Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

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you might might answer 
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{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "👑", "🌅", "🎶", "🦁"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "🔪", "🇮🇹", "💰"],
  "The Matrix": ["💊", "💻", "🕶️", "🔫", "🤖"],
  "Casablanca": ["✈️", "❤️", "🍸", "🕵️‍♂️", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🗿", "💥"],
  "V for Vendetta": ["🎭", "💣", "✊", "🇬🇧", "🔥"],
  "The Princess Bride": ["⚔️", "👸", "❤️", "🐀", "🏰"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "👨‍👩‍👦‍👦", "🎸"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "👑", "🌅", "🎶", "🦁"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "🔪", "🇮🇹", "💰"],
  "The Matrix": ["💊", "💻", "🕶️", "🔫", "🤖"],
  "Casablanca": ["✈️", "❤️", "🍸", "🕵️‍♂️", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🗿", "💥"],
  "V for Vendetta": ["🎭", "💣", "✊", "🇬🇧", "🔥"],
  "The Princess Bride": ["⚔️", "👸", "❤️", "🐀", "🏰"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "👨‍👩‍👦‍👦", "🎸"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

PyFunc

Resulting in output: [['🦁', '👑', '🌅', '🎶', '🦁'], ['🎃', '👻', '💀', '🎄', '🎶'], ['🔫', '🔪', '🇮🇹', '💰'], ['💊', '💻', '🕶️', '🔫', '🤖'], ['✈️', '❤️', '🍸', '😢'], ['🤠', '🐍', '🗺️', '🗿', '💥'], ['🎭', '💣', '✊', '🇬🇧', '🔥'], ['⚔️', '👸', '❤️', '🐀', '🏰'], ['🚗', '⚡️', '🕰️', '🎸'], ['🏜️', '🐛', '🔮', '⚔️', '🌌']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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['🎃', '👻', '💀', '🎄', '🎶'],
['🔫', '🔪', '🇮🇹', '💰'],
['💊', '💻', '🕶️', '🔫', '🤖'],
['✈️', '❤️', '🍸', '😢'],
['🤠', '🐍', '🗺️', '🗿', '💥'],
['🎭', '💣', '✊', '🇬🇧', '🔥'],
['⚔️', '👸', '❤️', '🐀', '🏰'],
['🚗', '⚡️', '🕰️', '🎸'],
['🏜️', '🐛', '🔮', '⚔️', '🌌']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "💔"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "💰", "🇮🇹", "🌹"],
  "The Matrix": ["💊", "😎", "🤖", "🔫", "💻"],
  "Casablanca": ["✈️", "🍸", "💔", "🎹", "🕵️‍♂️"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🗿", "💥"],
  "V for Vendetta": ["🎭", "💣", "✊", "🇬🇧", "🔥"],
  "The Princess Bride": ["⚔️", "👸", "🐭", "💋", "🏰"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "🎸", "👨‍👦"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🚀"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "💔"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "💰", "🇮🇹", "🌹"],
  "The Matrix": ["💊", "😎", "🤖", "🔫", "💻"],
  "Casablanca": ["✈️", "🍸", "💔", "🎹", "🕵️‍♂️"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🗿", "💥"],
  "V for Vendetta": ["🎭", "💣", "✊", "🇬🇧", "🔥"],
  "The Princess Bride": ["⚔️", "👸", "🐭", "💋", "🏰"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "🎸", "👨‍👦"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🚀"]
}

PyFunc

Resulting in output: [['🦁', '👑', '🌄', '🎶', '💔'], ['🎃', '👻', '💀', '🎄', '🎶'], ['🔫', '💰', '🇮🇹', '🌹'], ['💊', '😎', '🤖', '🔫', '💻'], ['✈️', '🍸', '💔', '🎹'], ['🤠', '🐍', '🗺️', '🗿', '💥'], ['🎭', '💣', '✊', '🇬🇧', '🔥'], ['⚔️', '👸', '🐭', '💋', '🏰'], ['🚗', '⚡️', '🕰️', '🎸'], ['🏜️', '🐛', '🔮', '⚔️', '🚀']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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2
3
4
5
6
7
8
9
['🎃', '👻', '💀', '🎄', '🎶'],
['🔫', '💰', '🇮🇹', '🌹'],
['💊', '😎', '🤖', '🔫', '💻'],
['✈️', '🍸', '💔', '🎹'],
['🤠', '🐍', '🗺️', '🗿', '💥'],
['🎭', '💣', '✊', '🇬🇧', '🔥'],
['⚔️', '👸', '🐭', '💋', '🏰'],
['🚗', '⚡️', '🕰️', '🎸'],
['🏜️', '🐛', '🔮', '⚔️', '🚀']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Sleeping Beauty", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King", "The Nightmare Before Christmas", "The Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Sleeping Beauty", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "🦁"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "💰", "🌹", "🇮🇹"],
  "The Matrix": ["💊", "🕶️", "🔫", "🤖", "❓"],
  "Casablanca": ["✈️", "🍸", "❤️", "🎹", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🏺", "🏃"],
  "V for Vendetta": ["🎭", "💥", "✊", "🇬🇧", "🔪"],
  "The Princess Bride": ["🤺", "👑", "🐀", "🏰", "❤️"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "🎸", "👨‍👩‍👧‍👦"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "🦁"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "💰", "🌹", "🇮🇹"],
  "The Matrix": ["💊", "🕶️", "🔫", "🤖", "❓"],
  "Casablanca": ["✈️", "🍸", "❤️", "🎹", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🏺", "🏃"],
  "V for Vendetta": ["🎭", "💥", "✊", "🇬🇧", "🔪"],
  "The Princess Bride": ["🤺", "👑", "🐀", "🏰", "❤️"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "🎸", "👨‍👩‍👧‍👦"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

PyFunc

Resulting in output: [['🦁', '👑', '🌄', '🎶', '🦁'], ['🎃', '👻', '💀', '🎄', '🎶'], ['🔫', '💰', '🌹', '🇮🇹'], ['💊', '🕶️', '🔫', '🤖', '❓'], ['✈️', '🍸', '❤️', '🎹', '😢'], ['🤠', '🐍', '🗺️', '🏺', '🏃'], ['🎭', '💥', '✊', '🇬🇧', '🔪'], ['🤺', '👑', '🐀', '🏰', '❤️'], ['🚗', '⚡️', '🕰️', '🎸'], ['🏜️', '🐛', '🔮', '⚔️', '🌌']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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2
3
4
5
6
7
8
9
['🎃', '👻', '💀', '🎄', '🎶'],
['🔫', '💰', '🌹', '🇮🇹'],
['💊', '🕶️', '🔫', '🤖', '❓'],
['✈️', '🍸', '❤️', '🎹', '😢'],
['🤠', '🐍', '🗺️', '🏺', '🏃'],
['🎭', '💥', '✊', '🇬🇧', '🔪'],
['🤺', '👑', '🐀', '🏰', '❤️'],
['🚗', '⚡️', '🕰️', '🎸'],
['🏜️', '🐛', '🔮', '⚔️', '🌌']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King", "The Nightmare Before Christmas", "The Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "🦁"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "🌹", "💰", "🇮🇹"],
  "The Matrix": ["💊", "😎", "🤖", "🔫", "💻"],
  "Casablanca": ["✈️", "❤️", "🍸", "🕵️‍♂️", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🗿", "💥"],
  "V for Vendetta": ["🎭", "💣", "✊", "🇬🇧", "🔥"],
  "The Princess Bride": ["⚔️", "👸", "❤️", "🐭", "🤺"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "👨‍👩‍👧‍👦", "🎸"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "🦁"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "🌹", "💰", "🇮🇹"],
  "The Matrix": ["💊", "😎", "🤖", "🔫", "💻"],
  "Casablanca": ["✈️", "❤️", "🍸", "🕵️‍♂️", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🗿", "💥"],
  "V for Vendetta": ["🎭", "💣", "✊", "🇬🇧", "🔥"],
  "The Princess Bride": ["⚔️", "👸", "❤️", "🐭", "🤺"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "👨‍👩‍👧‍👦", "🎸"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

