diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/__init__.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/__init__.py index a27b1bcf81..54407d27d9 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/__init__.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/__init__.py @@ -15,12 +15,16 @@ openai_attributes as OpenAIAttributes, ) from opentelemetry.semconv_ai import SpanAttributes +from opentelemetry.trace.status import Status, StatusCode from opentelemetry.trace.propagation import set_span_in_context from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator OPENAI_LLM_USAGE_TOKEN_TYPES = ["prompt_tokens", "completion_tokens"] PROMPT_FILTER_KEY = "prompt_filter_results" -PROMPT_ERROR = "prompt_error" +OPENAI_FINISH_REASON_MAP = { + "tool_calls": "tool_call", + "function_call": "tool_call", +} _PYDANTIC_VERSION = version("pydantic") @@ -48,11 +52,11 @@ def _set_client_attributes(span, instance): client = instance._client # pylint: disable=protected-access if isinstance(client, (openai.AsyncOpenAI, openai.OpenAI)): _set_span_attribute( - span, SpanAttributes.LLM_OPENAI_API_BASE, str(client.base_url) + span, SpanAttributes.GEN_AI_OPENAI_API_BASE, str(client.base_url) ) if isinstance(client, (openai.AsyncAzureOpenAI, openai.AzureOpenAI)): _set_span_attribute( - span, SpanAttributes.LLM_OPENAI_API_VERSION, client._api_version + span, SpanAttributes.GEN_AI_OPENAI_API_VERSION, client._api_version ) # pylint: disable=protected-access @@ -65,41 +69,69 @@ def _set_api_attributes(span): base_url = openai.base_url if hasattr(openai, "base_url") else openai.api_base - _set_span_attribute(span, SpanAttributes.LLM_OPENAI_API_BASE, base_url) - _set_span_attribute(span, SpanAttributes.LLM_OPENAI_API_TYPE, openai.api_type) - _set_span_attribute(span, SpanAttributes.LLM_OPENAI_API_VERSION, openai.api_version) + _set_span_attribute(span, SpanAttributes.GEN_AI_OPENAI_API_BASE, base_url) + _set_span_attribute(span, SpanAttributes.GEN_AI_OPENAI_API_TYPE, openai.api_type) + _set_span_attribute(span, SpanAttributes.GEN_AI_OPENAI_API_VERSION, openai.api_version) return +def _parse_arguments(raw_args): + """Best-effort parse of a JSON argument string to dict. Falls back to raw string.""" + if raw_args is None: + return None + if isinstance(raw_args, dict): + return raw_args + try: + return json.loads(raw_args) + except (json.JSONDecodeError, TypeError): + return raw_args + + +def _build_tool_def_dict(function_dict, tool_type=None): + """Build a tool definition dict matching OTel source system format.""" + tool_def = {} + t = tool_type or function_dict.get("type") + if t: + tool_def["type"] = t + if function_dict.get("name"): + tool_def["name"] = function_dict["name"] + if function_dict.get("description"): + tool_def["description"] = function_dict["description"] + if function_dict.get("parameters"): + tool_def["parameters"] = function_dict["parameters"] + return tool_def + + +def _set_tool_definitions_json(span, tool_defs): + """Set gen_ai.tool.definitions as a single JSON string attribute.""" + if tool_defs: + _set_span_attribute( + span, GenAIAttributes.GEN_AI_TOOL_DEFINITIONS, json.dumps(tool_defs) + ) + + def _set_functions_attributes(span, functions): if not functions: return - for i, function in enumerate(functions): - prefix = f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.{i}" - _set_span_attribute(span, f"{prefix}.name", function.get("name")) - _set_span_attribute(span, f"{prefix}.description", function.get("description")) - _set_span_attribute( - span, f"{prefix}.parameters", json.dumps(function.get("parameters")) - ) + tool_defs = [ + d for f in functions + if (d := _build_tool_def_dict(f, tool_type="function")) + ] + _set_tool_definitions_json(span, tool_defs) def set_tools_attributes(span, tools): if not tools: return - for i, tool in enumerate(tools): - function = tool.get("function") - if not function: - continue - - prefix = f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.{i}" - _set_span_attribute(span, f"{prefix}.name", function.get("name")) - _set_span_attribute(span, f"{prefix}.description", function.get("description")) - _set_span_attribute( - span, f"{prefix}.parameters", json.dumps(function.get("parameters")) - ) + tool_defs = [ + d for tool in tools + if tool.get("function") + and (d := _build_tool_def_dict(tool["function"], tool_type=tool.get("type"))) + ] + _set_tool_definitions_json(span, tool_defs) def _set_request_attributes(span, kwargs, instance=None): @@ -110,12 +142,12 @@ def _set_request_attributes(span, kwargs, instance=None): base_url = _get_openai_base_url(instance) if instance else "" vendor = _get_vendor_from_url(base_url) - _set_span_attribute(span, GenAIAttributes.GEN_AI_SYSTEM, vendor) + _set_span_attribute(span, GenAIAttributes.GEN_AI_PROVIDER_NAME, vendor) model = kwargs.get("model") - if vendor == "AWS" and model and "." in model: + if vendor == "aws.bedrock" and model and "." in model: model = _cross_region_check(model) - elif vendor == "OpenRouter": + elif vendor == "openrouter": model = _extract_model_name_from_provider_format(model) _set_span_attribute(span, GenAIAttributes.GEN_AI_REQUEST_MODEL, model) @@ -127,20 +159,17 @@ def _set_request_attributes(span, kwargs, instance=None): ) _set_span_attribute(span, GenAIAttributes.GEN_AI_REQUEST_TOP_P, kwargs.get("top_p")) _set_span_attribute( - span, SpanAttributes.LLM_FREQUENCY_PENALTY, kwargs.get("frequency_penalty") + span, GenAIAttributes.GEN_AI_REQUEST_FREQUENCY_PENALTY, kwargs.get("frequency_penalty") ) _set_span_attribute( - span, SpanAttributes.LLM_PRESENCE_PENALTY, kwargs.get("presence_penalty") + span, GenAIAttributes.GEN_AI_REQUEST_PRESENCE_PENALTY, kwargs.get("presence_penalty") ) - _set_span_attribute(span, SpanAttributes.LLM_USER, kwargs.get("user")) - _set_span_attribute(span, SpanAttributes.LLM_HEADERS, str(kwargs.get("headers"))) - # The new OpenAI SDK removed the `headers` and create new field called `extra_headers` - if kwargs.get("extra_headers") is not None: - _set_span_attribute( - span, SpanAttributes.LLM_HEADERS, str(kwargs.get("extra_headers")) - ) + _set_span_attribute(span, SpanAttributes.GEN_AI_USER, kwargs.get("user")) + headers = kwargs.get("extra_headers") or kwargs.get("headers") + if headers is not None: + _set_span_attribute(span, SpanAttributes.GEN_AI_HEADERS, str(headers)) _set_span_attribute( - span, SpanAttributes.LLM_IS_STREAMING, kwargs.get("stream") or False + span, SpanAttributes.GEN_AI_IS_STREAMING, kwargs.get("stream") or False ) _set_span_attribute( span, OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER, kwargs.get("service_tier") @@ -157,7 +186,7 @@ def _set_request_attributes(span, kwargs, instance=None): if schema: _set_span_attribute( span, - SpanAttributes.LLM_REQUEST_STRUCTURED_OUTPUT_SCHEMA, + SpanAttributes.GEN_AI_REQUEST_STRUCTURED_OUTPUT_SCHEMA, json.dumps(schema), ) elif ( @@ -169,7 +198,7 @@ def _set_request_attributes(span, kwargs, instance=None): ): _set_span_attribute( span, - SpanAttributes.LLM_REQUEST_STRUCTURED_OUTPUT_SCHEMA, + SpanAttributes.GEN_AI_REQUEST_STRUCTURED_OUTPUT_SCHEMA, json.dumps(response_format.model_json_schema()), ) else: @@ -185,7 +214,7 @@ def _set_request_attributes(span, kwargs, instance=None): if schema: _set_span_attribute( span, - SpanAttributes.LLM_REQUEST_STRUCTURED_OUTPUT_SCHEMA, + SpanAttributes.GEN_AI_REQUEST_STRUCTURED_OUTPUT_SCHEMA, schema, ) @@ -196,11 +225,13 @@ def _set_response_attributes(span, response): return if "error" in response: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}", - json.dumps(response.get("error")), - ) + error_data = response.get("error") + if isinstance(error_data, dict): + error_type = error_data.get("type") or error_data.get("code") or "api_error" + else: + error_type = "api_error" + _set_span_attribute(span, "error.type", error_type) + span.set_status(Status(StatusCode.ERROR, str(error_data))) return response_model = response.get("model") @@ -209,9 +240,22 @@ def _set_response_attributes(span, response): _set_span_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_MODEL, response_model) _set_span_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_ID, response.get("id")) + # Set gen_ai.response.finish_reasons (top-level, not gated by content opt-in) + choices = response.get("choices") + if choices: + finish_reasons = tuple( + OPENAI_FINISH_REASON_MAP.get(c.get("finish_reason"), c.get("finish_reason")) + for c in choices + if c.get("finish_reason") + ) + if finish_reasons: + _set_span_attribute( + span, GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS, finish_reasons + ) + _set_span_attribute( span, - SpanAttributes.LLM_OPENAI_RESPONSE_SYSTEM_FINGERPRINT, + GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SYSTEM_FINGERPRINT, response.get("system_fingerprint"), ) _set_span_attribute( @@ -228,7 +272,7 @@ def _set_response_attributes(span, response): usage = usage.__dict__ _set_span_attribute( - span, SpanAttributes.LLM_USAGE_TOTAL_TOKENS, usage.get("total_tokens") + span, SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS, usage.get("total_tokens") ) _set_span_attribute( span, @@ -241,7 +285,7 @@ def _set_response_attributes(span, response): prompt_tokens_details = dict(usage.get("prompt_tokens_details", {})) _set_span_attribute( span, - SpanAttributes.LLM_USAGE_CACHE_READ_INPUT_TOKENS, + SpanAttributes.GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS, prompt_tokens_details.get("cached_tokens", 0), ) return @@ -276,7 +320,7 @@ def _set_span_stream_usage(span, prompt_tokens, completion_tokens): ): _set_span_attribute( span, - SpanAttributes.LLM_USAGE_TOTAL_TOKENS, + SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS, completion_tokens + prompt_tokens, ) @@ -295,13 +339,13 @@ def _get_vendor_from_url(base_url): return "openai" if "openai.azure.com" in base_url: - return "Azure" + return "azure.ai.openai" elif "amazonaws.com" in base_url or "bedrock" in base_url: - return "AWS" + return "aws.bedrock" elif "googleapis.com" in base_url or "vertex" in base_url: - return "Google" + return "gcp.vertex_ai" elif "openrouter.ai" in base_url: - return "OpenRouter" + return "openrouter" return "openai" @@ -378,9 +422,9 @@ def metric_shared_attributes( return { **attributes, - GenAIAttributes.GEN_AI_SYSTEM: vendor, + GenAIAttributes.GEN_AI_PROVIDER_NAME: vendor, GenAIAttributes.GEN_AI_RESPONSE_MODEL: response_model, - "gen_ai.operation.name": operation, + GenAIAttributes.GEN_AI_OPERATION_NAME: operation, "server.address": server_address, "stream": is_streaming, } diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/chat_wrappers.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/chat_wrappers.py index 09c1908706..dd74fa2e81 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/chat_wrappers.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/chat_wrappers.py @@ -9,8 +9,10 @@ from opentelemetry import context as context_api import pydantic from opentelemetry.instrumentation.openai.shared import ( + OPENAI_FINISH_REASON_MAP, OPENAI_LLM_USAGE_TOKEN_TYPES, _get_openai_base_url, + _parse_arguments, _set_client_attributes, _set_functions_attributes, _set_request_attributes, @@ -45,9 +47,11 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) +from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import ( + GenAiOperationNameValues, +) from opentelemetry.semconv_ai import ( SUPPRESS_LANGUAGE_MODEL_INSTRUMENTATION_KEY, - LLMRequestTypeValues, SpanAttributes, ) from opentelemetry.trace import SpanKind, Tracer @@ -59,7 +63,7 @@ PROMPT_FILTER_KEY = "prompt_filter_results" CONTENT_FILTER_KEY = "content_filter_results" -LLM_REQUEST_TYPE = LLMRequestTypeValues.CHAT +OPERATION_NAME = GenAiOperationNameValues.CHAT logger = logging.getLogger(__name__) @@ -87,7 +91,7 @@ def chat_wrapper( span = tracer.start_span( SPAN_NAME, kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLM_REQUEST_TYPE.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: OPERATION_NAME.value}, ) # Use the span as current context to ensure events get proper trace context @@ -185,7 +189,7 @@ async def achat_wrapper( span = tracer.start_span( SPAN_NAME, kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLM_REQUEST_TYPE.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: OPERATION_NAME.value}, ) # Use the span as current context to ensure events get proper trace context @@ -292,8 +296,8 @@ async def _handle_request(span, kwargs, instance): reasoning_effort = kwargs.get("reasoning_effort") _set_span_attribute( span, - SpanAttributes.LLM_REQUEST_REASONING_EFFORT, - reasoning_effort or () + SpanAttributes.GEN_AI_REQUEST_REASONING_EFFORT, + reasoning_effort, ) @@ -345,8 +349,8 @@ def _handle_response( _set_span_attribute( span, - SpanAttributes.LLM_USAGE_REASONING_TOKENS, - reasoning_tokens or 0, + SpanAttributes.GEN_AI_USAGE_REASONING_TOKENS, + reasoning_tokens, ) if should_emit_events(): @@ -396,8 +400,9 @@ def _set_choice_counter_metrics(choice_counter, choices, shared_attributes): for choice in choices: attributes_with_reason = {**shared_attributes} if choice.get("finish_reason"): - attributes_with_reason[SpanAttributes.LLM_RESPONSE_FINISH_REASON] = ( - choice.get("finish_reason") + raw_reason = choice.get("finish_reason") + attributes_with_reason[SpanAttributes.GEN_AI_RESPONSE_FINISH_REASON] = ( + OPENAI_FINISH_REASON_MAP.get(raw_reason, raw_reason) ) choice_counter.add(1, attributes=attributes_with_reason) @@ -440,125 +445,170 @@ async def _process_image_item(item, trace_id, span_id, message_index, content_in @dont_throw async def _set_prompts(span, messages): + if Config.upload_base64_image and messages: + messages = await _preprocess_base64_images(span, messages) + _set_input_messages(span, messages) + + +async def _preprocess_base64_images(span, messages): + """Pre-process messages to upload base64 images before sync attribute setting.""" + import copy + processed = [] + for msg_idx, msg in enumerate(messages): + msg = model_as_dict(msg) + content = msg.get("content") + if not isinstance(content, list): + processed.append(msg) + continue + new_content = [] + for j, item in enumerate(content): + if _is_base64_image(item): + item = await _process_image_item( + copy.deepcopy(item), + span.context.trace_id, span.context.span_id, + msg_idx, j, + ) + new_content.append(item) + processed.append({**msg, "content": new_content}) + return processed + +def _map_content_block(block): + """Map an OpenAI content block to an OTel-compliant part.""" + if not isinstance(block, dict): + return block + block_type = block.get("type") + if block_type == "text": + return {"type": "text", "content": block.get("text", "")} + elif block_type == "image_url": + url = "" + image_url = block.get("image_url") + if isinstance(image_url, dict): + url = image_url.get("url", "") + if url.startswith("data:"): + # Parse data URI: data:;base64, + try: + header, content = url.split(",", 1) + mime_type = header.split(":", 1)[1].split(";", 1)[0] + except (ValueError, IndexError): + mime_type = "image/unknown" + content = url + return {"type": "blob", "modality": "image", "mime_type": mime_type, "content": content} + return {"type": "uri", "modality": "image", "uri": url} + # GenericPart: spread properties for unrecognized blocks + return {"type": block_type or "unknown", **{k: v for k, v in block.items() if k != "type"}} + +def _map_content_parts(content): + """Convert content to OTel parts list. Handles str, list, and None.""" + if isinstance(content, str): + return [{"content": content, "type": "text"}] + if isinstance(content, list): + return [_map_content_block(block) for block in content] + return content or [] + +def _set_input_messages(span, messages): if not span.is_recording() or messages is None: return - for i, msg in enumerate(messages): - prefix = f"{GenAIAttributes.GEN_AI_PROMPT}.{i}" - msg = msg if isinstance(msg, dict) else model_as_dict(msg) - - _set_span_attribute(span, f"{prefix}.role", msg.get("role")) - if msg.get("content"): - content = copy.deepcopy(msg.get("content")) - if isinstance(content, list): - content = [ - ( - await _process_image_item( - item, span.context.trace_id, span.context.span_id, i, j - ) - if _is_base64_image(item) - else item - ) - for j, item in enumerate(content) - ] - - content = json.dumps(content) - _set_span_attribute(span, f"{prefix}.content", content) - if msg.get("tool_call_id"): - _set_span_attribute( - span, f"{prefix}.tool_call_id", msg.get("tool_call_id")) - tool_calls = msg.get("tool_calls") - if tool_calls: - for i, tool_call in enumerate(tool_calls): - if is_openai_v1(): - tool_call = model_as_dict(tool_call) - - function = tool_call.get("function") - _set_span_attribute( - span, - f"{prefix}.tool_calls.{i}.id", - tool_call.get("id"), - ) - _set_span_attribute( - span, - f"{prefix}.tool_calls.{i}.name", - function.get("name"), - ) - _set_span_attribute( - span, - f"{prefix}.tool_calls.{i}.arguments", - function.get("arguments"), - ) - + attr_messages = [] + for msg in messages: + msg = model_as_dict(msg) + role = msg.get("role") + if role == "tool": + tool_call_id = msg.get("tool_call_id") + content = msg.get("content") + attr_messages.append({ + "role": role, + "parts": [{"type": "tool_call_response", "id": tool_call_id, "response": content}], + }) + elif role == "user": + content = msg.get("content") + parts = _map_content_parts(content) + attr_messages.append({ + "role": role, + "parts": parts, + }) + elif role in ["system", "developer"]: + content = msg.get("content") + parts = _map_content_parts(content) + attr_messages.append({ + "role": role, + "parts": parts, + }) + elif role == "assistant": + content = msg.get("content") + parts = _map_content_parts(content) + tool_calls = _parse_tool_calls(msg.get("tool_calls")) or [] + for tool_call in tool_calls: + parts.append({ + "type": "tool_call", + "name": tool_call["function"]["name"], + "id": tool_call["id"], + "arguments": _parse_arguments(tool_call["function"].get("arguments")), + }) + attr_messages.append({ + "role": "assistant", + "parts": parts, + }) + _set_span_attribute(span, GenAIAttributes.GEN_AI_INPUT_MESSAGES, json.dumps(attr_messages)) def _set_completions(span, choices): - if choices is None: - return - - for choice in choices: - index = choice.get("index") - prefix = f"{GenAIAttributes.GEN_AI_COMPLETION}.{index}" - _set_span_attribute( - span, f"{prefix}.finish_reason", choice.get("finish_reason") - ) + _set_output_messages(span, choices) - if choice.get("content_filter_results"): - _set_span_attribute( - span, - f"{prefix}.{CONTENT_FILTER_KEY}", - json.dumps(choice.get("content_filter_results")), - ) +def _map_finish_reason(reason): + if not reason: + return None + return OPENAI_FINISH_REASON_MAP.get(reason, reason) - if choice.get("finish_reason") == "content_filter": - _set_span_attribute(span, f"{prefix}.role", "assistant") - _set_span_attribute(span, f"{prefix}.content", "FILTERED") - - return +def _set_output_messages(span, choices): + if not span.is_recording() or choices is None: + return + messages = [] + for choice in choices: message = choice.get("message") - if not message: - return - - _set_span_attribute(span, f"{prefix}.role", message.get("role")) - - if message.get("refusal"): - _set_span_attribute( - span, f"{prefix}.refusal", message.get("refusal")) - else: - _set_span_attribute( - span, f"{prefix}.content", message.get("content")) - - function_call = message.get("function_call") - if function_call: - _set_span_attribute( - span, f"{prefix}.tool_calls.0.name", function_call.get("name") - ) - _set_span_attribute( - span, - f"{prefix}.tool_calls.0.arguments", - function_call.get("arguments"), - ) - - tool_calls = message.get("tool_calls") - if tool_calls: - for i, tool_call in enumerate(tool_calls): - function = tool_call.get("function") - _set_span_attribute( - span, - f"{prefix}.tool_calls.{i}.id", - tool_call.get("id"), - ) - _set_span_attribute( - span, - f"{prefix}.tool_calls.{i}.name", - function.get("name"), - ) - _set_span_attribute( - span, - f"{prefix}.tool_calls.{i}.arguments", - function.get("arguments"), - ) - + content_filter_results = choice.get("content_filter_results") + if not message and not content_filter_results: + continue + parts = [] + if message: + content = message.get("content") + parts = _map_content_parts(content) + refusal = message.get("refusal") + if refusal: + parts.append({"type": "refusal", "content": refusal}) + reasoning_content = message.get("reasoning_content") + if reasoning_content: + parts.append({"type": "reasoning", "content": reasoning_content}) + tool_calls = _parse_tool_calls(message.get("tool_calls")) or [] + for tool_call in tool_calls: + parts.append({ + "type": "tool_call", + "name": tool_call["function"]["name"], + "id": tool_call["id"], + "arguments": _parse_arguments(tool_call["function"].get("arguments")), + }) + # Handle legacy function_call API (not tool_calls) + function_call = message.get("function_call") + if function_call: + if isinstance(function_call, dict): + fc_name = function_call.get("name") + fc_args = function_call.get("arguments") + else: + # pydantic model + fc_dict = model_as_dict(function_call) + fc_name = fc_dict.get("name") + fc_args = fc_dict.get("arguments") + parts.append({ + "type": "tool_call", + "name": fc_name, + "arguments": _parse_arguments(fc_args), + }) + fr = _map_finish_reason(choice.get("finish_reason")) or "stop" + entry = {"role": "assistant", "parts": parts, "finish_reason": fr} + if content_filter_results: + entry["content_filter_results"] = content_filter_results + messages.append(entry) + _set_span_attribute(span, GenAIAttributes.GEN_AI_OUTPUT_MESSAGES, json.dumps(messages)) @dont_throw def _set_streaming_token_metrics( @@ -714,7 +764,7 @@ async def __anext__(self): def _process_item(self, item): self._span.add_event( - name=f"{SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK}") + name=SpanAttributes.GEN_AI_CONTENT_COMPLETION_CHUNK) if self._first_token and self._streaming_time_to_first_token: self._time_of_first_token = time.time() @@ -834,6 +884,11 @@ def _record_partial_metrics(self): if self._span and self._span.is_recording(): _set_response_attributes(self._span, self._complete_response) + # Set output messages for partial streams (parity with happy path) + if should_send_prompts() and not should_emit_events(): + _set_completions( + self._span, self._complete_response.get("choices")) + # Record partial token metrics if we have any data if self._complete_response.get("choices") or self._request_kwargs: _set_streaming_token_metrics( @@ -875,7 +930,7 @@ def _build_from_streaming_response( time_of_first_token = start_time # will be updated when first token is received for item in response: - span.add_event(name=f"{SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK}") + span.add_event(name=SpanAttributes.GEN_AI_CONTENT_COMPLETION_CHUNK) item_to_yield = item @@ -946,7 +1001,7 @@ async def _abuild_from_streaming_response( time_of_first_token = start_time # will be updated when first token is received async for item in response: - span.add_event(name=f"{SpanAttributes.LLM_CONTENT_COMPLETION_CHUNK}") + span.add_event(name=SpanAttributes.GEN_AI_CONTENT_COMPLETION_CHUNK) item_to_yield = item @@ -1162,6 +1217,11 @@ def _accumulate_stream_items(item, complete_response): if delta and delta.get("content"): complete_choice["message"]["content"] += delta.get("content") + if delta and delta.get("reasoning_content"): + if "reasoning_content" not in complete_choice["message"]: + complete_choice["message"]["reasoning_content"] = "" + complete_choice["message"]["reasoning_content"] += delta.get("reasoning_content") + if delta and delta.get("role"): complete_choice["message"]["role"] = delta.get("role") if delta and delta.get("tool_calls"): diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/completion_wrappers.