Financial Tone - Validator Details

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Financial Tone

🏅Guardrails Certified

Last updated 6 months ago

🇬🇧 EN

🧵 STRING

🤖 ML

🧐 ETIQUETTE

🤖 CHATBOTS

📞 CUSTOMER SUPPORT

Overview

Developed by	Cartesia AI
Date of development	Feb 14, 2024
Validator type	Format
Blog	-
License	Apache 2
Input/Output	Output

Description

This validator checks an LLM-generated output (in a financial context) for a particular tone.

Requirements

Dependencies: transformers, torch

Installation

guardrails hub install hub://cartesia/financial_tone

Usage Examples

Validating string output via Python

In this example, we use the financial_tone validator on any LLM generated text.

# Import Guard and Validator
from guardrails.hub import FinancialTone
from guardrails import Guard

# Use the Guard with the validator
guard = Guard().use(FinancialTone, on_fail="exception")

# Test passing response
guard.validate(
    "Growth is strong and we have plenty of liquidity.",
    metadata={"financial_tone": "positive"}
)

try:
    # Test failing response
    guard.validate(
        "There are doubts about our finances, and we are struggling to stay afloat.",
        metadata={"financial_tone": "positive"}
    )
except Exception as e:
    print(e)

API Reference

__init__(self, on_fail="noop")

Initializes a new instance of the Validator class.

Parameters:

on_fail (str, Callable): The policy to enact when a validator fails. If str, must be one of reask, fix, filter, refrain, noop, exception or fix_reask. Otherwise, must be a function that is called when the validator fails.

__call__(self, value, metadata={}) → ValidationResult

Validates the given value using the rules defined in this validator, relying on the metadata provided to customize the validation process. This method is automatically invoked by guard.parse(...), ensuring the validation logic is applied to the input data.

Note:

This method should not be called directly by the user. Instead, invoke guard.parse(...) where this method will be called internally for each associated Validator.
When invoking guard.parse(...), ensure to pass the appropriate metadata dictionary that includes keys and values required by this validator. If guard is associated with multiple validators, combine all necessary metadata into a single dictionary.

Parameters:

value (Any): The input value to validate.
metadata (dict): A dictionary containing metadata required for validation.

Key	Type	Description	Default	Required
`financial_tone`	string	One of `positive`, `negative`, `neutral`	`neutral`	No
`financial_tone_threshold`	float	A float value between 0 and 1	`0.8`	No

Guardrails API

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