BitAgent/bfcl_shuffle_full huggingface dataset:
user: Calculate the area of a triangle with base 5m and height 3m.

Available functions:
name: calc_area_triangle
description: Calculate the area of a triangle with the formula area = 0.5 * base * height.
parameters: type: dict
properties: base: type: integer
description: The length of the base of the triangle in meters.
height: type: integer
description: The perpendicular height of the triangle from the base to the opposite vertex in meters.
required: base
height
user: Find records in database in user table where age is greater than 25 and job is 'engineer'.

Available functions:
name: database.query
description: Query the database based on certain conditions.
parameters: type: dict
properties: table: type: string
description: Name of the table to query.
conditions: type: array
items: type: dict
properties: field: type: string
description: The field to apply the condition.
operation: type: string
description: The operation to be performed.
enum: <
>
=
>=
<=
value: type: string
description: The value to be compared.
required: field
operation
value
description: Conditions for the query.
required: table
conditions
user: What will be the angle between the hour and minute hands of a clock at 6:30 PM?

Available functions:
name: calculate_clock_angle
description: Calculate the angle between the hour and minute hands of a clock at a given time.
parameters: type: dict
properties: hours: type: integer
description: The hour on the clock face.
minutes: type: integer
description: The minutes on the clock face.
round_to: type: integer
description: The number of decimal places to round the result to, default is 2.
required: hours
minutes
user: Plot a sine wave from 0 to 2 pi with a frequency of 5 Hz.

Available functions:
name: plot_sine_wave
description: Plot a sine wave for a given frequency in a given range.
parameters: type: dict
properties: start_range: type: float
description: Start of the range in radians. Four decimal places.
end_range: type: float
description: End of the range in radians. Four decimal places.
frequency: type: integer
description: Frequency of the sine wave in Hz.
amplitude: type: integer
description: Amplitude of the sine wave. Default is 1.
phase_shift: type: integer
description: Phase shift of the sine wave in radians. Default is 0.
required: start_range
end_range
frequency
user: How much time will it take for the light to reach earth from a star 4 light years away?

Available functions:
name: light_travel_time
description: Calculate the time taken for light to travel from a celestial body to another.
parameters: type: dict
properties: distance_in_light_years: type: integer
description: The distance between the two celestial bodies in light years.
speed_of_light: type: integer
description: The speed of light in vacuum, in m/s. Default value is 299792458 m/s.
required: distance_in_light_years
user: Calculate the speed of an object in km/h if it traveled 450 meters in 20 seconds.

Available functions:
name: calculate_speed
description: Calculate the speed of an object based on the distance travelled and the time taken.
parameters: type: dict
properties: distance: type: integer
description: The distance the object travelled in meters.
time: type: integer
description: The time it took for the object to travel in seconds.
to_unit: type: string
description: The unit in which the speed should be calculated, default is m/s.
required: distance
time
user: What's the distance in milesfrom the Earth to the Moon?

Available functions:
name: calculate_distance
description: Calculate the distance between two celestial bodies.
parameters: type: dict
properties: body1: type: string
description: The first celestial body.
body2: type: string
description: The second celestial body.
unit: type: string
description: The unit of measurement, default is 'km'.
required: body1
body2
user: Calculate the area under the curve y=3x^2 + 2x - 4, between x = -1 and x = 2.

Available functions:
name: mathematics.calculate_area_under_curve
description: Calculate the area under the curve for a given polynomial function within a specified interval.
parameters: type: dict
properties: polynomial: type: array
items: type: float
description: The coefficients of the polynomial, in decreasing order of exponent, where the first element is the coefficient for x^n, the second element is the coefficient for x^(n-1), and so on. The last element is the constant term.
limits: type: array
items: type: float
description: A list of two numbers specifying the lower and upper limit for the integration interval.
required: polynomial
limits
user: Calculate the area of a triangle with base 6 and height 10.

Available functions:
name: geometry.area_triangle
description: Calculate the area of a triangle.
parameters: type: dict
properties: base: type: integer
description: The length of the base of the triangle.
height: type: integer
description: The height of the triangle from the base.
unit: type: string
description: The measurement unit for the area. Defaults to square meters.
required: base
height
user: Calculate the power of 3 raised to the power 4.

Available functions:
name: math.power
description: Calculate the power of one number raised to another.
parameters: type: dict
properties: base: type: integer
description: The base number.
exponent: type: integer
description: The exponent.
mod: type: integer
description: The modulus. Default is 1. Calculates pow(base, exponent) % mod when provided.
required: base
exponent
user: Train a random forest classifier on dataset your_dataset_name with maximum depth of trees as 5, and number of estimators as 100.

Available functions:
name: train_random_forest_classifier
description: Train a Random Forest classifier with the specified parameters.
parameters: type: dict
properties: dataset: type: string
description: The dataset to train the classifier on.
max_depth: type: integer
description: The maximum depth of the trees in the forest.
n_estimators: type: integer
description: The number of trees in the forest.
required: dataset
max_depth
n_estimators
user: Calculate the Body Mass Index for a person with a weight of 70 kg and a height of 175 cm.

