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

# Lambda Labs

> Use Lambda's GPU-powered inference for Llama and open-source models through Portkey.

## Quick Start

Get started with Lambda Labs in under 2 minutes:

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

  # 1. Install: pip install portkey-ai
  # 2. Add @lambda provider in model catalog
  # 3. Use it:

  portkey = Portkey(api_key="PORTKEY_API_KEY")

  response = portkey.chat.completions.create(
      model="@lambda/llama3.1-8b-instruct",
      messages=[{"role": "user", "content": "Hello!"}]
  )

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

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

  // 1. Install: npm install portkey-ai
  // 2. Add @lambda provider in model catalog
  // 3. Use it:

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

  const response = await portkey.chat.completions.create({
      model: "@lambda/llama3.1-8b-instruct",
      messages: [{ role: "user", content: "Hello!" }]
  })

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

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

  # 1. Install: pip install openai portkey-ai
  # 2. Add @lambda provider in model catalog
  # 3. Use it:

  client = OpenAI(
      api_key="PORTKEY_API_KEY",  # Portkey API key
      base_url=PORTKEY_GATEWAY_URL
  )

  response = client.chat.completions.create(
      model="@lambda/llama3.1-8b-instruct",
      messages=[{"role": "user", "content": "Hello!"}]
  )

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

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

  // 1. Install: npm install openai portkey-ai
  // 2. Add @lambda provider in model catalog
  // 3. Use it:

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

  const response = await client.chat.completions.create({
      model: "@lambda/llama3.1-8b-instruct",
      messages: [{ role: "user", content: "Hello!" }]
  })

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

  ```sh cURL icon="square-terminal" theme={null}
  # 1. Add @lambda provider in model catalog
  # 2. Use it:

  curl https://api.portkey.ai/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "model": "@lambda/llama3.1-8b-instruct",
      "messages": [{"role": "user", "content": "Hello!"}]
    }'
  ```
</CodeGroup>

## Add Provider in Model Catalog

Before making requests, add Lambda Labs to your Model Catalog:

1. Go to [**Model Catalog → Add Provider**](https://app.portkey.ai/model-catalog/providers)
2. Select **Lambda Labs**
3. Enter your [Lambda API key](https://cloud.lambdalabs.com/api-keys)
4. Name your provider (e.g., `lambda`)

<Card title="Complete Setup Guide" icon="book" href="/product/model-catalog">
  See all setup options and detailed configuration instructions
</Card>

***

## Lambda Capabilities

### Streaming

Stream responses for real-time output:

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

  portkey = Portkey(api_key="PORTKEY_API_KEY", provider="@lambda")

  stream = portkey.chat.completions.create(
      model="llama3.1-8b-instruct",
      messages=[{"role": "user", "content": "Tell me a story"}],
      stream=True
  )

  for chunk in stream:
      print(chunk.choices[0].delta.content or "", end="", flush=True)
  ```

  ```javascript Node.js theme={null}
  import Portkey from 'portkey-ai';

  const portkey = new Portkey({
      apiKey: 'PORTKEY_API_KEY',
      provider: '@lambda'
  });

  const stream = await portkey.chat.completions.create({
      model: 'llama3.1-8b-instruct',
      messages: [{ role: 'user', content: 'Tell me a story' }],
      stream: true
  });

  for await (const chunk of stream) {
      process.stdout.write(chunk.choices[0]?.delta?.content || '');
  }
  ```
</CodeGroup>

### Function Calling

Use Lambda's function calling capabilities:

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

  portkey = Portkey(api_key="PORTKEY_API_KEY", provider="@lambda")

  tools = [{
      "type": "function",
      "function": {
          "name": "getWeather",
          "description": "Get the current weather",
          "parameters": {
              "type": "object",
              "properties": {
                  "location": {"type": "string", "description": "City and state"},
                  "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
              },
              "required": ["location"]
          }
      }
  }]

  response = portkey.chat.completions.create(
      model="llama3.1-8b-instruct",
      messages=[
          {"role": "system", "content": "You are a helpful assistant."},
          {"role": "user", "content": "What's the weather in Delhi?"}
      ],
      tools=tools,
      tool_choice="auto"
  )

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

  ```javascript Node.js theme={null}
  import Portkey from 'portkey-ai';

  const portkey = new Portkey({
      apiKey: 'PORTKEY_API_KEY',
      provider: '@lambda'
  });

  const tools = [{
      type: "function",
      function: {
          name: "getWeather",
          description: "Get the current weather",
          parameters: {
              type: "object",
              properties: {
                  location: { type: "string", description: "City and state" },
                  unit: { type: "string", enum: ["celsius", "fahrenheit"] }
              },
              required: ["location"]
          }
      }
  }];

  const response = await portkey.chat.completions.create({
      model: "llama3.1-8b-instruct",
      messages: [
          { role: "system", content: "You are a helpful assistant." },
          { role: "user", content: "What's the weather in Delhi?" }
      ],
      tools,
      tool_choice: "auto"
  });

  console.log(response.choices[0].message);
  ```
</CodeGroup>

***

## Supported Endpoints and Parameters

| Endpoint            | Supported Parameters                                                                                                                                               |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `/chat/completions` | messages, max\_tokens, temperature, top\_p, stream, presence\_penalty, frequency\_penalty, tools, tool\_choice                                                     |
| `/completions`      | model, prompt, max\_tokens, temperature, top\_p, n, stream, logprobs, echo, stop, presence\_penalty, frequency\_penalty, best\_of, logit\_bias, user, seed, suffix |

Check [Lambda's documentation](https://docs.lambdalabs.com/) for more details.

***

## Next Steps

<CardGroup cols={2}>
  <Card title="Gateway Configs" icon="sliders" href="/product/ai-gateway">
    Add fallbacks, load balancing, and more
  </Card>

  <Card title="Observability" icon="chart-line" href="/product/observability">
    Monitor and trace your Lambda requests
  </Card>

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

  <Card title="Metadata" icon="tag" href="/product/observability/metadata">
    Add custom metadata to requests
  </Card>
</CardGroup>

For complete SDK documentation:

<Card title="SDK Reference" icon="code" href="/api-reference/sdk/list">
  Complete Portkey SDK documentation
</Card>