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-rw-r--r--.venv/lib/python3.12/site-packages/litellm/integrations/langtrace.py106
1 files changed, 106 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/litellm/integrations/langtrace.py b/.venv/lib/python3.12/site-packages/litellm/integrations/langtrace.py
new file mode 100644
index 00000000..51cd272f
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/integrations/langtrace.py
@@ -0,0 +1,106 @@
+import json
+from typing import TYPE_CHECKING, Any
+
+from litellm.proxy._types import SpanAttributes
+
+if TYPE_CHECKING:
+ from opentelemetry.trace import Span as _Span
+
+ Span = _Span
+else:
+ Span = Any
+
+
+class LangtraceAttributes:
+ """
+ This class is used to save trace attributes to Langtrace's spans
+ """
+
+ def set_langtrace_attributes(self, span: Span, kwargs, response_obj):
+ """
+ This function is used to log the event to Langtrace
+ """
+
+ vendor = kwargs.get("litellm_params").get("custom_llm_provider")
+ optional_params = kwargs.get("optional_params", {})
+ options = {**kwargs, **optional_params}
+ self.set_request_attributes(span, options, vendor)
+ self.set_response_attributes(span, response_obj)
+ self.set_usage_attributes(span, response_obj)
+
+ def set_request_attributes(self, span: Span, kwargs, vendor):
+ """
+ This function is used to get span attributes for the LLM request
+ """
+ span_attributes = {
+ "gen_ai.operation.name": "chat",
+ "langtrace.service.name": vendor,
+ SpanAttributes.LLM_REQUEST_MODEL.value: kwargs.get("model"),
+ SpanAttributes.LLM_IS_STREAMING.value: kwargs.get("stream"),
+ SpanAttributes.LLM_REQUEST_TEMPERATURE.value: kwargs.get("temperature"),
+ SpanAttributes.LLM_TOP_K.value: kwargs.get("top_k"),
+ SpanAttributes.LLM_REQUEST_TOP_P.value: kwargs.get("top_p"),
+ SpanAttributes.LLM_USER.value: kwargs.get("user"),
+ SpanAttributes.LLM_REQUEST_MAX_TOKENS.value: kwargs.get("max_tokens"),
+ SpanAttributes.LLM_RESPONSE_STOP_REASON.value: kwargs.get("stop"),
+ SpanAttributes.LLM_FREQUENCY_PENALTY.value: kwargs.get("frequency_penalty"),
+ SpanAttributes.LLM_PRESENCE_PENALTY.value: kwargs.get("presence_penalty"),
+ }
+
+ prompts = kwargs.get("messages")
+
+ if prompts:
+ span.add_event(
+ name="gen_ai.content.prompt",
+ attributes={SpanAttributes.LLM_PROMPTS.value: json.dumps(prompts)},
+ )
+
+ self.set_span_attributes(span, span_attributes)
+
+ def set_response_attributes(self, span: Span, response_obj):
+ """
+ This function is used to get span attributes for the LLM response
+ """
+ response_attributes = {
+ "gen_ai.response_id": response_obj.get("id"),
+ "gen_ai.system_fingerprint": response_obj.get("system_fingerprint"),
+ SpanAttributes.LLM_RESPONSE_MODEL.value: response_obj.get("model"),
+ }
+ completions = []
+ for choice in response_obj.get("choices", []):
+ role = choice.get("message").get("role")
+ content = choice.get("message").get("content")
+ completions.append({"role": role, "content": content})
+
+ span.add_event(
+ name="gen_ai.content.completion",
+ attributes={SpanAttributes.LLM_COMPLETIONS: json.dumps(completions)},
+ )
+
+ self.set_span_attributes(span, response_attributes)
+
+ def set_usage_attributes(self, span: Span, response_obj):
+ """
+ This function is used to get span attributes for the LLM usage
+ """
+ usage = response_obj.get("usage")
+ if usage:
+ usage_attributes = {
+ SpanAttributes.LLM_USAGE_PROMPT_TOKENS.value: usage.get(
+ "prompt_tokens"
+ ),
+ SpanAttributes.LLM_USAGE_COMPLETION_TOKENS.value: usage.get(
+ "completion_tokens"
+ ),
+ SpanAttributes.LLM_USAGE_TOTAL_TOKENS.value: usage.get("total_tokens"),
+ }
+ self.set_span_attributes(span, usage_attributes)
+
+ def set_span_attributes(self, span: Span, attributes):
+ """
+ This function is used to set span attributes
+ """
+ for key, value in attributes.items():
+ if not value:
+ continue
+ span.set_attribute(key, value)