Add edge_pipeline_config parameter to detector creation (#415)

## Summary

Adds support for the `edge_pipeline_config` parameter when creating
detectors, mirroring the existing `pipeline_config` parameter. This
allows callers to specify which pipeline config to use for edge
inference instead of always using the mode's default.

Corresponds to the backend change in zuuul, PR #6056.

## Changes

- Updated `spec/public-api.yaml` with the new `edge_pipeline_config`
field on `DetectorCreationInputRequest`
- Ran `make generate` to regenerate the OpenAPI client models
- Added `edge_pipeline_config` parameter to all detector creation
methods in `client.py` and `experimental_api.py`:
  - `_prep_create_detector`
  - `create_detector`
  - `get_or_create_detector`
  - `create_binary_detector`
  - `create_counting_detector`
  - `create_multiclass_detector`
  - `create_bounding_box_detector`
  - `create_text_recognition_detector` (ExperimentalApi)

## Testing

Tested end-to-end against an eksdev environment running the zuuul branch
from #6056:

```python
from groundlight import Groundlight

gl = Groundlight()

det = gl.create_detector(
    name="edge-config-sdk-test",
    query="Is this image relevant?",
    pipeline_config="never-review",
    edge_pipeline_config="generic-cached-timm-efficientnetv2s-knn",
)
print(f"Created detector: {det.id}")
# Created detector: det_3AuicidzisgV5ja7fFhenB8RSIL
```

---------

Co-authored-by: Ubuntu <ubuntu@ip-10-45-0-232.us-west-2.compute.internal>

Author: timmarkhuff

generated/docs/DetectorCreationInputRequest.md

@@ -11,6 +11,7 @@ Name | Type | Description | Notes
 **confidence_threshold** | **float** | If the detector's prediction is below this confidence threshold, send the image query for human review. | [optional]  if omitted the server will use the default value of 0.9
 **patience_time** | **float** | How long Groundlight will attempt to generate a confident prediction | [optional]  if omitted the server will use the default value of 30.0
 **pipeline_config** | **str, none_type** | (Advanced usage) Configuration needed to instantiate a prediction pipeline. | [optional] 
+**edge_pipeline_config** | **str, none_type** | (Advanced usage) Configuration for the edge inference pipeline. If not specified, the mode's default edge pipeline is used. | [optional] 
 **metadata** | **str** | Base64-encoded metadata for the detector. This should be a JSON object with string keys. The size after encoding should not exceed 1362 bytes, corresponding to 1KiB before encoding. | [optional] 
 **mode** | **bool, date, datetime, dict, float, int, list, str, none_type** | Mode in which this detector will work.  * `BINARY` - BINARY * `COUNT` - COUNT * `MULTI_CLASS` - MULTI_CLASS * `TEXT` - TEXT * `BOUNDING_BOX` - BOUNDING_BOX | [optional] 
 **mode_configuration** | **bool, date, datetime, dict, float, int, list, str, none_type** |  | [optional] 

generated/docs/DetectorsApi.md

@@ -59,6 +59,7 @@ with groundlight_openapi_client.ApiClient(configuration) as api_client:
         confidence_threshold=0.9,
         patience_time=30.0,
         pipeline_config="pipeline_config_example",
+        edge_pipeline_config="edge_pipeline_config_example",
         metadata="metadata_example",
         mode=None,
         mode_configuration=None,

