Agent components in Langflow
Agent components define the behavior and capabilities of AI agents in your flow.
Agents use LLMs as a reasoning engine to decide which of the connected tool components to use to solve a problem.
Tools in agentic functions are essentially functions that the agent can call to perform tasks or access external resources.
A function is wrapped as a Tool object with a common interface the agent understands.
Agents become aware of tools through tool registration where the agent is provided a list of available tools typically at agent initialization. The Tool object's description tells the agent what the tool can do.
The agent then uses a connected LLM to reason through the problem to decide which tool is best for the job.
Use an agent in a flow
The simple agent starter project uses an agent component connected to URL and Calculator tools to answer a user's questions. The OpenAI LLM acts as a brain for the agent to decide which tool to use. Tools are connected to agent components at the Tools port.
For a multi-agent example see, Create a problem-solving agent.
Agent component
This component creates an agent that can use tools to answer questions and perform tasks based on given instructions.
The component includes an LLM model integration, a system message prompt, and a Tools port to connect tools to extend its capabilities.
For more information on this component, see the tool calling agent documentation.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| agent_llm | Dropdown | The provider of the language model that the agent uses to generate responses. Options include OpenAI and other providers or Custom. |
| system_prompt | String | The system prompt provides initial instructions and context to guide the agent's behavior. |
| tools | List | The list of tools available for the agent to use. |
| input_value | String | The input task or question for the agent to process. |
| add_current_date_tool | Boolean | When true this adds a tool to the agent that returns the current date. |
| memory | Memory | An optional memory configuration for maintaining conversation history. |
| max_iterations | Integer | The maximum number of iterations the agent can perform. |
| handle_parsing_errors | Boolean | This determines whether to handle parsing errors during agent execution. |
| verbose | Boolean | This enables verbose output for detailed logging. |
Outputs
| Name | Type | Description |
|---|---|---|
| response | Message | The agent's response to the given input task. |
Legacy components
Legacy components are available for use but are no longer supported.
JSON Agent
This component creates a JSON agent from a JSON or YAML file and an LLM.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| path | File | The path to the JSON or YAML file. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The JSON agent instance. |
Vector Store Agent
This component creates a Vector Store Agent using LangChain.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| vectorstore | VectorStoreInfo | The vector store information for the agent to use. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The Vector Store Agent instance. |
Vector Store Router Agent
This component creates a Vector Store Router Agent using LangChain.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| vectorstores | List[VectorStoreInfo] | The list of vector store information for the agent to route between. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The Vector Store Router Agent instance. |
Moved components
The following components are available under Bundles.
CrewAI Agent
This component represents an Agent of CrewAI allowing for the creation of specialized AI agents with defined roles goals and capabilities within a crew.
For more information, see the CrewAI documentation.
Parameters
Inputs
| Name | Display Name | Info |
|---|---|---|
| role | Role | The role of the agent. |
| goal | Goal | The objective of the agent. |
| backstory | Backstory | The backstory of the agent. |
| tools | Tools | The tools at the agent's disposal. |
| llm | Language Model | The language model that runs the agent. |
| memory | Memory | This determines whether the agent should have memory or not. |
| verbose | Verbose | This enables verbose output. |
| allow_delegation | Allow Delegation | This determines whether the agent is allowed to delegate tasks to other agents. |
| allow_code_execution | Allow Code Execution | This determines whether the agent is allowed to execute code. |
| kwargs | kwargs | Additional keyword arguments for the agent. |
Outputs
| Name | Display Name | Info |
|---|---|---|
| output | Agent | The constructed CrewAI Agent object. |
Hierarchical Crew
This component represents a group of agents managing how they should collaborate and the tasks they should perform in a hierarchical structure. This component allows for the creation of a crew with a manager overseeing the task execution.
For more information, see the CrewAI documentation.