Available functions:
name: calculate_bmi
description: Calculate the Body Mass Index (BMI) for a person based on their weight and height.
parameters: type: dict
properties: weight: type: integer
description: The weight of the person in kilograms.
height: type: integer
description: The height of the person in centimeters.
system: type: string
description: The system of units to be used, 'metric' or 'imperial'. Default is 'metric'.
required: weight
height
user: Run a linear regression model with predictor variables 'Age', 'Income' and 'Education' and a target variable 'Purchase_Amount'. Also apply standardization.

Available functions:
name: run_linear_regression
description: Build a linear regression model using given predictor variables and a target variable.
parameters: type: dict
properties: predictors: type: array
items: type: string
description: Array containing the names of predictor variables.
target: type: string
description: The name of target variable.
standardize: type: boolean
description: Option to apply standardization on the predictors. Defaults to False.
required: predictors
target
user: Generate a random forest model with 100 trees and a depth of 5 on the provided data my_data.

Available functions:
name: random_forest.train
description: Train a Random Forest Model on given data
parameters: type: dict
properties: n_estimators: type: integer
description: The number of trees in the forest.
max_depth: type: integer
description: The maximum depth of the tree.
data: type: any
description: The training data for the model.
required: n_estimators
max_depth
data
user: Predict the price of the house in San Francisco with 3 bedrooms, 2 bathrooms and area of 1800 square feet.

Available functions:
name: predict_house_price
description: Predict the price of a house in a given area based on number of bedrooms, bathrooms and area.
parameters: type: dict
properties: bedrooms: type: integer
description: The number of bedrooms in the house.
bathrooms: type: integer
description: The number of bathrooms in the house.
area: type: integer
description: The area of the house in square feet.
location: type: string
description: The location of the house in the format of city name.
required: bedrooms
bathrooms
area
location
user: Calculate the probability of drawing a king from a deck of cards.

Available functions:
name: calculate_probability
description: Calculate the probability of an event.
parameters: type: dict
properties: total_outcomes: type: integer
description: Total number of possible outcomes.
favorable_outcomes: type: integer
description: Number of outcomes considered as 'successful'.
round_to: type: integer
description: Number of decimal places to round the result to.
default: 2
required: total_outcomes
favorable_outcomes
user: What's the probability of rolling a six on a six-sided die twice in a row?

Available functions:
name: probability.dice_roll
description: Calculate the probability of rolling a certain number on a six-sided die a certain number of times in a row.
parameters: type: dict
properties: desired_number: type: integer
description: The number you want to roll.
number_of_rolls: type: integer
description: How many times you want to roll that number in a row.
die_sides: type: integer
description: The number of sides on the die (optional; default is 6).
required: desired_number
number_of_rolls
user: Find the probability of getting exactly 5 heads in 10 fair coin tosses.

Available functions:
name: prob_dist.binomial
description: Compute the probability of having 'success' outcome from binomial distribution.
parameters: type: dict
properties: trials: type: integer
description: The number of independent experiments.
successes: type: integer
description: The number of success events.
p: type: float
description: The probability of success on any given trial, defaults to 0.5
required: trials
successes
user: Calculate the probability of getting exactly 5 heads in 8 tosses of a fair coin.

Available functions:
name: calculate_binomial_probability
description: Calculates the binomial probability given the number of trials, successes and the probability of success on an individual trial.
parameters: type: dict
properties: number_of_trials: type: integer
description: The total number of trials.
number_of_successes: type: integer
description: The desired number of successful outcomes.
probability_of_success: type: float
description: The probability of a successful outcome on any given trial.
default: 0.5
required: number_of_trials
number_of_successes
user: What's the probability of drawing a king from a well shuffled standard deck of 52 cards?

Available functions:
name: probabilities.calculate_single
description: Calculate the probability of an event.
parameters: type: dict
properties: total_outcomes: type: integer
description: The total number of outcomes.
event_outcomes: type: integer
description: The number of outcomes where the event occurs.
round: type: integer
description: Round the answer to a specified number of decimal places. Defaults to 2.
required: total_outcomes
event_outcomes
user: What are the odds of pulling a heart suit from a well-shuffled standard deck of 52 cards? Format it as ratio.

Available functions:
name: probability_of_event
description: Calculates the probability of an event.
parameters: type: dict
properties: success_outcomes: type: integer
description: The number of successful outcomes.
total_outcomes: type: integer
description: The total number of possible outcomes.
format_as_ratio: type: boolean
description: When true, formats the output as a ratio instead of a decimal. Default is false.
required: success_outcomes
total_outcomes
user: Perform a two-sample t-test on my experiment data of Control [10, 15, 12, 14, 11] and Treated [18, 16, 17, 20, 22] group with alpha equals to 0.05

Available functions:
name: stats.t_test
description: Perform a two-sample t-test for two given arrays.
parameters: type: dict
properties: array_1: type: array
items: type: integer
description: First array of data.
array_2: type: array
items: type: integer
description: Second array of data.
alpha: type: float
description: Significance level for hypothesis testing.
required: array_1
array_2
alpha
user: Perform a hypothesis test for two independent samples with scores of Sample1: [22,33,42,12,34] and Sample2: [23,45,44,14,38] at a significance level of 0.05.

