Fix import sorting in test file using ruff

Co-Authored-By: Joe Moura <joao@crewai.com>

src/crewai/agent.py

@@ -114,6 +114,7 @@ class Agent(BaseAgent):
 
     @model_validator(mode="after")
     def post_init_setup(self):
+        self._set_knowledge()
         self.agent_ops_agent_name = self.role
 
         self.llm = create_llm(self.llm)
@@ -133,11 +134,8 @@ class Agent(BaseAgent):
             self.cache_handler = CacheHandler()
         self.set_cache_handler(self.cache_handler)
 
-    def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
+    def _set_knowledge(self):
         try:
-            if self.embedder is None and crew_embedder:
-                self.embedder = crew_embedder
-
             if self.knowledge_sources:
                 full_pattern = re.compile(r"[^a-zA-Z0-9\-_\r\n]|(\.\.)")
                 knowledge_agent_name = f"{re.sub(full_pattern, '_', self.role)}"

src/crewai/agents/agent_builder/base_agent.py

@@ -351,6 +351,3 @@ class BaseAgent(ABC, BaseModel):
         if not self._rpm_controller:
             self._rpm_controller = rpm_controller
             self.create_agent_executor()
-
-    def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
-        pass

src/crewai/agents/crew_agent_executor.py

@@ -232,7 +232,14 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 self._format_answer(answer)
             except OutputParserException as e:
                 if FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE in e.error:
-                    answer = answer.split("Observation:")[0].strip()
+                    # If both Action and Final Answer are present, prioritize the Action
+                    # by removing the Final Answer part
+                    if "Final Answer:" in answer:
+                        parts = answer.split("Final Answer:")
+                        answer = parts[0].strip()
+                    # If that doesn't work, try splitting at Observation
+                    elif "Observation:" in answer:
+                        answer = answer.split("Observation:")[0].strip()
 
         return self._format_answer(answer)
 

src/crewai/crew.py

@@ -600,7 +600,6 @@ class Crew(BaseModel):
                 agent.i18n = i18n
                 # type: ignore[attr-defined] # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
                 agent.crew = self  # type: ignore[attr-defined]
-                agent.set_knowledge(crew_embedder=self.embedder)
                 # TODO: Create an AgentFunctionCalling protocol for future refactoring
                 if not agent.function_calling_llm:  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
                     agent.function_calling_llm = self.function_calling_llm  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"

src/crewai/flow/persistence/sqlite.py

@@ -4,7 +4,7 @@ SQLite-based implementation of flow state persistence.
 
 import json
 import sqlite3
-from datetime import datetime, timezone
+from datetime import datetime
 from pathlib import Path
 from typing import Any, Dict, Optional, Union
 
@@ -34,7 +34,6 @@ class SQLiteFlowPersistence(FlowPersistence):
             ValueError: If db_path is invalid
         """
         from crewai.utilities.paths import db_storage_path
-
         # Get path from argument or default location
         path = db_path or str(Path(db_storage_path()) / "flow_states.db")
 
@@ -47,8 +46,7 @@ class SQLiteFlowPersistence(FlowPersistence):
     def init_db(self) -> None:
         """Create the necessary tables if they don't exist."""
         with sqlite3.connect(self.db_path) as conn:
-            conn.execute(
-                """
+            conn.execute("""
             CREATE TABLE IF NOT EXISTS flow_states (
                 id INTEGER PRIMARY KEY AUTOINCREMENT,
                 flow_uuid TEXT NOT NULL,
@@ -56,15 +54,12 @@ class SQLiteFlowPersistence(FlowPersistence):
                 timestamp DATETIME NOT NULL,
                 state_json TEXT NOT NULL
             )
-            """
-            )
+            """)
             # Add index for faster UUID lookups
-            conn.execute(
-                """
+            conn.execute("""
             CREATE INDEX IF NOT EXISTS idx_flow_states_uuid
             ON flow_states(flow_uuid)
-            """
-            )
+            """)
 
     def save_state(
         self,
@@ -90,22 +85,19 @@ class SQLiteFlowPersistence(FlowPersistence):
             )
 
