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

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Web Fetch

The web fetch tool allows LLMs to retrieve full content from specified web pages and PDF documents. This enables AI models to access real-time information from the internet and incorporate web content into their responses.

Web Fetch vs Web Search

Web Fetch retrieves the full content from specific web pages that you provide URLs for, while Web Search performs internet searches to find relevant information based on your queries.

Feature	Web Fetch	Web Search
Purpose	Retrieve content from specific URLs	Search the internet for information
Input	You provide exact URLs to fetch	You provide search queries/questions
Output	Full page content from specified URLs	Search results with relevant information
Use Cases	- Analyzing specific articles - Comparing content from known websites - Extracting data from particular pages	- Finding current news/events - Researching topics - Getting real-time information

Example Web Fetch: "Fetch the content from https://example.com/pricing and summarize it"
Example Web Search: "What are the latest AI developments this week?"

Supported Providers:

• Anthropic API (anthropic/)

Supported Tool Types:

• web_fetch_20250910 - Web content retrieval tool with usage limits, domain filtering, and citation support

Quick Start

LiteLLM Python SDK

import os 
from litellm import completion

os.environ["ANTHROPIC_API_KEY"] = "your-api-key"

# Web fetch tool
tools = [
    {
        "type": "web_fetch_20250910",
        "name": "web_fetch",
        "max_uses": 5,
    }
]

messages = [
    {
        "role": "user", 
        "content": "Please analyze the content at https://example.com/article and summarize the main points"
    }
]

response = completion(
    model="anthropic/claude-3-5-sonnet-latest",
    messages=messages,
    tools=tools,
)

print(response)

LiteLLM Proxy

1. Define web fetch models on config.yaml

model_list:
  - model_name: claude-3-5-sonnet-latest # Anthropic claude-3-5-sonnet-latest
    litellm_params:
      model: anthropic/claude-3-5-sonnet-latest
      api_key: os.environ/ANTHROPIC_API_KEY

2. Run proxy server

litellm --config config.yaml

3. Test it using the OpenAI Python SDK

import os 
from openai import OpenAI

client = OpenAI(
    api_key="sk-1234", # your litellm proxy api key
    base_url="http://0.0.0.0:4000"
)

response = client.chat.completions.create(
    model="claude-3-5-sonnet-latest",
    messages=[
        {
            "role": "user", 
            "content": "Please fetch and analyze the content from https://news.ycombinator.com and tell me about the top stories"
        }
    ],
    tools=[
        {
            "type": "web_fetch_20250910",
            "name": "web_fetch",
            "max_uses": 5,
        }
    ]
)

print(response)

Supported Models

Web fetch is available on the following Anthropic API models:

• claude-opus-4-1-20250805 (Claude Opus 4.1)
• claude-opus-4-20250514 (Claude Opus 4)
• claude-sonnet-4-20250514 (Claude Sonnet 4)
• claude-3-7-sonnet-20250219 (Claude Sonnet 3.7)
• claude-3-5-sonnet-latest (Claude Sonnet 3.5 v2 - deprecated)
• claude-3-5-haiku-latest (Claude Haiku 3.5)

:::note The web fetch tool currently does not support websites dynamically rendered via JavaScript. :::

Usage Examples

Basic Web Content Retrieval

import os 
from litellm import completion

os.environ["ANTHROPIC_API_KEY"] = "your-api-key"

tools = [
    {
        "type": "web_fetch_20250910",
        "name": "web_fetch",
        "max_uses": 3,
    }
]

messages = [
    {
        "role": "user",
        "content": "Fetch the latest news from https://techcrunch.com and summarize the top 3 articles"
    }
]

response = completion(
    model="anthropic/claude-3-5-sonnet-latest",
    messages=messages,
    tools=tools,
)

print(response)

Research and Analysis

import os 
from litellm import completion

os.environ["ANTHROPIC_API_KEY"] = "your-api-key"

tools = [
    {
        "type": "web_fetch_20250910",
        "name": "web_fetch", 
        "max_uses": 10,
    }
]

messages = [
    {
        "role": "user",
        "content": "Research the latest developments in AI by fetching content from multiple tech news websites and provide a comprehensive analysis"
    }
]

response = completion(
    model="anthropic/claude-3-5-sonnet-latest",
    messages=messages,
    tools=tools,
)

print(response)

Content Comparison

import os 
from litellm import completion

os.environ["ANTHROPIC_API_KEY"] = "your-api-key"

tools = [
    {
        "type": "web_fetch_20250910",
        "name": "web_fetch",
        "max_uses": 5,
    }
]

messages = [
    {
        "role": "user",
        "content": "Compare the pricing information from https://openai.com/pricing and https://anthropic.com/pricing and create a comparison table"
    }
]

response = completion(
    model="anthropic/claude-3-5-sonnet-latest",
    messages=messages,
    tools=tools,
)

print(response)

Advanced Usage with Multiple Tools

You can combine web fetch with other tools like computer use or text editor:

import os 
from litellm import completion

os.environ["ANTHROPIC_API_KEY"] = "your-api-key"

tools = [
    {
        "type": "web_fetch_20250910",
        "name": "web_fetch",
        "max_uses": 5,
    },
    {
        "type": "text_editor_20250124", 
        "name": "str_replace_editor"
    }
]

messages = [
    {
        "role": "user",
        "content": "Fetch the latest AI research papers from arXiv, analyze them, and create a detailed report file with your findings"
    }
]
    
response = completion(
    model="anthropic/claude-3-5-sonnet-latest",
    messages=messages,
    tools=tools,
)

print(response)

Spec

Web Fetch Tool (web_fetch_20250910)

The web fetch tool supports the following parameters:

{
  "type": "web_fetch_20250910",
  "name": "web_fetch",

  // Optional: Limit the number of fetches per request
  "max_uses": 10,

  // Optional: Only fetch from these domains
  "allowed_domains": ["example.com", "docs.example.com"],

  // Optional: Never fetch from these domains
  "blocked_domains": ["private.example.com"],

  // Optional: Enable citations for fetched content
  "citations": {
    "enabled": true
  },

  // Optional: Maximum content length in tokens
  "max_content_tokens": 100000
}