Gemini 正在思考

Gemini 3 和 2.5 系列模型采用“思考过程”，可显著提升推理和多步规划能力，因此非常适合处理编码、高等数学和数据分析等复杂任务。

使用思考模型时，Gemini 会在内部进行推理，然后再做出回答。Interactions API 通过 thought 步骤（按时间顺序显示在 steps 数组中的专用步骤）展示这种推理过程。

每个思考步骤都包含两个字段：

字段 必填 说明
signature ✅ 是 模型内部推理状态的加密表示形式。始终存在，即使模型执行的推理最少也是如此。
summary ❌ 否 总结推理过程的内容（文本和/或图片）数组。可能会为空，具体取决于 thinking_summaries 配置、模型是否进行了足够的推理，或者内容类型（例如，图片潜在空间可能没有文本摘要）。

与思考的互动

与思考模型互动与任何其他互动请求类似。在 model 字段中指定支持思考的模型之一：

Python

# This will only work for SDK newer than 2.0.0
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input="Explain the concept of Occam's Razor and provide a simple, everyday example."
)
print(interaction.steps[-1].content[0].text)

JavaScript

// This will only work for SDK newer than 2.0.0
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    model: "gemini-3-flash-preview",
    input: "Explain the concept of Occam's Razor and provide a simple, everyday example."
});
console.log(interaction.steps.at(-1).content[0].text);

REST

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Api-Revision: 2026-05-20" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Explain the concept of Occam'\''s Razor and provide a simple example."
  }'

思考总结

思考总结可提供对模型内部推理过程的洞见。 默认情况下，仅返回最终输出。您可以使用 thinking_summaries 启用思路总结：

Python

# This will only work for SDK newer than 2.0.0
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input="What is the sum of the first 50 prime numbers?",
    generation_config={
        "thinking_summaries": "auto"
    }
)

for step in interaction.steps:
    if step.type == "thought":
        print("Thought summary:")
        if step.summary:
            for content_block in step.summary:
                if content_block.type == "text":
                    print(content_block.text)
        print()
    elif step.type == "model_output":
        for content_block in step.content:
            if content_block.type == "text":
                print("Answer:")
                print(content_block.text)
                print()

JavaScript

// This will only work for SDK newer than 2.0.0
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    model: "gemini-3-flash-preview",
    input: "What is the sum of the first 50 prime numbers?",
    generation_config: {
        thinking_summaries: "auto"
    }
});

for (const step of interaction.steps) {
    if (step.type === "thought") {
        console.log("Thought summary:");
        if (step.summary) {
            for (const contentBlock of step.summary) {
                if (contentBlock.type === "text") console.log(contentBlock.text);
            }
        }
    } else if (step.type === "model_output") {
        for (const contentBlock of step.content) {
            if (contentBlock.type === "text") {
                console.log("Answer:");
                console.log(contentBlock.text);
            }
        }
    }
}

REST

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Api-Revision: 2026-05-20" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "What is the sum of the first 50 prime numbers?",
    "generation_config": {
      "thinking_summaries": "auto"
    }
  }'

在以下情况下，思想块可能仅包含签名，而不包含摘要：

  • 简单请求，模型未进行充分推理来生成摘要
  • thinking_summaries: "none"，其中明确停用了摘要
  • 某些想法内容类型（例如图片）可能没有文字摘要

您的代码应始终处理 summary 为空或缺失的思考块。

包含思考过程的流式传输

使用流式传输在生成期间接收增量思维摘要。 系统会使用服务器发送的事件 (SSE) 传送思路块，其中包含两种不同的增量类型：

增量类型 包含 发送时间
thought_summary 文字或图片摘要内容 一个或多个增量（带有增量摘要）
thought_signature 加密签名 step.stop之前的最后一个增量

Python

# This will only work for SDK newer than 2.0.0
from google import genai

client = genai.Client()

prompt = """
Alice, Bob, and Carol each live in a different house on the same street: red, green, and blue.
Alice does not live in the red house.
Bob does not live in the green house.
Carol does not live in the red or green house.
Which house does each person live in?
"""

thoughts = ""
answer = ""

stream = client.interactions.create(
    model="gemini-3-flash-preview",
    input=prompt,
    generation_config={
        "thinking_summaries": "auto"
    },
    stream=True
)

for event in stream:
    if event.event_type == "step.delta":
        if event.delta.type == "thought_summary":
            if not thoughts:
                print("Thinking...")
            summary_text = event.delta.content.text
            print(f"[Thought] {summary_text}", end="")
            thoughts += summary_text
        elif event.delta.type == "text" and event.delta.text:
            if not answer:
                print("\nAnswer:")
            print(event.delta.text, end="")
            answer += event.delta.text

JavaScript

// This will only work for SDK newer than 2.0.0
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const prompt = `Alice, Bob, and Carol each live in a different house on the same
street: red, green, and blue. Alice does not live in the red house.
Bob does not live in the green house.
Carol does not live in the red or green house.
Which house does each person live in?`;

let thoughts = "";
let answer = "";

const stream = await client.interactions.create({
    model: "gemini-3-flash-preview",
    input: prompt,
    generation_config: {
        thinking_summaries: "auto"
    },
    stream: true
});

for await (const event of stream) {
    if (event.event_type === "step.delta") {
        if (event.delta.type === "thought_summary") {
            if (!thoughts) console.log("Thinking...");
            const text = event.delta.content?.text || "";
            process.stdout.write(`[Thought] ${text}`);
            thoughts += text;
        } else if (event.delta.type === "text" && event.delta.text) {
            if (!answer) console.log("\nAnswer:");
            process.stdout.write(event.delta.text);
            answer += event.delta.text;
        }
    }
}

