api/view: improve the collect of the Schema1 events

Harmonize how we collect we prepare the Schema1 events and how we
do the payload validation and the exception handling.

ansible_ai_connect/ai/api/exceptions.py

@@ -155,13 +155,6 @@ class InternalServerError(BaseWisdomAPIException):
     default_detail = "An error occurred attempting to complete the request."
 
 
-class FeedbackValidationException(WisdomBadRequest):
-    default_code = "error__feedback_validation"
-
-    def __init__(self, detail, *args, **kwargs):
-        super().__init__(detail, *args, **kwargs)
-
-
 class FeedbackInternalServerException(BaseWisdomAPIException):
     status_code = 500
     default_code = "error__feedback_internal_server"

ansible_ai_connect/ai/api/pipelines/completion_stages/deserialise.py

@@ -30,6 +30,7 @@
 class DeserializeStage(PipelineElement):
     def process(self, context: CompletionContext) -> None:
         request = context.request
+        # NOTE: This line is probably useless
         request._request._suggestion_id = request.data.get("suggestionId")
 
         request_serializer = CompletionRequestSerializer(
@@ -38,7 +39,9 @@ def process(self, context: CompletionContext) -> None:
 
         try:
             request_serializer.is_valid(raise_exception=True)
+            print(request_serializer.validated_data)
             request._request._suggestion_id = str(request_serializer.validated_data["suggestionId"])
+            request._request._model: str = request_serializer.validated_data.get("model", "")
             request._request._ansible_extension_version = str(
                 request_serializer.validated_data.get("metadata", {}).get(
                     "ansibleExtensionVersion", None

ansible_ai_connect/ai/api/pipelines/completion_stages/post_process.py

@@ -22,14 +22,15 @@
 from prometheus_client import Histogram
 from yaml.error import MarkedYAMLError
 
+import ansible_ai_connect.ai.api.telemetry.schema1 as schema1
 from ansible_ai_connect.ai.api import formatter as fmtr
 from ansible_ai_connect.ai.api.exceptions import (
     PostprocessException,
     process_error_count,
 )
 from ansible_ai_connect.ai.api.pipelines.common import PipelineElement
 from ansible_ai_connect.ai.api.pipelines.completion_context import CompletionContext
-from ansible_ai_connect.ai.api.utils.segment import send_segment_event
+from ansible_ai_connect.ai.api.utils.segment import send_schema1_event
 
 logger = logging.getLogger(__name__)
 
@@ -78,32 +79,29 @@ def write_to_segment(
         if isinstance(exception, MarkedYAMLError)
         else str(exception) if str(exception) else exception.__class__.__name__
     )
+
     if event_type == "ARI":
-        event_name = "postprocess"
-        event = {
-            "exception": exception is not None,
-            "problem": problem,
-            "duration": duration,
-            "recommendation": recommendation_yaml,
-            "truncated": truncated_yaml,
-            "postprocessed": postprocessed_yaml,
-            "details": postprocess_detail,
-            "suggestionId": str(suggestion_id) if suggestion_id else None,
-        }
-    if event_type == "ansible-lint":
-        event_name = "postprocessLint"
-        event = {
-            "exception": exception is not None,
-            "problem": problem,
-            "duration": duration,
-            "recommendation": recommendation_yaml,
-            "postprocessed": postprocessed_yaml,
-            "suggestionId": str(suggestion_id) if suggestion_id else None,
-        }
+        schema1_event = schema1.Postprocess()
+        schema1_event.details = postprocess_detail
+        schema1_event.truncated = truncated_yaml
+
+    elif event_type == "ansible-lint":
+
+        schema1_event = schema1.PostprocessLint()
+        schema1_event.postprocessed = postprocessed_yaml
+        schema1_event.problem = problem
+
+    schema1_event.set_user(user)
+    schema1_event.set_exception(exception)
+    schema1_event.duration = duration
+    schema1_event.postprocessed = postprocessed_yaml
+    schema1_event.problem = problem
+    schema1_event.recommendation = recommendation_yaml
+    schema1_event.suggestionId = str(suggestion_id) if suggestion_id else ""
 
     if model_id:
-        event["modelName"] = model_id
-    send_segment_event(event, event_name, user)
+        schema1_event.modelName = model_id
+    send_schema1_event(schema1_event)
 
 
 def trim_whitespace_lines(input: str):
@@ -358,6 +356,8 @@ def completion_post_process(context: CompletionContext):
     logger.debug(f"suggestion id: {suggestion_id}, indented recommendation: \n{indented_yaml}")
 
     # gather data for completion segment event
+    # WARNING: the block below do inplace transformation of 'tasks', we should refact the
+    # code to avoid that.
     for i, task in enumerate(tasks):
         if fmtr.is_multi_task_prompt(prompt):
             task["prediction"] = fmtr.extract_task(

ansible_ai_connect/ai/api/serializers.py

@@ -38,9 +38,6 @@
 
 
 class Metadata(serializers.Serializer):
-    class Meta:
-        fields = ["ansibleExtensionVersion"]
-
     ansibleExtensionVersion = serializers.RegexField(
         r"v?\d+\.\d+\.\d+",
         required=False,
@@ -111,14 +108,8 @@ class CompletionRequestSerializer(Metadata):
     model = serializers.CharField(required=False, allow_blank=True)
 
     @staticmethod
-    def validate_extracted_prompt(prompt, user):
+    def validate_extracted_prompt(prompt):
         if fmtr.is_multi_task_prompt(prompt):
-            # Multi-task is commercial-only
-            if user.rh_user_has_seat is False:
-                raise serializers.ValidationError(
-                    {"prompt": "requested prompt format is not supported"}
-                )
-
             if "&&" in prompt:
                 raise serializers.ValidationError(
                     {"prompt": "multiple task requests should be separated by a single '&'"}
@@ -146,18 +137,14 @@ def validate_extracted_prompt(prompt, user):
                 raise serializers.ValidationError({"prompt": "prompt contains a dictionary"})
 
     def validate_model(self, value):
-        user = self.context.get("request").user
-        if settings.ANSIBLE_AI_ENABLE_TECH_PREVIEW and user.rh_user_has_seat is False:
-            raise serializers.ValidationError("user is not entitled to customized model")
         return value
 
     def validate(self, data):
         data = super().validate(data)
 
         data["prompt"], data["context"] = fmtr.extract_prompt_and_context(data["prompt"])
-        CompletionRequestSerializer.validate_extracted_prompt(
-            data["prompt"], self.context.get("request").user
-        )
+
+        CompletionRequestSerializer.validate_extracted_prompt(data["prompt"])
 
         # If suggestion ID was not included in the request, set a random UUID to it.
         if data.get("suggestionId") is None: