ref: refactors the agents around and fixes a few bugs (#2847)

src/backend/base/langflow/base/agents/agent.py

@@ -1,5 +1,5 @@
 from abc import abstractmethod
-from typing import List, Optional, Union, cast
+from typing import List, Union, cast
 
 from langchain.agents import AgentExecutor, BaseMultiActionAgent, BaseSingleActionAgent
 from langchain.agents.agent import RunnableAgent
@@ -9,10 +9,9 @@ from langchain_core.runnables import Runnable
 from langflow.base.agents.callback import AgentAsyncHandler
 from langflow.base.agents.utils import data_to_messages
 from langflow.custom import Component
-from langflow.field_typing import Text, Tool
+from langflow.field_typing import Text
 from langflow.inputs.inputs import DataInput, InputTypes
 from langflow.io import BoolInput, HandleInput, IntInput, MessageTextInput
-from langflow.schema import Data
 from langflow.schema.message import Message
 from langflow.template import Output
 
@@ -39,6 +38,7 @@ class LCAgentComponent(Component):
             value=15,
             advanced=True,
         ),
+        DataInput(name="chat_history", display_name="Chat History", is_list=True, advanced=True),
     ]
 
     outputs = [
@@ -46,15 +46,16 @@ class LCAgentComponent(Component):
         Output(display_name="Response", name="response", method="message_response"),
     ]
 
+    @abstractmethod
+    def build_agent(self) -> AgentExecutor:
+        """Create the agent."""
+        pass
+
     async def message_response(self) -> Message:
+        """Run the agent and return the response."""
         agent = self.build_agent()
-        result = await self.run_agent(
+        result = await self.run_agent(agent=agent)
-            agent=agent,
+
-            inputs=self.input_value,
-            tools=self.tools,
-            message_history=self.chat_history,
-            handle_parsing_errors=self.handle_parsing_errors,
-        )
         if isinstance(result, list):
             result = "\n".join([result_dict["text"] for result_dict in result])
         message = Message(text=result, sender="Machine")
@@ -87,27 +88,11 @@ class LCAgentComponent(Component):
             }
         return {**base, "agent_executor_kwargs": agent_kwargs}
 
-    async def run_agent(
+    async def run_agent(self, agent: AgentExecutor) -> Text:
-        self,
+        input_dict: dict[str, str | list[BaseMessage]] = {"input": self.input_value}
-        agent: Union[Runnable, BaseSingleActionAgent, BaseMultiActionAgent, AgentExecutor],
+        if self.chat_history:
-        inputs: str,
+            input_dict["chat_history"] = data_to_messages(self.chat_history)
-        tools: List[Tool],
+        result = await agent.ainvoke(input_dict, config={"callbacks": [AgentAsyncHandler(self.log)]})
-        message_history: Optional[List[Data]] = None,
-        handle_parsing_errors: bool = True,
-    ) -> Text:
-        if isinstance(agent, AgentExecutor):
-            runnable = agent
-        else:
-            runnable = AgentExecutor.from_agent_and_tools(
-                agent=agent,  # type: ignore
-                tools=tools,
-                verbose=True,
-                handle_parsing_errors=handle_parsing_errors,
-            )
-        input_dict: dict[str, str | list[BaseMessage]] = {"input": inputs}
-        if message_history:
-            input_dict["chat_history"] = data_to_messages(message_history)
-        result = await runnable.ainvoke(input_dict, config={"callbacks": [AgentAsyncHandler(self.log)]})
         self.status = result
         if "output" not in result:
             raise ValueError("Output key not found in result. Tried 'output'.")
@@ -123,24 +108,41 @@ class LCToolsAgentComponent(LCAgentComponent):
             input_types=["Tool", "BaseTool"],
             is_list=True,
         ),
-        HandleInput(
-            name="llm",
-            display_name="Language Model",
-            input_types=["LanguageModel", "ToolEnabledLanguageModel"],
-            required=True,
-        ),
-        DataInput(name="chat_history", display_name="Chat History", is_list=True),
     ]
 
     def build_agent(self) -> AgentExecutor:
-        agent = self.creat_agent_runnable()
+        agent = self.create_agent_runnable()
         return AgentExecutor.from_agent_and_tools(
             agent=RunnableAgent(runnable=agent, input_keys_arg=["input"], return_keys_arg=["output"]),
             tools=self.tools,
             **self.get_agent_kwargs(flatten=True),
         )
 