generated/groundlight_openapi_client/model/detector_creation_input_request.py

@@ -93,6 +93,9 @@ class DetectorCreationInputRequest(ModelNormal):
         ("pipeline_config",): {
             "max_length": 100,
         },
+        ("edge_pipeline_config",): {
+            "max_length": 100,
+        },
         ("metadata",): {
             "max_length": 1362,
             "min_length": 1,
@@ -145,6 +148,10 @@ def openapi_types():
                 str,
                 none_type,
             ),  # noqa: E501
+            "edge_pipeline_config": (
+                str,
+                none_type,
+            ),  # noqa: E501
             "metadata": (str,),  # noqa: E501
             "mode": (
                 bool,
@@ -185,6 +192,7 @@ def discriminator():
         "confidence_threshold": "confidence_threshold",  # noqa: E501
         "patience_time": "patience_time",  # noqa: E501
         "pipeline_config": "pipeline_config",  # noqa: E501
+        "edge_pipeline_config": "edge_pipeline_config",  # noqa: E501
         "metadata": "metadata",  # noqa: E501
         "mode": "mode",  # noqa: E501
         "mode_configuration": "mode_configuration",  # noqa: E501
@@ -239,6 +247,7 @@ def _from_openapi_data(cls, name, query, *args, **kwargs):  # noqa: E501
             confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.9  # noqa: E501
             patience_time (float): How long Groundlight will attempt to generate a confident prediction. [optional] if omitted the server will use the default value of 30.0  # noqa: E501
             pipeline_config (str, none_type): (Advanced usage) Configuration needed to instantiate a prediction pipeline.. [optional]  # noqa: E501
+            edge_pipeline_config (str, none_type): (Advanced usage) Configuration for the edge inference pipeline. If not specified, the mode's default edge pipeline is used.. [optional]  # noqa: E501
             metadata (str): Base64-encoded metadata for the detector. This should be a JSON object with string keys. The size after encoding should not exceed 1362 bytes, corresponding to 1KiB before encoding.. [optional]  # noqa: E501
             mode (bool, date, datetime, dict, float, int, list, str, none_type): Mode in which this detector will work.  * `BINARY` - BINARY * `COUNT` - COUNT * `MULTI_CLASS` - MULTI_CLASS * `TEXT` - TEXT * `BOUNDING_BOX` - BOUNDING_BOX. [optional]  # noqa: E501
             mode_configuration (bool, date, datetime, dict, float, int, list, str, none_type): [optional]  # noqa: E501
@@ -337,6 +346,7 @@ def __init__(self, name, query, *args, **kwargs):  # noqa: E501
             confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.9  # noqa: E501
             patience_time (float): How long Groundlight will attempt to generate a confident prediction. [optional] if omitted the server will use the default value of 30.0  # noqa: E501
             pipeline_config (str, none_type): (Advanced usage) Configuration needed to instantiate a prediction pipeline.. [optional]  # noqa: E501
+            edge_pipeline_config (str, none_type): (Advanced usage) Configuration for the edge inference pipeline. If not specified, the mode's default edge pipeline is used.. [optional]  # noqa: E501
             metadata (str): Base64-encoded metadata for the detector. This should be a JSON object with string keys. The size after encoding should not exceed 1362 bytes, corresponding to 1KiB before encoding.. [optional]  # noqa: E501
             mode (bool, date, datetime, dict, float, int, list, str, none_type): Mode in which this detector will work.  * `BINARY` - BINARY * `COUNT` - COUNT * `MULTI_CLASS` - MULTI_CLASS * `TEXT` - TEXT * `BOUNDING_BOX` - BOUNDING_BOX. [optional]  # noqa: E501
             mode_configuration (bool, date, datetime, dict, float, int, list, str, none_type): [optional]  # noqa: E501

generated/model.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
 #   filename:  public-api.yaml
-#   timestamp: 2026-03-10T18:06:07+00:00
+#   timestamp: 2026-03-14T00:27:37+00:00
 
 from __future__ import annotations
 
@@ -412,6 +412,13 @@ class DetectorCreationInputRequest(BaseModel):
     pipeline_config: Optional[constr(max_length=100)] = Field(
         None, description="(Advanced usage) Configuration needed to instantiate a prediction pipeline."
     )
+    edge_pipeline_config: Optional[constr(max_length=100)] = Field(
+        None,
+        description=(
+            "(Advanced usage) Configuration for the edge inference pipeline. If not specified, the mode's default edge"
+            " pipeline is used."
+        ),
+    )
     metadata: Optional[constr(min_length=1, max_length=1362)] = Field(
         None,
         description=(

package-lock.json

@@ -1058,6 +1058,12 @@ components:
           description: (Advanced usage) Configuration needed to instantiate a prediction
             pipeline.
           maxLength: 100
+        edge_pipeline_config:
+          type: string
+          nullable: true
+          description: (Advanced usage) Configuration for the edge inference pipeline.
+            If not specified, the mode's default edge pipeline is used.
+          maxLength: 100
         metadata:
           type: string
           minLength: 1

