Resolve merge conflicts.

Author: michaelsafyan

CHANGELOG.md

@@ -13,6 +13,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- `opentelemetry-instrumentation-openai-v2` Update doc for OpenAI Instrumentation to support OpenAI Compatible Platforms
+  ([#3279](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3279))
 - `opentelemetry-instrumentation-system-metrics` Add `process` metrics and deprecated `process.runtime` prefixed ones 
   ([#3250](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3250))
 - `opentelemetry-instrumentation-botocore` Add support for GenAI user events and lazy initialize tracer

instrumentation-genai/opentelemetry-instrumentation-google-genai/src/opentelemetry/instrumentation/google_genai/generate_content.py

@@ -48,6 +48,9 @@
 # Constant used to make the absence of content more understandable.
 _CONTENT_ELIDED = "<elided>"
 
+# Constant used for the value of 'gen_ai.operation.name".
+_GENERATE_CONTENT_OP_NAME = "generate_content"
+
 
 class _MethodsSnapshot:
     def __init__(self):
@@ -189,12 +192,11 @@ def _get_top_p(config: Optional[GenerateContentConfigOrDict]):
 def _to_dict(value: object):
     if isinstance(value, dict):
         return value
-    if hasattr(value, 'model_dump'):
+    if hasattr(value, "model_dump"):
         return value.model_dump()
     return json.loads(json.dumps(value))
 
 
-
 class _GenerateContentInstrumentationHelper:
     def __init__(
         self,
@@ -216,13 +218,13 @@ def __init__(
 
     def start_span_as_current_span(self, model_name, function_name):
         return self._otel_wrapper.start_as_current_span(
-            f"generate_content {model_name}",
+            f"{_GENERATE_CONTENT_OP_NAME} {model_name}",
             start_time=self._start_time,
             attributes={
                 code_attributes.CODE_FUNCTION_NAME: function_name,
                 gen_ai_attributes.GEN_AI_SYSTEM: self._genai_system,
                 gen_ai_attributes.GEN_AI_REQUEST_MODEL: self._genai_request_model,
-                gen_ai_attributes.GEN_AI_OPERATION_NAME: "GenerateContent",
+                gen_ai_attributes.GEN_AI_OPERATION_NAME: _GENERATE_CONTENT_OP_NAME,
             },
         )
 
@@ -338,19 +340,19 @@ def _maybe_log_user_prompt(
         self, contents: Union[ContentListUnion, ContentListUnionDict]
     ):
         if isinstance(contents, list):
-            total=len(contents)
-            index=0
+            total = len(contents)
+            index = 0
             for entry in contents:
-                self._maybe_log_single_user_prompt(entry, index=index, total=total)
+                self._maybe_log_single_user_prompt(
+                    entry, index=index, total=total
+                )
                 index += 1
         else:
             self._maybe_log_single_user_prompt(contents)
 
     def _maybe_log_single_user_prompt(
-        self,
-        contents: Union[ContentUnion, ContentUnionDict],
-        index=0,
-        total=1):
+        self, contents: Union[ContentUnion, ContentUnionDict], index=0, total=1
+    ):
         # TODO: figure out how to report the index in a manner that is
         # aligned with the OTel semantic conventions.
         attributes = {
@@ -394,7 +396,9 @@ def _maybe_log_response_stats(self, response: GenerateContentResponse):
         #
         pass
 
-    def _maybe_log_response_safety_ratings(self, response: GenerateContentResponse):
+    def _maybe_log_response_safety_ratings(
+        self, response: GenerateContentResponse
+    ):
         # TODO: Determine if there is a way that we can log
         # the "prompt_feedback". This would be especially useful
         # in the case where the response is blocked.
@@ -411,7 +415,8 @@ def _maybe_log_response(self, response: GenerateContentResponse):
                 candidate,
                 flat_candidate_index=self._candidate_index,
                 candidate_in_response_index=candidate_in_response_index,
-                response_index=self._response_index)
+                response_index=self._response_index,
+            )
             self._candidate_index += 1
             candidate_in_response_index += 1
 
@@ -420,10 +425,11 @@ def _maybe_log_response_candidate(
         candidate: Candidate,
         flat_candidate_index: int,
         candidate_in_response_index: int,
-        response_index: int):
+        response_index: int,
+    ):
         # TODO: Determine if there might be a way to report the
         # response index and candidate response index.
-        attributes={
+        attributes = {
             gen_ai_attributes.GEN_AI_SYSTEM: self._genai_system,
         }
         # TODO: determine if "role" should be reported here or not and, if so,
@@ -438,7 +444,7 @@ def _maybe_log_response_candidate(
         # "citation_metadata", "grounding_metadata", "logprobs_result", etc.
         #
         # See also: "TODOS.md"
-        body={
+        body = {
             "index": flat_candidate_index,
         }
         if self._content_recording_enabled:
@@ -460,7 +466,7 @@ def _record_token_usage_metric(self):
                 gen_ai_attributes.GEN_AI_TOKEN_TYPE: "input",
                 gen_ai_attributes.GEN_AI_SYSTEM: self._genai_system,
                 gen_ai_attributes.GEN_AI_REQUEST_MODEL: self._genai_request_model,
-                gen_ai_attributes.GEN_AI_OPERATION_NAME: "GenerateContent",
+                gen_ai_attributes.GEN_AI_OPERATION_NAME: _GENERATE_CONTENT_OP_NAME,
             },
         )
         self._otel_wrapper.token_usage_metric.record(
@@ -469,15 +475,15 @@ def _record_token_usage_metric(self):
                 gen_ai_attributes.GEN_AI_TOKEN_TYPE: "output",
                 gen_ai_attributes.GEN_AI_SYSTEM: self._genai_system,
                 gen_ai_attributes.GEN_AI_REQUEST_MODEL: self._genai_request_model,
-                gen_ai_attributes.GEN_AI_OPERATION_NAME: "GenerateContent",
+                gen_ai_attributes.GEN_AI_OPERATION_NAME: _GENERATE_CONTENT_OP_NAME,
             },
         )
 