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/completion_wrappers.py index 08baf1ed11..2f9fe915be 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/completion_wrappers.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/completion_wrappers.py @@ -1,3 +1,4 @@ +import json import logging from opentelemetry import context as context_api @@ -14,6 +15,7 @@ propagate_trace_context, ) from opentelemetry.instrumentation.openai.shared.config import Config +from opentelemetry.instrumentation.openai.shared.chat_wrappers import _map_finish_reason from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE from opentelemetry.instrumentation.openai.shared.event_emitter import emit_event from opentelemetry.instrumentation.openai.shared.event_models import ( @@ -31,16 +33,17 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) +from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import ( + GenAiOperationNameValues, +) from opentelemetry.semconv_ai import ( SUPPRESS_LANGUAGE_MODEL_INSTRUMENTATION_KEY, - LLMRequestTypeValues, - SpanAttributes, ) from opentelemetry.trace import SpanKind from opentelemetry.trace.status import Status, StatusCode SPAN_NAME = "openai.completion" -LLM_REQUEST_TYPE = LLMRequestTypeValues.COMPLETION +OPERATION_NAME = GenAiOperationNameValues.TEXT_COMPLETION logger = logging.getLogger(__name__) @@ -56,7 +59,7 @@ def completion_wrapper(tracer, wrapped, instance, args, kwargs): span = tracer.start_span( SPAN_NAME, kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLM_REQUEST_TYPE.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: OPERATION_NAME.value}, ) # Use the span as current context to ensure events get proper trace context @@ -92,7 +95,7 @@ async def acompletion_wrapper(tracer, wrapped, instance, args, kwargs): span = tracer.start_span( name=SPAN_NAME, kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLM_REQUEST_TYPE.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: OPERATION_NAME.value}, ) # Use the span as current context to ensure events get proper trace context @@ -158,28 +161,47 @@ def _handle_response(response, span, instance=None): def _set_prompts(span, prompt): - if not span.is_recording() or not prompt: + _set_input_messages(span, prompt) + +def _set_input_messages(span, prompt): + if not span.is_recording() or prompt is None: return + prompts = prompt if isinstance(prompt, list) else [prompt] + + messages = [ + {"role": "user", "parts": [{"content": p, "type": "text"}]} + for p in prompts + ] _set_span_attribute( span, - f"{GenAIAttributes.GEN_AI_PROMPT}.0.user", - prompt[0] if isinstance(prompt, list) else prompt, + GenAIAttributes.GEN_AI_INPUT_MESSAGES, + json.dumps(messages), ) - @dont_throw def _set_completions(span, choices): + _set_output_messages(span, choices) + + +def _set_output_messages(span, choices): if not span.is_recording() or not choices: return + messages = [] for choice in choices: - index = choice.get("index") - prefix = f"{GenAIAttributes.GEN_AI_COMPLETION}.{index}" - _set_span_attribute( - span, f"{prefix}.finish_reason", choice.get("finish_reason") - ) - _set_span_attribute(span, f"{prefix}.content", choice.get("text")) + fr = _map_finish_reason(choice.get("finish_reason")) or "stop" + entry = { + "role": "assistant", + "parts": [{"content": choice.get("text"), "type": "text"}], + "finish_reason": fr, + } + messages.append(entry) + _set_span_attribute( + span, + GenAIAttributes.GEN_AI_OUTPUT_MESSAGES, + json.dumps(messages), + ) @dont_throw diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/embeddings_wrappers.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/embeddings_wrappers.py index 855e883a68..7899095f8a 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/embeddings_wrappers.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/embeddings_wrappers.py @@ -1,3 +1,4 @@ +import json import logging import time from collections.abc import Iterable @@ -35,10 +36,11 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) +from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import ( + GenAiOperationNameValues, +) from opentelemetry.semconv_ai import ( SUPPRESS_LANGUAGE_MODEL_INSTRUMENTATION_KEY, - LLMRequestTypeValues, - SpanAttributes, ) from opentelemetry.trace import SpanKind, Status, StatusCode @@ -46,7 +48,7 @@ from openai.types.create_embedding_response import CreateEmbeddingResponse SPAN_NAME = "openai.embeddings" -LLM_REQUEST_TYPE = LLMRequestTypeValues.EMBEDDING +OPERATION_NAME = GenAiOperationNameValues.EMBEDDINGS logger = logging.getLogger(__name__) @@ -71,7 +73,7 @@ def embeddings_wrapper( with tracer.start_as_current_span( name=SPAN_NAME, kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLM_REQUEST_TYPE.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: OPERATION_NAME.value}, ) as span: _handle_request(span, kwargs, instance) @@ -136,7 +138,7 @@ async def aembeddings_wrapper( tracer=tracer, name=SPAN_NAME, kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLM_REQUEST_TYPE.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: OPERATION_NAME.value}, ) as span: _handle_request(span, kwargs, instance) @@ -271,15 +273,16 @@ def _set_prompts(span, prompt): if not span.is_recording() or not prompt: return - if isinstance(prompt, list): - for i, p in enumerate(prompt): - _set_span_attribute(span, f"{GenAIAttributes.GEN_AI_PROMPT}.{i}.content", p) - else: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.0.content", - prompt, - ) + prompts = prompt if isinstance(prompt, list) else [prompt] + messages = [ + {"role": "user", "parts": [{"type": "text", "content": p}]} + for p in prompts + ] + _set_span_attribute( + span, + GenAIAttributes.GEN_AI_INPUT_MESSAGES, + json.dumps(messages), + ) def _emit_embeddings_message_event(embeddings) -> None: diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_emitter.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_emitter.py index 67ffcb0b5e..50212f29b0 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_emitter.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_emitter.py @@ -29,7 +29,7 @@ class Roles(Enum): """The valid roles for naming the message event.""" EVENT_ATTRIBUTES = { - GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiSystemValues.OPENAI.value + GenAIAttributes.GEN_AI_PROVIDER_NAME: GenAIAttributes.GenAiSystemValues.OPENAI.value } """The attributes to be used for the event.""" diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_models.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_models.py index e3b5f3cc60..d9e76a1eed 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_models.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/shared/event_models.py @@ -1,10 +1,12 @@ from dataclasses import dataclass from typing import Any, List, Literal, Optional, TypedDict +from typing_extensions import NotRequired + class _FunctionToolCall(TypedDict): - function_name: str - arguments: Optional[dict[str, Any]] + name: str + arguments: NotRequired[Optional[str]] class ToolCall(TypedDict): diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/assistant_wrappers.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/assistant_wrappers.py index 550f05632d..07e5cb7ae2 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/assistant_wrappers.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/assistant_wrappers.py @@ -1,3 +1,4 @@ +import json import logging import time @@ -23,7 +24,7 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) -from opentelemetry.semconv_ai import LLMRequestTypeValues, SpanAttributes +from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import GenAiOperationNameValues from opentelemetry.trace import SpanKind, Status, StatusCode from openai._legacy_response import LegacyAPIResponse @@ -128,7 +129,7 @@ def messages_list_wrapper(tracer, wrapped, instance, args, kwargs): span = tracer.start_span( "openai.assistant.run", kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLMRequestTypeValues.CHAT.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: GenAiOperationNameValues.CHAT.value}, start_time=run.get("start_time"), ) @@ -141,7 +142,9 @@ def messages_list_wrapper(tracer, wrapped, instance, args, kwargs): span.end() return response - prompt_index = 0 + input_msgs = [] + output_msgs = [] + completion_index = 0 if assistants.get(run["assistant_id"]) is not None or Config.enrich_assistant: if Config.enrich_assistant: assistant = model_as_dict( @@ -153,7 +156,7 @@ def messages_list_wrapper(tracer, wrapped, instance, args, kwargs): _set_span_attribute( span, - GenAIAttributes.GEN_AI_SYSTEM, + GenAIAttributes.GEN_AI_PROVIDER_NAME, "openai", ) _set_span_attribute( @@ -169,49 +172,31 @@ def messages_list_wrapper(tracer, wrapped, instance, args, kwargs): if should_emit_events(): emit_event(MessageEvent(content=assistant["instructions"], role="system")) else: - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", "system" - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - assistant["instructions"], - ) - prompt_index += 1 - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", "system" - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - run["instructions"], - ) + input_msgs.append({ + "role": "system", + "parts": [{"type": "text", "content": assistant["instructions"]}], + }) + if should_emit_events(): emit_event(MessageEvent(content=run["instructions"], role="system")) - prompt_index += 1 + else: + input_msgs.append({ + "role": "system", + "parts": [{"type": "text", "content": run["instructions"]}], + }) - completion_index = 0 for msg in messages: - prefix = f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}" content = msg.get("content") - message_content = content[0].get("text").get("value") message_role = msg.get("role") if message_role in ["user", "system"]: if should_emit_events(): emit_event(MessageEvent(content=message_content, role=message_role)) else: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", - message_role, - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - message_content, - ) - prompt_index += 1 + input_msgs.append({ + "role": message_role, + "parts": [{"type": "text", "content": message_content}], + }) else: if should_emit_events(): emit_event( @@ -221,24 +206,36 @@ def messages_list_wrapper(tracer, wrapped, instance, args, kwargs): ) ) else: - _set_span_attribute(span, f"{prefix}.role", msg.get("role")) - _set_span_attribute(span, f"{prefix}.content", message_content) + output_msgs.append({ + "role": message_role, + "parts": [{"type": "text", "content": message_content}], + }) _set_span_attribute( span, f"gen_ai.response.{completion_index}.id", msg.get("id") ) completion_index += 1 + if not should_emit_events(): + if input_msgs: + _set_span_attribute( + span, GenAIAttributes.GEN_AI_INPUT_MESSAGES, json.dumps(input_msgs) + ) + if output_msgs: + _set_span_attribute( + span, GenAIAttributes.GEN_AI_OUTPUT_MESSAGES, json.dumps(output_msgs) + ) + if run.get("usage"): usage_dict = model_as_dict(run.get("usage")) _set_span_attribute( span, GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS, - usage_dict.get("completion_tokens"), + usage_dict.get("prompt_tokens"), ) _set_span_attribute( span, GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS, - usage_dict.get("prompt_tokens"), + usage_dict.get("completion_tokens"), ) span.end(run.get("end_time")) @@ -257,12 +254,12 @@ def runs_create_and_stream_wrapper(tracer, wrapped, instance, args, kwargs): span = tracer.start_span( "openai.assistant.run_stream", kind=SpanKind.CLIENT, - attributes={SpanAttributes.LLM_REQUEST_TYPE: LLMRequestTypeValues.CHAT.value}, + attributes={GenAIAttributes.GEN_AI_OPERATION_NAME: GenAiOperationNameValues.CHAT.value}, ) # Use the span as current context to ensure events get proper trace context with trace.use_span(span, end_on_exit=False): - i = 0 + input_msgs = [] if assistants.get(assistant_id) is not None or Config.enrich_assistant: if Config.enrich_assistant: assistant = model_as_dict( @@ -277,7 +274,7 @@ def runs_create_and_stream_wrapper(tracer, wrapped, instance, args, kwargs): ) _set_span_attribute( span, - GenAIAttributes.GEN_AI_SYSTEM, + GenAIAttributes.GEN_AI_PROVIDER_NAME, "openai", ) _set_span_attribute( @@ -292,21 +289,20 @@ def runs_create_and_stream_wrapper(tracer, wrapped, instance, args, kwargs): ) ) else: - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{i}.role", "system" - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{i}.content", - assistants[assistant_id]["instructions"], - ) - i += 1 + input_msgs.append({ + "role": "system", + "parts": [{"type": "text", "content": assistants[assistant_id]["instructions"]}], + }) if should_emit_events(): emit_event(MessageEvent(content=instructions, role="system")) else: - _set_span_attribute(span, f"{GenAIAttributes.GEN_AI_PROMPT}.{i}.role", "system") + input_msgs.append({ + "role": "system", + "parts": [{"type": "text", "content": instructions}], + }) + if not should_emit_events() and input_msgs: _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{i}.content", instructions + span, GenAIAttributes.GEN_AI_INPUT_MESSAGES, json.dumps(input_msgs) ) from opentelemetry.instrumentation.openai.v1.event_handler_wrapper import ( diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/event_handler_wrapper.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/event_handler_wrapper.py index 7b58b21a8e..1eb9acc173 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/event_handler_wrapper.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/event_handler_wrapper.py @@ -1,3 +1,5 @@ +import json + from opentelemetry.instrumentation.openai.shared import _set_span_attribute from opentelemetry.instrumentation.openai.shared.event_emitter import emit_event from opentelemetry.instrumentation.openai.shared.event_models import ChoiceEvent @@ -21,6 +23,7 @@ def __init__(self, original_handler, span): super().__init__() self._original_handler = original_handler self._span = span + self._output_messages = [] @override def on_end(self): @@ -34,6 +37,12 @@ def on_end(self): GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS, self._completion_tokens, ) + if not should_emit_events() and self._output_messages: + _set_span_attribute( + self._span, + GenAIAttributes.GEN_AI_OUTPUT_MESSAGES, + json.dumps(self._output_messages), + ) self._original_handler.on_end() self._span.end() @@ -118,16 +127,10 @@ def on_text_delta(self, delta, snapshot): def on_text_done(self, text): self._original_handler.on_text_done(text) if not should_emit_events(): - _set_span_attribute( - self._span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.{self._current_text_index}.role", - "assistant", - ) - _set_span_attribute( - self._span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.{self._current_text_index}.content", - text.value, - ) + self._output_messages.append({ + "role": "assistant", + "parts": [{"type": "text", "content": text.value}], + }) @override def on_image_file_done(self, image_file): diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/realtime_wrappers.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/realtime_wrappers.py index 7c009a3132..fe406b6e97 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/realtime_wrappers.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/realtime_wrappers.py @@ -23,10 +23,14 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) +from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import ( + GenAiOperationNameValues, +) from opentelemetry.semconv_ai import SpanAttributes from opentelemetry.trace import SpanKind, Status, StatusCode, Tracer from opentelemetry.instrumentation.openai.shared import ( + _parse_arguments, _set_span_attribute, model_as_dict, ) @@ -119,11 +123,11 @@ def handle_session_updated(self, event): self._state.session_config.update(session_dict) if self._state.session_span and self._state.session_span.is_recording(): - if hasattr(session, "modalities"): + if hasattr(session, "modalities") and session.modalities: _set_span_attribute( self._state.session_span, - f"{SpanAttributes.LLM_REQUEST_TYPE}.modalities", - json.dumps(session.modalities) if session.modalities else None, + GenAIAttributes.GEN_AI_OUTPUT_TYPE, + json.dumps(session.modalities), ) if hasattr(session, "temperature") and session.temperature is not None: _set_span_attribute( @@ -199,68 +203,43 @@ def handle_response_done(self, event): ) _set_span_attribute( span, - SpanAttributes.LLM_USAGE_TOTAL_TOKENS, + SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS, total, ) - # Set output content if tracing is enabled + # Build output message in OTel JSON format + parts = [] + if self._state.accumulated_text: + parts.append({"type": "text", "content": self._state.accumulated_text}) + elif self._state.accumulated_audio_transcript: + parts.append({"type": "text", "content": self._state.accumulated_audio_transcript}) + + if self._state.function_calls: + finish_reason = "tool_call" + for call in self._state.function_calls: + parts.append({ + "type": "tool_call", + "name": call.get("name"), + "id": call.get("call_id"), + "arguments": _parse_arguments(call.get("arguments")), + }) + else: + finish_reason = "stop" + + _set_span_attribute( + span, + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS, + (finish_reason,), + ) + if should_send_prompts(): - # Always set role for completions + output_messages = [{"role": "assistant", "parts": parts, "finish_reason": finish_reason}] _set_span_attribute( span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.role", - "assistant", + GenAIAttributes.GEN_AI_OUTPUT_MESSAGES, + json.dumps(output_messages), ) - # Set content (text or audio transcript) - if self._state.accumulated_text: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content", - self._state.accumulated_text, - ) - elif self._state.accumulated_audio_transcript: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content", - self._state.accumulated_audio_transcript, - ) - - # Set tool calls and finish_reason - if self._state.function_calls: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.finish_reason", - "tool_calls", - ) - for i, call in enumerate(self._state.function_calls): - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{i}.type", - "function", - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{i}.name", - call.get("name"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{i}.id", - call.get("call_id"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{i}.arguments", - call.get("arguments"), - ) - else: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.finish_reason", - "stop", - ) - span.set_status(Status(StatusCode.OK)) span.end() @@ -302,7 +281,7 @@ def start_response_span(self, end_existing: bool = False, set_input: bool = Fals if self._state.response_span.is_recording(): _set_span_attribute( self._state.response_span, - GenAIAttributes.GEN_AI_SYSTEM, + GenAIAttributes.GEN_AI_PROVIDER_NAME, "openai", ) _set_span_attribute( @@ -312,21 +291,20 @@ def start_response_span(self, end_existing: bool = False, set_input: bool = Fals ) _set_span_attribute( self._state.response_span, - SpanAttributes.LLM_REQUEST_TYPE, - "realtime", + GenAIAttributes.GEN_AI_OPERATION_NAME, + GenAiOperationNameValues.CHAT.value, ) # Set input if available and requested if set_input and should_send_prompts() and self._state.input_text: + input_messages = [{ + "role": "user", + "parts": [{"type": "text", "content": self._state.input_text}], + }] _set_span_attribute( self._state.response_span, - f"{GenAIAttributes.GEN_AI_PROMPT}.0.content", - self._state.input_text, - ) - _set_span_attribute( - self._state.response_span, - f"{GenAIAttributes.GEN_AI_PROMPT}.0.role", - "user", + GenAIAttributes.GEN_AI_INPUT_MESSAGES, + json.dumps(input_messages), ) def reset_response_state(self): @@ -537,10 +515,13 @@ async def update(self, **kwargs): session_config["temperature"], ) if "instructions" in session_config: + instructions_parts = json.dumps([ + {"type": "text", "content": session_config["instructions"]} + ]) _set_span_attribute( self._state.session_span, GenAIAttributes.GEN_AI_SYSTEM_INSTRUCTIONS, - session_config["instructions"], + instructions_parts, ) return result @@ -668,7 +649,7 @@ async def __aenter__(self): if self._state.session_span.is_recording(): _set_span_attribute( self._state.session_span, - GenAIAttributes.GEN_AI_SYSTEM, + GenAIAttributes.GEN_AI_PROVIDER_NAME, "openai", ) _set_span_attribute( @@ -678,8 +659,8 @@ async def __aenter__(self): ) _set_span_attribute( self._state.session_span, - SpanAttributes.LLM_REQUEST_TYPE, - "realtime", + GenAIAttributes.GEN_AI_OPERATION_NAME, + GenAiOperationNameValues.CHAT.value, ) # Enter the underlying connection manager diff --git a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/responses_wrappers.py b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/responses_wrappers.py index ac629c0dbc..ec0d245add 100644 --- a/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/responses_wrappers.py +++ b/packages/opentelemetry-instrumentation-openai/opentelemetry/instrumentation/openai/v1/responses_wrappers.py @@ -20,11 +20,15 @@ from wrapt import ObjectProxy from opentelemetry.instrumentation.openai.shared import ( + _build_tool_def_dict, _extract_model_name_from_provider_format, + _parse_arguments, _set_request_attributes, _set_span_attribute, + _set_tool_definitions_json, model_as_dict, ) + from opentelemetry.instrumentation.openai.utils import ( _with_tracer_wrapper, dont_throw, @@ -216,17 +220,17 @@ def get_tools_from_kwargs(kwargs: dict) -> list[ToolParam]: def process_content_block( block: dict[str, Any], ) -> dict[str, Any]: - # TODO: keep the original type once backend supports it - if block.get("type") in ["text", "input_text", "output_text"]: + block_type = block.get("type") + if block_type in ["text", "input_text", "output_text"]: return {"type": "text", "text": block.get("text")} - elif block.get("type") in ["image", "input_image", "output_image"]: + elif block_type in ["image", "input_image", "output_image"]: return { "type": "image", "image_url": block.get("image_url"), "detail": block.get("detail"), "file_id": block.get("file_id"), } - elif block.get("type") in ["file", "input_file", "output_file"]: + elif block_type in ["file", "input_file", "output_file"]: return { "type": "file", "file_id": block.get("file_id"), @@ -251,7 +255,124 @@ def prepare_kwargs_for_shared_attributes(kwargs): return prepared_kwargs +def _set_responses_json_messages(traced_response: TracedData, span: Span): + """Set gen_ai.input.messages and gen_ai.output.messages as JSON.""" + # Build input messages + input_messages = [] + if traced_response.instructions: + input_messages.append({ + "role": "system", + "parts": [{"type": "text", "content": traced_response.instructions}], + }) + if isinstance(traced_response.input, str): + input_messages.append({ + "role": "user", + "parts": [{"type": "text", "content": traced_response.input}], + }) + elif