Challenge analysis
While traditional multi-intelligence systems need to deal with complex communication protocols and state management, PocketFlow simplifies this process through its minimalist design.
Upgrading program
- Built-in connection mechanism: use
connect()Methods to establish inter-intelligent body data flowflow.connect("agent1", "agent2") # 单向连接 flow.connect("agent2", "agent1") # 双向通信 - Visualize workflow: node connections automatically form an execution mapping, at a glance during debugging
- Asynchronous execution support: intelligences can run in parallel to improve overall efficiency
Typical Application Scenarios
1. Customer service dialog system: one intelligence understands the question, another generates the answer
2. Data analysis process: multiple intelligences handle data cleaning, feature extraction, model prediction, etc., respectively
Measured time savings of about 60% for collaborative development of smart bodies.
This answer comes from the articlePocketFlow: A Minimalist Framework for AI Application Development in 100 Lines of CodeThe
May not be reproduced without permission:AI productivity tools " How to Improve Development Efficiency for AI Multi-Intelligence Collaboration?
