> ## Documentation Index > Fetch the complete documentation index at: https://platform.stepfun.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Chat Completions API 调用 Chat Completions API，获取模型生成的对话响应数据。 ## 请求地址 `POST https://api.stepfun.com/v1/chat/completions` > [!NOTE] > > Step Plan 场景请使用 `POST https://api.stepfun.com/step_plan/v1/chat/completions` ## 请求参数 * `model` `string` ***required***\ 需要使用的模型名称，例如 `step-5-preview`、`step-3.7-flash`、`step-3.5-flash`、`step-3.5-flash-2603`、`stepaudio-3-chat-preview` 或 `stepaudio-2.5-chat`。`step-router-v1` 仅可通过 [Step Plan](https://platform.stepfun.com/docs/zh/step-plan/overview.md) 通道调用，详见本文「Step Plan 通道：Step Router V1 字段差异」。 * `messages` `object array` ***required***\ 迄今为止用户输入或模型生成的不同类别消息列表 * 系统消息 `object` * `role` `string`\ 系统类别名称，总是为 `system` * `content` `string`\ 系统消息的文本内容 * 用户消息 `object` * `role` `string`\ 用户类别名称，总是 `user` * `content` `string or object array`\ 用户消息内容，类型为 `multipart` 消息列表或者普通文本消息字符串 * 普通文本消息 `string` * `multipart` 消息列表 `object array`\ 结构化的图、视频、音频、文字混合消息 * 文本消息 `object` * `type` `string`\ 总为 `text` * `text` `string`\ 消息文本内容 * 图片消息 `object` * `type` `string`\ 总为 `image_url` * `image_url` `object` * `url` `string`\ 图片地址或 base64 编码的图片，图片格式：jpg/jpeg、png、webp、静态 gif，仅支持 http 和 https 协议。base64 格式举例：`data:image/jpeg;base64,${base64_string}`。 * `detail` `string` ***optional***\ 图片细节级别：`low` / `high` 可选。`high` 按原图分辨率理解，在大图、OCR、极端长宽比等场景表现更好，token 随图片大小变化；`low` 将图片缩放到固定尺寸、更省 token，适合不要求高清细节、想省 token 或提速的场景。 * 视频消息 `object` * `type` `string`\ 总为 `video_url` * `video_url` `object` * `url` `string`\ 视频的 URL 地址，视频格式：video/mp4，仅支持 http 和 https 协议，视频内容要小于 128M，时长建议小于 5 分钟。 * 音频消息 `object` * `type` `string`\ 总为 `input_audio` * `input_audio` `object` * `data` `string`\ 音频内容，为音频的 base64 编码。base64 格式举例：`data:audio/mpeg;base64,${base64_string}`，请更换音频格式（当前仅支持 mp3 和 wav）及对应的 base64 编码后字符串。 * 工具函数消息 `object` * `role` `string`\ 工具类别名称，总是为 `tool` * `content` `string`\ 函数执行得到的内容 * `tool_call_id` `string`\ 执行函数的 ID，由 assistant 在上一轮对话中返回。 * 聊天助手消息 `object` * `role` `string`\ 聊天助手类别名称，总是为 `assistant` * `content` `string | null`\ 聊天助手消息的文本内容 * `tools` `object array` ***optional***\ Toolcall 支持的函数列表。`step-5-preview` 不支持其中的 `type: "web_search"`，请改用 [网页搜索 API](https://platform.stepfun.com/docs/zh/api-reference/search/search.md)。 * `type` `string`\ 工具类型，总是为 `function` * `function` `object`\ 函数内容的描述 * `name` `string`\ 函数名称，要求纯英文、数字和 \_- 符号，建议不要超过 64 个字符长度。 * `description` `string`\ 函数描述，支持中英文，它用于告诉模型函数实现何种功能和目的，方便模型来判断和选择。 * `parameters` `object`\ 函数的参数 * `type` `object`\ 参数描述，一般为 object * `properties` `object`\ 函数参数内容，以 key 为参数的名称，然后通过 `type` 和 `description` 描述参数的类型和介绍。 * `type` `string|number|integer|object|array|boolean`\ 参数类型，可以参考 [json-schema](https://json-schema.org/understanding-json-schema/reference/type) 介绍。 * `description` `string`\ 函数参数描述，支持中英文，它用于告诉模型函数参数的含义。 * `audio` `object` ***optional***\ 用于控制音频输出的参数，只在支持端到端模型场景的模型下生效（`step-1o-audio`/`step-audio-2`/`step-audio-2-mini`/`step-audio-r1.5`） * `voice` `string` ***required***\ 指定生成音频的声音 ID，对于 `step-1o-audio` 可通过[获取声音列表接口](https://platform.stepfun.com/docs/zh/api-reference/audio/list-voice.md)查询可用的声音 ID，对于 `step-audio-2` 系列模型，可用 `wenrounansheng`（温柔男声）、`qingchunshaonv`（青春少女）、`livelybreezy-female`（活力少女）、`elegantgentle-female`（高雅女声）四种声音 ID。 * `format` `string` ***required***\ 指定生成音频的格式，支持 `pcm` 和 `wav` 两种格式，在非流式场景下（stream=false）支持 wav 输出；在流式场景下（stream=true）时，只支持 pcm 输出（24khz, 单声道, 16bit）。 * `modalities` `string array` ***optional***\ 指定输出的模态类型，支持 `text`、`audio` 两种模态类型，只在端到端模型场景下必填。如果需要模型输出音频，则需要将 `audio` 添加到该参数中，建议设置为 `["text", "audio"]`。`stepaudio-2.5-chat` 仅支持 `text`，若选择 `audio` 会报错。 * `max_tokens` `int` ***optional***\ 聊天需要生成的 token 最大数量，默认值为 INF（不作限制，由模型自动决定）。输入 token 和生成 token 的总数量受限于指定模型的最大上下文长度。 * `temperature` `float` ***optional***\ 采样温度，介于0.0和2.0之间的数字。