🤖 ZeroGPT

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📚 ZeroGPT Mini Docs

ZeroGPT is a Python library for interacting with AI APIs, providing capabilities for text and image generation.

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✨ Features

Feature	Description
💬 Text Generation	Various models for diverse text outputs
🎨 Image Creation	Generate images from textual descriptions
🔓 Uncensored Mode	More unrestricted response capabilities
⚡ Optimized Performance	Memory and data handling optimization
📡 Stream Support	Real-time streamed data processing
🔐 Secure Authentication	HMAC-SHA256 request signing

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🚀 Installation

pip install zerogpt

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🛠️ Usage

🔧 Client Initialization

from zerogpt import Client
client = Client()

💬 Text Generation

📝 Simple Text Generation

# Simple request
response = client.send_message("Hi, how are you?")

📋 Text Generation with Instructions

# Request with instruction
response = client.send_message(
    "Tell me about space",
    instruction="You are an astronomy expert"
)

🔓 Uncensored Mode

# Using "uncensored" mode
response = client.send_message(
    "Explain a complex topic",
    uncensored=True
)

🧠 Think Mode (Deep Reasoning)

# Using "think" mode (deeper reasoning)
response = client.send_message(
    "Solve a difficult math problem",
    think=True
)

💭 Contextual Conversations

# With context
messages=[
    {"role": "user", "content": "Hi"},
    {"role": "assistant", "content": "Hello!"}
]
response = client.send_message(
    messages,
    think=True
)

🎨 Image Generation

🖼️ Create Images

# Create image
result = client.create_image(
    prompt="anime neko girl",
    samples=1,
    resolution=(768, 512),
    seed=-1,
    steps=50
)

💾 Manage Generated Images

# Get generated image
image = client.get_image(result['data']['request_id'])

# Save image
image.download(['path/to/save/image.png'])

# View image
image.open()

🔄 Image to Prompt

from zerogpt.utils.tools import image_to_prompt
resp = image_to_prompt('path/to/image.png')

🗂️ Working with Dummy Context¹

💾 Context Management

from zerogpt.utils.prompt import Dummy

# Create context
dummy = Dummy()
dummy.create(messages=[
    {"role": "user", "content": "Hi"},
    {"role": "assistant", "content": "Hello!"}
])

# Also possible for image generation
dummy = Dummy()
dummy.create(prompt='neko girl', steps=100)

# Save context
dummy.save("context.bin")

# Load context
dummy.load("context.bin")

# Use instead of messages:
# client.send_message(dummy)
# or
# client.create_image(dummy)

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⚙️ Parameters

📤 send_message

Parameter	Type	Required	Description
input	str or list	✅	Text prompt or list of messages
instruction	str	❌	System instruction
think	bool	❌	Use model with deeper reasoning
uncensored	bool	❌	Use unrestricted mode

🎨 create_image

Parameter	Type	Required	Description
prompt	str	✅	Description of the desired image
samples	int	❌	Number of samples
resolution	tuple	❌	Image resolution (width, height)
seed	int	❌	Seed for reproducibility
steps	int	❌	Number of generation steps
negative_prompt	str	❌	Description of undesired elements

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🔒 Security

🔐	HMAC-SHA256 All requests are signed using HMAC-SHA256 for secure data transmission
⏰	Timestamp Authentication Prevents replay attacks with timestamp validation

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📋 Requirements

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📄 License

MIT License

Copyright (c) 2025 RedPiar

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👨‍💻 Author

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_{Made with ❤️ by RedPiar}

Footnotes

1. Dummy is used to compress context and data in general, very useful for systems with low RAM. It can also be saved for even greater memory efficiency! ↩