traced_response.input: + for block in traced_response.input: + block_dict = model_as_dict(block) + block_type = block_dict.get("type", "message") + if block_type == "message": + content = block_dict.get("content") + if is_validator_iterator(content): + content = [process_content_block(b) for b in content] + parts = [] + if isinstance(content, str): + parts.append({"type": "text", "content": content}) + elif isinstance(content, list): + for item in content: + if isinstance(item, dict): + item_type = item.get("type", "") + if item_type in ("text", "input_text", "output_text"): + parts.append({"type": "text", "content": item.get("text", "")}) + elif item_type in ("image", "input_image", "output_image"): + if item.get("image_url"): + parts.append({"type": "uri", "modality": "image", "uri": item.get("image_url")}) + elif item.get("file_id"): + parts.append({"type": "file", "modality": "image", "file_id": item.get("file_id")}) + elif item_type in ("file", "input_file", "output_file"): + parts.append({ + "type": "file", + "file_id": item.get("file_id"), + "filename": item.get("filename"), + }) + else: + # GenericPart for unrecognized types — preserve type, wrap content + parts.append({"type": item_type or "unknown", "content": item}) + else: + parts.append({"type": "text", "content": str(item)}) + input_messages.append({ + "role": block_dict.get("role", "user"), + "parts": parts, + }) + elif block_type == "function_call": + input_messages.append({ + "role": "assistant", + "parts": [{ + "type": "tool_call", + "name": block_dict.get("name"), + "id": block_dict.get("id") or block_dict.get("call_id"), + "arguments": _parse_arguments(block_dict.get("arguments")), + }], + }) + elif block_type == "function_call_output": + input_messages.append({ + "role": "tool", + "parts": [{ + "type": "tool_call_response", + "id": block_dict.get("call_id"), + "response": block_dict.get("output", ""), + }], + }) + + _set_span_attribute(span, GenAIAttributes.GEN_AI_INPUT_MESSAGES, json.dumps(input_messages)) + + # Build output messages + output_messages = [] + if traced_response.output_blocks: + parts = [] + if traced_response.output_text: + parts.append({"type": "text", "content": traced_response.output_text}) + for block in traced_response.output_blocks.values(): + block_dict = model_as_dict(block) + block_type = block_dict.get("type") + if block_type == "function_call": + parts.append({ + "type": "tool_call", + "name": block_dict.get("name"), + "id": block_dict.get("id"), + "arguments": _parse_arguments(block_dict.get("arguments")), + }) + elif block_type == "reasoning": + summary = block_dict.get("summary") + if summary is not None and summary != []: + if isinstance(summary, (dict, list)): + parts.append({"type": "reasoning", "content": json.dumps(summary)}) + else: + parts.append({"type": "reasoning", "content": summary}) + if parts: + has_tool_call = any(p.get("type") == "tool_call" for p in parts) + finish_reason = "tool_call" if has_tool_call else "stop" + output_messages.append({ + "role": "assistant", + "parts": parts, + "finish_reason": finish_reason, + }) + + _set_span_attribute(span, GenAIAttributes.GEN_AI_OUTPUT_MESSAGES, json.dumps(output_messages)) + + # Tool definitions as JSON + if traced_response.tools: + tool_defs = [ + d for tp in traced_response.tools + if (d := _build_tool_def_dict(model_as_dict(tp))) + ] + _set_tool_definitions_json(span, tool_defs) + + def set_data_attributes(traced_response: TracedData, span: Span): + _set_span_attribute(span, GenAIAttributes.GEN_AI_OPERATION_NAME, "chat") _set_span_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_ID, traced_response.response_id) response_model = _extract_model_name_from_provider_format(traced_response.response_model) @@ -261,13 +382,12 @@ def set_data_attributes(traced_response: TracedData, span: Span): if usage := traced_response.usage: _set_span_attribute(span, GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS, usage.input_tokens) _set_span_attribute(span, GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS, usage.output_tokens) - _set_span_attribute( - span, SpanAttributes.LLM_USAGE_TOTAL_TOKENS, usage.total_tokens - ) + _set_span_attribute(span, SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS, usage.total_tokens) + if usage.input_tokens_details: _set_span_attribute( span, - SpanAttributes.LLM_USAGE_CACHE_READ_INPUT_TOKENS, + SpanAttributes.GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS, usage.input_tokens_details.cached_tokens, ) @@ -276,220 +396,52 @@ def set_data_attributes(traced_response: TracedData, span: Span): usage.get("output_tokens_details") if isinstance(usage, dict) else getattr(usage, "output_tokens_details", None) ) - if tokens_details: reasoning_tokens = ( - tokens_details.get("reasoning_tokens", None) if isinstance(tokens_details, dict) + tokens_details.get("reasoning_tokens") if isinstance(tokens_details, dict) else getattr(tokens_details, "reasoning_tokens", None) ) - - _set_span_attribute( - span, - SpanAttributes.LLM_USAGE_REASONING_TOKENS, - reasoning_tokens or 0, - ) + _set_span_attribute(span, SpanAttributes.GEN_AI_USAGE_REASONING_TOKENS, reasoning_tokens) _set_span_attribute( span, - f"{SpanAttributes.LLM_REQUEST_REASONING_SUMMARY}", - traced_response.request_reasoning_summary or (), + SpanAttributes.GEN_AI_REQUEST_REASONING_SUMMARY, + traced_response.request_reasoning_summary, ) _set_span_attribute( span, - f"{SpanAttributes.LLM_REQUEST_REASONING_EFFORT}", - traced_response.request_reasoning_effort or (), + SpanAttributes.GEN_AI_REQUEST_REASONING_EFFORT, + traced_response.request_reasoning_effort, ) _set_span_attribute( span, - f"{SpanAttributes.LLM_RESPONSE_REASONING_EFFORT}", - traced_response.response_reasoning_effort or (), + SpanAttributes.GEN_AI_RESPONSE_REASONING_EFFORT, + traced_response.response_reasoning_effort, ) - if should_send_prompts(): - prompt_index = 0 - if traced_response.tools: - for i, tool_param in enumerate(traced_response.tools): - tool_dict = model_as_dict(tool_param) - description = tool_dict.get("description") - parameters = tool_dict.get("parameters") - name = tool_dict.get("name") - if parameters is None: - continue - _set_span_attribute( - span, - f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.{i}.description", - description, - ) - _set_span_attribute( - span, - f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.{i}.parameters", - json.dumps(parameters), - ) - _set_span_attribute( - span, - f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.{i}.name", - name, - ) - if traced_response.instructions: + # P1-2: Derive finish_reasons from output blocks + if traced_response.output_blocks: + finish_reasons = [] + has_tool_call = False + for block in traced_response.output_blocks.values(): + block_dict = model_as_dict(block) + block_type = block_dict.get("type") + if block_type == "message": + finish_reasons.append("stop") + elif block_type in ("function_call", "file_search_call", "web_search_call", + "computer_call", "code_interpreter_call"): + has_tool_call = True + if has_tool_call: + finish_reasons.append("tool_call") + if finish_reasons: _set_span_attribute( span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - traced_response.instructions, + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS, + tuple(finish_reasons), ) - _set_span_attribute(span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", "system") - prompt_index += 1 - - if isinstance(traced_response.input, str): - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", traced_response.input - ) - _set_span_attribute(span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", "user") - prompt_index += 1 - else: - for block in traced_response.input: - block_dict = model_as_dict(block) - if block_dict.get("type", "message") == "message": - content = block_dict.get("content") - if is_validator_iterator(content): - # we're after the actual call here, so we can consume the iterator - content = [process_content_block(block) for block in content] - try: - stringified_content = ( - content if isinstance(content, str) else json.dumps(content) - ) - except Exception: - stringified_content = ( - str(content) if content is not None else "" - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - stringified_content, - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", - block_dict.get("role"), - ) - prompt_index += 1 - elif block_dict.get("type") == "computer_call_output": - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", "computer-call" - ) - output_image_url = block_dict.get("output", {}).get("image_url") - if output_image_url: - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - json.dumps( - [ - { - "type": "image_url", - "image_url": {"url": output_image_url}, - } - ] - ), - ) - prompt_index += 1 - elif block_dict.get("type") == "computer_call": - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.role", "assistant" - ) - call_content = {} - if block_dict.get("id"): - call_content["id"] = block_dict.get("id") - if block_dict.get("call_id"): - call_content["call_id"] = block_dict.get("call_id") - if block_dict.get("action"): - call_content["action"] = block_dict.get("action") - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_PROMPT}.{prompt_index}.content", - json.dumps(call_content), - ) - prompt_index += 1 - # TODO: handle other block types - _set_span_attribute(span, f"{GenAIAttributes.GEN_AI_COMPLETION}.0.role", "assistant") - if traced_response.output_text: - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content", traced_response.output_text - ) - tool_call_index = 0 - for block in traced_response.output_blocks.values(): - block_dict = model_as_dict(block) - if block_dict.get("type") == "message": - # either a refusal or handled in output_text above - continue - if block_dict.get("type") == "function_call": - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.id", - block_dict.get("id"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.name", - block_dict.get("name"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.arguments", - block_dict.get("arguments"), - ) - tool_call_index += 1 - elif block_dict.get("type") == "file_search_call": - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.id", - block_dict.get("id"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.name", - "file_search_call", - ) - tool_call_index += 1 - elif block_dict.get("type") == "web_search_call": - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.id", - block_dict.get("id"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.name", - "web_search_call", - ) - tool_call_index += 1 - elif block_dict.get("type") == "computer_call": - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.id", - block_dict.get("call_id"), - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.name", - "computer_call", - ) - _set_span_attribute( - span, - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.{tool_call_index}.arguments", - json.dumps(block_dict.get("action")), - ) - tool_call_index += 1 - elif block_dict.get("type") == "reasoning": - reasoning_summary = block_dict.get("summary") - if reasoning_summary is not None and reasoning_summary != []: - if isinstance(reasoning_summary, (dict, list)): - reasoning_value = json.dumps(reasoning_summary) - else: - reasoning_value = reasoning_summary - _set_span_attribute( - span, f"{GenAIAttributes.GEN_AI_COMPLETION}.0.reasoning", reasoning_value - ) - # TODO: handle other block types, in particular other calls + if should_send_prompts(): + _set_responses_json_messages(traced_response, span) @dont_throw diff --git a/packages/opentelemetry-instrumentation-openai/tests/conftest.py b/packages/opentelemetry-instrumentation-openai/tests/conftest.py index a70ac5b47e..cde4894c0c 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/conftest.py +++ b/packages/opentelemetry-instrumentation-openai/tests/conftest.py @@ -189,6 +189,7 @@ def instrument_with_no_content( instrumentor.uninstrument() + @pytest.fixture(autouse=True) def clear_exporter(span_exporter): span_exporter.clear() @@ -196,4 +197,11 @@ def clear_exporter(span_exporter): @pytest.fixture(scope="module") def vcr_config(): - return {"filter_headers": ["authorization", "api-key"]} + return {"filter_headers": [ + "authorization", + "api-key", + "openai-organization", + "openai-project", + "set-cookie", + "x-request-id", + ]} diff --git a/packages/opentelemetry-instrumentation-openai/tests/metrics/test_openai_metrics.py b/packages/opentelemetry-instrumentation-openai/tests/metrics/test_openai_metrics.py index e5462442ae..fed2fc1771 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/metrics/test_openai_metrics.py +++ b/packages/opentelemetry-instrumentation-openai/tests/metrics/test_openai_metrics.py @@ -212,7 +212,7 @@ def test_chat_streaming_metrics(instrument_legacy, reader, deepseek_client): for data_point in metric.data.data_points: assert ( - data_point.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) == "openai" + data_point.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == "openai" ) # Add `deepseek-chat` to the list of models since it's a alternative to OpenAI API assert str( diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/cassettes/test_chat/test_chat_with_messages_attributes.yaml b/packages/opentelemetry-instrumentation-openai/tests/traces/cassettes/test_chat/test_chat_with_messages_attributes.yaml new file mode 100644 index 0000000000..49ddc68720 --- /dev/null +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/cassettes/test_chat/test_chat_with_messages_attributes.yaml @@ -0,0 +1,105 @@ +interactions: +- request: + body: '{"messages":[{"role":"user","content":"Tell me a joke about opentelemetry"}],"model":"gpt-5-nano"}' + headers: + Accept: + - application/json + Accept-Encoding: + - gzip, deflate + Connection: + - keep-alive + Content-Length: + - '98' + Content-Type: + - application/json + Host: + - api.openai.com + User-Agent: + - OpenAI/Python 1.99.7 + X-Stainless-Arch: + - arm64 + X-Stainless-Async: + - 'false' + X-Stainless-Lang: + - python + X-Stainless-OS: + - MacOS + X-Stainless-Package-Version: + - 1.99.7 + X-Stainless-Runtime: + - CPython + X-Stainless-Runtime-Version: + - 3.10.19 + traceparent: + - 00-72aeac60cac1acd2b6fc8d8b9fe6e376-7ed5bceefb31140d-01 + x-stainless-read-timeout: + - '600' + x-stainless-retry-count: + - '0' + method: POST + uri: https://api.openai.com/v1/chat/completions + response: + body: + string: !!binary | + H4sIAAAAAAAA/3VTQW7bMBC8+xUEz5YhpbUc5xgUyC29FE2DIhA25FpiTJEEuWoqBAbykPZzeUlJ + WY4UNLkQ4M7OanaGelowxpXkF4yLBki0Tmdftj82fSsuH/H6BkHW+6v+qtzuv9/eFiXxZWLY+wcU + dGKthI08JGXNERYegTBNLTaboig/l2U5AK2VqBOtdpStMwPGZmf52TrLz7N8M5IbqwSG2PUzXhl7 + 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a/packages/opentelemetry-instrumentation-openai/tests/traces/conftest.py b/packages/opentelemetry-instrumentation-openai/tests/traces/conftest.py index 6a37b10bd7..28dd321a66 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/conftest.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/conftest.py @@ -4,6 +4,13 @@ @pytest.fixture(scope="module") def vcr_config(): return { - "filter_headers": ["authorization", "api-key"], + "filter_headers": [ + "authorization", + "api-key", + "openai-organization", + "openai-project", + "set-cookie", + "x-request-id", + ], "ignore_hosts": ["openaipublic.blob.core.windows.net"], } diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_assistant.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_assistant.py index f767ffbd6f..3f21e55dbf 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_assistant.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_assistant.py @@ -4,9 +4,10 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) -from opentelemetry.semconv_ai import SpanAttributes from typing_extensions import override +from .utils import get_input_messages, get_output_messages + @pytest.fixture def assistant(openai_client): @@ -56,7 +57,7 @@ def test_new_assistant( "openai.assistant.run", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -65,46 +66,32 @@ def test_new_assistant( open_ai_span.attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] == "gpt-4-turbo-preview" ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "You are a personal math tutor. Write and run code to answer math questions." - ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.role"] == "system" - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.1.content") - == "Please address the user as Jane Doe. The user has a premium account." - ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.role"] == "system" - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.2.role"] == "user" - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.2.content"] - == user_message - ) - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 155 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 145 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" - - completion_index = 0 - for message in messages.data: - if message.role in ["user", "system"]: - continue - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}.content" - ] - == message.content[0].text.value - ) - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}.role" - ] - == message.role - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "system" + assert input_messages[0]["parts"][0]["content"] == ( + "You are a personal math tutor." + " Write and run code to answer math questions." + ) + assert input_messages[1]["role"] == "system" + assert input_messages[1]["parts"][0]["content"] == ( + "Please address the user as Jane Doe." + " The user has a premium account." + ) + assert input_messages[2]["role"] == "user" + assert input_messages[2]["parts"][0]["content"] == user_message + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 145 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 155 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" + + output_messages = get_output_messages(open_ai_span) + assistant_messages = [m for m in messages.data if m.role not in ["user", "system"]] + for idx, message in enumerate(assistant_messages): + assert output_messages[idx]["role"] == message.role + assert output_messages[idx]["parts"][0]["content"] == message.content[0].text.value assert ( - open_ai_span.attributes[f"gen_ai.response.{completion_index}.id"] + open_ai_span.attributes[f"gen_ai.response.{idx}.id"] == message.id ) - completion_index += 1 logs = log_exporter.get_finished_logs() assert ( @@ -153,7 +140,7 @@ def test_new_assistant_with_events_with_content( "openai.assistant.run", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -163,9 +150,9 @@ def test_new_assistant_with_events_with_content( == "gpt-4-turbo-preview" ) - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 155 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 145 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 145 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 155 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 4 @@ -234,7 +221,7 @@ def test_new_assistant_with_events_with_no_content( "openai.assistant.run", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -243,9 +230,9 @@ def test_new_assistant_with_events_with_no_content( open_ai_span.attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] == "gpt-4-turbo-preview" ) - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 155 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 145 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 145 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 155 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 4 @@ -298,46 +285,35 @@ def test_new_assistant_with_polling( "openai.assistant.run", ] open_ai_span = spans[0] - assert open_ai_span.attributes["llm.request.type"] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert open_ai_span.attributes["gen_ai.request.model"] == "gpt-4-turbo-preview" assert open_ai_span.attributes["gen_ai.response.model"] == "gpt-4-turbo-preview" - assert ( - open_ai_span.attributes["gen_ai.prompt.0.content"] - == "You are a personal math tutor. Write and run code to answer math questions." - ) - assert open_ai_span.attributes["gen_ai.prompt.0.role"] == "system" - assert ( - open_ai_span.attributes.get("gen_ai.prompt.1.content") - == "Please address the user as Jane Doe. The user has a premium account." - ) - assert open_ai_span.attributes["gen_ai.prompt.1.role"] == "system" - assert open_ai_span.attributes["gen_ai.prompt.2.role"] == "user" - assert open_ai_span.attributes["gen_ai.prompt.2.content"] == user_message - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 86 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 374 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" - - completion_index = 0 - for message in messages.data: - if message.role in ["user", "system"]: - continue - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}.content" - ] - == message.content[0].text.value - ) - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}.role" - ] - == message.role - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "system" + assert input_messages[0]["parts"][0]["content"] == ( + "You are a personal math tutor." + " Write and run code to answer math questions." + ) + assert input_messages[1]["role"] == "system" + assert input_messages[1]["parts"][0]["content"] == ( + "Please address the user as Jane Doe." + " The user has a premium account." + ) + assert input_messages[2]["role"] == "user" + assert input_messages[2]["parts"][0]["content"] == user_message + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 374 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 86 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" + + output_messages = get_output_messages(open_ai_span) + assistant_messages = [m for m in messages.data if m.role not in ["user", "system"]] + for idx, message in enumerate(assistant_messages): + assert output_messages[idx]["role"] == message.role + assert output_messages[idx]["parts"][0]["content"] == message.content[0].text.value assert ( - open_ai_span.attributes[f"gen_ai.response.{completion_index}.id"] + open_ai_span.attributes[f"gen_ai.response.{idx}.id"] == message.id ) - completion_index += 1 logs = log_exporter.get_finished_logs() assert ( @@ -378,12 +354,12 @@ def test_new_assistant_with_polling_with_events_with_content( "openai.assistant.run", ] open_ai_span = spans[0] - assert open_ai_span.attributes["llm.request.type"] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert open_ai_span.attributes["gen_ai.request.model"] == "gpt-4-turbo-preview" assert open_ai_span.attributes["gen_ai.response.model"] == "gpt-4-turbo-preview" - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 86 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 374 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 374 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 86 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 4 @@ -452,12 +428,12 @@ def test_new_assistant_with_polling_with_events_with_no_content( "openai.assistant.run", ] open_ai_span = spans[0] - assert open_ai_span.attributes["llm.request.type"] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert open_ai_span.attributes["gen_ai.request.model"] == "gpt-4-turbo-preview" assert open_ai_span.attributes["gen_ai.response.model"] == "gpt-4-turbo-preview" - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 86 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 374 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 374 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 86 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 4 @@ -523,43 +499,32 @@ def test_existing_assistant( open_ai_span.attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] == "gpt-4-turbo-preview" ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "You are a personal math tutor. Write and run code to answer math questions." - ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.role"] == "system" - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.1.content") - == "Please address the user as Jane Doe. The user has a premium account." - ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.role"] == "system" - assert open_ai_span.attributes["gen_ai.prompt.2.role"] == "user" - assert open_ai_span.attributes["gen_ai.prompt.2.content"] == user_message - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 170 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 639 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" - - completion_index = 0 - for message in messages.data: - if message.role in ["user", "system"]: - continue - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}.content" - ] - == message.content[0].text.value - ) - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_COMPLETION}.{completion_index}.role" - ] - == message.role - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "system" + assert input_messages[0]["parts"][0]["content"] == ( + "You are a personal math tutor." + " Write and run code to answer math questions." + ) + assert input_messages[1]["role"] == "system" + assert input_messages[1]["parts"][0]["content"] == ( + "Please address the user as Jane Doe." + " The user has a premium account." + ) + assert input_messages[2]["role"] == "user" + assert input_messages[2]["parts"][0]["content"] == user_message + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 639 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 170 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" + + output_messages = get_output_messages(open_ai_span) + assistant_messages = [m for m in messages.data if m.role not in ["user", "system"]] + for idx, message in enumerate(assistant_messages): + assert output_messages[idx]["role"] == message.role + assert output_messages[idx]["parts"][0]["content"] == message.content[0].text.value assert ( - open_ai_span.attributes[f"gen_ai.response.{completion_index}.id"] + open_ai_span.attributes[f"gen_ai.response.{idx}.id"] == message.id ) - completion_index += 1 logs = log_exporter.get_finished_logs() assert ( @@ -614,9 +579,9 @@ def test_existing_assistant_with_events_with_content( == "gpt-4-turbo-preview" ) - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 170 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 639 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 639 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 170 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 5 @@ -709,9 +674,9 @@ def test_existing_assistant_with_events_with_no_content( == "gpt-4-turbo-preview" ) - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 170 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 639 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 639 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 170 + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 5 @@ -772,7 +737,7 @@ def on_text_delta(self, delta, snapshot): "openai.assistant.run_stream", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -781,30 +746,26 @@ def on_text_delta(self, delta, snapshot): open_ai_span.attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] == "gpt-4-turbo-preview" ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "You are a personal math tutor. Write and run code to answer math questions." + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "system" + assert input_messages[0]["parts"][0]["content"] == ( + "You are a personal math tutor." + " Write and run code to answer math questions." ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.role"] == "system" - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.1.content") - == "Please address the user as Jane Doe. The user has a premium account." + assert input_messages[1]["role"] == "system" + assert input_messages[1]["parts"][0]["content"] == ( + "Please address the user as Jane Doe." + " The user has a premium account." ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.role"] == "system" assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 790 assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 225 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" + output_messages = get_output_messages(open_ai_span) for idx, message in enumerate(assistant_messages): - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.{idx}.content"] - == message - ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.{idx}.role"] - == "assistant" - ) + assert output_messages[idx]["role"] == "assistant" + assert output_messages[idx]["parts"][0]["content"] == message assert open_ai_span.attributes[f"gen_ai.response.{idx}.id"].startswith("msg") logs = log_exporter.get_finished_logs() @@ -850,7 +811,7 @@ def on_text_delta(self, delta, snapshot): "openai.assistant.run_stream", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -862,7 +823,7 @@ def on_text_delta(self, delta, snapshot): assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 790 assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 225 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 4 @@ -953,7 +914,7 @@ def on_text_delta(self, delta, snapshot): "openai.assistant.run_stream", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -965,7 +926,7 @@ def on_text_delta(self, delta, snapshot): assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 790 assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 225 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 4 @@ -1022,7 +983,7 @@ def on_text_delta(self, delta, snapshot): "openai.assistant.run_stream", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -1031,29 +992,25 @@ def on_text_delta(self, delta, snapshot): open_ai_span.attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] == "gpt-4-turbo-preview" ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "You are a personal math tutor. Write and run code to answer math questions." + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "system" + assert input_messages[0]["parts"][0]["content"] == ( + "You are a personal math tutor." + " Write and run code to answer math questions." ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.role"] == "system" - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.1.content") - == "Please address the user as Jane Doe. The user has a premium account." + assert input_messages[1]["role"] == "system" + assert input_messages[1]["parts"][0]["content"] == ( + "Please address the user as Jane Doe." + " The user has a premium account." ) - assert open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.role"] == "system" assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 364 assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 88 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" + output_messages = get_output_messages(open_ai_span) for idx, message in enumerate(assistant_messages): - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.{idx}.content"] - == message - ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.{idx}.role"] - == "assistant" - ) + assert output_messages[idx]["role"] == "assistant" + assert output_messages[idx]["parts"][0]["content"] == message assert open_ai_span.attributes[f"gen_ai.response.{idx}.id"].startswith("msg_") logs = log_exporter.get_finished_logs() @@ -1099,7 +1056,7 @@ def on_text_delta(self, delta, snapshot): "openai.assistant.run_stream", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -1111,7 +1068,7 @@ def on_text_delta(self, delta, snapshot): assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 364 assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 88 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 3 @@ -1187,7 +1144,7 @@ def on_text_delta(self, delta, snapshot): "openai.assistant.run_stream", ] open_ai_span = spans[0] - assert open_ai_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "chat" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4-turbo-preview" @@ -1199,7 +1156,7 @@ def on_text_delta(self, delta, snapshot): assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 364 assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == 88 - assert open_ai_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert open_ai_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" logs = log_exporter.get_finished_logs() assert len(logs) == 3 @@ -1218,7 +1175,7 @@ def on_text_delta(self, delta, snapshot): def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_azure.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_azure.py index 62d98692bc..f03a9f1bc2 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_azure.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_azure.py @@ -8,8 +8,9 @@ ) from opentelemetry.semconv_ai import SpanAttributes +from .utils import get_input_messages, get_output_messages + PROMPT_FILTER_KEY = "prompt_filter_results" -PROMPT_ERROR = "prompt_error" @pytest.mark.vcr @@ -25,16 +26,17 @@ def test_chat(instrument_legacy, span_exporter, log_exporter, azure_openai_clien "openai.chat", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "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(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpbZPf84KZFiQG6fdY0KVtIwHyIa" @@ -62,10 +64,10 @@ def test_chat_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "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(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpbZPf84KZFiQG6fdY0KVtIwHyIa" @@ -108,10 +110,10 @@ def test_chat_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "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(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpbZPf84KZFiQG6fdY0KVtIwHyIa" @@ -143,31 +145,23 @@ def test_chat_content_filtering( "openai.chat", ] open_ai_span = spans[0] + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - == "FILTERED" - ) - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "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(SpanAttributes.GEN_AI_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"{GenAIAttributes.GEN_AI_COMPLETION}.0.content_filter_results" - ) - - assert len(content_filter_json) > 0 - - content_filter_results = json.loads(content_filter_json) + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) > 0 + content_filter_results = output_messages[0].get("content_filter_results") + assert content_filter_results is not None assert content_filter_results["hate"]["filtered"] is True assert content_filter_results["hate"]["severity"] == "high" @@ -197,10 +191,10 @@ def test_chat_content_filtering_with_events_with_content( open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "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(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpyGSWv1hoKdGaUaiFhfxzTEVlZo" @@ -242,10 +236,10 @@ def test_chat_content_filtering_with_events_with_no_content( open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "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(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9HpyGSWv1hoKdGaUaiFhfxzTEVlZo" @@ -282,27 +276,8 @@ def test_prompt_content_filtering( ] open_ai_span = spans[0] - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}"], str - ) - - error = json.loads( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}"] - ) - - assert "innererror" in error - - assert "content_filter_result" in error["innererror"] - - assert error["innererror"]["code"] == "ResponsibleAIPolicyViolation" - - assert error["innererror"]["content_filter_result"]["hate"]["filtered"] - - assert error["innererror"]["content_filter_result"]["hate"]["severity"] == "high" - - assert error["innererror"]["content_filter_result"]["sexual"]["filtered"] is False - - assert error["innererror"]["content_filter_result"]["sexual"]["severity"] == "safe" + assert open_ai_span.attributes.get("error.type") is not None + assert open_ai_span.status.status_code.name == "ERROR" logs = log_exporter.get_finished_logs() assert ( @@ -326,27 +301,8 @@ def test_prompt_content_filtering_with_events_with_content( ] open_ai_span = spans[0] - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}"], str - ) - - error = json.loads( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}"] - ) - - assert "innererror" in error - - assert "content_filter_result" in error["innererror"] - - assert error["innererror"]["code"] == "ResponsibleAIPolicyViolation" - - assert error["innererror"]["content_filter_result"]["hate"]["filtered"] - - assert error["innererror"]["content_filter_result"]["hate"]["severity"] == "high" - - assert error["innererror"]["content_filter_result"]["sexual"]["filtered"] is False - - assert error["innererror"]["content_filter_result"]["sexual"]["severity"] == "safe" + assert open_ai_span.attributes.get("error.type") is not None + assert open_ai_span.status.status_code.name == "ERROR" logs = log_exporter.get_finished_logs() assert len(logs) == 1, "Should not have a response event because of the error." @@ -375,27 +331,8 @@ def test_prompt_content_filtering_with_events_with_no_content( ] open_ai_span = spans[0] - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}"], str - ) - - error = json.loads( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.{PROMPT_ERROR}"] - ) - - assert "innererror" in error - - assert "content_filter_result" in error["innererror"] - - assert error["innererror"]["code"] == "ResponsibleAIPolicyViolation" - - assert error["innererror"]["content_filter_result"]["hate"]["filtered"] - - assert error["innererror"]["content_filter_result"]["hate"]["severity"] == "high" - - assert error["innererror"]["content_filter_result"]["sexual"]["filtered"] is False - - assert error["innererror"]["content_filter_result"]["sexual"]["severity"] == "safe" + assert open_ai_span.attributes.get("error.type") is not None + assert open_ai_span.status.status_code.name == "ERROR" logs = log_exporter.get_finished_logs() assert len(logs) == 1, "Should not have a response event because of the error." @@ -424,16 +361,17 @@ def test_chat_streaming( "openai.chat", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://traceloop-stg.openai.azure.com/openai/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -483,10 +421,10 @@ def test_chat_streaming_with_events_with_content( open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://traceloop-stg.openai.azure.com/openai/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -553,10 +491,10 @@ def test_chat_streaming_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://traceloop-stg.openai.azure.com/openai/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -611,23 +549,24 @@ async def test_chat_async_streaming( ] open_ai_span = spans[0] + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://traceloop-stg.openai.azure.com/openai/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True # Only assert token usage if API provides it (Existing cassetes of Azure OpenAI may not include usage in streaming) - completion_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) - prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) - if completion_tokens and prompt_tokens and total_tokens: - assert completion_tokens + prompt_tokens == total_tokens + input_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) + output_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) + if input_tokens and output_tokens and total_tokens: + assert input_tokens + output_tokens == total_tokens events = open_ai_span.events assert len(events) == chunk_count @@ -665,17 +604,17 @@ async def test_chat_async_streaming_with_events_with_content( open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://traceloop-stg.openai.azure.com/openai/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True # Only assert token usage if API provides it (Existing cassetes of Azure OpenAI may not include usage in streaming) - completion_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) - prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) - if completion_tokens and prompt_tokens and total_tokens: - assert completion_tokens + prompt_tokens == total_tokens + input_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) + output_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) + if input_tokens and output_tokens and total_tokens: + assert input_tokens + output_tokens == total_tokens events = open_ai_span.events assert len(events) == chunk_count @@ -731,17 +670,17 @@ async def test_chat_async_streaming_with_events_with_no_content( open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://traceloop-stg.openai.azure.com/openai/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True # Only assert token usage if API provides it (Existing cassetes of Azure OpenAI may not include usage in streaming) - completion_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) - prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) - if completion_tokens and prompt_tokens and total_tokens: - assert completion_tokens + prompt_tokens == total_tokens + input_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) + output_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) + if input_tokens and output_tokens and total_tokens: + assert input_tokens + output_tokens == total_tokens events = open_ai_span.events assert len(events) == chunk_count @@ -781,14 +720,14 @@ def test_chat_reasoning(instrument_legacy, span_exporter, assert len(spans) >= 1 span = spans[-1] - assert span.attributes["llm.request.reasoning_effort"] == "low" - assert span.attributes["llm.usage.reasoning_tokens"] > 0 + assert span.attributes["gen_ai.request.reasoning_effort"] == "low" + assert span.attributes["gen_ai.usage.reasoning_tokens"] > 0 def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat.py index 352c042bab..3395aa6f2a 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat.py @@ -14,7 +14,7 @@ from opentelemetry.trace import StatusCode from opentelemetry.instrumentation.openai.utils import is_reasoning_supported -from .utils import assert_request_contains_tracecontext, spy_decorator +from .utils import assert_request_contains_tracecontext, spy_decorator, get_input_messages, get_output_messages @pytest.mark.vcr @@ -31,24 +31,26 @@ def test_chat(instrument_legacy, span_exporter, log_exporter, openai_client): "openai.chat", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert len(input_messages) == 1 + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert output_messages[0]["finish_reason"] == "stop" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert ( open_ai_span.attributes.get( - SpanAttributes.LLM_OPENAI_RESPONSE_SYSTEM_FINGERPRINT + GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SYSTEM_FINGERPRINT ) == "fp_2b778c6b35" ) assert open_ai_span.attributes.get( - SpanAttributes.LLM_IS_STREAMING) is False + SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-908MD9ivBBLb6EaIjlqwFokntayQK" @@ -78,17 +80,17 @@ def test_chat_with_events_with_content( open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert ( open_ai_span.attributes.get( - SpanAttributes.LLM_OPENAI_RESPONSE_SYSTEM_FINGERPRINT + GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SYSTEM_FINGERPRINT ) == "fp_2b778c6b35" ) assert open_ai_span.attributes.get( - SpanAttributes.LLM_IS_STREAMING) is False + SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-908MD9ivBBLb6EaIjlqwFokntayQK" @@ -133,17 +135,17 @@ def test_chat_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert ( open_ai_span.attributes.get( - SpanAttributes.LLM_OPENAI_RESPONSE_SYSTEM_FINGERPRINT + GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SYSTEM_FINGERPRINT ) == "fp_2b778c6b35" ) assert open_ai_span.attributes.get( - SpanAttributes.LLM_IS_STREAMING) is False + SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-908MD9ivBBLb6EaIjlqwFokntayQK" @@ -193,25 +195,19 @@ def test_chat_tool_calls(instrument_legacy, span_exporter, log_exporter, openai_ "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_PROMPT}.0.content" not in open_ai_span.attributes - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.tool_calls.0.name"] - == "get_current_weather" - ) - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_PROMPT}.0.tool_calls.0.arguments" - ] - == '{"location": "San Francisco"}' - ) - - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.content"] - == "The weather in San Francisco is 70 degrees and sunny." - ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.tool_call_id"] == "1" - ) + input_messages = get_input_messages(open_ai_span) + assert len(input_messages) == 2 + # assistant message with tool call + assert input_messages[0]["role"] == "assistant" + tool_parts = [p for p in input_messages[0]["parts"] if p["type"] == "tool_call"] + assert len(tool_parts) == 1 + assert tool_parts[0]["name"] == "get_current_weather" + assert tool_parts[0]["arguments"] == {"location": "San Francisco"} + # tool response message + assert input_messages[1]["role"] == "tool" + assert input_messages[1]["parts"][0]["type"] == "tool_call_response" + assert input_messages[1]["parts"][0]["id"] == "1" + assert input_messages[1]["parts"][0]["response"] == "The weather in San Francisco is 70 degrees and sunny." assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9gKNZbUWSC4s2Uh2QfVV7PYiqWIuH" @@ -258,8 +254,6 @@ def test_chat_tool_calls_with_events_with_content( ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_PROMPT}.0.content" not in open_ai_span.attributes - assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9gKNZbUWSC4s2Uh2QfVV7PYiqWIuH" @@ -337,7 +331,6 @@ def test_chat_tool_calls_with_events_with_no_content( ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_PROMPT}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9gKNZbUWSC4s2Uh2QfVV7PYiqWIuH" @@ -411,25 +404,17 @@ def test_chat_pydantic_based_tool_calls( ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_PROMPT}.0.content" not in open_ai_span.attributes - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.tool_calls.0.name"] - == "get_current_weather" - ) - assert ( - open_ai_span.attributes[ - f"{GenAIAttributes.GEN_AI_PROMPT}.0.tool_calls.0.arguments" - ] - == '{"location": "San Francisco"}' - ) - - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.content"] - == "The weather in San Francisco is 70 degrees and sunny." - ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.tool_call_id"] == "1" - ) + input_messages = get_input_messages(open_ai_span) + assert len(input_messages) == 2 + assert input_messages[0]["role"] == "assistant" + tool_parts = [p for p in input_messages[0]["parts"] if p["type"] == "tool_call"] + assert len(tool_parts) == 1 + assert tool_parts[0]["name"] == "get_current_weather" + assert tool_parts[0]["arguments"] == {"location": "San Francisco"} + assert input_messages[1]["role"] == "tool" + assert