较高值（如0.8）会使生成更随机，较低值（如0.2）会使其生成结果更集中且确定。 * `top_p` `float` ***optional***\ 核心采样，该值会使模型生成具有 top\_p 概率质量的 token 并输出到结果。 * `n` `int` ***optional***\ 控制模型为每个输入消息生成的响应消息结果条数，默认值为1，最大不限，建议不超过5。 * `stream` `bool` ***optional***\ 是否流式生成响应消息，默认值为 false * `stop` `string | string array` ***optional***\ 停止生成的字符串或字符串数组。生成过程中一旦命中其中任意内容，模型立即停止输出。默认为空。 * `frequency_penalty` `float` ***optional***\ 默认为 0，取值范围 -2.0 到 2.0。值越高，会根据 token 在已生成文本中出现的频率施加降频惩罚，从而降低模型重复生成相同内容的可能性。 * `response_format` `object` ***optional***\ 用于指导模型输出特定格式的内容。默认为 `{"type":"text"}`，表示输出文本。 * `type` `string`\ 输出格式类型，可选值为 `text`、`json_object`、`json_schema`。设置为 `json_object` 可以[开启 JSON Mode](https://platform.stepfun.com/docs/zh/guides/developer/json-mode.md)，输出可解析的 JSON 结构。设置为 `json_schema` 可以指定 JSON Schema 约束输出结构。 * `json_schema` `object`\ 当 `type` 为 `json_schema` 时必填，定义输出的 JSON Schema。 * `name` `string` ***required***\ Schema 名称，用于标识该 schema。 * `strict` `boolean` ***optional***\ 是否开启严格模式，开启后模型输出将严格遵循所定义的 schema。默认为 `false`。 * `schema` `object` ***required***\ JSON Schema 定义对象，描述期望的输出结构。遵循 [JSON Schema](https://json-schema.org/) 规范。 * `reasoning_format` `string` ***optional***\ 用于指导模型输出时使用的 reasoning 字段；默认为 `general`，表示通用推理，使用 `reasoning` 字段返回结果；可选项为 \[`general`,`deepseek-style`]。当设置为 `deepseek-style` 时，可使用 DeepSeek 兼容的 `reasoning_content` 字段获取到 reasoning 内容。 * `reasoning_effort` `string` ***optional***\ 控制模型的推理深度。支持三档推理强度的模型可选值为 `low`、`medium`、`high`；`step-3.5-flash-2603` 兼容 `low`、`high` 两档。值越高，模型会进行更深入的思考，但响应时间可能更长。 ## Step Plan 通道：Step Router V1 字段差异 `step-router-v1` 仅可通过 [Step Plan](https://platform.stepfun.com/docs/zh/step-plan/overview.md) 通道（`https://api.stepfun.com/step_plan/v1`）调用，系统会自动在 `step-5-preview` 与 `step-3.7-flash` 之间路由。该模型的字段约束与本文「请求参数」一致，下表列出的字段除外。 | 字段 | Step Plan 通道下的行为 | | - | - | | `model` | 仅接受 `step-router-v1`，其他名称返回 HTTP 400 `request_params_invalid` | | `max_tokens` | 上限为 64K | | `messages` 中的图像 / 文档输入 | 不支持，使用会返回 `unsupported_content_type` | | `tools` 中的 `web_search` | 不支持，使用会返回 `unsupported_content_type` | ## 响应格式 ### 非流式响应 当 `stream=false`（默认）时，返回单个 Chat Completion 响应对象。 #### 属性 * `id` `string` 生成的聊天响应 ID * `object` `string` 模型生成聊天响应的模式，此模式下总为 `chat.completion` * `model` `string` 模型名称 * `created` `timestamp` 生成聊天响应时的 Unix 时间戳，单位为秒 * `choices` `object array` 模型生成的聊天响应结果的可选路径列表。 * `finish_reason` `string`\ 模型停止继续生成的原因，可选值包括 `stop`（正常结束）、`length`（达到 `max_tokens` 上限）与 `tool_calls`（模型发起工具调用） * `index` `int` \ 当前可选路径序列号 * `message` `object` \ 模型生成的聊天响应实际消息内容 - `role` `string`\ 消息所属角色，这里总为 `assistant` - `content` `string`\ 消息文本内容 - `reasoning` `string`\ 推理思考过程内容，仅在 step 推理模型下返回。 - `reasoning_content` `string`\ 推理思考过程内容，与 `reasoning` 字段一同返回且内容一致（DeepSeek 兼容字段名），仅在 step 推理模型下返回。 - `audio` `object` ***optional***\ 端到端语音模型生成的音频内容，仅当请求参数 `modalities` 包含 `audio` 时返回。 * `data` `string`\ 生成音频的 base64 编码 * `transcript` `string`\ 生成音频对应的文本转写 - `tool_calls` `object array` ***optional***\ toolcall 内容返回 * `id` `string`\ 函数执行 ID，由模型生成，在 context 保持唯一。 * `type` `string`\ toolcall 的类型，默认为 `function` * `function` `object`\ 函数的消息体 - `name` `string` \ 函数名称，通常纯英文、数字和\_-符号，一般是在上一轮对话提交的 tools 列表中 - `arguments` `string` \ 函数执行的参数，一般为 json 结构化对象。 * `usage` `object` 模型聊天响应生成的 token 统计信息 * `prompt_tokens` `int` \ 生成过程中使用的提示信息总 token 数量 * `completion_tokens` `int` \ 生成的响应消息内容总 token 数量 * `total_tokens` `int`\ 生成结束后统计的总的 token 数量 * `prompt_tokens_details` `object` ***optional*** \ 提示 token 的细分统计 - `cached_tokens` `int`\ 提示信息中命中缓存的 token 数量 * `completion_tokens_details` `object` ***optional*** \ 生成 token 的细分统计 - `reasoning_tokens` `int`\ 推理思考过程消耗的 token 数量 #### 示例 ```json theme={"theme":{"light":"light-plus","dark":"dark-plus"}} { "id": "b7b56af0-52a6-483f-a589-948182676a1b", "object": "chat.completion", "created": 1709893411, "model": "step-5-preview", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "你好！