litellm/docs/my-website/docs/completion/web_search.md

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Web Search

Use web search with litellm

Feature	Details
Supported Endpoints	- /chat/completions - /responses
Supported Providers	openai, xai, vertex_ai, anthropic, gemini, perplexity
LiteLLM Cost Tracking	✅ Supported
LiteLLM Version	v1.71.0+

Which Search Engine is Used?

Each provider uses their own search backend:

Provider	Search Engine	Notes
OpenAI (gpt-4o-search-preview)	OpenAI's internal search	Real-time web data
xAI (grok-3)	xAI's search + X/Twitter	Real-time social media data
Google AI/Vertex (gemini-2.0-flash)	Google Search	Uses actual Google search results
Anthropic (claude-3-5-sonnet)	Anthropic's web search	Real-time web data
Perplexity	Perplexity's search engine	AI-powered search and reasoning

:::info Anthropic Web Search Models: Claude models that support web search: claude-3-5-sonnet-latest, claude-3-5-sonnet-20241022, claude-3-5-haiku-latest, claude-3-5-haiku-20241022, claude-3-7-sonnet-20250219 :::

/chat/completions (litellm.completion)

Quick Start

from litellm import completion

response = completion(
    model="openai/gpt-4o-search-preview",
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?",
        }
    ],
    web_search_options={
        "search_context_size": "medium"  # Options: "low", "medium", "high"
    }
)

1. Setup config.yaml

model_list:
  # OpenAI
  - model_name: gpt-4o-search-preview
    litellm_params:
      model: openai/gpt-4o-search-preview
      api_key: os.environ/OPENAI_API_KEY
  
  # xAI
  - model_name: grok-3
    litellm_params:
      model: xai/grok-3
      api_key: os.environ/XAI_API_KEY
  
  # Anthropic
  - model_name: claude-3-5-sonnet-latest
    litellm_params:
      model: anthropic/claude-3-5-sonnet-latest
      api_key: os.environ/ANTHROPIC_API_KEY
  
  # VertexAI
  - model_name: gemini-2-flash
    litellm_params:
      model: gemini-2.0-flash
      vertex_project: your-project-id
      vertex_location: us-central1
  
  # Google AI Studio
  - model_name: gemini-2-flash-studio
    litellm_params:
      model: gemini/gemini-2.0-flash
      api_key: os.environ/GOOGLE_API_KEY

2. Start the proxy

litellm --config /path/to/config.yaml

3. Test it!

from openai import OpenAI

# Point to your proxy server
client = OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

response = client.chat.completions.create(
    model="grok-3",  # or any other web search enabled model
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?"
        }
    ]
)

Search context size

OpenAI (using web_search_options)

from litellm import completion

# Customize search context size
response = completion(
    model="openai/gpt-4o-search-preview",
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?",
        }
    ],
    web_search_options={
        "search_context_size": "low"  # Options: "low", "medium" (default), "high"
    }
)

xAI (using web_search_options)

from litellm import completion

# Customize search context size for xAI
response = completion(
    model="xai/grok-3",
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?",
        }
    ],
    web_search_options={
        "search_context_size": "high"  # Options: "low", "medium" (default), "high"
    }
)

Anthropic (using web_search_options)

from litellm import completion

# Customize search context size for Anthropic
response = completion(
    model="anthropic/claude-3-5-sonnet-latest",
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?",
        }
    ],
    web_search_options={
        "search_context_size": "medium",  # Options: "low", "medium" (default), "high"
        "user_location": {
            "type": "approximate",
            "approximate": {
                "city": "San Francisco",
            },
        }
    }
)

VertexAI/Gemini (using web_search_options)

from litellm import completion

# Customize search context size for Gemini
response = completion(
    model="gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?",
        }
    ],
    web_search_options={
        "search_context_size": "low"  # Options: "low", "medium" (default), "high"
    }
)

from openai import OpenAI

# Point to your proxy server
client = OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

# Customize search context size
response = client.chat.completions.create(
    model="grok-3",  # works with any web search enabled model
    messages=[
        {
            "role": "user",
            "content": "What was a positive news story from today?"
        }
    ],
    web_search_options={
        "search_context_size": "low"  # Options: "low", "medium" (default), "high"
    }
)

/responses (litellm.responses)

Quick Start

from litellm import responses

response = responses(
    model="openai/gpt-4o",
    input=[
        {
            "role": "user",
            "content": "What was a positive news story from today?"
        }
    ],
    tools=[{
        "type": "web_search_preview"  # enables web search with default medium context size
    }]
)

1. Setup config.yaml

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: openai/gpt-4o
      api_key: os.environ/OPENAI_API_KEY

2. Start the proxy

litellm --config /path/to/config.yaml

3. Test it!

from openai import OpenAI

# Point to your proxy server
client = OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

response = client.responses.create(
    model="gpt-4o",
    tools=[{
        "type": "web_search_preview"
    }],
    input="What was a positive news story from today?",
)

print(response.output_text)