Parameters
Inputs
| Name | Display Name | Info |
|---|---|---|
| agents | Agents | The list of Agent objects representing the crew members. |
| tasks | Tasks | The list of HierarchicalTask objects representing the tasks to be executed. |
| manager_llm | Manager LLM | The language model for the manager agent. |
| manager_agent | Manager Agent | The specific agent to act as the manager. |
| verbose | Verbose | This enables verbose output for detailed logging. |
| memory | Memory | The memory configuration for the crew. |
| use_cache | Use Cache | This enables caching of results. |
| max_rpm | Max RPM | This sets the maximum requests per minute. |
| share_crew | Share Crew | This determines if the crew information is shared among agents. |
| function_calling_llm | Function Calling LLM | The language model for function calling. |
Outputs
| Name | Display Name | Info |
|---|---|---|
| crew | Crew | The constructed Crew object with hierarchical task execution. |
CSV Agent
This component creates a CSV agent from a CSV file and LLM.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| path | File | The path to the CSV file. |
| agent_type | String | The type of agent to create. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The CSV agent instance. |
OpenAI Tools Agent
This component creates an OpenAI Tools Agent.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use. |
| tools | List of Tools | The tools to give the agent access to. |
| system_prompt | String | The system prompt to provide context to the agent. |
| input_value | String | The user's input to the agent. |
| memory | Memory | The memory for the agent to use for context persistence. |
| max_iterations | Integer | The maximum number of iterations to allow the agent to execute. |
| verbose | Boolean | This determines whether to print out the agent's intermediate steps. |
| handle_parsing_errors | Boolean | This determines whether to handle parsing errors in the agent. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The OpenAI Tools agent instance. |
| output | String | The output from executing the agent on the input. |
OpenAPI Agent
This component creates an agent for interacting with OpenAPI services.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use. |
| openapi_spec | String | The OpenAPI specification for the service. |
| base_url | String | The base URL for the API. |
| headers | Dict | The optional headers for API requests. |
| agent_executor_kwargs | Dict | The optional parameters for the agent executor. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The OpenAPI agent instance. |
Sequential Crew
This component represents a group of agents with tasks that are executed sequentially. This component allows for the creation of a crew that performs tasks in a specific order.
For more information, see the CrewAI documentation.
Parameters
Inputs
| Name | Display Name | Info |
|---|---|---|
| tasks | Tasks | The list of SequentialTask objects representing the tasks to be executed. |
| verbose | Verbose | This enables verbose output for detailed logging. |
| memory | Memory | The memory configuration for the crew. |
| use_cache | Use Cache | This enables caching of results. |
| max_rpm | Max RPM | This sets the maximum requests per minute. |
| share_crew | Share Crew | This determines if the crew information is shared among agents. |
| function_calling_llm | Function Calling LLM | The language model for function calling. |
Outputs
| Name | Display Name | Info |
|---|---|---|
| crew | Crew | The constructed Crew object with sequential task execution. |
Sequential task agent
This component creates a CrewAI Task and its associated Agent allowing for the definition of sequential tasks with specific agent roles and capabilities.
For more information, see the CrewAI documentation.
Parameters
Inputs
| Name | Display Name | Info |
|---|---|---|
| role | Role | The role of the agent. |
| goal | Goal | The objective of the agent. |
| backstory | Backstory | The backstory of the agent. |
| tools | Tools | The tools at the agent's disposal. |
| llm | Language Model | The language model that runs the agent. |
| memory | Memory | This determines whether the agent should have memory or not. |
| verbose | Verbose | This enables verbose output. |
| allow_delegation | Allow Delegation | This determines whether the agent is allowed to delegate tasks to other agents. |
| allow_code_execution | Allow Code Execution | This determines whether the agent is allowed to execute code. |
| agent_kwargs | Agent kwargs | The additional kwargs for the agent. |
| task_description | Task Description | The descriptive text detailing the task's purpose and execution. |
| expected_output | Expected Task Output | The clear definition of the expected task outcome. |
| async_execution | Async Execution | The boolean flag indicating asynchronous task execution. |
| previous_task | Previous Task | The previous task in the sequence for chaining. |
Outputs
| Name | Display Name | Info |
|---|---|---|
| task_output | Sequential Task | The list of SequentialTask objects representing the created tasks. |
SQL Agent
This component creates an agent for interacting with SQL databases.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use. |
| database | Database | The SQL database connection. |
| top_k | Integer | The number of results to return from a SELECT query. |
| use_tools | Boolean | This determines whether to use tools for query execution. |
| return_intermediate_steps | Boolean | This determines whether to return the agent's intermediate steps. |
| max_iterations | Integer | The maximum number of iterations to run the agent. |
| max_execution_time | Integer | The maximum execution time in seconds. |
| early_stopping_method | String | The method to use for early stopping. |
| verbose | Boolean | This determines whether to print the agent's thoughts. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The SQL agent instance. |
Tool Calling Agent
This component creates an agent for structured tool calling with various language models.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use. |
| tools | List[Tool] | The list of tools available to the agent. |
| system_message | String | The system message to use for the agent. |
| return_intermediate_steps | Boolean | This determines whether to return the agent's intermediate steps. |
| max_iterations | Integer | The maximum number of iterations to run the agent. |
| max_execution_time | Integer | The maximum execution time in seconds. |
| early_stopping_method | String | The method to use for early stopping. |
| verbose | Boolean | This determines whether to print the agent's thoughts. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The tool calling agent instance. |
XML Agent
This component creates an XML Agent using LangChain.
The agent uses XML formatting for tool instructions to the Language Model.
Parameters
Inputs
| Name | Type | Description |
|---|---|---|
| llm | LanguageModel | The language model to use for the agent. |
| user_prompt | String | The custom prompt template for the agent with XML formatting instructions. |
| tools | List[Tool] | The list of tools available to the agent. |
Outputs
| Name | Type | Description |
|---|---|---|
| agent | AgentExecutor | The XML Agent instance. |
