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  1. Guides
  2. Getting Started

Getting started with AI Gateway

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Last updated 10 months ago

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is the Control Panel for AI apps. With it's popular AI Gateway and Observability Suite, hundreds of teams ship reliable, cost-efficient, and fast apps.

Quickstart

Since Portkey is fully compatible with the OpenAI signature, you can connect to the Portkey AI Gateway through OpenAI Client.

  • Set the base_url as PORTKEY_GATEWAY_URL

  • Add default_headers to consume the headers needed by Portkey using the createHeaders helper method.

Install the OpenAI and Portkey SDK

pip install -qU portkey-ai openai

Create the client

import os
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
  api_key=os.environ.get("OPENAI_API_KEY"),
  base_url=PORTKEY_GATEWAY_URL, # 👈 or 'http://localhost:8787/v1'
  default_headers=createHeaders(
    provider="openai", # 👈 or 'anthropic', 'together-ai', 'stability-ai', etc
    api_key=os.environ.get("PORTKEY_API_KEY") # 👈 skip when self-hosting
  )
)

Install the OpenAI and Portkey SDK

npm install --save openai portkey-ai

Create the client

import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL, // 👈 or 'http://localhost:8787/v1'
  defaultHeaders: createHeaders({
    provider: "openai", // 👈 or 'anthropic', 'together-ai', 'stability-ai', etc
    apiKey: "PORTKEY_API_KEY" // 👈 skip when self-hosting
  })
});
  • Replace the base URL to reflect the AI Gateway (http://localhost:8787/v1 when running locally or https://api.portkey.ai/v1 when using the hosted version)

  1. Replace the base URL to reflect the AI Gateway (http://localhost:8787/v1 when running locally or https://api.portkey.ai/v1 when using the hosted version)

Examples

Provider: openai

Model being tested here: gpt-4o-mini

import os
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
  api_key=os.environ.get("OPENAI_API_KEY"),
  base_url=PORTKEY_GATEWAY_URL, # 👈 or 'http://localhost:8787/v1'
  default_headers=createHeaders(
    provider="openai",
    api_key=os.environ.get("PORTKEY_API_KEY") # 👈 skip when self-hosting
  )
)

client.chat.completions.create(
  model="gpt-4o-mini",
  messages=[{"role": "user", "content": "What's a fractal?"}],
)
import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL, // 👈 or 'http://localhost:8787/v1'
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // 👈 skip when self-hosting
  })
});

const chatCompletion = await openai.chat.completions.create({
  messages: [{ role: 'user', content: 'Say this is a test' }],
  model: 'gpt-4o-mini',
});
curl https://api.portkey.ai/v1/chat/completions # 👈 or 'http://localhost:8787/v1'
-H "Content-Type: application/json"   
-H "Authorization: Bearer $OPENAI_API_KEY"
-H "x-portkey-provider: openai"
-H "x-portkey-api-key: $PORTKEY_API_KEY" # 👈 skip when self-hosting
-d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user","content": "What's a fractal"}]
}'
A fractal is a complex geometric shape that can be split into parts, each of which is a reduced-scale copy of the whole. Fractals are typically self-similar and independent of scale, meaning they look similar at any zoom level. They often appear in nature, in things like snowflakes, coastlines, and fern leaves. The term "fractal" was coined by mathematician Benoit Mandelbrot in 1975.

Anthropic

Provider: anthropic

Model being tested here: claude-3-5-sonnet-20240620

import os
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
  api_key=os.environ.get("OPENAI_API_KEY"),
  base_url=PORTKEY_GATEWAY_URL, # 👈 or 'http://localhost:8787/v1'
  default_headers=createHeaders(
    provider="anthropic",
    api_key=os.environ.get("PORTKEY_API_KEY") # 👈 skip when self-hosting
  )
)

client.chat.completions.create(
  model="claude-3-5-sonnet-20240620",
  messages=[{"role": "user", "content": "What's a fractal?"}],
  max_tokens=250
)
import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL, // 👈 or 'http://localhost:8787/v1'
  defaultHeaders: createHeaders({
    provider: "anthropic",
    apiKey: "PORTKEY_API_KEY" // 👈 skip when self-hosting
  })
});

