> ## Documentation Index
> Fetch the complete documentation index at: https://portkey-docs-feat-rerank-documentation.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Web Search for Any LLM in LibreChat

> Enable real-time internet search capabilities for any LLM in LibreChat using Portkey's Exa integration

Transform your LibreChat experience by adding web search capabilities to any LLM - whether it's GPT-5, Claude, Llama, or any of the 1,600+ models supported by Portkey. This guide shows you how to combine LibreChat, Portkey, and Exa to create a powerful AI chat interface with real-time internet access.

<Note>
  This integration builds upon the basic [LibreChat + Portkey setup](/integrations/libraries/librechat). Please complete that integration first before proceeding.
</Note>

## What You'll Get

By following this guide, your LibreChat installation will have:

* ✅ **Web search for any LLM** - Not just OpenAI's browsing models
* ✅ **Real-time information** - Access to current events, latest data, and up-to-date facts
* ✅ **All Portkey features** - Observability, caching, fallbacks, and more
* ✅ **Unified interface** - One LibreChat setup for all your AI needs
* ✅ **1,600+ LLM support** - Use web search with any model through Portkey

## How It Works

<Steps>
  <Step title="User asks a question in LibreChat">
    When you send a message requiring current information
  </Step>

  <Step title="Request routes through Portkey">
    Portkey intercepts the request and triggers the Exa plugin
  </Step>

  <Step title="Exa searches the web">
    Relevant search results are fetched from across the internet
  </Step>

  <Step title="Context enhancement">
    Search results are added to your prompt as additional context
  </Step>

  <Step title="LLM responds with current information">
    Your chosen LLM now has access to real-time data to answer accurately
  </Step>
</Steps>

## Prerequisites

Before starting, ensure you have:

1. ✅ [LibreChat installed and running](https://www.librechat.ai/docs/quick_start/local_setup)
2. ✅ [Basic Portkey + LibreChat integration](/integrations/libraries/librechat) completed
3. ✅ [Portkey account](https://app.portkey.ai) with API key
4. ✅ [Exa account](https://exa.ai) with API key

## Setup Guide

### Step 1: Enable Exa Plugin in Portkey

First, activate the Exa plugin in your Portkey account:

1. Log into your [Portkey dashboard](https://app.portkey.ai)
2. Navigate to `Settings` → `Plugins` in the sidebar
3. Find **Exa** in the list of available plugins
4. Click **Enable** and enter your Exa API key
5. Save your settings

<Frame>
  <img src="https://mintcdn.com/portkey-docs-feat-rerank-documentation/Cg9s-posKHJ6UAN_/images/product/exa-plugin.png?fit=max&auto=format&n=Cg9s-posKHJ6UAN_&q=85&s=562b1af029c9655fa5d9b25a53669b06" height="40" data-path="images/product/exa-plugin.png" />
</Frame>

### Step 2: Create an Exa Guardrail

Next, create a guardrail that will add web search to your requests:

1. Go to the `Guardrails` page in Portkey
2. Click `Create New Guardrail`
3. Search for **"Exa Online Search"** and click `Add`
4. Configure the following parameters:

```json theme={"system"}
{
  "context_prefix": "<web_search_context>",
  "context_suffix": "</web_search_context>",
  "num_results": 3,
  "timeout": 10000
}
```

<Info>
  **Recommended Settings:**

  * **Number of Results**: 3-5 (balances information vs token usage)
  * **Timeout**: 10000ms (10 seconds)
  * **Include/Exclude Domains**: Leave empty for general use, or specify trusted sources
</Info>

5. Set the action to `passthrough` (default)
6. Save the guardrail and copy the **Guardrail ID**

### Step 3: Create a Config with Web Search

Now create a Portkey config that includes your Exa guardrail:

1. Navigate to `Configs` in the Portkey dashboard
2. Click `Create New Config`
3. Add your configuration:

```json Config theme={"system"}
{
    "input_guardrails": ["your_exa_guardrail_id"]
}
```

4. Save the config and note the **Config ID** (e.g., `pc-websearch-xxx`)

### Step 4: Update Your LibreChat Configuration

Finally, update your LibreChat setup to use the web-search enabled config:

