Professional Python SDK for AutoAgents AI platform, providing intuitive APIs for intelligent conversation, file processing, knowledge base management, and more.
Table of Contents
- Why AutoAgents AI Python SDK?
- Quick Start
- Core Features
- API Reference
- Configuration
- Examples
- Contributing
- License
Why AutoAgents AI Python SDK?
AutoAgents AI Python SDK is a comprehensive toolkit that transforms how developers interact with AI-powered automation systems. Built for modern Python applications, it provides seamless integration with the AutoAgents AI platform.
Core Features
Intelligent Conversation
- Streaming Chat: Real-time conversation with multi-turn interactions
- Reasoning Process: Display AI thinking and decision-making steps
- Multi-modal Support: Handle text, images, and files in unified interface
File Processing
- Multi-format Support: Automatic processing of PDF, Word, images, and more
- Smart Analysis: Extract insights and content from documents
- Batch Operations: Handle multiple files efficiently
Knowledge Base Management
- Complete CRUD Operations: Create, read, update, delete knowledge bases
- Advanced Search: Semantic search and content retrieval
- Content Organization: Structured storage and management
Pre-built Agents
- PowerPoint Generation: Create presentations from templates and data
- React Agents: Interactive problem-solving agents
- Workflow Automation: Complex multi-step task orchestration
- Data Science Tools: Analytics and visualization capabilities
Modern Architecture
- Async Support: High-performance asynchronous API calls
- Type Safety: Full Pydantic type validation
- Extensible Design: Modular components for custom solutions
Why Choose AutoAgents AI Python SDK?
- Developer-First: Intuitive APIs designed for modern Python development
- Production-Ready: Battle-tested in enterprise environments
- Comprehensive: Everything needed for AI automation in one package
- Well-Documented: Extensive examples and clear API documentation
Quick Start
Prerequisites
- Python 3.11+
- AutoAgents AI platform account
Installation
pip install autoagentsai
Or install from source:
git clone https://github.com/your-repo/autoagents-python-sdk.git
cd autoagents-python-sdk
pip install -e .
Get API Keys
- Log in to AutoAgents AI platform
- Navigate to Profile → Personal Keys
- Copy your
personal_auth_keyandpersonal_auth_secret
First Conversation
from autoagentsai.client import ChatClient
# Initialize client
client = ChatClient(
agent_id="your_agent_id",
personal_auth_key="your_auth_key",
personal_auth_secret="your_auth_secret"
)
# Start conversation
for event in client.invoke("Hello, please introduce artificial intelligence"):
if event['type'] == 'token':
print(event['content'], end='', flush=True)
elif event['type'] == 'finish':
break
File Processing
# Upload and analyze files
for event in client.invoke(
prompt="Please analyze the main content of this document",
files=["document.pdf"]
):
if event['type'] == 'token':
print(event['content'], end='', flush=True)
Knowledge Base Management
from autoagentsai.client import KbClient
# Initialize knowledge base client
kb_client = KbClient(
personal_auth_key="your_auth_key",
personal_auth_secret="your_auth_secret"
)
# Create knowledge base
result = kb_client.create_kb(
name="Technical Documentation",
description="Store technical documents"
)
# Query knowledge base list
kb_list = kb_client.query_kb_list()
Slide Generation
from autoagentsai.slide import SlideAgent
# Create slide agent
slide_agent = SlideAgent()
# Generate presentation
slide_agent.fill(
prompt="Create a presentation about AI development",
template_file_path="template.pptx",
output_file_path="output.pptx"
)
Advanced Workflow Automation
from autoagentsai.graph import FlowGraph
# Create workflow graph
graph = FlowGraph(
personal_auth_key="your_auth_key",
personal_auth_secret="your_auth_secret"
)
# Add workflow nodes and compile
graph.add_node("chat_node", "chat", {"prompt": "Analyze this data"})
graph.add_node("ppt_node", "slide", {"template": "report.pptx"})
graph.add_edge("chat_node", "ppt_node")
# Deploy workflow
graph.compile(workflow_name="data_analysis_pipeline")
API Reference
ChatClient
Main conversation client supporting streaming chat and multimodal input.
Methods
invoke(prompt, images=None, files=None)- Start conversationhistory()- Get conversation history
Event Types
start_bubble- New response bubble startstoken- Text fragment (for typewriter effect)reasoning_token- AI reasoning processend_bubble- Response bubble endsfinish- Conversation complete
KbClient
Knowledge base management client.
Methods
create_kb(name, description)- Create knowledge basequery_kb_list()- Query knowledge base listget_kb_detail(kb_id)- Get knowledge base detailsdelete_kb(kb_id)- Delete knowledge base
FlowGraph
Workflow automation and orchestration.
Methods
add_node(node_id, module_type, inputs)- Add workflow nodeadd_edge(source, target)- Connect nodescompile(workflow_name)- Deploy workflow
Configuration
Environment Settings
# Development environment (default)
base_url = "https://uat.agentspro.cn"
# Production environment
base_url = "https://agentspro.cn"
API Keys Setup
Set your credentials as environment variables:
export AUTOAGENTS_AUTH_KEY="your_auth_key"
export AUTOAGENTS_AUTH_SECRET="your_auth_secret"
Or pass them directly when initializing clients:
client = ChatClient(
personal_auth_key="your_auth_key",
personal_auth_secret="your_auth_secret"
)
Getting Agent ID
- Open Agent details page
- Click "Share" → "API"
- Copy Agent ID
Examples
Explore the playground/ directory for comprehensive examples:
playground/client/- Chat and API examplesplayground/slide/- PowerPoint generation examplesplayground/kb/- Knowledge base managementplayground/react/- React Agent examplesplayground/graph/- Workflow automationplayground/datascience/- Data analysis tools
Contributing
We welcome contributions! Please feel free to submit issues and pull requests.
Development Setup
git clone https://github.com/your-repo/autoagents-python-sdk.git
cd autoagents-python-sdk
pip install -e .[dev]
License
MIT License
Support
- Email: forhheart5532@gmail.com
- Documentation: AutoAgents AI Official Docs
- Issues: GitHub Issues
Release files for autoagentsai 0.1.36
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| autoagentsai-0.1.36.tar.gz | 19.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autoagentsai-0.1.36-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.5 MB
Release files / autoagentsai-0.1.36.tar.gz
| Download URL | autoagentsai-0.1.36.tar.gz |
|---|---|
| Size | 19.7 MB |
| Tags | Source |
|
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No |
| Uploaded via |
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Release files / autoagentsai-0.1.36-py3-none-any.whl
| Download URL | autoagentsai-0.1.36-py3-none-any.whl |
|---|---|
| Size | 13.9 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.7.9
|