---
license: mit
---

# Table of Contents

* [LCToolFlow](#LCToolFlow)
  * [LCToolFlow](#LCToolFlow.LCToolFlow)
    * [instantiate\_from\_config](#LCToolFlow.LCToolFlow.instantiate_from_config)
    * [run](#LCToolFlow.LCToolFlow.run)

<a id="LCToolFlow"></a>

# LCToolFlow

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## LCToolFlow Objects

```python
class LCToolFlow(AtomicFlow)
```

A flow that runs a tool using langchain. For example, a tool could be to excute a query with the duckduckgo search engine.

*Configuration Parameters*:

- `name` (str): The name of the flow. Default: "search"
- `description` (str): A description of the flow. This description is used to generate the help message of the flow.
Default: "useful when you need to look for the answer online, especially for recent events."
- `keep_raw_response` (bool): If True, the raw response of the tool is kept. Default: False
- `clear_flow_namespase_on_run_end` (bool): If True, the flow namespace is cleared at the end of the run. Default: False
- `backend` (Dict[str, Any]): The configuration of the backend. Default: langchain.tools.DuckDuckGoSearchRun
- Other parameters are inherited from the default configuration of AtomicFlow (see AtomicFlow)

*Input Interface*:

- `query` (str): the query to run the tool on

*Output Interface*:

- `observation` (str): the observation returned by the tool

**Arguments**:

- `backend` (`BaseTool`): The backend of the flow. It is a tool that is run by the flow. (e.g. duckduckgo search engine)
- `\**kwargs`: Additional arguments to pass to the flow. See :class:`aiflows.base_flows.AtomicFlow` for more details.

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#### instantiate\_from\_config

```python
@classmethod
def instantiate_from_config(cls, config: Dict[str, Any]) -> LCToolFlow
```

This method instantiates the flow from a configuration file

**Arguments**:

- `config` (`Dict[str, Any]`): The configuration of the flow.

**Returns**:

`LCToolFlow`: The instantiated flow.

<a id="LCToolFlow.LCToolFlow.run"></a>

#### run

```python
def run(input_data: Dict[str, Any]) -> Dict[str, Any]
```

This method runs the flow. It runs the backend on the input data.

**Arguments**:

- `input_data` (`Dict[str, Any]`): The input data of the flow.

**Returns**:

`Dict[str, Any]`: The output data of the flow.