阶跃星辰是一家专注于人工智能技术的公司，致力于开发和提供各种AI解决方案。我们的人工智能技术涵盖了自然语言处理、计算机视觉、机器学习等领域，旨在帮助用户在各个行业和领域中提高效率和创造价值。" }, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 83, "completion_tokens": 176, "total_tokens": 259 } } ``` ### 流式响应 当 `stream=true` 时，返回 Server-Sent Events (SSE) 格式的流式数据。每个事件包含一个 Chat Completion 响应对象块。 #### 属性 * `id` `string` 生成的聊天响应 ID * `object` `string` 模型生成聊天响应的模式，此模式下总为 `chat.completion.chunk` * `created` `timestamp` 聊天响应时的 Unix 时间戳，单位为秒 * `model` `string` 模型名称 * `choices` `object array` 模型流式生成的聊天响应结果的可选路径列表。单个 `choice` object 属性： * `finish_reason` `string`\ 模型停止继续生成的原因，可选值包括 `stop`（正常结束）、`length`（达到 `max_tokens` 上限）与 `tool_calls`（模型发起工具调用） * `index` `int`\ 当前可选路径序列号 * `delta` object\ 模型渐进生成的聊天响应块 - `role` `string`\ 消息所属角色，此处总为 `assistant` - `content` `string`\ 消息文本内容 - `reasoning` `string`\ 推理思考过程内容，仅在 step 推理模型下返回。 - `reasoning_content` `string`\ 推理思考过程内容，与 `reasoning` 字段一同返回且内容一致（DeepSeek 兼容字段名），仅在 step 推理模型下返回。 - `tool_calls` `object array` ***optional***\ toolcall 内容返回 * `id` `string`\ 函数执行 ID，由模型生成，在 context 保持唯一。 * `type` `string`\ toolcall 的类型，默认为 `function` * `function` `object`\ 函数的消息体 - `name` `string`\ 函数名称，通常纯英文、数字和\_-符号，一般是在上一轮对话提交的 tools 列表中 - `arguments` `string`\ 函数执行的参数，一般为 json 结构化对象。 * `usage` `object` 模型聊天响应生成的 token 统计信息 * `prompt_tokens` `int`\ 生成过程中使用的提示信息总 token 数量 * `completion_tokens` `int`\ 生成的响应消息内容总 token 数量 * `total_tokens` `int`\ 生成结束后统计的总的 token 数量 * `prompt_tokens_details` `object` ***optional***\ 提示 token 的细分统计 - `cached_tokens` `int`\ 提示信息中命中缓存的 token 数量 * `completion_tokens_details` `object` ***optional***\ 生成 token 的细分统计 - `reasoning_tokens` `int`\ 推理思考过程消耗的 token 数量 #### 示例 ```text theme={"theme":{"light":"light-plus","dark":"dark-plus"}} data: {"id":"d7ae7c4a-1524-4fe5-9d58-e4d59b89d8f0","object":"chat.completion.chunk","created":1709899323,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"您"},"finish_reason":""}],"usage":{"prompt_tokens":83,"completion_tokens":1,"total_tokens":84}} data: {"id":"d7ae7c4a-1524-4fe5-9d58-e4d59b89d8f0","object":"chat.completion.chunk","created":1709899323,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"好"},"finish_reason":""}],"usage":{"prompt_tokens":83,"completion_tokens":2,"total_tokens":85}} data: {"id":"d7ae7c4a-1524-4fe5-9d58-e4d59b89d8f0","object":"chat.completion.chunk","created":1709899323,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"！"},"finish_reason":""}],"usage":{"prompt_tokens":83,"completion_tokens":3,"total_tokens":86}} ... data: {"id":"d7ae7c4a-1524-4fe5-9d58-e4d59b89d8f0","object":"chat.completion.chunk","created":1709899323,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":""},"finish_reason":"stop"}],"usage":{"prompt_tokens":83,"completion_tokens":150,"total_tokens":233}} data: [DONE] ``` ## 示例 > 说明：以下基础示例默认使用 `step-5-preview`。如需控制模型的推理深度，可参考「推理强度」示例中的 `reasoning_effort` 用法。 > [tab] 推理强度 > > ```bash theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > curl https://api.stepfun.com/v1/chat/completions \ > -H "Content-Type: application/json" \ > -H "Authorization: Bearer $STEPFUN_API_KEY" \ > -d '{ > "model": "step-5-preview", > "messages": [ > { > "role": "user", > "content": "请用三句话解释什么是强化学习。" > } > ], > "reasoning_effort": "medium", > "max_tokens": 1024 > }' > ``` > [tab] 文字聊天 > > > [tab] python > > > > ```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > from openai import OpenAI > > > > client = OpenAI(api_key="YOUR_STEP_API_KEY", base_url="https://api.stepfun.com/v1") > > > > completion = client.chat.completions.create( > > model="step-5-preview", > > messages=[ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你擅长中文，英文，以及多种其他语言的对话。