Web Search Integration

Web Search Integration

Enable transparent server-side web search execution for any LLM provider. LiteLLM automatically intercepts web search tool calls and executes them using your configured search provider (Perplexity, Tavily, etc.).

Quick Start

1. Configure Web Search Interception

Add to your config.yaml:

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

litellm_settings:
  callbacks:
    - websearch_interception:
        enabled_providers:
          - openai
          - minimax
          - anthropic
        search_tool_name: perplexity-search  # Optional

search_tools:
  - search_tool_name: perplexity-search
    litellm_params:
      search_provider: perplexity
      api_key: os.environ/PERPLEXITY_API_KEY

2. Use with Any Provider

import litellm

response = await litellm.acompletion(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "What's the weather in San Francisco today?"}
    ],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "litellm_web_search",
                "description": "Search the web for information",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "query": {"type": "string", "description": "Search query"}
                    },
                    "required": ["query"]
                }
            }
        }
    ]
)

# Response includes search results automatically!
print(response.choices[0].message.content)

How It Works

When a model makes a web search tool call, LiteLLM:

1. Detects the litellm_web_search tool call in the response
2. Executes the search using your configured search provider
3. Makes a follow-up request with the search results
4. Returns the final answer to the user

sequenceDiagram
    participant User
    participant LiteLLM
    participant LLM as LLM Provider
    participant Search as Search Provider

    User->>LiteLLM: Request with web_search tool
    LiteLLM->>LLM: Forward request
    LLM-->>LiteLLM: Response with tool_call
    Note over LiteLLM: Detect web search<br/>tool call
    LiteLLM->>Search: Execute search
    Search-->>LiteLLM: Search results
    LiteLLM->>LLM: Follow-up with results
    LLM-->>LiteLLM: Final answer
    LiteLLM-->>User: Final answer with search results

Result: One API call from user → Complete answer with search results

Supported Providers

Web search integration works with all providers that use:

• ✅ Base HTTP Handler (BaseLLMHTTPHandler)
• ✅ OpenAI Completion Handler (OpenAIChatCompletion)

Providers Using Base HTTP Handler

Providers Using OpenAI Handler

Configuration

WebSearch Interception Parameters

Provider Values

Use these values in enabled_providers:

Search Providers

Configure which search provider to use. LiteLLM supports multiple search providers:

See Search Providers Documentation for detailed setup instructions.

Complete Configuration Example

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

  # MiniMax
  - model_name: minimax
    litellm_params:
      model: minimax/MiniMax-M2.1
      api_key: os.environ/MINIMAX_API_KEY

  # Anthropic
  - model_name: claude
    litellm_params:
      model: anthropic/claude-sonnet-4-5
      api_key: os.environ/ANTHROPIC_API_KEY

  # Azure OpenAI
  - model_name: azure-gpt4
    litellm_params:
      model: azure/gpt-4
      api_base: https://my-azure.openai.azure.com
      api_key: os.environ/AZURE_API_KEY

litellm_settings:
  callbacks:
    - websearch_interception:
        enabled_providers:
          - openai
          - minimax
          - anthropic
          - azure
        search_tool_name: perplexity-search

search_tools:
  - search_tool_name: perplexity-search
    litellm_params:
      search_provider: perplexity
      api_key: os.environ/PERPLEXITY_API_KEY

  - search_tool_name: tavily-search
    litellm_params:
      search_provider: tavily
      api_key: os.environ/TAVILY_API_KEY

Usage Examples

Python SDK

import litellm

# Configure callbacks
litellm.callbacks = ["websearch_interception"]

# Make completion with web search tool
response = await litellm.acompletion(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "What are the latest AI news?"}
    ],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "litellm_web_search",
                "description": "Search the web for current information",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "query": {
                            "type": "string",
                            "description": "Search query"
                        }
                    },
                    "required": ["query"]
                }
            }
        }
    ]
)

print(response.choices[0].message.content)

Proxy Server

# Start proxy with config
litellm --config config.yaml

# Make request
curl http://localhost:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "user", "content": "What is the weather in San Francisco?"}
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "litellm_web_search",
          "description": "Search the web",
          "parameters": {
            "type": "object",
            "properties": {
              "query": {"type": "string"}
            },
            "required": ["query"]
          }
        }
      }
    ]
  }'

How Search Tool Selection Works

1. If search_tool_name is specified → Uses that specific search tool
2. If search_tool_name is not specified → Uses first search tool in search_tools list

search_tools:
  - search_tool_name: perplexity-search  # ← This will be used if no search_tool_name specified
    litellm_params:
      search_provider: perplexity
      api_key: os.environ/PERPLEXITY_API_KEY

  - search_tool_name: tavily-search
    litellm_params:
      search_provider: tavily
      api_key: os.environ/TAVILY_API_KEY

Troubleshooting

Web Search Not Working

1. Check provider is enabled:

   enabled_providers:
     - openai  # Make sure your provider is in this list
   

2. Verify search tool is configured:

   search_tools:
     - search_tool_name: perplexity-search
       litellm_params:
         search_provider: perplexity
         api_key: os.environ/PERPLEXITY_API_KEY
   

3. Check API keys are set:

   export PERPLEXITY_API_KEY=your-key
   

4. Enable debug logging:

   litellm.set_verbose = True
   

Common Issues

Issue: Model returns tool_calls instead of final answer

• Cause: Provider not in enabled_providers list
• Solution: Add provider to enabled_providers

Issue: "No search tool configured" error

• Cause: No search tools in search_tools config
• Solution: Add at least one search tool configuration

Issue: "Invalid function arguments json string" error (MiniMax)

• Cause: Fixed in latest version - arguments weren't properly JSON serialized
• Solution: Update to latest LiteLLM version

Related Documentation

• Search Providers - Detailed search provider setup
• Claude Code WebSearch - Using with Claude Code
• Tool Calling - General tool calling documentation
• Callbacks - Custom callback documentation

Technical Details

Architecture

Web search integration is implemented as a custom callback (WebSearchInterceptionLogger) that:

1. Pre-request Hook: Converts native web search tools to LiteLLM standard format
2. Post-response Hook: Detects web search tool calls in responses
3. Agentic Loop: Executes searches and makes follow-up requests automatically

Supported APIs

• ✅ Chat Completions API (OpenAI format)
• ✅ Anthropic Messages API (Anthropic format)
• ✅ Streaming (automatically converted)
• ✅ Non-streaming

Response Format Detection

The handler automatically detects response format:

• OpenAI format: tool_calls in assistant message
• Anthropic format: tool_use blocks in content

Performance

• Latency: Adds one additional LLM call (follow-up request with search results)
• Caching: Search results can be cached (depends on search provider)
• Parallel Searches: Multiple search queries executed in parallel

Contributing

Found a bug or want to add support for a new provider? See our Contributing Guide.