feat(otel): read gen_ai.conversation.id from OTEL baggage and set as span attribute (#429)

Read gen_ai.conversation.id from OTEL baggage in get_traced_request_and_span()
and set it as an attribute on SDK-created spans. This allows callers that
propagate conversation ID via standard OTEL baggage (opentelemetry.baggage)
to have it automatically attached to descendant Mistral SDK spans, per GenAI
semantic conventions.

Generated by Mistral Vibe.

Co-authored-by: Mistral Vibe <vibe@mistral.ai>

Author: simonvdk-mistral

src/mistralai/extra/observability/otel.py

@@ -20,6 +20,7 @@
 import opentelemetry.semconv.attributes.server_attributes as server_attributes
 from opentelemetry import context as context_api
 from opentelemetry import propagate, trace
+from opentelemetry.baggage import get_baggage
 from opentelemetry.trace import Span, Status, StatusCode, Tracer, set_span_in_context
 
 from .serialization import (
@@ -453,6 +454,12 @@ def get_traced_request_and_span(
     try:
         span = tracer.start_span(name=operation_id)
         span.set_attributes({"agent.trace.public": ""})
+        # Propagate gen_ai.conversation.id from OTEL baggage if present
+        conversation_id = get_baggage(gen_ai_attributes.GEN_AI_CONVERSATION_ID)
+        if conversation_id:
+            span.set_attribute(
+                gen_ai_attributes.GEN_AI_CONVERSATION_ID, str(conversation_id)
+            )
         # Inject the span context into the request headers to be used by the backend service to continue the trace
         propagate.inject(request.headers, context=set_span_in_context(span))
         span = enrich_span_from_request(span, operation_id, request)

src/mistralai/extra/tests/test_otel_tracing.py

@@ -18,7 +18,9 @@
 from unittest.mock import MagicMock
 
 import httpx
+from opentelemetry import context as context_api
 from opentelemetry import trace
+from opentelemetry.baggage import set_baggage
 from opentelemetry.sdk.trace import TracerProvider
 from opentelemetry.sdk.trace.export import SimpleSpanProcessor
 from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter
@@ -1525,5 +1527,76 @@ def failing_tool(x: int) -> str:
         )
 
 
+    # -- Baggage propagation: gen_ai.conversation.id ---------------------------
+
+    def test_conversation_id_from_baggage(self):
+        """When gen_ai.conversation.id is set in OTEL baggage, it must appear as a span attribute."""
+        request = ChatCompletionRequest(
+            model="mistral-small-latest",
+            messages=[UserMessage(content="Hello")],
+        )
+        response = ChatCompletionResponse(
+            id="cmpl-baggage-001",
+            object="chat.completion",
+            model="mistral-small-latest",
+            created=1700000010,
+            choices=[
+                ChatCompletionChoice(
+                    index=0,
+                    message=AssistantMessage(content="Hi!", tool_calls=None),
+                    finish_reason="stop",
+                ),
+            ],
+            usage=UsageInfo(prompt_tokens=5, completion_tokens=2, total_tokens=7),
+        )
+
+        # Attach baggage to the current context
+        ctx = set_baggage("gen_ai.conversation.id", "conv-from-baggage-123")
+        token = context_api.attach(ctx)
+        try:
+            self._run_hook_lifecycle(
+                "chat_completion_v1_chat_completions_post",
+                request,
+                response,
+            )
+        finally:
+            context_api.detach(token)
+
+        span = self._get_single_span()
+        self.assertEqual(
+            span.attributes["gen_ai.conversation.id"], "conv-from-baggage-123"
+        )
+
+    def test_no_conversation_id_without_baggage(self):
+        """When no baggage is set, gen_ai.conversation.id must NOT appear on a chat span."""
+        request = ChatCompletionRequest(
+            model="mistral-small-latest",
+            messages=[UserMessage(content="Hello")],
+        )
+        response = ChatCompletionResponse(
+            id="cmpl-nobag-001",
+            object="chat.completion",
+            model="mistral-small-latest",
+            created=1700000011,
+            choices=[
+                ChatCompletionChoice(
+                    index=0,
+                    message=AssistantMessage(content="Hi!", tool_calls=None),
+                    finish_reason="stop",
+                ),
+            ],
+            usage=UsageInfo(prompt_tokens=5, completion_tokens=2, total_tokens=7),
+        )
+
+        self._run_hook_lifecycle(
+            "chat_completion_v1_chat_completions_post",
+            request,
+            response,
+        )
+
+        span = self._get_single_span()
+        self.assertNotIn("gen_ai.conversation.id", span.attributes)
+
+
 if __name__ == "__main__":
     unittest.main()