input_messages[1]["parts"][0]["type"] == "tool_call_response" + assert input_messages[1]["parts"][0]["id"] == "1" + assert input_messages[1]["parts"][0]["response"] == "The weather in San Francisco is 70 degrees and sunny." assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9lvGJKrBUPeJjHi3KKSEbGfcfomOP" @@ -484,7 +469,6 @@ def test_chat_pydantic_based_tool_calls_with_events_with_content( ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_PROMPT}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9lvGJKrBUPeJjHi3KKSEbGfcfomOP" @@ -570,7 +554,6 @@ def test_chat_pydantic_based_tool_calls_with_events_with_no_content( ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_PROMPT}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9lvGJKrBUPeJjHi3KKSEbGfcfomOP" @@ -620,17 +603,18 @@ def test_chat_streaming(instrument_legacy, span_exporter, log_exporter, mock_ope "openai.chat", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert len(input_messages) == 1 + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "http://localhost:5002/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events # Mock OpenAI background may produce different number of events, just check it's reasonable @@ -639,7 +623,7 @@ def test_chat_streaming(instrument_legacy, span_exporter, log_exporter, mock_ope # check token usage attributes for stream completion_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) assert completion_tokens and prompt_tokens and total_tokens # When OpenAI API provides token usage, check that the sum of completion and prompt tokens equals total tokens assert completion_tokens + prompt_tokens == total_tokens @@ -676,10 +660,10 @@ def test_chat_streaming_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -687,7 +671,7 @@ def test_chat_streaming_with_events_with_content( # check token usage attributes for stream completion_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) # Only assert token usage if API provides it (modern OpenAI API includes usage in streaming) if completion_tokens and prompt_tokens and total_tokens: assert completion_tokens + prompt_tokens == total_tokens @@ -743,10 +727,10 @@ def test_chat_streaming_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -754,7 +738,7 @@ def test_chat_streaming_with_events_with_no_content( # check token usage attributes for stream (optional, depends on API support) completion_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) if completion_tokens and prompt_tokens and total_tokens: assert completion_tokens + prompt_tokens == total_tokens assert ( @@ -796,16 +780,18 @@ async def test_chat_async_streaming( "openai.chat", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert len(input_messages) == 1 + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -815,7 +801,7 @@ async def test_chat_async_streaming( GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS ) prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) if completion_tokens and prompt_tokens and total_tokens: assert completion_tokens + prompt_tokens == total_tokens assert ( @@ -852,10 +838,10 @@ async def test_chat_async_streaming_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -865,7 +851,7 @@ async def test_chat_async_streaming_with_events_with_content( GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS ) prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) if completion_tokens and prompt_tokens and total_tokens: assert completion_tokens + prompt_tokens == total_tokens assert ( @@ -919,10 +905,10 @@ async def test_chat_async_streaming_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True events = open_ai_span.events assert len(events) == chunk_count @@ -932,7 +918,7 @@ async def test_chat_async_streaming_with_events_with_no_content( GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS ) prompt_tokens = open_ai_span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) - total_tokens = open_ai_span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) + total_tokens = open_ai_span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) if completion_tokens and prompt_tokens and total_tokens: assert completion_tokens + prompt_tokens == total_tokens assert ( @@ -1325,7 +1311,7 @@ def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_con # In OpenTelemetry 1.37.0+, event_name is a field on LogRecord, not in attributes assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) @@ -1337,7 +1323,7 @@ def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_con @pytest.mark.vcr -def test_chat_history_message_dict(span_exporter, openai_client): +def test_chat_history_message_dict(instrument_legacy, span_exporter, openai_client): first_user_message = { "role": "user", "content": "Generate a random noun in Korean. Respond with just that word.", @@ -1368,46 +1354,29 @@ def test_chat_history_message_dict(span_exporter, openai_client): assert len(spans) == 2 first_span = spans[0] assert first_span.name == "openai.chat" - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == first_user_message["content"] - ) - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.role"] - == first_user_message["role"] - ) - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content"] - == first_response.choices[0].message.content - ) - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.role"] == "assistant" - ) + first_input = get_input_messages(first_span) + assert first_input[0]["role"] == first_user_message["role"] + assert first_input[0]["parts"][0]["content"] == first_user_message["content"] + first_output = get_output_messages(first_span) + assert first_output[0]["role"] == "assistant" + assert first_output[0]["parts"][0]["content"] == first_response.choices[0].message.content second_span = spans[1] assert second_span.name == "openai.chat" - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == first_user_message["content"] - ) - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content"] - == second_response.choices[0].message.content - ) - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.content"] - == first_response.choices[0].message.content - ) - assert second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.role"] == "assistant" - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.2.content"] - == second_user_message["content"] - ) - assert second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.2.role"] == "user" + second_input = get_input_messages(second_span) + assert second_input[0]["role"] == "user" + assert second_input[0]["parts"][0]["content"] == first_user_message["content"] + assert second_input[1]["role"] == "assistant" + assert second_input[1]["parts"][0]["content"] == first_response.choices[0].message.content + assert second_input[2]["role"] == "user" + assert second_input[2]["parts"][0]["content"] == second_user_message["content"] + second_output = get_output_messages(second_span) + assert second_output[0]["role"] == "assistant" + assert second_output[0]["parts"][0]["content"] == second_response.choices[0].message.content @pytest.mark.vcr -def test_chat_history_message_pydantic(span_exporter, openai_client): +def test_chat_history_message_pydantic(instrument_legacy, span_exporter, openai_client): first_user_message = { "role": "user", "content": "Generate a random noun in Korean. Respond with just that word.", @@ -1435,42 +1404,25 @@ def test_chat_history_message_pydantic(span_exporter, openai_client): assert len(spans) == 2 first_span = spans[0] assert first_span.name == "openai.chat" - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == first_user_message["content"] - ) - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.role"] - == first_user_message["role"] - ) - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content"] - == first_response.choices[0].message.content - ) - assert ( - first_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.role"] == "assistant" - ) + first_input = get_input_messages(first_span) + assert first_input[0]["role"] == first_user_message["role"] + assert first_input[0]["parts"][0]["content"] == first_user_message["content"] + first_output = get_output_messages(first_span) + assert first_output[0]["role"] == "assistant" + assert first_output[0]["parts"][0]["content"] == first_response.choices[0].message.content second_span = spans[1] assert second_span.name == "openai.chat" - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == first_user_message["content"] - ) - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content"] - == second_response.choices[0].message.content - ) - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.content"] - == first_response.choices[0].message.content - ) - assert second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.1.role"] == "assistant" - assert ( - second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.2.content"] - == second_user_message["content"] - ) - assert second_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.2.role"] == "user" + second_input = get_input_messages(second_span) + assert second_input[0]["role"] == "user" + assert second_input[0]["parts"][0]["content"] == first_user_message["content"] + assert second_input[1]["role"] == "assistant" + assert second_input[1]["parts"][0]["content"] == first_response.choices[0].message.content + assert second_input[2]["role"] == "user" + assert second_input[2]["parts"][0]["content"] == second_user_message["content"] + second_output = get_output_messages(second_span) + assert second_output[0]["role"] == "assistant" + assert second_output[0]["parts"][0]["content"] == second_response.choices[0].message.content @pytest.mark.vcr @@ -1493,8 +1445,8 @@ def test_chat_reasoning(instrument_legacy, span_exporter, assert len(spans) >= 1 span = spans[-1] - assert span.attributes["llm.request.reasoning_effort"] == "low" - assert span.attributes["llm.usage.reasoning_tokens"] > 0 + assert span.attributes["gen_ai.request.reasoning_effort"] == "low" + assert span.attributes["gen_ai.usage.reasoning_tokens"] > 0 @pytest.mark.vcr @@ -1533,16 +1485,15 @@ def test_chat_exception(instrument_legacy, span_exporter, openai_client): "openai.chat", ] open_ai_span = spans[0] + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert open_ai_span.attributes.get( - SpanAttributes.LLM_IS_STREAMING) is False + SpanAttributes.GEN_AI_IS_STREAMING) is False assert open_ai_span.status.status_code == StatusCode.ERROR assert open_ai_span.status.description.startswith("Error code: 401") events = open_ai_span.events @@ -1573,16 +1524,15 @@ async def test_chat_async_exception(instrument_legacy, span_exporter, async_open "openai.chat", ] open_ai_span = spans[0] + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert open_ai_span.attributes.get( - SpanAttributes.LLM_IS_STREAMING) is False + SpanAttributes.GEN_AI_IS_STREAMING) is False assert open_ai_span.status.status_code == StatusCode.ERROR assert open_ai_span.status.description.startswith("Error code: 401") events = open_ai_span.events @@ -1628,15 +1578,14 @@ def test_chat_streaming_not_consumed(instrument_legacy, span_exporter, log_expor assert open_ai_span.end_time > open_ai_span.start_time assert open_ai_span.attributes.get( - SpanAttributes.LLM_REQUEST_MODEL) == "gpt-3.5-turbo" - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + GenAIAttributes.GEN_AI_REQUEST_MODEL) == "gpt-3.5-turbo" + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True assert open_ai_span.attributes.get( - SpanAttributes.LLM_REQUEST_TYPE) == "chat" + GenAIAttributes.GEN_AI_OPERATION_NAME) == "chat" - assert open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_PROMPT}.0.content") == "Tell me a joke about opentelemetry" - assert open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_PROMPT}.0.role") == "user" + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + assert input_messages[0]["role"] == "user" # Verify duration metric was recorded even without consuming the stream metrics_data = reader.get_metrics_data() @@ -1655,9 +1604,18 @@ def test_chat_streaming_not_consumed(instrument_legacy, span_exporter, log_expor assert len(duration_metrics) == 1, "Duration metric should be recorded" duration_metric = duration_metrics[0] - # Verify metric data + # Verify metric data - filter for openai provider data points to avoid cross-test contamination + # (session-scoped reader may contain data points from Azure tests) assert duration_metric.data.data_points - data_point = duration_metric.data.data_points[0] + openai_data_points = [ + dp for dp in duration_metric.data.data_points + if dp.attributes.get("gen_ai.provider.name") == "openai" + ] + assert len(openai_data_points) >= 1, ( + f"Expected at least one openai data point, got data points with attributes: " + f"{[dict(dp.attributes) for dp in duration_metric.data.data_points]}" + ) + data_point = openai_data_points[0] assert data_point.count >= 1, f"Expected count >= 1, got {data_point.count}" assert data_point.sum > 0, f"Duration should be greater than 0, got {data_point.sum}" assert data_point.min > 0, f"Min duration should be greater than 0, got {data_point.min}" @@ -1665,14 +1623,14 @@ def test_chat_streaming_not_consumed(instrument_legacy, span_exporter, log_expor # Verify metric attributes attributes = data_point.attributes - assert attributes.get( - "gen_ai.system") == "openai", f"Expected gen_ai.system=openai, got {attributes.get('gen_ai.system')}" - assert attributes.get( - "gen_ai.operation.name") == "chat", f"Expected operation=chat, got {attributes.get('gen_ai.operation.name')}" + provider = attributes.get("gen_ai.provider.name") + assert provider == "openai", f"Expected gen_ai.provider.name=openai, got {provider}" + operation = attributes.get("gen_ai.operation.name") + assert operation == "chat", f"Expected operation=chat, got {operation}" streaming_data_points = [ dp for dp in duration_metric.data.data_points - if dp.attributes.get("stream") is True + if dp.attributes.get("stream") is True and dp.attributes.get("gen_ai.provider.name") == "openai" ] assert len(streaming_data_points) >= 1, ( f"Expected at least one streaming data point, got data points with attributes: " @@ -1709,8 +1667,8 @@ def test_chat_streaming_partial_consumption(instrument_legacy, span_exporter, lo assert open_ai_span.end_time is not None assert open_ai_span.attributes.get( - SpanAttributes.LLM_REQUEST_MODEL) == "gpt-3.5-turbo" - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is True + GenAIAttributes.GEN_AI_REQUEST_MODEL) == "gpt-3.5-turbo" + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is True # Should have at least one event from the consumed chunk events = open_ai_span.events @@ -1741,10 +1699,10 @@ def test_chat_streaming_partial_consumption(instrument_legacy, span_exporter, lo assert data_point.sum > 0, f"Duration should be greater than 0, got {data_point.sum}" attributes = data_point.attributes - assert attributes.get( - "gen_ai.system") == "openai", f"Expected gen_ai.system=openai, got {attributes.get('gen_ai.system')}" - assert attributes.get( - "gen_ai.operation.name") == "chat", f"Expected operation=chat, got {attributes.get('gen_ai.operation.name')}" + provider = attributes.get("gen_ai.provider.name") + assert provider == "openai", f"Expected gen_ai.provider.name=openai, got {provider}" + operation = attributes.get("gen_ai.operation.name") + assert operation == "chat", f"Expected operation=chat, got {operation}" streaming_data_points = [ dp for dp in duration_metric.data.data_points diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_parse.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_parse.py index 4a908d10ea..b3fa311b83 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_parse.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_parse.py @@ -9,6 +9,8 @@ from opentelemetry.sdk.trace import Span from opentelemetry.trace import StatusCode +from .utils import get_input_messages, get_output_messages + class StructuredAnswer(BaseModel): rating: int @@ -30,16 +32,17 @@ def test_parsed_completion( "openai.chat", ] open_ai_span = spans[0] - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1gNoe1Zyq9yZicdhLc85lmt2Ep" @@ -72,10 +75,10 @@ def test_parsed_completion_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1gNoe1Zyq9yZicdhLc85lmt2Ep" @@ -121,10 +124,10 @@ def test_parsed_completion_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1gNoe1Zyq9yZicdhLc85lmt2Ep" @@ -161,12 +164,10 @@ def test_parsed_refused_completion( "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" not in open_ai_span.attributes - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.refusal" in open_ai_span.attributes - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.refusal"] - == "I'm very sorry, but I can't assist with that request." - ) + output_messages = get_output_messages(open_ai_span) + refusal_parts = [p for p in output_messages[0]["parts"] if p.get("type") == "refusal"] + assert len(refusal_parts) == 1 + assert refusal_parts[0]["content"] == "I'm very sorry, but I can't assist with that request." assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGky8KFDbg6f5fF4qLtsBredIjZZh" @@ -197,7 +198,6 @@ def test_parsed_refused_completion_with_events_with_content( "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGky8KFDbg6f5fF4qLtsBredIjZZh" @@ -240,7 +240,6 @@ def test_parsed_refused_completion_with_events_with_no_content( "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGky8KFDbg6f5fF4qLtsBredIjZZh" @@ -278,16 +277,17 @@ async def test_async_parsed_completion( "openai.chat", ] open_ai_span = spans[0] - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1iysV7rZ0qZ510vbeKVTNxSOHB" @@ -320,10 +320,10 @@ async def test_async_parsed_completion_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1iysV7rZ0qZ510vbeKVTNxSOHB" @@ -370,10 +370,10 @@ async def test_async_parsed_completion_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGC1iysV7rZ0qZ510vbeKVTNxSOHB" @@ -411,12 +411,10 @@ async def test_async_parsed_refused_completion( "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" not in open_ai_span.attributes - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.refusal" in open_ai_span.attributes - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.refusal"] - == "I'm very sorry, but I can't assist with that request." - ) + output_messages = get_output_messages(open_ai_span) + refusal_parts = [p for p in output_messages[0]["parts"] if p.get("type") == "refusal"] + assert len(refusal_parts) == 1 + assert refusal_parts[0]["content"] == "I'm very sorry, but I can't assist with that request." assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGkyFJGzZPUGAAEDJJuOS3idKvD3G" @@ -448,7 +446,6 @@ async def test_async_parsed_refused_completion_with_events_with_content( "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGkyFJGzZPUGAAEDJJuOS3idKvD3G" @@ -492,7 +489,6 @@ async def test_async_parsed_refused_completion_with_events_with_no_content( "openai.chat", ] open_ai_span = spans[0] - assert f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" not in open_ai_span.attributes assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-AGkyFJGzZPUGAAEDJJuOS3idKvD3G" @@ -517,7 +513,7 @@ async def test_async_parsed_refused_completion_with_events_with_no_content( def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) @@ -543,10 +539,11 @@ def test_parsed_completion_exception( assert len(spans) == 1 span: Span = spans[0] assert span.name == "openai.chat" - assert span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) == "https://api.openai.com/v1/" - assert span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False - assert span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.0.content") == "Tell me a joke about opentelemetry" - assert span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.0.role") == "user" + assert span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" + assert span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert span.status.status_code == StatusCode.ERROR assert span.status.description.startswith("Error code: 401") @@ -578,10 +575,11 @@ async def test_async_parsed_completion_exception( assert len(spans) == 1 span: Span = spans[0] assert span.name == "openai.chat" - assert span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) == "https://api.openai.com/v1/" - assert span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False - assert span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.0.content") == "Tell me a joke about opentelemetry" - assert span.attributes.get(f"{GenAIAttributes.GEN_AI_PROMPT}.0.role") == "user" + assert span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" + assert span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert span.status.status_code == StatusCode.ERROR assert span.status.description.startswith("Error code: 401") diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_response_format.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_response_format.py index 3a77eb92cc..35f70ef67f 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_response_format.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_chat_response_format.py @@ -6,6 +6,8 @@ import pytest import pydantic +from .utils import get_input_messages, get_output_messages + class Joke(pydantic.BaseModel): joke: str @@ -43,10 +45,11 @@ def test_chat_response_format( assert span.attributes.get("gen_ai.response.model") == "gpt-4.1-nano-2025-04-14" assert json.loads(span.attributes.get("gen_ai.request.structured_output_schema")) == Joke.model_json_schema() - # legacy input and output attributes - assert span.attributes.get("gen_ai.prompt.0.content") == "Tell me a joke about opentelemetry" - assert span.attributes.get("gen_ai.prompt.0.role") == "user" - assert span.attributes.get("gen_ai.completion.0.role") == "assistant" + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" @pytest.mark.vcr @@ -81,7 +84,8 @@ async def test_async_chat_response_format( assert span.attributes.get("gen_ai.response.model") == "gpt-4.1-nano-2025-04-14" assert json.loads(span.attributes.get("gen_ai.request.structured_output_schema")) == Joke.model_json_schema() - # legacy input and output attributes - assert span.attributes.get("gen_ai.prompt.0.content") == "Tell me a joke about opentelemetry" - assert span.attributes.get("gen_ai.prompt.0.role") == "user" - assert span.attributes.get("gen_ai.completion.0.role") == "assistant" + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_completions.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_completions.py index fd67cbf2bb..0574de076e 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_completions.