openai-unofficial 0.1.0

Unofficial OpenAI API Python SDK

OpenAI Unofficial Python SDK

An unofficial Python SDK for the OpenAI API, providing seamless integration and easy-to-use methods for interacting with OpenAI's latest powerful AI models, including GPT-4o (Including gpt-4o-audio-preview & gpt-4o-realtime-preview Models), GPT-4, GPT-3.5 Turbo, DALL·E 3, Whisper & Text-to-Speech (TTS) models

Table of Contents

• Features
• Installation
• Quick Start
• Usage Examples
  • List Available Models
  • Basic Chat Completion
  • Chat Completion with Image Input
  • Streaming Chat Completion using Real-Time Model
  • Audio Generation with TTS Model
  • Chat Completion with Audio Preview Model
  • Image Generation
  • Audio Speech Recognition with Whisper Model
• Contributing
• License

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Features

• Comprehensive Model Support: Integrate with the latest OpenAI models, including GPT-4, GPT-4o, GPT-3.5 Turbo, DALL·E 3, Whisper, Text-to-Speech (TTS) models, and the newest audio preview and real-time models.
• Chat Completions: Generate chat-like responses using a variety of models.
• Streaming Responses: Support for streaming chat completions, including real-time models for instantaneous outputs.
• Audio Generation: Generate high-quality speech audio with various voice options using TTS models.
• Audio and Text Responses: Utilize models like gpt-4o-audio-preview to receive both audio and text responses.
• Image Generation: Create stunning images using DALL·E models with customizable parameters.
• Audio Transcription: Convert speech to text using Whisper models.
• Easy to Use: Simple and intuitive methods to interact with various endpoints.
• Extensible: Designed to be easily extendable for future OpenAI models and endpoints.

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Installation

Install the package via pip:

pip install openai-unofficial

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Quick Start

from openai_unofficial import OpenAIUnofficial

# Initialize the client
client = OpenAIUnofficial()

# Basic chat completion
response = client.chat.completions.create(
    messages=[{"role": "user", "content": "Say hello!"}],
    model="gpt-4o"
)
print(response.choices[0].message.content)

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Usage Examples

List Available Models

from openai_unofficial import OpenAIUnofficial

client = OpenAIUnofficial()
models = client.list_models()
print("Available Models:")
for model in models['data']:
    print(f"- {model['id']}")

Basic Chat Completion

from openai_unofficial import OpenAIUnofficial

client = OpenAIUnofficial()
response = client.chat.completions.create(
    messages=[{"role": "user", "content": "Tell me a joke."}],
    model="gpt-4o"
)
print("ChatBot:", response.choices[0].message.content)

Chat Completion with Image Input

client = OpenAIUnofficial()
response = client.chat.completions.create(
    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",
                }
            },
        ],
    }],
    model="gpt-4o-mini-2024-07-18"
)
print("Response:", response.choices[0].message.content)

Audio Generation with TTS Model

from openai_unofficial import OpenAIUnofficial

client = OpenAIUnofficial()
audio_data = client.audio.create(
    input_text="This is a test of the TTS capabilities!",
    model="tts-1-hd",
    voice="nova"
)
with open("tts_output.mp3", "wb") as f:
    f.write(audio_data)
print("TTS Audio saved as tts_output.mp3")

Chat Completion with Audio Preview Model

from openai_unofficial import OpenAIUnofficial

client = OpenAIUnofficial()
response = client.chat.completions.create(
    messages=[{"role": "user", "content": "Tell me a fun fact."}],
    model="gpt-4o-audio-preview",
    modalities=["text", "audio"],
    audio={"voice": "fable", "format": "wav"}
)

message = response.choices[0].message
print("Text Response:", message.content)

if message.audio and 'data' in message.audio:
    from base64 import b64decode
    with open("audio_preview.wav", "wb") as f:
        f.write(b64decode(message.audio['data']))
    print("Audio saved as audio_preview.wav")

Image Generation

from openai_unofficial import OpenAIUnofficial

client = OpenAIUnofficial()
response = client.image.create(
    prompt="A futuristic cityscape at sunset",
    model="dall-e-3",
    size="1024x1024"
)
print("Image URL:", response.data[0].url)

Audio Speech Recognition with Whisper Model

from openai_unofficial import OpenAIUnofficial

client = OpenAIUnofficial()
with open("speech.mp3", "rb") as audio_file:
    transcription = client.audio.transcribe(
        file=audio_file,
        model="whisper-1"
    )
print("Transcription:", transcription.text)

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Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature/my-feature.
3. Commit your changes: git commit -am 'Add new feature'.
4. Push to the branch: git push origin feature/my-feature.
5. Open a pull request.

Please ensure your code adheres to the project's coding standards and passes all tests.

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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Note: This SDK is unofficial and not affiliated with OpenAI.

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If you encounter any issues or have suggestions, please open an issue on GitHub.

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Supported Models

Here's a partial list of models that the SDK currently supports. For Complete list, check out the /models endpoint:

• Chat Models:

  • gpt-4
  • gpt-4-turbo
  • gpt-4o
  • gpt-4o-mini
  • gpt-3.5-turbo
  • gpt-3.5-turbo-16k
  • gpt-3.5-turbo-instruct
  • gpt-4o-realtime-preview
  • gpt-4o-audio-preview

• Image Generation Models:

  • dall-e-2
  • dall-e-3

• Text-to-Speech (TTS) Models:

  • tts-1
  • tts-1-hd
  • tts-1-1106
  • tts-1-hd-1106

• Audio Models:

  • whisper-1

• Embedding Models:

  • text-embedding-ada-002
  • text-embedding-3-small
  • text-embedding-3-large

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