BitAgent/bfcl_shuffle_full huggingface dataset:
Expected function call(s):
spotify.play: artist: Taylor Swift
duration: 20
spotify.play: artist: Maroon 5
duration: 15
Expected function call(s):
calculate_em_force: b_field: 5
area: 2
d_time: 4
calculate_em_force: b_field: 5
area: 2
d_time: 10
Expected function call(s):
calculate_resistance: length: 5
area: 0.01
resistivity: copper
calculate_resistance: length: 5
area: 0.01
resistivity: aluminum
Expected function call(s):
protein_info.get_sequence_and_3D: protein_name: human HbA1c
HbA1c
model_3d: yes
protein_info.get_sequence_and_3D: protein_name: normal hemoglobin
model_3d: yes
protein_info.get_sequence_and_3D: protein_name: rat hemoglobin
model_3d: yes
Expected function call(s):
calculate_bmi: height: 6
weight: 80
calculate_bmi: height: 5.6
weight: 60
Expected function call(s):
streaming_services.shows_list_and_ratings: streaming_service: Netflix
show_list: Friends
sort_by_rating: yes
streaming_services.shows_list_and_ratings: streaming_service: Hulu
show_list: The Office
Stranger Things
Stranger Things
The Office
sort_by_rating: yes
Expected function call(s):
calculate_sales_tax: purchase_amount: 30.45
city: Chicago
CHI
state: IL
Illinois
calculate_sales_tax: purchase_amount: 52.33
city: Sacramento
state: CA
California
calculate_sales_tax: purchase_amount: 11.23
city: Portland
state: OR
Oregon
Expected function call(s):
math.factorial: number: 5
math.factorial: number: 10
math.factorial: number: 15
Expected function call(s):
database_us_census.get_population: area: New York City
NY
New York City, NY
NYC
type: city
year: 2000
database_us_census.get_population: area: Los Angeles
Los Angeles, CA
CA
Los Angeles, CA
type: city
year: 2000
database_us_census.get_population: area: Alaska
type: state
year: 2000
database_us_census.get_population: area: USA
United States
United States of America
type: country
year: 2000
Expected function call(s):
find_movie_showing: location: San Diego
San Diego, CA
CA
movie: Tenet
time: 5 pm
17:00
find_movie_showing: location: San Diego
San Diego, CA
CA
movie: No Time To Die
time: 7:30 pm
19:30
Expected function call(s):
math.pythagoras: a: 3
b: 4
math.pythagoras: a: 5
b: 12
Expected function call(s):
ml.predict_house_price: location: New York
New York, NY
NYC
size: 3000
ml.predict_house_price: location: Los Angeles
Los Angeles, CA
LA
size: 4000
Expected function call(s):
model.DecisionTreeClassifier: criterion: gini
max_depth: 5
random_state: 1
model.DecisionTreeClassifier: criterion: entropy
max_depth: 10
random_state: 1
Expected function call(s):
confidence_interval.calculate: sample_std_dev: 10
sample_size: 50
sample_mean: 25
confidence_level: 0.95
confidence_interval.calculate: sample_std_dev: 10
sample_size: 150
sample_mean: 25
confidence_level: 0.95
Expected function call(s):
calculate_present_value: payment_per_year: 1000
interest_rate: 0.05
years: 20
calculate_present_value: payment_per_year: 1000
interest_rate: 0.05
years: 30
calculate_present_value: payment_per_year: 1000
interest_rate: 0.05
years: 10
Expected function call(s):
calculate_capital_gains_tax: short_term_gain: 15000
long_term_gain: 25000
state: CA
California
calculate_capital_gains_tax: short_term_gain: 20000
long_term_gain: 50000
state: FL
Florida
Expected function call(s):
calculate_return_on_investment: initial_investment: 2000
gain_loss: 500
calculate_return_on_investment: initial_investment: 5000
gain_loss: -1000
Expected function call(s):
get_stock_data: symbol: AAPL
data_points: price
volume
volume
price
get_stock_data: symbol: GOOG
GOOGL
data_points: price
volume
volume
price
get_stock_data: symbol: MSFT
data_points: price
volume
volume
price
Expected function call(s):
financials.calculate_future_value: present_value: 1000
annual_interest_rate: 0.05
number_of_years: 1
financials.calculate_future_value: present_value: 1000
annual_interest_rate: 0.05
number_of_years: 5
financials.calculate_future_value: present_value: 1000
annual_interest_rate: 0.05
number_of_years: 10
Expected function call(s):
calculate_mortgage_payment: loan_amount: 400000
interest_rate: 0.04
loan_term: 15
calculate_mortgage_payment: loan_amount: 400000
interest_rate: 0.04
loan_term: 20
calculate_mortgage_payment: loan_amount: 400000
interest_rate: 0.04
loan_term: 30
Expected function call(s):
loan_eligibility_check: financial_institution: HSBC
loan_amount: 500000
annual_income: 100000
loan_eligibility_check: financial_institution: Wells Fargo
loan_amount: 700000
annual_income: 120000
Expected function call(s):
law_crimes.search: crime: money laundering
location: San Francisco
SF
year: 2019
law_crimes.search: crime: money laundering
location: Texas
TX
year: 2018
Expected function call(s):
court_info.get_case_status: case_number: XY1234
court: Los Angeles County Court
Los Angeles
Los Angeles, CA
LA
details: status
court_info.get_case_status: case_number: GH5678
court: Orange County Court
Orange County
OC
details: status
court_info.get_case_status: case_number: XY1234
court: Los Angeles County Court
Los Angeles
Los Angeles, CA
LA
details: trial_date
court_info.get_case_status: case_number: GH5678
court: Orange County Court
Orange County
OC
details: trial_date
Expected function call(s):
alimony_calculator.ca.calculate: payor_income: 10000
recipient_income: 3000
duration: 10
alimony_calculator.ca.calculate: payor_income: 10000
recipient_income: 3000
duration: 20
Expected function call(s):
law_case.get_details: case_number: 28473
include_history: yes
include_litigants: yes
law_case.get_details: case_number: 64725
include_history: yes
include_litigants: yes
Expected function call(s):
lawsuit.lookup: company_name: Dara Inc
year: 2019
lawsuit.lookup: company_name: Dara Inc
year: 2018
Expected function call(s):
court_case.find: location: New York District
NY District
New York
New York, NY
NY
case_number: 67813
case_type: Civil
court_case.find: location: New York District
NY District
New York
New York, NY
NY
case_number: 71249
case_type: Criminal
court_case.find: location: New York District
NY District
New York
New York, NY
NY
case_number: 67813
case_type: Criminal
court_case.find: location: New York District
NY District
New York
New York, NY
NY
case_number: 71249
case_type: Civil
Expected function call(s):
nature_reserve.find_nearby: location: Berkeley
Berkeley,California
CA
amenities: Picnic Tables
Public Restrooms
Public Restrooms
Picnic Tables
proximity: 10
nature_reserve.find_nearby: location: Tokyo
