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

# Getting Started with AI Gateway

> Connect to 1,600+ LLMs through Portkey's unified API with observability, reliability, and cost controls.

Portkey's AI Gateway provides a unified interface to 1,600+ LLMs with enterprise features: observability, automatic retries, fallbacks, caching, and cost controls—all through a simple API.

## Quick Start

Get started in 3 steps:

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  # 1. Install: pip install portkey-ai
  # 2. Add provider in Model Catalog (e.g., @openai-prod)
  # 3. Use it:

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  response = portkey.chat.completions.create(
      model="@openai-prod/gpt-4o",  # @provider-slug/model-name
      messages=[{"role": "user", "content": "What is a fractal?"}]
  )

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

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  // 1. Install: npm install portkey-ai
  // 2. Add provider in Model Catalog (e.g., @openai-prod)
  // 3. Use it:

  const portkey = new Portkey({
      apiKey: "PORTKEY_API_KEY"
  })

  const response = await portkey.chat.completions.create({
      model: "@openai-prod/gpt-4o",  // @provider-slug/model-name
      messages: [{ role: "user", content: "What is a fractal?" }]
  })

  console.log(response.choices[0].message.content)
  ```

  ```python OpenAI Python icon="openai" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  # Use OpenAI SDK with Portkey gateway
  client = OpenAI(
      api_key="PORTKEY_API_KEY",
      base_url=PORTKEY_GATEWAY_URL
  )

  response = client.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{"role": "user", "content": "What is a fractal?"}]
  )

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

  ```javascript OpenAI JS icon="openai" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'

  // Use OpenAI SDK with Portkey gateway
  const client = new OpenAI({
      apiKey: "PORTKEY_API_KEY",
      baseURL: PORTKEY_GATEWAY_URL
    })

  const response = await client.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{ role: "user", content: "What is a fractal?" }]
  })

  console.log(response.choices[0].message.content)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -d '{
      "model": "@openai-prod/gpt-4o",
      "messages": [{"role": "user", "content": "What is a fractal?"}]
  }'
  ```
</CodeGroup>

<Info>
  Portkey also supports Anthropic's native `/messages` endpoint. See [Using with Anthropic SDK](#using-with-anthropic-sdk) below.
</Info>

## Add Provider in Model Catalog

Before making requests, add a provider:

1. Go to [**Model Catalog → Add Provider**](https://app.portkey.ai/model-catalog/providers)
2. Select your provider (OpenAI, Anthropic, etc.)
3. Choose existing credentials or enter your API key
4. Name your provider (e.g., `openai-prod`)

Your provider slug will be **`@openai-prod`** (the name you chose with `@` prefix).

<Card title="Complete Model Catalog Guide →" href="/product/model-catalog">
  Set up budgets, rate limits, and manage credentials
</Card>

## Switch Between Providers

Change the model string to use different providers—same code, different models:

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  # OpenAI
  response = portkey.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{"role": "user", "content": "Hello!"}]
  )

  # Anthropic
  response = portkey.chat.completions.create(
      model="@anthropic-prod/claude-sonnet-4-5-20250929",
      messages=[{"role": "user", "content": "Hello!"}],
      max_tokens=250  # Required for Anthropic
  )

  # Mistral
  response = portkey.chat.completions.create(
      model="@mistral-prod/mistral-large-latest",
      messages=[{"role": "user", "content": "Hello!"}]
  )
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" })

  // OpenAI
  const openaiResponse = await portkey.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{ role: "user", content: "Hello!" }]
  })

  // Anthropic
  const anthropicResponse = await portkey.chat.completions.create({
      model: "@anthropic-prod/claude-sonnet-4-5-20250929",
      messages: [{ role: "user", content: "Hello!" }],
      max_tokens: 250  // Required for Anthropic
  })

  // Mistral
  const mistralResponse = await portkey.chat.completions.create({
      model: "@mistral-prod/mistral-large-latest",
      messages: [{ role: "user", content: "Hello!" }]
  })
  ```
</CodeGroup>

## Examples

### Vision

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  response = portkey.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{
          "role": "user",
          "content": [
              {"type": "text", "text": "What's in this image?"},
              {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/800px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"}}
          ]
      }],
      max_tokens=300
  )

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

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" })

  const response = await portkey.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{
          role: "user",
          content: [
              { type: "text", text: "What's in this image?" },
              { type: "image_url", image_url: { url: "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/800px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" } }
          ]
      }],
      max_tokens: 300
  })

  console.log(response.choices[0].message.content)
  ```

  ```python OpenAI Python icon="openai" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  client = OpenAI(api_key="PORTKEY_API_KEY", base_url=PORTKEY_GATEWAY_URL)

  response = client.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{
          "role": "user",
          "content": [
              {"type": "text", "text": "What's in this image?"},
              {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/800px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"}}
          ]
      }],
      max_tokens=300
  )

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