Available functions:
name: hypothesis_testing.ttest_ind
description: Conducts a hypothesis test for two independent samples.
parameters: type: dict
properties: sample1: type: array
items: type: integer
description: First set of observations (array of numbers).
sample2: type: array
items: type: integer
description: Second set of observations (array of numbers).
significance_level: type: float
description: Significance level of the test (default: 0.05)
required: sample1
sample2
user: Run a two sample T-test to compare the average of Group A [3, 4, 5, 6, 4] and Group B [7, 8, 9, 8, 7] assuming equal variance.

Available functions:
name: run_two_sample_ttest
description: Runs a two sample t-test for two given data groups.
parameters: type: dict
properties: group1: type: array
items: type: integer
description: First group of data points.
group2: type: array
items: type: integer
description: Second group of data points.
equal_variance: type: boolean
description: Assumption about whether the two samples have equal variance.
default: yes
required: group1
group2
user: Calculate the probability of observing 60 heads if I flip a coin 100 times with probability of heads 0.5.

Available functions:
name: calc_binomial_prob
description: Calculates the probability of an outcome based on the binomial distribution
parameters: type: dict
properties: num_trials: type: integer
description: Number of independent experiments.
num_success: type: integer
description: Number of times the event of interest has occurred.
prob_success: type: float
description: Probability of the event of interest on any single experiment.
required: num_trials
num_success
prob_success
user: Perform a Chi-Squared test for independence on a 2x2 contingency table [ [10, 20], [30, 40] ]

Available functions:
name: chi_squared_test
description: Performs a Chi-Squared test for independence on a 2x2 contingency table.
parameters: type: dict
properties: table: type: array
items: type: array
items: type: integer
description: A 2x2 contingency table presented in array form.
alpha: type: float
description: Significance level for the Chi-Squared test. Default is 0.05.
required: table
user: Perform a two-sample t-test to determine if there is a significant difference between the mean of group1 (e.g., 12.4, 15.6, 11.2, 18.9) and group2 (e.g., 10.5, 9.8, 15.2, 13.8) at the significance level 0.05.

Available functions:
name: hypothesis_testing.two_sample_t_test
description: Perform a two-sample t-test to determine if there is a significant difference between the means of two independent samples.
parameters: type: dict
properties: group1: type: array
items: type: float
description: Sample observations from group 1.
group2: type: array
items: type: float
description: Sample observations from group 2.
alpha: type: float
description: Significance level for the t-test. Default is 0.05.
required: group1
group2
user: Find the statistical significance between two set of variables, dataset_A with the values 12, 24, 36 and dataset_B with the values 15, 30, 45.

Available functions:
name: t_test
description: Perform a statistical t-test to check if the means of two independent datasets are statistically different.
parameters: type: dict
properties: dataset_A: type: array
items: type: integer
description: Dataset A for comparison.
dataset_B: type: array
items: type: integer
description: Dataset B for comparison.
alpha: type: float
description: Significance level for the test. Default is 0.05.
required: dataset_A
dataset_B
user: Predict house price in San Francisco based on its area of 2500 square feet, number of rooms as 5 and year of construction is 1990.

Available functions:
name: predict_house_price
description: Predict house price based on area, number of rooms and year of construction.
parameters: type: dict
properties: area: type: integer
description: Area of the house in square feet.
rooms: type: integer
description: Number of rooms in the house.
year: type: integer
description: Year when the house was constructed.
location: type: string
description: The location or city of the house.
required: area
rooms
year
location
user: What is the coefficient of determination (R-squared) for a model using engine size and fuel economy variables to predict car_price with a dataset in path C:/data/cars.csv?

Available functions:
name: linear_regression.get_r_squared
description: Calculate the coefficient of determination of a regression model.
parameters: type: dict
properties: dataset_path: type: string
description: Path to the CSV dataset file.
independent_variables: type: array
items: type: string
description: The independent variables to use in the regression model.
dependent_variable: type: string
description: The dependent variable to predict in the regression model.
required: dataset_path
independent_variables
dependent_variable
user: Find the Net Present Value (NPV) of an investment, given cash_flows=[200,300,400,500], a discount rate of 10%, and an initial investment of $2000.

