google-web-search

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Google Web Search

Google 网页搜索

Overview

概述

This skill provides the capability to perform real-time web searches via the Gemini API's

google_search

grounding tool. It is designed to fetch the most current information available on the web to provide grounded, citable answers to user queries.

Key Features:

Real-time web search via Gemini API
Grounded responses with verifiable citations
Configurable model selection
Simple Python API

本Skill可通过Gemini API的

google_search

grounding工具执行实时网页搜索。它旨在获取网络上最新的可用信息，为用户的查询提供基于事实、可引用的答案。

核心特性：

通过Gemini API实现实时网页搜索
提供带有可验证引用的基于事实的响应
可配置模型选择
简洁的Python API

Usage

使用方法

This skill exposes the Gemini API's

google_search

tool. It should be used when the user asks for real-time information, recent events, or requests verifiable citations.

本Skill封装了Gemini API的

google_search

工具。当用户询问实时信息、近期事件或要求可验证引用时，应使用本Skill。

Execution Context

执行环境

The core logic is in

scripts/example.py

. This script requires the following environment variables:

GEMINI_API_KEY (required): Your Gemini API key
GEMINI_MODEL (optional): Model to use (default:
```
gemini-2.5-flash-lite
```
)

Supported Models:

```
gemini-2.5-flash-lite
```
(default) - Fast and cost-effective
```
gemini-3-flash-preview
```
- Latest flash model
```
gemini-3-pro-preview
```
- More capable, slower
```
gemini-2.5-flash-lite-preview-09-2025
```
- Specific version

核心逻辑位于

scripts/example.py

脚本中。该脚本需要以下环境变量：

GEMINI_API_KEY（必填）：您的Gemini API密钥
GEMINI_MODEL（可选）：使用的模型（默认值：
```
gemini-2.5-flash-lite
```
）

支持的模型：

```
gemini-2.5-flash-lite
```
（默认）- 快速且经济高效
```
gemini-3-flash-preview
```
- 最新的flash模型
```
gemini-3-pro-preview
```
- 功能更强，速度稍慢
```
gemini-2.5-flash-lite-preview-09-2025
```
- 特定版本

Python Tool Implementation Pattern

Python工具实现模式

When integrating this skill into a larger workflow, the helper script should be executed in an environment where the

google-genai

library is available and the

GEMINI_API_KEY

is exposed.

Example Python invocation structure:

python

from skills.google-web-search.scripts.example import get_grounded_response

将本Skill集成到更大的工作流中时，辅助脚本应在已安装

google-genai

库且已配置

GEMINI_API_KEY

的环境中执行。

Python调用示例结构：

python

from skills.google-web-search.scripts.example import get_grounded_response

Basic usage (uses default model):

基础用法（使用默认模型）：

prompt = "What is the latest market trend?" response_text = get_grounded_response(prompt) print(response_text)

Using a specific model:

使用特定模型：

response_text = get_grounded_response(prompt, model="gemini-3-pro-preview") print(response_text)

Or set via environment variable:

或通过环境变量设置：

import os os.environ["GEMINI_MODEL"] = "gemini-3-flash-preview" response_text = get_grounded_response(prompt) print(response_text)

undefined

import os os.environ["GEMINI_MODEL"] = "gemini-3-flash-preview" response_text = get_grounded_response(prompt) print(response_text)

undefined

Troubleshooting

故障排除

If the script fails:

Missing API Key: Ensure
```
GEMINI_API_KEY
```
is set in the execution environment.
Library Missing: Verify that the
```
google-genai
```
library is installed (
```
pip install google-generativeai
```
).
API Limits: Check the API usage limits on the Google AI Studio dashboard.
Invalid Model: If you set
```
GEMINI_MODEL
```
, ensure it's a valid Gemini model name.
Model Not Supporting Grounding: Some models may not support the
```
google_search
```
tool. Use flash or pro variants.

如果脚本运行失败：

缺少API密钥：确保执行环境中已设置
```
GEMINI_API_KEY
```
。
缺少依赖库：确认已安装
```
google-genai
```
库（执行
```
pip install google-generativeai
```
）。
API限制：在Google AI Studio控制台检查API使用限制。
无效模型：如果设置了
```
GEMINI_MODEL
```
，请确保它是有效的Gemini模型名称。
模型不支持Grounding：部分模型可能不支持
```
google_search
```
工具，请使用flash或pro系列模型。