chore: release 1.5.0

.github/workflows/release.yml

@@ -41,6 +41,7 @@ on:
         default: true
 
 
+
 jobs:
   ci:
     if: ${{ github.event.inputs.release_package_base == 'true' || github.event.inputs.release_package_main == 'true' }}
@@ -50,6 +51,8 @@ jobs:
       python-versions: "['3.10', '3.11', '3.12', '3.13']"
       frontend-tests-folder: "tests"
       release: true
+    secrets: inherit
+
 
   release-base:
     name: Release Langflow Base

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "langflow"
-version = "1.4.3"
+version = "1.5.0"
 description = "A Python package with a built-in web application"
 requires-python = ">=3.10,<3.14"
 license = "MIT"
@@ -17,7 +17,7 @@ maintainers = [
 ]
 # Define your main dependencies here
 dependencies = [
-    "langflow-base==0.4.3",
+    "langflow-base==0.5.0",
     "beautifulsoup4==4.12.3",
     "google-search-results>=2.4.1,<3.0.0",
     "google-api-python-client==2.154.0",
@@ -104,11 +104,10 @@ dependencies = [
     "sseclient-py==1.8.0",
     "arize-phoenix-otel>=0.6.1",
     "openinference-instrumentation-langchain>=0.1.29",
-    "crewai==0.102.0",
+    # "crewai>=0.126.0",
     "mcp>=1.10.1",
     "uv>=0.5.7",
     "scipy>=1.14.1",
-    "ag2>=0.1.0",
     "scrapegraph-py>=1.12.0",
     "pydantic-ai>=0.0.19",
     "smolagents>=1.8.0",

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

@@ -2,10 +2,6 @@
 from typing import Any, cast
 
 import litellm
-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.custom_component.component import Component
@@ -45,7 +41,7 @@ def _find_api_key(model):
     return None
 
 
-def convert_llm(llm: Any, excluded_keys=None) -> LLM:
+def convert_llm(llm: Any, excluded_keys=None):
     """Converts a LangChain LLM object to a CrewAI-compatible LLM object.
 
     Args:
@@ -55,6 +51,12 @@ def convert_llm(llm: Any, excluded_keys=None) -> LLM:
     Returns:
         A CrewAI-compatible LLM object
     """
+    try:
+        from crewai import LLM
+    except ImportError as e:
+        msg = "CrewAI is not installed. Please install it with `uv pip install crewai`."
+        raise ImportError(msg) from e
+
     if not llm:
         return None
 
@@ -109,6 +111,12 @@ def convert_tools(tools):
     Returns:
         A CrewAI-compatible tools list.
     """
+    try:
+        from crewai.tools.base_tool import Tool
+    except ImportError as e:
+        msg = "CrewAI is not installed. Please install it with `uv pip install crewai`."
+        raise ImportError(msg) from e
+
     if not tools:
         return []
 
@@ -142,12 +150,12 @@ class BaseCrewComponent(Component):
     ]
 
     # Model properties to exclude when creating a CrewAI LLM object
-    manager_llm: LLM | None
+    manager_llm = None
 
-    def task_is_valid(self, task_data: Data, crew_type: Process) -> Task:
+    def task_is_valid(self, task_data: Data, crew_type) -> bool:
         return "task_type" in task_data and task_data.task_type == crew_type
 
-    def get_tasks_and_agents(self, agents_list=None) -> tuple[list[Task], list[Agent]]:
+    def get_tasks_and_agents(self, agents_list=None) -> tuple[list, list]:
         # Allow passing a custom list of agents
         if not agents_list:
             agents_list = self.agents or []
@@ -160,21 +168,27 @@ def get_tasks_and_agents(self, agents_list=None) -> tuple[list[Task], list[Agent
 
         return self.tasks, agents_list
 
-    def get_manager_llm(self) -> LLM | None:
+    def get_manager_llm(self):
         if not self.manager_llm:
             return None
 
         self.manager_llm = convert_llm(self.manager_llm)
 
         return self.manager_llm
 
-    def build_crew(self) -> Crew:
+    def build_crew(self):
         msg = "build_crew must be implemented in subclasses"
         raise NotImplementedError(msg)
 
     def get_task_callback(
         self,
     ) -> Callable:
+        try:
+            from crewai.task import TaskOutput
+        except ImportError as e:
+            msg = "CrewAI is not installed. Please install it with `uv pip install crewai`."
+            raise ImportError(msg) from e
+
         def task_callback(task_output: TaskOutput) -> None:
             vertex_id = self._vertex.id if self._vertex else self.display_name or self.__class__.__name__
             self.log(task_output.model_dump(), name=f"Task (Agent: {task_output.agent}) - {vertex_id}")
@@ -184,7 +198,13 @@ def task_callback(task_output: TaskOutput) -> None:
     def get_step_callback(
         self,
     ) -> Callable:
-        def step_callback(agent_output: AgentFinish | list[tuple[AgentAction, str]]) -> None:
+        try:
+            from langchain_core.agents import AgentFinish
+        except ImportError as e:
+            msg = "langchain_core is not installed. Please install it with `uv pip install langchain-core`."
+            raise ImportError(msg) from e
+
+        def step_callback(agent_output) -> None:
             id_ = self._vertex.id if self._vertex else self.display_name
             if isinstance(agent_output, AgentFinish):
                 messages = agent_output.messages

