fix(service): propagate text_keys to ops via get_init_configs in _set…#960
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…up_cfg When cfg is constructed directly from a JSON string in the API path, it bypasses init_configs() and update_op_attr(), causing text_keys (e.g. 'output') to not be injected into each op's text_key parameter. This results in ops using the default text_key 'text', leading to 'NoneType' object is not subscriptable when the dataset field name differs from 'text'. Fix: replace direct Namespace construction with get_init_configs() to ensure full config initialization including op attribute propagation.
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This pull request updates the configuration initialization in service.py by replacing manual Namespace creation with the get_init_configs utility. The review identifies several critical issues with this implementation: it introduces side effects by reconfiguring the global logger on every request, contains a concurrency bug due to fixed temporary file paths in the underlying configuration logic, and fails to handle cases where the configuration is already parsed as a dictionary by FastAPI. A code suggestion was provided to address these issues by handling both data types and using load_configs_only=True.
… race - Call get_init_configs() in _setup_cfg to ensure text_keys is properly propagated to each operator's text_key parameter - Use NamedTemporaryFile with delete=True to avoid race conditions when multiple API requests are processed concurrently
HYLcool
approved these changes
Apr 8, 2026
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…up_cfg
When cfg is constructed directly from a JSON string in the API path, it bypasses init_configs() and update_op_attr(), causing text_keys (e.g. 'output') to not be injected into each op's text_key parameter. This results in ops using the default text_key 'text', leading to 'NoneType' object is not subscriptable when the dataset field name differs from 'text'.
Fix: replace direct Namespace construction with get_init_configs() to ensure full config initialization including op attribute propagation.