  ```javascript OpenAI JS icon="openai" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'

  const client = new OpenAI({ apiKey: "PORTKEY_API_KEY", baseURL: PORTKEY_GATEWAY_URL })

  const response = await client.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{
          role: "user",
          content: [
              { type: "text", text: "What's in this image?" },
              { type: "image_url", image_url: { url: "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/800px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" } }
          ]
      }],
      max_tokens: 300
  })

  console.log(response.choices[0].message.content)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "model": "@openai-prod/gpt-4o",
      "messages": [{
        "role": "user",
        "content": [
          {"type": "text", "text": "What is in this image?"},
          {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/800px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"}}
        ]
      }],
      "max_tokens": 300
    }'
  ```
</CodeGroup>

### Function Calling

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  tools = [{
          "type": "function",
          "function": {
          "name": "get_weather",
          "description": "Get current weather in a location",
            "parameters": {
              "type": "object",
              "properties": {
                  "location": {"type": "string", "description": "City and state, e.g. San Francisco, CA"}
              },
              "required": ["location"]
          }
          }
  }]

  response = portkey.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{"role": "user", "content": "What's the weather in Boston?"}],
    tools=tools,
    tool_choice="auto"
  )

  print(response.choices[0].message.tool_calls)
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" })

  const tools = [{
      type: "function",
      function: {
          name: "get_weather",
          description: "Get current weather in a location",
          parameters: {
              type: "object",
              properties: {
                  location: { type: "string", description: "City and state, e.g. San Francisco, CA" }
              },
              required: ["location"]
          }
          }
  }]

    const response = await portkey.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{ role: "user", content: "What's the weather in Boston?" }],
      tools: tools,
      tool_choice: "auto"
  })

  console.log(response.choices[0].message.tool_calls)
  ```

  ```python OpenAI Python icon="openai" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  client = OpenAI(api_key="PORTKEY_API_KEY", base_url=PORTKEY_GATEWAY_URL)

  tools = [{
      "type": "function",
      "function": {
          "name": "get_weather",
          "description": "Get current weather in a location",
        "parameters": {
          "type": "object",
          "properties": {
                  "location": {"type": "string", "description": "City and state, e.g. San Francisco, CA"}
            },
              "required": ["location"]
          }
      }
  }]

  response = client.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{"role": "user", "content": "What's the weather in Boston?"}],
    tools=tools,
    tool_choice="auto"
  )

  print(response.choices[0].message.tool_calls)
  ```

  ```javascript OpenAI JS icon="openai" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'

  const client = new OpenAI({ apiKey: "PORTKEY_API_KEY", baseURL: PORTKEY_GATEWAY_URL })

  const tools = [{
      type: "function",
      function: {
          name: "get_weather",
          description: "Get current weather in a location",
          parameters: {
              type: "object",
              properties: {
                  location: { type: "string", description: "City and state, e.g. San Francisco, CA" }
              },
              required: ["location"]
          }
      }
  }]

  const response = await client.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{ role: "user", content: "What's the weather in Boston?" }],
      tools: tools,
      tool_choice: "auto"
  })

  console.log(response.choices[0].message.tool_calls)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "model": "@openai-prod/gpt-4o",
      "messages": [{"role": "user", "content": "What is the weather in Boston?"}],
      "tools": [{
        "type": "function",
        "function": {
          "name": "get_weather",
          "description": "Get current weather in a location",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {"type": "string", "description": "City and state, e.g. San Francisco, CA"}
            },
            "required": ["location"]
          }
        }
      }],
    "tool_choice": "auto"
    }'
  ```
</CodeGroup>

### Image Generation

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  image = portkey.images.generate(
      model="@openai-prod/dall-e-3",
      prompt="A serene mountain landscape at sunset",
      size="1024x1024"
  )

  print(image.data[0].url)
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" })

  const image = await portkey.images.generate({
      model: "@openai-prod/dall-e-3",
      prompt: "A serene mountain landscape at sunset",
      size: "1024x1024"
  })

  console.log(image.data[0].url)
  ```

  ```python OpenAI Python icon="openai" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  client = OpenAI(api_key="PORTKEY_API_KEY", base_url=PORTKEY_GATEWAY_URL)

  image = client.images.generate(
      model="@openai-prod/dall-e-3",
      prompt="A serene mountain landscape at sunset",
      size="1024x1024"
  )

