README.md

---
license: mit
---
# Table of Contents

* [ChatHumanFlowModule](#ChatHumanFlowModule)
  * [ChatHumanFlowModule](#ChatHumanFlowModule.ChatHumanFlowModule)
    * [set\_up\_flow\_state](#ChatHumanFlowModule.ChatHumanFlowModule.set_up_flow_state)
    * [type](#ChatHumanFlowModule.ChatHumanFlowModule.type)
    * [max\_rounds\_reached](#ChatHumanFlowModule.ChatHumanFlowModule.max_rounds_reached)
    * [generate\_reply](#ChatHumanFlowModule.ChatHumanFlowModule.generate_reply)
    * [call\_to\_user](#ChatHumanFlowModule.ChatHumanFlowModule.call_to_user)
    * [call\_to\_assistant](#ChatHumanFlowModule.ChatHumanFlowModule.call_to_assistant)
    * [run](#ChatHumanFlowModule.ChatHumanFlowModule.run)

<a id="ChatHumanFlowModule"></a>

# ChatHumanFlowModule

<a id="ChatHumanFlowModule.ChatHumanFlowModule"></a>

## ChatHumanFlowModule Objects

```python
class ChatHumanFlowModule(CompositeFlow)
```

This class implements a Chat Human Flow Module. It is a flow that consists of two sub-flows that are executed circularly. It Contains the following subflows:

- A User Flow: A flow makes queries to the Assistant Flow. E.g. The user asks the assistant (LLM) a question.
- A Assistant Flow: A flow that responds to queries made by the User Flow. E.g. The assistant (LLM) answers the user's question.

To end the interaction, the user must type "\<END\>"

An illustration of the flow is as follows:

        |------> User Flow -----------> |
        ^                               |
        |                               |
        |                               v
        |<------ Assistant Flow <-------|

*Configuration Parameters*:

- `name` (str): The name of the flow. Default: "ChatHumanFlowModule"
- `description` (str): A description of the flow. This description is used to generate the help message of the flow.
Default: "Flow that enables chatting between a ChatAtomicFlow and a user providing the input."
- `max_rounds` (int): The maximum number of rounds the flow can run for. Default: None, which means that there is no limit on the number of rounds.
- `early_exit_key` (str): The key that is used to exit the flow. Default: "end_of_interaction"
- `subflows_config` (Dict[str,Any]): A dictionary of subflows configurations. Default:
    - `Assistant Flow`: The configuration of the Assistant Flow. By default, it a ChatAtomicFlow. It default parmaters are defined in ChatAtomicFlowModule.
    - `User Flow`: The configuration of the User Flow. By default, it a HumanStandardInputFlow. It default parmaters are defined in HumanStandardInputFlowModule.
- `topology` (str): (List[Dict[str,Any]]): The topology of the flow which is "circular".
By default, the topology is the one shown in the illustration above (the topology is also described in ChatHumanFlowModule.yaml).

*Input Interface*:

- None. By default, the input interface doesn't expect any input.

*Output Interface*:

- `end_of_interaction` (bool): Whether the interaction is finished or not.

**Arguments**:

- `\**kwargs` (`Dict[str, Any]`): Arguments to be passed to the parent class CircularFlow constructor.

<a id="ChatHumanFlowModule.ChatHumanFlowModule.set_up_flow_state"></a>

#### set\_up\_flow\_state

```python
def set_up_flow_state()
```

This method sets up the flow state. It is called when the flow is executed.

<a id="ChatHumanFlowModule.ChatHumanFlowModule.type"></a>

#### type

```python
@classmethod
def type(cls)
```

This method returns the type of the flow.

<a id="ChatHumanFlowModule.ChatHumanFlowModule.max_rounds_reached"></a>

#### max\_rounds\_reached

```python
def max_rounds_reached()
```

This method checks if the maximum number of rounds has been reached. If the maximum number of rounds has been reached, it returns True. Otherwise, it returns False.

<a id="ChatHumanFlowModule.ChatHumanFlowModule.generate_reply"></a>

#### generate\_reply

```python
def generate_reply()
```

This method generates the reply message. It is called when the interaction is finished.

**Arguments**:

- `input_message` (`FlowMessage`): The input message to the flow.

<a id="ChatHumanFlowModule.ChatHumanFlowModule.call_to_user"></a>

#### call\_to\_user

```python
def call_to_user(input_message)
```

This method calls the User Flow. (Human)

**Arguments**:

- `input_message` (`FlowMessage`): The input message to the flow.

<a id="ChatHumanFlowModule.ChatHumanFlowModule.call_to_assistant"></a>

#### call\_to\_assistant

```python
def call_to_assistant(input_message)
```

This method calls the Assistant Flow.

**Arguments**:

- `input_message` (`FlowMessage`): The input message to the flow.

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

#### run

```python
def run(input_message: FlowMessage)
```

This method runs the flow. It is the main method of the flow and it is called when the flow is executed.

**Arguments**:

- `input_message` (`FlowMessage`): The input message to the flow.