elastic-opentelemetry-instrumentation-openai: Drop span events support

Author: xrmx

instrumentation/elastic-opentelemetry-instrumentation-openai/README.md

@@ -27,9 +27,6 @@ opentelemetry-instrument python use_openai.py
 
 # You can record more information about prompts as log events by enabling content capture.
 OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true opentelemetry-instrument python use_openai.py
-
-# You can record more information about prompts as span events by enabling content capture.
-OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true ELASTIC_OTEL_GENAI_EVENTS=span opentelemetry-instrument python use_openai.py
 ```
 
 Or manual instrumentation:
@@ -55,8 +52,7 @@ chat_completion = client.chat.completions.create(model="gpt-4o-mini", messages=m
 
 ### Instrumentation specific environment variable configuration
 
-- `ELASTIC_OTEL_GENAI_EVENTS` (default: `span`): when set to `log` exports GenAI events as
-log events instead of span events.
+None
 
 ### Elastic specific semantic conventions
 

instrumentation/elastic-opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/__init__.py

@@ -14,7 +14,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import logging
 import os
 from timeit import default_timer
@@ -26,14 +25,12 @@
 from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
 from opentelemetry.instrumentation.utils import unwrap
 from opentelemetry.instrumentation.openai.environment_variables import (
-    ELASTIC_OTEL_GENAI_EVENTS,
     OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT,
 )
 from opentelemetry.instrumentation.openai.helpers import (
     _get_embeddings_span_attributes_from_wrapper,
     _get_event_attributes,
     _get_span_attributes_from_wrapper,
-    _message_from_choice,
     _record_token_usage_metrics,
     _record_operation_duration_metric,
     _send_log_events_from_messages,
@@ -46,10 +43,6 @@
 from opentelemetry.instrumentation.openai.version import __version__
 from opentelemetry.instrumentation.openai.wrappers import StreamWrapper
 from opentelemetry.metrics import get_meter
-from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import (
-    GEN_AI_COMPLETION,
-    GEN_AI_PROMPT,
-)
 from opentelemetry.semconv._incubating.metrics.gen_ai_metrics import (
     create_gen_ai_client_token_usage,
     create_gen_ai_client_operation_duration,
@@ -86,13 +79,6 @@ def _instrument(self, **kwargs):
             == "true"
         )
 
-        # we support 3 values for deciding how to send events:
-        # - "latest" to match latest semconv, as 1.28.0 it's log
-        # - "log" to send log events (default)
-        # - "span" to send span events
-        genai_events = os.environ.get(ELASTIC_OTEL_GENAI_EVENTS, "latest").lower()
-        self.event_kind = "span" if genai_events == "span" else "log"
-
         tracer_provider = kwargs.get("tracer_provider")
         self.tracer = get_tracer(
             __name__,
@@ -165,13 +151,7 @@ def _chat_completion_wrapper(self, wrapped, instance, args, kwargs):
             if self.capture_message_content:
                 messages = kwargs.get("messages", [])
 
-                if self.event_kind == "log":
-                    _send_log_events_from_messages(self.event_logger, messages=messages, attributes=event_attributes)
-                elif span.is_recording():
-                    try:
-                        span.add_event(EVENT_GEN_AI_CONTENT_PROMPT, attributes={GEN_AI_PROMPT: json.dumps(messages)})
-                    except TypeError:
-                        logger.error(f"Failed to serialize {EVENT_GEN_AI_CONTENT_PROMPT}")
+                _send_log_events_from_messages(self.event_logger, messages=messages, attributes=event_attributes)
 
             start_time = default_timer()
             try:
@@ -188,7 +168,6 @@ def _chat_completion_wrapper(self, wrapped, instance, args, kwargs):
                     stream=result,
                     span=span,
