Merge branch 'main' into gl/fix/crewai-tools-mypy

lib/crewai-tools/src/crewai_tools/tools/brave_search_tool/base.py

@@ -240,10 +240,9 @@ class BraveSearchToolBase(BaseTool, ABC):
             # (e.g., 422 Unprocessable Entity, 400 Bad Request (OPTION_NOT_IN_PLAN))
             _raise_for_error(resp)
 
-        # All retries exhausted
-        if last_resp is not None:
-            _raise_for_error(last_resp)
-        return {}
+        # All retries exhausted — last_resp is always set when we reach here
+        _raise_for_error(last_resp or resp)
+        return {}  # unreachable; satisfies return type
 
     def _run(self, q: str | None = None, **params: Any) -> Any:
         # Allow positional usage: tool.run("latest Brave browser features")

lib/crewai/src/crewai/flow/human_feedback.py

@@ -374,10 +374,8 @@ def human_feedback(
         ) -> Any:
             """Recall past HITL lessons and use LLM to pre-review the output."""
             try:
-                from crewai.memory.unified_memory import Memory
-
                 mem = flow_instance.memory
-                if not isinstance(mem, Memory):
+                if mem is None:
                     return method_output
                 query = f"human feedback lessons for {func.__name__}: {method_output!s}"
                 matches = mem.recall(query, source=learn_source)
@@ -412,10 +410,8 @@ def human_feedback(
         ) -> None:
             """Extract generalizable lessons from output + feedback, store in memory."""
             try:
-                from crewai.memory.unified_memory import Memory
-
                 mem = flow_instance.memory
-                if not isinstance(mem, Memory):
+                if mem is None:
                     return
                 llm_inst = _resolve_llm_instance()
                 prompt = _get_hitl_prompt("hitl_distill_user").format(
@@ -448,7 +444,7 @@ def human_feedback(
                         ]
 
                 if lessons:
-                    mem.remember_many(lessons, source=learn_source)
+                    mem.remember_many(lessons, source=learn_source)  # type: ignore[union-attr]
             except Exception:  # noqa: S110
                 pass  # non-critical: don't fail the flow because lesson storage failed