AGI Open Network China Models - A Simple and Powerful Framework for Chinese AI Models
Project description
AGI Open Network China Models
A simple yet powerful framework for accessing Chinese AI models. Currently supports the full range of SiliconFlow models, with plans to support more Chinese AI service providers in the future.
Features
- 🚀 Simple and intuitive API interface
- 🎯 Support for multiple model types (Chat, Text, Image, Audio, Video)
- 🔧 Flexible configuration options
- 📚 Comprehensive documentation and examples
- 🛠 Complete type hints
Installation
pip install agi-open-network-cn
Quick Start
SiliconFlow Models
from agi_open_network_cn import (
SiliconFlowClient,
SiliconFlowChatModel,
SiliconFlowImageModel,
SiliconFlowAudioModel,
)
# Initialize client
client = SiliconFlowClient(api_key="your-api-key")
# Use ChatGLM
chat_model = SiliconFlowChatModel(client, model_name="chatglm-turbo")
response = chat_model.simple_chat("Tell me about ChatGLM")
print(response)
# Use Stable Diffusion to generate images
image_model = SiliconFlowImageModel(client)
image_url = image_model.simple_generate("A cute Chinese dragon")
print(image_url)
# Speech to text
audio_model = SiliconFlowAudioModel(client)
text = audio_model.simple_transcribe("speech.mp3")
print(text)
Supported Models and Features
SiliconFlow
Chat Models
- ChatGLM Series
- chatglm-turbo: General-purpose model with balanced performance
- chatglm-pro: Professional version with enhanced capabilities
- chatglm-std: Standard version with good cost-performance ratio
- chatglm-lite: Lightweight version for faster responses
- Qwen Series
- qwen-turbo: Qwen general version
- qwen-plus: Qwen enhanced version
- GPT Series
- gpt-3.5-turbo
- gpt-4
Image Models
- Stable Diffusion Series
- stable-diffusion-3-5-large-turbo: Latest version, faster generation
- stable-diffusion-xl: Large model for higher quality
- FLUX Series
- FLUX.1-schnell: High-performance image generation
- Pro/black-forest-labs/FLUX.1-schnell: Professional version
Audio Features
- Speech to Text: Supports multiple languages and scenarios
- Text to Speech: High naturalness with emotional expression
- Custom Voice: Support for voice cloning
Video Features
- Text to Video: Supports various styles and scenarios
- Async Generation: Support for long video generation
- Auto Status Query: Convenient progress tracking
Advanced Usage
Custom Model Parameters
# Using advanced parameters
response = chat_model.chat(
messages=[
{"role": "system", "content": "You are a professional Python teacher"},
{"role": "user", "content": "Explain decorators"},
],
temperature=0.7,
max_tokens=2000,
top_p=0.9,
)
Batch Processing
# Batch image generation
prompts = [
"Chinese ink painting: Mountains and waters",
"Chinese ink painting: Plum blossoms",
"Chinese ink painting: Bamboo",
]
for prompt in prompts:
image_url = image_model.simple_generate(prompt)
print(f"{prompt}: {image_url}")
Async Video Generation
from agi_open_network_cn import SiliconFlowVideoModel
video_model = SiliconFlowVideoModel(client)
response = video_model.generate("A video showcasing Chinese traditional culture")
request_id = response["request_id"]
# Poll for results
while True:
status = video_model.get_status(request_id)
if status["status"] == "completed":
print(f"Video URL: {status['url']}")
break
time.sleep(10)
Error Handling
from agi_open_network_cn.exceptions import AGIOpenNetworkError
try:
response = chat_model.simple_chat("Hello")
except AGIOpenNetworkError as e:
print(f"Error occurred: {e}")
Contributing
We welcome all forms of contributions, including but not limited to:
- Submitting issues and suggestions
- Improving documentation
- Adding new features
- Fixing bugs
- Adding new model providers
License
MIT License
Contact Us
- Website: https://www.agiopen.network
- GitHub: https://github.com/agiopennetwork/agi-open-network-cn
- Email: info@agiopen.network
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