                     capture_message_content=self.capture_message_content,
-                    event_kind=self.event_kind,
                     event_attributes=event_attributes,
                     event_logger=self.event_logger,
                     start_time=start_time,
@@ -205,19 +184,7 @@ def _chat_completion_wrapper(self, wrapped, instance, args, kwargs):
             _record_operation_duration_metric(self.operation_duration_metric, span, start_time)
 
             if self.capture_message_content:
-                if self.event_kind == "log":
-                    _send_log_events_from_choices(
-                        self.event_logger, choices=result.choices, attributes=event_attributes
-                    )
-                elif span.is_recording():
-                    # same format as the prompt
-                    completion = [_message_from_choice(choice) for choice in result.choices]
-                    try:
-                        span.add_event(
-                            EVENT_GEN_AI_CONTENT_COMPLETION, attributes={GEN_AI_COMPLETION: json.dumps(completion)}
-                        )
-                    except TypeError:
-                        logger.error(f"Failed to serialize {EVENT_GEN_AI_CONTENT_COMPLETION}")
+                _send_log_events_from_choices(self.event_logger, choices=result.choices, attributes=event_attributes)
 
             span.end()
 
@@ -239,14 +206,7 @@ async def _async_chat_completion_wrapper(self, wrapped, instance, args, kwargs):
         ) as span:
             if self.capture_message_content:
                 messages = kwargs.get("messages", [])
-
-                if self.event_kind == "log":
-                    _send_log_events_from_messages(self.event_logger, messages=messages, attributes=event_attributes)
-                elif span.is_recording():
-                    try:
-                        span.add_event(EVENT_GEN_AI_CONTENT_PROMPT, attributes={GEN_AI_PROMPT: json.dumps(messages)})
-                    except TypeError:
-                        logger.error(f"Failed to serialize {EVENT_GEN_AI_CONTENT_PROMPT}")
+                _send_log_events_from_messages(self.event_logger, messages=messages, attributes=event_attributes)
 
             start_time = default_timer()
             try:
@@ -263,7 +223,6 @@ async def _async_chat_completion_wrapper(self, wrapped, instance, args, kwargs):
                     stream=result,
                     span=span,
                     capture_message_content=self.capture_message_content,
-                    event_kind=self.event_kind,
                     event_attributes=event_attributes,
                     event_logger=self.event_logger,
                     start_time=start_time,
@@ -280,19 +239,7 @@ async def _async_chat_completion_wrapper(self, wrapped, instance, args, kwargs):
             _record_operation_duration_metric(self.operation_duration_metric, span, start_time)
 
             if self.capture_message_content:
-                if self.event_kind == "log":
-                    _send_log_events_from_choices(
-                        self.event_logger, choices=result.choices, attributes=event_attributes
-                    )
-                elif span.is_recording():
-                    # same format as the prompt
-                    completion = [_message_from_choice(choice) for choice in result.choices]
-                    try:
-                        span.add_event(
-                            EVENT_GEN_AI_CONTENT_COMPLETION, attributes={GEN_AI_COMPLETION: json.dumps(completion)}
-                        )
-                    except TypeError:
-                        logger.error(f"Failed to serialize {EVENT_GEN_AI_CONTENT_COMPLETION}")
+                _send_log_events_from_choices(self.event_logger, choices=result.choices, attributes=event_attributes)
 
             span.end()
 

instrumentation/elastic-opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/environment_variables.py

