Feat: Add Langtrace integration (#5341)

* Feat: Add Langtrace integration

* add langtrace service name

* fix timestamps for traces

* add tests

* Discard Callback + use existing otel logger

* cleanup

* remove print statments

* remove callback

* add docs

* docs

* add logging docs

* format logging

* remove emoji and add litellm proxy example

* format logging

* format `logging.md`

* add langtrace docs to logging.md

* sync conflict

litellm/integrations/langtrace.py

@@ -0,0 +1,108 @@
+import traceback
+import json
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.proxy._types import SpanAttributes
+
+from typing import TYPE_CHECKING, Any, Optional, Union
+
+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)