         with sqlite3.connect(self.db_path) as conn:
-            conn.execute(
-                """
+            conn.execute("""
             INSERT INTO flow_states (
                 flow_uuid,
                 method_name,
                 timestamp,
                 state_json
             ) VALUES (?, ?, ?, ?)
-            """,
-                (
-                    flow_uuid,
-                    method_name,
-                    datetime.now(timezone.utc).isoformat(),
-                    json.dumps(state_dict),
-                ),
-            )
+            """, (
+                flow_uuid,
+                method_name,
+                datetime.utcnow().isoformat(),
+                json.dumps(state_dict),
+            ))
 
     def load_state(self, flow_uuid: str) -> Optional[Dict[str, Any]]:
         """Load the most recent state for a given flow UUID.
@@ -117,16 +109,13 @@ class SQLiteFlowPersistence(FlowPersistence):
             The most recent state as a dictionary, or None if no state exists
         """
         with sqlite3.connect(self.db_path) as conn:
-            cursor = conn.execute(
-                """
+            cursor = conn.execute("""
             SELECT state_json
             FROM flow_states
             WHERE flow_uuid = ?
             ORDER BY id DESC
             LIMIT 1
-            """,
-                (flow_uuid,),
-            )
+            """, (flow_uuid,))
             row = cursor.fetchone()
 
         if row:

tests/agents/test_action_final_answer_error.py

@@ -0,0 +1,84 @@
+from unittest.mock import MagicMock
+
+import pytest
+
+from crewai.agents.crew_agent_executor import CrewAgentExecutor
+from crewai.agents.parser import (
+    FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE,
+    AgentAction,
+    AgentFinish,
+    OutputParserException,
+)
+
+
+def test_process_llm_response_with_action_and_final_answer():
+    """Test that _process_llm_response correctly handles outputs with both Action and Final Answer."""
+    # Create a mock LLM
+    mock_llm = MagicMock()
+    mock_llm.supports_stop_words.return_value = False
+    
+    # Create a mock agent
+    mock_agent = MagicMock()
+    
+    # Create a CrewAgentExecutor instance
+    executor = CrewAgentExecutor(
+        llm=mock_llm,
+        task=MagicMock(),
+        crew=MagicMock(),
+        agent=mock_agent,
+        prompt={},
+        max_iter=5,
+        tools=[],
+        tools_names="",
+        stop_words=[],
+        tools_description="",
+        tools_handler=MagicMock(),
+    )
+    
+    # Test case 1: Output with both Action and Final Answer, with Final Answer after Action
+    output_with_both = """
+    Thought: I need to search for information and then provide an answer.
+    Action: search
+    Action Input: what is the temperature in SF?
+    Final Answer: The temperature is 100 degrees
+    """
+    
+    # Mock the _format_answer method to first raise an exception and then return a valid result
+    format_answer_mock = MagicMock()
+    format_answer_mock.side_effect = [
+        OutputParserException(FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE),
+        AgentAction(thought="", tool="search", tool_input="what is the temperature in SF?", text=""),
+    ]
+    executor._format_answer = format_answer_mock
+    
+    # Process the response
+    result = executor._process_llm_response(output_with_both)
+    
+    # Verify that the result is an AgentAction
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF?"
+    
+    # Test case 2: Output with both Action and Final Answer, with Observation in between
+    output_with_observation = """
+    Thought: I need to search for information.
+    Action: search
+    Action Input: what is the temperature in SF?
+    Observation: The temperature in SF is 100 degrees.
+    Final Answer: The temperature is 100 degrees
+    """
+    
+    # Reset the mock
+    format_answer_mock.reset_mock()
+    format_answer_mock.side_effect = [
+        OutputParserException(FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE),
+        AgentAction(thought="", tool="search", tool_input="what is the temperature in SF?", text=""),
+    ]
+    
+    # Process the response
+    result = executor._process_llm_response(output_with_observation)
+    
+    # Verify that the result is an AgentAction
+    assert isinstance(result, AgentAction)
+    assert result.tool == "search"
+    assert result.tool_input == "what is the temperature in SF?"