autoagents_core 0.1.0
SDK for interacting with AutoAgents.ai API
Requires Python: >=3.11

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<h4>Professional AI Platform Python SDK</h4>

**English** | [简体中文](README-CN.md)



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Professional Python SDK for autoagents_core AI platform, providing intuitive APIs for intelligent conversation, file processing, knowledge base management, and more.

## Table of Contents
- [Why autoagents_core AI Python SDK?](#why-autoagents_core-ai-python-sdk)
- [Quick Start](#quick-start)
- [Core Features](#core-features)
- [API Reference](#api-reference)
- [Configuration](#configuration)
- [Examples](#examples)
- [Contributing](#contributing)
- [License](#license)

## Why autoagents_core AI Python SDK?

autoagents_core 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_core 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_core 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_core AI platform account

### Installation

```bash
pip install autoagents_coreai
```

Or install from source:

```bash
git clone https://github.com/your-repo/autoagents_core-python-sdk.git
cd autoagents_core-python-sdk
pip install -e .
```

### Get API Keys

1. Log in to autoagents_core AI platform
2. Navigate to Profile → Personal Keys
3. Copy your `personal_auth_key` and `personal_auth_secret`

### First Conversation

```python
from autoagents_coreai.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

```python
# 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

```python
from autoagents_coreai.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

```python
from autoagents_coreai.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

```python
from autoagents_coreai.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 conversation
- `history()` - Get conversation history

#### Event Types

- `start_bubble` - New response bubble starts
- `token` - Text fragment (for typewriter effect)
- `reasoning_token` - AI reasoning process
- `end_bubble` - Response bubble ends
- `finish` - Conversation complete

### KbClient

Knowledge base management client.

#### Methods

- `create_kb(name, description)` - Create knowledge base
- `query_kb_list()` - Query knowledge base list
- `get_kb_detail(kb_id)` - Get knowledge base details
- `delete_kb(kb_id)` - Delete knowledge base

### FlowGraph

Workflow automation and orchestration.

#### Methods

- `add_node(node_id, module_type, inputs)` - Add workflow node
- `add_edge(source, target)` - Connect nodes
- `compile(workflow_name)` - Deploy workflow

## Configuration

### Environment Settings

```python
# 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:

```bash
export autoagents_core_AUTH_KEY="your_auth_key"
export autoagents_core_AUTH_SECRET="your_auth_secret"
```

Or pass them directly when initializing clients:

```python
client = ChatClient(
    personal_auth_key="your_auth_key",
    personal_auth_secret="your_auth_secret"
)
```

### Getting Agent ID

1. Open Agent details page
2. Click "Share" → "API"
3. Copy Agent ID

## Examples

Explore the `playground/` directory for comprehensive examples:

- `playground/client/` - Chat and API examples
- `playground/slide/` - PowerPoint generation examples
- `playground/kb/` - Knowledge base management
- `playground/react/` - React Agent examples
- `playground/graph/` - Workflow automation
- `playground/datascience/` - Data analysis tools

## Contributing

We welcome contributions! Please feel free to submit issues and pull requests.

### Development Setup

```bash
git clone https://github.com/your-repo/autoagents_core-python-sdk.git
cd autoagents_core-python-sdk
pip install -e .[dev]
```

## License

MIT License

## Support

- **Email**: forhheart5532@gmail.com
- **Documentation**: [autoagents_core AI Official Docs](https://docs.agentspro.cn)
- **Issues**: [GitHub Issues](https://github.com/your-repo/autoagents_core-python-sdk/issues)