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_completions.py @@ -9,7 +9,7 @@ from opentelemetry.trace import StatusCode from opentelemetry.semconv_ai import SpanAttributes -from .utils import assert_request_contains_tracecontext, spy_decorator +from .utils import assert_request_contains_tracecontext, spy_decorator, get_input_messages, get_output_messages @pytest.mark.vcr @@ -24,16 +24,18 @@ def test_completion(instrument_legacy, span_exporter, log_exporter, openai_clien "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert len(input_messages) == 1 + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq42D1Socatcl1rCmgYZOFX7dFZw" @@ -60,10 +62,10 @@ def test_completion_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq42D1Socatcl1rCmgYZOFX7dFZw" @@ -104,10 +106,10 @@ def test_completion_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) - assert open_ai_span.attributes.get(SpanAttributes.LLM_IS_STREAMING) is False + assert open_ai_span.attributes.get(SpanAttributes.GEN_AI_IS_STREAMING) is False assert ( open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq42D1Socatcl1rCmgYZOFX7dFZw" @@ -140,11 +142,12 @@ async def test_async_completion( "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" assert ( open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq43c8U5ZZCQBX5lrSpsANwcd3OF" @@ -248,11 +251,12 @@ def test_completion_langchain_style( "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" assert ( open_ai_span.attributes.get("gen_ai.response.id") == "cmpl-8wq43QD6R2WqfxXLpYsRvSAIn9LB9" @@ -358,15 +362,14 @@ def test_completion_streaming( "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content" - ) - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "http://localhost:5002/v1/" ) @@ -378,7 +381,7 @@ def test_completion_streaming( GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS ) total_tokens = open_ai_span.attributes.get( - SpanAttributes.LLM_USAGE_TOTAL_TOKENS + SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS ) # Only assert if token usage is available (depends on API support) if completion_tokens and prompt_tokens and total_tokens: @@ -409,7 +412,7 @@ def test_completion_streaming_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) @@ -420,7 +423,7 @@ def test_completion_streaming_with_events_with_content( GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS ) total_tokens = open_ai_span.attributes.get( - SpanAttributes.LLM_USAGE_TOTAL_TOKENS + SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS ) # Only assert token usage if API provides it (modern OpenAI API includes usage in streaming) if completion_tokens and prompt_tokens and total_tokens: @@ -471,7 +474,7 @@ def test_completion_streaming_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) @@ -483,7 +486,7 @@ def test_completion_streaming_with_events_with_no_content( GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS ) total_tokens = open_ai_span.attributes.get( - SpanAttributes.LLM_USAGE_TOTAL_TOKENS + SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS ) # Only assert token usage if API provides it (modern OpenAI API includes usage in streaming) if completion_tokens and prompt_tokens and total_tokens: @@ -524,13 +527,14 @@ async def test_async_completion_streaming( "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") - assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" + assert ( + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert ( @@ -564,7 +568,7 @@ async def test_async_completion_streaming_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert ( @@ -614,7 +618,7 @@ async def test_async_completion_streaming_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes.get(SpanAttributes.LLM_OPENAI_API_BASE) + open_ai_span.attributes.get(SpanAttributes.GEN_AI_OPENAI_API_BASE) == "https://api.openai.com/v1/" ) assert ( @@ -895,10 +899,9 @@ def test_completion_exception(instrument_legacy, span_exporter, openai_client): "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert open_ai_span.status.status_code == StatusCode.ERROR assert open_ai_span.status.description.startswith("Error code: 401") events = open_ai_span.events @@ -927,10 +930,9 @@ async def test_async_completion_exception(instrument_legacy, span_exporter, asyn "openai.completion", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.user"] - == "Tell me a joke about opentelemetry" - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert open_ai_span.status.status_code == StatusCode.ERROR assert open_ai_span.status.description.startswith("Error code: 401") events = open_ai_span.events @@ -948,7 +950,7 @@ async def test_async_completion_exception(instrument_legacy, span_exporter, asyn def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_embedding_metrics_handler.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_embedding_metrics_handler.py index 817aab10d6..53faa62bbf 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_embedding_metrics_handler.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_embedding_metrics_handler.py @@ -21,7 +21,7 @@ def test_set_embeddings_metrics_handles_none_values(): duration = 1.23 expected_attributes = { - 'gen_ai.system': 'openai', + 'gen_ai.provider.name': 'openai', 'gen_ai.response.model': 'text-embedding-ada-002', 'gen_ai.operation.name': 'embeddings', 'server.address': '', diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_embeddings.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_embeddings.py index a56510ad48..f764a7ede8 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_embeddings.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_embeddings.py @@ -3,6 +3,8 @@ import httpx import openai import pytest + +from .utils import get_input_messages from opentelemetry.sdk._logs import ReadableLogRecord from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, @@ -25,17 +27,17 @@ def test_embeddings(instrument_legacy, span_exporter, log_exporter, openai_clien "openai.embeddings", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["type"] == "text" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "text-embedding-ada-002" ) assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) @@ -65,7 +67,7 @@ def test_embeddings_with_events_with_content( ) assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) @@ -109,7 +111,7 @@ def test_embeddings_with_events_with_no_content( ) assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) @@ -138,10 +140,10 @@ def test_embeddings_with_raw_response( "openai.embeddings", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["type"] == "text" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert ( open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] @@ -149,7 +151,7 @@ def test_embeddings_with_raw_response( ) assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) @@ -182,7 +184,7 @@ def test_embeddings_with_raw_response_with_events_with_content( ) assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) @@ -229,7 +231,7 @@ def test_embeddings_with_raw_response_with_events_with_no_content( ) assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) @@ -270,18 +272,18 @@ def test_azure_openai_embeddings(instrument_legacy, span_exporter, log_exporter) "openai.embeddings", ] open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "Tell me a joke about opentelemetry" - ) + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["type"] == "text" + assert input_messages[0]["parts"][0]["content"] == "Tell me a joke about opentelemetry" assert open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "embedding" assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == f"https://{azure_resource}.openai.azure.com/openai/deployments/{azure_deployment}/" ) assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_VERSION] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_VERSION] == "2023-07-01-preview" ) @@ -318,11 +320,11 @@ def test_azure_openai_embeddings_with_events_with_content( assert open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "embedding" assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == f"https://{azure_resource}.openai.azure.com/openai/deployments/{azure_deployment}/" ) assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_VERSION] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_VERSION] == "2023-07-01-preview" ) @@ -373,11 +375,11 @@ def test_azure_openai_embeddings_with_events_with_no_content( assert open_ai_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "embedding" assert open_ai_span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == 8 assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == f"https://{azure_resource}.openai.azure.com/openai/deployments/{azure_deployment}/" ) assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_VERSION] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_VERSION] == "2023-07-01-preview" ) @@ -648,7 +650,7 @@ async def test_async_embeddings_exception(instrument_legacy, span_exporter, asyn def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_event_emitter.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_event_emitter.py new file mode 100644 index 0000000000..9c8ecc27dc --- /dev/null +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_event_emitter.py @@ -0,0 +1,211 @@ +"""Unit tests for event_emitter behavior with optional tool call arguments. + +These tests verify that emitting events with tool calls that omit the +`arguments` key does not raise errors, and that the _FunctionToolCall +TypedDict correctly allows arguments to be absent. +""" + +from unittest.mock import MagicMock, patch + +import pytest + +from opentelemetry.instrumentation.openai.shared.event_models import ( + ChoiceEvent, + MessageEvent, + ToolCall, + _FunctionToolCall, +) +from opentelemetry.instrumentation.openai.shared.event_emitter import ( + emit_event, +) + + +@pytest.fixture +def mock_event_logger(): + logger = MagicMock() + with patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.Config" + ) as mock_config: + mock_config.event_logger = logger + yield logger + + +def _make_tool_call_without_arguments() -> ToolCall: + """Build a ToolCall whose _FunctionToolCall omits the arguments key.""" + function: _FunctionToolCall = {"name": "get_weather"} # no arguments key + return {"id": "call_123", "type": "function", "function": function} + + +def _make_tool_call_with_none_arguments() -> ToolCall: + function: _FunctionToolCall = {"name": "get_weather", "arguments": None} + return {"id": "call_456", "type": "function", "function": function} + + +def _make_tool_call_with_arguments() -> ToolCall: + function: _FunctionToolCall = { + "name": "get_weather", + "arguments": '{"location": "NYC"}', + } + return {"id": "call_789", "type": "function", "function": function} + + +class TestFunctionToolCallTypedDict: + def test_can_instantiate_without_arguments(self): + """_FunctionToolCall should be constructable without the arguments key.""" + func: _FunctionToolCall = {"name": "my_tool"} + assert func["name"] == "my_tool" + assert "arguments" not in func + + def test_can_instantiate_with_none_arguments(self): + func: _FunctionToolCall = {"name": "my_tool", "arguments": None} + assert func["arguments"] is None + + def test_can_instantiate_with_string_arguments(self): + func: _FunctionToolCall = {"name": "my_tool", "arguments": "{}"} + assert func["arguments"] == "{}" + + +class TestEmitMessageEventWithMissingArguments: + def test_emit_with_send_prompts_arguments_absent(self, mock_event_logger): + """Emitting a message event with arguments absent should not raise.""" + event = MessageEvent( + role="assistant", + content=None, + tool_calls=[_make_tool_call_without_arguments()], + ) + with ( + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_emit_events", + return_value=True, + ), + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_send_prompts", + return_value=True, + ), + ): + emit_event(event) + + mock_event_logger.emit.assert_called_once() + body = mock_event_logger.emit.call_args[0][0].body + assert body["tool_calls"][0]["function"]["name"] == "get_weather" + assert "arguments" not in body["tool_calls"][0]["function"] + + def test_emit_with_no_send_prompts_arguments_absent(self, mock_event_logger): + """When should_send_prompts=False, pop on absent arguments key should not raise.""" + event = MessageEvent( + role="assistant", + content=None, + tool_calls=[_make_tool_call_without_arguments()], + ) + with ( + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_emit_events", + return_value=True, + ), + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_send_prompts", + return_value=False, + ), + ): + emit_event(event) + + mock_event_logger.emit.assert_called_once() + body = mock_event_logger.emit.call_args[0][0].body + assert "arguments" not in body["tool_calls"][0]["function"] + + def test_emit_with_no_send_prompts_arguments_none(self, mock_event_logger): + """When should_send_prompts=False, arguments=None is popped without error.""" + event = MessageEvent( + role="assistant", + content=None, + tool_calls=[_make_tool_call_with_none_arguments()], + ) + with ( + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_emit_events", + return_value=True, + ), + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_send_prompts", + return_value=False, + ), + ): + emit_event(event) + + mock_event_logger.emit.assert_called_once() + body = mock_event_logger.emit.call_args[0][0].body + assert "arguments" not in body["tool_calls"][0]["function"] + + def test_emit_with_no_send_prompts_arguments_present(self, mock_event_logger): + """When should_send_prompts=False, present arguments are stripped.""" + event = MessageEvent( + role="assistant", + content=None, + tool_calls=[_make_tool_call_with_arguments()], + ) + with ( + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_emit_events", + return_value=True, + ), + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_send_prompts", + return_value=False, + ), + ): + emit_event(event) + + mock_event_logger.emit.assert_called_once() + body = mock_event_logger.emit.call_args[0][0].body + assert "arguments" not in body["tool_calls"][0]["function"] + + +class TestEmitChoiceEventWithMissingArguments: + def test_emit_with_send_prompts_arguments_absent(self, mock_event_logger): + """Emitting a choice event with arguments absent should not raise.""" + event = ChoiceEvent( + index=0, + message={"content": None, "role": "assistant"}, + finish_reason="tool_calls", + tool_calls=[_make_tool_call_without_arguments()], + ) + with ( + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_emit_events", + return_value=True, + ), + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_send_prompts", + return_value=True, + ), + ): + emit_event(event) + + mock_event_logger.emit.assert_called_once() + body = mock_event_logger.emit.call_args[0][0].body + assert body["tool_calls"][0]["function"]["name"] == "get_weather" + assert "arguments" not in body["tool_calls"][0]["function"] + + def test_emit_with_no_send_prompts_arguments_absent(self, mock_event_logger): + """When should_send_prompts=False, pop on absent arguments should not raise.""" + event = ChoiceEvent( + index=0, + message={"content": None, "role": "assistant"}, + finish_reason="tool_calls", + tool_calls=[_make_tool_call_without_arguments()], + ) + with ( + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_emit_events", + return_value=True, + ), + patch( + "opentelemetry.instrumentation.openai.shared.event_emitter.should_send_prompts", + return_value=False, + ), + ): + emit_event(event) + + mock_event_logger.emit.assert_called_once() + body = mock_event_logger.emit.call_args[0][0].body + assert "arguments" not in body["tool_calls"][0]["function"] diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_functions.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_functions.py index d088630be8..e910e8efc1 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_functions.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_functions.py @@ -5,6 +5,8 @@ ) from opentelemetry.semconv_ai import SpanAttributes +from .utils import get_input_messages, get_output_messages, get_tool_definitions + @pytest.fixture def openai_tools(): @@ -61,24 +63,17 @@ def test_open_ai_function_calls( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "What's the weather like in Boston?" - ) - assert ( - open_ai_span.attributes[f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.name"] - == "get_current_weather" - ) - assert ( - open_ai_span.attributes[f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.description"] - == "Get the current weather in a given location" - ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.name"] - == "get_current_weather" - ) - assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "What's the weather like in Boston?" + tool_defs = get_tool_definitions(open_ai_span) + assert tool_defs[0]["name"] == "get_current_weather" + assert tool_defs[0]["description"] == "Get the current weather in a given location" + output_messages = get_output_messages(open_ai_span) + tool_parts = [p for p in output_messages[0]["parts"] if p["type"] == "tool_call"] + assert tool_parts[0]["name"] == "get_current_weather" + assert ( + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -125,7 +120,7 @@ def test_open_ai_function_calls_with_events_with_content( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -196,7 +191,7 @@ def test_open_ai_function_calls_with_events_with_no_content( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -240,28 +235,18 @@ def test_open_ai_function_calls_tools( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - == "What's the weather like in Boston?" - ) - assert ( - open_ai_span.attributes[f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.name"] - == "get_current_weather" - ) - assert ( - open_ai_span.attributes[f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.description"] - == "Get the current weather" - ) - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.id"], - str, - ) - assert ( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.name"] - == "get_current_weather" - ) - assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == "What's the weather like in Boston?" + tool_defs = get_tool_definitions(open_ai_span) + assert tool_defs[0]["name"] == "get_current_weather" + assert tool_defs[0]["description"] == "Get the current weather" + output_messages = get_output_messages(open_ai_span) + tool_parts = [p for p in output_messages[0]["parts"] if p["type"] == "tool_call"] + assert isinstance(tool_parts[0]["id"], str) + assert tool_parts[0]["name"] == "get_current_weather" + assert ( + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -289,7 +274,7 @@ def test_open_ai_function_calls_tools_with_events_with_content( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -341,7 +326,7 @@ def test_open_ai_function_calls_tools_with_events_with_no_content( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -392,30 +377,14 @@ async def test_open_ai_function_calls_tools_streaming( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.id"], - str, - ) - assert ( - open_ai_span.attributes.get(f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.name") - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.finish_reason") - == "tool_calls" - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.name" - ) - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.arguments" - ) - == '{"location":"San Francisco, CA"}' - ) + tool_defs = get_tool_definitions(open_ai_span) + assert tool_defs[0]["name"] == "get_current_weather" + output_messages = get_output_messages(open_ai_span) + assert output_messages[0]["finish_reason"] == "tool_call" + tool_parts = [p for p in output_messages[0]["parts"] if p["type"] == "tool_call"] + assert isinstance(tool_parts[0]["id"], str) + assert tool_parts[0]["name"] == "get_current_weather" + assert tool_parts[0]["arguments"] == {"location": "San Francisco, CA"} assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9g4TmLd49mPoD6c0EnGlhNAp8b0on" @@ -559,48 +528,17 @@ def test_open_ai_function_calls_tools_parallel( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] - assert ( - open_ai_span.attributes.get(f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.name") - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.finish_reason") - == "tool_calls" - ) - - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.id"], - str, - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.name" - ) - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.arguments" - ) - == '{"location": "San Francisco"}' - ) - - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.1.id"], - str, - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.1.name" - ) - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.1.arguments" - ) - == '{"location": "Boston"}' - ) + tool_defs = get_tool_definitions(open_ai_span) + assert tool_defs[0]["name"] == "get_current_weather" + output_messages = get_output_messages(open_ai_span) + assert output_messages[0]["finish_reason"] == "tool_call" + tool_parts = [p for p in output_messages[0]["parts"] if p["type"] == "tool_call"] + assert isinstance(tool_parts[0]["id"], str) + assert tool_parts[0]["name"] == "get_current_weather" + assert tool_parts[0]["arguments"] == {"location": "San Francisco"} + assert isinstance(tool_parts[1]["id"], str) + assert tool_parts[1]["name"] == "get_current_weather" + assert tool_parts[1]["arguments"] == {"location": "Boston"} assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9g4cZhrW9CsqihSvXslk0EUtjASsO" @@ -753,48 +691,17 @@ async def test_open_ai_function_calls_tools_streaming_parallel( spans = span_exporter.get_finished_spans() open_ai_span = spans[0] - assert ( - open_ai_span.attributes.get(f"{SpanAttributes.LLM_REQUEST_FUNCTIONS}.0.name") - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.finish_reason") - == "tool_calls" - ) - - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.id"], - str, - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.name" - ) - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.0.arguments" - ) - == '{"location": "San Francisco"}' - ) - - assert isinstance( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.1.id"], - str, - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.1.name" - ) - == "get_current_weather" - ) - assert ( - open_ai_span.attributes.get( - f"{GenAIAttributes.GEN_AI_COMPLETION}.0.tool_calls.1.arguments" - ) - == '{"location": "Boston"}' - ) + tool_defs = get_tool_definitions(open_ai_span) + assert tool_defs[0]["name"] == "get_current_weather" + output_messages = get_output_messages(open_ai_span) + assert output_messages[0]["finish_reason"] == "tool_call" + tool_parts = [p for p in output_messages[0]["parts"] if p["type"] == "tool_call"] + assert isinstance(tool_parts[0]["id"], str) + assert tool_parts[0]["name"] == "get_current_weather" + assert tool_parts[0]["arguments"] == {"location": "San Francisco"} + assert isinstance(tool_parts[1]["id"], str) + assert tool_parts[1]["name"] == "get_current_weather" + assert tool_parts[1]["arguments"] == {"location": "Boston"} assert ( open_ai_span.attributes.get("gen_ai.response.id") == "chatcmpl-9g58noIjRkOeNNxfFsFfcNjhXlul7" @@ -939,7 +846,7 @@ async def test_open_ai_function_calls_tools_streaming_parallel_with_events_with_ def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_prompt_caching.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_prompt_caching.py index e7c8cc34af..da39f5686b 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_prompt_caching.