fix(openai): add response id attribute

packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/__init__.py

@@ -11,6 +11,7 @@
 from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
 
 from opentelemetry.instrumentation.openai.shared.config import Config
+from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import GEN_AI_RESPONSE_ID
 from opentelemetry.semconv_ai import SpanAttributes
 from opentelemetry.instrumentation.openai.utils import (
     dont_throw,
@@ -149,14 +150,14 @@ def _set_response_attributes(span, response):
         return
 
     _set_span_attribute(span, SpanAttributes.LLM_RESPONSE_MODEL, response.get("model"))
+    _set_span_attribute(span, GEN_AI_RESPONSE_ID, response.get("id"))
 
     _set_span_attribute(
         span,
         SpanAttributes.LLM_OPENAI_RESPONSE_SYSTEM_FINGERPRINT,
         response.get("system_fingerprint"),
     )
     _log_prompt_filter(span, response)
-
     usage = response.get("usage")
     if not usage:
         return

packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/chat_wrappers.py

@@ -700,7 +700,7 @@ def _build_from_streaming_response(
     start_time=None,
     request_kwargs=None,
 ):
-    complete_response = {"choices": [], "model": ""}
+    complete_response = {"choices": [], "model": "", "id": ""}
 
     first_token = True
     time_of_first_token = start_time  # will be updated when first token is received
@@ -767,7 +767,7 @@ async def _abuild_from_streaming_response(
     start_time=None,
     request_kwargs=None,
 ):
-    complete_response = {"choices": [], "model": ""}
+    complete_response = {"choices": [], "model": "", "id": ""}
 
     first_token = True
     time_of_first_token = start_time  # will be updated when first token is received
@@ -826,6 +826,7 @@ def _accumulate_stream_items(item, complete_response):
         item = model_as_dict(item)
 
     complete_response["model"] = item.get("model")
+    complete_response["id"] = item.get("id")
 
     # prompt filter results
     if item.get("prompt_filter_results"):

packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/completion_wrappers.py

@@ -142,7 +142,7 @@ def _set_completions(span, choices):
 
 @dont_throw
 def _build_from_streaming_response(span, request_kwargs, response):
-    complete_response = {"choices": [], "model": ""}
+    complete_response = {"choices": [], "model": "", "id": ""}
     for item in response:
         yield item
         _accumulate_streaming_response(complete_response, item)
@@ -160,7 +160,7 @@ def _build_from_streaming_response(span, request_kwargs, response):
 
 @dont_throw
 async def _abuild_from_streaming_response(span, request_kwargs, response):
-    complete_response = {"choices": [], "model": ""}
+    complete_response = {"choices": [], "model": "", "id": ""}
     async for item in response:
         yield item
         _accumulate_streaming_response(complete_response, item)
@@ -215,7 +215,7 @@ def _accumulate_streaming_response(complete_response, item):
         item = model_as_dict(item)
 
     complete_response["model"] = item.get("model")
-
+    complete_response["id"] = item.get("id")
     for choice in item.get("choices"):
         index = choice.get("index")
         if len(complete_response.get("choices")) <= index:

packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/assistant_wrappers.py

@@ -151,6 +151,7 @@ def messages_list_wrapper(tracer, wrapped, instance, args, kwargs):
         _set_span_attribute(
             span, f"{prefix}.content", content[0].get("text").get("value")
         )
+        _set_span_attribute(span, f"gen_ai.response.{i}.id", msg.get("id"))
 
     if run.get("usage"):
         usage_dict = model_as_dict(run.get("usage"))

packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/event_handler_wrapper.py

@@ -81,7 +81,13 @@ def on_message_delta(self, delta, snapshot):
 
     @override
     def on_message_done(self, message):
+        _set_span_attribute(
+            self._span,
+            f"gen_ai.response.{self._current_text_index}.id",
+            message.id,
+        )
         self._original_handler.on_message_done(message)
+        self._current_text_index += 1
 
     @override
     def on_text_created(self, text):
@@ -105,8 +111,6 @@ def on_text_done(self, text):
             text.value,
         )
 