Available functions:
name: calculate_NPV
description: Calculate the NPV (Net Present Value) of an investment, considering a series of future cash flows, discount rate, and an initial investment.
parameters: type: dict
properties: cash_flows: type: array
items: type: integer
description: Series of future cash flows.
discount_rate: type: float
description: The discount rate to use.
initial_investment: type: integer
description: The initial investment. Default is 0 if not specified.
required: cash_flows
discount_rate
user: What's the quarterly dividend per share of a company with 100 million outstanding shares and total dividend payout of 50 million USD?

Available functions:
name: finance.calculate_quarterly_dividend_per_share
description: Calculate quarterly dividend per share for a company given total dividend payout and outstanding shares
parameters: type: dict
properties: total_payout: type: integer
description: The total amount of dividends paid out in USD
outstanding_shares: type: integer
description: Total number of outstanding shares
required: total_payout
outstanding_shares
user: Calculate the discounted cash flow of a bond that is giving a coupon payment of $100 annually for next 5 years with discount rate 4%.

Available functions:
name: calculate_discounted_cash_flow
description: Calculate the discounted cash flow of a bond for a given annual coupon payment, time frame and discount rate.
parameters: type: dict
properties: coupon_payment: type: integer
description: The annual coupon payment.
period: type: integer
description: The time frame in years for which coupon payment is made.
discount_rate: type: float
description: The discount rate.
face_value: type: integer
description: The face value of the bond, default is 1000.
required: coupon_payment
period
discount_rate
user: What's the NPV (Net Present Value) of a series of cash flows: [-50000, 10000, 15000, 20000, 25000, 30000] discounted at 8% annually?

Available functions:
name: finance_calculator.npv
description: Calculate the Net Present Value (NPV) for a series of cash flows discounted at a certain interest rate.
parameters: type: dict
properties: cash_flows: type: array
items: type: integer
description: A list of cash flows.
discount_rate: type: float
description: The annual interest rate used to discount the cash flows.
years: type: array
items: type: integer
description: A list of years when the cash flow occurs. Default is empty array.
required: cash_flows
discount_rate
user: Calculate the compound interest for an initial principal amount of $10000, with an annual interest rate of 5% and the number of times interest applied per time period is 4 and the time the money is invested for 10 years.

Available functions:
name: calculate_compound_interest
description: Calculate compound interest for an initial principal amount.
parameters: type: dict
properties: principal: type: integer
description: The principal amount that the interest is applied to.
rate: type: float
description: The annual interest rate. Enter as a decimal. E.g, 5% is 0.05
time: type: integer
description: The time the money is invested for in years.
n: type: integer
description: The number of times that interest is compounded per time period. Default is 1.
required: principal
rate
time
user: Calculate the company's return on equity given its net income of $2,000,000, shareholder's equity of $10,000,000, and dividends paid of $200,000.

Available functions:
name: calculate_return_on_equity
description: Calculate a company's return on equity based on its net income, shareholder's equity, and dividends paid.
parameters: type: dict
properties: net_income: type: integer
description: The company's net income.
shareholder_equity: type: integer
description: The company's total shareholder's equity.
dividends_paid: type: integer
description: The total dividends paid by the company. Optional. If not given, default to 0.
required: net_income
shareholder_equity
user: Predict the future value of a $5000 investment with an annual interest rate of 5% in 3 years with monthly compounding.

Available functions:
name: finance.predict_future_value
description: Calculate the future value of an investment given its present value, interest rate, the number of compounding periods per year, and the time horizon.
parameters: type: dict
properties: present_value: type: integer
description: The present value of the investment.
annual_interest_rate: type: float
description: The annual interest rate of the investment.
compounding_periods_per_year: type: integer
description: The number of times that interest is compounded per year. Default is 1 (annually).
time_years: type: integer
description: The investment horizon in years.
required: present_value
annual_interest_rate
time_years
user: Predict the total expected profit of stocks XYZ in 5 years given I have invested $5000 and annual return rate is 7%.

Available functions:
name: investment.predictProfit
description: Predict the profit for given investment after specified number of years.
parameters: type: dict
properties: investment_amount: type: integer
description: The amount invested in dollars.
annual_return: type: float
description: The annual return rate of the investment.
years: type: integer
description: The time period in years for which the investment is made.
required: investment_amount
annual_return
years
user: Calculate the return on investment for a stock bought at $20, sold at $25, with a dividend of $2.

Available functions:
name: calculate_return_on_investment
description: Calculate the return on investment for a given stock based on its purchase price, sale price, and any dividends received.
parameters: type: dict
properties: purchase_price: type: integer
description: The price the stock was bought at.
sale_price: type: integer
description: The price the stock was sold at.
dividend: type: integer
description: Any dividends received from the stock.
default: 0
required: purchase_price
sale_price
user: Find the compound interest for an investment of $10000 with an annual interest rate of 5% compounded monthly for 5 years.

Available functions:
name: compound_interest
description: Calculate compound interest for a certain time period.
parameters: type: dict
properties: principal: type: integer
description: The initial amount of money that was invested or loaned out.
annual_rate: type: float
description: The interest rate for a year as a percentage.
compounding_freq: type: string
enum: monthly
quarterly
annually
description: The number of times that interest is compounded per unit period.
time_in_years: type: integer
description: The time the money is invested for in years.
required: principal
annual_rate
compounding_freq
time_in_years
user: Calculate the projected return on a $5000 investment in ABC company's stock, if the expected annual growth rate is 6% and the holding period is 5 years.

Available functions:
name: calculate_stock_return
description: Calculate the projected return of a stock investment given the investment amount, the annual growth rate and holding period in years.
parameters: type: dict
properties: investment_amount: type: integer
description: The amount of money to invest.
annual_growth_rate: type: float
description: The expected annual growth rate of the stock.
holding_period: type: integer
description: The number of years you intend to hold the stock.
dividends: type: boolean
description: Optional. True if the calculation should take into account potential dividends. Default is false.
required: investment_amount
annual_growth_rate
holding_period
user: Calculate the future value of my portfolio if I invest $5000 in stock 'X' with an expected annual return of 5% for 7 years.

Available functions:
name: portfolio_future_value
description: Calculate the future value of an investment in a specific stock based on the invested amount, expected annual return and number of years.
parameters: type: dict
properties: stock: type: string
description: The ticker symbol of the stock.
invested_amount: type: integer
description: The invested amount in USD.
expected_annual_return: type: float
description: The expected annual return on investment as a decimal. E.g. 5% = 0.05
years: type: integer
description: The number of years for which the investment is made.
required: stock
invested_amount
expected_annual_return
years
user: What is the estimated return on a mutual fund, given that it has a yearly yield of 5%, an investment amount of $2000 and a time period of 3 years?

Available functions:
name: estimate_mutual_fund_return
description: Calculate the estimated return on a mutual fund given the yearly yield, the investment amount and the time period.
parameters: type: dict
properties: yearly_yield: type: float
description: The yearly yield of the mutual fund as a percentage.
investment_amount: type: integer
description: The initial investment amount in the mutual fund.
years: type: integer
description: The time period for which the investment is made in years.
required: yearly_yield
investment_amount
years
user: Calculate the Compound Annual Growth Rate (CAGR) for an initial investment of $2000, final value of $3000 in a period of 4 years.

Available functions:
name: calculate_cagr
description: Calculate the Compound Annual Growth Rate (CAGR) given an initial investment value, a final investment value, and the number of years.
parameters: type: dict
properties: initial_value: type: integer
description: The initial investment value.
final_value: type: integer
description: The final investment value.
period_in_years: type: integer
description: The period of the investment in years.
required: initial_value
final_value
period_in_years
user: Find the NASDAQ stock price for the company Amazon at closing March.11, 2022.

Available functions:
name: get_stock_price
description: Get the closing stock price for a specific company on a specified date.
parameters: type: dict
properties: company_name: type: string
description: Name of the company.
date: type: string
description: Date of when to get the stock price. Format: yyyy-mm-dd.
exchange: type: string
description: Name of the stock exchange market where the company's stock is listed. Default is 'NASDAQ'
required: company_name
date
user: 'Get stock price of Apple for the last 5 days in NASDAQ.'

Available functions:
name: get_stock_price
description: Retrieve the stock price for a specific company and time frame.
parameters: type: dict
properties: company: type: string
description: The ticker symbol of the company.
days: type: integer
description: Number of past days for which the stock price is required.
exchange: type: string
description: The stock exchange where the company is listed, default is NYSE
required: company
days
user: Find the market performance of the S&P 500 and the Dow Jones over the past 5 days.

Available functions:
name: market_performance.get_data
description: Retrieve the market performance data for specified indexes over a specified time period.
parameters: type: dict
properties: indexes: type: array
items: type: string
description: Array of stock market indexes. Supported indexes are 'S&P 500', 'Dow Jones', 'NASDAQ', 'FTSE 100', 'DAX' etc.
days: type: integer
description: Number of days in the past for which the performance data is required.
detailed: type: boolean
description: Whether to return detailed performance data. If set to true, returns high, low, opening, and closing prices. If false, returns only closing prices. Default is false.
required: indexes
days
user: Calculate the compounded interest for an initial principal of $5000, annual interest rate of 5%, and compounding period of 10 years.

Available functions:
name: calculate_compounded_interest
description: Calculate the compounded interest for a given principal, interest rate, and period.
parameters: type: dict
properties: principal: type: integer
description: The initial principal.
interest_rate: type: float
description: The annual interest rate.
period: type: integer
description: The period in years.
compounding_frequency: type: string
description: The frequency of compounding per year. Defaults to 'Annually'.
enum: Annually
Semiannually
Quarterly
Monthly
Daily
required: principal
interest_rate
period
user: What's the price of Amazon stock for the last 3 days?