  print(image.data[0].url)
  ```

  ```javascript OpenAI JS icon="openai" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'

  const client = new OpenAI({ apiKey: "PORTKEY_API_KEY", baseURL: PORTKEY_GATEWAY_URL })

  const image = await client.images.generate({
      model: "@openai-prod/dall-e-3",
      prompt: "A serene mountain landscape at sunset",
      size: "1024x1024"
  })

  console.log(image.data[0].url)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/images/generations \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "model": "@openai-prod/dall-e-3",
      "prompt": "A serene mountain landscape at sunset",
      "size": "1024x1024"
    }'
  ```
</CodeGroup>

### Embeddings

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  embeddings = portkey.embeddings.create(
      model="@openai-prod/text-embedding-3-small",
      input=["Hello world", "Goodbye world"]
  )

  print(embeddings.data[0].embedding[:5])  # First 5 dimensions
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" })

  const embeddings = await portkey.embeddings.create({
      model: "@openai-prod/text-embedding-3-small",
      input: ["Hello world", "Goodbye world"]
  })

  console.log(embeddings.data[0].embedding.slice(0, 5))  // First 5 dimensions
  ```

  ```python OpenAI Python icon="openai" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  client = OpenAI(api_key="PORTKEY_API_KEY", base_url=PORTKEY_GATEWAY_URL)

  embeddings = client.embeddings.create(
      model="@openai-prod/text-embedding-3-small",
      input=["Hello world", "Goodbye world"]
  )

  print(embeddings.data[0].embedding[:5])
  ```

  ```javascript OpenAI JS icon="openai" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'

  const client = new OpenAI({ apiKey: "PORTKEY_API_KEY", baseURL: PORTKEY_GATEWAY_URL })

  const embeddings = await client.embeddings.create({
      model: "@openai-prod/text-embedding-3-small",
      input: ["Hello world", "Goodbye world"]
  })

  console.log(embeddings.data[0].embedding.slice(0, 5))
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/embeddings \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "model": "@openai-prod/text-embedding-3-small",
      "input": ["Hello world", "Goodbye world"]
    }'
  ```
</CodeGroup>

### Audio Transcription

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  transcription = portkey.audio.transcriptions.create(
      model="@openai-prod/whisper-1",
      file=open("/path/to/audio.mp3", "rb")
  )

  print(transcription.text)
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'
  import fs from 'fs'

  const portkey = new Portkey({ apiKey: "PORTKEY_API_KEY" })

  const transcription = await portkey.audio.transcriptions.create({
      model: "@openai-prod/whisper-1",
      file: fs.createReadStream("/path/to/audio.mp3")
  })

  console.log(transcription.text)
  ```

  ```python OpenAI Python icon="openai" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  client = OpenAI(api_key="PORTKEY_API_KEY", base_url=PORTKEY_GATEWAY_URL)

  transcription = client.audio.transcriptions.create(
      model="@openai-prod/whisper-1",
      file=open("/path/to/audio.mp3", "rb")
  )

  print(transcription.text)
  ```

  ```javascript OpenAI JS icon="openai" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'
  import fs from 'fs'

  const client = new OpenAI({ apiKey: "PORTKEY_API_KEY", baseURL: PORTKEY_GATEWAY_URL })

  const transcription = await client.audio.transcriptions.create({
      model: "@openai-prod/whisper-1",
      file: fs.createReadStream("/path/to/audio.mp3")
  })

  console.log(transcription.text)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/audio/transcriptions \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -F file="@/path/to/audio.mp3" \
    -F model="@openai-prod/whisper-1"
  ```
</CodeGroup>

## Using with OpenAI SDK

Use your existing OpenAI code with Portkey—just change 2 parameters:

<CodeGroup>
  ```python Python icon="python" theme={null}
  from openai import OpenAI
  from portkey_ai import PORTKEY_GATEWAY_URL

  # Change base_url and api_key
  client = OpenAI(
      api_key="PORTKEY_API_KEY",
      base_url=PORTKEY_GATEWAY_URL
  )

  # Use model with @provider-slug prefix
  response = client.chat.completions.create(
      model="@openai-prod/gpt-4o",
      messages=[{"role": "user", "content": "Hello!"}]
  )
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import OpenAI from 'openai'
  import { PORTKEY_GATEWAY_URL } from 'portkey-ai'

  // Change baseURL and apiKey
  const client = new OpenAI({
      apiKey: "PORTKEY_API_KEY",
      baseURL: PORTKEY_GATEWAY_URL
  })