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

@@ -1,4 +1,7 @@
-from crewai import Task
+try:
+    from crewai import Task
+except ImportError:
+    Task = object
 
 
 class SequentialTask(Task):

src/backend/base/langflow/base/data/docling_utils.py

@@ -26,7 +26,11 @@ def extract_docling_documents(data_inputs: Data | list[Data] | DataFrame, doc_ke
 
         if isinstance(data_inputs, Data):
             if doc_key not in data_inputs.data:
-                msg = f"{doc_key} field not available in the input Data"
+                msg = (
+                    f"'{doc_key}' field not available in the input Data. "
+                    "Check that your input is a DoclingDocument. "
+                    "You can use the Docling component to convert your input to a DoclingDocument."
+                )
                 raise TypeError(msg)
             documents = [data_inputs.data[doc_key]]
         else:

src/backend/base/langflow/base/models/model.py

@@ -84,12 +84,9 @@ def _validate_outputs(self) -> None:
                 raise ValueError(msg)
 
     async def text_response(self) -> Message:
-        input_value = self.input_value
-        stream = self.stream
-        system_message = self.system_message
         output = self.build_model()
         result = await self.get_chat_result(
-            runnable=output, stream=stream, input_value=input_value, system_message=system_message
+            runnable=output, stream=self.stream, input_value=self.input_value, system_message=self.system_message
         )
         self.status = result
         return result
@@ -176,6 +173,7 @@ async def get_chat_result(
         input_value: str | Message,
         system_message: str | None = None,
     ) -> Message:
+        # NVIDIA reasoning models use detailed thinking
         if getattr(self, "detailed_thinking", False):
             system_message = DETAILED_THINKING_PREFIX + (system_message or "")
 

src/backend/base/langflow/base/models/openai_constants.py

@@ -17,6 +17,13 @@
     create_model_metadata(provider="OpenAI", name="gpt-3.5-turbo", icon="OpenAI", tool_calling=True),
     # Reasoning Models
     create_model_metadata(provider="OpenAI", name="o1", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o1-mini", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o1-pro", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o3-mini", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o3", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o3-pro", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o4-mini", icon="OpenAI", reasoning=True),
+    create_model_metadata(provider="OpenAI", name="o4-mini-high", icon="OpenAI", reasoning=True),
     # Search Models
     create_model_metadata(
         provider="OpenAI",
@@ -27,7 +34,12 @@
         preview=True,
     ),
     create_model_metadata(
-        provider="OpenAI", name="gpt-4o-search-preview", icon="OpenAI", tool_calling=True, search=True, preview=True
+        provider="OpenAI",
+        name="gpt-4o-search-preview",
+        icon="OpenAI",
+        tool_calling=True,
+        search=True,
+        preview=True,
     ),
     # Not Supported Models
     create_model_metadata(
@@ -45,16 +57,13 @@
     create_model_metadata(
         provider="OpenAI", name="gpt-4o-mini-realtime-preview", icon="OpenAI", not_supported=True, preview=True
     ),
-    create_model_metadata(provider="OpenAI", name="o3-mini", icon="OpenAI", reasoning=True, not_supported=True),
-    create_model_metadata(provider="OpenAI", name="o1-mini", icon="OpenAI", reasoning=True, not_supported=True),
 ]
-
-OPENAI_MODEL_NAMES = [
+OPENAI_CHAT_MODEL_NAMES = [
     metadata["name"]
     for metadata in OPENAI_MODELS_DETAILED
-    if not metadata.get("reasoning", False)
+    if not metadata.get("not_supported", False)
+    and not metadata.get("reasoning", False)
     and not metadata.get("search", False)
-    and not metadata.get("not_supported", False)
 ]
 
 OPENAI_REASONING_MODEL_NAMES = [
@@ -78,4 +87,4 @@
 ]
 
 # Backwards compatibility
-MODEL_NAMES = OPENAI_MODEL_NAMES
+MODEL_NAMES = OPENAI_CHAT_MODEL_NAMES

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

@@ -1,5 +1,3 @@
-from crewai import Agent
-
 from langflow.base.agents.crewai.crew import convert_llm, convert_tools
 from langflow.custom.custom_component.component import Component
 from langflow.io import BoolInput, DictInput, HandleInput, MultilineInput, Output
@@ -22,6 +20,7 @@ class CrewAIAgentComponent(Component):
     description = "Represents an agent of CrewAI."
     documentation: str = "https://docs.crewai.com/how-to/LLM-Connections/"
     icon = "CrewAI"
+    legacy = True
 
     inputs = [
         MultilineInput(name="role", display_name="Role", info="The role of the agent."),
@@ -80,7 +79,13 @@ class CrewAIAgentComponent(Component):
         Output(display_name="Agent", name="output", method="build_output"),
     ]
 
