 作為這些模式下唯一的用量指標。

object | null

你在請求中傳入的元數據，原樣回傳。

string | null

本輪對話最終解析所依據的服務端會話 ID。若未創建或關聯任何會話，則為 null。若請求中傳入了 conversation_id，則原樣回傳。

string

服務器分配的請求標識符（同時以 X-Request-Id 響應頭返回）。在提交支持工單時附上此值，便於我們在日誌中查詢該請求。

響應示例

{
  "id": "cmpl_abc123",
  "object": "completion",
  "created": "2026-04-10T12:00:00Z",
  "content": "Microservices architecture is a design pattern where an application is composed of small, independent services...",
  "mode": "auto",
  "resolved_mode": "fast",
  "model": {
    "id": "theo-1-flash",
    "label": "Theo Flash",
    "engine": "theo-core"
  },
  "tools_used": [],
  "artifacts": [],
  "follow_ups": [
    { "label": "Compare with monoliths", "prompt": "Compare microservices vs monolithic architecture" },
    { "label": "Service mesh", "prompt": "Explain service mesh in microservices" }
  ],
  "usage": {
    "cost_cents": 0.02,
    "prompt_tokens": 12,
    "completion_tokens": 156,
    "total_tokens": 168
  },
  "metadata": null,
  "conversation_id": null,
  "request_id": "req_9f2e1a"
}

兼容 OpenAI 的格式

傳入 format: "openai" 即可獲得符合 OpenAI chat.completions 格式的響應。這使其可以直接替換現有基於 OpenAI 的應用。

curl -X POST https://www.hitheo.ai/api/v1/completions \
  -H "Authorization: Bearer $THEO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Hello",
    "format": "openai"
  }'

該響應遵循 OpenAI 的 chat.completion 結構，包含 choices、usage 和 model 字段。

語義緩存

非會話類補全（未提供 conversation_id）會被自動緩存。相同的請求會零成本即時返回緩存結果。參閱語義緩存。緩存命中的響應體中會包含 "_cached": true。

錯誤

狀態碼	錯誤碼	說明
400	`validation_error`	請求體無效（缺少 prompt、mode 非法等）
400	`context_length_exceeded`	請求超出該密鑰上最大的上下文窗口 — 請添加支持更大上下文的模型或縮短請求內容
401	`invalid_api_key`	API 密鑰缺失或無效
402	`insufficient_credits`	賬戶餘額不足
403	`model_not_allowed`	請求解析到的模型不在該密鑰的模型允許列表中
404	`not_found`	未找到該對話 ID
422	`guardrail_violation`	該密鑰上的某條 Gateway Guardrails 策略拒絕了該請求
422	`orchestrator_no_path`	該密鑰的編排器圖未能為此請求解析出可用路徑
429	`rate_limit_exceeded`	請求過於頻繁 — 請查看 `Retry-After` 響應頭
500	`server_error`	服務器內部錯誤

創建補全

curl --request POST \
  --url https://api.example.com/api/v1/completions \
  --header 'Content-Type: application/json' \
  --data '
{
  "prompt": "<string>",
  "mode": "<string>",
  "stream": true,
  "conversation_id": "<string>",
  "skills": [
    "<string>"
  ],
  "tools": [
    {
      "name": "<string>",
      "description": "<string>",
      "input_schema": {}
    }
  ],
  "persona": {},
  "temperature": 123,
  "max_iterations": 123,
  "model_overrides": {},
  "format": "<string>",
  "metadata": {},
  "component_library": "<string>",
  "memory": true,
  "conversation": {},
  "response_style": {},
  "personality_config": {},
  "theo_branding": true,
  "brand_soul": true,
  "attachments": [
    {}
  ],
  "image_model": "<string>",
  "image_quality": "<string>",
  "stealth_model": "<string>",
  "stealth_aspect": "<string>",
  "stealth_duration": "<string>"
}
'

import requests

url = "https://api.example.com/api/v1/completions"

payload = {
    "prompt": "<string>",
    "mode": "<string>",
    "stream": True,
    "conversation_id": "<string>",
    "skills": ["<string>"],
    "tools": [
        {
            "name": "<string>",
            "description": "<string>",
            "input_schema": {}
        }
    ],
    "persona": {},
    "temperature": 123,
    "max_iterations": 123,
    "model_overrides": {},
    "format": "<string>",
    "metadata": {},
    "component_library": "<string>",
    "memory": True,
    "conversation": {},
    "response_style": {},
    "personality_config": {},
    "theo_branding": True,
    "brand_soul": True,
    "attachments": [{}],
    "image_model": "<string>",
    "image_quality": "<string>",
    "stealth_model": "<string>",
    "stealth_aspect": "<string>",
    "stealth_duration": "<string>"
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    prompt: '<string>',
    mode: '<string>',
    stream: true,
    conversation_id: '<string>',
    skills: ['<string>'],
    tools: [{name: '<string>', description: '<string>', input_schema: {}}],
    persona: {},
    temperature: 123,
    max_iterations: 123,
    model_overrides: {},
    format: '<string>',
    metadata: {},
    component_library: '<string>',
    memory: true,
    conversation: {},
    response_style: {},
    personality_config: {},
    theo_branding: true,
    brand_soul: true,
    attachments: [{}],
    image_model: '<string>',
    image_quality: '<string>',
    stealth_model: '<string>',
    stealth_aspect: '<string>',
    stealth_duration: '<string>'
  })
};

fetch('https://api.example.com/api/v1/completions', 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.example.com/api/v1/completions",
  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([
    'prompt' => '<string>',
    'mode' => '<string>',
    'stream' => true,
    'conversation_id' => '<string>',
    'skills' => [
        '<string>'
    ],
    'tools' => [
        [
                'name' => '<string>',
                'description' => '<string>',
                'input_schema' => [
                                
