Fix LLM Obs custom evaluator provider names and add deterministic provider

.generator/schemas/v2/openapi.yaml

@@ -70997,16 +70997,18 @@ components:
         - attributes
       type: object
     LLMObsCustomEvalConfigEvalScope:
-      description: Scope at which to evaluate spans.
+      description: Scope at which to evaluate spans. `trace_fan_out` requires `llm_judge_config.target_query`.
       enum:
         - span
         - trace
+        - trace_fan_out
         - session
       example: "span"
       type: string
       x-enum-varnames:
         - SPAN
         - TRACE
+        - TRACE_FAN_OUT
         - SESSION
     LLMObsCustomEvalConfigInferenceParams:
       description: LLM inference parameters for a custom evaluator.
@@ -71043,14 +71045,20 @@ components:
           type: number
       type: object
     LLMObsCustomEvalConfigIntegrationProvider:
-      description: Name of the LLM integration provider.
+      description: >-
+        Name of the LLM integration provider. Use `deterministic` for a code evaluator, which runs `llm_judge_config.user_specified_json_post_processing_function` instead of calling an LLM. `insights_sponsored` is returned for evaluators that Datadog manages and cannot be set.
       enum:
         - openai
-        - amazon-bedrock
+        - amazon_bedrock
         - anthropic
-        - azure-openai
-        - vertex-ai
-        - llm-proxy
+        - azure_openai
+        - vertex_ai
+        - llmproxy
+        - deterministic
+        - typesafe
+        - datadog
+        - datadog_ai_gateway
+        - insights_sponsored
       example: "openai"
       type: string
       x-enum-varnames:
@@ -71060,6 +71068,11 @@ components:
         - AZURE_OPENAI
         - VERTEX_AI
         - LLM_PROXY
+        - DETERMINISTIC
+        - TYPESAFE
+        - DATADOG
+        - DATADOG_AI_GATEWAY
+        - INSIGHTS_SPONSORED
     LLMObsCustomEvalConfigLLMJudgeConfig:
       description: LLM judge configuration for a custom evaluator.
       properties:
@@ -71084,13 +71097,13 @@ components:
           type: boolean
         output_schema:
           additionalProperties: {}
-          description: JSON schema describing the expected output format of the LLM judge.
+          description: JSON schema describing the expected output format of the LLM judge. Omit for a `deterministic` evaluator.
           nullable: true
           type: object
         parsing_type:
           $ref: "#/components/schemas/LLMObsCustomEvalConfigParsingType"
         prompt_template:
-          description: List of messages forming the LLM judge prompt template.
+          description: List of messages forming the LLM judge prompt template. Omit for a `deterministic` evaluator.
           items:
             $ref: "#/components/schemas/LLMObsCustomEvalConfigPromptMessage"
           type: array
@@ -71100,7 +71113,8 @@ components:
           nullable: true
           type: string
         user_specified_json_post_processing_function:
-          description: User-provided function applied to post-process the JSON output of the LLM judge.
+          description: >-
+            User-provided JavaScript function applied to post-process the JSON output of the LLM judge. For a `deterministic` evaluator it is the evaluator itself: it receives the evaluated span (span scope), `{spans}` (trace scope), or `{session_id, traces}` (session scope), and its return value sets the result. A boolean, number, string or object becomes a boolean, score, categorical or JSON metric; `null` skips the evaluation; and `{value, assessment, reasoning, metadata}` also sets pass or fail, reasoning, and metadata.
           nullable: true
           type: string
       required:
@@ -71118,7 +71132,7 @@ components:
         integration_provider:
           $ref: "#/components/schemas/LLMObsCustomEvalConfigIntegrationProvider"
         model_name:
-          description: Name of the LLM model.
+          description: Name of the LLM model. Use `javascript` for a `deterministic` evaluator.
           example: "gpt-4o"
           type: string
         vertex_ai:
@@ -71141,12 +71155,14 @@ components:
         - structured_output
         - json
         - keyword_search
+        - typed_questions
       example: "structured_output"
       type: string
       x-enum-varnames:
         - STRUCTURED_OUTPUT
         - JSON
         - KEYWORD_SEARCH
+        - TYPED_QUESTIONS
     LLMObsCustomEvalConfigPromptContent:
       description: A content block within a prompt message.
       properties:

lib/datadog_api_client/v2/models/llm_obs_custom_eval_config_eval_scope.rb

@@ -17,12 +17,13 @@
 require 'time'
 
 module DatadogAPIClient::V2
-  # Scope at which to evaluate spans.
+  # Scope at which to evaluate spans. `trace_fan_out` requires `llm_judge_config.target_query`.
   class LLMObsCustomEvalConfigEvalScope
     include BaseEnumModel
 
