网址上下文

您可以使用网址上下文工具为 Gemini 提供网址，作为提示的额外上下文。然后，模型可以从网址中检索内容，并使用该内容来提供和调整回答。

此工具适用于以下任务：

  • 从文章中提取关键数据点或谈话要点
  • 比较多个链接中的信息
  • 综合来自多个来源的数据
  • 根据特定网页的内容回答问题
  • 出于特定目的（例如撰写职位描述或创建测试题）分析内容

本指南介绍了如何使用 Vertex AI 中 Gemini API 的网址上下文工具。

支持的模型

以下模型提供对网址上下文的支持：

使用网址上下文

您可以通过两种主要方式使用网址上下文工具：单独使用或与依托 Google 搜索进行接地搭配使用。

仅限网址上下文

您可以在提示中直接提供要让模型分析的具体网址：

Summarize this document: YOUR_URLs

Extract the key features from the product description on this page: YOUR_URLs

Python

from google import genai
from google.genai.types import Tool, GenerateContentConfig, HttpOptions, UrlContext

client = genai.Client(http_options=HttpOptions(api_version="v1"))
model_id = "gemini-2.5-flash"

url_context_tool = Tool(
    url_context = UrlContext
)

response = client.models.generate_content(
    model=model_id,
    contents="Compare recipes from YOUR_URL1 and YOUR_URL2",
    config=GenerateContentConfig(
        tools=[url_context_tool],
        response_modalities=["TEXT"],
    )
)

for each in response.candidates[0].content.parts:
    print(each.text)
# get URLs retrieved for context
print(response.candidates[0].url_context_metadata)

JavaScript

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_VERTEXAI=True

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

const ai = new GoogleGenAI({
  vertexai: true,
  project: process.env.GOOGLE_CLOUD_PROJECT,
  location: process.env.GOOGLE_CLOUD_LOCATION,
  apiVersion: 'v1',
});

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.5-flash",
    contents: [
        "Compare recipes from YOUR_URL1 and YOUR_URL2",
    ],
    config: {
      tools: [{urlContext: {}}],
    },
  });
  console.log(response.text);
  // To get URLs retrieved for context
  console.log(response.candidates[0].urlContextMetadata)
}

await main();

REST

curl -X POST \
  -H "Authorization: Bearer $(gcloud auth print-access-token)" \
  -H "Content-Type: application/json" \
  https://aiplatform.googleapis.com/v1beta1/projects/GOOGLE_CLOUD_PROJECT/locations/global/publishers/google/models/gemini-2.5-flash:generateContent \
  -d '{
      "contents": [
          {
              "role": "user",
              "parts": [
                  {"text": "Compare recipes from YOUR_URL1 and YOUR_URL2"}
              ]
          }
      ],
      "tools": [
          {
              "url_context": {}
          }
      ]
  }' > result.json

cat result.json

依托 Google 搜索进行接地（含网址上下文）

您还可以同时启用网址上下文和“依托 Google 搜索进行接地”，使用包含或不包含网址的提示。模型可能会先搜索相关信息，然后使用网址上下文工具读取搜索结果的内容，以便更深入地了解相关信息。

此功能为实验性功能，可在 API 版本 v1beta1 中使用。

示例提示：

Give me a three day event schedule based on YOUR_URL. Also let me know what needs to taken care of considering weather and commute.

Recommend 3 books for beginners to read to learn more about the latest YOUR_SUBJECT.

Python

from google import genai
from google.genai.types import Tool, GenerateContentConfig, HttpOptions, UrlContext, GoogleSearch

client = genai.Client(http_options=HttpOptions(api_version="v1beta1"))
model_id = "gemini-2.5-flash"

tools = []
tools.append(Tool(url_context=UrlContext))
tools.append(Tool(google_search=GoogleSearch))

response = client.models.generate_content(
    model=model_id,
    contents="Give me three day events schedule based on YOUR_URL. Also let me know what needs to taken care of considering weather and commute.",
    config=GenerateContentConfig(
        tools=tools,
        response_modalities=["TEXT"],
    )
)

for each in response.candidates[0].content.parts:
    print(each.text)
# get URLs retrieved for context
print(response.candidates[0].url_context_metadata)

JavaScript

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_VERTEXAI=True

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

const ai = new GoogleGenAI({
  vertexai: true,
  project: process.env.GOOGLE_CLOUD_PROJECT,
  location: process.env.GOOGLE_CLOUD_LOCATION,
  apiVersion: 'v1beta1',
});

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.5-flash",
    contents: [
        "Give me a three day event schedule based on YOUR_URL. Also let me know what needs to taken care of considering weather and commute.",
    ],
    config: {
      tools: [{urlContext: {}}, {googleSearch: {}}],
    },
  });
  console.log(response.text);
  // To get URLs retrieved for context
  console.log(response.candidates[0].urlContextMetadata)
}

await main();

REST

curl -X POST \
  -H "Authorization: Bearer $(gcloud auth print-access-token)" \
  -H "Content-Type: application/json" \
  https://aiplatform.googleapis.com/v1beta1/projects/GOOGLE_CLOUD_PROJECT/locations/global/publishers/google/models/gemini-2.5-flash:generateContent \
  -d '{
      "contents": [
          {
              "role": "user",
              "parts": [
                  {"text": "Give me a three day event schedule based on YOUR_URL. Also let me know what needs to taken care of considering weather and commute."}
              ]
          }
      ],
      "tools": [
          {
              "url_context": {}
          },
          {
              "google_search": {}
          }
      ]
  }' > result.json

cat result.json

如需详细了解如何“依托 Google 搜索进行接地”，请参阅概览页面。

适用于企业的 Web 接地（含网址上下文）

如果您有特定的合规性需求，或者您所在的行业受监管（例如健康、金融或公共部门），则可以同时启用网址上下文和适用于企业的 Web 接地。适用于企业的 Web 接地中使用的 Web 索引比标准“依托 Google 搜索进行接地”索引更有限，因为它使用了 Google 搜索中可用的部分内容。

如需详细了解适用于企业的 Web 接地，请参阅适用于企业的 Web 接地页面。

情境化回答

模型的回答将基于其从网址中检索到的内容。如果模型从网址中检索到了内容，回答中将包含 url_context_metadata。此类回答可能如下所示（为简洁起见，省略了部分回答）：

{
  "candidates": [
    {
      "content": {
        "parts": [
          {
            "text": "... \n"
          }
        ],
        "role": "model"
      },
      ...
      "url_context_metadata":
      {
          "url_metadata":
          [
            {
              "retrieved_url": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/code-execution",
              "url_retrieval_status": <UrlRetrievalStatus.URL_RETRIEVAL_STATUS_SUCCESS: "URL_RETRIEVAL_STATUS_SUCCESS">
            },
            {
              "retrieved_url": "https://cloud.google.com/vertex-ai/generative-ai/docs/grounding/grounding-with-google-search",
              "url_retrieval_status": <UrlRetrievalStatus.URL_RETRIEVAL_STATUS_SUCCESS: "URL_RETRIEVAL_STATUS_SUCCESS">
            },
          ]
        }
    }
  ]
}

限制

  • 该工具每次最多可使用 20 个网址进行分析。
  • 该工具不会提取网页的实时版本，因此可能会存在新鲜度问题或信息可能过时。
  • 为了在实验阶段获得最佳效果，请在标准网页上使用该工具，而不是在 YouTube 视频等多媒体内容上使用。