Loosen openai version for instrumentation + linting

Author: alizenhom

Diff for: instrumentation/opentelemetry-instrumentation-openai/pyproject.toml

@@ -26,12 +26,12 @@ classifiers = [
 ]
 dependencies = [
   "opentelemetry-api ~= 1.12",
-  "opentelemetry-instrumentation == 0.48b0.dev",
+  "opentelemetry-instrumentation == 0.47b0",
 ]
 
 [project.optional-dependencies]
 instruments = [
-  "openai ~= 1.37.1",
+  "openai >= 0.27.0",
 ]
 
 [project.entry-points.opentelemetry_instrumentor]

Diff for: instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/__init__.py

@@ -48,7 +48,7 @@
 from opentelemetry.trace import get_tracer
 from wrapt import wrap_function_wrapper
 from langtrace_python_sdk.instrumentation.openai.patch import (
-    chat_completions_create
+    chat_completions_create,
 )
 
 
@@ -58,16 +58,16 @@ def instrumentation_dependencies(self) -> Collection[str]:
         return _instruments
 
     def _instrument(self, **kwargs):
-        """Enable OpenAI instrumentation.
-        """
+        """Enable OpenAI instrumentation."""
         tracer_provider = kwargs.get("tracer_provider")
         tracer = get_tracer(__name__, "", tracer_provider)
         version = importlib.metadata.version("openai")
-
         wrap_function_wrapper(
             "openai.resources.chat.completions",
             "Completions.create",
-            chat_completions_create("openai.chat.completions.create", version, tracer),
+            chat_completions_create(
+                "openai.chat.completions.create", version, tracer
+            ),
         )
 
     def _uninstrument(self, **kwargs):

Diff for: instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/package.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 
 
-_instruments = ("openai ~= 1.37.1",)
+_instruments = ("openai >= 0.27.0",)

Diff for: instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/patch.py

@@ -19,7 +19,12 @@
 from opentelemetry.trace.propagation import set_span_in_context
 from openai._types import NOT_GIVEN
 from span_attributes import SpanAttributes, LLMSpanAttributes, Event
-from utils import estimate_tokens, silently_fail, extract_content, calculate_prompt_tokens
+from utils import (
+    estimate_tokens,
+    silently_fail,
+    extract_content,
+    calculate_prompt_tokens,
+)
 
 
 def chat_completions_create(original_method, version, tracer):
@@ -34,7 +39,11 @@ def traced_method(wrapped, instance, args, kwargs):
                 for tool_call in tools:
                     tool_call_dict = {
                         "id": tool_call.id if hasattr(tool_call, "id") else "",
-                        "type": tool_call.type if hasattr(tool_call, "type") else "",
+                        "type": (
+                            tool_call.type
+                            if hasattr(tool_call, "type")
+                            else ""
+                        ),
                     }
                     if hasattr(tool_call, "function"):
                         tool_call_dict["function"] = {
@@ -125,9 +134,14 @@ def _set_input_attributes(span, kwargs, attributes):
     for field, value in attributes.model_dump(by_alias=True).items():
         set_span_attribute(span, field, value)
 
-    if kwargs.get("functions") is not None and kwargs.get("functions") != NOT_GIVEN:
+    if (
+        kwargs.get("functions") is not None
+        and kwargs.get("functions") != NOT_GIVEN
+    ):
         for function in kwargs.get("functions"):
-            tools.append(json.dumps({"type": "function", "function": function}))
+            tools.append(
+                json.dumps({"type": "function", "function": function})
+            )
 
     if kwargs.get("tools") is not None and kwargs.get("tools") != NOT_GIVEN:
         tools.append(json.dumps(kwargs.get("tools")))
@@ -149,7 +163,11 @@ def _set_response_attributes(span, kwargs, result):
                 ),
                 "content": extract_content(choice),
                 **(
-                    {"content_filter_results": choice["content_filter_results"]}
+                    {
+                        "content_filter_results": choice[
+                            "content_filter_results"
+                        ]
+                    }
                     if "content_filter_results" in choice
                     else {}
                 ),
@@ -239,7 +257,9 @@ def is_streaming(kwargs):
     )
 
 
-def get_llm_request_attributes(kwargs, prompts=None, model=None, operation_name="chat"):
+def get_llm_request_attributes(
+    kwargs, prompts=None, model=None, operation_name="chat"
+):
 
     user = kwargs.get("user", None)
     if prompts is None:
@@ -267,7 +287,9 @@ def get_llm_request_attributes(kwargs, prompts=None, model=None, operation_name=
         SpanAttributes.LLM_USER: user,
         SpanAttributes.LLM_REQUEST_TOP_P: top_p,
         SpanAttributes.LLM_REQUEST_MAX_TOKENS: kwargs.get("max_tokens"),
-        SpanAttributes.LLM_SYSTEM_FINGERPRINT: kwargs.get("system_fingerprint"),
+        SpanAttributes.LLM_SYSTEM_FINGERPRINT: kwargs.get(
+            "system_fingerprint"
+        ),
         SpanAttributes.LLM_PRESENCE_PENALTY: kwargs.get("presence_penalty"),
         SpanAttributes.LLM_FREQUENCY_PENALTY: kwargs.get("frequency_penalty"),
         SpanAttributes.LLM_REQUEST_SEED: kwargs.get("seed"),
@@ -283,7 +305,12 @@ class StreamWrapper:
     span: Span
 
