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

Sounds fun! Let's get started. 1. [First, let's narrow down the type of animal] Question: Is the animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is the animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the 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 quite a bit. Let's see if it's a wild or domestic animal] Question: Is the animal commonly kept as a pet?

Iteration 1

PyFunc

Resulting in output: Is the 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 the 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. [Alright, so it's a wild mammal. Let's narrow down the habitat] Question: Does the animal primarily live on land?

Iteration 2

PyFunc

Resulting in output: Does the animal primarily live on land?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [So it's a land-dwelling wild mammal. Let's consider the size] Question: Is the animal larger than a human?

Iteration 3

PyFunc

Resulting in output: Is the 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 the animal larger than a human?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [A wild, land-dwelling mammal smaller than a human. Let's think about its diet] Question: Is the animal a carnivore?

Iteration 4

PyFunc

Resulting in output: Is the animal a carnivore?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the 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. [So it's a herbivore or omnivore. Let's narrow down the diet further] Question: Is the animal a herbivore?

Iteration 5

PyFunc

Resulting in output: Is the animal a herbivore?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

7. [A wild, land-dwelling, herbivorous mammal smaller than a human. Let's consider its habitat more specifically] Question: Does the animal primarily live in forests?

Iteration 6

PyFunc

Resulting in output: Does the animal primarily live in forests?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does the animal primarily live in forests?. 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 forest dweller. Let's consider other possible habitats] Question: Does the animal primarily live in grasslands or savannas?

Iteration 7

PyFunc

Resulting in output: Does the animal primarily live in grasslands or savannas?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

9. [A herbivorous mammal smaller than a human that lives in grasslands or savannas. Let's think about its physical characteristics] Question: Does the animal have hooves?

Iteration 8

PyFunc

Resulting in output: Does the animal have hooves?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does the 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. [A herbivorous, hoofed mammal smaller than a human that lives in grasslands or savannas. This narrows it down quite a bit. Let's consider more features] Question: Does the animal have horns or antlers?

Iteration 9

PyFunc

Resulting in output: Does the animal have horns or antlers?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

11. [A herbivorous, hoofed mammal smaller than a human that lives in grasslands or savannas without horns or antlers. This excludes species like antelopes or deer. Let's think about some specific possibilities] Question: Is the animal known for having long ears?

Iteration 10

PyFunc

Resulting in output: Is the animal known for having long ears?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the animal known for having long ears?. 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 ears, which might rule out animals like hares. Let's consider another distinctive feature] Question: Does the animal have a mane or a prominent feature on its neck?

Iteration 11

PyFunc

Resulting in output: Does the animal have a mane or a prominent feature on its neck?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. [No mane or prominent neck feature. That makes it less likely to be something like a small horse or donkey. Let's think about common hoofed herbivores in grasslands] Question: Is the animal commonly found in Africa?

Iteration 12

PyFunc

Resulting in output: Is the animal commonly found in Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the animal commonly found in 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 commonly found in Africa. This might rule out many savanna animals. Let's think of other grassland environments] Question: Is the animal native to North America?

Iteration 13

PyFunc

Resulting in output: Is the animal native to North America?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. [Not native to North America either. Let's consider other continents with significant grassland regions] Question: Is the animal native to Asia?

Iteration 14

PyFunc

Resulting in output: Is the 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 the 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

16. [Not native to Asia. That leaves us with fewer options. Let's think about other regions with grasslands] Question: Is the animal native to South America?

Iteration 15

PyFunc

Resulting in output: Is the 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 the 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. [A herbivorous, hoofed mammal native to South American grasslands. This could be a llama, alpaca, or something similar. Let's narrow it down further] Question: Is the animal a type of camelid?

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

Sounds like fun! Let's get started. 1. [First, let's narrow down the habitat.] Question: Does this animal primarily live on land?

Looping until done

Iteration 0

PyFunc

Resulting in output: Does this animal primarily live on land?

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? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

2. [Alright, so it's a land animal. Next, let's figure out if it's a mammal, bird, reptile, or something else.] Question: Is this animal a mammal?