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容", > > }, > > { > > "role": "user", > > "content": "你好，请介绍一下阶跃星辰的人工智能!" > > } > > ], > > ) > > > > print(completion) > > ``` > > > [tab] js > > > > ```js theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > import OpenAI from "openai"; > > > > const openai = new OpenAI({ > > apiKey: "YOUR_STEP_API_KEY", > > baseURL: "https://api.stepfun.com/v1" > > }); > > > > async function main() { > > const completion = await openai.chat.completions.create({ > > model: "step-5-preview", > > messages: [ > > { > > role: "system", > > content: "你是由阶跃星辰提供的AI聊天助手，你擅长中文，英文，以及多种其他语言的对话。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容" > > }, > > { > > role: "user", > > content: "你好，请介绍一下阶跃星辰的人工智能!" > > } > > ] > > }); > > > > console.log(JSON.stringify(completion)); > > } > > > > main(); > > ``` > > > [tab] curl > > > > ```bash theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > curl https://api.stepfun.com/v1/chat/completions \ > > -H "Content-Type: application/json" \ > > -H "Authorization: Bearer $STEP_API_KEY" \ > > -d '{ > > "model": "step-5-preview", > > "messages": [ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你擅长中文，英文，以及多种其他语言的对话。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容。" > > }, > > { > > "role": "user", > > "content": "你好，请介绍一下阶跃星辰的人工智能！" > > } > > ] > > }' > > ``` > > ```json filename="返回" theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > { > "id": "e2eb4b00d2c226517de3882f17d9664b.ffead889783a0bcd8d2bd17ea4d4c2af", > "object": "chat.completion", > "created": 1772624997, > "model": "step-5-preview", > "choices": [ > { > "index": 0, > "message": { > "role": "assistant", > "content": "阶跃星辰（StepFun）是一家专注于**多模态人工智能技术研发与应用**的科技公司，致力于推动大模型（LLM）在文本、图像、逻辑推理等多领域的融合创新。其核心产品 **Step AI**（又称Step模型）具备以下特点：\n\n---\n\n### 🔍 **核心能力**\n1. **多模态融合** \n - 不仅能处理文本，还可理解图片、图表等视觉信息，实现跨模态推理（例如根据图片描述内容、解答视觉逻辑题）。\n2. **强大的逻辑与知识能力** \n - 在数理逻辑、代码生成、专业知识问答等场景表现突出，支持复杂任务拆解与精准分析。\n3. **多语言支持** \n - 覆盖中、英及多语种交流，适应全球化场景。\n4. **安全与合规** \n - 严格遵循内容安全规范，拒绝生成暴力、仇恨、虚假信息等有害内容，注重用户隐私保护。\n\n---\n\n### 🌟 **技术亮点**\n- **自主研发大模型架构**：针对多模态任务优化，提升视觉-语言对齐能力。\n- **高效推理与低能耗设计**：在保证性能的同时，兼顾部署效率。\n- **持续迭代能力**：通过数据与算法优化，动态提升模型的理解与生成质量。\n\n---\n\n### 🚀 **应用场景**\n- **教育科研**：辅助解题、文献分析、多学科知识问答。\n- **办公创作**：文档总结、代码辅助、创意文案生成。\n- **工业与商业**：数据分析报告生成、多模态信息检索、智能客服升级。\n- **日常生活**：跨语言交流、图像内容解读、个性化知识助手。\n\n---\n\n### 🌍 **价值观与愿景**\n阶跃星辰强调 **“技术向善”**，推动AI在安全、可靠、有益的方向发展，致力于成为多模态智能时代的引领者，让技术服务于社会创新与人类福祉。\n\n---\n\n如需了解具体技术细节或应用案例，可进一步探讨！ 🌟" > }, > "finish_reason": "stop" > } > ], > "usage": { > "prompt_tokens": 85, > "completion_tokens": 701, > "total_tokens": 786 > } > } > ``` > [tab] 图片理解 > > > [tab] python > > > > ```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > from openai import OpenAI > > > > client = OpenAI(api_key="YOUR_STEP_API_KEY", base_url="https://api.stepfun.com/v1") > > > > completion = client.chat.completions.create( > > model="step-5-preview", > > messages=[ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你除了擅长中文，英文，以及多种其他语言的对话以外，还能够根据用户提供的图片，对内容进行精准的内容文本描述。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容", > > }, > > { > > "role": "user", > > "content": [ > > { > > "type": "text", > > "text": "用优雅的语言描述这张图片", > > }, > > { > > "type": "image_url", > > "image_url": { > > "url": "https://www.stepfun.com/assets/section-1-CTe4nZiO.webp", > > "detail": "high" > > }, > > }, > > ], > > }, > > ], > > ) > > > > print(completion) > > ``` > > > [tab] js > > > > ```js theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > import OpenAI from "openai"; > > > > const openai = new OpenAI({ > > apiKey: "YOUR_STEP_API_KEY", > > baseURL: "https://api.stepfun.com/v1" > > }); > > > > async function main() { > > const completion = await openai.chat.completions.create({ > > model: "step-5-preview", > > messages: [ > > { > > role: "system", > > content: "你是由阶跃星辰提供的AI聊天助手，你除了擅长中文，英文，以及多种其他语言的对话以外，还能够根据用户提供的图片，对内容进行精准的内容文本描述。