-        self._current_text_index += 1
-
     @override
     def on_image_file_done(self, image_file):
         self._original_handler.on_image_file_done(image_file)

packages/opentelemetry-instrumentation-openai/tests/traces/test_assistant.py

@@ -82,6 +82,10 @@ def test_new_assistant(exporter, openai_client, assistant):
             open_ai_span.attributes[f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.role"]
             == message.role
         )
+        assert (
+            open_ai_span.attributes[f"gen_ai.response.{idx}.id"]
+            == message.id
+        )
 
 
 @pytest.mark.vcr
@@ -134,6 +138,10 @@ def test_new_assistant_with_polling(exporter, openai_client, assistant):
             == message.content[0].text.value
         )
         assert open_ai_span.attributes[f"gen_ai.completion.{idx}.role"] == message.role
+        assert (
+            open_ai_span.attributes[f"gen_ai.response.{idx}.id"]
+            == message.id
+        )
 
 
 @pytest.mark.vcr
@@ -202,6 +210,10 @@ def test_existing_assistant(exporter, openai_client):
             open_ai_span.attributes[f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.role"]
             == message.role
         )
+        assert (
+            open_ai_span.attributes[f"gen_ai.response.{idx}.id"]
+            == message.id
+        )
 
 
 @pytest.mark.vcr
@@ -272,6 +284,9 @@ def on_text_delta(self, delta, snapshot):
             open_ai_span.attributes[f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.role"]
             == "assistant"
         )
+        assert (
+            open_ai_span.attributes[f"gen_ai.response.{idx}.id"].startswith("msg")
+        )
 
 
 @pytest.mark.vcr
@@ -341,3 +356,6 @@ def on_text_delta(self, delta, snapshot):
             open_ai_span.attributes[f"{SpanAttributes.LLM_COMPLETIONS}.{idx}.role"]
             == "assistant"
         )
+        assert (
+            open_ai_span.attributes[f"gen_ai.response.{idx}.id"].startswith("msg_")
+        )

packages/opentelemetry-instrumentation-openai/tests/traces/test_azure.py

@@ -29,6 +29,7 @@ def test_chat(exporter, azure_openai_client):
         == "https://traceloop-stg.openai.azure.com//openai/"
     )
     assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpbZPf84KZFiQG6fdY0KVtIwHyIa"
 
 
 @pytest.mark.vcr
@@ -57,6 +58,7 @@ def test_chat_content_filtering(exporter, azure_openai_client):
         == "https://traceloop-stg.openai.azure.com//openai/"
     )
     assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpyGSWv1hoKdGaUaiFhfxzTEVlZo"
 
     content_filter_json = open_ai_span.attributes.get(
         f"{SpanAttributes.LLM_COMPLETIONS}.0.content_filter_results"
@@ -153,6 +155,7 @@ def test_chat_streaming(exporter, azure_openai_client):
         prompt_filter_results[0]["content_filter_results"]["self_harm"]["filtered"]
         is False
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpbaAXyt0cAnlWvI8kUAFpZt5jyQ"
 
 
 @pytest.mark.vcr
@@ -192,3 +195,4 @@ async def test_chat_async_streaming(exporter, async_azure_openai_client):
 
     events = open_ai_span.events
     assert len(events) == chunk_count
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpbbsSaH8U6amSDAwdA2WzMeDdLB"

packages/opentelemetry-instrumentation-openai/tests/traces/test_chat.py

@@ -39,6 +39,7 @@ def test_chat(exporter, openai_client):
         == "fp_2b778c6b35"
     )
     assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-908MD9ivBBLb6EaIjlqwFokntayQK"
 
 
 @pytest.mark.vcr
@@ -93,6 +94,7 @@ def test_chat_tool_calls(exporter, openai_client):
     assert (
         open_ai_span.attributes[f"{SpanAttributes.LLM_PROMPTS}.1.tool_call_id"] == "1"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9gKNZbUWSC4s2Uh2QfVV7PYiqWIuH"
 