spec/public-api.yaml

@@ -352,6 +352,7 @@ def _prep_create_detector(  # noqa: PLR0913 # pylint: disable=too-many-arguments
         confidence_threshold: Optional[float] = None,
         patience_time: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
         priming_group_id: Optional[str] = None,
     ) -> Detector:
@@ -363,6 +364,7 @@ def _prep_create_detector(  # noqa: PLR0913 # pylint: disable=too-many-arguments
             name=name,
             query=query,
             pipeline_config=pipeline_config,
+            edge_pipeline_config=edge_pipeline_config,
         )
         if group_name is not None:
             detector_creation_input.group_name = group_name
@@ -388,6 +390,7 @@ def create_detector(  # noqa: PLR0913
         confidence_threshold: Optional[float] = None,
         patience_time: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
         class_names: Optional[Union[List[str], str]] = None,
         priming_group_id: Optional[str] = None,
@@ -441,6 +444,8 @@ def create_detector(  # noqa: PLR0913
                             confident prediction before falling back to human review. Defaults to 30 seconds.
         :param pipeline_config: Advanced usage only. Configuration string needed to instantiate a specific
                               prediction pipeline for this detector.
+        :param edge_pipeline_config: Advanced usage only. Configuration for the edge inference pipeline.
+                              If not specified, the mode's default edge pipeline is used.
         :param metadata: A dictionary or JSON string containing custom key/value pairs to associate with
                         the detector (limited to 1KB). This metadata can be used to store additional
                         information like location, purpose, or related system IDs. You can retrieve this
@@ -464,6 +469,7 @@ def create_detector(  # noqa: PLR0913
                 confidence_threshold=confidence_threshold,
                 patience_time=patience_time,
                 pipeline_config=pipeline_config,
+                edge_pipeline_config=edge_pipeline_config,
                 metadata=metadata,
                 priming_group_id=priming_group_id,
             )
@@ -480,6 +486,7 @@ def create_detector(  # noqa: PLR0913
                 confidence_threshold=confidence_threshold,
                 patience_time=patience_time,
                 pipeline_config=pipeline_config,
+                edge_pipeline_config=edge_pipeline_config,
                 metadata=metadata,
                 priming_group_id=priming_group_id,
             )
@@ -496,6 +503,7 @@ def create_detector(  # noqa: PLR0913
                 confidence_threshold=confidence_threshold,
                 patience_time=patience_time,
                 pipeline_config=pipeline_config,
+                edge_pipeline_config=edge_pipeline_config,
                 metadata=metadata,
                 priming_group_id=priming_group_id,
             )
@@ -511,6 +519,7 @@ def get_or_create_detector(  # noqa: PLR0913
         group_name: Optional[str] = None,
         confidence_threshold: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
     ) -> Detector:
         """
@@ -541,6 +550,8 @@ def get_or_create_detector(  # noqa: PLR0913
                                   the query may be sent for human review.
         :param pipeline_config: Advanced usage only. Configuration string needed to instantiate a specific
                               prediction pipeline for this detector.
+        :param edge_pipeline_config: Advanced usage only. Configuration for the edge inference pipeline.
+                              If not specified, the mode's default edge pipeline is used.
         :param metadata: A dictionary or JSON string containing custom key/value pairs to associate with
                         the detector (limited to 1KB). This metadata can be used to store additional
                         information like location, purpose, or related system IDs. You can retrieve this
@@ -567,6 +578,7 @@ def get_or_create_detector(  # noqa: PLR0913
                 group_name=group_name,
                 confidence_threshold=confidence_threshold,
                 pipeline_config=pipeline_config,
+                edge_pipeline_config=edge_pipeline_config,
                 metadata=metadata,
             )
 