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容" > > }, > > { > > role: "user", > > content: [ > > { > > type: "text", > > text: "用优雅的语言描述这张图片" > > }, > > { > > type: "image_url", > > image_url: { > > url: "https://www.stepfun.com/assets/section-1-CTe4nZiO.webp", > > detail: "high" > > } > > } > > ] > > } > > ] > > }); > > > > console.log(JSON.stringify(completion)); > > } > > > > main(); > > ``` > > > [tab] curl > > > > ```bash theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > curl https://api.stepfun.com/v1/chat/completions \ > > -H "Content-Type: application/json" \ > > -H "Authorization: Bearer $STEP_API_KEY" \ > > -d '{ > > "model": "step-5-preview", > > "messages": [ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你除了擅长中文，英文，以及多种其他语言的对话以外，还能够根据用户提供的图片，对内容进行精准的内容文本描述。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容" > > }, > > { > > "role": "user", > > "content": [ > > { > > "type": "text", > > "text": "用优雅的语言描述这张图片" > > }, > > { > > "type": "image_url", > > "image_url": { > > "url": "https://www.stepfun.com/assets/section-1-CTe4nZiO.webp", > > "detail": "high" > > } > > } > > ] > > } > > ] > > }' > > ``` > > ```json filename="返回" theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > { > "id": "298ad5e6-033a-41f8-9801-43be6e106f22", > "object": "chat.completion", > "created": 1710145618, > "model": "step-5-preview", > "choices": [ > { > "index": 0, > "message": { > "role": "assistant", > "content": "在黄昏的柔和光线下，一座现代化的建筑映入眼帘，它拥有鲜明的红色外观，与周围环境形成鲜明对比。这座建筑的底层设有宽敞的玻璃窗，为室内提供了充足的自然光。建筑的一侧有醒目的标识，顶部的窗户排列整齐，展现了现代设计的风格。\n\n在建筑前的空地上，有一棵光秃的树，其枝条在微风中轻轻摇曳。树下是一片铺着碎石的土地，为这个空间增添了一丝自然的气息。在空地的一侧，还可以看到几个小巧的灯具，它们发出的温暖光线在傍晚显得格外温馨。\n\n建筑周围环境整洁，道路上没有车辆，显得非常宁静。远处可以看到其他建筑的轮廓，以及天空中即将落下的太阳，为这幅画面增添了丰富的层次感。整个场景透露出一种宁静而有序的都市生活氛围。" > }, > "finish_reason": "stop" > } > ], > "usage": { > "prompt_tokens": 497, > "completion_tokens": 169, > "total_tokens": 666 > } > } > ``` > [tab] 语音输入输出 > > > [tab] python > > > > ```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > import base64 > > from openai import OpenAI > > > > client = OpenAI(api_key="YOUR_STEP_API_KEY", base_url="https://api.stepfun.com/v1") > > > > completion = client.chat.completions.create( > > model="step-audio-2", > > modalities=["text", "audio"], > > messages=[ > > { > > "role": "system", > > "content": "你是一个老北京大爷，喜欢用京片子和用户聊天。", > > }, > > { > > "role": "user", > > "content": "今儿个北京的天气咋样啊？", > > }, > > ], > > audio={ > > "voice": "wenrounansheng", > > "format": "wav", > > }, > > stream=False, > > ) > > > > # response transcript > > print(completion.choices[0].message.audio.transcript) > > # save response audio > > with open("response.wav", "wb") as f: > > f.write(base64.b64decode(completion.choices[0].message.audio.data)) > > # 打开 response.wav 即可收听音频回复 > > ``` > > > [tab] js > > > > ```js theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > import OpenAI from "openai"; > > import fs from "fs"; > > > > const openai = new OpenAI({ > > apiKey: "YOUR_STEP_API_KEY", > > baseURL: "https://api.stepfun.com/v1" > > }); > > > > const downloadAudioAsBase64 = async (url) => { > > const response = await fetch(url); > > const arrayBuffer = await response.arrayBuffer(); > > const buffer = Buffer.from(arrayBuffer); > > return "data:audio/wav;base64," + buffer.toString("base64"); > > }; > > > > async function main() { > > const completion = await openai.chat.completions.create({ > > model: "step-audio-2", > > modalities: ["text", "audio"], > > messages: [ > > { > > role: "system", > > content: "你是一个动物声音识别专家，请根据用户提供的动物声音进行识别。" > > }, > > { > > role: "user", > > content: [ > > { > > type: "text", > > text: "听听这是什么声音" > > }, > > { > > type: "input_audio", > > input_audio: { > > data: await downloadAudioAsBase64("https://stepchat-static.tos-cn-shanghai.volces.com/resource_tmp/cat-meow.wav") > > } > > } > > ] > > } > > ], > > audio: { > > voice: "wenrounansheng", > > format: "wav" > > }, > > stream: false > > }); > > // response transcript > > console.log(completion.choices[0].message.audio.transcript); > > // save response audio > > fs.writeFileSync("response.wav", Buffer.from(completion.choices[0].message.audio.data, "base64")); > > // 打开 response.wav 即可收听音频回复 > > } > > > > main(); > > ``` > > > [tab] curl > > > > ```bash theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > curl https://api.stepfun.com/v1/chat/completions \ > > -H "Content-Type: application/json" \ > > -H "Authorization: Bearer $STEP_API_KEY" \ > > -d '{ > > "model": "step-audio-2", > > "modalities": ["text", "audio"], > > "messages": [ > > { > > "role": "system", > > "content": "你是一个老北京大爷，喜欢用京片子和用户聊天。" > > }, > > { > > "role": "user", > > "content": "今儿个北京的天气咋样啊？" > > } > > ], > > "audio": { > > "voice": "wenrounansheng", > > "format": "wav" > > }, > > "stream": false > > }' > > ``` > > 语音示例返回（text+audio 模态，带 toolcall 字段），由于带有 audio，所以返回内容较大，audio 字段内容被截断显示： > > ```json theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > { > "id": "019b55f32eb27db7a0cc933be0216686", > "choices": [ > { > "finish_reason": null, > "index": 0, > "logprobs": null, > "message": { > "role": "assistant", > "audio": { > "data": "[base64 wav, length=193940]", > "transcript": "哎呀，现在是下午三点啦。" > }, > "tool_calls": [ > { > "id": "call-1766673564415832077", > "function": { > "arguments": "{\"city\": \"北京\"}", > "name": "get_weather" > }, > "type": "function", > "index": 0 > } > ] > } > } > ], > "created": 1766673565, > "model": "step-audio-2", > "object": "chat.completion", > "usage": { > "completion_tokens": 106, > "prompt_tokens": 410, > "total_tokens": 516, > "completion_tokens_details": null, > "prompt_tokens_details": null > } > } > ``` > [tab] Base64编码图片 > > > [tab] python > > > > ```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > # -*- coding: utf8 -*- > > > > import base64 > > import requests > > from openai import OpenAI > > > > client = OpenAI(api_key="YOUR_STEP_API_KEY", base_url="https://api.stepfun.com/v1") > > > > # 加载图片到内存，仅演示。按需改成读文件等 > > r = requests.get("https://www.stepfun.com/assets/section-1-CTe4nZiO.webp") > > r.raise_for_status() > > image_str = base64.b64encode(r.content).decode("ascii") > > > > completion = client.chat.completions.create( > > model="step-5-preview", > > messages=[ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你除了擅长中文，英文，以及多种其他语言的对话以外，还能够根据用户提供的图片，对内容进行精准的内容文本描述。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容", > > }, > > { > > "role": "user", > > "content": [ > > { > > "type": "text", > > "text": "用优雅的语言描述这张图片", > > }, > > { > > "type": "image_url", > > "image_url": { > > "url": "data:image/webp;base64,%s" % (image_str), > > }, > > }, > > ], > > }, > > ], > > ) > > > > print(completion) > > ``` > > > [tab] js > > > > ```js theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > import OpenAI from "openai"; > > > > const openai = new OpenAI({ > > apiKey: "YOUR_STEP_API_KEY", > > baseURL: "https://api.stepfun.com/v1" > > }); > > > > // 加载图片到内存，仅演示。按需改成读文件等 > > async function load_image(url) { > > let response = await fetch(url); > > let blob = await response.blob(); > > let buffer = Buffer.from(await blob.arrayBuffer()); > > return "data:" + blob.type + ";base64," + buffer.toString("base64"); > > } > > > > async function main() { > > const completion = await openai.chat.completions.create({ > > model: "step-5-preview", > > messages: [ > > { > > role: "system", > > content: "你是由阶跃星辰提供的AI聊天助手，你除了擅长中文，英文，以及多种其他语言的对话以外，还能够根据用户提供的图片，对内容进行精准的内容文本描述。