completion = portkey.chat.completions.create(
    messages=[{"role": "user", "content": "Say this is a test"}],
    model="gpt-4o"
)

print(completion.choices[0].message.content)

chat_complete = portkey.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Say this is a test"}],
    stream=True
)

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

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-4o",
    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);

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(response)

response = portkey.embeddings.create(
    input="Your text string goes here",
    model="text-embedding-3-small"
)

print(response.data[0].embedding)

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

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

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

from pathlib import Path

speech_file_path = Path(__file__).parent / "speech.mp3"
response = portkey.audio.speech.create(
  model="tts-1",
  voice="alloy",
  input="Today is a wonderful day to build something people love!"
)

with open(speech_file_path, "wb") as f:
    f.write(response.content)

response = portkey.chat.completions.create(
  model="gpt-4o",
  messages=[{"role": "user", "content": "Say this is a test"}],
  user="user_123456"
)