const chatCompletion = await openai.chat.completions.create({
  messages: [{ role: 'user', content: 'Say this is a test' }],
  model: 'claude-3-5-sonnet-20240620',
  max_tokens: 250
});
curl https://api.portkey.ai/v1/chat/completions # 👈 or 'http://localhost:8787/v1'
-H "Content-Type: application/json"   
-H "Authorization: Bearer $OPENAI_API_KEY"
-H "x-portkey-provider: anthropic"
-H "x-portkey-api-key: $PORTKEY_API_KEY" # 👈 skip when self-hosting
-d '{
    "model": "claude-3-5-sonnet-20240620",
    "messages": [{"role": "user","content": "What's a fractal"}],
    "max_tokens": 250
}'
A fractal is a complex geometric shape that can be split into parts, each of which is a reduced-scale copy of the whole. Fractals are typically self-similar and independent of scale, meaning they look similar at any zoom level. They often appear in nature, in things like snowflakes, coastlines, and fern leaves. The term "fractal" was coined by mathematician Benoit Mandelbrot in 1975.

Mistral AI

Provider: mistral-ai

Model being tested here: mistral-medium

import os
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
  api_key=os.environ.get("OPENAI_API_KEY"),
  base_url=PORTKEY_GATEWAY_URL, # 👈 or 'http://localhost:8787/v1'
  default_headers=createHeaders(
    provider="mistral-ai",
    api_key=os.environ.get("PORTKEY_API_KEY") # 👈 skip when self-hosting
  )
)

client.chat.completions.create(
  model="mistral-medium",
  messages=[{"role": "user", "content": "What's a fractal?"}],
)
import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL, // 👈 or 'http://localhost:8787/v1'
  defaultHeaders: createHeaders({
    provider: "mistral-ai",
    apiKey: "PORTKEY_API_KEY" // 👈 skip when self-hosting
  })
});

const chatCompletion = await openai.chat.completions.create({
  messages: [{ role: 'user', content: 'Say this is a test' }],
  model: 'mistral-medium',
});
curl https://api.portkey.ai/v1/chat/completions # 👈 or 'http://localhost:8787/v1'
-H "Content-Type: application/json"   
-H "Authorization: Bearer $OPENAI_API_KEY"
-H "x-portkey-provider: mistral-ai"
-H "x-portkey-api-key: $PORTKEY_API_KEY" # 👈 skip when self-hosting
-d '{
    "model": "mistral-medium",
    "messages": [{"role": "user","content": "What's a fractal"}]
}'
A fractal is a complex geometric shape that can be spl

Together AI

Provider: together-ai

Model being tested here: togethercomputer/llama-2-70b-chat

import os
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
  api_key=os.environ.get("OPENAI_API_KEY"),
  base_url=PORTKEY_GATEWAY_URL, # 👈 or 'http://localhost:8787/v1'
  default_headers=createHeaders(
    provider="together-ai",
    api_key=os.environ.get("PORTKEY_API_KEY") # 👈 skip when self-hosting
  )
)

client.chat.completions.create(
  model="togethercomputer/llama-2-70b-chat",
  messages=[{"role": "user", "content": "What's a fractal?"}],
)
import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL, // 👈 or 'http://localhost:8787/v1'
  defaultHeaders: createHeaders({
    provider: "together-ai",
    apiKey: "PORTKEY_API_KEY" // 👈 skip when self-hosting
  })
});

const chatCompletion = await openai.chat.completions.create({
  messages: [{ role: 'user', content: 'Say this is a test' }],
  model: 'togethercomputer/llama-2-70b-chat',
});
curl https://api.portkey.ai/v1/chat/completions # 👈 or 'http://localhost:8787/v1'
-H "Content-Type: application/json"   
-H "Authorization: Bearer $OPENAI_API_KEY"
-H "x-portkey-provider: together-ai"
-H "x-portkey-api-key: $PORTKEY_API_KEY" # 👈 skip when self-hosting
-d '{
    "model": "togethercomputer/llama-2-70b-chat",
    "messages": [{"role": "user","content": "What's a fractal"}]
}'
A fractal is a complex geometric shape that can be spl