-    def build_output(self) -> Agent:
+    def build_output(self):
+        try:
+            from crewai import Agent
+        except ImportError as e:
+            msg = "CrewAI is not installed. Please install it with `uv pip install crewai`."
+            raise ImportError(msg) from e
+
         kwargs = self.kwargs or {}
 
         # Define the Agent

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

@@ -1,5 +1,3 @@
-from crewai import Crew, Process
-
 from langflow.base.agents.crewai.crew import BaseCrewComponent
 from langflow.io import HandleInput
 
@@ -11,6 +9,7 @@ class HierarchicalCrewComponent(BaseCrewComponent):
     )
     documentation: str = "https://docs.crewai.com/how-to/Hierarchical/"
     icon = "CrewAI"
+    legacy = True
 
     inputs = [
         *BaseCrewComponent._base_inputs,
@@ -20,7 +19,13 @@ class HierarchicalCrewComponent(BaseCrewComponent):
         HandleInput(name="manager_agent", display_name="Manager Agent", input_types=["Agent"], required=False),
     ]
 
-    def build_crew(self) -> Crew:
+    def build_crew(self):
+        try:
+            from crewai import Crew, Process
+        except ImportError as e:
+            msg = "CrewAI is not installed. Please install it with `uv pip install crewai`."
+            raise ImportError(msg) from e
+
         tasks, agents = self.get_tasks_and_agents()
         manager_llm = self.get_manager_llm()
 

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

@@ -7,6 +7,7 @@ class HierarchicalTaskComponent(Component):
     display_name: str = "Hierarchical Task"
     description: str = "Each task must have a description, an expected output and an agent responsible for execution."
     icon = "CrewAI"
+    legacy = True
     inputs = [
         MultilineInput(
             name="task_description",

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

@@ -1,5 +1,3 @@
-from crewai import Agent, Crew, Process, Task
-
 from langflow.base.agents.crewai.crew import BaseCrewComponent
 from langflow.io import HandleInput
 from langflow.schema.message import Message
@@ -10,18 +8,19 @@ class SequentialCrewComponent(BaseCrewComponent):
     description: str = "Represents a group of agents with tasks that are executed sequentially."
     documentation: str = "https://docs.crewai.com/how-to/Sequential/"
     icon = "CrewAI"
+    legacy = True
 
     inputs = [
         *BaseCrewComponent._base_inputs,
         HandleInput(name="tasks", display_name="Tasks", input_types=["SequentialTask"], is_list=True),
     ]
 
     @property
-    def agents(self: "SequentialCrewComponent") -> list[Agent]:
+    def agents(self: "SequentialCrewComponent") -> list:
         # Derive agents directly from linked tasks
         return [task.agent for task in self.tasks if hasattr(task, "agent")]
 
-    def get_tasks_and_agents(self, agents_list=None) -> tuple[list[Task], list[Agent]]:
+    def get_tasks_and_agents(self, agents_list=None) -> tuple[list, list]:
         # Use the agents property to derive agents
         if not agents_list:
             existing_agents = self.agents
@@ -30,6 +29,12 @@ def get_tasks_and_agents(self, agents_list=None) -> tuple[list[Task], list[Agent
         return super().get_tasks_and_agents(agents_list=agents_list)
 
     def build_crew(self) -> Message:
+        try:
+            from crewai import Crew, Process
+        except ImportError as e:
+            msg = "CrewAI is not installed. Please install it with `uv pip install crewai`."
+            raise ImportError(msg) from e
+
         tasks, agents = self.get_tasks_and_agents()
 
         return Crew(

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

@@ -7,6 +7,7 @@ class SequentialTaskComponent(Component):
     display_name: str = "Sequential Task"
     description: str = "Each task must have a description, an expected output and an agent responsible for execution."
     icon = "CrewAI"
+    legacy = True
     inputs = [
         MultilineInput(
             name="task_description",
@@ -65,7 +66,7 @@ def build_task(self) -> list[SequentialTask]:
         tasks.append(task)
         self.status = task
         if self.task:
-            if isinstance(self.task, list) and all(isinstance(task, SequentialTask) for task in self.task):
+            if isinstance(self.task, list) and all(isinstance(task_item, SequentialTask) for task_item in self.task):
                 tasks = self.task + tasks
             elif isinstance(self.task, SequentialTask):
                 tasks = [self.task, *tasks]