craftflow 1.0.0

A powerful workflow orchestration framework

CraftFlow

CraftFlow is a powerful workflow orchestration framework designed for building complex processing pipelines, including RAG systems, multi-agent collaborations, and data processing workflows.

Features

• 🚀 Asynchronous Processing: Native support for async tasks
• ⚡ Parallel Execution: Execute tasks in parallel
• 🔍 RAG System Support: Built-in components for Retrieval-Augmented Generation
• 🧠 MCP Decision Nodes: Multi-Conditional Path decision making
• 🛠️ Tool Integration: Unified tool registry and invocation system
• 🤖 Agent System: Support for single and multi-agent collaboration
• 📊 Execution Tracing: Detailed trace of workflow execution

🛠️ Flow Chart

The overall technical flowchart is shown below, covering the entire lifecycle from input to output.

💿 Installation

pip install craftflow

🏁Quick Start

RAG System Example

from craftflow.examples import rag_system

# Run a simple RAG workflow
rag_system.run_rag_example()

Multi-Agent System

from craftflow.examples import multi_agent_system

# Run a multi-agent collaboration workflow
multi_agent_system.run_multi_agent_example()

🔑Core Concepts

FlowContext

The data sharing context that tracks execution history and tool calls.

FlowNode

Base class for all workflow nodes. Various node types include:

• TaskNode: Synchronous task node
• AsyncTaskNode: Asynchronous task node
• ToolNode: Tool invocation node
• MCPNode: Multi-Conditional Path decision node
• AgentNode: Agent encapsulation node
• ParallelNode: Parallel execution node
• BatchNode: Batch processing node

ToolRegistry

Central registry for managing tools and their metadata.

⚙️Documentation

Full documentation is available at CraftFlow Docs

📂 Examples & Templates (Developing)

Explore more examples in the examples directory:

• rag_system.py: Full RAG workflow
• multi_agent_system.py: Multi-agent collaboration system

💡 Future Work

• Intelligent Scheduling & Optimization: Leverage historical execution metrics to dynamically allocate resources and optimize task ordering.

• Multi-Level Nested Workflows: Support complex hierarchical workflows with dependencies and parallel sub-flows across multiple levels.

• Visual Monitoring & Debugging: Provide a real-time graphical interface for inspecting workflow state, logs, and performance metrics.

• Enhanced Fault Tolerance & Rollback: Implement automatic error detection, compensation, and rollback mechanisms for robust recovery.

• Plugin Architecture: Offer a plugin system to allow community-built custom nodes, connectors, and tool integrations.

🤝 Contributing

Contributions are welcome! Please read our Contribution Guidelines before submitting pull requests.

📜 License

CraftFlow is released under the MIT License.