fix: CrewAI-based flows with no extra openai (#4683)

* fix: CrewAI-based flows with no extra openai

* [autofix.ci] apply automated fixes

* Clean up the location of the crewai model processing

* [autofix.ci] apply automated fixes

* Properly subclass the tasks and agents method

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

src/backend/base/langflow/base/agents/crewai/crew.py

@@ -1,9 +1,11 @@
 from collections.abc import Callable
-from typing import cast
+from typing import Any, cast
 
-from crewai import Agent, Crew, Process, Task
+from crewai import LLM, Agent, Crew, Process, Task
 from crewai.task import TaskOutput
+from crewai.tools.base_tool import Tool
 from langchain_core.agents import AgentAction, AgentFinish
+from pydantic import SecretStr
 
 from langflow.custom import Component
 from langflow.inputs.inputs import HandleInput, InputTypes
@@ -13,6 +15,82 @@ from langflow.schema.message import Message
 from langflow.utils.constants import MESSAGE_SENDER_AI
 
 
+def _find_api_key(model):
+    """Attempts to find the API key attribute for a LangChain LLM model instance using partial matching.
+
+    Args:
+        model: LangChain LLM model instance.
+
+    Returns:
+        The API key if found, otherwise None.
+    """
+    # Define the possible API key attribute patterns
+    key_patterns = ["key", "token"]
+
+    # Iterate over the model attributes
+    for attr in dir(model):
+        attr_lower = attr.lower()
+
+        # Check if the attribute name contains any of the key patterns
+        if any(pattern in attr_lower for pattern in key_patterns):
+            value = getattr(model, attr, None)
+
+            # Check if the value is a non-empty string
+            if isinstance(value, str):
+                return value
+            if isinstance(value, SecretStr):
+                return value.get_secret_value()
+
+    return None
+
+
+def convert_llm(llm: Any, excluded_keys=None) -> LLM:
+    """Converts a LangChain LLM object to a CrewAI-compatible LLM object.
+
+    Args:
+        llm: A LangChain LLM object.
+        excluded_keys: A set of keys to exclude from the conversion.
+
+    Returns:
+        A CrewAI-compatible LLM object
+    """
+    if not llm:
+        return None
+
+    # Check if this is already an LLM object
+    if isinstance(llm, LLM):
+        return llm
+
+    # Retrieve the API Key from the LLM
+    if excluded_keys is None:
+        excluded_keys = {"model", "model_name", "_type", "api_key"}
+
+    # Find the API key in the LLM
+    api_key = _find_api_key(llm)
+
+    # Convert Langchain LLM to CrewAI-compatible LLM object
+    return LLM(
+        model=llm.model_name,
+        api_key=api_key,
+        **{k: v for k, v in llm.dict().items() if k not in excluded_keys},
+    )
+
+
+def convert_tools(tools):
+    """Converts LangChain tools to CrewAI-compatible tools.
+
+    Args:
+        tools: A LangChain tools list.
+
+    Returns:
+        A CrewAI-compatible tools list.
+    """
+    if not tools:
+        return []
+
+    return [Tool.from_langchain(tool) for tool in tools]
+
+
 class BaseCrewComponent(Component):
     description: str = (
         "Represents a group of agents, defining how they should collaborate and the tasks they should perform."
@@ -39,12 +117,33 @@ class BaseCrewComponent(Component):
         Output(display_name="Output", name="output", method="build_output"),
     ]
 
+    # Model properties to exclude when creating a CrewAI LLM object
+    manager_llm: LLM | None
+
     def task_is_valid(self, task_data: Data, crew_type: Process) -> Task:
         return "task_type" in task_data and task_data.task_type == crew_type
 
-    def get_tasks_and_agents(self) -> tuple[list[Task], list[Agent]]:
+    def get_tasks_and_agents(self, agents_list=None) -> tuple[list[Task], list[Agent]]:
+        # Allow passing a custom list of agents
+        if not agents_list:
+            agents_list = self.agents or []
+
+        # Set all the agents llm attribute to the crewai llm
+        for agent in agents_list:
+            # Convert Agent LLM and Tools to proper format
+            agent.llm = convert_llm(agent.llm)
+            agent.tools = convert_tools(agent.tools)
+
         return self.tasks, self.agents
 
