openai-unofficial

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
• 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
  • Function Calling and Tool Usage
    • Basic Function Calling
• 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 -U 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

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)

Function Calling and Tool Usage

The SDK supports OpenAI's function calling capabilities, allowing you to define and use tools/functions in your conversations. Here are examples of function calling & tool usage:

Basic Function Calling

⚠️ Important Note: In the current version (0.1.2), complex or multiple function calling is not yet fully supported. The SDK currently supports basic function calling capabilities. Support for multiple function calls and more complex tool usage patterns will be added in upcoming releases.

from openai_unofficial import OpenAIUnofficial
import json

client = OpenAIUnofficial()

# Define your functions as tools
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"],
                        "description": "The temperature unit"
                    }
                },
                "required": ["location"]
            }
        }
    }
]

# Function to actually get weather data
def get_current_weather(location: str, unit: str = "celsius") -> str:
    # This is a mock function - replace with actual weather API call
    return f"The current weather in {location} is 22°{unit[0].upper()}"

# Initial conversation message
messages = [
    {"role": "user", "content": "What's the weather like in London?"}
]

# First API call to get function calling response
response = client.chat.completions.create(
    model="gpt-4o-mini-2024-07-18",
    messages=messages,
    tools=tools,
    tool_choice="auto"
)

# Get the assistant's message
assistant_message = response.choices[0].message
messages.append(assistant_message.to_dict())

# Check if the model wants to call a function
if assistant_message.tool_calls:
    # Process each tool call
    for tool_call in assistant_message.tool_calls:
        function_name = tool_call.function.name
        function_args = json.loads(tool_call.function.arguments)
        
        # Call the function and get the result
        function_response = get_current_weather(**function_args)
        
        # Append the function response to messages
        messages.append({
            "role": "tool",
            "tool_call_id": tool_call.id,
            "name": function_name,
            "content": function_response
        })
    
    # Get the final response from the model
    final_response = client.chat.completions.create(
        model="gpt-4o-mini-2024-07-18",
        messages=messages
    )
    
    print("Final Response:", final_response.choices[0].message.content)

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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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