1. Edit your `librechat.yaml` file:

```yaml librechat.yaml theme={"system"}
version: 1.1.4
cache: true
endpoints:
  custom:
    - name: "Portkey with Web Search"
      apiKey: "dummy"
      baseURL: ${PORTKEY_GATEWAY_URL}
      headers:
        x-portkey-api-key: "${PORTKEY_API_KEY}"
        x-portkey-config: "pc-websearch-xxx"  # Your config ID from Step 3
      models:
        default: ["@openai-prod/gpt-5", "@anthropic-prod/claude-4.5-sonnet", "@together-ai-prod/llama-4-70b"]
        fetch: true
      titleConvo: true
      titleModel: "current_model"
      summarize: false
      summaryModel: "current_model"
      forcePrompt: false
      modelDisplayLabel: "Portkey:WebSearch"
```

2. Restart your LibreChat instance

### Step 5: Test Your Setup

1. Open LibreChat in your browser
2. Select **"Portkey with Web Search"** as your endpoint
3. Try asking questions that require current information:

```
"What happened in the tech industry today?"
"What's the current price of Bitcoin?"
"Who won the latest sports championship?"
"What are the latest AI model releases?"
```

You should see responses with up-to-date information pulled from the web!

## Advanced Configuration

### Domain Filtering

For specialized use cases, you can limit search results to specific domains:

```json Config theme={"system"}
{
    "input_guardrails": ["your_exa_guardrail_id"]
}
```

In your Exa guardrail settings:

* **Include Domains**: `["arxiv.org", "nature.com", "pubmed.ncbi.nlm.nih.gov"]` (for academic research)
* **Exclude Domains**: `["reddit.com", "twitter.com"]` (to avoid social media)

### Multiple Configurations

Create different configs for different use cases:

```yaml librechat.yaml theme={"system"}
endpoints:
  custom:
    - name: "AI Research Assistant"
      apiKey: "dummy"
      baseURL: ${PORTKEY_GATEWAY_URL}
      headers:
        x-portkey-api-key: "${PORTKEY_API_KEY}"
        x-portkey-config: "pc-research-xxx"  # Config with academic domains
      models:
        default: ["@openai-prod/gpt-5"]
      modelDisplayLabel: "Research:WebSearch"

    - name: "News & Current Events"
      apiKey: "dummy"
      baseURL: ${PORTKEY_GATEWAY_URL}
      headers:
        x-portkey-api-key: "${PORTKEY_API_KEY}"
        x-portkey-config: "pc-news-xxx"  # Config with news domains
      models:
        default: ["@anthropic-prod/claude-4.5-sonnet"]
      modelDisplayLabel: "News:WebSearch"
```

### Combining with Other Portkey Features

Enhance your web-search enabled config with additional Portkey features:

```json Config theme={"system"}
{
    "input_guardrails": ["your_exa_guardrail_id"],
    "output_guardrails": ["content_safety_guardrail_id"],
    "cache": {"mode": "semantic", "max_age": 3600},
    "retry": {"attempts": 3},
    "override_params": {"temperature": 0.7}
}
```

## Monitoring Web Search Usage

Track your web-search enhanced conversations in the Portkey dashboard:

1. Navigate to **Logs** in Portkey
2. Filter by config ID to see web-search requests
3. Click on individual logs to see:
   * The original user query
   * Web search results added as context
   * Token usage (including search context)
   * Response time and costs

<Frame>
  <img src="https://mintcdn.com/portkey-docs-feat-rerank-documentation/igF6AIVPgbUAWApF/images/product/EXA-LOGS.png?fit=max&auto=format&n=igF6AIVPgbUAWApF&q=85&s=1004e3a5119279f442d4e316c75a10eb" alt="Web Search Logs" width="2569" height="1770" data-path="images/product/EXA-LOGS.png" />
</Frame>

## Best Practices

<CardGroup cols={2}>
  <Card title="Token Management" icon="coins">
    Monitor token usage as web search adds context. Adjust the number of search results based on your needs and budget.
  </Card>

  <Card title="Model Selection" icon="robot">
    Some models handle web context better than others. Test different models to find the best fit for your use case.
  </Card>

  <Card title="Query Optimization" icon="magnifying-glass">
    Not every query needs web search. Consider creating separate endpoints for general chat vs. current information needs.
  </Card>

  <Card title="Caching Strategy" icon="database">
    Use semantic caching for frequently asked current events questions to reduce API calls and costs.
  </Card>
</CardGroup>

## Next Steps

* **Try different models** with web search to compare performance
* **Monitor costs** using Portkey's analytics dashboard
* **Create specialized configs** for your team's specific use cases
* **Set up access controls** with user-specific API keys

## Support

Need help? Contact us:

* Email: [support@portkey.ai](mailto:support@portkey.ai)
* [Documentation](https://docs.portkey.ai)
* [Discord Community](https://portkey.sh/discord-report)