zozo123 commented on issue #68845:
URL: https://github.com/apache/airflow/issues/68845#issuecomment-4965954165

   Scope update after deeper review and maintainer feedback:
   
   PR #68847 no longer implements the `SandboxExecutor` originally described by 
this issue. It now proposes a narrower `SandboxToolset` in `common.ai` for 
executing model-generated Python in an isolated sandbox.
   
   We now see four separate layers:
   
   - **Monty code mode:** restricted orchestration code invoking registered 
tools.
   - **SandboxToolset:** full model-generated Python executed in a separate 
sandbox.
   - **Future SandboxOperator:** an author-defined remote command/job with 
files and artifacts.
   - **Future SandboxExecutor:** the complete Airflow `ExecuteTask` workload 
running remotely.
   
   These are complementary, but they should not share one underspecified API. 
In particular, the current `create/run/destroy` backend is a code-sandbox 
contract, not an Airflow executor contract. A real executor must additionally 
support workload submission, logs, durable status, cancellation, 
scheduler-restart adoption, DAG bundles, scoped Execution API access, and 
leaked-resource reconciliation.
   
   Proposed progression:
   
   1. Harden and land the narrowly scoped `SandboxToolset`.
   2. Add backend conformance tests and vendor-owned adapters.
   3. Prove artifacts, cancellation, and reconnection with a 
resumable/deferrable `SandboxOperator`.
   4. Explore a separate third-party `SandboxExecutor` using Airflow's existing 
`BaseExecutor` and `ExecuteTask` interfaces.
   
   Therefore this issue remains the future executor tracker; PR #68847 should 
not be presented as implementing or defining that executor.
   


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