> ## 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.

# OVHcloud AI Endpoints

Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including [OVHcloud AI Endpoints](https://www.ovhcloud.com/en/public-cloud/ai-endpoints/).

With Portkey, you can take advantage of features like fast AI gateway access, observability, prompt management, and more, all while ensuring the secure management of your LLM API keys through [Model Catalog](/product/model-catalog).

<Note>
  Provider Slug. `ovhcloud`
</Note>

## Portkey SDK Integration with OVHcloud AI Endpoints Models

Portkey provides a consistent API to interact with models from various providers. To integrate AI Endpoints with Portkey:

### 1. Install the Portkey SDK

Add the Portkey SDK to your application to interact with AI Endpoints's API through Portkey's gateway.

<Tabs>
  <Tab title="NodeJS">
    ```sh theme={null}
    npm install --save portkey-ai
    ```
  </Tab>

  <Tab title="Python">
    ```sh theme={null}
    pip install portkey-ai
    ```
  </Tab>
</Tabs>

### 2. Initialize Portkey with Your AI Provider

Navigate to the [OVHcloud control panel](https://ovh.com/manager), in `Public Cloud` > `AI & Machine Learning` > AI Endpoints > API key. Add it to [Model Catalog](https://app.portkey.ai/model-catalog) to get your AI Provider slug.

<Tabs>
  <Tab title="NodeJS SDK">
    ```js theme={null}
    import Portkey from 'portkey-ai'

    const portkey = new Portkey({
        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
        provider:"@ovhcloud-prod" // Your AI Provider slug from Model Catalog
    })
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={null}
    from portkey_ai import Portkey

    portkey = Portkey(
        api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
        provider="@ovhcloud-prod"  # Your AI Provider slug from Model Catalog
    )
    ```
  </Tab>
</Tabs>

### **3. Invoke Chat Completions with** AI Endpoints

Use the Portkey instance to send requests to AI Endpoints.

<Tabs>
  <Tab title="NodeJS SDK">
    ```js theme={null}
    const chatCompletion = await portkey.chat.completions.create({
        messages: [{ role: 'user', content: 'Say this is a test' }],
        model: 'mixtral-8x7b-32768',
    });

    console.log(chatCompletion.choices);
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={null}
    completion = portkey.chat.completions.create(
        messages= [{ "role": 'user', "content": 'Say this is a test' }],
        model= 'mistral-medium'
    )

    print(completion)
    ```
  </Tab>
</Tabs>

## Managing OVHcloud AI Endpoints Prompts

You can manage all prompts to AI Endpoints in the [Prompt Library](/product/prompt-library). All the current models of AI Endpoints are supported and you can easily start testing different prompts.

Once you're ready with your prompt, you can use the `portkey.prompts.completions.create` interface to use the prompt in your application.

### AI Endpoints Tool Calling

Tool calling feature lets models trigger external tools based on conversation context. You define available functions, the model chooses when to use them, and your application executes them and returns results.

Portkey supports AI Endpoints Tool Calling and makes it interoperable across multiple providers. With Portkey Prompts, you can templatize various your prompts & tool schemas as well.

<Card title="Supported OVHcloud AI Endpoints Models with Tool Calling" href="https://www.ovhcloud.com/en/public-cloud/ai-endpoints/catalog/" />

<Tabs>
  <Tab title="Node.js">
    ```javascript Get Weather Tool theme={null}
    let 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"]
            }
        }
    }];

    let response = await portkey.chat.completions.create({
        model: "gpt-oss-120b",
        messages: [
            { role: "system", content: "You are a helpful assistant." },
            { role: "user", content: "What's the weather like in Delhi - respond in JSON" }
        ],
        tools,
        tool_choice: "auto",
    });

    console.log(response.choices[0].finish_reason);
    ```
  </Tab>

  <Tab title="Python">
    ```python Get Weather Tool theme={null}
    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="gpt-oss-120b",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "What's the weather like in Delhi - respond in JSON"}
        ],
        tools=tools,
        tool_choice="auto"
    )

    print(response.choices[0].finish_reason)
    ```
  </Tab>

  <Tab title="cURL">
    ```curl Get Weather Tool theme={null}
    curl -X POST "https://api.portkey.ai/v1/chat/completions" \
         -H "Content-Type: application/json" \
         -H "Authorization: Bearer YOUR_PORTKEY_API_KEY" \
         -d '{
           "model": "gpt-oss-120b",
           "messages": [
             {"role": "system", "content": "You are a helpful assistant."},
             {"role": "user", "content": "What'\''s the weather like in Delhi - respond in JSON"}
           ],
           "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"]
               }
             }
           }],
           "tool_choice": "auto"
         }'
    ```
  </Tab>

  <Tab title="Portkey Prompts" />
</Tabs>

### AI Endpoints Speech to Text (Whisper)

OpenAI's Audio API converts speech to text using the Whisper model. It offers transcription in the original language and translation to English, supporting multiple file formats and languages with high accuracy.

<CodeGroup>
  ```python Python theme={null}
  audio_file= open("/path/to/file.mp3", "rb")

  # Transcription
  transcription = portkey.audio.transcriptions.create(
    model="whisper-large-v3",
    file=audio_file
  )
  print(transcription.text)

  # Translation
  translation = portkey.audio.translations.create(
    model="whisper-large-v3",
    file=audio_file
  )
  print(translation.text)
  ```

  ```javascript Node.js theme={null}
  import fs from "fs";

  // Transcription
  async function transcribe() {
    const transcription = await portkey.audio.transcriptions.create({
      file: fs.createReadStream("/path/to/file.mp3"),
      model: "whisper-large-v3",
    });
    console.log(transcription.text);
  }
  transcribe();

  // Translation
  async function translate() {
      const translation = await portkey.audio.translations.create({
          file: fs.createReadStream("/path/to/file.mp3"),
          model: "whisper-large-v3",
      });
      console.log(translation.text);
  }
  translate();
  ```

  ```curl REST theme={null}
  # Transcription
  curl -X POST "https://api.portkey.ai/v1/audio/transcriptions" \
       -H "Authorization: Bearer YOUR_PORTKEY_API_KEY" \
       -H "Content-Type: multipart/form-data" \
       -F "file=@/path/to/file.mp3" \
       -F "model=whisper-large-v3"

  # Translation
  curl -X POST "https://api.portkey.ai/v1/audio/translations" \
       -H "Authorization: Bearer YOUR_PORTKEY_API_KEY" \
       -H "Content-Type: multipart/form-data" \
       -F "file=@/path/to/file.mp3" \
       -F "model=whisper-large-v3"
  ```
</CodeGroup>

***