Portkey Supports other Providers

Portkey supports 30+ providers and all the models within those providers. To use these different providers and models with OpenAI's SDK, you just need to change the provider and model names in your code with their respective auth keys. It's that easy!

import os
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
  api_key=os.environ.get("OPENAI_API_KEY"),
  base_url=PORTKEY_GATEWAY_URL, # 👈 or 'http://localhost:8787/v1'
  default_headers=createHeaders(
    provider="openai",
    api_key=os.environ.get("PORTKEY_API_KEY") # 👈 skip when self-hosting
  )
)

def get_embedding(text, model="text-embedding-3-small"):
   text = text.replace("\n", " ")
   return client.embeddings.create(input = [text], model=model).data[0].embedding

df['ada_embedding'] = df.combined.apply(lambda x: get_embedding(x, model='text-embedding-3-small'))
df.to_csv('output/embedded_1k_reviews.csv', index=False)




import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

// Generate a chat completion with streaming
async function getChatCompletionFunctions(){
  const messages = [{"role": "user", "content": "What's the weather like in Boston today?"}];
  const tools = [
      {
        "type": "function",
        "function": {
          "name": "get_current_weather",
          "description": "Get the current weather in a given location",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {
                "type": "string",
                "description": "The city and state, e.g. San Francisco, CA",
              },
              "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
            },
            "required": ["location"],
          },
        }
      }
  ];

  const response = await openai.chat.completions.create({
    model: "gpt-3.5-turbo",
    messages: messages,
    tools: tools,
    tool_choice: "auto",
  });
  
  console.log(response)

}
await getChatCompletionFunctions();
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

tools = [
  {
    "type": "function",
    "function": {
      "name": "get_current_weather",
      "description": "Get the current weather in a given location",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. San Francisco, CA",
          },
          "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
        },
        "required": ["location"],
      },
    }
  }
]
messages = [{"role": "user", "content": "What's the weather like in Boston today?"}]
completion = openai.chat.completions.create(
  model="gpt-3.5-turbo",
  messages=messages,
  tools=tools,
  tool_choice="auto"
)

print(completion)
import Portkey from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

// Generate a chat completion with streaming
async function getChatCompletionFunctions(){
  const messages = [{"role": "user", "content": "What's the weather like in Boston today?"}];
  const tools = [
      {
        "type": "function",
        "function": {
          "name": "get_current_weather",
          "description": "Get the current weather in a given location",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {
                "type": "string",
                "description": "The city and state, e.g. San Francisco, CA",
              },
              "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
            },
            "required": ["location"],
          },
        }
      }
  ];

  const response = await portkey.chat.completions.create({
    model: "gpt-3.5-turbo",
    messages: messages,
    tools: tools,
    tool_choice: "auto",
  });
  
  console.log(response)

}
await getChatCompletionFunctions();
from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY"   # Add your provider's virtual key
)

tools = [
  {
    "type": "function",
    "function": {
      "name": "get_current_weather",
      "description": "Get the current weather in a given location",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. San Francisco, CA",
          },
          "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
        },
        "required": ["location"],
      },
    }
  }
]
messages = [{"role": "user", "content": "What's the weather like in Boston today?"}]
completion = portkey.chat.completions.create(
  model="gpt-3.5-turbo",
  messages=messages,
  tools=tools,
  tool_choice="auto"
)

print(completion)
curl "https://api.portkey.ai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-provider: openai" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
  "model": "gpt-3.5-turbo",
  "messages": [
    {
      "role": "user",
      "content": "What is the weather like in Boston?"
    }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. San Francisco, CA"
            },
            "unit": {
              "type": "string",
              "enum": ["celsius", "fahrenheit"]
            }
          },
          "required": ["location"]
        }
      }
    }
  ],
  "tool_choice": "auto"
}
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

