Web Search

Web search lets LLMs access real-time information from the internet when generating responses. Instead of relying solely on training data, the model can search the web to ground its answers with up-to-date facts, links, and sources.

How It Works

Enable web search by adding web_search_options to your chat completion request. When enabled, the model will:

Analyze the user’s query to determine if web search is needed.
Search the web for relevant, current information.
Generate a response grounded in the search results, often including source citations.

Basic Example

import requests

url = "https://api.edenai.run/v3/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "model": "openai/gpt-5.2",
    "messages": [
        {"role": "user", "content": "What are the latest developments in AI regulation in 2025?"}
    ],
    "web_search_options": {
        "search_context_size": "medium"
    }
}

response = requests.post(url, headers=headers, json=payload)
result = response.json()
print(result["choices"][0]["message"]["content"])

const url = 'https://api.edenai.run/v3/chat/completions';
const headers = {
  'Authorization': 'Bearer YOUR_API_KEY',
  'Content-Type': 'application/json'
};

const payload = {
  model: 'openai/gpt-4o',
  messages: [
    { role: 'user', content: 'What are the latest developments in AI regulation in 2025?' }
  ],
  web_search_options: {
    search_context_size: 'medium'
  }
};

const response = await fetch(url, {
  method: 'POST',
  headers: headers,
  body: JSON.stringify(payload)
});

const result = await response.json();
console.log(result.choices[0].message.content);

curl -X POST https://api.edenai.run/v3/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-4o",
    "messages": [
      {"role": "user", "content": "What are the latest developments in AI regulation in 2025?"}
    ],
    "web_search_options": {
      "search_context_size": "medium"
    }
  }'

Supported Models

Not all models support web search. Use the List LLM Models endpoint to find models where capabilities.web_search is true.

Parameters

Parameter	Type	Description
`web_search_options`	object	Options for web search integration. Omit to disable web search.
`web_search_options.search_context_size`	string	Amount of context retrieved from the web. Options: `"low"`, `"medium"`, `"high"`. Default: `"medium"`

With System Messages

Combine web search with system messages to control how the model uses search results:

import requests

url = "https://api.edenai.run/v3/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "model": "google/gemini-2.5-flash",
    "messages": [
        {
            "role": "system",
            "content": "You are a research assistant. When answering, always cite your sources with URLs."
        },
        {
            "role": "user",
            "content": "What is the current stock price of Apple?"
        }
    ],
    "web_search_options": {
        "search_context_size": "high"
    }
}

response = requests.post(url, headers=headers, json=payload)
result = response.json()
print(result["choices"][0]["message"]["content"])

When to Use Web Search

Web search is useful when the user’s question involves:

Current events — news, stock prices, weather, sports scores
Recent releases — software versions, product launches, research papers
Factual lookups — statistics, regulations, schedules that change over time
Verification — checking claims against live sources

For questions about static knowledge (math, programming concepts, general reasoning), web search adds latency without much benefit. Only enable it when freshness matters.

Next Steps

Topic Extraction

Extract structured topics from text with Expert Models

V3 Documentation

Quick Start

Overview

LLMs

Expert Models

General

Organization

Data Governance

Integrations

How It Works

Basic Example

Supported Models

Parameters

With System Messages

When to Use Web Search

Next Steps

Topic Extraction

​How It Works

​Basic Example

​Supported Models

​Parameters

​With System Messages

​When to Use Web Search

​Next Steps

Topic Extraction

How It Works

Basic Example

Supported Models

Parameters

With System Messages

When to Use Web Search

Next Steps