     SPAN = "span".freeze
     TRACE = "trace".freeze
+    TRACE_FAN_OUT = "trace_fan_out".freeze
     SESSION = "session".freeze
   end
 end

lib/datadog_api_client/v2/models/llm_obs_custom_eval_config_integration_provider.rb

@@ -17,15 +17,20 @@
 require 'time'
 
 module DatadogAPIClient::V2
-  # Name of the LLM integration provider.
+  # Name of the LLM integration provider. Use `deterministic` for a code evaluator, which runs `llm_judge_config.user_specified_json_post_processing_function` instead of calling an LLM. `insights_sponsored` is returned for evaluators that Datadog manages and cannot be set.
   class LLMObsCustomEvalConfigIntegrationProvider
     include BaseEnumModel
 
     OPENAI = "openai".freeze
-    AMAZON_BEDROCK = "amazon-bedrock".freeze
+    AMAZON_BEDROCK = "amazon_bedrock".freeze
     ANTHROPIC = "anthropic".freeze
-    AZURE_OPENAI = "azure-openai".freeze
-    VERTEX_AI = "vertex-ai".freeze
-    LLM_PROXY = "llm-proxy".freeze
+    AZURE_OPENAI = "azure_openai".freeze
+    VERTEX_AI = "vertex_ai".freeze
+    LLM_PROXY = "llmproxy".freeze
+    DETERMINISTIC = "deterministic".freeze
+    TYPESAFE = "typesafe".freeze
+    DATADOG = "datadog".freeze
+    DATADOG_AI_GATEWAY = "datadog_ai_gateway".freeze
+    INSIGHTS_SPONSORED = "insights_sponsored".freeze
   end
 end

lib/datadog_api_client/v2/models/llm_obs_custom_eval_config_llm_judge_config.rb

@@ -36,19 +36,19 @@ class LLMObsCustomEvalConfigLLMJudgeConfig
     # Whether the library prompt template was modified.
     attr_accessor :modified_library_prompt_template
 
-    # JSON schema describing the expected output format of the LLM judge.
+    # JSON schema describing the expected output format of the LLM judge. Omit for a `deterministic` evaluator.
     attr_accessor :output_schema
 
     # Output parsing type for a custom LLM judge evaluator.
     attr_accessor :parsing_type
 
-    # List of messages forming the LLM judge prompt template.
+    # List of messages forming the LLM judge prompt template. Omit for a `deterministic` evaluator.
     attr_accessor :prompt_template
 
     # Query used to extract the target value to evaluate.
     attr_accessor :target_query
 
-    # User-provided function applied to post-process the JSON output of the LLM judge.
+    # User-provided JavaScript function applied to post-process the JSON output of the LLM judge. For a `deterministic` evaluator it is the evaluator itself: it receives the evaluated span (span scope), `{spans}` (trace scope), or `{session_id, traces}` (session scope), and its return value sets the result. A boolean, number, string or object becomes a boolean, score, categorical or JSON metric; `null` skips the evaluation; and `{value, assessment, reasoning, metadata}` also sets pass or fail, reasoning, and metadata.
     attr_accessor :user_specified_json_post_processing_function
 
     attr_accessor :additional_properties

lib/datadog_api_client/v2/models/llm_obs_custom_eval_config_llm_provider.rb

@@ -27,10 +27,10 @@ class LLMObsCustomEvalConfigLLMProvider
     # Integration account identifier.
     attr_accessor :integration_account_id
 
-    # Name of the LLM integration provider.
+    # Name of the LLM integration provider. Use `deterministic` for a code evaluator, which runs `llm_judge_config.user_specified_json_post_processing_function` instead of calling an LLM. `insights_sponsored` is returned for evaluators that Datadog manages and cannot be set.
     attr_accessor :integration_provider
 
-    # Name of the LLM model.
+    # Name of the LLM model. Use `javascript` for a `deterministic` evaluator.
     attr_accessor :model_name
 
     # Google Vertex AI-specific options for LLM provider configuration.

lib/datadog_api_client/v2/models/llm_obs_custom_eval_config_parsing_type.rb

@@ -24,5 +24,6 @@ class LLMObsCustomEvalConfigParsingType
     STRUCTURED_OUTPUT = "structured_output".freeze
     JSON = "json".freeze
     KEYWORD_SEARCH = "keyword_search".freeze
+    TYPED_QUESTIONS = "typed_questions".freeze
   end
 end

lib/datadog_api_client/v2/models/llm_obs_custom_eval_config_target.rb

@@ -27,7 +27,7 @@ class LLMObsCustomEvalConfigTarget
     # Whether the evaluator is active for the target application.
     attr_reader :enabled
 
-    # Scope at which to evaluate spans.
+    # Scope at which to evaluate spans. `trace_fan_out` requires `llm_judge_config.target_query`.
     attr_accessor :eval_scope
 
     # Experiment project IDs this evaluator is scoped to.