流式传输互动

创建 Interaction 时，您可以将 stream: true 设置为使用服务器发送的事件 (SSE) 逐步流式传输回答。

Python

from google import genai

client = genai.Client()

stream = client.interactions.create(
    model="gemini-3.6-flash",
    input="Count from 1 to 25.",
    stream=True,
)
for event in stream:
    if event.event_type == "step.delta":
        if event.delta.type == "text":
            print(event.delta.text, end="", flush=True)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const stream = await client.interactions.create({
    model: "gemini-3.6-flash",
    input: "Count from 1 to 25.",
    stream: true,
});
for await (const event of stream) {
    if (event.event_type === "step.delta") {
        if (event.delta.type === "text") {
            process.stdout.write(event.delta.text);
        }
    }
}

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  --no-buffer \
  -d '{
    "model": "gemini-3.6-flash",
    "input": "Count from 1 to 25.",
    "stream": true
  }'

event: interaction.created
data: {"interaction":{"id":"v1_...","status":"in_progress","object":"interaction","model":"gemini-3.6-flash"},"event_type":"interaction.created"}

event: interaction.status_update
data: {"interaction_id":"v1_...","status":"in_progress","event_type":"interaction.status_update"}

event: step.start
data: {"index":0,"step":{"type":"thought"},"event_type":"step.start"}

event: step.delta
data: {"index":0,"delta":{"signature":"...","type":"thought_signature"},"event_type":"step.delta"}

event: step.stop
data: {"index":0,"event_type":"step.stop"}

event: step.start
data: {"index":1,"step":{"type":"model_output"},"event_type":"step.start"}

event: step.delta
data: {"index":1,"delta":{"text":"1, 2, 3, 4, 5, 6, ","type":"text"},"event_type":"step.delta"}

event: step.delta
data: {"index":1,"delta":{"text":"7, 8, 9, 10, 11, 12, 13,","type":"text"},"event_type":"step.delta"}

...

event: step.stop
data: {"index":1,"event_type":"step.stop"}

event: interaction.completed
data: {"interaction":{"id":"v1_...","status":"completed","usage":{"total_tokens":346,"total_input_tokens":11,"input_tokens_by_modality":[{"modality":"text","tokens":11}],"total_cached_tokens":0,"total_output_tokens":90,"total_tool_use_tokens":0,"total_thought_tokens":245},"created":"2026-05-12T18:44:51Z","updated":"2026-05-12T18:44:51Z","service_tier":"standard","object":"interaction","model":"gemini-3.6-flash"},"event_type":"interaction.completed"}

event: done
data: [DONE]

事件类型

每个服务器发送的事件都包含一个名为 event_type 的名称和关联的 JSON 数据。Interactions API 使用对称的流式传输模型，其中所有内容（文本、工具调用、思考）都通过一致的基于步骤的事件进行传输。

每个数据流都遵循以下事件流：

  1. interaction.created：创建互动，包括元数据（ID、模型、状态）。
  2. 一系列步骤，每个步骤都包含：
    • step.start 事件，用于指示步骤类型（例如 model_output、thought、function_call）。
    • 一个或多个 step.delta 事件，其中包含相应步骤的增量数据。
    • 用于将步骤标记为已完成的 step.stop 事件。
  3. 具有最终 usage 统计信息的 interaction.completed 事件。

设置 stream: false 后，API 会返回一个包含 steps 数组的 interaction 对象。steps 中的每个元素都是一个 step.start → step.delta(s) → step.stop 周期的完全组装版本。

interaction.created

在首次创建互动时发送。包含互动 ID、模型和初始状态。

event: interaction.created
data: {"interaction": {"id": "...", "model": "gemini-3.6-flash", "status": "in_progress", "object": "interaction"}, "event_type": "interaction.created"}

interaction.status_update

表示互动级状态转换。可能会显示在步骤之间。

event: interaction.status_update
data: {"interaction_id": "...", "status": "in_progress", "event_type": "interaction.status_update"}

step.start

标记新步骤的开始。包含步骤 type 和 index。步数类型决定了要预期哪些增量类型，以及步数在非流式响应中的显示方式：

步骤类型 预期增量类型 说明
model_output text、image、audio 模型的最终回答内容。
thought thought_signature、thought_summary 思维链推理。仅当 thinking_summaries 处于启用状态时，才会显示 summary。
function_call arguments_delta 客户端执行函数的请求。将互动状态设置为 requires_action。
服务器端工具 因工具而异 由 API 执行的工具（例如 google_search_call、google_search_result、code_execution_call、code_execution_result）。

如需查看完整列表，请参阅互动 API 参考文档。

event: step.start
data: {"index": 0, "step": {"type": "model_output"}, "event_type": "step.start"}

对于函数调用，该步骤包括函数名称、ID 和空实参 {}。

event: step.start
data: {"index": 0, "step": {"type": "function_call", "id":"un6k8t18", "name": "get_weather", "arguments":{}}, "event_type": "step.start"}

step.delta

当前步的增量数据。delta 对象包含一个用于确定其形状的 type 字段。

示例：

text：来自 model_output 步骤的增量文本令牌：

event: step.delta
data: {"index": 0, "delta": {"type": "text", "text": "Hello, my name is Phil"}, "event_type": "step.delta"}

event: step.delta
data: {"index": 0, "delta": {"type": "text", "text": ", and I live in Germany." }, "event_type": "step.delta"}

image：来自 model_output 步骤的 Base64 编码图片数据：

event: step.delta
data: {"index": 0, "delta": {"type": "image", "mime_type": "image/jpeg", "data": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCg..."}, "event_type": "step.delta"}

thought_summary：来自 thought 步骤的思考总结内容：

event: step.delta
data: {"index": 0, "delta": {"type": "thought_summary", "content": {"type": "text", "text": "I need to find the GCD..."}}, "event_type": "step.delta"}

arguments_delta：函数调用实参的（部分）JSON 字符串。必须在多个增量中累积：

event: step.delta
data: {"index": 0, "delta": {"type": "arguments_delta", "arguments": "{\"location\": \"San Francisco, CA\"}"}, "event_type": "step.delta"}

以下是一些最常见的增量类型。如需查看所有增量类型的完整列表，请参阅 Interactions API 参考文档。

step.stop

标记步骤的结束。包含步骤 index。

event: step.stop
data: {"index": 0, "event_type": "step.stop"}

interaction.completed

互动结束时发送。包含具有 usage 统计信息的最终互动对象。在非流式模式下，这是顶级响应对象本身。不在响应中包含 steps。

event: interaction.completed
data: {"interaction": {"id": "v1_abc123", "status": "completed", "usage": {"total_input_tokens": 7, "total_output_tokens": 12, "total_tokens": 19}}, "event_type": "interaction.completed"}

error

在互动期间发生错误时发送。包含一个带有消息和代码的错误对象。

event: error
data: {"error":{"message":"Deadline expired before operation could complete.","code":"gateway_timeout"},"event_type":"error"}

使用工具进行流式传输

Interactions API 支持在单个请求中通过客户端工具（函数调用）和服务器端工具（Google 搜索、代码执行等）进行流式传输。在流式传输期间，工具调用会以输入步骤的形式显示在事件流中。对于函数调用，step.start 事件会传递函数名称，而 step.delta 事件会以 JSON 字符串 (arguments_delta) 的形式流式传输实参。您必须累积这些增量才能获得完整的实参。Google 搜索等服务器端工具由 API 自动执行，从而生成 google_search_call 和 google_search_result 步骤。

使用函数调用进行流式传输

如需使用流式处理执行函数调用，客户端必须处理多轮对话：

  1. 第 1 轮（函数请求）：使用 stream: true 和您定义的 tools 调用 interactions.create。该 API 将以流式传输 function_call 步。您必须从 step.delta 事件中累积增量实参 JSON 字符串 (arguments_delta)，直到互动以状态 requires_action 完成。
  2. 第 2 轮（发送结果）：再次调用 interactions.create，传递 previous_interaction_id（与第一次互动的 ID 匹配），并在 input 数组中发送 function_result 块。这会恢复流，使模型能够生成最终回答。

