fix(ai-monitoring): Rename LLM -> AI, add aiModelMetadata to GlobalConfig

Rename all LLM prefixes to AI for consistency with existing naming:
- LLMModelCost -> AIModelCost
- LLMModelMetadata -> AIModelMetadata
- LLMModelMetadataConfig -> AIModelMetadataConfig
- llm-model-metadata:v1 -> ai-model-metadata:v1
- fetch_llm_model_metadata -> fetch_ai_model_metadata
- llm_model_metadata_config -> ai_model_metadata_config

Add aiModelMetadata to GlobalConfig alongside aiModelCosts. Relay's
normalize_global_config strips unknown fields, so relay globalconfig
tests pop aiModelMetadata before comparing until Relay adds support.

Restore original fetch_ai_model_costs code untouched from master.
New fetch_ai_model_metadata task appended at the bottom of the file.

Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com>

Author: constantinius

src/sentry/conf/server.py

@@ -1200,13 +1200,13 @@ def SOCIAL_AUTH_DEFAULT_USERNAME() -> str:
         "task": "relocation:sentry.relocation.transfer.find_relocation_transfer_region",
         "schedule": crontab("*/5", "*", "*", "*", "*"),
     },
-    # TODO: Remove fetch-ai-model-costs once all consumers have migrated to fetch-llm-model-metadata
+    # TODO(constantinius): Remove fetch-ai-model-costs once all consumers have migrated to fetch-ai-model-metadata
     "fetch-ai-model-costs": {
         "task": "ai_agent_monitoring:sentry.tasks.ai_agent_monitoring.fetch_ai_model_costs",
         "schedule": crontab("*/30", "*", "*", "*", "*"),
     },
-    "fetch-llm-model-metadata": {
-        "task": "ai_agent_monitoring:sentry.tasks.ai_agent_monitoring.fetch_llm_model_metadata",
+    "fetch-ai-model-metadata": {
+        "task": "ai_agent_monitoring:sentry.tasks.ai_agent_monitoring.fetch_ai_model_metadata",
         "schedule": crontab("*/30", "*", "*", "*", "*"),
     },
     "llm-issue-detection": {

src/sentry/relay/config/ai_model_costs.py

@@ -12,18 +12,18 @@
 
 
 # Legacy cache key for AI model costs (v2 flat format)
-# TODO: Remove once all consumers have migrated to LLM_MODEL_METADATA_CACHE_KEY
+# TODO(constantinius): Remove once all consumers have migrated to AI_MODEL_METADATA_CACHE_KEY
 AI_MODEL_COSTS_CACHE_KEY = "ai-model-costs:v2"
 AI_MODEL_COSTS_CACHE_TTL = 30 * 24 * 60 * 60
 
 # Cache key for storing LLM model metadata (v1 nested format)
-LLM_MODEL_METADATA_CACHE_KEY = "llm-model-metadata:v1"
+AI_MODEL_METADATA_CACHE_KEY = "ai-model-metadata:v1"
 # Cache timeout: 30 days (we re-fetch every 30 minutes, so this provides more than enough overlap)
-LLM_MODEL_METADATA_CACHE_TTL = 30 * 24 * 60 * 60
+AI_MODEL_METADATA_CACHE_TTL = 30 * 24 * 60 * 60
 
 
 class AIModelCostV2(TypedDict):
-    """Legacy flat format. TODO: Remove once all consumers have migrated."""
+    """Legacy flat format. TODO(constantinius): Remove once all consumers have migrated."""
 
     inputPerToken: float
     outputPerToken: float
@@ -33,34 +33,34 @@ class AIModelCostV2(TypedDict):
 
 
 class AIModelCosts(TypedDict):
-    """Legacy config type. TODO: Remove once all consumers have migrated."""
+    """Legacy config type. TODO(constantinius): Remove once all consumers have migrated."""
 
     version: Required[int]
     models: Required[dict[ModelId, AIModelCostV2]]
 
 
-class LLMModelCost(TypedDict):
+class AIModelCost(TypedDict):
     inputPerToken: float
     outputPerToken: float
     outputReasoningPerToken: float
     inputCachedPerToken: float
     inputCacheWritePerToken: float
 
 
-class LLMModelMetadata(TypedDict, total=False):
-    costs: Required[LLMModelCost]
+class AIModelMetadata(TypedDict, total=False):
+    costs: Required[AIModelCost]
     contextSize: int
 
 
-class LLMModelMetadataConfig(TypedDict):
+class AIModelMetadataConfig(TypedDict):
     version: Required[int]
-    models: Required[dict[ModelId, LLMModelMetadata]]
+    models: Required[dict[ModelId, AIModelMetadata]]
 
 
 def ai_model_costs_config() -> AIModelCosts | None:
     """
     Legacy: Get AI model costs configuration.
-    TODO: Remove once all consumers have migrated to llm_model_metadata_config.
+    TODO(constantinius): Remove once all consumers have migrated to ai_model_metadata_config.
     """
     if settings.SENTRY_AIR_GAP:
         return None
@@ -75,19 +75,19 @@ def ai_model_costs_config() -> AIModelCosts | None:
     return None
 
 
-def llm_model_metadata_config() -> LLMModelMetadataConfig | None:
+def ai_model_metadata_config() -> AIModelMetadataConfig | None:
     """
     Get LLM model metadata configuration.
     LLM model metadata is set in cache by a cron job,
     if there is no metadata, it should be investigated why.
 
     Returns:
-        LLMModelMetadataConfig containing cost and context size information for LLM models
+        AIModelMetadataConfig containing cost and context size information for LLM models
     """
     if settings.SENTRY_AIR_GAP:
         return None
 
-    cached_metadata = cache.get(LLM_MODEL_METADATA_CACHE_KEY)
+    cached_metadata = cache.get(AI_MODEL_METADATA_CACHE_KEY)
     if cached_metadata is not None:
         return cached_metadata
 

src/sentry/relay/globalconfig.py

@@ -1,7 +1,12 @@
 from typing import Any, TypedDict
 
 import sentry.options
-from sentry.relay.config.ai_model_costs import AIModelCosts, ai_model_costs_config
+from sentry.relay.config.ai_model_costs import (
+    AIModelCosts,
+    AIModelMetadataConfig,
+    ai_model_costs_config,
+    ai_model_metadata_config,
+)
 from sentry.relay.config.measurements import MeasurementsConfig, get_measurements_config
 from sentry.relay.config.metric_extraction import (
     MetricExtractionGroups,
@@ -40,7 +45,10 @@ class SpanOpDefaults(TypedDict):
 
 class GlobalConfig(TypedDict, total=False):
     measurements: MeasurementsConfig
-    aiModelCosts: AIModelCosts | None
+    aiModelCosts: (
+        AIModelCosts | None
+    )  # TODO(constantinius): Remove once all consumers use aiModelMetadata
+    aiModelMetadata: AIModelMetadataConfig | None
     metricExtraction: MetricExtractionGroups
     filters: GenericFiltersConfig | None
     spanOpDefaults: SpanOpDefaults
@@ -79,7 +87,8 @@ def get_global_config() -> GlobalConfig:
 
     global_config: GlobalConfig = {
         "measurements": get_measurements_config(),
-        "aiModelCosts": ai_model_costs_config(),
+        "aiModelCosts": ai_model_costs_config(),  # TODO(constantinius): Remove once all consumers use aiModelMetadata
+        "aiModelMetadata": ai_model_metadata_config(),
         "metricExtraction": global_metric_extraction_groups(),
         "spanOpDefaults": span_op_defaults(),
     }