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容" > > }, > > { > > role: "user", > > content: [ > > { > > type: "text", > > text: "用优雅的语言描述这张图片" > > }, > > { > > type: "image_url", > > image_url: { > > url: await load_image("https://www.stepfun.com/assets/section-1-CTe4nZiO.webp") > > } > > } > > ] > > } > > ] > > }); > > > > console.log(JSON.stringify(completion)); > > } > > > > main(); > > ``` > > > [tab] curl > > > > ```bash theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > # 加载图片到内存，仅演示。按需改成读文件等 > > image_base64="data:image/webp;base64,"$(curl -s "https://www.stepfun.com/assets/section-1-CTe4nZiO.webp" | base64) > > > > curl https://api.stepfun.com/v1/chat/completions \ > > -H "Content-Type: application/json" \ > > -H "Authorization: Bearer $STEP_API_KEY" \ > > -d "{ > > \"model\": \"step-5-preview\", > > \"messages\": [ > > { > > \"role\": \"system\", > > \"content\": \"你是由阶跃星辰提供的AI聊天助手，你除了擅长中文，英文，以及多种其他语言的对话以外，还能够根据用户提供的图片，对内容进行精准的内容文本描述。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容\" > > }, > > { > > \"role\": \"user\", > > \"content\": [ > > { > > \"type\": \"text\", > > \"text\": \"用优雅的语言描述这张图片\" > > }, > > { > > \"type\": \"image_url\", > > \"image_url\": { > > \"url\": \"${image_base64}\" > > } > > } > > ] > > } > > ] > > }" > > ``` > > ```json filename="返回" theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > { > "id": "018ec23da38c7e2cbbe2f669c7b62483", > "object": "chat.completion", > "created": 1710145618, > "model": "step-5-preview", > "choices": [ > { > "index": 0, > "message": { > "role": "assistant", > "content": "在黄昏的柔和光线下，一座现代化的建筑映入眼帘，它拥有鲜明的红色外观，与周围环境形成鲜明对比。这座建筑的底层设有宽敞的玻璃窗，为室内提供了充足的自然光。建筑的一侧有醒目的标识，顶部的窗户排列整齐，展现了现代设计的风格。\n\n在建筑前的空地上，有一棵光秃的树，其枝条在微风中轻轻摇曳。树下是一片铺着碎石的土地，为这个空间增添了一丝自然的气息。在空地的一侧，还可以看到几个小巧的灯具，它们发出的温暖光线在傍晚显得格外温馨。\n\n建筑周围环境整洁，道路上没有车辆，显得非常宁静。远处可以看到其他建筑的轮廓，以及天空中即将落下的太阳，为这幅画面增添了丰富的层次感。整个场景透露出一种宁静而有序的都市生活氛围。" > }, > "finish_reason": "stop" > } > ], > "usage": { > "prompt_tokens": 497, > "completion_tokens": 169, > "total_tokens": 666 > } > } > ``` > [tab] 流式响应 > > > [tab] python > > > > ```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > from openai import OpenAI > > > > client = OpenAI(api_key="YOUR_STEP_API_KEY", base_url="https://api.stepfun.com/v1") > > > > completion = client.chat.completions.create( > > model="step-5-preview", > > stream=True, > > messages=[ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你擅长中文，英文，以及多种其他语言的对话。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容", > > }, > > {"role": "user", "content": "你好，请在64字数以内介绍一下阶跃星辰的人工智能!"}, > > ], > > ) > > > > for chunk in completion: > > print(chunk) > > ``` > > > [tab] js > > > > ```js theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > import OpenAI from "openai"; > > > > const openai = new OpenAI({ > > apiKey: "YOUR_STEP_API_KEY", > > baseURL: "https://api.stepfun.com/v1" > > }); > > > > async function main() { > > const completion = await openai.chat.completions.create({ > > model: "step-5-preview", > > stream: true, > > messages: [ > > { > > role: "system", > > content: "你是由阶跃星辰提供的AI聊天助手，你擅长中文，英文，以及多种其他语言的对话。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容" > > }, > > { > > role: "user", > > content: "你好，请在64字数以内介绍一下阶跃星辰的人工智能!" > > } > > ] > > }); > > > > for await (const chunk of completion) { > > console.log(JSON.stringify(chunk)); > > } > > } > > > > main(); > > ``` > > > [tab] curl > > > > ```bash theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > > curl https://api.stepfun.com/v1/chat/completions \ > > -H "Content-Type: application/json" \ > > -H "Authorization: Bearer $STEP_API_KEY" \ > > -d '{ > > "model": "step-5-preview", > > "stream": true, > > "messages": [ > > { > > "role": "system", > > "content": "你是由阶跃星辰提供的AI聊天助手，你擅长中文，英文，以及多种其他语言的对话。在保证用户数据安全的前提下，你能对用户的问题和请求，作出快速和精准的回答。同时，你的回答和建议应该拒绝黄赌毒，暴力恐怖主义的内容" > > }, > > { > > "role": "user", > > "content": "你好，请在64字数以内介绍一下阶跃星辰的人工智能!" > > } > > ] > > }' > > ``` > > ```text filename="返回" theme={"theme":{"light":"light-plus","dark":"dark-plus"}} > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":0,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":""}],"usage":{"prompt_tokens":0,"completion_tokens":0,"total_tokens":0}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"阶"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":1,"total_tokens":91}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"跃"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":2,"total_tokens":92}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"星辰"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":3,"total_tokens":93}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"AI"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":4,"total_tokens":94}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"，"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":5,"total_tokens":95}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"智能"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":6,"total_tokens":96}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"安全"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":7,"total_tokens":97}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"，"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":8,"total_tokens":98}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"多"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":9,"total_tokens":99}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"语言"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":10,"total_tokens":100}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"，"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":11,"total_tokens":101}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"快速"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":12,"total_tokens":102}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"精准"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":13,"total_tokens":103}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"，"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":14,"total_tokens":104}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"拒绝"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":15,"total_tokens":105}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"不良"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":16,"total_tokens":106}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"，"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":17,"total_tokens":107}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"用"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":18,"total_tokens":108}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"科技"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":19,"total_tokens":109}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"创造"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":20,"total_tokens":110}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"美好"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":21,"total_tokens":111}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"未来"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":22,"total_tokens":112}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":"。"},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":23,"total_tokens":113}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":""},"finish_reason":""}],"usage":{"prompt_tokens":90,"completion_tokens":24,"total_tokens":114}} > > data: {"id":"d4ca43cd-83a7-4012-9ee7-b8f143eb1f8f","object":"chat.completion.chunk","created":1710146871,"model":"step-5-preview","choices":[{"index":0,"delta":{"role":"","content":""},"finish_reason":"stop"}],"usage":{"prompt_tokens":90,"completion_tokens":24,"total_tokens":114}} > > data: [DONE] > > ``` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.