Python

from google import genai

client = genai.Client()

weather_tool = {
    "type": "function",
    "name": "get_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"
            }
        },
        "required": ["location"]
    }
}

# Turn 1: Request function call
stream = client.interactions.create(
    model="gemini-3.6-flash",
    tools=[weather_tool],
    input="What is the weather in Paris right now?",
    stream=True,
)

first_interaction_id = None
func_call_id = None
func_call_name = None
func_args_accumulated = ""

for event in stream:
    if event.event_type == "interaction.created":
        first_interaction_id = event.interaction.id
    elif event.event_type == "step.start":
        step = event.step
        if step.type == "function_call":
            func_call_id = step.id
            func_call_name = step.name
    elif event.event_type == "step.delta":
        if event.delta.type == "arguments_delta":
            func_args_accumulated += event.delta.arguments

# Turn 2: Execute tool and send the result back to resume stream
if func_call_id:
    # Execute weather_tool using accumulated arguments
    dummy_result = {
        "content": [{"type": "text", "text": '{"weather": "Sunny and 22°C"}'}]
    }

    stream2 = client.interactions.create(
        model="gemini-3.6-flash",
        previous_interaction_id=first_interaction_id,
        input=[{
            "type": "function_result",
            "name": func_call_name,
            "call_id": func_call_id,
            "result": dummy_result
        }],
        stream=True,
    )

    for event in stream2:
        if event.event_type == "step.delta":
            if event.delta.type == "text":
                print(event.delta.text, end="", flush=True)

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const weatherTool = {
    type: "function",
    name: "get_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"
            }
        },
        required: ["location"]
    }
};

// Turn 1: Request function call
const stream = await client.interactions.create({
    model: "gemini-3.6-flash",
    tools: [weatherTool],
    input: "What is the weather in Paris right now?",
    stream: true,
});

let firstInteractionId = null;
let funcCallId = null;
let funcCallName = null;
let funcArgsAccumulated = "";

for await (const event of stream) {
    if (event.event_type === "interaction.created") {
        firstInteractionId = event.interaction.id;
    } else if (event.event_type === "step.start") {
        const step = event.step;
        if (step.type === "function_call") {
            funcCallId = step.id;
            funcCallName = step.name;
        }
    } else if (event.event_type === "step.delta") {
        if (event.delta.type === "arguments_delta") {
            funcArgsAccumulated += event.delta.arguments;
        }
    }
}

// Turn 2: Execute tool and send the result back to resume stream
if (funcCallId && firstInteractionId && funcCallName) {
    const dummyResult = {
        content: [{ type: "text", text: '{"weather": "Sunny and 22°C"}' }]
    };

    const stream2 = await client.interactions.create({
        model: "gemini-3.6-flash",
        previous_interaction_id: firstInteractionId,
        input: [{
            type: "function_result",
            name: funcCallName,
            call_id: funcCallId,
            result: dummyResult
        }],
        stream: true,
    });

    for await (const event of stream2) {
        if (event.event_type === "step.delta") {
            if (event.delta.type === "text") {
                process.stdout.write(event.delta.text);
            }
        }
    }
}

REST

第 1 轮：请求函数调用

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  --no-buffer \
  -d '{
    "model": "gemini-3.6-flash",
    "input": "What is the weather in Paris right now?",
    "stream": true,
    "tools": [
      {
        "type": "function",
        "name": "get_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"
            }
          },
          "required": ["location"]
        }
      }
    ]
  }'

第 2 轮：使用第 1 轮中的 previous_interaction_id 和 call_id 发送函数结果

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  --no-buffer \
  -d '{
    "model": "gemini-3.6-flash",
    "previous_interaction_id": "v1_ChdGUVFJYXBXVUdLVEF4TjhQ...",
    "stream": true,
    "input": [
      {
        "type": "function_result",
        "name": "get_weather",
        "call_id": "CALL_ID",
        "result": {
          "content": [
            {
              "type": "text",
              "text": "{\"weather\": \"Sunny and 22°C\"}"
            }
          ]
        }
      }
    ]
  }'