amenities: Playgrounds
Biking Trails
Biking Trails
Playgrounds
proximity: 5
Expected function call(s):
get_current_and_future_temperature: location: Seattle
Seattle, Washington
Seattle, WA
hours: 3
get_current_and_future_temperature: location: Los Angeles
Los Angeles, CA
LA
Los Angeles, California
Los Angeles, CA
hours: 3
Expected function call(s):
waste_calculation.calculate: population: adults: 2
children: 2
singles: 0
location: Los Angeles
Los Angeles, CA
LA
waste_calculation.calculate: population: adults: 0
children: 0
singles: 1
location: New York
New York, NY
NY
New York City
NYC
Expected function call(s):
book_flight: departure_city: San Francisco
SF
destination_city: Tokyo
date: 2022-05-03
05/03/2022
May 3rd, 2022
May 3, 2022
May 3rd 2022
book_flight: departure_city: Tokyo
destination_city: Sydney
date: 2022-05-18
05/18/2022
May 18th, 2022
May 18, 2022
May 18th 2022
Expected function call(s):
history_fact.fetch: event: Treaty of Paris
depth: detailed
year: 0
history_fact.fetch: event: Magna Carta
depth: detailed
year: 0
Expected function call(s):
us_history.events_by_presidency: president_name: Abraham Lincoln
start_year: 0
end_year: 2000
us_history.events_by_presidency: president_name: George Washington
start_year: 0
end_year: 2000
Expected function call(s):
get_president_and_vp: year: 1980
position: president
get_president_and_vp: year: 2016
position: president
get_president_and_vp: year: 1975
position: vice president
get_president_and_vp: year: 2011
position: vice president
Expected function call(s):
religion_history.track: region: Egypt
religion: Christianity
start_year: 100
end_year: 1500
religion_history.track: region: Turkey
religion: Christianity
start_year: 100
end_year: 1500
Expected function call(s):
ancient_empires.get_religion_info: empire_name: Mauryan Empire
include_influences: yes
ancient_empires.get_religion_info: empire_name: Persian Empire
include_influences: yes
Expected function call(s):
paint_color_mixture: paint_type: Watercolor
watercolor
color: Magenta
magenta
paint_color_mixture: paint_type: Acrylic
acrylic
color: Navy
navy
Expected function call(s):
color_converter.get_color_info: color_name: navy
conversion_type: RGB
HEX
HEX
RGB
color_converter.get_color_info: color_name: purple
conversion_type: RGB
HEX
HEX
RGB
color_converter.get_color_info: color_name: maroon
conversion_type: RGB
HEX
HEX
RGB
Expected function call(s):
calc_distance: start_loc: New York
New York, NY
New York City
NYC
end_loc: Washington DC
Washington D.C.
shortest_route: yes
calc_distance: start_loc: Los Angeles
Los Angeles, CA
LA
end_loc: San Francisco
SF
shortest_route: yes
Expected function call(s):
museum_info.get_info: location: Washington D.C.
Washington DC
details: Opening hours
Adult tickets
Child tickets
Opening hours
Child tickets
Adult tickets
Child tickets
Opening hours
Adult tickets
Child tickets
Adult tickets
Opening hours
Adult tickets
Opening hours
Child tickets
Adult tickets
Child tickets
Opening hours
museum_info.get_info: location: Paris
details: Opening hours
Adult tickets
Child tickets
Opening hours
Child tickets
Adult tickets
Child tickets
Opening hours
Adult tickets
Child tickets
Adult tickets
Opening hours
Adult tickets
Opening hours
Child tickets
Adult tickets
Child tickets
Opening hours
Expected function call(s):
museum.exhibition_detail: exhibition_name: Wonder of Nature
museum_name: Louvre
Louvre Museum
visitor_type: child
adult
adult
child
museum.exhibition_detail: exhibition_name: Age of Reptiles
museum_name: British Museum
visitor_type: child
adult
adult
child
Expected function call(s):
find_music_instrument_store: location: San Francisco, CA
San Francisco, CA
San Francisco, California
instruments: Yamaha Acoustic Guitar
Kawai Piano
Kawai Piano
Yamaha Acoustic Guitar
Yamaha acoustic guitar
Kawai piano
Kawai piano
Yamaha acoustic guitar
find_music_instrument_store: location: Chicago, IL
Chicago, Illinois
Chicago, IL.
instruments: Yamaha Acoustic Guitar
Kawai Piano
Kawai Piano
Yamaha Acoustic Guitar
Yamaha acoustic guitar
Kawai piano
Kawai piano
Yamaha acoustic guitar
Expected function call(s):
check_instrument_availability: instrument: Yamaha P125
Yamaha P125 piano
city: Berlin
check_instrument_availability: instrument: Yamaha P125
Yamaha P125 piano
city: Madrid
Expected function call(s):
concert_finder: location: San Francisco, California
San Francisco, CA
SF, California
SF, CA
music_genre: rock
time_period: 30
concert_finder: location: San Francisco, California
San Francisco, CA
SF, California
SF, CA
music_genre: jazz
time_period: 30
concert_finder: location: New York, New York
New York, NY
NYC
NY, NY
music_genre: rock
time_period: 30
concert_finder: location: New York, New York
New York, NY
NYC
NY, NY
music_genre: jazz
time_period: 30
Expected function call(s):
concert.find_nearby: location: Berlin
date: next Friday
genre: Classical
classical
amenities: Parking
concert.find_nearby: location: Paris
date: next Friday
genre: Classical
classical
amenities: Parking
Expected function call(s):
musicCharts.getMostPlayed: genre: Pop
region: Australia
AU
duration: 0
musicCharts.getMostPlayed: genre: Rock
region: Australia
AU
duration: 0
Expected function call(s):
calculate_winning_percentage: team: Lakers
season: 2018
calculate_winning_percentage: team: Bulls
season: 2018
calculate_winning_percentage: team: Lakers
season: 2020
calculate_winning_percentage: team: Bulls
season: 2020
Expected function call(s):
get_team_ranking: team: Barcelona
Barca
league: UEFA Champions League
Champions League
get_team_ranking: team: Manchester United
Man United
Man U
MUFC
league: La Liga
Expected function call(s):
PokemonGO.get_moves: pokemon: Pikachu
move: Run
PokemonGO.get_moves: pokemon: Bulbasaur
move: Solar Beam
Expected function call(s):
player_status.check: team: RocketLeague
player_id: 3142
season: 2017
player_status.check: team: RocketLeague
player_id: 3142
season: 2018
player_status.check: team: RocketLeague
player_id: 3142
season: 2019
Expected function call(s):
game.save_progress: stage: 7
mode: easy
level: user
game.save_progress: stage: 3
mode: hard
level: user
Expected function call(s):
recipe_search.find: dish: Chicken Noodle Soup
diet: Keto
recipe_search.find: dish: Salad
salad
Vegan Salad
vegan salad
diet: Vegan
Expected function call(s):
restaurant_finder: location: New York
New York, NY
New York City
NYC
NY
cuisine: Italian
preferences: Vegetarian
restaurant_finder: location: Los Angeles
Los Angeles, CA
LA
L.A.