+    def get_manager_llm(self) -> LLM | None:
+        if not self.manager_llm:
+            return None
+
+        self.manager_llm = convert_llm(self.manager_llm)
+
+        return self.manager_llm
+
     def build_crew(self) -> Crew:
         msg = "build_crew must be implemented in subclasses"
         raise NotImplementedError(msg)

src/backend/base/langflow/components/crewai/crewai.py

@@ -1,10 +1,23 @@
 from crewai import Agent
 
+from langflow.base.agents.crewai.crew import convert_llm, convert_tools
 from langflow.custom import Component
 from langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output
 
 
 class CrewAIAgentComponent(Component):
+    """Component for creating a CrewAI agent.
+
+    This component allows you to create a CrewAI agent with the specified role, goal, backstory, tools,
+    and language model.
+
+    Args:
+        Component (Component): Base class for all components.
+
+    Returns:
+        Agent: CrewAI agent.
+    """
+
     display_name = "CrewAI Agent"
     description = "Represents an agent of CrewAI."
     documentation: str = "https://docs.crewai.com/how-to/LLM-Connections/"
@@ -69,17 +82,21 @@ class CrewAIAgentComponent(Component):
 
     def build_output(self) -> Agent:
         kwargs = self.kwargs or {}
+
+        # Define the Agent
         agent = Agent(
             role=self.role,
             goal=self.goal,
             backstory=self.backstory,
-            llm=self.llm,
+            llm=convert_llm(self.llm),
             verbose=self.verbose,
             memory=self.memory,
-            tools=self.tools or [],
+            tools=convert_tools(self.tools),
             allow_delegation=self.allow_delegation,
             allow_code_execution=self.allow_code_execution,
             **kwargs,
         )
+
         self.status = repr(agent)
+
         return agent

src/backend/base/langflow/components/crewai/hierarchical_crew.py

@@ -1,9 +1,7 @@
-import os
-
 from crewai import Crew, Process
 
 from langflow.base.agents.crewai.crew import BaseCrewComponent
-from langflow.io import HandleInput, SecretStrInput
+from langflow.io import HandleInput
 
 
 class HierarchicalCrewComponent(BaseCrewComponent):
@@ -20,20 +18,11 @@ class HierarchicalCrewComponent(BaseCrewComponent):
         HandleInput(name="tasks", display_name="Tasks", input_types=["HierarchicalTask"], is_list=True),
         HandleInput(name="manager_llm", display_name="Manager LLM", input_types=["LanguageModel"], required=False),
         HandleInput(name="manager_agent", display_name="Manager Agent", input_types=["Agent"], required=False),
-        SecretStrInput(
-            name="openai_api_key",
-            display_name="OpenAI API Key",
-            info="The OpenAI API Key to use for the OpenAI model.",
-            value="OPENAI_API_KEY",
-        ),
     ]
 
     def build_crew(self) -> Crew:
         tasks, agents = self.get_tasks_and_agents()
-
-        # Set the OpenAI API Key
-        if self.openai_api_key:
-            os.environ["OPENAI_API_KEY"] = self.openai_api_key
+        manager_llm = self.get_manager_llm()
 
         return Crew(
             agents=agents,
@@ -46,7 +35,7 @@ class HierarchicalCrewComponent(BaseCrewComponent):
             share_crew=self.share_crew,
             function_calling_llm=self.function_calling_llm,
             manager_agent=self.manager_agent,
-            manager_llm=self.manager_llm,
+            manager_llm=manager_llm,
             step_callback=self.get_step_callback(),
             task_callback=self.get_task_callback(),
         )

src/backend/base/langflow/components/crewai/sequential_crew.py

@@ -16,11 +16,16 @@ class SequentialCrewComponent(BaseCrewComponent):
         HandleInput(name="tasks", display_name="Tasks", input_types=["SequentialTask"], is_list=True),
     ]
 
-    def get_tasks_and_agents(self) -> tuple[list[Task], list[Agent]]:
-        return self.tasks, [task.agent for task in self.tasks]
+    def get_tasks_and_agents(self, agents_list=None) -> tuple[list[Task], list[Agent]]:
+        if not agents_list:
+            agents_list = [task.agent for task in self.tasks] or []
+
+        # Use the superclass implementation, passing the customized agents_list
+        return super().get_tasks_and_agents(agents_list=agents_list)
 
     def build_crew(self) -> Message:
         tasks, agents = self.get_tasks_and_agents()
+
         return Crew(
             agents=agents,
             tasks=tasks,

src/backend/base/pyproject.toml

@@ -154,7 +154,7 @@ dependencies = [
     "nanoid>=2.0.0",
     "filelock>=3.15.4",
     "grandalf>=0.8.0",
-    "crewai>=0.74.2",
+    "crewai~=0.80.0",
     "spider-client>=0.0.27",
     "diskcache>=5.6.3",
     "clickhouse-connect==0.7.19",