+    async def run_agent(
+        self,
+        agent: Union[Runnable, BaseSingleActionAgent, BaseMultiActionAgent, AgentExecutor],
+    ) -> Text:
+        if isinstance(agent, AgentExecutor):
+            runnable = agent
+        else:
+            runnable = AgentExecutor.from_agent_and_tools(
+                agent=agent,  # type: ignore
+                tools=self.tools,
+                handle_parsing_errors=self.handle_parsing_errors,
+                verbose=self.verbose,
+                max_iterations=self.max_iterations,
+            )
+        input_dict: dict[str, str | list[BaseMessage]] = {"input": self.input_value}
+        if self.chat_history:
+            input_dict["chat_history"] = data_to_messages(self.chat_history)
+        result = await runnable.ainvoke(input_dict, config={"callbacks": [AgentAsyncHandler(self.log)]})
+        self.status = result
+        if "output" not in result:
+            raise ValueError("Output key not found in result. Tried 'output'.")
+
+        return cast(str, result.get("output"))
+
     @abstractmethod
-    def creat_agent_runnable(self) -> Runnable:
+    def create_agent_runnable(self) -> Runnable:
         """Create the agent."""
         pass

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

@@ -27,6 +27,7 @@ class BaseCrewComponent(Component):
             name="function_calling_llm",
             display_name="Function Calling LLM",
             input_types=["LanguageModel"],
+            info="Turns the ReAct CrewAI agent into a function-calling agent",
             required=False,
             advanced=True,
         ),

src/backend/base/langflow/components/agents/CSVAgent.py

@@ -12,8 +12,8 @@ class CSVAgentComponent(LCAgentComponent):
     name = "CSVAgent"
 
     inputs = LCAgentComponent._base_inputs + [
-        FileInput(name="path", display_name="File Path", file_types=["csv"], required=True),
         HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
+        FileInput(name="path", display_name="File Path", file_types=["csv"], required=True),
         DropdownInput(
             name="agent_type",
             display_name="Agent Type",

src/backend/base/langflow/components/agents/HierarchicalCrew.py

@@ -9,6 +9,8 @@ class HierarchicalCrewComponent(BaseCrewComponent):
     description: str = (
         "Represents a group of agents, defining how they should collaborate and the tasks they should perform."
     )
+    documentation: str = "https://docs.crewai.com/how-to/Hierarchical/"
+    icon = "CrewAI"
 
     inputs = BaseCrewComponent._base_inputs + [
         HandleInput(name="agents", display_name="Agents", input_types=["Agent"], is_list=True),

src/backend/base/langflow/components/agents/JsonAgent.py

@@ -16,8 +16,8 @@ class JsonAgentComponent(LCAgentComponent):
     name = "JsonAgent"
 
     inputs = LCAgentComponent._base_inputs + [
-        FileInput(name="path", display_name="File Path", file_types=["json", "yaml", "yml"], required=True),
         HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
+        FileInput(name="path", display_name="File Path", file_types=["json", "yaml", "yml"], required=True),
     ]
 
     def build_agent(self) -> AgentExecutor:

src/backend/base/langflow/components/agents/OpenAIToolsAgent.py

@@ -3,6 +3,7 @@ from langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMess
 
 from langflow.base.agents.agent import LCToolsAgentComponent
 from langflow.inputs import MultilineInput
+from langflow.inputs.inputs import HandleInput
 
 
 class OpenAIToolsAgentComponent(LCToolsAgentComponent):
@@ -13,6 +14,12 @@ class OpenAIToolsAgentComponent(LCToolsAgentComponent):
     name = "OpenAIToolsAgent"
 
     inputs = LCToolsAgentComponent._base_inputs + [
+        HandleInput(
+            name="llm",
+            display_name="Language Model",
+            input_types=["LanguageModel", "ToolEnabledLanguageModel"],
+            required=True,
+        ),
         MultilineInput(
             name="system_prompt",
             display_name="System Prompt",
@@ -24,7 +31,7 @@ class OpenAIToolsAgentComponent(LCToolsAgentComponent):
         ),
     ]
 
-    def creat_agent_runnable(self):
+    def create_agent_runnable(self):
         if "input" not in self.user_prompt:
             raise ValueError("Prompt must contain 'input' key.")
         messages = [

src/backend/base/langflow/components/agents/OpenAPIAgent.py

@@ -17,8 +17,8 @@ class OpenAPIAgentComponent(LCAgentComponent):
     name = "OpenAPIAgent"
 
     inputs = LCAgentComponent._base_inputs + [
-        FileInput(name="path", display_name="File Path", file_types=["json", "yaml", "yml"], required=True),
         HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
+        FileInput(name="path", display_name="File Path", file_types=["json", "yaml", "yml"], required=True),
         BoolInput(name="allow_dangerous_requests", display_name="Allow Dangerous Requests", value=False, required=True),
     ]
 