Search context size

from litellm import responses

# Customize search context size
response = responses(
    model="openai/gpt-4o",
    input=[
        {
            "role": "user",
            "content": "What was a positive news story from today?"
        }
    ],
    tools=[{
        "type": "web_search_preview",
        "search_context_size": "low"  # Options: "low", "medium" (default), "high"
    }]
)

from openai import OpenAI

# Point to your proxy server
client = OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

# Customize search context size
response = client.responses.create(
    model="gpt-4o",
    tools=[{
        "type": "web_search_preview",
        "search_context_size": "low"  # Options: "low", "medium" (default), "high"
    }],
    input="What was a positive news story from today?",
)

print(response.output_text)

Configuring Web Search in config.yaml

You can set default web search options directly in your proxy config file:

model_list:
  # Enable web search by default for all requests to this model
  - model_name: grok-3
    litellm_params:
      model: xai/grok-3
      api_key: os.environ/XAI_API_KEY
      web_search_options: {}  # Enables web search with default settings

Advanced

You can configure LiteLLM's router to optionally drop models that do not support WebSearch, for example

  - model_name: gpt-4.1
    litellm_params:
      model: openai/gpt-4.1
  - model_name: gpt-4.1
    litellm_params:
      model: azure/gpt-4.1
      api_base: "x.openai.azure.com/"
      api_version: 2025-03-01-preview
    model_info:
      supports_web_search: False <---- KEY CHANGE!

In this example, LiteLLM will still route LLM requests to both deployments, but for WebSearch, will solely route to OpenAI.

model_list:
  # Set custom web search context size
  - model_name: grok-3
    litellm_params:
      model: xai/grok-3
      api_key: os.environ/XAI_API_KEY
      web_search_options:
        search_context_size: "high"  # Options: "low", "medium", "high"
  
  # Different context size for different models
  - model_name: gpt-4o-search-preview
    litellm_params:
      model: openai/gpt-4o-search-preview
      api_key: os.environ/OPENAI_API_KEY
      web_search_options:
        search_context_size: "low"
  
  # Gemini with medium context (default)
  - model_name: gemini-2-flash
    litellm_params:
      model: gemini-2.0-flash
      vertex_project: your-project-id
      vertex_location: us-central1
      web_search_options:
        search_context_size: "medium"

Note: When web_search_options is set in the config, it applies to all requests to that model. Users can still override these settings by passing web_search_options in their API requests.

Checking if a model supports web search

Use litellm.supports_web_search(model="model_name") -> returns True if model can perform web searches

# Check OpenAI models
assert litellm.supports_web_search(model="openai/gpt-4o-search-preview") == True

# Check xAI models
assert litellm.supports_web_search(model="xai/grok-3") == True

# Check Anthropic models
assert litellm.supports_web_search(model="anthropic/claude-3-5-sonnet-latest") == True

# Check VertexAI models
assert litellm.supports_web_search(model="gemini-2.0-flash") == True

# Check Google AI Studio models
assert litellm.supports_web_search(model="gemini/gemini-2.0-flash") == True

1. Define models in config.yaml

model_list:
  # OpenAI
  - model_name: gpt-4o-search-preview
    litellm_params:
      model: openai/gpt-4o-search-preview
      api_key: os.environ/OPENAI_API_KEY
    model_info:
      supports_web_search: True
  
  # xAI
  - model_name: grok-3
    litellm_params:
      model: xai/grok-3
      api_key: os.environ/XAI_API_KEY
    model_info:
      supports_web_search: True
  
  # Anthropic
  - model_name: claude-3-5-sonnet-latest
    litellm_params:
      model: anthropic/claude-3-5-sonnet-latest
      api_key: os.environ/ANTHROPIC_API_KEY
    model_info:
      supports_web_search: True
  
  # VertexAI
  - model_name: gemini-2-flash
    litellm_params:
      model: gemini-2.0-flash
      vertex_project: your-project-id
      vertex_location: us-central1
    model_info:
      supports_web_search: True
  
  # Google AI Studio
  - model_name: gemini-2-flash-studio
    litellm_params:
      model: gemini/gemini-2.0-flash
      api_key: os.environ/GOOGLE_API_KEY
    model_info:
      supports_web_search: True

2. Run proxy server

litellm --config config.yaml

3. Call /model_group/info to check if a model supports web search

curl -X 'GET' \
  'http://localhost:4000/model_group/info' \
  -H 'accept: application/json' \
  -H 'x-api-key: sk-1234'

Expected Response

{
  "data": [
    {
      "model_group": "gpt-4o-search-preview",
      "providers": ["openai"],
      "max_tokens": 128000,
      "supports_web_search": true
    },
    {
      "model_group": "grok-3",
      "providers": ["xai"],
      "max_tokens": 131072,
      "supports_web_search": true
    },
    {
      "model_group": "gemini-2-flash",
      "providers": ["vertex_ai"],
      "max_tokens": 8192,
      "supports_web_search": true
    }
  ]
}