@@ -15,5 +15,3 @@
 # limitations under the License.
 
 OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT = "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT"
-
-ELASTIC_OTEL_GENAI_EVENTS = "ELASTIC_OTEL_GENAI_EVENTS"

instrumentation/elastic-opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/helpers.py

@@ -79,62 +79,6 @@ def _set_embeddings_span_attributes_from_response(span: Span, model: str, usage:
     span.set_attribute(GEN_AI_USAGE_INPUT_TOKENS, usage.prompt_tokens)
 
 
-def _message_from_choice(choice):
-    """Format a choice into a message of the same shape of the prompt"""
-    if tool_calls := getattr(choice.message, "tool_calls", None):
-        return {
-            "role": choice.message.role,
-            "content": "",
-            "tool_calls": [
-                {
-                    "id": tool_call.id,
-                    "type": tool_call.type,
-                    "function": {
-                        "name": tool_call.function.name,
-                        "arguments": tool_call.function.arguments,
-                    },
-                }
-                for tool_call in tool_calls
-            ],
-        }
-    else:
-        return {"role": choice.message.role, "content": choice.message.content}
-
-
-def _message_from_stream_choices(choices):
-    """Format an iterable of choices into a message of the same shape of the prompt"""
-    messages = {}
-    tool_calls = {}
-    for choice in choices:
-        messages.setdefault(choice.index, {"role": None, "content": ""})
-        message = messages[choice.index]
-        if choice.delta.role:
-            message["role"] = choice.delta.role
-        if choice.delta.content:
-            message["content"] += choice.delta.content
-
-        if choice.delta.tool_calls:
-            for call in choice.delta.tool_calls:
-                tool_calls.setdefault(choice.index, {})
-                tool_calls[choice.index].setdefault(call.index, {"function": {"arguments": ""}})
-                tool_call = tool_calls[choice.index][call.index]
-                if call.function.arguments:
-                    tool_call["function"]["arguments"] += call.function.arguments
-                if call.function.name:
-                    tool_call["function"]["name"] = call.function.name
-                if call.id:
-                    tool_call["id"] = call.id
-                if call.type:
-                    tool_call["type"] = call.type
-
-    for message_index in tool_calls:
-        message = messages[message_index]
-        message["tool_calls"] = [arguments for _, arguments in sorted(tool_calls[message_index].items())]
-
-    # assumes there's only one message
-    return [message for _, message in sorted(messages.items())][0]
-
-
 def _attributes_from_client(client) -> Attributes:
     span_attributes = {}
 

instrumentation/elastic-opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/wrappers.py

@@ -14,23 +14,17 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import logging
-from typing import Literal
 
 from opentelemetry._events import EventLogger
 from opentelemetry.instrumentation.openai.helpers import (
-    _message_from_stream_choices,
     _record_token_usage_metrics,
     _record_operation_duration_metric,
     _set_span_attributes_from_response,
     _send_log_events_from_stream_choices,
 )
 from opentelemetry.metrics import Histogram
 from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
-from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import (
-    GEN_AI_COMPLETION,
-)
 from opentelemetry.trace import Span
 from opentelemetry.trace.status import StatusCode
 from opentelemetry.util.types import Attributes
@@ -46,7 +40,6 @@ def __init__(
         stream,
         span: Span,
         capture_message_content: bool,
-        event_kind: Literal["log", "span"],
         event_attributes: Attributes,
         event_logger: EventLogger,
         start_time: float,
@@ -56,7 +49,6 @@ def __init__(
         self.stream = stream
         self.span = span
         self.capture_message_content = capture_message_content
-        self.event_kind = event_kind
         self.event_attributes = event_attributes
         self.event_logger = event_logger
         self.token_usage_metric = token_usage_metric
@@ -85,19 +77,9 @@ def end(self, exc=None):
             _record_token_usage_metrics(self.token_usage_metric, self.span, self.usage)
 
         if self.capture_message_content:
-            if self.event_kind == "log":
-                _send_log_events_from_stream_choices(
-                    self.event_logger, choices=self.choices, span=self.span, attributes=self.event_attributes
-                )
-            elif self.span.is_recording():
-                # same format as the prompt
-                completion = [_message_from_stream_choices(self.choices)]
-                try:
-                    self.span.add_event(
-                        EVENT_GEN_AI_CONTENT_COMPLETION, attributes={GEN_AI_COMPLETION: json.dumps(completion)}
-                    )
-                except TypeError:
-                    logger.error(f"Failed to serialize {EVENT_GEN_AI_CONTENT_COMPLETION}")
+            _send_log_events_from_stream_choices(
+                self.event_logger, choices=self.choices, span=self.span, attributes=self.event_attributes
+            )
 
         self.span.end()