Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

Understood. I'll ask yes or no questions to try to determine the animal you're thinking of. I'll number my questions, provide my internal thought process, and then ask the question. I won't make my final guess until I'm confident. Let's begin! 1. [It's best to start with broad categories to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Great, knowing it's a mammal narrows down the possibilities significantly. Let's try to determine its habitat next.] Question: Does this animal primarily live on land (as opposed to water or air)?

Iteration 1

PyFunc

Resulting in output: Does this animal primarily live on land (as opposed to water or air)?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal primarily live on land (as opposed to water or air)?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [That eliminates aquatic mammals and bats. Now let's try to get a sense of its size.] Question: Is this animal larger than a house cat?

Iteration 2

PyFunc

Resulting in output: Is this animal larger than a house cat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a house cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [So we're dealing with a medium to large land mammal. Let's narrow down the diet.] Question: Is this animal a carnivore?

Iteration 3

PyFunc

Resulting in output: Is this animal a carnivore?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a carnivore?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [Not a carnivore, so it's likely an herbivore or omnivore. Let's check if it's a common domesticated animal.] Question: Is this animal commonly kept as livestock or a pet?

Iteration 4

PyFunc

Resulting in output: Is this animal commonly kept as livestock or a pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly kept as livestock or a pet?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. [This narrows it down considerably. Let's try to determine if it's primarily raised for food or companionship.] Question: Is this animal primarily raised for food production (meat, milk, etc.)?

Iteration 5

PyFunc

Resulting in output: Is this animal primarily raised for food production (meat, milk, etc.)?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal primarily raised for food production (meat, milk, etc.)?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. [Interesting. So it's a larger-than-cat mammal that's commonly kept as a pet or for non-food purposes. Let's check a popular pet option.] Question: Is this animal a dog?

Iteration 6

PyFunc

Resulting in output: Is this animal a dog?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a dog?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. [Not a dog. Given its size and domestic nature, there aren't too many options left. Let's check another common large pet.] Question: Is this animal a horse?

Iteration 7

PyFunc

Resulting in output: Is this animal a horse?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a horse?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

9. [Not a horse either. This is intriguing. Let's try to narrow down some physical characteristics.] Question: Does this animal have hooves?

Iteration 8

PyFunc

Resulting in output: Does this animal have hooves?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have hooves?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. [Hooved, larger than a cat, domestic, but not primarily for food. The possibilities are narrowing.] Question: Is this animal often used for riding or transportation?

Iteration 9

PyFunc

Resulting in output: Is this animal often used for riding or transportation?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal often used for riding or transportation?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [Interesting. A hooved animal not primarily used for riding or food. Let's check its relative size again.] Question: Is this animal smaller than a cow?

Iteration 10

PyFunc

Resulting in output: Is this animal smaller than a cow?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal smaller than a cow?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

12. [So it's a large hooved animal, at least as big as a cow, kept as a pet or for non-food purposes, not primarily for riding. The options are becoming quite limited.] Question: Does this animal have a long neck?

Iteration 11

PyFunc

Resulting in output: Does this animal have a long neck?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a long neck?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

13. [A long neck on a large, hooved animal narrows it down significantly. I have a strong suspicion, but I'll ask a few more questions to be certain.] Question: Is this animal native to Africa?

Iteration 12

PyFunc

Resulting in output: Is this animal native to Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. [Not native to Africa, which rules out some possibilities. Given its size and characteristics, I'm fairly certain, but I'll ask one more question to be absolutely sure.] Question: Is this animal known for its ability to spit?

Iteration 13

PyFunc

Resulting in output: Is this animal known for its ability to spit?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal known for its ability to spit?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

15. [At this point, I'm very confident about the answer.] Question: Is the answer a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

Understood. I'll ask yes or no questions to try and guess the animal you're thinking of. I'll number my questions, provide any internal thoughts, and then ask the question. I won't make a final guess until I'm confident. Let's begin! 1. Let's start with a broad category to narrow down our options. Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. That narrows it down significantly. Let's try to determine its habitat next. Question: Does this animal primarily live on land (as opposed to water or air)?

Iteration 1

PyFunc

Resulting in output: Does this animal primarily live on land (as opposed to water or air)?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal primarily live on land (as opposed to water or air)?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. Okay, we're dealing with a land-dwelling mammal. Let's consider size next. Question: Is this animal larger than a house cat?

Iteration 2

PyFunc

Resulting in output: Is this animal larger than a house cat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a house cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. Interesting. We're looking at a medium to large land mammal. Let's explore its diet. Question: Is this animal a carnivore?

