refactor: remove internal record_aicore_metric function (#19)

Author: jeanscherf

src/sap_cloud_sdk/core/telemetry/__init__.py

@@ -8,7 +8,6 @@
 from sap_cloud_sdk.core.telemetry.telemetry import (
     record_request_metric,
     record_error_metric,
-    record_aicore_metric,
     set_tenant_id,
     get_tenant_id,
 )
@@ -33,7 +32,6 @@
     "record_metrics",
     "record_request_metric",
     "record_error_metric",
-    "record_aicore_metric",
     "set_tenant_id",
     "get_tenant_id",
     "auto_instrument",

src/sap_cloud_sdk/core/telemetry/telemetry.py

@@ -13,16 +13,11 @@
 from sap_cloud_sdk.core.telemetry.constants import (
     REQUEST_COUNTER_NAME,
     ERROR_COUNTER_NAME,
-    LLM_TOKEN_HISTOGRAM_NAME,
     ATTR_SAP_TENANT_ID,
     ATTR_CAPABILITY,
     ATTR_FUNCTIONALITY,
     ATTR_SOURCE,
     ATTR_DEPRECATED,
-    ATTR_GENAI_REQUEST_MODEL,
-    ATTR_GENAI_OPERATION_NAME,
-    ATTR_GENAI_TOKEN_TYPE,
-    ATTR_GENAI_PROVIDER,
 )
 from sap_cloud_sdk.core.telemetry.module import Module
 
@@ -32,7 +27,6 @@
 # Global metric instruments
 _request_counter: Optional[metrics.Counter] = None
 _error_counter: Optional[metrics.Counter] = None
-_aicore_token_histogram: Optional[metrics.Histogram] = None
 
 # Context variable for per-request tenant ID
 _tenant_id_var: ContextVar[str] = ContextVar("tenant_id", default="")
@@ -136,141 +130,6 @@ def record_error_metric(
         logger.debug(f"Failed to record error metric: {e}")
 
 
-def record_aicore_metric(
-    model_name: str,
-    provider: str,
-    operation_name: str,
-    input_tokens: int,
-    output_tokens: int,
-    custom_attributes: Optional[Dict[str, Any]] = None,
-) -> None:
-    """Record token usage metrics for GenAI model API calls.
-
-    This function records token consumption for Generative AI model API calls following
-    OpenTelemetry GenAI semantic conventions. It creates two separate histogram observations:
-    one for input tokens and one for output tokens, each differentiated by the gen_ai.token.type
-    attribute. The metrics include all default SDK attributes (service instance, SDK version,
-    deployment metadata, etc.) along with the model name.
-
-    Args:
-        model_name: The name of the GenAI model (e.g., "gpt-4", "claude-3-opus")
-        provider: The name of the GenAI provider (e.g., "openai", "anthropic", "sap-aicore")
-        operation_name: The type of GenAI operation. Well-known values include:
-            - "chat": Chat completion operation (e.g., OpenAI Chat API)
-            - "text_completion": Text completion operation
-            - "embeddings": Embeddings operation (e.g., OpenAI Create embeddings API)
-            - "generate_content": Multimodal content generation (e.g., Gemini Generate Content)
-            - "create_agent": Create GenAI agent
-            - "invoke_agent": Invoke GenAI agent
-            - "execute_tool": Execute a tool
-            Custom values are also allowed.
-        input_tokens: Number of input/prompt tokens consumed
-        output_tokens: Number of output/completion tokens generated
-        custom_attributes: Optional dictionary of additional custom attributes to include
-            in the metric. These will be merged with the standard attributes.
-
-    Example:
-        ```python
-        from sap_cloud_sdk.core.telemetry import record_aicore_metric
-
-        # Chat completion
-        record_aicore_metric(
-            model_name="gpt-4",
-            provider="openai",
-            operation_name="chat",
-            input_tokens=150,
-            output_tokens=75
-        )
-
-        # With additional custom attributes
-        record_aicore_metric(
-            model_name="gpt-4",
-            provider="openai",
-            operation_name="chat",
-            input_tokens=150,
-            output_tokens=75,
-            custom_attributes={
-                "user_id": "user123",
-                "session_id": "session456"
-            }
-        )
-        ```
-    """
-    global _aicore_token_histogram
-
-    # Lazy initialization of metrics
-    if _aicore_token_histogram is None:
-        _initialize_aicore_metrics()
-    if _aicore_token_histogram is None:
-        return
-
-    try:
-        base_attributes = _genai_base_attributes(model_name, provider, operation_name)
-
-        # Merge in any additional user-provided attributes
-        if custom_attributes:
-            base_attributes.update(custom_attributes)
-
-        # Record input tokens as separate histogram observation
-        input_attributes = base_attributes.copy()
-        input_attributes[ATTR_GENAI_TOKEN_TYPE] = "input"
-        _aicore_token_histogram.record(input_tokens, input_attributes)
-
-        # Record output tokens as separate histogram observation
-        output_attributes = base_attributes.copy()
-        output_attributes[ATTR_GENAI_TOKEN_TYPE] = "output"
-        _aicore_token_histogram.record(output_tokens, output_attributes)
-
-    except Exception as e:
-        logger.debug(f"Failed to record GenAI metric: {e}")
-
-
-def _genai_base_attributes(
-    model_name: str, provider: str, operation_name: str
-) -> Dict[str, Any]:
-    """Get base attributes for GenAI metrics.
-
-    Args:
-        model_name: The name of the LLM model
-        provider: The name of the GenAI provider
-        operation_name: The type of GenAI operation
-
-    Returns:
-        Dictionary of attributes with default SDK attributes plus GenAI-specific ones.
-    """
-    # Start with default SDK attributes for AI Core module
-    attributes = default_attributes(
-        module=Module.AICORE, source=None, operation="model_call", deprecated=False
-    )
-
-    # Add GenAI-specific attributes
-    attributes[ATTR_GENAI_REQUEST_MODEL] = model_name
-    attributes[ATTR_GENAI_PROVIDER] = provider
-    attributes[ATTR_GENAI_OPERATION_NAME] = operation_name
-
-    return attributes
-
-
-def _initialize_aicore_metrics() -> None:
-    """Initialize GenAI-specific metric instruments."""
-    global _aicore_token_histogram
-
-    try:
-        meter = get_meter()
-
-        # GenAI token usage histogram
-        _aicore_token_histogram = meter.create_histogram(
-            name=LLM_TOKEN_HISTOGRAM_NAME,
-            description="Token usage for GenAI model requests",
-            unit="{tokens}",
-        )
-
-        logger.debug("GenAI telemetry metrics initialized successfully")
-
-    except Exception as e:
-        logger.error(f"Failed to initialize GenAI telemetry metrics: {e}")
-
-
 def default_attributes(
     module: Module, source: Optional[Module], operation: str, deprecated: bool = False
 ) -> Dict[str, Any]:

src/sap_cloud_sdk/core/telemetry/user-guide.md

@@ -104,38 +104,6 @@ with invoke_agent_span(provider="openai", agent_name="SupportBot", agent_id="id"
     response = client.beta.threads.runs.create(...)
 ```
 
-### Record token metrics
-
-```python
-from sap_cloud_sdk.core.telemetry import record_aicore_metric
-
-record_aicore_metric(
-    model_name="gpt-4",
-    provider="openai",
-    operation_name="chat",
-    input_tokens=150,
-    output_tokens=75
-)
-```
-
-With custom attributes:
-
-```python
-record_aicore_metric(
-    model_name="gpt-4",
-    provider="openai",
-    operation_name="chat",
-    input_tokens=150,
-    output_tokens=75,
-    custom_attributes={
-        "user_id": "user123",
-        "feature": "document_summarization"
-    }
-)
-```
-
-Operation names: `"chat"`, `"text_completion"`, `"embeddings"`, `"generate_content"`, `"create_agent"`, `"invoke_agent"`, `"execute_tool"`
-
 ### Track tenant ID
 
 Set at request entry point:

tests/core/unit/telemetry/test_init.py

@@ -13,8 +13,7 @@ def test_module_exports(self):
         # Core functions
         assert hasattr(telemetry, 'record_request_metric')
         assert hasattr(telemetry, 'record_error_metric')
-        assert hasattr(telemetry, 'record_aicore_metric')
-        
+
         # Types
         assert hasattr(telemetry, 'Module')
         assert hasattr(telemetry, 'Operation')
@@ -42,7 +41,6 @@ def test_all_exports_in_all(self):
             'record_metrics',
             'record_request_metric',
             'record_error_metric',
-            'record_aicore_metric',
             'auto_instrument',
             'context_overlay',
             'get_current_span',
@@ -58,7 +56,6 @@ def test_imports_work(self):
         from sap_cloud_sdk.core.telemetry import (
             record_request_metric,
             record_error_metric,
-            record_aicore_metric,
             Module,
             Operation,
             GenAIOperation,
@@ -72,7 +69,6 @@ def test_imports_work(self):
         # All should be callable or types
         assert callable(record_request_metric)
         assert callable(record_error_metric)
-        assert callable(record_aicore_metric)
         assert callable(record_metrics)
         assert callable(auto_instrument)
         assert callable(context_overlay)
@@ -102,7 +98,6 @@ def test_star_import(self):
         assert 'record_metrics' in test_module.__dict__
         assert 'record_request_metric' in test_module.__dict__
         assert 'record_error_metric' in test_module.__dict__
-        assert 'record_aicore_metric' in test_module.__dict__
         assert 'auto_instrument' in test_module.__dict__
         assert 'context_overlay' in test_module.__dict__
         assert 'get_current_span' in test_module.__dict__