From beaf862941845b529a083d74819c7b698491dae0 Mon Sep 17 00:00:00 2001
From: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Fri, 27 Mar 2026 20:38:36 +0000
Subject: [PATCH] fix: use _extract_stop_reason to safely handle non-string
 stop_reason values
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MagicMock objects (and other non-Anthropic responses) can return non-string
values for getattr(response, 'stop_reason', None). Add a typed extraction
helper that returns None unless the value is actually a string, preventing
Pydantic validation errors in LLMCallCompletedEvent.

Co-Authored-By: João <joao@crewai.com>
---
 .../llms/providers/anthropic/completion.py    | 20 ++++++++++++-------
 1 file changed, 13 insertions(+), 7 deletions(-)

diff --git a/lib/crewai/src/crewai/llms/providers/anthropic/completion.py b/lib/crewai/src/crewai/llms/providers/anthropic/completion.py
index a49c1ce2f..6c83bd28c 100644
--- a/lib/crewai/src/crewai/llms/providers/anthropic/completion.py
+++ b/lib/crewai/src/crewai/llms/providers/anthropic/completion.py
@@ -676,13 +676,19 @@ class AnthropicCompletion(BaseLLM):
 
         return converted
 
+    @staticmethod
+    def _extract_stop_reason(response: Message | BetaMessage) -> str | None:
+        """Extract stop_reason from an Anthropic response, returning None if absent."""
+        raw = getattr(response, "stop_reason", None)
+        return raw if isinstance(raw, str) else None
+
     def _warn_if_truncated(
         self,
         response: Message | BetaMessage,
         from_agent: Any | None = None,
     ) -> None:
         """Log a warning if the response was truncated due to max_tokens."""
-        stop_reason = getattr(response, "stop_reason", None)
+        stop_reason = self._extract_stop_reason(response)
         if stop_reason == "max_tokens":
             agent_hint = f" [{from_agent.role}]" if from_agent else ""
             logging.warning(
@@ -872,7 +878,7 @@ class AnthropicCompletion(BaseLLM):
         usage = self._extract_anthropic_token_usage(response)
         self._track_token_usage_internal(usage)
 
-        stop_reason = getattr(response, "stop_reason", None)
+        stop_reason = self._extract_stop_reason(response)
         self._warn_if_truncated(response, from_agent)
 
         if _is_pydantic_model_class(response_model) and response.content:
@@ -1098,7 +1104,7 @@ class AnthropicCompletion(BaseLLM):
         usage = self._extract_anthropic_token_usage(final_message)
         self._track_token_usage_internal(usage)
 
-        stop_reason = getattr(final_message, "stop_reason", None)
+        stop_reason = self._extract_stop_reason(final_message)
         self._warn_if_truncated(final_message, from_agent)
 
         if _is_pydantic_model_class(response_model):
@@ -1302,7 +1308,7 @@ class AnthropicCompletion(BaseLLM):
             follow_up_usage = self._extract_anthropic_token_usage(final_response)
             self._track_token_usage_internal(follow_up_usage)
 
-            stop_reason = getattr(final_response, "stop_reason", None)
+            stop_reason = self._extract_stop_reason(final_response)
             self._warn_if_truncated(final_response, from_agent)
 
             final_content = ""
@@ -1410,7 +1416,7 @@ class AnthropicCompletion(BaseLLM):
         usage = self._extract_anthropic_token_usage(response)
         self._track_token_usage_internal(usage)
 
-        stop_reason = getattr(response, "stop_reason", None)
+        stop_reason = self._extract_stop_reason(response)
         self._warn_if_truncated(response, from_agent)
 
         if _is_pydantic_model_class(response_model) and response.content:
@@ -1614,7 +1620,7 @@ class AnthropicCompletion(BaseLLM):
         usage = self._extract_anthropic_token_usage(final_message)
         self._track_token_usage_internal(usage)
 
-        stop_reason = getattr(final_message, "stop_reason", None)
+        stop_reason = self._extract_stop_reason(final_message)
         self._warn_if_truncated(final_message, from_agent)
 
         if _is_pydantic_model_class(response_model):
@@ -1715,7 +1721,7 @@ class AnthropicCompletion(BaseLLM):
             follow_up_usage = self._extract_anthropic_token_usage(final_response)
             self._track_token_usage_internal(follow_up_usage)
 
-            stop_reason = getattr(final_response, "stop_reason", None)
+            stop_reason = self._extract_stop_reason(final_response)
             self._warn_if_truncated(final_response, from_agent)
 
             final_content = ""