Background to the issue
Many AI frameworks are deeply tied to specific cloud services or hardware platforms, resulting in high migration costs.
The PocketFlow Solution
- Zero-dependency design: only a standard Python environment is required, no third-party library requirements
- LLM-compatible program: support arbitrary API access
# 接入OpenAI示例 flow.add_node("llm", lambda x: openai.ChatCompletion.create( model="gpt-3.5", messages=[{"role":"user","content":x}])) - Cross-platform operation: seamlessly migrate between environments such as local PCs, Raspberry Pi or cloud servers
Migration implementation recommendations
1. Step-by-step alternatives: migrate non-core modules first
2. Abstract interface layer: secondary encapsulation of required vendor services
3. Use of configuration centers: externalization of volatile parameters such as API keys
Vendor lock-in can be completely avoided with this program, and migration costs are reduced by 90%.
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 overcome vendor lock-in in AI application development?