cuisine: Japanese
preferences: Delivery
Expected function call(s):
get_cooking_recipe: dish_name: Lasagne Bolognese
serving_size: 4
get_cooking_recipe: dish_name: Caesar Salad
serving_size: 2
Expected function call(s):
whole_foods.order: location: downtown
Downtown
items: pepperoni pizza
chicken Caesar salad
chicken Caesar salad
pepperoni pizza
size: large
whole_foods.order: location: uptown
Uptown
items: pepperoni pizza
chicken Caesar salad
chicken Caesar salad
pepperoni pizza
size: large
Expected function call(s):
grocery_store.find_by_criteria: location: New York City
NYC
criteria: 24 hours
grocery_store.find_by_criteria: location: SD
San Diego
criteria: Home Delivery
Expected function call(s):
hotel_booking.check_availability: hotel_name: Queens Hotel
location: Berlin, Germany
check_in_date: 2022-03-10
03/10/2022
Mar.10,2022
check_out_date: 2022-03-20
03/20/2022
Mar.20,2022
hotel_booking.check_availability: hotel_name: Royal Hotel
location: Paris, France
check_in_date: 2022-04-05
04/05/2022
Apr.5,2022
check_out_date: 2022-04-15
04/15/2022
Apr.15,2022
Expected function call(s):
hotel_booking.book: hotel_name: Sheraton Hotel
Sheraton
location: New York
New York, NY
New York City
NYC
check_in: 2022-05-01
05/01/2022
May 1, 2022
check_out: 2022-05-05
05/05/2022
May 5, 2022
adults: 2
children: 1
hotel_booking.book: hotel_name: Marriott
location: Los Angeles
Los Angeles, CA
LA
check_in: 2022-06-01
06/01/2022
June 1, 2022
check_out: 2022-06-10
06/10/2022
June 10, 2022
adults: 1
children: 2
Expected function call(s):
get_exchange_rate: base_currency: USD
target_currency: AUD
get_exchange_rate: base_currency: USD
target_currency: CAD
Expected function call(s):
get_conversion_cost: amount: 15000
from_currency: Euro
EUR
to_currency: dollars
USD
Dollar
get_conversion_cost: amount: 200
from_currency: pounds
GBP
to_currency: dollars
USD
Expected function call(s):
math.factorial: number: 5
math.factorial: number: 7
math.factorial: number: 9
Expected function call(s):
math.hypot: x: 3
y: 4
z: 0
math.hypot: x: 6
y: 8
z: 0
math.hypot: x: 9
y: 12
z: 15
Expected function call(s):
algebra.quadratic_roots: a: 3
b: 4
c: 2
algebra.quadratic_roots: a: 5
b: -7
c: 3
Expected function call(s):
solve_quadratic_equation: a: 5
b: 6
c: 1
solve_quadratic_equation: a: 3
b: 2
c: 1
Expected function call(s):
solve_quadratic: a: 2
b: 5
c: 3
root_type: all
solve_quadratic: a: 1
b: -3
c: 2
root_type: real
solve_quadratic: a: 4
b: -7
c: 3
root_type: all
solve_quadratic: a: 1
b: 2
c: 1
root_type: real
Expected function call(s):
calculate_circumference: radius: 5
unit: cm
centimeter
calculate_circumference: radius: 10
unit: cm
centimeter
calculate_circumference: radius: 15
unit: cm
centimeter
calculate_circumference: radius: 20
unit: cm
centimeter
Expected function call(s):
geometry.area_circle: radius: 5
units: meters
m
geometry.area_circle: radius: 10
units: meters
m
geometry.area_circle: radius: 15
units: meters
m
Expected function call(s):
geometry.calculate_area_circle: radius: 5
unit: meters
m
geometry.calculate_area_circle: radius: 10
unit: meters
m
Expected function call(s):
calculate_area: base: 12
height: 15
unit: m
meters
meter
calculate_area: base: 18
height: 24
unit: m
meters
meter
Expected function call(s):
calculate_triangle_area: base: 10
height: 5
calculate_triangle_area: base: 8
height: 6
Expected function call(s):
geometry.circumference: radius: 5
units: m
meters
geometry.circumference: radius: 10
units: m
meters
geometry.circumference: radius: 15
units: m
meters
geometry.circumference: radius: 20
units: m
meters
Expected function call(s):
calculate_derivative: function: 3x**3 - 2x**2 + 5x - 7
lambda x: 3x**3 - 2x**2 + 5x - 7
x_value: 4
calculate_derivative: function: 9x**2 - 4x + 5
lambda x: 9x**2 - 4x + 5
x_value: 2
Expected function call(s):
integrate: function: x**3
lambda x: x**3
start_x: 2
end_x: 5
method: trapezoid
integrate: function: x**3
lambda x: x**3
start_x: 2
end_x: 5
method: simpson
integrate: function: 2x**2 + 3x - 1
lambda x: 2x**2 + 3x - 1
start_x: -1
end_x: 3
method: trapezoid
integrate: function: 2x**2 + 3x - 1
lambda x: 2x**2 + 3x - 1
start_x: -1
end_x: 3
method: simpson
Expected function call(s):
calculus.derivative: function: 3x**2 + 2x - 1
lambda x: 3x**2 + 2x - 1
value: 5
function_variable: x
calculus.derivative: function: 4y**3 - 3y**2 + 2y - 1
lambda y: 4y**3 - 3y**2 + 2y - 1
value: 3
function_variable: y
Expected function call(s):
get_prime_factors: number: 4567
formatted: yes
get_prime_factors: number: 4567
formatted: no
get_prime_factors: number: 7890
formatted: yes
get_prime_factors: number: 7890
formatted: no
Expected function call(s):
number_analysis.prime_factors: number: 45
number_analysis.prime_factors: number: 100
number_analysis.prime_factors: number: 150
Expected function call(s):
math.gcd: num1: 45
num2: 60
math.gcd: num1: 81
num2: 27
Expected function call(s):
math.hcf: number1: 45
number2: 60
math.hcf: number1: 90
number2: 120
math.hcf: number1: 36
number2: 48
math.hcf: number1: 72
number2: 96
Expected function call(s):
number_theory.gcd: number1: 45
number2: 60
number_theory.gcd: number1: 81
number2: 63
Expected function call(s):
prime_factorize: number: 4567
return_type: dictionary
prime_factorize: number: 7890
return_type: dictionary
Expected function call(s):
math.gcd: num1: 36
num2: 48
math.gcd: num1: 60
num2: 96
Expected function call(s):
calculate_final_velocity: height: 10
initial_velocity: 0
gravity: 9.81
calculate_final_velocity: height: 20
initial_velocity: 0
gravity: 9.81
calculate_final_velocity: height: 15
initial_velocity: 0
gravity: 9.81
calculate_final_velocity: height: 25
initial_velocity: 0
gravity: 9.81
Expected function call(s):
calculate_velocity: distance: 120
duration: 5
unit: km/h
calculate_velocity: distance: 150
duration: 6
unit: km/h
Expected function call(s):
final_velocity: initial_velocity: 0
acceleration: 5
time: 10
final_velocity: initial_velocity: 10
acceleration: 7
