feat(pydantic-ai): Set system instruction attribute

sentry_sdk/consts.py

@@ -542,6 +542,12 @@ class SPANDATA:
     Example: 2048
     """
 
+    GEN_AI_SYSTEM_INSTRUCTIONS = "gen_ai.system_instructions"
+    """
+    The system instructions passed to the model.
+    Example: [{"type": "text", "text": "You are a helpful assistant."},{"type": "text", "text": "Be concise and clear."}]
+    """
+
     GEN_AI_REQUEST_MESSAGES = "gen_ai.request.messages"
     """
     The messages passed to the model. The "content" can be a string or an array of objects.

sentry_sdk/integrations/pydantic_ai/spans/ai_client.py

@@ -48,6 +48,20 @@
     BinaryContent = None
 
 
+def _set_system_instruction(span: "sentry_sdk.tracing.Span", messages: "Any") -> None:
+    for msg in messages:
+        for part in msg.parts:
+            if SystemPromptPart and isinstance(part, SystemPromptPart):
+                system_prompt = part.content
+                set_data_normalized(
+                    span,
+                    SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS,
+                    system_prompt,
+                    unpack=False,
+                )
+                return
+
+
 def _set_input_messages(span: "sentry_sdk.tracing.Span", messages: "Any") -> None:
     """Set input messages data on a span."""
     if not _should_send_prompts():
@@ -58,27 +72,14 @@ def _set_input_messages(span: "sentry_sdk.tracing.Span", messages: "Any") -> Non
 
     try:
         formatted_messages = []
-        system_prompt = None
-
-        # Extract system prompt from any ModelRequest with instructions
-        for msg in messages:
-            if hasattr(msg, "instructions") and msg.instructions:
-                system_prompt = msg.instructions
-                break
-
-        # Add system prompt as first message if present
-        if system_prompt:
-            formatted_messages.append(
-                {"role": "system", "content": [{"type": "text", "text": system_prompt}]}
-            )
 
         for msg in messages:
             if hasattr(msg, "parts"):
                 for part in msg.parts:
                     role = "user"
                     # Use isinstance checks with proper base classes
                     if SystemPromptPart and isinstance(part, SystemPromptPart):
-                        role = "system"
+                        continue
                     elif (
                         (TextPart and isinstance(part, TextPart))
                         or (ThinkingPart and isinstance(part, ThinkingPart))
@@ -235,6 +236,7 @@ def ai_client_span(
 
     # Set input messages (full conversation history)
     if messages:
+        _set_system_instruction(span, messages)
         _set_input_messages(span, messages)
 
     return span

tests/integrations/pydantic_ai/test_pydantic_ai.py

@@ -514,7 +514,7 @@ async def test_model_settings(sentry_init, capture_events, test_agent_with_setti
 
 
 @pytest.mark.asyncio
-async def test_system_prompt_in_messages(sentry_init, capture_events):
+async def test_system_prompt_attribute(sentry_init, capture_events):
     """
     Test that system prompts are included as the first message.
     """
@@ -542,12 +542,8 @@ async def test_system_prompt_in_messages(sentry_init, capture_events):
     assert len(chat_spans) >= 1
 
     chat_span = chat_spans[0]
-    messages_str = chat_span["data"]["gen_ai.request.messages"]
-
-    # Messages is serialized as a string
-    # Should contain system role and helpful assistant text
-    assert "system" in messages_str
-    assert "helpful assistant" in messages_str
+    system_instruction = chat_span["data"][SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS]
+    assert "helpful assistant" in system_instruction
 
 
 @pytest.mark.asyncio
@@ -1211,14 +1207,15 @@ async def test_invoke_agent_with_instructions(sentry_init, capture_events):
     await agent.run("Test input")
 
     (transaction,) = events
+    spans = transaction["spans"]
 
-    # Check that the invoke_agent transaction has messages data
-    if "gen_ai.request.messages" in transaction["contexts"]["trace"]["data"]:
-        messages_str = transaction["contexts"]["trace"]["data"][
-            "gen_ai.request.messages"
-        ]
-        # Should contain both instructions and system prompts
-        assert "Instruction" in messages_str or "System prompt" in messages_str
+    # The transaction IS the invoke_agent span, check for messages in chat spans instead
+    chat_spans = [s for s in spans if s["op"] == "gen_ai.chat"]
+    assert len(chat_spans) >= 1
+
+    chat_span = chat_spans[0]
+    system_instruction = chat_span["data"][SPANDATA.GEN_AI_SYSTEM_INSTRUCTIONS]
+    assert "System prompt" in system_instruction
 
 
 @pytest.mark.asyncio