     def _record_duration_metric(self):
         attributes = {
             gen_ai_attributes.GEN_AI_SYSTEM: self._genai_system,
             gen_ai_attributes.GEN_AI_REQUEST_MODEL: self._genai_request_model,
-            gen_ai_attributes.GEN_AI_OPERATION_NAME: "GenerateContent",
+            gen_ai_attributes.GEN_AI_OPERATION_NAME: _GENERATE_CONTENT_OP_NAME,
         }
         if self._error_type is not None:
             attributes[error_attributes.ERROR_TYPE] = self._error_type

instrumentation-genai/opentelemetry-instrumentation-google-genai/tests/common/requests_mocker.py

@@ -32,6 +32,7 @@
 # Because they APIs that need to be mocked are simple enough and well documented
 # enough, it seems approachable to mock the requests library, instead.
 
+from typing import Optional
 import copy
 import functools
 import http.client
@@ -81,7 +82,7 @@ def response(self):
 
 
 def _return_error_status(
-    args: RequestsCallArgs, status_code: int, reason: str = None
+    args: RequestsCallArgs, status_code: int, reason: Optional[str] = None
 ):
     result = requests.Response()
     result.url = args.request.url
@@ -198,6 +199,7 @@ def _do_send_streaming(
         request: requests.PreparedRequest,
         **kwargs,
     ):
+        args = RequestsCallArgs(session, request, **kwargs)
         response_generators = []
         for matcher, response_generator in self._handlers:
             if matcher is None:
@@ -206,7 +208,6 @@ def _do_send_streaming(
                 response_generators.append(response_generator)
         if not response_generators:
             response_generators.append(_return_404)
-        args = RequestsCallArgs(session, request, **kwargs)
         response_generator = _to_stream_response_generator(response_generators)
         call = RequestsCall(args, response_generator)
         result = call.response

instrumentation-genai/opentelemetry-instrumentation-google-genai/tests/generate_content/nonstreaming_base.py

@@ -76,7 +76,7 @@ def test_generated_span_has_minimal_genai_attributes(self):
         span = self.otel.get_span_named("generate_content gemini-2.0-flash")
         self.assertEqual(span.attributes["gen_ai.system"], "gemini")
         self.assertEqual(
-            span.attributes["gen_ai.operation.name"], "GenerateContent"
+            span.attributes["gen_ai.operation.name"], "generate_content"
         )
 
     def test_generated_span_has_correct_function_name(self):
@@ -100,7 +100,7 @@ def test_generated_span_has_vertex_ai_system_when_configured(self):
         span = self.otel.get_span_named("generate_content gemini-2.0-flash")
         self.assertEqual(span.attributes["gen_ai.system"], "vertex_ai")
         self.assertEqual(
-            span.attributes["gen_ai.operation.name"], "GenerateContent"
+            span.attributes["gen_ai.operation.name"], "generate_content"
         )
 
     def test_generated_span_counts_tokens(self):

instrumentation-genai/opentelemetry-instrumentation-openai-v2/README.rst

@@ -10,6 +10,28 @@ This library allows tracing LLM requests and logging of messages made by the
 `OpenAI Python API library <https://pypi.org/project/openai/>`_. It also captures
 the duration of the operations and the number of tokens used as metrics.
 
+Many LLM platforms support the OpenAI SDK. This means systems such as the following are observable with this instrumentation when accessed using it:
+
+.. list-table:: OpenAI Compatible Platforms
+   :widths: 40 25
+   :header-rows: 1
+
+   * - Name
+     - gen_ai.system
+   * - `Azure OpenAI <https://github.com/openai/openai-python?tab=readme-ov-file#microsoft-azure-openai>`_
+     - ``az.ai.openai``
+   * - `Gemini <https://developers.googleblog.com/en/gemini-is-now-accessible-from-the-openai-library/>`_
+     - ``gemini``
+   * - `Perplexity <https://docs.perplexity.ai/api-reference/chat-completions>`_
+     - ``perplexity``
+   * - `xAI <https://x.ai/api>`_ (Compatible with Anthropic)
+     - ``xai``
+   * - `DeepSeek <https://api-docs.deepseek.com/>`_
+     - ``deepseek``
+   * - `Groq <https://console.groq.com/docs/openai>`_
+     - ``groq``
+   * - `MistralAI <https://docs.mistral.ai/api/>`_
+     - ``mistral_ai``
 
 Installation
 ------------

pyproject.toml

@@ -144,6 +144,10 @@ members = [
   "propagator/*",
   "util/opentelemetry-util-http",
 ]
+# TODO: remove after https://github.com/open-telemetry/opentelemetry-python-contrib/issues/3300
+exclude = [
+  "instrumentation-genai/opentelemetry-instrumentation-google-genai",
+]
 
 [tool.ruff]
 # https://docs.astral.sh/ruff/configuration/

scripts/generate_instrumentation_bootstrap.py

@@ -60,7 +60,6 @@
     # by manually adding it to their environment.
     # See https://github.com/open-telemetry/opentelemetry-python-contrib/issues/2787
     "opentelemetry-instrumentation-aws-lambda",
-
     # Google GenAI instrumentation is currently excluded because it is still in early
     # development. This filter will get removed once it is further along in its
     # development lifecycle and ready to be included by default.