response = openai.chat.completions.create(
    model="gpt-4-vision-preview",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What’s in this image?"},
                {
                    "type": "image_url",
                    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
                },
            ],
        }
    ],
    max_tokens=300,
)

print(completion)
import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

// Generate a chat completion with streaming
async function getChatCompletionFunctions(){
  const response = await openai.chat.completions.create({
    model: "gpt-4-vision-preview",
    messages: [
      {
        role: "user",
        content: [
          { type: "text", text: "What’s in this image?" },
          {
            type: "image_url",
            image_url:
              "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
          },
        ],
      },
    ],
  });
  
  console.log(response)

}
await getChatCompletionFunctions();
import Portkey from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

// Generate a chat completion with streaming
async function getChatCompletionFunctions(){
  const response = await portkey.chat.completions.create({
    model: "gpt-4-vision-preview",
    messages: [
      {
        role: "user",
        content: [
          { type: "text", text: "What’s in this image?" },
          {
            type: "image_url",
            image_url:
              "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
          },
        ],
      },
    ],
  });
  
  console.log(response)

}
await getChatCompletionFunctions();
from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY"   # Add your provider's virtual key
)


response = portkey.chat.completions.create(
    model="gpt-4-vision-preview",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What’s in this image?"},
                {
                    "type": "image_url",
                    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
                },
            ],
        }
    ],
    max_tokens=300,
)

print(completion)
curl "https://api.portkey.ai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-provider: openai" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-4-vision-preview",
    "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/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
            }
          }
        ]
      }
    ],
    "max_tokens": 300
  }'
import OpenAI from 'openai'; // We're using the v4 SDK
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY', // defaults to process.env["OPENAI_API_KEY"],
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "openai",
    apiKey: "PORTKEY_API_KEY" // defaults to process.env["PORTKEY_API_KEY"]
  })
});

async function main() {
  const image = await openai.images.generate({ 
    model: "dall-e-3", 
    prompt: "Lucy in the sky with diamonds" 
  });
  
  console.log(image.data);
}

main();
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
from IPython.display import display, Image

client = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY"
    )
)

image = client.images.generate(
  model="dall-e-3",
  prompt="Lucy in the sky with diamonds",
  n=1,
  size="1024x1024"
)

# Display the image
display(Image(url=image.data[0].url))
import Portkey from 'portkey-ai';

// Initialize the Portkey client
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

async function main() {
  const image = await portkey.images.generate({ 
    model: "dall-e-3", 
    prompt: "Lucy in the sky with diamonds" 
  });
  
  console.log(image.data);
}

main();
from portkey_ai import Portkey
from IPython.display import display, Image

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY"   # Add your provider's virtual key
)

image = portkey.images.generate(
  model="dall-e-3",
  prompt="Lucy in the sky with diamonds"
)

# Display the image
display(Image(url=image.data[0].url))
curl "https://api.portkey.ai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-virtual-key: openai-virtual-key" \
  -d '{
    "model": "dall-e-3",
    "prompt": "Lucy in the sky with diamonds"
  }'

Here's an example of Text-to-Speech

import fs from "fs";
import OpenAI from "openai";
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const openai = new OpenAI({
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    apiKey: "PORTKEY_API_KEY",
    virtualKey: "OPENAI_VIRTUAL_KEY"
  })
});

// Transcription

async function transcribe() {
  const transcription = await openai.audio.transcriptions.create({
    file: fs.createReadStream("/path/to/file.mp3"),
    model: "whisper-1",
  });

  console.log(transcription.text);
}
transcribe();

// Translation

async function translate() {
    const translation = await openai.audio.translations.create({
        file: fs.createReadStream("/path/to/file.mp3"),
        model: "whisper-1",
    });
    console.log(translation.text);
}
translate();
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        api_key="PORTKEY_API_KEY",
        virtual_key="OPENAI_VIRTUAL_KEY"
    )
)

audio_file= open("/path/to/file.mp3", "rb")