使用多种工具进行直播

以下示例在一个请求中同时使用了 function 工具和 google_search：

Python

from google import genai

client = genai.Client()

tools = [
    {"type": "google_search"},
    {
        "type": "function",
        "name": "get_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"
                }
            },
            "required": ["location"]
        }
    }
]

stream = client.interactions.create(
    model="gemini-3.6-flash",
    tools=tools,
    input="Search what is the largest mountain in Europe and what the weather is there right now?",
    stream=True,
)
for event in stream:
    if event.event_type == "step.start":
        step = event.step
        print(f"\n--- Step {event.index}: {step.type} ---")
        # Show details for tool steps
        if step.type == "google_search_call":
            print(f"  Search ID: {step.id}")
        elif step.type == "google_search_result":
            print(f"  Result for: {step.call_id}")
        elif step.type == "function_call":
            print(f"  Function: {step.name}({step.arguments})")
    elif event.event_type == "step.delta":
        if event.delta.type == "text":
            print(event.delta.text, end="", flush=True)
        elif event.delta.type == "google_search_call":
            print(f"  Queries: {event.delta.arguments}")
        elif event.delta.type == "arguments_delta":
            print(f"  Args chunk: {event.delta.arguments}", end="", flush=True)
    elif event.event_type == "interaction.completed":
        print(f"\n\nStatus: {event.interaction.status}")
        if event.interaction.status == "requires_action":
            print("Action required: provide function call results to continue.")

JavaScript

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const tools = [
    { type: "google_search" },
    {
        type: "function",
        name: "get_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"
                }
            },
            required: ["location"]
        }
    }
];

const stream = await client.interactions.create({
    model: "gemini-3.6-flash",
    tools: tools,
    input: "Search what is the largest mountain in Europe and what the weather is there right now?",
    stream: true,
});
for await (const event of stream) {
    if (event.event_type === "step.start") {
        const step = event.step;
        console.log(`\n--- Step ${event.index}: ${step.type} ---`);
        // Show details for tool steps
        if (step.type === "google_search_call") {
            console.log(`  Search ID: ${step.id}`);
        } else if (step.type === "google_search_result") {
            console.log(`  Result for: ${step.call_id}`);
        } else if (step.type === "function_call") {
            console.log(`  Function: ${step.name}(${JSON.stringify(step.arguments)})`);
        }
    } else if (event.event_type === "step.delta") {
        if (event.delta.type === "text") {
            process.stdout.write(event.delta.text);
        } else if (event.delta.type === "google_search_call") {
            console.log(`  Queries: ${JSON.stringify(event.delta.arguments?.queries)}`);
        } else if (event.delta.type === "arguments_delta") {
            process.stdout.write(`  Args chunk: ${event.delta.arguments}`);
        }
    } else if (event.event_type === "interaction.completed") {
        console.log(`\n\nStatus: ${event.interaction.status}`);
        if (event.interaction.status === "requires_action") {
            console.log("Action required: provide function call results to continue.");
        }
    }
}

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  --no-buffer \
  -d '{
    "model": "gemini-3.6-flash",
    "input": "Search what is the largest mountain in Europe and what the weather is there right now?",
    "stream": true,
    "tools": [
      { "type": "google_search" },
      {
        "type": "function",
        "name": "get_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"
            }
          },
          "required": ["location"]
        }
      }
    ]
  }'

event: interaction.created
data: {"interaction":{"id":"v1_...","status":"in_progress","object":"interaction","model":"gemini-3.6-flash"},"event_type":"interaction.created"}

event: interaction.status_update
data: {"interaction_id":"v1_...","status":"in_progress","event_type":"interaction.status_update"}

event: step.start
data: {"index":0,"step":{"id":"mkutnkgn","signature":"","type":"google_search_call"},"event_type":"step.start"}

event: step.delta
data: {"index":0,"delta":{"signature":"...","type":"google_search_call","arguments":{"queries":["largest mountain in Europe"]}},