Iteration 3

PyFunc

Resulting in output: Is this animal a carnivore?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a carnivore?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. Not a carnivore. This narrows things down further. Let's consider its geographical distribution. Question: Can this animal be found in North America?

Iteration 4

PyFunc

Resulting in output: Can this animal be found in North America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Can this animal be found in North America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. Not found in North America. This is helpful. Let's consider other continents. Question: Is this animal native to Africa?

Iteration 5

PyFunc

Resulting in output: Is this animal native to Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. Not native to Africa either. Let's continue exploring geographical possibilities. Question: Is this animal found in Asia?

Iteration 6

PyFunc

Resulting in output: Is this animal found in Asia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal found in Asia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. Interesting. We've ruled out North America, Africa, and Asia. Let's consider another continent. Question: Is this animal native to Australia?

Iteration 7

PyFunc

Resulting in output: Is this animal native to Australia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Australia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

9. This is getting quite intriguing. We've ruled out several major continents. Let's try one more. Question: Is this animal found in South America?

Iteration 8

PyFunc

Resulting in output: Is this animal found in South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal found in South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. Excellent, we've narrowed it down to a South American land mammal that's larger than a house cat and not a carnivore. Let's explore some physical characteristics. Question: Does this animal have fur?

Iteration 9

PyFunc

Resulting in output: Does this animal have fur?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have fur?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

11. A furry South American mammal. We're making progress. Let's consider some distinctive features. Question: Does this animal have a long neck?

Iteration 10

PyFunc

Resulting in output: Does this animal have a long neck?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a long neck?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

12. A long-necked, furry South American mammal. This is starting to sound familiar. Let's confirm a few more details. Question: Is this animal known for spitting when agitated?

Iteration 11

PyFunc

Resulting in output: Is this animal known for spitting when agitated?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal known for spitting when agitated?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

13. I'm becoming quite confident, but I'll ask a few more questions to be absolutely sure. Question: Is this animal often used as a pack animal in the Andes mountains?

Iteration 12

PyFunc

Resulting in output: Is this animal often used as a pack animal in the Andes mountains?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal often used as a pack animal in the Andes mountains?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

14. I'm nearly certain, but I'll ask one final question to confirm. Question: Is the animal I'm thinking of a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

Understood. I'll ask yes or no questions to try and guess the animal you're thinking of. I'll number my questions, provide my internal thoughts, and then ask the question. I won't make my final guess until I'm confident. Let's begin! 1. [Let's start with a broad category to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Good, that narrows it down significantly. Let's try to determine its habitat next.] Question: Does this animal primarily live on land (as opposed to water or air)?

Iteration 1

PyFunc

Resulting in output: Does this animal primarily live on land (as opposed to water or air)?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal primarily live on land (as opposed to water or air)?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [Okay, we're dealing with a land-dwelling mammal. Let's consider size next to further narrow our options.] Question: Is this animal larger than a house cat?

Iteration 2

PyFunc

Resulting in output: Is this animal larger than a house cat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a house cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [That eliminates many smaller mammals. Let's try to determine if it's a common domesticated animal or something more exotic.] Question: Is this animal commonly kept as a pet or domesticated animal?

Iteration 3

PyFunc

Resulting in output: Is this animal commonly kept as a pet or domesticated animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly kept as a pet or domesticated animal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [Interesting. So we're likely dealing with a wild animal. Let's try to narrow down its geographic range.] Question: Is this animal native to Africa?

Iteration 4

PyFunc

Resulting in output: Is this animal native to Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. [Not native to Africa. Let's try another continent.] Question: Is this animal found in North America?

Iteration 5

PyFunc

Resulting in output: Is this animal found in North America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal found in North America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. [Not North America either. Let's continue exploring geographical distribution.] Question: Is this animal native to Asia?

Iteration 6

PyFunc

Resulting in output: Is this animal native to Asia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Asia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. [Not Africa, North America, or Asia. Let's check another continent.] Question: Is this animal native to South America?

Iteration 7

PyFunc

Resulting in output: Is this animal native to South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. [Great, we've narrowed it down to a South American land mammal larger than a house cat. Let's explore some physical characteristics.] Question: Does this animal have fur?

Iteration 8

PyFunc

Resulting in output: Does this animal have fur?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have fur?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. [A furry South American mammal. We're making progress. Let's consider its diet.] Question: Is this animal primarily carnivorous?

Iteration 9

PyFunc

Resulting in output: Is this animal primarily carnivorous?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal primarily carnivorous?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [Not primarily carnivorous. This is narrowing things down. Let's explore some more specific physical traits.] Question: Does this animal have a long snout or nose?

