Unofficial OpenAI API Python SDK
Project description
OpenAI Unofficial Python SDK
An Free & Unlimited 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 for Free
Table of Contents
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.
Installation
Install the package via pip:
pip install openai-unofficial
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)
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
from openai_unofficial import OpenAIUnofficial
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)
Streaming Chat Completion
from openai_unofficial import OpenAIUnofficial
client = OpenAIUnofficial()
completion_stream = client.chat.completions.create(
messages=[{"role": "user", "content": "Write a short story in 3 sentences."}],
model="gpt-4o-mini-2024-07-18",
stream=True
)
for chunk in completion_stream:
content = chunk.choices[0].delta.content
if content:
print(content, end='', flush=True)
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)
Contributing
Contributions are welcome! Please follow these steps:
- Fork the repository.
- Create a new branch:
git checkout -b feature/my-feature
. - Commit your changes:
git commit -am 'Add new feature'
. - Push to the branch:
git push origin feature/my-feature
. - Open a pull request.
Please ensure your code adheres to the project's coding standards and passes all tests.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Note: This SDK is unofficial and not affiliated with OpenAI.
If you encounter any issues or have suggestions, please open an issue on GitHub.
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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