                ]
        ]
    ],
    'persona' => [
        
    ],
    'temperature' => 123,
    'max_iterations' => 123,
    'model_overrides' => [
        
    ],
    'format' => '<string>',
    'metadata' => [
        
    ],
    'component_library' => '<string>',
    'memory' => true,
    'conversation' => [
        
    ],
    'response_style' => [
        
    ],
    'personality_config' => [
        
    ],
    'theo_branding' => true,
    'brand_soul' => true,
    'attachments' => [
        [
                
        ]
    ],
    'image_model' => '<string>',
    'image_quality' => '<string>',
    'stealth_model' => '<string>',
    'stealth_aspect' => '<string>',
    'stealth_duration' => '<string>'
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($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.example.com/api/v1/completions"

	payload := strings.NewReader("{\n  \"prompt\": \"<string>\",\n  \"mode\": \"<string>\",\n  \"stream\": true,\n  \"conversation_id\": \"<string>\",\n  \"skills\": [\n    \"<string>\"\n  ],\n  \"tools\": [\n    {\n      \"name\": \"<string>\",\n      \"description\": \"<string>\",\n      \"input_schema\": {}\n    }\n  ],\n  \"persona\": {},\n  \"temperature\": 123,\n  \"max_iterations\": 123,\n  \"model_overrides\": {},\n  \"format\": \"<string>\",\n  \"metadata\": {},\n  \"component_library\": \"<string>\",\n  \"memory\": true,\n  \"conversation\": {},\n  \"response_style\": {},\n  \"personality_config\": {},\n  \"theo_branding\": true,\n  \"brand_soul\": true,\n  \"attachments\": [\n    {}\n  ],\n  \"image_model\": \"<string>\",\n  \"image_quality\": \"<string>\",\n  \"stealth_model\": \"<string>\",\n  \"stealth_aspect\": \"<string>\",\n  \"stealth_duration\": \"<string>\"\n}")

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

	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.example.com/api/v1/completions")
  .header("Content-Type", "application/json")
  .body("{\n  \"prompt\": \"<string>\",\n  \"mode\": \"<string>\",\n  \"stream\": true,\n  \"conversation_id\": \"<string>\",\n  \"skills\": [\n    \"<string>\"\n  ],\n  \"tools\": [\n    {\n      \"name\": \"<string>\",\n      \"description\": \"<string>\",\n      \"input_schema\": {}\n    }\n  ],\n  \"persona\": {},\n  \"temperature\": 123,\n  \"max_iterations\": 123,\n  \"model_overrides\": {},\n  \"format\": \"<string>\",\n  \"metadata\": {},\n  \"component_library\": \"<string>\",\n  \"memory\": true,\n  \"conversation\": {},\n  \"response_style\": {},\n  \"personality_config\": {},\n  \"theo_branding\": true,\n  \"brand_soul\": true,\n  \"attachments\": [\n    {}\n  ],\n  \"image_model\": \"<string>\",\n  \"image_quality\": \"<string>\",\n  \"stealth_model\": \"<string>\",\n  \"stealth_aspect\": \"<string>\",\n  \"stealth_duration\": \"<string>\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/completions")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"prompt\": \"<string>\",\n  \"mode\": \"<string>\",\n  \"stream\": true,\n  \"conversation_id\": \"<string>\",\n  \"skills\": [\n    \"<string>\"\n  ],\n  \"tools\": [\n    {\n      \"name\": \"<string>\",\n      \"description\": \"<string>\",\n      \"input_schema\": {}\n    }\n  ],\n  \"persona\": {},\n  \"temperature\": 123,\n  \"max_iterations\": 123,\n  \"model_overrides\": {},\n  \"format\": \"<string>\",\n  \"metadata\": {},\n  \"component_library\": \"<string>\",\n  \"memory\": true,\n  \"conversation\": {},\n  \"response_style\": {},\n  \"personality_config\": {},\n  \"theo_branding\": true,\n  \"brand_soul\": true,\n  \"attachments\": [\n    {}\n  ],\n  \"image_model\": \"<string>\",\n  \"image_quality\": \"<string>\",\n  \"stealth_model\": \"<string>\",\n  \"stealth_aspect\": \"<string>\",\n  \"stealth_duration\": \"<string>\"\n}"

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

{
  "id": "<string>",
  "object": "<string>",
  "created": "<string>",
  "content": "<string>",
  "mode": "<string>",
  "resolved_mode": "<string>",
  "model": {
    "id": "<string>",
    "label": "<string>",
    "engine": "<string>"
  },
  "tools_used": [
    {
      "name": "<string>",
      "status": "<string>",
      "description": "<string>"
    }
  ],
  "artifacts": [
    {}
  ],
  "follow_ups": [
    {
      "label": "<string>",
      "prompt": "<string>"
    }
  ],
  "usage": {
    "cost_cents": 123,
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123,
    "cached": true
  },
  "metadata": {},
  "conversation_id": {},
  "request_id": "<string>"
}

概覽

補全

媒體生成

音頻

技能 API

技能構建器

工作流

Hooks

設置

嵌入式組件

護欄

Routing Studio

Theo Browser

基準測試

Webhooks

計費

資源

認證

請求體

請求示例

結合技能與工具

響應

響應示例

兼容 OpenAI 的格式

語義緩存

錯誤

​認證

​請求體

​請求示例

​結合技能與工具

​響應

​響應示例

​兼容 OpenAI 的格式

​語義緩存

​錯誤

認證

請求體

請求示例

結合技能與工具

響應

響應示例

兼容 OpenAI 的格式

語義緩存

錯誤