diff --git a/packages/opentelemetry-instrumentation-azureai/.flake8 b/packages/opentelemetry-instrumentation-azureai/.flake8 new file mode 100644 index 000000000..e7a29b4e7 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/.flake8 @@ -0,0 +1,15 @@ +[flake8] +max-line-length = 120 +exclude = + .git, + __pycache__, + build, + dist, + *.pyc, + *.egg-info, + .cache, + .eggs +ignore = + E203, # whitespace before ':' (black compatibility) + W503, # line break before binary operator + F401 # unused imports \ No newline at end of file diff --git a/packages/opentelemetry-instrumentation-azureai/.python-version b/packages/opentelemetry-instrumentation-azureai/.python-version new file mode 100644 index 000000000..38f42faa0 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/.python-version @@ -0,0 +1,4 @@ +3.8.10 +3.9.16 +3.10.11 +3.11.4 \ No newline at end of file diff --git a/packages/opentelemetry-instrumentation-azureai/README.md b/packages/opentelemetry-instrumentation-azureai/README.md new file mode 100644 index 000000000..3eb64bacb --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/README.md @@ -0,0 +1,91 @@ +# OpenTelemetry Azure AI Search Instrumentation + +This package provides OpenTelemetry instrumentation for the Azure AI Search Python client library. It automatically captures telemetry data from Azure AI Search operations, including search queries, durations, result counts, and errors. + +## Installation + +```bash +pip install opentelemetry-instrumentation-azure-search +``` +C:\Users\Mr.Imperium\Documents\GitHub\openllmetry\packages\opentelemetry-instrumentation-azureai +## Requirements + +- Python 3.7 or later +- `azure-search-documents >= 11.4.0` +- `opentelemetry-api` +- `opentelemetry-instrumentation` + +## Features + +- Automatic instrumentation of Azure AI Search client operations +- Spans for search, suggest, and autocomplete operations +- Metrics for operation duration, result counts, and exceptions +- Detailed operation attributes including query parameters +- Integration with OpenTelemetry semantic conventions for AI/ML + +## Usage + +### Basic Setup + +```python +from azure.search.documents import SearchClient +from azure.core.credentials import AzureKeyCredential +from opentelemetry.instrumentation.azure_search import AzureSearchInstrumentor + +# Initialize the instrumentor +AzureSearchInstrumentor().instrument() + +# Your existing Azure Search client code continues to work as normal +search_client = SearchClient( + endpoint="", + index_name="", + credential=AzureKeyCredential("") +) + +# Operations will now automatically generate telemetry +results = search_client.search(search_text="example query") +``` + +### Custom Configuration + +```python +from opentelemetry import trace +from opentelemetry import metrics +from opentelemetry.instrumentation.azure_search import AzureSearchInstrumentor + +# Configure custom trace and metric providers +tracer_provider = trace.TracerProvider() +meter_provider = metrics.MeterProvider() + +# Initialize with custom providers +AzureSearchInstrumentor().instrument( + tracer_provider=tracer_provider, + meter_provider=meter_provider +) +``` + +## Telemetry Details + +### Spans + +Each search operation creates a span with the following attributes: + +- `llm.system`: "Azure AI Search" +- `llm.request.type`: "search" +- `azure.search.index_name`: Name of the search index +- `azure.search.query`: Search query text (when available) +- `azure.search.filter`: Applied filters (when available) +- `azure.search.facets`: Requested facets (when available) +- `azure.search.top`: Number of results requested (when available) +- `azure.search.result_count`: Number of results returned (when available) + +### Metrics + +The following metrics are collected: + +| Name | Type | Description | Unit | +|------|------|-------------|------| +| `llm.operation.duration` | Histogram | Duration of search operations | seconds | +| `llm.azure_search.results` | Counter | Number of results returned | result | +| `llm.azure_search.exceptions` | Counter | Number of exceptions occurred | exception | + diff --git a/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/__init__.py b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/__init__.py new file mode 100644 index 000000000..025398578 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/__init__.py @@ -0,0 +1,240 @@ +"""OpenTelemetry Azure AI Search instrumentation""" + +import logging +import time +from typing import Collection, Dict, Optional, Callable + +from opentelemetry import context as context_api +from opentelemetry.instrumentation.instrumentor import BaseInstrumentor +from opentelemetry.instrumentation.utils import _SUPPRESS_INSTRUMENTATION_KEY, unwrap +from opentelemetry.metrics import Counter, Histogram, Meter, get_meter +from opentelemetry.semconv_ai import ( + SUPPRESS_LANGUAGE_MODEL_INSTRUMENTATION_KEY, + SpanAttributes, + Meters, + LLMRequestTypeValues, +) +from opentelemetry.trace import SpanKind, Tracer, get_tracer +from opentelemetry.trace.status import Status, StatusCode +from wrapt import wrap_function_wrapper + +from .version import __version__ +from .utils import ( + error_metrics_attributes, + set_span_attribute, + shared_metrics_attributes, +) + +logger = logging.getLogger(__name__) + +_instruments = ("azure-search-documents >= 11.4.0",) + +WRAPPED_METHODS = [ + { + "package": "azure.search.documents", + "object": "SearchClient", + "method": "search", + "span_name": "azure.search", + }, + { + "package": "azure.search.documents", + "object": "SearchClient", + "method": "suggest", + "span_name": "azure.search.suggest", + }, + { + "package": "azure.search.documents", + "object": "SearchClient", + "method": "autocomplete", + "span_name": "azure.search.autocomplete", + }, +] + +def _create_metrics(meter: Meter): + """Create metrics collectors.""" + duration_histogram = meter.create_histogram( + name=Meters.LLM_OPERATION_DURATION, + unit="s", + description="Azure AI Search operation duration", + ) + + result_counter = meter.create_counter( + name=f"{Meters.LLM_AZURE_SEARCH_PREFIX}.results", + unit="result", + description="Number of results returned by search operation", + ) + + exception_counter = meter.create_counter( + name=f"{Meters.LLM_AZURE_SEARCH_PREFIX}.exceptions", + unit="exception", + description="Number of exceptions occurred during search operations", + ) + + return duration_histogram, result_counter, exception_counter + +def _with_search_telemetry_wrapper(func): + """Helper for providing tracer for wrapper functions with metrics.""" + def _with_search_telemetry( + tracer, + duration_histogram, + result_counter, + exception_counter, + to_wrap, + ): + def wrapper(wrapped, instance, args, kwargs): + return func( + tracer, + duration_histogram, + result_counter, + exception_counter, + to_wrap, + wrapped, + instance, + args, + kwargs, + ) + return wrapper + return _with_search_telemetry + +@_with_search_telemetry_wrapper +def _wrap( + tracer: Tracer, + duration_histogram: Histogram, + result_counter: Counter, + exception_counter: Counter, + to_wrap, + wrapped, + instance, + args, + kwargs, +): + """Instruments and calls Azure Search methods.""" + if context_api.get_value(_SUPPRESS_INSTRUMENTATION_KEY) or context_api.get_value( + SUPPRESS_LANGUAGE_MODEL_INSTRUMENTATION_KEY + ): + return wrapped(*args, **kwargs) + + name = to_wrap.get("span_name") + span = tracer.start_span( + name, + kind=SpanKind.CLIENT, + attributes={ + SpanAttributes.LLM_SYSTEM: "Azure AI Search", + SpanAttributes.LLM_REQUEST_TYPE: LLMRequestTypeValues.SEARCH.value, + }, + ) + + if span.is_recording(): + # Record search parameters + set_span_attribute(span, "azure.search.index_name", instance._index_name) + if kwargs.get("search_text"): + set_span_attribute(span, "azure.search.query", kwargs["search_text"]) + if kwargs.get("filter"): + set_span_attribute(span, "azure.search.filter", kwargs["filter"]) + if kwargs.get("facets"): + set_span_attribute(span, "azure.search.facets", str(kwargs["facets"])) + if kwargs.get("top"): + set_span_attribute(span, "azure.search.top", kwargs["top"]) + + start_time = time.time() + try: + response = wrapped(*args, **kwargs) + except Exception as e: + end_time = time.time() + attributes = error_metrics_attributes(e) + + if duration_histogram: + duration = end_time - start_time + duration_histogram.record(duration, attributes=attributes) + + if exception_counter: + exception_counter.add(1, attributes=attributes) + + span.set_status(Status(StatusCode.ERROR, str(e))) + span.end() + raise e + + end_time = time.time() + + try: + metric_attributes = shared_metrics_attributes(response) + + if duration_histogram: + duration = end_time - start_time + duration_histogram.record( + duration, + attributes=metric_attributes, + ) + + if result_counter and hasattr(response, 'get_count'): + result_count = response.get_count() + if result_count is not None: + result_counter.add( + result_count, + attributes=metric_attributes, + ) + set_span_attribute(span, "azure.search.result_count", result_count) + + except Exception as ex: + logger.warning( + "Failed to set response attributes for Azure Search span, error: %s", + str(ex), + ) + + if span.is_recording(): + span.set_status(Status(StatusCode.OK)) + span.end() + return response + +class AzureSearchInstrumentor(BaseInstrumentor): + """An instrumentor for Azure AI Search client library.""" + + def __init__( + self, + exception_logger: Optional[Callable] = None, + get_common_metrics_attributes: Callable[[], Dict] = lambda: {}, + ): + super().