Available functions:
name: stock_price
description: Get stock price data for a given company over a specified number of days.
parameters: type: dict
properties: company: type: string
description: The company name.
days: type: integer
description: The number of previous days to retrieve data for.
data_type: type: string
description: The type of price data to retrieve (e.g., 'Open', 'Close', 'High', 'Low'). Default is 'Close'.
required: company
days
user: Retrieve stock prices of Microsoft and Google for the last 2 weeks.

Available functions:
name: get_stock_prices
description: Retrieves stock prices for specified companies and duration.
parameters: type: dict
properties: companies: type: array
items: type: string
description: List of companies to retrieve stock prices for.
duration: type: string
description: Time duration to retrieve stock prices for. E.g., '1 week', '2 weeks', '1 month', etc.
required: companies
duration
user: Calculate the future value of an investment with an annual rate of return of 8%, an initial investment of $20000, and a time frame of 5 years.

Available functions:
name: finance.calculate_future_value
description: Calculate the future value of an investment given an initial investment, annual rate of return, and a time frame.
parameters: type: dict
properties: initial_investment: type: integer
description: The initial investment amount.
rate_of_return: type: float
description: The annual rate of return.
years: type: integer
description: The time frame of the investment in years.
contribution: type: integer
description: Optional: Additional regular contributions. Default is 0.
required: initial_investment
rate_of_return
years
user: Calculate the return of investment of a bank's savings account with a deposit of $1000, annual interest rate of 3% for 1 year.

Available functions:
name: calculate_roi
description: Calculate the return on investment for a given deposit amount, annual interest rate, and time frame.
parameters: type: dict
properties: deposit: type: integer
description: The initial deposit amount.
annual_interest_rate: type: float
description: The annual interest rate provided by the bank.
years: type: integer
description: The period for which the money is invested.
required: deposit
annual_interest_rate
years
user: Find the highest grossing bank in the U.S for year 2020.

Available functions:
name: highest_grossing_banks
description: Retrieve the highest grossing banks in a specified country and year.
parameters: type: dict
properties: country: type: string
description: The country to get the data from.
year: type: integer
description: The year to get the data from.
top_n: type: integer
description: Top n banks in terms of grossing. Default is 5
required: country
year
user: Calculate the balance of a mutual fund given a total investment of $50000 with a 5% annual yield after 3 years.

Available functions:
name: calculate_mutual_fund_balance
description: Calculate the final balance of a mutual fund investment based on the total initial investment, annual yield rate and the time period.
parameters: type: dict
properties: investment_amount: type: integer
description: The initial total amount invested in the fund.
annual_yield: type: float
description: The annual yield rate of the fund.
years: type: integer
description: The period of time for the fund to mature.
required: investment_amount
annual_yield
years
user: Calculate the compounded interest on an initial deposit of $5000 at an annual interest rate of 3% for 5 years, compounded quarterly.

Available functions:
name: calculate_compounded_interest
description: Calculate the compounded interest for a given initial deposit, interest rate, time and number of times the interest is compounded per unit time.
parameters: type: dict
properties: principal: type: integer
description: The initial amount of money that is being invested or loaned.
rate: type: float
description: The annual interest rate.
time: type: integer
description: The number of time periods the money is invested or loaned for.
n: type: integer
description: The number of times that interest is compounded per unit time.
required: principal
rate
time
n
user: Calculate the Future Value of a $5000 investment made today for a term of 10 years at an annual interest rate of 5%

Available functions:
name: calculate_future_value
description: Calculates the future value of an investment based on the present value, interest rate, and time period.
parameters: type: dict
properties: present_value: type: integer
description: The present value or principal amount.
annual_interest_rate: type: float
description: The annual interest rate in decimal form. Example, 5% is 0.05.
years: type: integer
description: The time period in years for which the investment is made.
compounds_per_year: type: integer
description: The number of times the interest is compounded per year. Default is 1 (annual compounding).
required: present_value
annual_interest_rate
years
user: Calculate the future value of my investment of $1000 with an annual interest rate of 5% over 2 years.

Available functions:
name: calculate_future_value
description: Calculate the future value of an investment given the initial amount, interest rate, and investment duration.
parameters: type: dict
properties: initial_investment: type: integer
description: The initial investment amount.
interest_rate: type: float
description: The annual interest rate in decimal form.
duration: type: integer
description: The investment duration in years.
compounded: type: integer
description: The number of times the interest is compounded per year. Default is 1 (annual compounding).
required: initial_investment
interest_rate
duration
user: Look up details of a felony crime record for case number CA123456 in San Diego County

Available functions:
name: crime_record.get_record
description: Retrieve detailed felony crime records using a specific case number and location.
parameters: type: dict
properties: case_number: type: string
description: The case number related to the crime.
county: type: string
description: The county in which the crime occurred.
details: type: boolean
description: To get a detailed report, set as true. Defaults to false.
required: case_number
county
user: Find out if an individual John Doe with a birthday 01-01-1980 has any prior felony convictions in California.

