two version of R2R are here HEAD master

1 files changed, 126 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/integrations/arize/_utils.py b/.venv/lib/python3.12/site-packages/litellm/integrations/arize/_utils.py
new file mode 100644
index 00000000..487304cc
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/integrations/arize/_utils.py
@@ -0,0 +1,126 @@
+from typing import TYPE_CHECKING, Any, Optional
+
+from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+from litellm.types.utils import StandardLoggingPayload
+
+if TYPE_CHECKING:
+    from opentelemetry.trace import Span as _Span
+
+    Span = _Span
+else:
+    Span = Any
+
+
+def set_attributes(span: Span, kwargs, response_obj):
+    from litellm.integrations._types.open_inference import (
+        MessageAttributes,
+        OpenInferenceSpanKindValues,
+        SpanAttributes,
+    )
+
+    try:
+        standard_logging_payload: Optional[StandardLoggingPayload] = kwargs.get(
+            "standard_logging_object"
+        )
+
+        #############################################
+        ############ LLM CALL METADATA ##############
+        #############################################
+
+        if standard_logging_payload and (
+            metadata := standard_logging_payload["metadata"]
+        ):
+            span.set_attribute(SpanAttributes.METADATA, safe_dumps(metadata))
+
+        #############################################
+        ########## LLM Request Attributes ###########
+        #############################################
+
+        # The name of the LLM a request is being made to
+        if kwargs.get("model"):
+            span.set_attribute(SpanAttributes.LLM_MODEL_NAME, kwargs.get("model"))
+
+        span.set_attribute(
+            SpanAttributes.OPENINFERENCE_SPAN_KIND,
+            OpenInferenceSpanKindValues.LLM.value,
+        )
+        messages = kwargs.get("messages")
+
+        # for /chat/completions
+        # https://docs.arize.com/arize/large-language-models/tracing/semantic-conventions
+        if messages:
+            span.set_attribute(
+                SpanAttributes.INPUT_VALUE,
+                messages[-1].get("content", ""),  # get the last message for input
+            )
+
+            # LLM_INPUT_MESSAGES shows up under `input_messages` tab on the span page
+            for idx, msg in enumerate(messages):
+                # Set the role per message
+                span.set_attribute(
+                    f"{SpanAttributes.LLM_INPUT_MESSAGES}.{idx}.{MessageAttributes.MESSAGE_ROLE}",
+                    msg["role"],
+                )
+                # Set the content per message
+                span.set_attribute(
+                    f"{SpanAttributes.LLM_INPUT_MESSAGES}.{idx}.{MessageAttributes.MESSAGE_CONTENT}",
+                    msg.get("content", ""),
+                )
+
+        if standard_logging_payload and (
+            model_params := standard_logging_payload["model_parameters"]
+        ):
+            # The Generative AI Provider: Azure, OpenAI, etc.
+            span.set_attribute(
+                SpanAttributes.LLM_INVOCATION_PARAMETERS, safe_dumps(model_params)
+            )
+
+            if model_params.get("user"):
+                user_id = model_params.get("user")
+                if user_id is not None:
+                    span.set_attribute(SpanAttributes.USER_ID, user_id)
+
+        #############################################
+        ########## LLM Response Attributes ##########
+        # https://docs.arize.com/arize/large-language-models/tracing/semantic-conventions
+        #############################################
+        if hasattr(response_obj, "get"):
+            for choice in response_obj.get("choices", []):
+                response_message = choice.get("message", {})
+                span.set_attribute(
+                    SpanAttributes.OUTPUT_VALUE, response_message.get("content", "")
+                )
+
+                # This shows up under `output_messages` tab on the span page
+                # This code assumes a single response
+                span.set_attribute(
+                    f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_ROLE}",
+                    response_message.get("role"),
+                )
+                span.set_attribute(
+                    f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_CONTENT}",
+                    response_message.get("content", ""),
+                )
+
+            usage = response_obj.get("usage")
+            if usage:
+                span.set_attribute(
+                    SpanAttributes.LLM_TOKEN_COUNT_TOTAL,
+                    usage.get("total_tokens"),
+                )
+
+                # The number of tokens used in the LLM response (completion).
+                span.set_attribute(
+                    SpanAttributes.LLM_TOKEN_COUNT_COMPLETION,
+                    usage.get("completion_tokens"),
+                )
+
+                # The number of tokens used in the LLM prompt.
+                span.set_attribute(
+                    SpanAttributes.LLM_TOKEN_COUNT_PROMPT,
+                    usage.get("prompt_tokens"),
+                )
+        pass
+    except Exception as e:
+        verbose_logger.error(f"Error setting arize attributes: {e}")