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.

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.

Provider Slug. ovhcloud

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.

NodeJS

npm install --save portkey-ai

Python

pip install portkey-ai

2. Initialize Portkey with Your AI Provider

Navigate to the OVHcloud control panel, in Public Cloud > AI & Machine Learning > AI Endpoints > API key. Add it to Model Catalog to get your AI Provider slug.

NodeJS SDK

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
})

Python SDK

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
)

3. Invoke Chat Completions with AI Endpoints

Use the Portkey instance to send requests to AI Endpoints.

NodeJS SDK

const chatCompletion = await portkey.chat.completions.create({
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'mixtral-8x7b-32768',
});

console.log(chatCompletion.choices);

Python SDK

completion = portkey.chat.completions.create(
    messages= [{ "role": 'user', "content": 'Say this is a test' }],
    model= 'mistral-medium'
)

print(completion)

Managing OVHcloud AI Endpoints Prompts

You can manage all prompts to AI Endpoints in the 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.

Supported OVHcloud AI Endpoints Models with Tool Calling

Node.js

Get Weather Tool

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);

Python

Get Weather Tool

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)

cURL

Get Weather Tool

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"
     }'

Portkey Prompts

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.

Python

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)

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