PyFunc

Resulting in output: [['🦁', '👑', '🌄', '🎶', '🦁'], ['🎃', '👻', '💀', '🎄', '🎶'], ['🔫', '🌹', '💰', '🇮🇹'], ['💊', '😎', '🤖', '🔫', '💻'], ['✈️', '❤️', '🍸', '😢'], ['🤠', '🐍', '🗺️', '🗿', '💥'], ['🎭', '💣', '✊', '🇬🇧', '🔥'], ['⚔️', '👸', '❤️', '🐭', '🤺'], ['🚗', '⚡️', '🕰️', '🎸'], ['🏜️', '🐛', '🔮', '⚔️', '🌌']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
1
2
3
4
5
6
7
8
9
['🎃', '👻', '💀', '🎄', '🎶'],
['🔫', '🌹', '💰', '🇮🇹'],
['💊', '😎', '🤖', '🔫', '💻'],
['✈️', '❤️', '🍸', '😢'],
['🤠', '🐍', '🗺️', '🗿', '💥'],
['🎭', '💣', '✊', '🇬🇧', '🔥'],
['⚔️', '👸', '❤️', '🐭', '🤺'],
['🚗', '⚡️', '🕰️', '🎸'],
['🏜️', '🐛', '🔮', '⚔️', '🌌']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

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you might might answer 
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{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
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Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

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you might might answer 
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{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
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Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "💔"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "🔪", "🇮🇹", "💰"],
  "The Matrix": ["💊", "💻", "😎", "🔫", "🤖"],
  "Casablanca": ["✈️", "❤️", "🍸", "🕵️‍♂️", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🏃‍♂️", "🛕"],
  "V for Vendetta": ["🎭", "💥", "✊", "🇬🇧", "🔪"],
  "The Princess Bride": ["⚔️", "👸", "❤️", "🐀", "巨人"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "👨‍👩‍👧‍👦", "🎸"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "👑", "🌄", "🎶", "💔"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🎄", "🎶"],
  "The Godfather": ["👨‍👩‍👧‍👦", "🔫", "🔪", "🇮🇹", "💰"],
  "The Matrix": ["💊", "💻", "😎", "🔫", "🤖"],
  "Casablanca": ["✈️", "❤️", "🍸", "🕵️‍♂️", "😢"],
  "Raiders of the Lost Ark": ["🤠", "🐍", "🗺️", "🏃‍♂️", "🛕"],
  "V for Vendetta": ["🎭", "💥", "✊", "🇬🇧", "🔪"],
  "The Princess Bride": ["⚔️", "👸", "❤️", "🐀", "巨人"],
  "Back to the Future": ["🚗", "⚡️", "🕰️", "👨‍👩‍👧‍👦", "🎸"],
  "Dune": ["🏜️", "🐛", "🔮", "⚔️", "🌌"]
}

PyFunc

Resulting in output: [['🦁', '👑', '🌄', '🎶', '💔'], ['🎃', '👻', '💀', '🎄', '🎶'], ['🔫', '🔪', '🇮🇹', '💰'], ['💊', '💻', '😎', '🔫', '🤖'], ['✈️', '❤️', '🍸', '😢'], ['🤠', '🐍', '🗺️', '🛕'], ['🎭', '💥', '✊', '🇬🇧', '🔪'], ['⚔️', '👸', '❤️', '🐀', '巨人'], ['🚗', '⚡️', '🕰️', '🎸'], ['🏜️', '🐛', '🔮', '⚔️', '🌌']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

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You might answer 
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["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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['🎃', '👻', '💀', '🎄', '🎶'],
['🔫', '🔪', '🇮🇹', '💰'],
['💊', '💻', '😎', '🔫', '🤖'],
['✈️', '❤️', '🍸', '😢'],
['🤠', '🐍', '🗺️', '🛕'],
['🎭', '💥', '✊', '🇬🇧', '🔪'],
['⚔️', '👸', '❤️', '🐀', '巨人'],
['🚗', '⚡️', '🕰️', '🎸'],
['🏜️', '🐛', '🔮', '⚔️', '🌌']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Ella Enchanted", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Ella Enchanted", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True