# Transcription

transcription = client.audio.transcriptions.create(
  model="whisper-1", 
  file=audio_file
)
print(transcription.text)

# Translation

translation = client.audio.translations.create(
  model="whisper-1", 
  file=audio_file
)
print(translation.text)

For Transcriptions:

curl "https://api.portkey.ai/v1/audio/transcriptions" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-provider: openai" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H 'Content-Type: multipart/form-data' \
  --form file=@/path/to/file/audio.mp3 \
  --form model=whisper-1

For Translations:

curl "https://api.portkey.ai/v1/audio/translations" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-provider: openai" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H 'Content-Type: multipart/form-data' \
  --form file=@/path/to/file/audio.mp3 \
  --form model=whisper-1
import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const client = new OpenAI({
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    apiKey: "PORTKEY_API_KEY",
    virtualKey: "PROVIDER_VIRTUAL_KEY"
  })
});

async function main() {
  const batch = await client.batches.create({
    input_file_id: "file-abc123",
    endpoint: "/v1/chat/completions",
    completion_window: "24h"
  });

  console.log(batch);
}

main();
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        api_key="PORTKEY_API_KEY",
        virtual_key="PROVIDER_VIRTUAL_KEY"
    )
)

batch = client.batches.create(
  input_file_id="file-abc123",
  endpoint="/v1/chat/completions",
  completion_window="24h"
)
import Portkey from 'portkey-ai';

const client = new Portkey({
  apiKey: 'PORTKEY_API_KEY',
  virtualKey: 'PROVIDER_VIRTUAL_KEY'
});

async function main() {
  const batch = await client.batches.create({
    input_file_id: "file-abc123",
    endpoint: "/v1/chat/completions",
    completion_window: "24h"
  });

  console.log(batch);
}

main();
from portkey_ai import Portkey

client = Portkey(
  api_key = "PORTKEY_API_KEY",
  virtual_key = "PROVIDER_VIRTUAL_KEY"
)

batch = client.batches.create(
  input_file_id="file-abc123",
  endpoint="/v1/chat/completions",
  completion_window="24h"
)
curl https://api.portkey.ai/v1/batches \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input_file_id": "file-abc123",
    "endpoint": "/v1/chat/completions",
    "completion_window": "24h"
  }'
import fs from "fs";
import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai'

const client = new OpenAI({
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    apiKey: "PORTKEY_API_KEY",
    virtualKey: "PROVIDER_VIRTUAL_KEY"
  })
});

async function main() {
  const file = await client.files.create({
    file: fs.createReadStream("mydata.jsonl"),
    purpose: "batch",
  });

  console.log(file);
}

main();
from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        api_key="PORTKEY_API_KEY",
        virtual_key="PROVIDER_VIRTUAL_KEY"
    )
)

upload = client.files.create(
  file=open("mydata.jsonl", "rb"),
  purpose="batch"
)
import fs from "fs";
import Portkey from 'portkey-ai';

const client = new Portkey({
  apiKey: 'PORTKEY_API_KEY',
  virtualKey: 'PROVIDER_VIRTUAL_KEY'
});

async function main() {
  const file = await client.files.create({
    file: fs.createReadStream("mydata.jsonl"),
    purpose: "batch",
  });

  console.log(file);
}

main();
from portkey_ai import Portkey

client = Portkey(
  api_key = "PORTKEY_API_KEY",
  virtual_key = "PROVIDER_VIRTUAL_KEY"
)

upload = client.files.create(
  file=open("mydata.jsonl", "rb"),
  purpose="batch"
)
curl https://api.portkey.ai/v1/files \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
  -F purpose="fine-tune" \
  -F file="@mydata.jsonl"

to enable the AI gateway features.

to enable the AI gateway features.

If you want to see all the providers Portkey works with, check out the

OpenAI Chat Completion
list of providers
.
OpenAI Embeddings
OpenAI Function Calling
OpenAI Chat-Vision
Images
OpenAI Audio
OpenAI Batch - Create Batch
Files - Upload File
Portkey
Add the relevant headers
Add the relevant headers