@@ -1566,6 +1578,7 @@ def create_counting_detector(  # noqa: PLR0913 # pylint: disable=too-many-argume
         confidence_threshold: Optional[float] = None,
         patience_time: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
         priming_group_id: Optional[str] = None,
     ) -> Detector:
@@ -1602,6 +1615,8 @@ def create_counting_detector(  # noqa: PLR0913 # pylint: disable=too-many-argume
                             confident prediction before falling back to human review. Defaults to 30 seconds.
         :param pipeline_config: Advanced usage only. Configuration string needed to instantiate a specific
                               prediction pipeline for this detector.
+        :param edge_pipeline_config: Advanced usage only. Configuration for the edge inference pipeline.
+                              If not specified, the mode's default edge pipeline is used.
         :param metadata: A dictionary or JSON string containing custom key/value pairs to associate with
                         the detector (limited to 1KB). This metadata can be used to store additional
                         information like location, purpose, or related system IDs. You can retrieve this
@@ -1620,6 +1635,7 @@ def create_counting_detector(  # noqa: PLR0913 # pylint: disable=too-many-argume
             confidence_threshold=confidence_threshold,
             patience_time=patience_time,
             pipeline_config=pipeline_config,
+            edge_pipeline_config=edge_pipeline_config,
             metadata=metadata,
             priming_group_id=priming_group_id,
         )
@@ -1643,6 +1659,7 @@ def create_binary_detector(  # noqa: PLR0913 # pylint: disable=too-many-argument
         confidence_threshold: Optional[float] = None,
         patience_time: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
         priming_group_id: Optional[str] = None,
     ) -> Detector:
@@ -1671,6 +1688,7 @@ def create_binary_detector(  # noqa: PLR0913 # pylint: disable=too-many-argument
             confidence_threshold=confidence_threshold,
             patience_time=patience_time,
             pipeline_config=pipeline_config,
+            edge_pipeline_config=edge_pipeline_config,
             metadata=metadata,
             priming_group_id=priming_group_id,
         )
@@ -1687,6 +1705,7 @@ def create_multiclass_detector(  # noqa: PLR0913 # pylint: disable=too-many-argu
         confidence_threshold: Optional[float] = None,
         patience_time: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
         priming_group_id: Optional[str] = None,
     ) -> Detector:
@@ -1719,6 +1738,8 @@ def create_multiclass_detector(  # noqa: PLR0913 # pylint: disable=too-many-argu
                             confident prediction before falling back to human review. Defaults to 30 seconds.
         :param pipeline_config: Advanced usage only. Configuration string needed to instantiate a specific
                               prediction pipeline for this detector.
+        :param edge_pipeline_config: Advanced usage only. Configuration for the edge inference pipeline.
+                              If not specified, the mode's default edge pipeline is used.
         :param metadata: A dictionary or JSON string containing custom key/value pairs to associate with
                         the detector (limited to 1KB). This metadata can be used to store additional
                         information like location, purpose, or related system IDs. You can retrieve this
@@ -1737,6 +1758,7 @@ def create_multiclass_detector(  # noqa: PLR0913 # pylint: disable=too-many-argu
             confidence_threshold=confidence_threshold,
             patience_time=patience_time,
             pipeline_config=pipeline_config,
+            edge_pipeline_config=edge_pipeline_config,
             metadata=metadata,
             priming_group_id=priming_group_id,
         )
@@ -1757,6 +1779,7 @@ def create_bounding_box_detector(  # noqa: PLR0913 # pylint: disable=too-many-ar
         confidence_threshold: Optional[float] = None,
         patience_time: Optional[float] = None,
         pipeline_config: Optional[str] = None,
+        edge_pipeline_config: Optional[str] = None,
         metadata: Union[dict, str, None] = None,
         priming_group_id: Optional[str] = None,
     ) -> Detector:
@@ -1795,6 +1818,8 @@ def create_bounding_box_detector(  # noqa: PLR0913 # pylint: disable=too-many-ar
                             confident prediction before falling back to human review. Defaults to 30 seconds.
         :param pipeline_config: Advanced usage only. Configuration string needed to instantiate a specific
                               prediction pipeline for this detector.
+        :param edge_pipeline_config: Advanced usage only. Configuration for the edge inference pipeline.
+                              If not specified, the mode's default edge pipeline is used.
         :param metadata: A dictionary or JSON string containing custom key/value pairs to associate with
                         the detector (limited to 1KB). This metadata can be used to store additional
                         information like location, purpose, or related system IDs. You can retrieve this
@@ -1813,6 +1838,7 @@ def create_bounding_box_detector(  # noqa: PLR0913 # pylint: disable=too-many-ar
             confidence_threshold=confidence_threshold,
             patience_time=patience_time,
             pipeline_config=pipeline_config,
+            edge_pipeline_config=edge_pipeline_config,
             metadata=metadata,
             priming_group_id=priming_group_id,
         )