  // Use model with @provider-slug prefix
  const response = await client.chat.completions.create({
      model: "@openai-prod/gpt-4o",
      messages: [{ role: "user", content: "Hello!" }]
  })
  ```
</CodeGroup>

## Using with Anthropic SDK

Portkey fully supports Anthropic's native `/messages` endpoint. Use the Anthropic SDK directly with Portkey:

<CodeGroup>
  ```python Python icon="python" theme={null}
  import anthropic

  client = anthropic.Anthropic(
          api_key="PORTKEY_API_KEY",
      base_url="https://api.portkey.ai"
      )

  message = client.messages.create(
      model="@anthropic-prod/claude-sonnet-4-5-20250929",
      max_tokens=1024,
      messages=[{"role": "user", "content": "Hello, Claude!"}]
  )

  print(message.content[0].text)
  ```

  ```javascript JavaScript icon="square-js" theme={null}
  import Anthropic from '@anthropic-ai/sdk'

  const client = new Anthropic({
      apiKey: "PORTKEY_API_KEY",
      baseURL: "https://api.portkey.ai"
  })

  const message = await client.messages.create({
      model: "@anthropic-prod/claude-sonnet-4-5-20250929",
      max_tokens: 1024,
      messages: [{ role: "user", content: "Hello, Claude!" }]
  })

  console.log(message.content[0].text)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/messages \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "model": "@anthropic-prod/claude-sonnet-4-5-20250929",
      "max_tokens": 1024,
      "messages": [{"role": "user", "content": "Hello, Claude!"}]
    }'
  ```
</CodeGroup>

All Portkey features (caching, observability, configs) work with the Anthropic SDK—just add the `x-portkey-*` headers.

<Card title="Anthropic Integration Guide →" href="/integrations/llms/anthropic">
  Learn about prompt caching, extended thinking, and more Anthropic features
</Card>

## Gateway Features

Add production features through configs:

```python theme={null}
from portkey_ai import Portkey

# Attach a config for retries, caching, fallbacks
portkey = Portkey(
        api_key="PORTKEY_API_KEY",
    config="pc-your-config-id"  # Created in Portkey dashboard
)
```

<CardGroup cols={2}>
  <Card title="Automatic Retries" icon="rotate" href="/product/ai-gateway/automatic-retries">
    Retry failed requests with exponential backoff
  </Card>

  <Card title="Fallbacks" icon="arrow-rotate-left" href="/product/ai-gateway/fallbacks">
    Automatically switch to backup providers
  </Card>

  <Card title="Caching" icon="database" href="/product/ai-gateway/cache-simple-and-semantic">
    Cache responses to reduce costs and latency
  </Card>

  <Card title="Load Balancing" icon="scale-balanced" href="/product/ai-gateway/load-balancing">
    Distribute requests across multiple providers
  </Card>
</CardGroup>

<Card title="Gateway Configs Guide →" href="/product/ai-gateway/configs">
  Learn how to create and use configs
</Card>

## Supported Integrations

Portkey integrates with the entire AI ecosystem:

<CardGroup cols={2}>
  <Card title="LLM Providers" icon="microchip" href="/integrations/llms">
    **1,600+ models** from OpenAI, Anthropic, Google, Mistral, Cohere, and 30+ providers
  </Card>

  <Card title="Agent Frameworks" icon="robot" href="/integrations/agents">
    LangChain, CrewAI, AutoGen, OpenAI Agents, Strands, and more
  </Card>

  <Card title="Libraries" icon="book" href="/integrations/libraries">
    LangChain, LlamaIndex, Vercel AI SDK, and popular frameworks
  </Card>

  <Card title="Guardrails" icon="shield" href="/integrations/guardrails">
    Aporia, Pillar, Patronus, and content safety providers
  </Card>

  <Card title="Vector Databases" icon="database" href="/integrations/vector-databases">
    Pinecone, Weaviate, and vector store integrations
  </Card>

  <Card title="MCP Servers" icon="server" href="/integrations/mcp-servers">
    Model Context Protocol servers and tools
  </Card>
</CardGroup>

## Next Steps

<CardGroup cols={2}>
  <Card title="Observability" icon="chart-line" href="/product/observability">
    Track costs, latency, and usage
  </Card>

  <Card title="Prompt Library" icon="book" href="/product/prompt-library">
    Manage and version prompts
  </Card>

  <Card title="Guardrails" icon="shield" href="/product/guardrails">
    Add PII detection and content filtering
  </Card>

  <Card title="Model Catalog" icon="list" href="/product/model-catalog">
    Manage providers, budgets, and access
  </Card>
</CardGroup>