__init__() + self._exception_logger = exception_logger + self._get_common_metrics_attributes = get_common_metrics_attributes + + def instrumentation_dependencies(self) -> Collection[str]: + return _instruments + + def _instrument(self, **kwargs): + tracer_provider = kwargs.get("tracer_provider") + tracer = get_tracer(__name__, __version__, tracer_provider) + + meter_provider = kwargs.get("meter_provider") + meter = get_meter(__name__, __version__, meter_provider) + + duration_histogram, result_counter, exception_counter = _create_metrics(meter) + + for wrapped_method in WRAPPED_METHODS: + wrap_package = wrapped_method.get("package") + wrap_object = wrapped_method.get("object") + wrap_method = wrapped_method.get("method") + + try: + wrap_function_wrapper( + wrap_package, + f"{wrap_object}.{wrap_method}", + _wrap( + tracer, + duration_histogram, + result_counter, + exception_counter, + wrapped_method, + ), + ) + except ModuleNotFoundError: + pass + + def _uninstrument(self, **kwargs): + for wrapped_method in WRAPPED_METHODS: + wrap_package = wrapped_method.get("package") + wrap_object = wrapped_method.get("object") + unwrap( + f"{wrap_package}.{wrap_object}", + wrapped_method.get("method"), + ) \ No newline at end of file diff --git a/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/metrics.py b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/metrics.py new file mode 100644 index 000000000..07765142f --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/metrics.py @@ -0,0 +1,106 @@ +"""Metrics utilities for Azure Search OpenTelemetry instrumentation.""" + +from typing import Dict, Optional, Any +from opentelemetry.metrics import Meter, Counter, Histogram +from opentelemetry.semconv_ai import Meters + +class SearchMetricsRecorder: + """Class to handle recording of Azure Search metrics.""" + + def __init__(self, meter: Meter): + """Initialize metrics recorder with OpenTelemetry meter. + + Args: + meter: OpenTelemetry meter instance + """ + self._duration_histogram = self._create_duration_histogram(meter) + self._result_counter = self._create_result_counter(meter) + self._exception_counter = self._create_exception_counter(meter) + + @staticmethod + def _create_duration_histogram(meter: Meter) -> Histogram: + """Create histogram for operation duration tracking. + + Args: + meter: OpenTelemetry meter instance + + Returns: + Histogram metric for tracking operation duration + """ + return meter.create_histogram( + name=Meters.LLM_OPERATION_DURATION, + unit="s", + description="Azure AI Search operation duration" + ) + + @staticmethod + def _create_result_counter(meter: Meter) -> Counter: + """Create counter for tracking search results. + + Args: + meter: OpenTelemetry meter instance + + Returns: + Counter metric for tracking search results + """ + return meter.create_counter( + name=f"{Meters.LLM_AZURE_SEARCH_PREFIX}.results", + unit="result", + description="Number of results returned by search operation" + ) + + @staticmethod + def _create_exception_counter(meter: Meter) -> Counter: + """Create counter for tracking exceptions. + + Args: + meter: OpenTelemetry meter instance + + Returns: + Counter metric for tracking exceptions + """ + return meter.create_counter( + name=f"{Meters.LLM_AZURE_SEARCH_PREFIX}.exceptions", + unit="exception", + description="Number of exceptions occurred during search operations" + ) + + def record_duration(self, duration: float, attributes: Optional[Dict[str, Any]] = None) -> None: + """Record operation duration. + + Args: + duration: Operation duration in seconds + attributes: Optional attributes to attach to the metric + """ + if self._duration_histogram: + self._duration_histogram.record(duration, attributes=attributes or {}) + + def record_results(self, count: int, attributes: Optional[Dict[str, Any]] = None) -> None: + """Record number of search results. + + Args: + count: Number of results returned + attributes: Optional attributes to attach to the metric + """ + if self._result_counter and count is not None: + self._result_counter.add(count, attributes=attributes or {}) + + def record_exception(self, attributes: Optional[Dict[str, Any]] = None) -> None: + """Record occurrence of an exception. + + Args: + attributes: Optional attributes to attach to the metric + """ + if self._exception_counter: + self._exception_counter.add(1, attributes=attributes or {}) + +def create_metrics_recorder(meter: Meter) -> SearchMetricsRecorder: + """Create a new metrics recorder instance. + + Args: + meter: OpenTelemetry meter instance + + Returns: + SearchMetricsRecorder instance + """ + return SearchMetricsRecorder(meter) \ No newline at end of file diff --git a/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/utils.py b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/utils.py new file mode 100644 index 000000000..654feccf8 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/utils.py @@ -0,0 +1,52 @@ +"""Utility functions for Azure AI Search instrumentation.""" + +import logging +from typing import Dict, Any, Optional +from azure.core.exceptions import HttpResponseError + +logger = logging.getLogger(__name__) + +def set_span_attribute(span, name: str, value: Any): + """Sets a span attribute if the value is not None.""" + if value is not None: + span.set_attribute(name, value) + +def error_metrics_attributes(error: Exception) -> Dict[str, str]: + """Extract error attributes for metrics.""" + attributes = {} + + if isinstance(error, HttpResponseError): + attributes["error.type"] = "http_response_error" + attributes["error.code"] = str(error.status_code) + else: + attributes["error.type"] = error.__class__.__name__ + + return attributes + +def shared_metrics_attributes(response) -> Dict[str, str]: + """Extract common attributes for metrics from response.""" + attributes = {} + + if hasattr(response, "coverage"): + attributes["search.coverage"] = str(response.coverage) + + if hasattr(response, "facets"): + attributes["search.has_facets"] = "true" if response.facets else "false" + + return attributes + +class Config: + """Configuration for Azure Search instrumentation.""" + + exception_logger = None + get_common_metrics_attributes = lambda: {} + + @staticmethod + def set_exception_logger(logger): + """Sets the exception logger.""" + Config.exception_logger = logger + + @staticmethod + def set_common_metrics_attributes(func): + """Sets the function to get common metrics attributes.""" + Config.get_common_metrics_attributes = func \ No newline at end of file diff --git a/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/version.py b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/version.py new file mode 100644 index 000000000..e74b6e43b --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/opentelemetry/instrumentation/azureai/version.py @@ -0,0 +1 @@ +__version__ = "0.33.12" diff --git a/packages/opentelemetry-instrumentation-azureai/poetry.lock b/packages/opentelemetry-instrumentation-azureai/poetry.lock new file mode 100644 index 000000000..039afe274 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/poetry.lock @@ -0,0 +1,682 @@ +# This file is 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100644 index 000000000..8d0e43b1d --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/project.json @@ -0,0 +1,24 @@ +{ + "name": "openllmetry-azure-search", + "version": "0.1.0", + "description": "Azure AI Search integration for OpenLLMetry", + "keywords": [ + "openllmetry", + "azure", + "search", + "observability", + "tracing" + ], + "homepage": "https://github.com/traceloop/openllmetry", + "repository": { + "type": "git", + "url": "https://github.com/traceloop/openllmetry.git" + }, + "authors": [ + { + "name": "Traceloop Team", + "email": "opensource@traceloop.com" + } + ], + "license": "MIT" +} \ No newline at end of file diff --git a/packages/opentelemetry-instrumentation-azureai/pyproject.toml b/packages/opentelemetry-instrumentation-azureai/pyproject.toml new file mode 100644 index 000000000..92777e694 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/pyproject.toml @@ -0,0 +1,37 @@ +[tool.poetry] +name = "opentelemetry-instrumentation-azureai" +version = "0.1.0" +description = "OpenTelemetry Azure AI Search Instrumentation" +authors = ["Your Name "] +license = "MIT" +readme = "README.md" + +[tool.poetry.dependencies] +python = "^3.8" +opentelemetry-api = ">=1.12.0" +opentelemetry-sdk = ">=1.12.0" +opentelemetry-instrumentation = ">=0.35b0" +azure-search-documents = ">=11.4.0" + +[tool.poetry.group.dev.dependencies] +pytest = "^7.3.1" +pytest-cov = "^4.0.0" +pytest-asyncio = "^0.21.0" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" + +[tool.poetry.extras] +test = ["pytest", "pytest-cov", "pytest-asyncio"] + +[tool.poetry.plugins."opentelemetry_instrumentor"] +azureai = "opentelemetry.instrumentation.azureai:AzureAIInstrumentor" + +[tool.black] +line-length = 120 +target-version = ['py38'] + +[tool.mypy] +ignore_missing_imports = true + diff --git a/packages/opentelemetry-instrumentation-azureai/tests/__init__.py b/packages/opentelemetry-instrumentation-azureai/tests/__init__.py new file mode 100644 index 000000000..d8e96c603 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/tests/__init__.py @@ -0,0 +1 @@ +"""unit tests.""" diff --git a/packages/opentelemetry-instrumentation-azureai/tests/conftest.py b/packages/opentelemetry-instrumentation-azureai/tests/conftest.py new file mode 100644 index 000000000..b6afca7d7 --- /dev/null +++ b/packages/opentelemetry-instrumentation-azureai/tests/conftest.py @@ -0,0 +1,153 @@ +import pytest +from unittest.mock import Mock, patch +from opentelemetry.metrics import Counter, Histogram +from opentelemetry.trace import Span +from opentelemetry import context as context_api +from opentelemetry.trace import set_tracer_provider, TracerProvider +from opentelemetry.sdk.trace import ReadableSpan +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry import trace +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter +from opentelemetry import metrics +from opentelemetry.sdk.resources import Resource +from opentelemetry.sdk.metrics import MeterProvider +from opentelemetry.sdk.metrics.export import InMemoryMetricReader +from contextlib import contextmanager + +# Mock the Azure Search SDK +class MockSearchClient: + def search(self, *args, **kwargs): + return {"value": [], "count": 0} + +class AzureSearchInstrumentor: + def __init__(self, meter, tracer): + self.meter = meter + self.tracer = tracer + self.search_counter = self.meter.create_counter( + "azure_search_requests", + description="Number of Azure Search requests" + ) + self.latency_histogram = self.meter.create_histogram( + "azure_search_latency", + description="Azure Search request latency" + ) + self.enabled = True + + def instrument_search_client(self, client): + original_search = client.search + + def instrumented_search(*args, **kwargs): + if not self.enabled: + return original_search(*args, **kwargs) + + with self.tracer.start_span("azure_search") as span: + try: + span.set_attribute("search.query", kwargs.get("search_text", "")) + span.set_attribute("search.top", kwargs.get("top", 0)) + + result = original_search(*args, **kwargs) + + self.search_counter.add(1, {"status": "success"}) + self.latency_histogram.record(0.1) + + return result + except Exception as e: + self.search_counter.add(1, {"status": "error"}) + span.record_exception(e) + raise + + client.search = instrumented_search + return client + + def suppress_instrumentation(self): + self.enabled = False + + def enable_instrumentation(self): + self.enabled = True + +# Test fixtures +@pytest.fixture +def mock_meter(): + meter = Mock() + meter.create_counter.return_value = Mock(spec=Counter) + meter.create_histogram.return_value = Mock(spec=Histogram) + return meter + +@pytest.fixture +def mock_span(): + span = MagicMock(spec=Span) + return span + +@pytest.fixture +def mock_tracer(mock_span): + tracer = MagicMock() + + @contextmanager + def mock_span_context(*args, **kwargs): + yield mock_span + + tracer.start_span = mock_span_context + return tracer + +@pytest.fixture +def search_client(): + return MockSearchClient() + +@pytest.fixture +def instrumentation(mock_meter, mock_tracer): + return AzureSearchInstrumentor(mock_meter, mock_tracer) + +# Tests +def test_instrumentation_suppression(instrumentation, search_client, mock_meter): + instrumented_client = instrumentation.instrument_search_client(search_client) + instrumentation.suppress_instrumentation() + + instrumented_client.search(search_text="test") + + # Verify metrics weren't recorded when suppressed + assert mock_meter.create_counter().add.call_count == 0 + assert mock_meter.create_histogram().record.call_count == 0 + +def test_normal_instrumentation(instrumentation, search_client, mock_meter): + instrumented_client = instrumentation.instrument_search_client(search_client) + + instrumented_client.search(search_text="test", top=10) + + # Verify metrics were recorded + mock_meter.create_counter().add.assert_called_once_with(1, {"status": "success"}) + mock_meter.create_histogram().record.assert_called_once_with(0.1) + +def test_exception_handling(instrumentation, search_client, mock_meter): + instrumented_client = instrumentation.instrument_search_client(search_client) + + # Make the search method raise an exception + def raise_error(*args, **kwargs): + raise Exception("Search failed") + + search_client.search = raise_error + + with pytest.raises(Exception): + instrumented_client.search(search_text="test") + + # Verify error metrics were recorded + mock_meter.create_counter().add.assert_called_once_with(1, {"status": "error"}) + +def test_metrics_recording(instrumentation, search_client, mock_meter): + instrumented_client = instrumentation.instrument_search_client(search_client) + + instrumented_client.search(search_text="test") + + # Verify both counter and 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