time: 8
final_velocity: initial_velocity: 20
acceleration: 4
time: 12
Expected function call(s):
calculate_displacement: initial_velocity: 15
time: 7
acceleration: 3.5
calculate_displacement: initial_velocity: 20
time: 10
acceleration: 2
calculate_displacement: initial_velocity: 25
time: 8
acceleration: 0
Expected function call(s):
calculate_final_speed: initial_speed: 0
time: 10
gravity: -9.81
calculate_final_speed: initial_speed: 5
time: 7
gravity: -9.81
Expected function call(s):
kinematics.final_velocity_from_distance: acceleration: 5
distance: 100
initial_velocity: 0
kinematics.final_velocity_from_distance: acceleration: 10
distance: 200
initial_velocity: 0
Expected function call(s):
calculate_final_velocity: initial_velocity: 0
acceleration: 6
time: 10
calculate_final_velocity: initial_velocity: 20
acceleration: 4
time: 15
Expected function call(s):
calculate_final_speed: initial_velocity: 0
height: 10
gravity: 9.8
calculate_final_speed: initial_velocity: 5
height: 20
gravity: 9.8
Expected function call(s):
get_directions: start_location: San Francisco
SF
end_location: Palo Alto
route_type: fastest
get_directions: start_location: Palo Alto
end_location: Golden Gate Bridge in San Francisco
Golden Gate Bridge, San Francisco
Golden Gate Bridge
route_type: scenic
get_directions: start_location: Golden Gate Bridge in San Francisco
Golden Gate Bridge, San Francisco
Golden Gate Bridge
end_location: San Francisco
SF
route_type: fastest
Expected function call(s):
travel_itinerary_generator: destination: Tokyo
days: 7
daily_budget: 200
exploration_type: urban
travel_itinerary_generator: destination: Paris
days: 10
daily_budget: 150
exploration_type: history
travel_itinerary_generator: destination: Sydney
days: 5
daily_budget: 100
exploration_type: nature
travel_itinerary_generator: destination: Rome
days: 12
daily_budget: 180
exploration_type: culture
Expected function call(s):
vegan_restaurant.find_nearby: location: Los Angeles, CA
Los Angeles
LA, CA
operating_hours: 22
vegan_restaurant.find_nearby: location: San Francisco, CA
San Francisco
SF, CA
operating_hours: 22
vegan_restaurant.find_nearby: location: Seattle, WA
Seattle
WA
operating_hours: 22
Expected function call(s):
get_shortest_driving_distance: origin: New York City
NYC
destination: Los Angeles
Los Angeles, CA
LA
unit: miles
mile
get_shortest_driving_distance: origin: Los Angeles
Los Angeles, CA
LA
destination: Miami
unit: miles
mile
get_shortest_driving_distance: origin: Miami
destination: New York City
NYC
unit: miles
mile
Expected function call(s):
route.estimate_time: start_location: New York
New York, NY
NYC
end_location: Miami
stops: Philadelphia
Washington D.C.
Atlanta
Philadelphia
Washington D.C.
Atlanta
Philadelphia
Washington D.C.
Atlanta
Atlanta
Philadelphia
Washington D.C.
Atlanta
Philadelphia
Washington D.C.
Atlanta
Philadelphia
Washington D.C.
Washington D.C.
Philadelphia
Atlanta
Washington D.C.
Philadelphia
Atlanta
Washington D.C.
Philadelphia
Atlanta
route.estimate_time: start_location: New York
New York, NY
NYC
end_location: Miami
stops: Washington D.C.
Philadelphia
Washington D.C.
Philadelphia
Washington D.C.
New York
Philadelphia
Washington D.C.
NYC
Washington D.C.
Philadelphia
Washington D.C.
Philadelphia
New York
Washington D.C.
Philadelphia
NYC
route.estimate_time: start_location: Philadelphia
end_location: Miami
stops: Washington D.C.
Washington D.C.
Philadelphia
Expected function call(s):
calculate_electric_field: charge: 5
distance: 2
permitivity: 0
calculate_electric_field: charge: 3
distance: 4
permitivity: 0
Expected function call(s):
calculate_magnetic_field: current: 10
radius: 0.5
permeability: 0
calculate_magnetic_field: current: 15
radius: 1
permeability: 0
Expected function call(s):
electromagnetic_force: charge1: 5
charge2: 10
distance: 2
medium_permittivity: 8.854e-12
electromagnetic_force: charge1: 5
charge2: 10
distance: 2
medium_permittivity: 5e-12
Expected function call(s):
calculate_resonant_frequency: inductance: 0.005
capacitance: 1e-07
round_off: 3
calculate_resonant_frequency: inductance: 0.007
capacitance: 2e-07
round_off: 4
Expected function call(s):
calculate_electric_field_strength: charge: 2
distance: 0.5
medium: vacuum
calculate_electric_field_strength: charge: 2
distance: 1
medium: vacuum
calculate_electric_field_strength: charge: 2
distance: 2
medium: vacuum
calculate_electric_field_strength: charge: 2
distance: 1
medium: air
Expected function call(s):
thermo.calculate_energy: mass: 500
phase_transition: melting
substance: water
thermo.calculate_energy: mass: 500
phase_transition: freezing
substance: water
thermo.calculate_energy: mass: 500
phase_transition: vaporization
substance: water
thermo.calculate_energy: mass: 500
phase_transition: condensation
substance: water
Expected function call(s):
get_boiling_melting_points: substance: water
sea_level: 0
get_boiling_melting_points: substance: iron
sea_level: 1000
get_boiling_melting_points: substance: water
sea_level: 1000
get_boiling_melting_points: substance: iron
sea_level: 0
Expected function call(s):
calculate_density: mass: 10
volume: 2
unit: kg/m³
calculate_density: mass: 15
volume: 3
unit: kg/m³
Expected function call(s):
calc_absolute_pressure: gauge_pressure: 2.5
atm_pressure: 1
calc_absolute_pressure: gauge_pressure: 2.5
atm_pressure: 0.85
Expected function call(s):
entropy_change.calculate: substance: A
mass: 2
initial_temperature: 25
final_temperature: 75
pressure: 1
entropy_change.calculate: substance: A
mass: 2
initial_temperature: 10
final_temperature: 50
pressure: 1
Expected function call(s):
calculate_entropy_change: initial_temp: 300
final_temp: 350
heat_capacity: 4.18
isothermal: yes
calculate_entropy_change: initial_temp: 300
final_temp: 350
heat_capacity: 4.18
isothermal: no
Expected function call(s):
calc_heat_capacity: temp: 300
volume: 2.5
gas: air
calc_heat_capacity: temp: 350
volume: 2.5
gas: air
calc_heat_capacity: temp: 300
volume: 1.5
