## Module/Class Name: TaskInput

The `TaskInput` class is designed to handle the input parameters for a task. It is an abstract class that serves as the base model for input data manipulation.

### Overview and Introduction
The `TaskInput` class is an essential component of the `swarms.structs` library, allowing users to define and pass input parameters to tasks. It is crucial for ensuring the correct and structured input to various tasks and processes within the library.

### Class Definition

#### TaskInput Class:
- Parameters:
    - `__root__` (Any): The input parameters for the task. Any value is allowed.

### Disclaimer:
It is important to note that the `TaskInput` class extends the `BaseModel` from the `pydantic` library. This means that it inherits all the properties and methods of the `BaseModel`.

### Functionality and Usage
The `TaskInput` class encapsulates the input parameters in a structured format. It allows for easy validation and manipulation of input data.

#### Usage Example 1: Using TaskInput for Debugging
```python
from pydantic import BaseModel, Field

from swarms.structs import TaskInput


class DebugInput(TaskInput):
    debug: bool


# Creating an instance of DebugInput
debug_params = DebugInput(__root__={"debug": True})

# Accessing the input parameters
print(debug_params.debug)  # Output: True
```

#### Usage Example 2: Using TaskInput for Task Modes
```python
from pydantic import BaseModel, Field

from swarms.structs import TaskInput


class ModeInput(TaskInput):
    mode: str


# Creating an instance of ModeInput
mode_params = ModeInput(__root__={"mode": "benchmarks"})

# Accessing the input parameters
print(mode_params.mode)  # Output: benchmarks
```

#### Usage Example 3: Using TaskInput with Arbitrary Parameters
```python
from pydantic import BaseModel, Field

from swarms.structs import TaskInput


class ArbitraryInput(TaskInput):
    message: str
    quantity: int


# Creating an instance of ArbitraryInput
arbitrary_params = ArbitraryInput(__root__={"message": "Hello, world!", "quantity": 5})

# Accessing the input parameters
print(arbitrary_params.message)  # Output: Hello, world!
print(arbitrary_params.quantity)  # Output: 5
```

### Additional Information and Tips
- The `TaskInput` class can be extended to create custom input models with specific parameters tailored to individual tasks.
- The `Field` class from `pydantic` can be used to specify metadata and constraints for the input parameters.

### References and Resources
- Official `pydantic` Documentation: [https://pydantic-docs.helpmanual.io/](https://pydantic-docs.helpmanual.io/)
- Additional resources on data modelling with `pydantic`: [https://www.tiangolo.com/blog/2021/02/16/real-python-tutorial-modern-fastapi-pydantic/](https://www.tiangolo.com/blog/2021/02/16/real-python-tutorial-modern-fastapi-pydantic/)

This documentation presents the `TaskInput` class, its usage, and practical examples for creating and handling input parameters within the `swarms.structs` library.