Iteration 10

PyFunc

Resulting in output: Does this animal have a long snout or nose?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a long snout or nose?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

12. [No long snout. This is eliminating some possibilities. Let's consider its social behavior.] Question: Does this animal typically live in groups or herds?

Iteration 11

PyFunc

Resulting in output: Does this animal typically live in groups or herds?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal typically live in groups or herds?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

13. [Lives in groups, herbivorous or omnivorous, furry, larger than a house cat, native to South America. I'm starting to form some ideas, but need more information. Let's ask about a distinctive feature.] Question: Does this animal have a humped back?

Iteration 12

PyFunc

Resulting in output: Does this animal have a humped back?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a humped back?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. [No humped back. That eliminates some options. Let's consider its movement.] Question: Can this animal climb trees?

Iteration 13

PyFunc

Resulting in output: Can this animal climb trees?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Can this animal climb trees?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. [Not a tree climber. This is helpful. Let's ask about another potential distinctive feature.] Question: Does this animal have particularly large ears?

Iteration 14

PyFunc

Resulting in output: Does this animal have particularly large ears?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have particularly large ears?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

16. [No large ears. I'm starting to form a clearer picture, but want to be certain. Let's ask about its legs.] Question: Does this animal have relatively short legs compared to its body size?

Iteration 15

PyFunc

Resulting in output: Does this animal have relatively short legs compared to its body size?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have relatively short legs compared to its body size?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

17. [Not short-legged. This is very informative. Let's consider its coloration.] Question: Is this animal primarily brown in color?

Iteration 16

PyFunc

Resulting in output: Is this animal primarily brown in color?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal primarily brown in color?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

18. [Not primarily brown. This is quite revealing. I have a strong suspicion now, but I want to be absolutely certain. Let's ask about a very specific feature.] Question: Does this animal have a recognizable hump on its back, even if it's not as pronounced as a camel's?

Iteration 17

PyFunc

Resulting in output: Does this animal have a recognizable hump on its back, even if it's not as pronounced as a camel's?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a recognizable hump on its back, even if it's not as pronounced as a camel's?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

19. [No hump at all. I'm now quite confident, but I'll ask one more question to be absolutely sure.] Question: Does this animal have a wooly coat?

Iteration 18

PyFunc

Resulting in output: Does this animal have a wooly coat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a wooly coat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

20. [With all this information, I'm now confident enough to make my guess.] Question: Is the answer llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

Understood. I'll ask yes or no questions to try to guess the animal you're thinking of. I'll number my questions, provide any internal thoughts, and then ask the question. I won't make my final guess until I'm confident. Let's begin! 1. Let's start with a broad category to narrow down the possibilities. Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. That narrows it down significantly. Let's try to determine its habitat next. Question: Does this animal primarily live on land (as opposed to water or air)?

Iteration 1

PyFunc

Resulting in output: Does this animal primarily live on land (as opposed to water or air)?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal primarily live on land (as opposed to water or air)?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. Okay, we're dealing with a land-dwelling mammal. Let's consider size now. Question: Is this animal larger than a house cat?

Iteration 2

PyFunc

Resulting in output: Is this animal larger than a house cat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a house cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. Interesting. This helps eliminate many smaller mammals. Let's try to narrow down its characteristics further. Question: Does this animal have fur?

Iteration 3

PyFunc

Resulting in output: Does this animal have fur?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have fur?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

5. A furry, land-dwelling mammal larger than a house cat. Let's consider its diet. Question: Is this animal a carnivore?

Iteration 4

PyFunc

Resulting in output: Is this animal a carnivore?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a carnivore?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. Not a carnivore. This helps eliminate many predators. Let's explore its habitat more specifically. Question: Does this animal commonly live in forests or wooded areas?

Iteration 5

PyFunc

Resulting in output: Does this animal commonly live in forests or wooded areas?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal commonly live in forests or wooded areas?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. Not typically found in forests. This is intriguing. Let's consider other habitats. Question: Is this animal commonly found on farms or in agricultural settings?

Iteration 6

PyFunc

Resulting in output: Is this animal commonly found on farms or in agricultural settings?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly found on farms or in agricultural settings?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

8. A farm animal. This narrows it down considerably. Let's explore its uses. Question: Is this animal commonly raised for its meat?

Iteration 7

PyFunc

Resulting in output: Is this animal commonly raised for its meat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly raised for its meat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

9. Interesting. Not raised primarily for meat, but found on farms. Let's consider other common farm animals. Question: Is this animal known for producing milk?

Iteration 8

PyFunc

Resulting in output: Is this animal known for producing milk?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal known for producing milk?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. A milk-producing farm animal. We're getting close. Let's confirm a few more details. Question: Does this animal have hooves?

