About bundles
Bundles contain custom components that support specific third-party integrations with Langflow. You add them to your flows and configure them in the same way as Langflow's core components.
To browse bundles, click Bundles in the visual editor.
Bundle maintenance and documentation
Many bundled components are developed by third-party contributors to the Langflow codebase.
Some providers contribute documentation with their bundles, whereas others document their bundles in their own documentation. Some bundles have no documentation.
To find documentation for a specific bundled component, browse the Langflow docs and your provider's documentation. If available, you can also find links to relevant documentation, such as API endpoints, through the component itself:
- Click the component to expose the component inspection panel.
- Click More.
- Select Docs.
The Langflow documentation focuses on using bundles within flows. For that reason, it focuses on the Langflow-specific configuration steps for bundled components. For information about provider-specific features or APIs, see the provider's documentation.
Component parameters
Some parameters are hidden by default in the visual editor. You can modify all component parameters through the component inspection panel that appears when you select a component.
Core components and bundles
For the most accurate and up-to-date list of components within each bundle for your version of Langflow, check Bundles in the visual editor.
If you can't find a component that you used in an earlier version of Langflow, it may have been removed or marked as a legacy component.
Langflow offers generic Core components in addition to third-party, provider-specific bundles.
If you are looking for a specific service or integration, you can Search components in the visual editor.
If all else fails, you can always create your own custom components.
Install bundle components
uv pip install langflow includes the default curated provider set.
It does not include the opt-in bundles listed in
Additional bundles.
Install a missing provider, or install the supported torch-free full
profile with uv pip install "langflow[bundles]".
If you install lfx directly or need to add bundles to an existing environment, see Install LFX with bundle components.
Torch opt-in installs
The default uv pip install langflow and full uv pip install "langflow[bundles]" installations do not install dependencies for components that require PyTorch.
To install PyTorch and the components that require it, run the following in your Langflow virtual environment:
uv pip install "lfx-bundles[all]"
Legacy bundles
Legacy components are no longer supported and can be removed in a future release. You can continue to use them in existing flows, but it is recommended that you replace them with supported components as soon as possible. Suggested replacements are included in the Legacy banner on components in your flows. They are also given in release notes and Langflow documentation whenever possible.
If you aren't sure how to replace a legacy component, Search for components by provider, service, or component name. The component may have been deprecated in favor of a completely new component, a similar component, or a new version of the same component in a different category.
If there is no obvious replacement, consider whether another component can be adapted to your use case. For example, many Core components provide generic functionality that can support multiple providers and use cases, such as the API Request component.
If neither of these options are viable, you could use the legacy component's code to create your own custom component, or start a discussion about the legacy component.
To discourage use of legacy components in new flows, these components are hidden by default. In the visual editor, you can click Component settings to toggle the Legacy filter.
The following bundles include only legacy components.
Chroma DB and Local DB
The Chroma DB and Local DB components are legacy in Langflow 1.13. Saved nodes remain on the canvas so you can inspect older flows. Replace Chroma DB and Local DB with a knowledge base or a supported remote vector store before running the flow. For data already stored in local Chroma, see Upgrade Knowledge and Memory storage.
ALTK bundle
The ALTK component is removed in Langflow 1.13. Saved nodes remain on the canvas so you can inspect older flows. Replace ALTK with the Agent component before running the flow.
CrewAI bundle
Replace the following legacy CrewAI components with other agentic components, such as the Agent component.
CrewAI Agent
This component represents CrewAI agents, allowing for the creation of specialized AI agents with defined roles goals and capabilities within a crew. For more information, see the CrewAI agents documentation.
This component accepts the following parameters:
| Name | Display Name | Info |
|---|---|---|
| role | Role | Input parameter. The role of the agent. |
| goal | Goal | Input parameter. The objective of the agent. |
| backstory | Backstory | Input parameter. The backstory of the agent. |
| tools | Tools | Input parameter. The tools at the agent's disposal. |
| llm | Language Model | Input parameter. The language model that runs the agent. |
| memory | Memory | Input parameter. This determines whether the agent should have memory or not. |
| verbose | Verbose | Input parameter. This enables verbose output. |
| allow_delegation | Allow Delegation | Input parameter. This determines whether the agent is allowed to delegate tasks to other agents. |
| allow_code_execution | Allow Code Execution | Input parameter. This determines whether the agent is allowed to execute code. |
| kwargs | kwargs | Input parameter. Additional keyword arguments for the agent. |
| output | Agent | Output parameter. The constructed CrewAI Agent object. |
CrewAI Hierarchical Crew, CrewAI Hierarchical Task
The CrewAI Hierarchical Crew 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 hierarchical crew documentation.
