Solution: Lightweight Architecture and Modular Design
To address the complexity of AI agent development, ZeroGraph offers the following solutions through a lightweight architecture with 300 lines and no dependencies:
- Node Flow Architecture: Using Node and Flow classes to split tasks, each Node only needs to implement prep (prepare data), exec (execute logic), post (store results) three methods
- Batch optimization: Batch data processing through the BatchNode class to avoid duplicate code
- Process Visualization: Data transfer between nodes is handled automatically through the Flow.run() method, so developers only need to focus on a single point of logic
Implementation Steps:
- Inherit Node class to create specific functional modules (e.g., network requests, data processing)
- Combining multiple Nodes to form a workflow with the Flow class
- Passing context data through shared objects
Sample Scenario: When developing a search agent, you can split crawling, parsing, and storing into separate Nodes, which are automatically connected by Flow.
This answer comes from the articleZeroGraph: a lightweight AI agent programming frameworkThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of complex processes and bloated code in AI agent development?
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