gas: air
Expected function call(s):
fetch_DNA_sequence: DNA_id: XYZ123
format: fasta
upstream: 0
fetch_DNA_sequence: DNA_id: XYZ123
format: genbank
upstream: 0
fetch_DNA_sequence: DNA_id: XYZ123
format: fasta
upstream: 500
Expected function call(s):
get_protein_sequence: gene: BRCA1
species: Homo sapiens
get_protein_sequence: gene: BRCA2
species: Homo sapiens
get_protein_sequence: gene: BRCA1
species: Pan troglodytes
get_protein_sequence: gene: BRCA2
species: Pan troglodytes
Expected function call(s):
biology.get_cell_info: cell_type: neuron
detailed: yes
biology.get_cell_info: cell_type: muscle
detailed: no
Expected function call(s):
cellbio.get_proteins: cell_compartment: nucleus
include_description: yes
cellbio.get_proteins: cell_compartment: mitochondria
include_description: yes
cellbio.get_proteins: cell_compartment: cytoplasm
include_description: yes
Expected function call(s):
cell_biology.function_lookup: molecule: ATP
organelle: mitochondria
specific_function: yes
cell_biology.function_lookup: molecule: DNA
organelle: nucleus
specific_function: yes
Expected function call(s):
calculate_molecular_weight: compound: C6H12O6
to_unit: grams/mole
g/mol
calculate_molecular_weight: compound: C12H22O11
to_unit: grams/mole
g/mol
Expected function call(s):
mutation_type.find: snp_id: rs123456
species: Homo sapiens
Humans
mutation_type.find: snp_id: rs7891011
species: Canis lupus familiaris
Dog
Expected function call(s):
diabetes_prediction: weight: 180
height: 70
activity_level: lightly active
diabetes_prediction: weight: 200
height: 65
activity_level: very active
diabetes_prediction: weight: 150
height: 72
activity_level: moderately active
diabetes_prediction: weight: 220
height: 68
activity_level: extra active
Expected function call(s):
analyze_dna_sequence: sequence: AGCTTAGCTA
reference_sequence: AGCTTAGCTA
mutation_type: insertion
analyze_dna_sequence: sequence: AGCTTAGGCTA
reference_sequence: AGCTTAGCTA
mutation_type: insertion
analyze_dna_sequence: sequence: AGCTTAGCTA
reference_sequence: AGCTTAGCTA
mutation_type: deletion
analyze_dna_sequence: sequence: AGCTTAGGCTA
reference_sequence: AGCTTAGCTA
mutation_type: deletion
analyze_dna_sequence: sequence: AGCTTAGCTA
reference_sequence: AGCTTAGCTA
mutation_type: substitution
analyze_dna_sequence: sequence: AGCTTAGGCTA
reference_sequence: AGCTTAGCTA
mutation_type: substitution
Expected function call(s):
genetics.calculate_similarity: species1: human
Human
species2: chimpanzee
format: percentage
genetics.calculate_similarity: species1: human
species2: chimpanzee
format: fraction
genetics.calculate_similarity: species1: human
species2: gorilla
format: percentage
genetics.calculate_similarity: species1: human
species2: gorilla
format: fraction
Expected function call(s):
calculate_genotype_frequency: allele_frequency: 0.7
genotype: AA
calculate_genotype_frequency: allele_frequency: 0.7
genotype: Aa
calculate_genotype_frequency: allele_frequency: 0.7
genotype: aa
Expected function call(s):
calculate_density: country: China
year: 2000
population: 1267000000
land_area: 9597000
calculate_density: country: China
year: 2010
population: 1341000000
land_area: 9597000
Expected function call(s):
ecology_data.precipitation_stats: location: Amazon rainforest
time_frame: six_months
ecology_data.precipitation_stats: location: Amazon rainforest
time_frame: year
ecology_data.precipitation_stats: location: Amazon rainforest
time_frame: five_years
Expected function call(s):
identify_bird: color: blue
habitat: forest
size: small
identify_bird: color: black
habitat: lake
size: large
identify_bird: color: brown
habitat: desert
size: medium
identify_bird: color: green
habitat: tropical rainforest
size: large
Expected function call(s):
forest_growth_forecast: location: Amazon Rainforest
years: 10
include_human_impact: no
forest_growth_forecast: location: Boreal Forests of Canada
years: 20
include_human_impact: no
Expected function call(s):
ecology.get_turtle_population: location: Galapagos Islands
year: 2015
species: yes
ecology.get_turtle_population: location: Galapagos Islands
year: 2020
species: yes
Expected function call(s):
calculate_vehicle_emission: vehicle_type: gas
miles_driven: 15000
emission_factor: 1.4
calculate_vehicle_emission: vehicle_type: diesel
miles_driven: 15000
emission_factor: 2.7
calculate_vehicle_emission: vehicle_type: EV
miles_driven: 15000
emission_factor: 0
Expected function call(s):
generate_DNA_sequence: length: 500
preferences: A
generate_DNA_sequence: length: 500
preferences: T
generate_DNA_sequence: length: 500
preferences: C
generate_DNA_sequence: length: 500
preferences: G
Expected function call(s):
population_projections: country: Japan
years: 10
growth_rate: 0.01
population_projections: country: Japan
years: 10
growth_rate: 0.015
population_projections: country: India
years: 20
growth_rate: 0.021
population_projections: country: India
years: 20
growth_rate: 0.01
Expected function call(s):
elephant_population_estimate: current_population: 500
growth_rate: 0.02
years: 10
elephant_population_estimate: current_population: 500
growth_rate: 0.015
years: 10
elephant_population_estimate: current_population: 500
growth_rate: 0.025
years: 10
Expected function call(s):
prediction.evolution: species: African Elephant
years: 5000
model: Darwin
prediction.evolution: species: African Elephant
years: 5000
model: Lamarck
Expected function call(s):
restaurant.find_nearby: location: New York, NY
New York City
NYC
NY
dietary_preference: Vegan
Gluten-free
Dairy-free
restaurant.find_nearby: location: Los Angeles, CA
LA
Los Angeles
Los Angeles, CA
CA
dietary_preference: Vegan
Gluten-free
Dairy-free
restaurant.find_nearby: location: Chicago, IL
Chicago
IL
dietary_preference: Vegan
Gluten-free
Dairy-free
Expected function call(s):
average_temperature: location: New York
New York, NY
NYC
days: 7
temp_unit: Fahrenheit
average_temperature: location: Los Angeles
Los Angeles, CA
LA
days: 7
temp_unit: Celsius
Expected function call(s):
create_histogram: data: 12
15
11
14
18
19
13
14
15
16
17
18
19
20
21
22
23
24
25
26
bins: 5
create_histogram: data: 32
35
31
34
38
39
33
34
35
36
37
38
39
40
41
42
43
44
45
46
bins: 5
Expected function call(s):
find_restaurants: location: New York
New York, NY
NYC
food_type: Italian
italian
number: 4
dietary_requirements: vegan
gluten-free
find_restaurants: location: Los Angeles
Los Angeles, CA
LA
food_type: Italian
number: 4
dietary_requirements: vegan
gluten-free
Expected function call(s):
map_routing.fastest_route: start_location: San Francisco
SF
end_location: Palo Alto
avoid_tolls: yes
map_routing.fastest_route: start_location: Palo Alto
end_location: San Jose
SJ
avoid_tolls: yes
map_routing.fastest_route: start_location: San Jose
SJ
end_location: San Francisco
SF
avoid_tolls: yes
Expected function call(s):
calculate_average: numbers: 23
45
67
89
calculate_average: numbers: 12
34
56
78
calculate_average: numbers: 98
76
54
32
calculate_average: numbers: 87
65
43
21
Expected function call(s):
calculate_distance: coord1: 48.8584
2.2945
coord2: 41.8902
12.4922
unit: kilometers
km
calculate_distance: coord1: 41.8902
12.4922
coord2: 37.9715
23.7257
unit: kilometers
km
calculate_distance: coord1: 37.9715
23.7257
coord2: 29.9792
31.1342
unit: kilometers
km
Expected function call(s):
calculate_bmi: weight: 85
height: 175
unit: metric
calculate_bmi: weight: 60
height: 160
unit: metric
calculate_bmi: weight: 75
height: 180
unit: metric
calculate_bmi: weight: 90
height: 185
unit: metric
Expected function call(s):
geo_distance.calculate: start_location: New York
New York, NY
New York, NY
NYC
end_location: Los Angeles
Los Angeles, CA
LA
units: kilometers
geo_distance.calculate: start_location: Los Angeles
Los Angeles, CA
LA
end_location: Miami
units: kilometers
geo_distance.calculate: start_location: Miami
end_location: New York
New York, NY
NYC
units: kilometers
Expected function call(s):
city_distance.find_shortest: start_city: New York
New York, NY
NYC
end_city: Los Angeles
Los Angeles, CA
LA
transportation: bus
allow_transfer: no
city_distance.find_shortest: start_city: New York
New York, NY
NYC
end_city: Los Angeles
Los Angeles, CA
LA
transportation: bus
allow_transfer: yes
Expected function call(s):
array_sort: list: 45
12
67
21
89
order: ascending
array_sort: list: 45
12
67
21
89
order: descending
array_sort: list: 34
78
12
56
90
order: ascending
array_sort: list: 34
78
12
56
90
order: descending
array_sort: list: 23
45
67
89
12
order: ascending
array_sort: list: 23
45
67
89
12
order: descending
array_sort: list: 56
78
90
12
34
order: ascending
array_sort: list: 56
78
90
12
34
order: descending
Expected function call(s):
calculate_BMI: weight_kg: 85
height_m: 1.8
calculate_BMI: weight_kg: 60
height_m: 1.65
calculate_BMI: weight_kg: 75
height_m: 1.7
Expected function call(s):
employee.fetch_data: company_name: Tech Solutions
employee_id: 12345
data_field: Personal Info
Job History
Payroll
Attendance
employee.fetch_data: company_name: Tech Solutions
employee_id: 67890
data_field: Personal Info
Job History
Payroll
Attendance
Expected function call(s):
imdb.find_movies_by_actor: actor_name: Leonardo DiCaprio
year: 2010
category: Drama
imdb.find_movies_by_actor: actor_name: Leonardo DiCaprio
year: 2012
category: Comedy
Expected function call(s):
get_theater_movie_releases: location: New York
New York, NY
NYC
timeframe: 7
format: IMAX
get_theater_movie_releases: location: Los Angeles
Los Angeles, CA
LA
timeframe: 14
format: 2D
Expected function call(s):
update_user_info: user_id: 12345
update_info: name: John
email: example@.com
database: CustomerInfo
update_user_info: user_id: 67890
update_info: name: John
email: example@.com
database: CustomerInfo
Expected function call(s):
calc_area_triangle: base: 10
height: 5
calc_area_triangle: base: 15
height: 7
calc_area_triangle: base: 20
height: 10
Expected function call(s):
math.factorial: number: 5
math.factorial: number: 3
math.factorial: number: 4
math.factorial: number: 2
Expected function call(s):
calculate_clock_angle: hours: 3
minutes: 15
round_to: 2
calculate_clock_angle: hours: 8
minutes: 20
round_to: 2
calculate_clock_angle: hours: 11
minutes: 50
round_to: 2
Expected function call(s):
plot_sine_wave: start_range: 0
end_range: 10
frequency: 5
amplitude: 2
phase_shift: 1
plot_sine_wave: start_range: 0
end_range: 20
frequency: 10
amplitude: 3
phase_shift: 2
Expected function call(s):
light_travel_time: distance_in_light_years: 4.22
speed_of_light: 299792458
light_travel_time: distance_in_light_years: 6.1
speed_of_light: 299792458
light_travel_time: distance_in_light_years: 5.88
speed_of_light: 299792458
Expected function call(s):
calculate_speed: distance: 500
time: 25
to_unit: km/h
calculate_speed: distance: 1000
time: 200
to_unit: m/s
calculate_speed: distance: 10000
time: 600
to_unit: km/h
Expected function call(s):
calculate_distance: body1: Mars
body2: Venus
unit: miles
calculate_distance: body1: Mars
body2: Jupiter
unit: miles
Expected function call(s):
mathematics.calculate_area_under_curve: polynomial: 3
-2
1
limits: -1
2
mathematics.calculate_area_under_curve: polynomial: 1
0
-1
limits: 0
3
Expected function call(s):
geometry.area_triangle: base: 15
height: 20
unit: square meters
m^2
geometry.area_triangle: base: 25
height: 30
unit: square feet
ft^2
geometry.area_triangle: base: 35
height: 40
unit: square inches
in^2
Expected function call(s):
math.power: base: 2
exponent: 3
math.power: base: 3
exponent: 5
Expected function call(s):
train_random_forest_classifier: dataset: dataset1
max_depth: 10
n_estimators: 100
train_random_forest_classifier: dataset: dataset2
max_depth: 20
n_estimators: 200
Expected function call(s):
calculate_bmi: weight: 75
height: 180
system: metric
calculate_bmi: weight: 60
height: 165
system: metric
calculate_bmi: weight: 80
height: 175
system: metric
calculate_bmi: weight: 90
height: 185
system: metric
Expected function call(s):
run_linear_regression: predictors: Age
Income
Education
target: Spending Score
standardize: no
run_linear_regression: predictors: Age
Income
Education
target: Spending Score
standardize: yes
no
Expected function call(s):
random_forest.train: n_estimators: 100
max_depth: 10
data: data_random_forest
random_forest.train: n_estimators: 200
max_depth: 20
data: data_random_forest
random_forest.train: n_estimators: 300
max_depth: 30
data: data_random_forest
random_forest.train: n_estimators: 400
max_depth: 40
data: data_random_forest
Expected function call(s):
predict_house_price: bedrooms: 3
bathrooms: 2
area: 1500
location: New York
New York, NY
New York City
NYC
predict_house_price: bedrooms: 4
bathrooms: 3
area: 2000
location: Los Angeles
Los Angeles, CA
LA
predict_house_price: bedrooms: 2
bathrooms: 1
area: 1200
location: Chicago
predict_house_price: bedrooms: 3
bathrooms: 2
area: 1800
location: Miami
Expected function call(s):
random.normalvariate: mu: 5
sigma: 2
random.normalvariate: mu: 10
sigma: 3
Expected function call(s):
probability.dice_roll: desired_number: 4
number_of_rolls: 3
die_sides: 6
probability.dice_roll: desired_number: 2
number_of_rolls: 2
die_sides: 6
probability.dice_roll: desired_number: 7
number_of_rolls: 2
die_sides: 8
Expected function call(s):
prob_dist.binomial: trials: 20
successes: 5
p: 0.3
prob_dist.binomial: trials: 50
successes: 15
p: 0.3
prob_dist.binomial: trials: 100
successes: 30
p: 0.3
Expected function call(s):
calculate_binomial_probability: number_of_trials: 10
number_of_successes: 7
probability_of_success: 0.6
calculate_binomial_probability: number_of_trials: 15
number_of_successes: 10
probability_of_success: 0.6
calculate_binomial_probability: number_of_trials: 20
number_of_successes: 15
probability_of_success: 0.6
Expected function call(s):
probability_of_event: success_outcomes: 4
total_outcomes: 52
format_as_ratio: no
probability_of_event: success_outcomes: 13
total_outcomes: 52
format_as_ratio: no
probability_of_event: success_outcomes: 26
total_outcomes: 52
format_as_ratio: yes
Expected function call(s):
calc_binomial_prob: num_trials: 10
num_success: 6
prob_success: 0.6
calc_binomial_prob: num_trials: 10
num_success: 6
prob_success: 0.5
calc_binomial_prob: num_trials: 15
num_success: 6
prob_success: 0.5
Expected function call(s):
chi_squared_test: table: 45
55
35
65
alpha: 0.05
chi_squared_test: table: 30
70
50
50
alpha: 0.05
Expected function call(s):
t_test: dataset_A: 12
15
18
20
22
25
28
30
32
35
dataset_B: 14
17
19
21
23
26
29
31
33
36
alpha: 0.05
t_test: dataset_A: 12
15
18
20
22
25
28
30
32
35
dataset_B: 14
17
19
21
23
26
29
31
33
36
alpha: 0.01
Expected function call(s):
predict_house_price: area: 2500
rooms: 3
year: 2000
location: New York
New York, NY
New York City
NYC
NY
predict_house_price: area: 3000
rooms: 3
year: 2005
location: Los Angeles
Los Angeles, CA
LA
Los Angeles, CA
CA
predict_house_price: area: 2000
rooms: 2
year: 1995
location: Chicago
Expected function call(s):
linear_regression.get_r_squared: dataset_path: /user/home/datasets/finance.csv
independent_variables: income
age
education
dependent_variable: credit_score
linear_regression.get_r_squared: dataset_path: /user/home/datasets/finance.csv
independent_variables: income
age
credit_score
dependent_variable: education
Expected function call(s):
finance.calculate_quarterly_dividend_per_share: total_payout: 5000000
outstanding_shares: 2000000
finance.calculate_quarterly_dividend_per_share: total_payout: 6000000
outstanding_shares: 2500000
finance.calculate_quarterly_dividend_per_share: total_payout: 6000000
outstanding_shares: 2000000
Expected function call(s):
calculate_discounted_cash_flow: coupon_payment: 50
period: 5
discount_rate: 0.05
face_value: 1000
calculate_discounted_cash_flow: coupon_payment: 60
period: 7
discount_rate: 0.04
face_value: 1000
Expected function call(s):
calculate_compound_interest: principal: 5000
rate: 0.025
time: 2
n: 4
calculate_compound_interest: principal: 5000
rate: 0.025
time: 3
n: 4
calculate_compound_interest: principal: 5000
rate: 0.025
time: 5
n: 4
Expected function call(s):
calculate_return_on_equity: net_income: 1000000
shareholder_equity: 5000000
dividends_paid: 200000
calculate_return_on_equity: net_income: 2000000
shareholder_equity: 10000000
dividends_paid: 0
Expected function call(s):
finance.predict_future_value: present_value: 5000
annual_interest_rate: 0.05
compounding_periods_per_year: 1
time_years: 10
finance.predict_future_value: present_value: 7000
annual_interest_rate: 0.04
compounding_periods_per_year: 1
time_years: 15
Expected function call(s):
investment.predictProfit: investment_amount: 5000
annual_return: 0.07
years: 5
investment.predictProfit: investment_amount: 8000
annual_return: 0.05
years: 7
Expected function call(s):
calculate_return_on_investment: purchase_price: 150
sale_price: 180
dividend: 20
calculate_return_on_investment: purchase_price: 200
sale_price: 210
dividend: 30
calculate_return_on_investment: purchase_price: 250
sale_price: 300
dividend: 40
Expected function call(s):
portfolio_future_value: stock: AAPL
invested_amount: 5000
expected_annual_return: 0.07
years: 5
portfolio_future_value: stock: MSFT
invested_amount: 8000
expected_annual_return: 0.06
years: 7
portfolio_future_value: stock: AMZN
invested_amount: 10000
expected_annual_return: 0.08
years: 10
Expected function call(s):
calculate_cagr: initial_value: 5000
final_value: 7000
period_in_years: 5
calculate_cagr: initial_value: 8000
final_value: 12000
period_in_years: 3
Expected function call(s):
get_metal_price: metal: gold
measure: ounce
get_metal_price: metal: silver
measure: ounce
get_metal_price: metal: platinum
measure: ounce
get_metal_price: metal: palladium
measure: ounce
Expected function call(s):
get_stock_price: company_name: Microsoft
Apple
date: 2022-01-01
01/01/2022
Jan.1,2022
exchange: NASDAQ
get_stock_price: company_name: Microsoft