It accepts the following parameters:
| Name | Display Name | Info |
|---|---|---|
| agents | Agents | Input parameter. The list of Agent objects representing the crew members. |
| tasks | Tasks | Input parameter. The list of HierarchicalTask objects representing the tasks to be executed. |
| manager_llm | Manager LLM | Input parameter. The language model for the manager agent. |
| manager_agent | Manager Agent | Input parameter. The specific agent to act as the manager. |
| verbose | Verbose | Input parameter. This enables verbose output for detailed logging. |
| memory | Memory | Input parameter. The memory configuration for the crew. |
| use_cache | Use Cache | Input parameter. This enables caching of results. |
| max_rpm | Max RPM | Input parameter. This sets the maximum requests per minute. |
| share_crew | Share Crew | Input parameter. This determines if the crew information is shared among agents. |
| function_calling_llm | Function Calling LLM | Input parameter. The language model for function calling. |
| crew | Crew | Output parameter. The constructed Crew object with hierarchical task execution. |
CrewAI Sequential Crew, CrewAI Sequential Task
The CrewAI Sequential Crew 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 sequential crew documentation.
It accepts the following parameters:
| Name | Display Name | Info |
|---|---|---|
| tasks | Tasks | Input parameter. The list of SequentialTask objects representing the tasks to be executed. |
| verbose | Verbose | Input parameter. This enables verbose output for detailed logging. |
| memory | Memory | Input parameter. The memory configuration for the crew. |
| use_cache | Use Cache | Input parameter. This enables caching of results. |
| max_rpm | Max RPM | Input parameter. This sets the maximum requests per minute. |
| share_crew | Share Crew | Input parameter. This determines if the crew information is shared among agents. |
| function_calling_llm | Function Calling LLM | Input parameter. The language model for function calling. |
| crew | Crew | Output parameter. The constructed Crew object with sequential task execution. |
CrewAI 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 sequential agents documentation.
It accepts the following parameters:
| Name | Display Name | Info |
|---|---|---|
| role | Role | Input parameter. The role of the agent. |
| goal | Goal | Input parameter. The objective of the agent. |
| backstory | Backstory | Input parameter. The backstory of the agent. |
| tools | Tools | Input parameter. The tools at the agent's disposal. |
| llm | Language Model | Input parameter. The language model that runs the agent. |
| memory | Memory | Input parameter. This determines whether the agent should have memory or not. |
| verbose | Verbose | Input parameter. This enables verbose output. |
| allow_delegation | Allow Delegation | Input parameter. This determines whether the agent is allowed to delegate tasks to other agents. |
| allow_code_execution | Allow Code Execution | Input parameter. This determines whether the agent is allowed to execute code. |
| agent_kwargs | Agent kwargs | Input parameter. The additional kwargs for the agent. |
| task_description | Task Description | Input parameter. The descriptive text detailing the task's purpose and execution. |
| expected_output | Expected Task Output | Input parameter. The clear definition of the expected task outcome. |
| async_execution | Async Execution | Input parameter. Boolean flag indicating asynchronous task execution. |
| previous_task | Previous Task | Input parameter. The previous task in the sequence for chaining. |
| task_output | Sequential Task | Output parameter. The list of SequentialTask objects representing the created tasks. |
Embeddings bundle
- Embedding Similarity: Replaced by built-in similarity search functionality in vector store components.
- Text Embedder: Replaced by the embedding model components.
Zep bundle
Zep Chat Memory
The Zep Chat Memory component is a legacy component. Replace this component with the Message History component.
This component creates a ZepChatMessageHistory instance, enabling storage and retrieval of chat messages using Zep, a memory server for LLMs.
It accepts the following parameters:
| Name | Type | Description |
|---|---|---|
| url | MessageText | Input parameter. The URL of the Zep instance. Required. |
| api_key | SecretString | Input parameter. The API Key for authentication with the Zep instance. |
| api_base_path | Dropdown | Input parameter. The API version to use. Options include api/v1 or api/v2. |
| session_id | MessageText | Input parameter. The unique identifier for the chat session. Optional. |
| message_history | BaseChatMessageHistory | Output parameter. An instance of ZepChatMessageHistory for the session. |
Was this page helpful?