 
 @pytest.mark.vcr
@@ -147,6 +149,7 @@ def test_chat_pydantic_based_tool_calls(exporter, openai_client):
     assert (
         open_ai_span.attributes[f"{SpanAttributes.LLM_PROMPTS}.1.tool_call_id"] == "1"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9lvGJKrBUPeJjHi3KKSEbGfcfomOP"
 
 
 @pytest.mark.vcr
@@ -190,6 +193,7 @@ def test_chat_streaming(exporter, openai_client):
     total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS)
     assert completion_tokens and prompt_tokens and total_tokens
     assert completion_tokens + prompt_tokens == total_tokens
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-908MECg5dMyTTbJEltubwQXeeWlBA"
 
 
 @pytest.mark.vcr
@@ -233,6 +237,7 @@ async def test_chat_async_streaming(exporter, async_openai_client):
     total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS)
     assert completion_tokens and prompt_tokens and total_tokens
     assert completion_tokens + prompt_tokens == total_tokens
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9AGW3t9akkLW9f5f93B7mOhiqhNMC"
 
 
 @pytest.mark.vcr
@@ -249,6 +254,8 @@ def test_with_asyncio_run(exporter, async_openai_client):
     assert [span.name for span in spans] == [
         "openai.chat",
     ]
+    open_ai_span = spans[0]
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-ANnyEsyt6uxfIIA7lcPLH95lKcEeK"
 
 
 @pytest.mark.vcr
@@ -266,7 +273,7 @@ def test_chat_context_propagation(exporter, vllm_openai_client):
         "openai.chat",
     ]
     open_ai_span = spans[0]
-
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chat-43f4347c3299481e9704ab77439fbdb8"
     args, kwargs = send_spy.mock.call_args
     request = args[0]
 
@@ -289,7 +296,7 @@ async def test_chat_async_context_propagation(exporter, async_vllm_openai_client
         "openai.chat",
     ]
     open_ai_span = spans[0]
-
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chat-4db07f02ecae49cbafe1d359db1650df"
     args, kwargs = send_spy.mock.call_args
     request = args[0]
 

packages/opentelemetry-instrumentation-openai/tests/traces/test_completions.py

@@ -29,6 +29,7 @@ def test_completion(exporter, openai_client):
         == "https://api.openai.com/v1/"
     )
     assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq42D1Socatcl1rCmgYZOFX7dFZw"
 
 
 @pytest.mark.vcr
@@ -49,6 +50,7 @@ async def test_async_completion(exporter, async_openai_client):
         == "Tell me a joke about opentelemetry"
     )
     assert open_ai_span.attributes.get(f"{SpanAttributes.LLM_COMPLETIONS}.0.content")
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq43c8U5ZZCQBX5lrSpsANwcd3OF"
 
 
 @pytest.mark.vcr
@@ -68,6 +70,7 @@ def test_completion_langchain_style(exporter, openai_client):
         == "Tell me a joke about opentelemetry"
     )
     assert open_ai_span.attributes.get(f"{SpanAttributes.LLM_COMPLETIONS}.0.content")
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq43QD6R2WqfxXLpYsRvSAIn9LB9"
 
 
 @pytest.mark.vcr
@@ -115,6 +118,7 @@ def test_completion_streaming(exporter, openai_client):
         )
         assert completion_tokens and prompt_tokens and total_tokens
         assert completion_tokens + prompt_tokens == total_tokens
+        assert open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq44ev1DvyhsBfm1hNwxfv6Dltco"
     finally:
         # unset env
         if original_value is None:
@@ -149,6 +153,7 @@ async def test_async_completion_streaming(exporter, async_openai_client):
         open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE)
         == "https://api.openai.com/v1/"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq44uFYuGm6kNe44ntRwluggKZFY"
 
 
 @pytest.mark.vcr
@@ -172,6 +177,7 @@ def test_completion_context_propagation(exporter, vllm_openai_client):
     request = args[0]
 
     assert_request_contains_tracecontext(request, openai_span)
+    assert openai_span.attributes.get("gen_ai.response.id") == "cmpl-2996bf68f7f142fa817bdd32af678df9"
 