     def __init__(
-        self, stream, span, prompt_tokens, function_call=False, tool_calls=False
+        self,
+        stream,
+        span,
+        prompt_tokens,
+        function_call=False,
+        tool_calls=False,
     ):
         self.stream = stream
         self.span = span
@@ -416,7 +443,11 @@ def process_chunk(self, chunk):
                                 content.append(tool_call.function.arguments)
             set_event_completion_chunk(
                 self.span,
-                "".join(content) if len(content) > 0 and content[0] is not None else "",
+                (
+                    "".join(content)
+                    if len(content) > 0 and content[0] is not None
+                    else ""
+                ),
             )
             if content:
                 self.result_content.append(content[0])
@@ -427,12 +458,18 @@ def process_chunk(self, chunk):
             content = [chunk.text]
             set_event_completion_chunk(
                 self.span,
-                "".join(content) if len(content) > 0 and content[0] is not None else "",
+                (
+                    "".join(content)
+                    if len(content) > 0 and content[0] is not None
+                    else ""
+                ),
             )
 
             if content:
                 self.result_content.append(content[0])
 
         if hasattr(chunk, "usage_metadata"):
-            self.completion_tokens = chunk.usage_metadata.candidates_token_count
+            self.completion_tokens = (
+                chunk.usage_metadata.candidates_token_count
+            )
             self.prompt_tokens = chunk.usage_metadata.prompt_token_count

Diff for: instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/span_attributes.py