Available functions:
name: criminal_history.check_felonies
description: This function checks if an individual has any prior felony convictions based on their full name and birth date.
parameters: type: dict
properties: full_name: type: string
description: The full name of the individual.
birth_date: type: string
description: The birth date of the individual. Must be in MM-DD-YYYY format.
state: type: string
description: The state to search the criminal record in. Default to 'None', which the function will search across all states.
required: full_name
birth_date
user: Find the information of criminal cases of Mr. X in New York between 2012 and 2015.

Available functions:
name: get_criminal_records
description: Retrieve the criminal records of a specific person in a specific area during a certain time period.
parameters: type: dict
properties: name: type: string
description: The name of the person.
location: type: string
description: The city and state, e.g. New York, NY
from_year: type: integer
description: The start year of the time frame.
to_year: type: integer
description: The end year of the time frame.
required: name
location
from_year
to_year
user: Give me the details of Criminal Law Amendment Act of 2013.

Available functions:
name: get_act_details
description: Retrieve the details of a particular legal act based on its name and year of amendment if any.
parameters: type: dict
properties: act_name: type: string
description: The name of the act.
amendment_year: type: integer
description: Year of amendment if any. If not provided, the latest amendment year will be considered.
required: act_name
amendment_year
user: Who was the victim in the case docket numbered 2022/AL2562 in California?

Available functions:
name: get_case_info
description: Retrieve case details using a specific case docket number and court location.
parameters: type: dict
properties: docket: type: string
description: Docket number for the specific court case.
court: type: string
description: Court in which the case was heard.
info_type: type: string
description: Specify the information type needed for the case. i.e., victim, accused, verdict etc.
required: docket
court
info_type
user: Find out the possible punishments for the crime of theft in California in detail.

Available functions:
name: crime_statute_lookup
description: Look up the criminal statutes in a specific jurisdiction to find possible punishments for a specific crime.
parameters: type: dict
properties: jurisdiction: type: string
description: The jurisdiction to search in, usually a state or country.
crime: type: string
description: The crime to search for.
detail_level: type: string
enum: basic
detailed
description: How detailed of a report to return. Optional, default is 'basic'.
required: jurisdiction
crime
user: Generate a customized law contract between John and Alice for rental agreement in California.

Available functions:
name: generate_law_contract
description: Generates a customized law contract given involved parties, contract type and location.
parameters: type: dict
properties: parties: type: array
items: type: string
description: Parties involved in the contract.
contract_type: type: string
description: Type of the contract.
location: type: string
description: Location where the contract will be in effect.
required: parties
contract_type
location
user: Provide me with the property records of my house located at 123 main street, with parcel number 1234567890 in Santa Clara county. Include owners information in the response.

Available functions:
name: property_records.get
description: Fetch property records based on location, parcel number and county.
parameters: type: dict
properties: address: type: string
description: Address of the property.
parcel_number: type: string
description: Parcel number of the property.
county: type: string
description: County where the property is located.
include_owner: type: boolean
description: Include owner's name in the property record. Default is false.
default: no
required: address
parcel_number
county
user: Provide me the official crime rate of violent crime in San Francisco in 2020.

Available functions:
name: get_crime_rate
description: Retrieve the official crime rate of a city.
parameters: type: dict
properties: city: type: string
description: The name of the city.
state: type: string
description: The state where the city is located.
type: type: string
description: Optional. The type of crime. Default is 'violent'
year: type: integer
description: Optional. The year for the crime rate data. Default is year 2001.
required: city
state
user: Retrieve cases from 2020 about theft crimes in Los Angeles, California

Available functions:
name: civil_cases.retrieve
description: Retrieve civil cases based on given parameters, including year, crime type, and location.
parameters: type: dict
properties: year: type: integer
description: Year of the cases
crime_type: type: string
description: Type of the crime.
location: type: string
description: Location of the case in the format of city name.
required: year
crime_type
location
user: Find a lawyer specializing in divorce cases and charge fee less than 400 dollars per hour in Chicago.

Available functions:
name: lawyer.find_nearby
description: Locate nearby lawyers based on specific criteria like specialty, fee per hour and city.
parameters: type: dict
properties: city: type: string
description: The city and state, e.g. Chicago, IL.
specialty: type: array
items: type: string
enum: Civil
Divorce
Immigration
Business
Criminal
description: Specialization of the lawyer.
fee: type: integer
description: Hourly fee charged by lawyer
required: city
specialty
fee
user: Retrieve the details of a Supreme Court case titled 'Roe v. Wade'.Include dissent information.

Available functions:
name: law.civil.get_case_details
description: Retrieve the details of a Supreme Court case given its title.
parameters: type: dict
properties: case_title: type: string
description: Title of the Supreme Court case.
include_dissent: type: boolean
description: If true, the output will include details of the dissenting opinion.
required: case_title
include_dissent
user: Search for ongoing lawsuits related to the company 'Google' filed after January 1, 2021 in California.