@@ -37,6 +37,9 @@ class OpenAPIAgentComponent(LCAgentComponent):
         )
 
         agent_args = self.get_agent_kwargs()
+
+        # This is bit weird - generally other create_*_agent functions have max_iterations in the
+        # `agent_executor_kwargs`, but openai has this parameter passed directly.
         agent_args["max_iterations"] = agent_args["agent_executor_kwargs"]["max_iterations"]
         del agent_args["agent_executor_kwargs"]["max_iterations"]
         return create_openapi_agent(llm=self.llm, toolkit=toolkit, **agent_args)

src/backend/base/langflow/components/agents/SQLAgent.py

@@ -13,8 +13,15 @@ class SQLAgentComponent(LCAgentComponent):
     name = "SQLAgent"
 
     inputs = LCAgentComponent._base_inputs + [
-        MessageTextInput(name="database_uri", display_name="Database URI", required=True),
         HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
+        MessageTextInput(name="database_uri", display_name="Database URI", required=True),
+        HandleInput(
+            name="extra_tools",
+            display_name="Extra Tools",
+            input_types=["Tool", "BaseTool"],
+            is_list=True,
+            advanced=True,
+        ),
     ]
 
     def build_agent(self) -> AgentExecutor:
@@ -23,4 +30,4 @@ class SQLAgentComponent(LCAgentComponent):
         agent_args = self.get_agent_kwargs()
         agent_args["max_iterations"] = agent_args["agent_executor_kwargs"]["max_iterations"]
         del agent_args["agent_executor_kwargs"]["max_iterations"]
-        return create_sql_agent(llm=self.llm, toolkit=toolkit, **agent_args)
+        return create_sql_agent(llm=self.llm, toolkit=toolkit, extra_tools=self.extra_tools or [], **agent_args)

src/backend/base/langflow/components/agents/SequentialCrew.py

@@ -7,10 +7,8 @@ from langflow.schema.message import Message
 
 class SequentialCrewComponent(BaseCrewComponent):
     display_name: str = "Sequential Crew"
-    description: str = (
+    description: str = "Represents a group of agents with tasks that are executed sequentially."
-        "Represents a group of agents, defining how they should collaborate and the tasks they should perform."
+    documentation: str = "https://docs.crewai.com/how-to/Sequential/"
-    )
-    documentation: str = "https://docs.crewai.com/how-to/LLM-Connections/"
     icon = "CrewAI"
 
     inputs = BaseCrewComponent._base_inputs + [

src/backend/base/langflow/components/agents/ToolCallingAgent.py

@@ -2,6 +2,7 @@ from langchain.agents import create_tool_calling_agent
 from langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMessagePromptTemplate
 from langflow.base.agents.agent import LCToolsAgentComponent
 from langflow.inputs import MultilineInput
+from langflow.inputs.inputs import HandleInput
 
 
 class ToolCallingAgentComponent(LCToolsAgentComponent):
@@ -12,6 +13,7 @@ class ToolCallingAgentComponent(LCToolsAgentComponent):
     name = "ToolCallingAgent"
 
     inputs = LCToolsAgentComponent._base_inputs + [
+        HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
         MultilineInput(
             name="system_prompt",
             display_name="System Prompt",
@@ -23,7 +25,7 @@ class ToolCallingAgentComponent(LCToolsAgentComponent):
         ),
     ]
 
-    def creat_agent_runnable(self):
+    def create_agent_runnable(self):
         if "input" not in self.user_prompt:
             raise ValueError("Prompt must contain 'input' key.")
         messages = [

src/backend/base/langflow/components/agents/XMLAgent.py

@@ -3,6 +3,7 @@ from langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMess
 
 from langflow.base.agents.agent import LCToolsAgentComponent
 from langflow.inputs import MultilineInput
+from langflow.inputs.inputs import HandleInput
 
 
 class XMLAgentComponent(LCToolsAgentComponent):
@@ -13,6 +14,7 @@ class XMLAgentComponent(LCToolsAgentComponent):
     name = "XMLAgent"
 
     inputs = LCToolsAgentComponent._base_inputs + [
+        HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
         MultilineInput(
             name="user_prompt",
             display_name="Prompt",
@@ -44,7 +46,7 @@ Question: {input}
         ),
     ]
 
-    def creat_agent_runnable(self):
+    def create_agent_runnable(self):
         messages = [
             HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=["input"], template=self.user_prompt))
         ]