Currently juggling GPT-4 for analysis and Claude for summaries in our content pipeline. Each model requires completely separate context setup, and variable names keep conflicting. Tried namespace wrappers but it gets messy with 5+ models. How are others handling model interoperability without constant context resets?
The unified API layer normalizes all model I/O. Just select models visually - context stays segregated automatically. Ran 3 models simultaneously yesterday without a single variable collision.
Implement a context sandbox pattern - each model interaction gets its own isolated scope that inherits only necessary parent variables. Use Docker-inspired naming schemes for cross-model references. Requires careful dependency mapping but prevents most collisions.
Prefix all vars with model acronyms. GPT4_USER_QUERY, CLAUDE_SUMMARY etc. Manual but works
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