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librechat web search docs
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‎docs.json

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"integrations/libraries/cline",
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"integrations/libraries/goose",
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"integrations/libraries/janhq",
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"integrations/libraries/librechat",
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{
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"group": "Librechat",
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"pages": [
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"integrations/libraries/librechat",
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"guides/use-cases/librechat-web-search"
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]
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},
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"integrations/libraries/n8n",
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"integrations/libraries/codex",
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"integrations/libraries/openwebui",
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"group": "Use Cases",
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"pages": [
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"guides/use-cases",
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"guides/use-cases/librechat-web-search",
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"guides/use-cases/run-batch-evals",
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"guides/use-cases/few-shot-prompting",
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"guides/use-cases/enforcing-json-schema-with-anyscale-and-together",

‎guides/use-cases/librechat-web-search.mdx

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---
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title: "Web Search for Any LLM in LibreChat"
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---
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> Enable real-time internet search capabilities for any LLM in LibreChat using Portkey's Exa integration
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Transform your LibreChat experience by adding web search capabilities to any LLM - whether it's GPT-4, Claude, Llama, or any of the 250+ 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.
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<Note>
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This integration builds upon the basic [LibreChat + Portkey setup](/integrations/apps/librechat). Please complete that integration first before proceeding.
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</Note>
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## What You'll Get
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By following this guide, your LibreChat installation will have:
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- ✅ **Web search for any LLM** - Not just OpenAI's browsing models
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- ✅ **Real-time information** - Access to current events, latest data, and up-to-date facts
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- ✅ **All Portkey features** - Observability, caching, fallbacks, and more
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- ✅ **Unified interface** - One LibreChat setup for all your AI needs
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- ✅ **250+ LLM support** - Use web search with any model through Portkey
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## How It Works
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<Steps>
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<Step title="User asks a question in LibreChat">
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When you send a message requiring current information
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</Step>
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<Step title="Request routes through Portkey">
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Portkey intercepts the request and triggers the Exa plugin
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</Step>
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<Step title="Exa searches the web">
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Relevant search results are fetched from across the internet
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</Step>
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<Step title="Context enhancement">
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Search results are added to your prompt as additional context
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</Step>
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<Step title="LLM responds with current information">
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Your chosen LLM now has access to real-time data to answer accurately
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</Step>
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</Steps>
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## Prerequisites
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Before starting, ensure you have:
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1. ✅ [LibreChat installed and running](https://www.librechat.ai/docs/installation)
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2. ✅ [Basic Portkey + LibreChat integration](/integrations/apps/librechat) completed
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3. ✅ [Portkey account](https://app.portkey.ai) with API key
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4. ✅ [Exa account](https://exa.ai) with API key
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## Setup Guide
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### Step 1: Enable Exa Plugin in Portkey
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First, activate the Exa plugin in your Portkey account:
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1. Log into your [Portkey dashboard](https://app.portkey.ai)
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2. Navigate to `Settings` → `Plugins` in the sidebar
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3. Find **Exa** in the list of available plugins
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4. Click **Enable** and enter your Exa API key
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5. Save your settings
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<Frame>
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<img src="/images/product/exa-plugin.png" height="40" />
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</Frame>
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### Step 2: Create an Exa Guardrail
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Next, create a guardrail that will add web search to your requests:
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1. Go to the `Guardrails` page in Portkey
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2. Click `Create New Guardrail`
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3. Search for **"Exa Online Search"** and click `Add`
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4. Configure the following parameters:
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```json
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{
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"context_prefix": "<web_search_context>",
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"context_suffix": "</web_search_context>",
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"num_results": 3,
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"timeout": 10000
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}
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```
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<Info>
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**Recommended Settings:**
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- **Number of Results**: 3-5 (balances information vs token usage)
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- **Timeout**: 10000ms (10 seconds)
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- **Include/Exclude Domains**: Leave empty for general use, or specify trusted sources
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</Info>
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5. Set the action to `passthrough` (default)
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6. Save the guardrail and copy the **Guardrail ID**
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### Step 3: Create a Config with Web Search
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Now create a Portkey config that includes your Exa guardrail:
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1. Navigate to `Configs` in the Portkey dashboard
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2. Click `Create New Config`
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3. Add your configuration:
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<CodeGroup>
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```json Using Virtual Key
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{
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"virtual_key": "YOUR_PROVIDER_VIRTUAL_KEY",
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"input_guardrails": ["your_exa_guardrail_id"],
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"override_params": {
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"model": "gpt-4o" // or any model you prefer
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}
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}
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```
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```json Using Provider API Key
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{
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"provider": "openai",
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"api_key": "YOUR_PROVIDER_API_KEY",
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"input_guardrails": ["your_exa_guardrail_id"],
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"override_params": {
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"model": "gpt-4o"
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}
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}
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```
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</CodeGroup>
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4. Save the config and note the **Config ID** (e.g., `pc-websearch-xxx`)
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### Step 4: Update Your LibreChat Configuration
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Finally, update your LibreChat setup to use the web-search enabled config:
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1. Edit your `librechat.yaml` file:
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```yaml librechat.yaml
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version: 1.1.4
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cache: true
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endpoints:
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custom:
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- name: "Portkey with Web Search"
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apiKey: "dummy"
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baseURL: ${PORTKEY_GATEWAY_URL}
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headers:
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x-portkey-api-key: "${PORTKEY_API_KEY}"
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x-portkey-config: "pc-websearch-xxx" # Your config ID from Step 3
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models:
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default: ["gpt-4o", "claude-3-sonnet", "llama-3.1-70b"]
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fetch: true
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titleConvo: true
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titleModel: "current_model"
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summarize: false
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summaryModel: "current_model"
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forcePrompt: false
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modelDisplayLabel: "Portkey:WebSearch"
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```
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2. Restart your LibreChat instance
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### Step 5: Test Your Setup
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1. Open LibreChat in your browser
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2. Select **"Portkey with Web Search"** as your endpoint
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3. Try asking questions that require current information:
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```
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"What happened in the tech industry today?"
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"What's the current price of Bitcoin?"
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"Who won the latest sports championship?"
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"What are the latest AI model releases?"
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```
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You should see responses with up-to-date information pulled from the web!
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## Advanced Configuration
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### Domain Filtering
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For specialized use cases, you can limit search results to specific domains:
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```json
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{
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"virtual_key": "YOUR_VIRTUAL_KEY",
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"input_guardrails": ["your_exa_guardrail_id"],
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"override_params": {
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"model": "gpt-4o"
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}
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}
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```
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In your Exa guardrail settings:
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- **Include Domains**: `["arxiv.org", "nature.com", "pubmed.ncbi.nlm.nih.gov"]` (for academic research)
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- **Exclude Domains**: `["reddit.com", "twitter.com"]` (to avoid social media)
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### Multiple Configurations
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Create different configs for different use cases:
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```yaml librechat.yaml
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endpoints:
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custom:
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- name: "AI Research Assistant"
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apiKey: "dummy"
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baseURL: ${PORTKEY_GATEWAY_URL}
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headers:
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x-portkey-api-key: "${PORTKEY_API_KEY}"
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x-portkey-config: "pc-research-xxx" # Config with academic domains
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models:
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default: ["gpt-4o"]
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modelDisplayLabel: "Research:WebSearch"
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- name: "News & Current Events"
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apiKey: "dummy"
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baseURL: ${PORTKEY_GATEWAY_URL}
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headers:
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x-portkey-api-key: "${PORTKEY_API_KEY}"
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x-portkey-config: "pc-news-xxx" # Config with news domains
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models:
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default: ["claude-3-sonnet"]
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modelDisplayLabel: "News:WebSearch"
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```
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### Combining with Other Portkey Features
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Enhance your web-search enabled config with additional Portkey features:
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```json
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{
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"virtual_key": "YOUR_VIRTUAL_KEY",
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"input_guardrails": ["your_exa_guardrail_id"],
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"output_guardrails": ["content_safety_guardrail_id"],
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"cache": {
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"mode": "semantic",
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"max_age": 3600
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},
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"retry": {
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"attempts": 3
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},
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"override_params": {
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"model": "gpt-4o",
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"temperature": 0.7
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}
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}
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```
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## Monitoring Web Search Usage
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Track your web-search enhanced conversations in the Portkey dashboard:
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1. Navigate to **Logs** in Portkey
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2. Filter by config ID to see web-search requests
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3. Click on individual logs to see:
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- The original user query
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- Web search results added as context
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- Token usage (including search context)
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- Response time and costs
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<Frame>
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<img src="/images/product/EXA-LOGS.png" alt="Web Search Logs" />
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</Frame>
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## Best Practices
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<CardGroup cols={2}>
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<Card title="Token Management" icon="coins">
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Monitor token usage as web search adds context. Adjust the number of search results based on your needs and budget.
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</Card>
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<Card title="Model Selection" icon="robot">
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Some models handle web context better than others. Test different models to find the best fit for your use case.
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</Card>
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<Card title="Query Optimization" icon="magnifying-glass">
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Not every query needs web search. Consider creating separate endpoints for general chat vs. current information needs.
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</Card>
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<Card title="Caching Strategy" icon="database">
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Use semantic caching for frequently asked current events questions to reduce API calls and costs.
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</Card>
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</CardGroup>
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## Next Steps
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- **Try different models** with web search to compare performance
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- **Monitor costs** using Portkey's analytics dashboard
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- **Create specialized configs** for your team's specific use cases
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- **Set up access controls** with user-specific API keys
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## Support
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Need help? Contact us:
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- Email: [email protected]
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- [Documentation](https://docs.portkey.ai)
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- [Discord Community](https://portkey.sh/discord-report)

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