date: 2022-02-01
02/01/2022
Feb.1,2022
exchange: NASDAQ
get_stock_price: company_name: Apple
date: 2022-01-01
01/01/2022
Jan.1,2022
exchange: NASDAQ
get_stock_price: company_name: Apple
date: 2022-02-01
02/01/2022
Feb.1,2022
exchange: NASDAQ
Expected function call(s):
get_stock_price: company: AAPL
days: 10
exchange: NASDAQ
get_stock_price: company: MSFT
days: 15
exchange: NYSE
Expected function call(s):
stock_price: company: Microsoft
days: 30
data_type: Open
stock_price: company: Microsoft
days: 30
data_type: Close
stock_price: company: Microsoft
days: 30
data_type: High
stock_price: company: Microsoft
days: 30
data_type: Low
stock_price: company: Apple
days: 30
data_type: Open
stock_price: company: Apple
days: 30
data_type: Close
stock_price: company: Apple
days: 30
data_type: High
stock_price: company: Apple
days: 30
data_type: Low
Expected function call(s):
get_stock_prices: companies: Apple
duration: 1 week
get_stock_prices: companies: Microsoft
duration: 2 weeks
get_stock_prices: companies: Amazon
duration: 3 weeks
get_stock_prices: companies: Tesla
duration: 1 month
Expected function call(s):
finance.calculate_future_value: initial_investment: 5000
rate_of_return: 0.07
years: 10
contribution: 0
finance.calculate_future_value: initial_investment: 3000
rate_of_return: 0.06
years: 10
contribution: 200
Expected function call(s):
math.hypot: x: 5
y: 7
z: 0
math.hypot: x: 10
y: 15
z: 0
math.hypot: x: 20
y: 25
z: 0
Expected function call(s):
algebra.quadratic_roots: a: 3
b: 7
c: 2
algebra.quadratic_roots: a: 5
b: -4
c: 1
Expected function call(s):
estimate_population: species: Bengal Tigers
Bengal Tiger
country: India
year: 2021
estimate_population: species: African Elephants
country: Kenya
year: 2021
estimate_population: species: Bengal Tigers
Bengal Tiger
country: India
estimate_population: species: African Elephants
country: Kenya
year: 2023
Expected function call(s):
calculate_emission_savings: energy_type: solar
usage_duration: 12
region: Midwest
Midwest region
calculate_emission_savings: energy_type: wind
usage_duration: 8
region: Midwest
Midwest region
Expected function call(s):
get_air_quality: location: New York City
NYC
detail: yes
historical: 2023-05-05
get_air_quality: location: New York City
NYC
detail: yes
historical: 2023-05-04
get_air_quality: location: New York City
NYC
detail: yes
historical: 2023-05-03
Expected function call(s):
get_traffic_info: start_location: New York
New York, NY
NYC
end_location: Los Angeles
Los Angeles, CA
LA
mode: driving
get_traffic_info: start_location: Los Angeles
Los Angeles, CA
LA
end_location: San Francisco
SF
mode: bicycling
get_traffic_info: start_location: San Francisco
SF
end_location: New York
New York, NY
NYC
mode: transit
Expected function call(s):
parks.find_nearby: location: New York, USA
NY, USA
New York City, USA
NYC, USA
amenities: Tennis Court
Picnic Area
parks.find_nearby: location: Los Angeles, USA
LA, USA
amenities: Playground
Running Track
parks.find_nearby: location: Chicago, USA
amenities: Tennis Court
Playground
Expected function call(s):
calculate_shortest_distance: start_location: New York City
NYC
end_location: Los Angeles
Los Angeles, CA
LA
route_preference: Shortest
calculate_shortest_distance: start_location: Los Angeles
Los Angeles, CA
LA
end_location: Miami
route_preference: Shortest
calculate_shortest_distance: start_location: New York City
NYC
end_location: Los Angeles
Los Angeles, CA
LA
route_preference: Scenic
calculate_shortest_distance: start_location: Los Angeles
Los Angeles, CA
LA
end_location: Miami
route_preference: Scenic
Expected function call(s):
public_library.find_nearby: location: New York, NY
NY
facilities: Reading Room
Fiction
public_library.find_nearby: location: Los Angeles, CA
LA
facilities: Wi-Fi
Children Section
public_library.find_nearby: location: Chicago, IL
Chi
facilities: Cafe
Reading Room
Expected function call(s):
get_news: topic: Climate Change
quantity: 5
region: Europe
EU
get_news: topic: Artificial Intelligence
quantity: 5
region: Europe
EU
Expected function call(s):
send_email: to: john.doe@example.com
subject: Project Update
body: Dear John, The project is progressing as planned and we are on track to meet our deadlines. Best, Alex
cc: manager@example.com
bcc: hr@example.com
send_email: to: jane.doe@example.com
subject: Meeting Reminder
body: Dear Jane, This is a reminder for our meeting scheduled for tomorrow at 10 AM. Best, Alex
cc: assistant@example.com
bcc: hr@example.com
Expected function call(s):
event_finder.find_upcoming: location: Los Angeles, CA
LA
genre: jazz
days_ahead: 14
event_finder.find_upcoming: location: Chicago, IL
genre: rock
days_ahead: 10
event_finder.find_upcoming: location: Boston, MA
genre: classical music
classical
days_ahead: 7
Expected function call(s):
movie_details.brief: title: Inception
extra_info: yes
movie_details.brief: title: The Dark Knight
extra_info: yes
Expected function call(s):
get_lawsuit_details: case_number: 12345
court_location: New York Supreme Court
NY Supreme Court
with_verdict: yes
get_lawsuit_details: case_number: 67890
court_location: Los Angeles Superior Court
LA Superior Court
with_verdict: no
Expected function call(s):
lawsuit_info: case_number: 12345ABC
year: 2018
location: New York
New York, NY
NY
lawsuit_info: case_number: 67890XYZ
year: 2019
location: California
CA
Expected function call(s):
lawsuit_search: entity: Google
county: Santa Clara
state: California
CA
lawsuit_search: entity: Facebook
county: San Mateo
state: California
CA
Expected function call(s):
get_current_weather: location: New York
New York, NY
New York City
NYC
include_temperature: yes
include_humidity: yes
get_current_weather: location: Los Angeles
Los Angeles, CA
LA
include_temperature: yes
include_humidity: yes
get_current_weather: location: London
include_temperature: yes
include_humidity: yes
get_current_weather: location: Tokyo
include_temperature: yes
include_humidity: yes