@@ -80,133 +80,139 @@ class LLMSpanAttributes(BaseModel):
     model_config = ConfigDict(extra="allow")
     gen_ai_operation_name: str = Field(
         ...,
-        alias='gen_ai.operation.name',
-        description='The name of the operation being performed.',
+        alias="gen_ai.operation.name",
+        description="The name of the operation being performed.",
     )
     gen_ai_request_model: str = Field(
         ...,
-        alias='gen_ai.request.model',
-        description='Model name from the input request',
+        alias="gen_ai.request.model",
+        description="Model name from the input request",
     )
     gen_ai_response_model: Optional[str] = Field(
-        None, alias='gen_ai.response.model', description='Model name from the response'
+        None,
+        alias="gen_ai.response.model",
+        description="Model name from the response",
     )
     gen_ai_request_temperature: Optional[float] = Field(
         None,
-        alias='gen_ai.request.temperature',
-        description='Temperature value from the input request',
+        alias="gen_ai.request.temperature",
+        description="Temperature value from the input request",
     )
     gen_ai_request_logit_bias: Optional[str] = Field(
         None,
-        alias='gen_ai.request.logit_bias',
-        description='Likelihood bias of the specified tokens the input request.',
+        alias="gen_ai.request.logit_bias",
+        description="Likelihood bias of the specified tokens the input request.",
     )
     gen_ai_request_logprobs: Optional[bool] = Field(
         None,
-        alias='gen_ai.request.logprobs',
-        description='Logprobs flag returns log probabilities.',
+        alias="gen_ai.request.logprobs",
+        description="Logprobs flag returns log probabilities.",
     )
     gen_ai_request_top_logprobs: Optional[float] = Field(
         None,
-        alias='gen_ai.request.top_logprobs',
-        description='Integer between 0 and 5 specifying the number of most likely tokens to return.',
+        alias="gen_ai.request.top_logprobs",
+        description="Integer between 0 and 5 specifying the number of most likely tokens to return.",
     )
     gen_ai_request_top_p: Optional[float] = Field(
         None,
-        alias='gen_ai.request.top_p',
-        description='Top P value from the input request',
+        alias="gen_ai.request.top_p",
+        description="Top P value from the input request",
     )
     gen_ai_request_top_k: Optional[float] = Field(
         None,
-        alias='gen_ai.request.top_k',
-        description='Top K results to return from the input request',
+        alias="gen_ai.request.top_k",
+        description="Top K results to return from the input request",
     )
     gen_ai_user: Optional[str] = Field(
-        None, alias='gen_ai.user', description='User ID from the input request'
+        None, alias="gen_ai.user", description="User ID from the input request"
     )
     gen_ai_prompt: Optional[str] = Field(
-        None, alias='gen_ai.prompt', description='Prompt text from the input request'
+        None,
+        alias="gen_ai.prompt",
+        description="Prompt text from the input request",
     )
     gen_ai_completion: Optional[str] = Field(
         None,
-        alias='gen_ai.completion',
+        alias="gen_ai.completion",
         description='Completion text from the response. This will be an array of json objects with the following format {"role": "", "content": ""}. Role can be one of the following values: [system, user, assistant, tool]',
     )
     gen_ai_request_stream: Optional[bool] = Field(
         None,
-        alias='gen_ai.request.stream',
-        description='Stream flag from the input request',
+        alias="gen_ai.request.stream",
+        description="Stream flag from the input request",
     )
     gen_ai_request_encoding_formats: Optional[List[str]] = Field(
         None,
-        alias='gen_ai.request.encoding_formats',
+        alias="gen_ai.request.encoding_formats",
         description="Encoding formats from the input request. Allowed values: ['float', 'int8','uint8', 'binary', 'ubinary', 'base64']",
     )
     gen_ai_completion_chunk: Optional[str] = Field(
         None,
-        alias='gen_ai.completion.chunk',
-        description='Chunk text from the response',
+        alias="gen_ai.completion.chunk",
+        description="Chunk text from the response",
     )
     gen_ai_response_finish_reasons: Optional[List[str]] = Field(
         None,
-        alias='gen_ai.response.finish_reasons',
-        description='Array of reasons the model stopped generating tokens, corresponding to each generation received',
+        alias="gen_ai.response.finish_reasons",
+        description="Array of reasons the model stopped generating tokens, corresponding to each generation received",
     )
     gen_ai_system_fingerprint: Optional[str] = Field(
         None,
-        alias='gen_ai.system_fingerprint',
-        description='System fingerprint of the system that generated the response',
+        alias="gen_ai.system_fingerprint",
+        description="System fingerprint of the system that generated the response",
     )
     gen_ai_request_tool_choice: Optional[str] = Field(
         None,
-        alias='gen_ai.request.tool_choice',
-        description='Tool choice from the input request',
+        alias="gen_ai.request.tool_choice",
+        description="Tool choice from the input request",
     )
     gen_ai_response_tool_calls: Optional[str] = Field(
         None,
-        alias='gen_ai.response.tool_calls',
-        description='Array of tool calls from the response json stringified',
+        alias="gen_ai.response.tool_calls",
+        description="Array of tool calls from the response json stringified",
     )
     gen_ai_request_max_tokens: Optional[float] = Field(
         None,
-        alias='gen_ai.request.max_tokens',
-        description='The maximum number of tokens the LLM generates for a request.',
+        alias="gen_ai.request.max_tokens",
+        description="The maximum number of tokens the LLM generates for a request.",
     )
     gen_ai_usage_input_tokens: Optional[float] = Field(
         None,
-        alias='gen_ai.usage.input_tokens',
-        description='The number of tokens used in the llm prompt.',
+        alias="gen_ai.usage.input_tokens",
+        description="The number of tokens used in the llm prompt.",
     )
     gen_ai_usage_total_tokens: Optional[float] = Field(
         None,
-        alias='gen_ai.usage.total_tokens',
-        description='The total number of tokens used in the llm request.',
+        alias="gen_ai.usage.total_tokens",
+        description="The total number of tokens used in the llm request.",
     )
     gen_ai_usage_output_tokens: Optional[float] = Field(
         None,
-        alias='gen_ai.usage.output_tokens',
-        description='The number of tokens in the llm response.',
+        alias="gen_ai.usage.output_tokens",
+        description="The number of tokens in the llm response.",
     )
     gen_ai_request_seed: Optional[str] = Field(
-        None, alias='gen_ai.request.seed', description='Seed from the input request'
+        None,
+        alias="gen_ai.request.seed",
+        description="Seed from the input request",
     )
     gen_ai_request_frequency_penalty: Optional[float] = Field(
         None,
-        alias='gen_ai.request.frequency_penalty',
-        description='Frequency penalty from the input request',
+        alias="gen_ai.request.frequency_penalty",
+        description="Frequency penalty from the input request",
     )
     gen_ai_request_presence_penalty: Optional[float] = Field(
         None,
-        alias='gen_ai.request.presence_penalty',
-        description='Presence penalty from the input request',
+        alias="gen_ai.request.presence_penalty",
+        description="Presence penalty from the input request",
     )
     gen_ai_request_tools: Optional[str] = Field(
         None,
-        alias='gen_ai.request.tools',
-        description='An array of tools from the input request json stringified',
+        alias="gen_ai.request.tools",
+        description="An array of tools from the input request json stringified",
     )
     gen_ai_request_tool_results: Optional[str] = Field(
         None,
-        alias='gen_ai.request.tool_results',
-        description='An array of tool results from the input request json stringified',
+        alias="gen_ai.request.tool_results",
+        description="An array of tool results from the input request json stringified",
     )

Diff for: instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/utils.py

@@ -56,7 +56,9 @@ def wrapper(*args, **kwargs):
             return func(*args, **kwargs)
         except Exception as exception:
             logger.warning(
-                "Failed to execute %s, error: %s", func.__name__, str(exception)
+                "Failed to execute %s, error: %s",
+                func.__name__,
+                str(exception),
             )
 
     return wrapper

Diff for: instrumentation/opentelemetry-instrumentation-openai/src/opentelemetry/instrumentation/openai/version.py

@@ -12,4 +12,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "0.0.1dev"
+__version__ = "0.47b0"