REST

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Api-Revision: 2026-05-20" \
  -H 'Content-Type: application/json' \
  --no-buffer \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Alice, Bob, and Carol each live in a different house on the same street: red, green, and blue. Alice does not live in the red house. Bob does not live in the green house. Carol does not live in the red or green house. Which house does each person live in?",
    "generation_config": {
      "thinking_summaries": "auto"
    },
    "stream": true
  }'

流式回答使用服务器发送的事件 (SSE)，由步骤和事件组成。请参阅下文的示例。

event: interaction.created
data: {"interaction":{"id":"v1_xxx","status":"in_progress","object":"interaction","model":"gemini-3-flash-preview"},"event_type":"interaction.created"}

event: step.start
data: {"index":0,"step":{"signature":"","summary":[{"text":"**Evaluating the clues**\n\nI'm considering...","type":"text"}],"type":"thought"},"event_type":"step.start"}

event: step.delta
data: {"index":0,"delta":{"signature":"EpoGCpcGAXLI2nx/...","type":"thought_signature"},"event_type":"step.delta"}

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

event: step.start
data: {"index":1,"step":{"content":[{"text":"Based on the clues provided, here","type":"text"}],"type":"model_output"},"event_type":"step.start"}

event: step.delta
data: {"index":1,"delta":{"text":" is the answer to your question...","type":"text"},"event_type":"step.delta"}

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

event: interaction.completed
data: {"interaction":{"id":"v1_xxx","status":"completed","usage":{"total_tokens":530,"total_input_tokens":62,"total_output_tokens":171,"total_thought_tokens":297}},"event_type":"interaction.completed"}

event: done
data: [DONE]

控制思维

Gemini 模型默认采用动态思维，会根据请求的复杂程度自动调整推理力度。您可以使用 thinking_level 参数控制此行为。

模型 默认思维 支持的级别
gemini-3.1-pro-preview 开启（高） 低、中、高
gemini-3-flash-preview 开启（高） 极低、低、中、高
gemini-3-pro-preview 开启（高） 低、高
gemini-2.5-pro 开启 低、中、高
gemini-2.5-flash 开启 低、中、高
gemini-2.5-flash-lite 关闭 低、中、高

Python

# This will only work for SDK newer than 2.0.0
from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input="Provide a list of 3 famous physicists and their key contributions",
    generation_config={
        "thinking_level": "low"
    }
)
print(interaction.steps[-1].content[0].text)

JavaScript

// This will only work for SDK newer than 2.0.0
import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
    model: "gemini-3-flash-preview",
    input: "Provide a list of 3 famous physicists and their key contributions",
    generation_config: {
        thinking_level: "low"
    }
});
console.log(interaction.steps.at(-1).content[0].text);

REST

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "Api-Revision: 2026-05-20" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Provide a list of 3 famous physicists and their key contributions",
    "generation_config": {
      "thinking_level": "low"
    }
  }'

思考签名

思考特征是模型内部推理的加密表示形式。它们需要在多轮互动中保持推理的连续性。

与 generateContent API 相比，Interactions API 可让处理意念签名变得更加简单。

默认情况下，当您在有状态模式下使用 Interactions API 时（通过设置 store: true 并在后续轮次中传递 previous_interaction_id），服务器会自动管理对话状态，包括所有思考块和签名。在此模式下，您无需针对签名执行任何操作。它们完全在服务器端处理。

无状态模式

如果您自行管理对话状态（无状态模式），并在每次请求中传递完整的输入和输出历史记录，请执行以下操作：

  • 您必须始终完全按照从模型收到的方式重新发送所有 thought 代码块。
  • 您不应从历史记录中移除或修改思考块，因为它们包含模型继续推理所需的签名。
  • 在会话中切换模型时，您仍应重新发送之前模型的思考块。后端会管理兼容性。

价格

开启思考功能后，回答价格是输出 token 和思考 token 的总和。您可以从 total_thought_tokens 字段获取生成的思考令牌总数。

Python

# This will only work for SDK newer than 2.0.0
# ...
print("Thoughts tokens:", interaction.usage.total_thought_tokens)
print("Output tokens:", interaction.usage.total_output_tokens)

JavaScript

// This will only work for SDK newer than 2.0.0
// ...
console.log(`Thoughts tokens: ${interaction.usage.total_thought_tokens}`);
console.log(`Output tokens: ${interaction.usage.total_output_tokens}`);

思考模型会生成完整的想法，以提高最终回答的质量，然后输出总结，以便深入了解思考过程。尽管 API 只输出摘要，但价格仍基于模型需要生成的完整思考令牌数。

如需详细了解令牌，请参阅令牌计数指南。

最佳做法

遵循以下准则，可高效使用思考模型。

  • 查看推理过程：分析思维总结，了解失败原因并改进提示。
  • 控制思考预算：提示模型减少思考，以节省 token。
  • 简单任务：只需少量思考即可完成事实检索或分类（例如“DeepMind 是在哪里成立的？”）。
  • 中等任务：使用默认的思考模式来比较概念或进行创意推理（例如，比较电动汽车和混合动力汽车）。
  • 复杂任务：使用最大思考量来处理高级编码、数学或多步规划任务（例如，解决 AIME 数学问题）。

后续步骤