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_prompt_caching.py @@ -7,6 +7,8 @@ gen_ai_attributes as GenAIAttributes, ) +from .utils import get_input_messages, get_output_messages + @pytest.mark.vcr def test_openai_prompt_caching(instrument_legacy, span_exporter, log_exporter): @@ -42,15 +44,16 @@ def test_openai_prompt_caching(instrument_legacy, span_exporter, log_exporter): cache_creation_span = spans[0] cache_read_span = spans[1] - assert cache_creation_span.attributes["gen_ai.prompt.0.role"] == "system" - assert system_message == cache_creation_span.attributes["gen_ai.prompt.0.content"] - assert cache_read_span.attributes["gen_ai.prompt.0.role"] == "system" - assert system_message == cache_read_span.attributes["gen_ai.prompt.0.content"] - - assert cache_creation_span.attributes["gen_ai.prompt.1.role"] == "user" - assert text == cache_creation_span.attributes["gen_ai.prompt.1.content"] - assert cache_read_span.attributes["gen_ai.prompt.1.role"] == "user" - assert text == cache_read_span.attributes["gen_ai.prompt.1.content"] + creation_input = get_input_messages(cache_creation_span) + assert creation_input[0]["role"] == "system" + assert creation_input[0]["parts"][0]["content"] == system_message + assert creation_input[1]["role"] == "user" + assert creation_input[1]["parts"][0]["content"] == text + read_input = get_input_messages(cache_read_span) + assert read_input[0]["role"] == "system" + assert read_input[0]["parts"][0]["content"] == system_message + assert read_input[1]["role"] == "user" + assert read_input[1]["parts"][0]["content"] == text assert ( cache_creation_span.attributes.get("gen_ai.response.id") @@ -61,8 +64,8 @@ def test_openai_prompt_caching(instrument_legacy, span_exporter, log_exporter): == "chatcmpl-BNi420iFNtIOHzy8Gq2fVS5utTus7" ) - assert cache_creation_span.attributes["gen_ai.completion.0.role"] == "assistant" - assert cache_read_span.attributes["gen_ai.completion.0.role"] == "assistant" + assert get_output_messages(cache_creation_span)[0]["role"] == "assistant" + assert get_output_messages(cache_read_span)[0]["role"] == "assistant" assert cache_creation_span.attributes["gen_ai.usage.input_tokens"] == 1149 assert cache_creation_span.attributes["gen_ai.usage.output_tokens"] == 315 @@ -287,15 +290,16 @@ async def test_openai_prompt_caching_async( cache_creation_span = spans[0] cache_read_span = spans[1] - assert cache_creation_span.attributes["gen_ai.prompt.0.role"] == "system" - assert system_message == cache_creation_span.attributes["gen_ai.prompt.0.content"] - assert cache_read_span.attributes["gen_ai.prompt.0.role"] == "system" - assert system_message == cache_read_span.attributes["gen_ai.prompt.0.content"] - - assert cache_creation_span.attributes["gen_ai.prompt.1.role"] == "user" - assert text == cache_creation_span.attributes["gen_ai.prompt.1.content"] - assert cache_read_span.attributes["gen_ai.prompt.1.role"] == "user" - assert text == cache_read_span.attributes["gen_ai.prompt.1.content"] + creation_input = get_input_messages(cache_creation_span) + assert creation_input[0]["role"] == "system" + assert creation_input[0]["parts"][0]["content"] == system_message + assert creation_input[1]["role"] == "user" + assert creation_input[1]["parts"][0]["content"] == text + read_input = get_input_messages(cache_read_span) + assert read_input[0]["role"] == "system" + assert read_input[0]["parts"][0]["content"] == system_message + assert read_input[1]["role"] == "user" + assert read_input[1]["parts"][0]["content"] == text assert ( cache_creation_span.attributes.get("gen_ai.response.id") == "chatcmpl-BNhr79TlegaJvfSOAOH2jsPEpRHMd" @@ -305,8 +309,8 @@ async def test_openai_prompt_caching_async( == "chatcmpl-BNhrEFvKSNY08Uphau5iA4InZH6jn" ) - assert cache_creation_span.attributes["gen_ai.completion.0.role"] == "assistant" - assert cache_read_span.attributes["gen_ai.completion.0.role"] == "assistant" + assert get_output_messages(cache_creation_span)[0]["role"] == "assistant" + assert get_output_messages(cache_read_span)[0]["role"] == "assistant" assert cache_creation_span.attributes["gen_ai.usage.input_tokens"] == 1150 assert cache_creation_span.attributes["gen_ai.usage.output_tokens"] == 293 @@ -500,7 +504,7 @@ async def test_openai_prompt_caching_async_with_events_with_no_content( def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_realtime.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_realtime.py index de0d5b4d4a..9f3514cfae 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_realtime.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_realtime.py @@ -6,6 +6,8 @@ requiring real API connections. """ +import json + import pytest from unittest.mock import AsyncMock, MagicMock from opentelemetry.sdk.trace import TracerProvider @@ -13,7 +15,6 @@ from opentelemetry.semconv._incubating.attributes import ( gen_ai_attributes as GenAIAttributes, ) -from opentelemetry.semconv_ai import SpanAttributes from opentelemetry.trace import StatusCode @@ -472,18 +473,19 @@ async def test_full_text_conversation_flow(self, tracer_provider_and_exporter): assert "openai.realtime" in span_names session_span = next(s for s in spans if s.name == "openai.session") - assert session_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" + assert session_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" assert session_span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4o-realtime-preview" - assert session_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "realtime" + assert session_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" assert session_span.status.status_code == StatusCode.OK response_span = next(s for s in spans if s.name == "openai.realtime") - assert response_span.attributes[GenAIAttributes.GEN_AI_SYSTEM] == "openai" - assert response_span.attributes[SpanAttributes.LLM_REQUEST_TYPE] == "realtime" + assert response_span.attributes[GenAIAttributes.GEN_AI_PROVIDER_NAME] == "openai" + assert response_span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" - # Verify finish_reason is "stop" for text response without tool calls - attrs = dict(response_span.attributes) - assert attrs.get("gen_ai.completion.0.finish_reason") == "stop" + # Verify finish_reasons top-level attribute + assert response_span.attributes[ + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS + ] == ("stop",) @pytest.mark.asyncio async def test_response_span_is_child_of_session_span(self, tracer_provider_and_exporter): @@ -617,14 +619,23 @@ async def test_function_call_flow(self, tracer_provider_and_exporter): response_span = next(s for s in spans if s.name == "openai.realtime") assert response_span.status.status_code == StatusCode.OK - # Verify tool call attributes are set - attrs = dict(response_span.attributes) - assert attrs.get("gen_ai.completion.0.role") == "assistant" - assert attrs.get("gen_ai.completion.0.finish_reason") == "tool_calls" - assert attrs.get("gen_ai.completion.0.tool_calls.0.type") == "function" - assert attrs.get("gen_ai.completion.0.tool_calls.0.name") == "get_weather" - assert attrs.get("gen_ai.completion.0.tool_calls.0.id") == "call_123" - assert attrs.get("gen_ai.completion.0.tool_calls.0.arguments") == '{"location": "NYC"}' + # Verify finish_reasons top-level attribute + assert response_span.attributes[ + GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS + ] == ("tool_call",) + + # Verify output messages in OTel JSON format + output = json.loads( + response_span.attributes[GenAIAttributes.GEN_AI_OUTPUT_MESSAGES] + ) + assert len(output) == 1 + assert output[0]["role"] == "assistant" + assert output[0]["finish_reason"] == "tool_call" + tool_part = output[0]["parts"][0] + assert tool_part["type"] == "tool_call" + assert tool_part["name"] == "get_weather" + assert tool_part["id"] == "call_123" + assert tool_part["arguments"] == {"location": "NYC"} @pytest.mark.asyncio async def test_error_handling_in_response(self, tracer_provider_and_exporter): diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_responses.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_responses.py index 6f9c1ee036..4e6b80ce5b 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_responses.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_responses.py @@ -1,3 +1,4 @@ +import json import pytest from openai import AsyncOpenAI, OpenAI @@ -7,6 +8,8 @@ ) from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter +from .utils import get_input_messages, get_output_messages + @pytest.mark.vcr def test_responses( @@ -20,13 +23,9 @@ def test_responses( assert len(spans) == 1 span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert span.attributes["gen_ai.response.model"] == "gpt-4.1-nano-2025-04-14" - # assert ( - # span.attributes["gen_ai.prompt.0.content"] == "What is the capital of France?" - # ) - # assert span.attributes["gen_ai.prompt.0.role"] == "user" @pytest.mark.vcr @@ -45,7 +44,7 @@ def test_responses_with_request_params( assert len(spans) == 1 span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" # Check that request parameters are captured @@ -104,26 +103,9 @@ def test_responses_with_input_history( assert len(spans) == 2 span = spans[1] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert span.attributes["gen_ai.response.model"] == "gpt-4.1-nano-2025-04-14" - # assert ( - # span.attributes["gen_ai.prompt.0.content"] - # == "Come up with an adjective in English. Respond with just one word." - # ) - # assert span.attributes["gen_ai.prompt.0.role"] == "user" - # assert json.loads(span.attributes["gen_ai.prompt.1.content"]) == [ - # { - # "type": "output_text", - # "text": first_response.output[0].content[0].text, - # } - # ] - # assert span.attributes["gen_ai.prompt.1.role"] == "assistant" - # assert ( - # span.attributes["gen_ai.prompt.2.content"] - # == "Can you explain why you chose that word?" - # ) - # assert span.attributes["gen_ai.prompt.2.role"] == "user" @pytest.mark.vcr @@ -165,29 +147,10 @@ def test_responses_tool_calls( assert len(spans) == 1 span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert span.attributes["gen_ai.response.model"] == "gpt-4.1-nano-2025-04-14" - # assert span.attributes["gen_ai.prompt.0.content"] == "What's the weather in London?" - # assert span.attributes["gen_ai.prompt.0.role"] == "user" - # assert span.attributes["llm.request.functions.0.name"] == "get_weather" - # assert json.loads(span.attributes["llm.request.functions.0.parameters"]) == { - # "type": "object", - # "properties": { - # "location": { - # "type": "string", - # "description": "The city and state, e.g. San Francisco, CA" - # } - # }, - # "required": ["location"] - # } - # assert span.attributes["llm.request.functions.0.description"] == "Get the current weather for a location" - - # assert ( - # span.attributes["gen_ai.completion.0.tool_calls.0.id"] - # == "fc_685ff89422ec819a977b2ea385bc9b6601c537ddeff5c2a2" - # ) assert ( span.attributes["gen_ai.response.id"] == "resp_685ff8928dc4819aac45e085ba66838101c537ddeff5c2a2" @@ -210,16 +173,6 @@ def test_responses_reasoning( spans = span_exporter.get_finished_spans() assert len(spans) == 1 - span = spans[0] - - # assert span.attributes["gen_ai.request.reasoning_effort"] == "low" - # assert span.attributes["gen_ai.request.reasoning_summary"] == () - - # assert span.attributes["gen_ai.response.reasoning_effort"] == "low" - # When reasoning summary is None/empty, the attribute should not be set - assert "gen_ai.completion.0.reasoning" not in span.attributes - - # assert span.attributes["gen_ai.usage.reasoning_tokens"] > 0 @pytest.mark.vcr @@ -245,17 +198,29 @@ def test_responses_reasoning_dict_issue( # The main goal of this test is to ensure that when the API returns reasoning data # as a dict/list, it gets properly serialized as JSON without causing "Invalid type" warnings - # The reasoning should be serialized as JSON since it contains complex data - reasoning_attr = span.attributes["gen_ai.completion.0.reasoning"] - assert isinstance(reasoning_attr, str), "Reasoning should be serialized as a string" + # Reasoning content is embedded in gen_ai.output.messages as a reasoning part + output_messages = get_output_messages(span) + assert len(output_messages) > 0, "Expected at least one output message" - # Should be valid JSON containing reasoning summary data - import json + # Find any reasoning parts across all output messages + reasoning_parts = [ + p for msg in output_messages + for p in msg.get("parts", []) + if p.get("type") == "reasoning" + ] - parsed_reasoning = json.loads(reasoning_attr) - assert isinstance( - parsed_reasoning, (dict, list) - ), "Reasoning should be a dict or list structure" + # If reasoning parts exist, verify their content is a properly serialized string + for part in reasoning_parts: + content = part.get("content") + assert isinstance(content, str), ( + f"Reasoning content should be a string (not raw dict/list), got: {type(content)}" + ) + # If it looks like JSON, verify it parses correctly + if content and content.strip().startswith(("[", "{")): + parsed = json.loads(content) + assert isinstance(parsed, (dict, list)), ( + "Reasoning content that looks like JSON should parse to dict or list" + ) @pytest.mark.vcr @@ -285,14 +250,16 @@ def test_responses_streaming( span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert span.attributes["gen_ai.response.model"] == "gpt-4.1-nano-2025-04-14" assert full_text != "", "Should have received streaming content" - assert span.attributes["gen_ai.prompt.0.content"] == input_text - assert span.attributes["gen_ai.prompt.0.role"] == "user" - assert span.attributes["gen_ai.completion.0.role"] == "assistant" - assert span.attributes["gen_ai.completion.0.content"] == full_text + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == input_text + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" + assert output_messages[0]["parts"][0]["content"] == full_text @pytest.mark.vcr @@ -322,13 +289,15 @@ async def test_responses_streaming_async( span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert full_text != "", "Should have received streaming content" - assert span.attributes["gen_ai.prompt.0.content"] == input_text - assert span.attributes["gen_ai.prompt.0.role"] == "user" - assert span.attributes["gen_ai.completion.0.role"] == "assistant" - assert span.attributes["gen_ai.completion.0.content"] == full_text + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == input_text + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" + assert output_messages[0]["parts"][0]["content"] == full_text @pytest.mark.vcr @@ -355,13 +324,15 @@ def test_responses_streaming_with_content( span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert full_text != "", "Should have received streaming content" - assert span.attributes["gen_ai.prompt.0.content"] == input_text - assert span.attributes["gen_ai.prompt.0.role"] == "user" - assert span.attributes["gen_ai.completion.0.role"] == "assistant" - assert span.attributes["gen_ai.completion.0.content"] == full_text + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == input_text + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" + assert output_messages[0]["parts"][0]["content"] == full_text @pytest.mark.vcr @@ -386,13 +357,15 @@ def test_responses_streaming_with_context_manager( span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert full_text != "", "Should have received streaming content" - assert span.attributes["gen_ai.prompt.0.content"] == input_text - assert span.attributes["gen_ai.prompt.0.role"] == "user" - assert span.attributes["gen_ai.completion.0.role"] == "assistant" - assert span.attributes["gen_ai.completion.0.content"] == full_text + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == input_text + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" + assert output_messages[0]["parts"][0]["content"] == full_text @pytest.mark.vcr @@ -422,13 +395,15 @@ async def test_responses_streaming_async_with_context_manager( span = spans[0] assert span.name == "openai.response" - assert span.attributes["gen_ai.system"] == "openai" + assert span.attributes["gen_ai.provider.name"] == "openai" assert span.attributes["gen_ai.request.model"] == "gpt-4.1-nano" assert full_text != "", "Should have received streaming content" - assert span.attributes["gen_ai.prompt.0.content"] == input_text - assert span.attributes["gen_ai.prompt.0.role"] == "user" - assert span.attributes["gen_ai.completion.0.role"] == "assistant" - assert span.attributes["gen_ai.completion.0.content"] == full_text + input_messages = get_input_messages(span) + assert input_messages[0]["role"] == "user" + assert input_messages[0]["parts"][0]["content"] == input_text + output_messages = get_output_messages(span) + assert output_messages[0]["role"] == "assistant" + assert output_messages[0]["parts"][0]["content"] == full_text def test_get_tools_from_kwargs_with_none(): @@ -654,9 +629,9 @@ def test_responses_streaming_with_parent_span( # Verify streaming worked correctly assert full_text != "", "Should have received streaming content" - assert openai_span.attributes["gen_ai.system"] == "openai" + assert openai_span.attributes["gen_ai.provider.name"] == "openai" assert openai_span.attributes["gen_ai.request.model"] == "gpt-4o" - assert openai_span.attributes["llm.is_streaming"] is True + assert openai_span.attributes["gen_ai.is_streaming"] is True @pytest.mark.vcr @@ -726,9 +701,9 @@ async def test_responses_streaming_async_with_parent_span( # Verify streaming worked correctly assert full_text != "", "Should have received streaming content" - assert openai_span.attributes["gen_ai.system"] == "openai" + assert openai_span.attributes["gen_ai.provider.name"] == "openai" assert openai_span.attributes["gen_ai.request.model"] == "gpt-4o" - assert openai_span.attributes["llm.is_streaming"] is True + assert openai_span.attributes["gen_ai.is_streaming"] is True def test_response_stream_init_with_not_given_reasoning(): diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_semconv_compliance.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_semconv_compliance.py new file mode 100644 index 0000000000..e87822f8c8 --- /dev/null +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_semconv_compliance.py @@ -0,0 +1,676 @@ +"""Tests for semconv compliance fixes from openai-semconv-review.md. + +TDD: These tests are written FIRST, before any implementation changes. +Each test class maps to an issue ID from the review document. +""" + +import json +import time +from unittest.mock import MagicMock, AsyncMock + +import pytest +from opentelemetry.semconv._incubating.attributes import ( + gen_ai_attributes as GenAIAttributes, +) +from opentelemetry.semconv.attributes.server_attributes import SERVER_ADDRESS + +from openai.types.responses import ( + ResponseOutputMessage, + ResponseOutputText, + ResponseFunctionToolCall, +) + +from opentelemetry.instrumentation.openai.shared import ( + metric_shared_attributes, + set_tools_attributes, + _set_functions_attributes, +) +from opentelemetry.instrumentation.openai.shared.chat_wrappers import ( + _accumulate_stream_items, + _map_content_block, + _set_output_messages, +) + + +@pytest.fixture +def mock_span(): + span = MagicMock() + span.is_recording.return_value = True + attrs = {} + + def set_attribute(name, value): + attrs[name] = value + + span.set_attribute = set_attribute + span._attrs = attrs + return span + + +def _get_output_messages(span): + return json.loads(span._attrs[GenAIAttributes.GEN_AI_OUTPUT_MESSAGES]) + + +def _make_message_output(msg_id="msg_001", text="Hi there"): + """Helper to create a proper ResponseOutputMessage.""" + return ResponseOutputMessage( + id=msg_id, + type="message", + status="completed", + role="assistant", + content=[ResponseOutputText(type="output_text", text=text, annotations=[])], + ) + + +def _make_function_call_output(fc_id="fc_001", name="get_weather", args="{}"): + """Helper to create a proper ResponseFunctionToolCall.""" + return ResponseFunctionToolCall( + id=fc_id, + type="function_call", + name=name, + arguments=args, + call_id="call_001", + status="completed", + ) + + +# --------------------------------------------------------------------------- +# P1-1: Responses API must set gen_ai.operation.name on every span +# --------------------------------------------------------------------------- + +class TestP1_1_ResponsesOperationName: + """Every start_span() call in responses_wrappers.py must include + gen_ai.operation.name = 'chat'.""" + + def test_set_data_attributes_sets_operation_name(self, mock_span): + """set_data_attributes should set gen_ai.operation.name = 'chat'.""" + from opentelemetry.instrumentation.openai.v1.responses_wrappers import ( + set_data_attributes, + TracedData, + ) + + traced = TracedData( + start_time=1000, + response_id="resp_123", + input="Hello", + instructions=None, + tools=None, + output_blocks={}, + usage=None, + output_text="Hi", + request_model="gpt-4", + response_model="gpt-4", + ) + set_data_attributes(traced, mock_span) + + assert GenAIAttributes.GEN_AI_OPERATION_NAME in mock_span._attrs, ( + f"Expected '{GenAIAttributes.GEN_AI_OPERATION_NAME}' in span attrs, " + f"got: {list(mock_span._attrs.keys())}" + ) + assert mock_span._attrs[GenAIAttributes.GEN_AI_OPERATION_NAME] == "chat" + + +# --------------------------------------------------------------------------- +# P1-2: Responses API must set gen_ai.response.finish_reasons +# --------------------------------------------------------------------------- + +class TestP1_2_ResponsesFinishReasons: + """set_data_attributes must emit gen_ai.response.finish_reasons.""" + + def test_completed_message_has_stop_finish_reason(self, mock_span): + from opentelemetry.instrumentation.openai.v1.responses_wrappers import ( + set_data_attributes, + TracedData, + ) + + msg = _make_message_output("msg_001", "Hi there") + traced = TracedData( + start_time=1000, + response_id="resp_123", + input="Hello", + instructions=None, + tools=None, + output_blocks={"msg_001": msg}, + usage=None, + output_text="Hi there", + request_model="gpt-4", + response_model="gpt-4", + ) + set_data_attributes(traced, mock_span) + + assert GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS in mock_span._attrs, ( + f"Expected '{GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS}' in span attrs, " + f"got: {list(mock_span._attrs.keys())}" + ) + reasons = mock_span._attrs[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] + assert "stop" in reasons + + def test_function_call_has_tool_call_finish_reason(self, mock_span): + from opentelemetry.instrumentation.openai.v1.responses_wrappers import ( + set_data_attributes, + TracedData, + ) + + fc = _make_function_call_output("fc_001", "get_weather", "{}") + traced = TracedData( + start_time=1000, + response_id="resp_456", + input="What's the weather?", + instructions=None, + tools=None, + output_blocks={"fc_001": fc}, + usage=None, + output_text=None, + request_model="gpt-4", + response_model="gpt-4", + ) + set_data_attributes(traced, mock_span) + + assert GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS in mock_span._attrs + reasons = mock_span._attrs[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] + assert reasons == ("tool_call",), ( + f"Expected exactly ('tool_call',) per OTel spec, got: {reasons}" + ) + + +# --------------------------------------------------------------------------- +# P1-3: Responses API must support gen_ai.input/output.messages JSON path +# --------------------------------------------------------------------------- + +class TestP1_3_ResponsesMessagesAttributes: + """set_data_attributes must emit gen_ai.input.messages / + gen_ai.output.messages as JSON.""" + + def test_input_messages_json_when_flag_enabled(self, mock_span): + from opentelemetry.instrumentation.openai.v1.responses_wrappers import ( + set_data_attributes, + TracedData, + ) + + msg = _make_message_output("msg_001", "Hi there") + traced = TracedData( + start_time=1000, + response_id="resp_789", + input=[ + {"role": "user", "content": "Hello", "type": "message"}, + ], + instructions="Be helpful", + tools=None, + output_blocks={"msg_001": msg}, + usage=None, + output_text="Hi there", + request_model="gpt-4", + response_model="gpt-4", + ) + set_data_attributes(traced, mock_span) + + assert GenAIAttributes.GEN_AI_INPUT_MESSAGES in mock_span._attrs, ( + f"Expected gen_ai.input.messages, " + f"got keys: {list(mock_span._attrs.keys())}" + ) + assert GenAIAttributes.GEN_AI_OUTPUT_MESSAGES in mock_span._attrs, ( + f"Expected gen_ai.output.messages, " + f"got keys: {list(mock_span._attrs.keys())}" + ) + + input_msgs = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_INPUT_MESSAGES]) + assert isinstance(input_msgs, list) + + output_msgs = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_OUTPUT_MESSAGES]) + assert isinstance(output_msgs, list) + + def test_string_input_as_user_message(self, mock_span): + from opentelemetry.instrumentation.openai.v1.responses_wrappers import ( + set_data_attributes, + TracedData, + ) + + msg = _make_message_output("msg_001", "4") + traced = TracedData( + start_time=1000, + response_id="resp_str", + input="What is 2+2?", + instructions=None, + tools=None, + output_blocks={"msg_001": msg}, + usage=None, + output_text="4", + request_model="gpt-4", + response_model="gpt-4", + ) + set_data_attributes(traced, mock_span) + + assert GenAIAttributes.GEN_AI_INPUT_MESSAGES in mock_span._attrs + input_msgs = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_INPUT_MESSAGES]) + assert input_msgs[0]["role"] == "user" + + +# --------------------------------------------------------------------------- +# P1-4: Streaming must accumulate reasoning/thinking blocks +# --------------------------------------------------------------------------- + +class TestP1_4_StreamingReasoningAccumulation: + """_accumulate_stream_items must capture reasoning_content from deltas.""" + + def test_reasoning_content_accumulated(self): + complete_response = {"choices": [], "model": "o3-mini", "id": "cmpl-1"} + + # First chunk: role + item1 = { + "model": "o3-mini", + "id": "cmpl-1", + "choices": [{"index": 0, "delta": {"role": "assistant"}, "finish_reason": None}], + } + _accumulate_stream_items(item1, complete_response) + + # Second chunk: reasoning_content + item2 = { + "model": "o3-mini", + "id": "cmpl-1", + "choices": [{"index": 0, "delta": {"reasoning_content": "Let me think..."