Available functions:
name: lawsuit_search
description: Search for lawsuits related to a specific company within a specific date range and location.
parameters: type: dict
properties: company: type: string
description: The company related to the lawsuit.
start_date: type: string
description: Start of the date range for when the lawsuit was filed in the format of MM-DD-YYY.
location: type: string
description: Location where the lawsuit was filed in the format of full state name.
status: type: string
enum: ongoing
settled
dismissed
description: The status of the lawsuit. Default is 'ongoing'.
required: company
start_date
location
user: Find the details of the court case identified by docket number 123456 in Texas. Don't return full text

Available functions:
name: court_case.search
description: Retrieves details about a court case using its docket number and location.
parameters: type: dict
properties: docket_number: type: string
description: The docket number for the case.
location: type: string
description: The location where the case is registered, in the format: state, e.g., Texas
full_text: type: boolean
default: false
description: Option to return the full text of the case ruling.
required: docket_number
location
user: Find a historical law case about fraud from 2010 to 2015.

Available functions:
name: law_case_search.find_historical
description: Search for a historical law case based on specific criteria like the subject and year.
parameters: type: dict
properties: subject: type: string
description: The subject matter of the case, e.g., 'fraud'
from_year: type: integer
description: The start year for the range of the case. The case should happen after this year.
to_year: type: integer
description: The end year for the range of the case. The case should happen before this year.
required: subject
from_year
to_year
user: Fetch details of a law case with number 43403 in New York court for year 2018.

Available functions:
name: fetch_law_case_details
description: Fetch details of a specific law case based on case number, year and court.
parameters: type: dict
properties: case_number: type: integer
description: The specific number of the law case.
court: type: string
description: The city name where the court takes place
year: type: integer
description: The year in which the law case took place.
required: case_number
court
year
user: Find state law cases related to land disputes in the past 5 years from 2015 to 2021 in New York.

Available functions:
name: law_case_search
description: Search and retrieve law cases based on the topic, timeline, and location.
parameters: type: dict
properties: topic: type: string
description: The subject matter of the case.
year_range: type: array
items: type: integer
description: The start and end year for searching cases.
location: type: string
description: The location where the case is being heard.
judicial_system: type: string
description: The specific judicial system in which to search (e.g. 'federal', 'state').
default: all
required: topic
year_range
location
user: Get me the top 10 landmark cases in constitutional law in China.

Available functions:
name: get_top_cases
description: Retrieve a list of the most influential or landmark cases in a specific field of law.
parameters: type: dict
properties: field_of_law: type: string
description: The specific field of law e.g., constitutional law, criminal law, etc.
top_number: type: integer
description: The number of top cases to retrieve.
country: type: string
description: The country where the law cases should be retrieved from. Default is United States of America.
required: field_of_law
top_number
user: How many months of experience a Lawyer John Doe has on handling Bankruptcy cases.

Available functions:
name: lawyer.get_experience
description: Retrieve months of experience of a Lawyer on handling certain type of law cases.
parameters: type: dict
properties: name: type: string
description: The full name of the Lawyer.
law_type: type: string
description: The type of law case. eg. Bankruptcy
required: name
law_type
user: Find details of patent lawsuits involving the company 'Apple Inc.' from the year 2010.

Available functions:
name: lawsuit_details.find
description: Find details of lawsuits involving a specific company from a given year.
parameters: type: dict
properties: company_name: type: string
description: Name of the company.
year: type: integer
description: Year of the lawsuit.
case_type: type: string
description: Type of the lawsuit, e.g., 'IPR', 'Patent', 'Commercial', etc. Default is 'all'.
required: company_name
year
user: Find all Patent lawsuit cases of Facebook in 2018.

Available functions:
name: get_lawsuit_cases
description: Retrieve all lawsuit cases related to a specific company during a particular year.
parameters: type: dict
properties: company_name: type: string
description: The name of the company.
year: type: integer
description: The specific year to search for lawsuit cases.
status: type: string
enum: open
closed
all
description: The status of the lawsuit cases to retrieve. If not specified, defaults to 'all'.
required: company_name
year
user: Find details about lawsuit case numbered 'LAX2019080202' in the Los Angeles court.

Available functions:
name: get_lawsuit_details
description: Retrieve the detailed information about a lawsuit based on its case number and the court location.
parameters: type: dict
properties: case_number: type: string
description: The case number of the lawsuit.
court_location: type: string
description: The location of the court where the case is filed.
additional_details: type: array
items: type: string
enum: attorneys
plaintiffs
defendants
charges
court_updates
description: Optional. Array containing additional details to be fetched. Default is all.
required: case_number
court_location
user: Find the latest court case between Apple and Samsung occured in USA.

Available functions:
name: find_latest_court_case
description: Find the latest court case between two companies.
parameters: type: dict
properties: company1: type: string
description: The name of the first company.
company2: type: string
description: The name of the second company.
country: type: string
description: The country in which the court case is located.
default: USA
required: company1
company2