Iteration 9

PyFunc

Resulting in output: Does this animal have hooves?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have hooves?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

11. A hooved, milk-producing farm animal. I have a strong suspicion, but let's verify a few more characteristics to be certain. Question: Does this animal typically have horns?

Iteration 10

PyFunc

Resulting in output: Does this animal typically have horns?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal typically have horns?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

12. No horns. This is very telling. I'm quite confident now, but I'll ask one more question to be absolutely certain. Question: Is the answer a cow?

Iteration 11

PyFunc

Resulting in output: Is the answer a cow?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the answer a cow?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. I see. I apologize for my hasty conclusion. This is an unexpected turn. Let's reassess what we know and explore further. Question: Is this animal typically smaller than a cow?

Iteration 12

PyFunc

Resulting in output: Is this animal typically smaller than a cow?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal typically smaller than a cow?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. Interesting. Larger than or similar in size to a cow, but not a cow. This is quite puzzling. Let's consider other large farm animals. Question: Does this animal have a long neck?

Iteration 13

PyFunc

Resulting in output: Does this animal have a long neck?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a long neck?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

15. A long neck on a large, milk-producing farm animal. This is a very distinctive feature. I'm starting to form a new hypothesis, but I'll ask a couple more questions to be certain. Question: Is this animal known for spitting?

Iteration 14

PyFunc

Resulting in output: Is this animal known for spitting?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal known for spitting?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

16. A large, milk-producing farm animal with a long neck, known for spitting. I'm now quite confident, but I'll ask one final question to be absolutely sure. Question: Is this animal native to South America?

Iteration 15

PyFunc

Resulting in output: Is this animal native to South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

17. With all these characteristics combined - a large, milk-producing farm animal with a long neck, known for spitting, and native to South America - I'm now certain of the answer. Question: Is the answer a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

Understood! I'll ask yes or no questions to try and guess the animal you're thinking of. I'll number my questions, provide my internal thought process, and then ask the question. I won't make my final guess until I'm confident. Let's begin! 1. [Let's start with a broad category to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Great, that narrows it down significantly. Now let's determine if it's a common pet or a wild animal.] Question: Is this animal commonly kept as a pet?

Iteration 1

PyFunc

Resulting in output: Is this animal commonly kept as a pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly kept as a pet?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

3. [Interesting. So it's likely a wild mammal. Let's try to determine its size.] Question: Is this animal larger than a human?

Iteration 2

PyFunc

Resulting in output: Is this animal larger than a human?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a human?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [A large wild mammal. This could be a variety of animals. Let's narrow down the habitat.] Question: Does this animal primarily live on land (as opposed to water)?

Iteration 3

PyFunc

Resulting in output: Does this animal primarily live on land (as opposed to water)?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal primarily live on land (as opposed to water)?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

5. [A large land-dwelling wild mammal. Let's consider diet next.] Question: Is this animal a carnivore?

Iteration 4

PyFunc

Resulting in output: Is this animal a carnivore?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a carnivore?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. [Not a carnivore, so likely an herbivore or omnivore. Let's focus on physical characteristics.] Question: Does this animal have a long neck?

Iteration 5

PyFunc

Resulting in output: Does this animal have a long neck?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have a long neck?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

7. [A long-necked, large, land-dwelling herbivore or omnivore. This is narrowing down our options considerably. Let's confirm the continent.] Question: Is this animal native to Africa?

Iteration 6

PyFunc

Resulting in output: Is this animal native to Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. [Interesting. Not native to Africa, which rules out giraffes. Let's consider other continents.] Question: Is this animal native to South America?

Iteration 7

PyFunc

Resulting in output: Is this animal native to South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. [A large, long-necked herbivore or omnivore native to South America. This is becoming clearer. Let's confirm a key characteristic.] Question: Does this animal have woolly fur?

Iteration 8

PyFunc

Resulting in output: Does this animal have woolly fur?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have woolly fur?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. [A large, long-necked, woolly herbivore or omnivore from South America. This is sounding very specific. Let's confirm one more physical trait.] Question: Does this animal have padded feet?

Iteration 9

PyFunc

Resulting in output: Does this animal have padded feet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have padded feet?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [No padded feet, which aligns with our leading hypothesis. Let's confirm its relation to other animals.] Question: Is this animal related to camels?

Iteration 10

PyFunc

Resulting in output: Is this animal related to camels?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal related to camels?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

12. [At this point, I'm fairly certain of the answer, but I'll ask one more question to be absolutely sure.] Question: Is the animal I'm thinking of a llama?

PyFunc

Resulting in output: True