}, "finish_reason": None}], + } + _accumulate_stream_items(item2, complete_response) + + # Third chunk: more reasoning + item3 = { + "model": "o3-mini", + "id": "cmpl-1", + "choices": [{"index": 0, "delta": {"reasoning_content": " The answer is 3."}, "finish_reason": None}], + } + _accumulate_stream_items(item3, complete_response) + + # Fourth chunk: regular content + item4 = { + "model": "o3-mini", + "id": "cmpl-1", + "choices": [{"index": 0, "delta": {"content": "There are 3 r's."}, "finish_reason": None}], + } + _accumulate_stream_items(item4, complete_response) + + msg = complete_response["choices"][0]["message"] + assert msg["content"] == "There are 3 r's." + assert msg.get("reasoning_content") == "Let me think... The answer is 3.", ( + f"Expected accumulated reasoning_content, got: {msg}" + ) + + def test_reasoning_content_in_output_messages(self, mock_span): + """Reasoning content should become a 'reasoning' part in output messages.""" + choices = [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "3 r's", + "reasoning_content": "Let me count...", + }, + "finish_reason": "stop", + } + ] + _set_output_messages(mock_span, choices) + result = _get_output_messages(mock_span) + + parts = result[0]["parts"] + reasoning_parts = [p for p in parts if p.get("type") == "reasoning"] + assert len(reasoning_parts) == 1, ( + f"Expected 1 reasoning part, got parts: {parts}" + ) + assert reasoning_parts[0]["content"] == "Let me count..." + + +# --------------------------------------------------------------------------- +# P2-1: _map_content_block must distinguish base64 data URIs from URLs +# --------------------------------------------------------------------------- + +class TestP2_1_Base64ImageMapping: + """Base64 inline images should map to BlobPart, not UriPart.""" + + def test_regular_url_maps_to_uri_part(self): + block = {"type": "image_url", "image_url": {"url": "https://example.com/img.png"}} + result = _map_content_block(block) + assert result["type"] == "uri" + assert result["uri"] == "https://example.com/img.png" + + def test_base64_image_maps_to_blob_part(self): + data_uri = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUg..." + block = {"type": "image_url", "image_url": {"url": data_uri}} + result = _map_content_block(block) + assert result["type"] == "blob", ( + f"Expected 'blob' type for base64 data URI, got: {result}" + ) + assert result["modality"] == "image" + assert result["mime_type"] == "image/png" + assert result["content"] == "iVBORw0KGgoAAAANSUhEUg..." + + def test_base64_jpeg_image(self): + data_uri = "data:image/jpeg;base64,/9j/4AAQSkZJRg..." + block = {"type": "image_url", "image_url": {"url": data_uri}} + result = _map_content_block(block) + assert result["type"] == "blob" + assert result["mime_type"] == "image/jpeg" + assert result["content"] == "/9j/4AAQSkZJRg..." + + +# --------------------------------------------------------------------------- +# P2-2: gen_ai.tool.definitions must use JSON +# --------------------------------------------------------------------------- + +class TestP2_2_ToolDefinitionsJson: + """set_tools_attributes and _set_functions_attributes should emit a single + JSON string attribute for gen_ai.tool.definitions.""" + + def test_tools_as_json(self, mock_span): + tools = [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "Get weather", + "parameters": {"type": "object", "properties": {}}, + }, + } + ] + set_tools_attributes(mock_span, tools) + + assert GenAIAttributes.GEN_AI_TOOL_DEFINITIONS in mock_span._attrs, ( + f"Expected single '{GenAIAttributes.GEN_AI_TOOL_DEFINITIONS}' key, " + f"got: {list(mock_span._attrs.keys())}" + ) + parsed = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_TOOL_DEFINITIONS]) + assert isinstance(parsed, list) + assert len(parsed) == 1 + assert parsed[0]["type"] == "function" + assert parsed[0]["name"] == "get_weather" + + def test_functions_as_json(self, mock_span): + functions = [ + { + "name": "search", + "description": "Search the web", + "parameters": {"type": "object", "properties": {}}, + } + ] + _set_functions_attributes(mock_span, functions) + + assert GenAIAttributes.GEN_AI_TOOL_DEFINITIONS in mock_span._attrs, ( + f"Expected single '{GenAIAttributes.GEN_AI_TOOL_DEFINITIONS}' key, " + f"got: {list(mock_span._attrs.keys())}" + ) + parsed = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_TOOL_DEFINITIONS]) + assert isinstance(parsed, list) + assert parsed[0]["type"] == "function" + assert parsed[0]["name"] == "search" + + def test_tools_emits_json_format(self, mock_span): + """Tools always use JSON format (gen_ai.tool.definitions as JSON array).""" + tools = [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "Get weather", + "parameters": {"type": "object", "properties": {}}, + }, + } + ] + set_tools_attributes(mock_span, tools) + + assert GenAIAttributes.GEN_AI_TOOL_DEFINITIONS in mock_span._attrs, ( + f"Expected '{GenAIAttributes.GEN_AI_TOOL_DEFINITIONS}' key, " + f"got: {list(mock_span._attrs.keys())}" + ) + parsed = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_TOOL_DEFINITIONS]) + assert isinstance(parsed, list) + assert parsed[0]["name"] == "get_weather" + + +# --------------------------------------------------------------------------- +# P2-3: _set_output_messages must handle refusal content +# --------------------------------------------------------------------------- + +class TestP2_3_OutputRefusal: + """Refusal in output messages should be captured as a refusal part.""" + + def test_refusal_captured_in_output_messages(self, mock_span): + choices = [ + { + "index": 0, + "message": { + "role": "assistant", + "content": None, + "refusal": "I cannot help with that request.", + }, + "finish_reason": "stop", + } + ] + _set_output_messages(mock_span, choices) + result = _get_output_messages(mock_span) + + assert len(result) == 1 + msg = result[0] + refusal_parts = [p for p in msg["parts"] if p.get("type") == "refusal"] + text_with_refusal = [p for p in msg["parts"] + if "cannot help" in (p.get("content") or "")] + assert refusal_parts or text_with_refusal, ( + f"Expected refusal to be captured in output parts, got: {msg['parts']}" + ) + + +# --------------------------------------------------------------------------- +# P2-4: Metrics must map finish reason values correctly +# --------------------------------------------------------------------------- + +class TestP2_4_MetricsFinishReasonMapping: + """Choice counter metrics should use mapped finish reason constant key.""" + + def test_finish_reason_uses_correct_attribute_key(self): + from opentelemetry.instrumentation.openai.shared.chat_wrappers import ( + _set_choice_counter_metrics, + ) + mock_counter = MagicMock() + choices = [ + {"index": 0, "finish_reason": "tool_calls"}, + ] + shared_attrs = {"gen_ai.operation.name": "chat"} + + _set_choice_counter_metrics(mock_counter, choices, shared_attrs) + + calls = mock_counter.add.call_args_list + assert len(calls) > 0, "Expected at least one counter add call" + # The attribute key used should be the mapped key + for call in calls: + attrs = call.kwargs.get("attributes") or call[1].get("attributes", {}) + # Check that finish_reason value is the OTel canonical value + for key, val in attrs.items(): + if "finish_reason" in key: + assert val == "tool_call", ( + f"Expected OTel canonical 'tool_call', got '{val}'" + ) + + +# --------------------------------------------------------------------------- +# Reasoning attrs must be ABSENT (not empty tuple) when value is None +# --------------------------------------------------------------------------- + +class TestReasoningAttrsOmittedWhenNone: + """When reasoning fields are None, _set_span_attribute must skip them + entirely — not emit an empty tuple ().""" + + def test_responses_reasoning_attrs_absent_when_none(self, mock_span): + from opentelemetry.instrumentation.openai.v1.responses_wrappers import ( + set_data_attributes, + TracedData, + ) + from opentelemetry.semconv_ai import SpanAttributes + + traced = TracedData( + start_time=1000, + response_id="resp_none", + input="Hi", + instructions=None, + tools=None, + output_blocks={}, + usage=None, + output_text="Hello", + request_model="gpt-4", + response_model="gpt-4", + request_reasoning_summary=None, + request_reasoning_effort=None, + response_reasoning_effort=None, + ) + set_data_attributes(traced, mock_span) + + for attr_name in ( + SpanAttributes.GEN_AI_REQUEST_REASONING_SUMMARY, + SpanAttributes.GEN_AI_REQUEST_REASONING_EFFORT, + SpanAttributes.GEN_AI_RESPONSE_REASONING_EFFORT, + ): + assert attr_name not in mock_span._attrs, ( + f"Attribute '{attr_name}' should be ABSENT when value is None, " + f"but it was set to: {mock_span._attrs.get(attr_name)!r}" + ) + + def test_chat_reasoning_effort_absent_when_none(self, mock_span): + from opentelemetry.instrumentation.openai.shared.chat_wrappers import ( + _handle_request, + ) + from opentelemetry.semconv_ai import SpanAttributes + + # Simulate a request without reasoning_effort + _handle_request(mock_span, {"model": "gpt-4", "messages": []}) + + assert SpanAttributes.GEN_AI_REQUEST_REASONING_EFFORT not in mock_span._attrs, ( + f"Attribute should be ABSENT when reasoning_effort not provided, " + f"but was set to: {mock_span._attrs.get(SpanAttributes.GEN_AI_REQUEST_REASONING_EFFORT)!r}" + ) + + +# --------------------------------------------------------------------------- +# P2-3b: Partial stream cleanup must emit gen_ai.output.messages +# --------------------------------------------------------------------------- + +class TestPartialStreamCleanupOutputMessages: + """ChatStream._ensure_cleanup must call _set_completions so that + gen_ai.output.messages is emitted even on abrupt stream teardown.""" + + def test_ensure_cleanup_sets_output_messages(self, mock_span): + from opentelemetry.instrumentation.openai.shared.chat_wrappers import ( + ChatStream, + _accumulate_stream_items, + ) + + # Create a ChatStream with a MagicMock response (ObjectProxy needs a real object) + mock_response = MagicMock() + stream = ChatStream( + span=mock_span, + response=mock_response, + instance=None, + start_time=time.time(), + request_kwargs={"model": "gpt-4"}, + ) + + # Simulate partial accumulation (as if some chunks were received) + _accumulate_stream_items( + { + "model": "gpt-4", + "id": "cmpl-partial", + "choices": [{"index": 0, "delta": {"role": "assistant"}, "finish_reason": None}], + }, + stream._complete_response, + ) + _accumulate_stream_items( + { + "model": "gpt-4", + "id": "cmpl-partial", + "choices": [{"index": 0, "delta": {"content": "Partial answer"}, "finish_reason": None}], + }, + stream._complete_response, + ) + + # Trigger cleanup (simulates GC or abrupt teardown) + stream._ensure_cleanup() + + assert GenAIAttributes.GEN_AI_OUTPUT_MESSAGES in mock_span._attrs, ( + f"Expected gen_ai.output.messages after partial cleanup, " + f"got keys: {list(mock_span._attrs.keys())}" + ) + output_msgs = json.loads(mock_span._attrs[GenAIAttributes.GEN_AI_OUTPUT_MESSAGES]) + assert len(output_msgs) > 0 + assert output_msgs[0]["role"] == "assistant" + text_parts = [p for p in output_msgs[0]["parts"] if p.get("type") == "text"] + assert any("Partial answer" in p.get("content", "") for p in text_parts), ( + f"Expected partial content in output messages, got: {output_msgs}" + ) + + +# --------------------------------------------------------------------------- +# P2-5: Realtime gen_ai.system_instructions must be parts array JSON +# --------------------------------------------------------------------------- + +class TestP2_5_RealtimeSystemInstructions: + """gen_ai.system_instructions should be JSON parts array, not raw string.""" + + @pytest.mark.asyncio + async def test_system_instructions_as_parts_array(self): + from opentelemetry.instrumentation.openai.v1.realtime_wrappers import ( + RealtimeSessionWrapper, + RealtimeSessionState, + ) + + mock_tracer = MagicMock() + mock_span = MagicMock() + mock_span.is_recording.return_value = True + attrs = {} + mock_span.set_attribute = lambda k, v: attrs.__setitem__(k, v) + + state = RealtimeSessionState(mock_tracer, "gpt-4o-realtime-preview") + state.session_span = mock_span + + mock_session = MagicMock() + mock_session.update = AsyncMock() + + wrapper = RealtimeSessionWrapper(mock_session, state) + await wrapper.update(session={ + "instructions": "You are a helpful assistant.", + }) + + val = attrs.get(GenAIAttributes.GEN_AI_SYSTEM_INSTRUCTIONS) + assert val is not None, "gen_ai.system_instructions should be set" + parsed = json.loads(val) + assert isinstance(parsed, list), ( + f"Expected JSON array, got: {type(parsed)}" + ) + assert parsed[0]["type"] == "text" + assert parsed[0]["content"] == "You are a helpful assistant." + + +# --------------------------------------------------------------------------- +# P3-1: metric_shared_attributes must use constants, not hardcoded strings +# --------------------------------------------------------------------------- + +class TestP3_1_MetricAttributeConstants: + """'server.address' key should use upstream constant.""" + + def test_server_address_uses_constant(self): + attrs = metric_shared_attributes( + response_model="gpt-4", + operation="chat", + server_address="https://api.openai.com/v1/", + ) + assert SERVER_ADDRESS in attrs, ( + f"Expected '{SERVER_ADDRESS}' key (from constant), got: {list(attrs.keys())}" + ) + + +# --------------------------------------------------------------------------- +# P3-2: _map_content_block must wrap unrecognized types +# --------------------------------------------------------------------------- + +class TestP3_2_UnrecognizedBlockWrapping: + """Unrecognized block types should not pass through raw.""" + + def test_unknown_block_type_wrapped(self): + block = {"type": "custom_widget", "data": "something"} + result = _map_content_block(block) + assert result.get("type") == "custom_widget" + assert result != block or "type" in result, ( + "Unrecognized blocks should be wrapped, not passed through raw" + ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_span_context_propagation.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_span_context_propagation.py index dec1cd1bb8..4918d0f0a1 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_span_context_propagation.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_span_context_propagation.py @@ -20,7 +20,8 @@ def assert_event_has_span_context(log: ReadableLogRecord, expected_trace_id: int ) # Verify it's a proper OpenAI event - assert log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) == GenAIAttributes.GenAiSystemValues.OPENAI.value + provider = log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) + assert provider == GenAIAttributes.GenAiSystemValues.OPENAI.value def test_span_context_propagation_with_mock_client( diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_streaming_with_api_usage.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_streaming_with_api_usage.py index 1faca441ee..72c72450e4 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_streaming_with_api_usage.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_streaming_with_api_usage.py @@ -41,7 +41,7 @@ def test_streaming_with_api_usage_capture( # Check that token usage is captured from API response assert span.attributes.get(GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS) > 0 assert span.attributes.get(GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS) > 0 - assert span.attributes.get(SpanAttributes.LLM_USAGE_TOTAL_TOKENS) > 0 + assert span.attributes.get(SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS) > 0 # Verify that the response content is meaningful assert len(response_content) > 0 diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/test_vision.py b/packages/opentelemetry-instrumentation-openai/tests/traces/test_vision.py index b1aa7c642b..29261c434d 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/test_vision.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/test_vision.py @@ -1,5 +1,4 @@ import base64 -import json import pytest import requests @@ -9,6 +8,8 @@ ) from opentelemetry.semconv_ai import SpanAttributes +from .utils import get_input_messages, get_output_messages + @pytest.mark.vcr def test_vision(instrument_legacy, span_exporter, log_exporter, openai_client): @@ -38,19 +39,19 @@ def test_vision(instrument_legacy, span_exporter, log_exporter, openai_client): "openai.chat", ] open_ai_span = spans[0] - assert json.loads( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - ) == [ - {"type": "text", "text": "What is in this image?"}, - { - "type": "image_url", - "image_url": {"url": "https://source.unsplash.com/8xznAGy4HcY/800x400"}, - }, - ] - - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + parts = input_messages[0]["parts"] + text_parts = [p for p in parts if p.get("type") == "text"] + uri_parts = [p for p in parts if p.get("type") == "uri"] + assert text_parts[0]["content"] == "What is in this image?" + assert len(uri_parts) == 1 + assert uri_parts[0]["uri"] == "https://source.unsplash.com/8xznAGy4HcY/800x400" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -95,7 +96,7 @@ def test_vision_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -166,7 +167,7 @@ def test_vision_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -224,19 +225,20 @@ def test_vision_base64(instrument_legacy, span_exporter, log_exporter, openai_cl "openai.chat", ] open_ai_span = spans[0] - assert json.loads( - open_ai_span.attributes[f"{GenAIAttributes.GEN_AI_PROMPT}.0.content"] - ) == [ - {"type": "text", "text": "What is in this image?"}, - { - "type": "image_url", - "image_url": {"url": "/some/url"}, - }, - ] - - assert open_ai_span.attributes.get(f"{GenAIAttributes.GEN_AI_COMPLETION}.0.content") + input_messages = get_input_messages(open_ai_span) + assert input_messages[0]["role"] == "user" + parts = input_messages[0]["parts"] + text_parts = [p for p in parts if p.get("type") == "text"] + uri_parts = [p for p in parts if p.get("type") == "uri"] + assert text_parts[0]["content"] == "What is in this image?" + assert len(uri_parts) == 1 + # base64 images are replaced with /some/url + assert uri_parts[0]["uri"] == "/some/url" + output_messages = get_output_messages(open_ai_span) + assert len(output_messages) == 1 + assert output_messages[0]["role"] == "assistant" assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -291,7 +293,7 @@ def test_vision_base64_with_events_with_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -370,7 +372,7 @@ def test_vision_base64_with_events_with_no_content( ] open_ai_span = spans[0] assert ( - open_ai_span.attributes[SpanAttributes.LLM_OPENAI_API_BASE] + open_ai_span.attributes[SpanAttributes.GEN_AI_OPENAI_API_BASE] == "https://api.openai.com/v1/" ) assert ( @@ -393,7 +395,7 @@ def test_vision_base64_with_events_with_no_content( def assert_message_in_logs(log: ReadableLogRecord, event_name: str, expected_content: dict): assert log.log_record.event_name == event_name assert ( - log.log_record.attributes.get(GenAIAttributes.GEN_AI_SYSTEM) + log.log_record.attributes.get(GenAIAttributes.GEN_AI_PROVIDER_NAME) == GenAIAttributes.GenAiSystemValues.OPENAI.value ) diff --git a/packages/opentelemetry-instrumentation-openai/tests/traces/utils.py b/packages/opentelemetry-instrumentation-openai/tests/traces/utils.py index 0db9c16c94..cfda1b714c 100644 --- a/packages/opentelemetry-instrumentation-openai/tests/traces/utils.py +++ b/packages/opentelemetry-instrumentation-openai/tests/traces/utils.py @@ -1,4 +1,5 @@ import httpx +import json from opentelemetry.sdk.trace import Span from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator from opentelemetry.trace.propagation import get_current_span @@ -17,6 +18,18 @@ def wrapper(self, *args, **kwargs): return wrapper +def get_input_messages(span): + return json.loads(span.attributes["gen_ai.input.messages"]) + + +def get_output_messages(span): + return json.loads(span.attributes["gen_ai.output.messages"]) + + +def get_tool_definitions(span): + return json.loads(span.attributes["gen_ai.tool.definitions"]) + + def assert_request_contains_tracecontext(request: httpx.Request, expected_span: Span): assert TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME in request.headers ctx = TraceContextTextMapPropagator().extract(request.headers) diff --git a/packages/opentelemetry-instrumentation-openai/uv.lock b/packages/opentelemetry-instrumentation-openai/uv.lock index c739773ccc..31453dc923 100644 --- a/packages/opentelemetry-instrumentation-openai/uv.lock +++ b/packages/opentelemetry-instrumentation-openai/uv.lock @@ -546,7 +546,7 @@ wheels = [ [[package]] name = "opentelemetry-instrumentation-openai" -version = "0.53.3" +version = "0.54.0" source = { editable = "." } dependencies = [ { name = "opentelemetry-api" },