 
 @pytest.mark.vcr
@@ -195,3 +201,4 @@ async def test_async_completion_context_propagation(exporter, async_vllm_openai_
     request = args[0]
 
     assert_request_contains_tracecontext(request, openai_span)
+    assert openai_span.attributes.get("gen_ai.response.id") == "cmpl-4acc6171f6c34008af07ca8490da3b95"

packages/opentelemetry-instrumentation-openai/tests/traces/test_functions.py

@@ -75,6 +75,7 @@ def test_open_ai_function_calls(exporter, openai_client):
         open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE]
         == "https://api.openai.com/v1/"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-8wq4AUDD36geK9Za8cccowhObkV9H"
 
 
 @pytest.mark.vcr
@@ -112,6 +113,7 @@ def test_open_ai_function_calls_tools(exporter, openai_client, openai_tools):
         open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE]
         == "https://api.openai.com/v1/"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-934OqhoorTmk1VnovIRXQCPk8PUTd"
 
 
 @pytest.mark.vcr
@@ -158,6 +160,7 @@ async def test_open_ai_function_calls_tools_streaming(
         )
         == '{"location":"San Francisco, CA"}'
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9g4TmLd49mPoD6c0EnGlhNAp8b0on"
 
 
 @pytest.mark.vcr
@@ -221,6 +224,7 @@ def test_open_ai_function_calls_tools_parallel(exporter, openai_client, openai_t
         )
         == '{"location": "Boston"}'
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9g4cZhrW9CsqihSvXslk0EUtjASsO"
 
 
 @pytest.mark.vcr
@@ -288,3 +292,4 @@ async def test_open_ai_function_calls_tools_streaming_parallel(
         )
         == '{"location": "Boston"}'
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9g58noIjRkOeNNxfFsFfcNjhXlul7"

packages/opentelemetry-instrumentation-openai/tests/traces/test_structured.py

@@ -31,6 +31,7 @@ def test_parsed_completion(exporter, openai_client):
             open_ai_span.attributes[f"{SpanAttributes.LLM_PROMPTS}.0.content"]
             == "Tell me a joke about opentelemetry"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1gNoe1Zyq9yZicdhLc85lmt2Ep"
 
 
 @pytest.mark.vcr
@@ -52,6 +53,7 @@ def test_parsed_refused_completion(exporter, openai_client):
             open_ai_span.attributes[f"{SpanAttributes.LLM_COMPLETIONS}.0.refusal"]
             == "I'm very sorry, but I can't assist with that request."
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGky8KFDbg6f5fF4qLtsBredIjZZh"
 
 
 @pytest.mark.vcr
@@ -78,6 +80,7 @@ async def test_async_parsed_completion(exporter, async_openai_client):
             open_ai_span.attributes[f"{SpanAttributes.LLM_PROMPTS}.0.content"]
             == "Tell me a joke about opentelemetry"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1iysV7rZ0qZ510vbeKVTNxSOHB"
 
 
 @pytest.mark.vcr
@@ -100,3 +103,4 @@ async def test_async_parsed_refused_completion(exporter, async_openai_client):
             open_ai_span.attributes[f"{SpanAttributes.LLM_COMPLETIONS}.0.refusal"]
             == "I'm very sorry, but I can't assist with that request."
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGkyFJGzZPUGAAEDJJuOS3idKvD3G"

packages/opentelemetry-instrumentation-openai/tests/traces/test_vision.py

@@ -48,6 +48,7 @@ def test_vision(exporter, openai_client):
         open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE]
         == "https://api.openai.com/v1/"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-8wq4EsSXTQC0JbGzob3SBHg6pS7Tt"
 
 
 @pytest.mark.vcr
@@ -103,3 +104,4 @@ def test_vision_base64(exporter, openai_client):
         open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE]
         == "https://api.openai.com/v1/"
     )
+    assert open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AC7YAG2uy8c4VfbqJp4QkdHc5PDZ4"