Iteration 1

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

3. [Great, it's a mammal. Now let's narrow down the 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

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

4. [So, it's a smaller mammal. Let's figure out more about its lifestyle.] Question: Is this animal commonly kept as a pet?

Iteration 3

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

5. [Not a common pet. That eliminates cats, dogs, and some small mammals like hamsters. Let's consider its diet.] Question: Is this animal primarily herbivorous?

Iteration 4

PyFunc

Resulting in output: Is this animal primarily herbivorous?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. [A small herbivorous mammal that isn't commonly kept as a pet. Let's narrow down its habitat further.] Question: Does this animal live in forests?

Iteration 5

PyFunc

Resulting in output: Does this animal live in forests?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

7. [Not a forest-dweller. Let's consider other habitats.] Question: Does this animal live in grasslands or savannas?

Iteration 6

PyFunc

Resulting in output: Does this animal live in grasslands or savannas?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

8. [A small herbivorous mammal that lives in grasslands or savannas. Let's think about its social behavior.] Question: Does this animal live in groups or herds?

Iteration 7

PyFunc

Resulting in output: Does this animal 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 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

9. [A small, herbivorous, social mammal in grasslands or savannas. Let's get more specific about its appearance.] Question: Does this animal have long ears?

Iteration 8

PyFunc

Resulting in output: Does this animal have long 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 long ears?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

10. [No long ears, so it's not a rabbit or a hare. Let's think about its physical characteristics.] Question: Does this animal have a long tail?

Iteration 9

PyFunc

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

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 tail?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

11. [No long tail. This makes me think of certain rodents or small hoofed animals. Let's try to narrow it down more.] Question: Is this animal known for burrowing or digging?

Iteration 10

PyFunc

Resulting in output: Is this animal known for burrowing or digging?

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 burrowing or digging?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

12. [Not a burrower. This makes me think of some small hoofed mammals or certain rodents that live above ground.] Question: Does this animal have hooves?

Iteration 11

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

13. [A small, hoofed, herbivorous, social mammal in grasslands or savannas. This is getting clearer.] Question: Is this animal a type of antelope?

Iteration 12

PyFunc

Resulting in output: Is this animal a type of antelope?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

14. [Not an antelope. Let's think of other small, hoofed animals in grasslands.] Question: Is this animal a type of rodent?

Iteration 13

PyFunc

Resulting in output: Is this animal a type of rodent?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a type of rodent?. 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 rodent, and we've established it's not an antelope. Let's consider other possibilities.] Question: Is this animal commonly known for having a distinctive coat pattern, like stripes or spots?

Iteration 14

PyFunc

Resulting in output: Is this animal commonly known for having a distinctive coat pattern, like stripes or spots?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly known for having a distinctive coat pattern, like stripes or spots?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

16. [No distinctive coat pattern, so that rules out some animals like zebras.] Question: Does this animal have horns or antlers?

Iteration 15

PyFunc

Resulting in output: Does this animal have horns or antlers?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

17. [No horns or antlers. Considering the options, it could be a smaller ungulate without these features.] Question: Is this animal native to Africa?

Iteration 16

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

18. [Not native to Africa, so it could be from another continent with grasslands.] Question: Is this animal native to North America?

Iteration 17

PyFunc

Resulting in output: Is this animal native to 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 native to North America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

19. [Not native to North America either. Let's consider other continents with grasslands, like Asia or Australia.] Question: Is this animal native to Australia?

Iteration 18

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

20. [Not native to Australia either. Given the remaining possibilities, it could be from Asia or South America.] Question: Is the animal a deer?

Iteration 19

PyFunc

Resulting in output: Is the animal a deer?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

It looks like I didn't guess correctly within 20 questions. The animal you were thinking of must be quite unique! What was the animal?

PyFunc

Resulting in output: False

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

Sounds like fun! Let's get started. 1. [I need to narrow down the type of animal first.] Question: Is the animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is the animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the 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, it's a mammal. Let's narrow it down further.] Question: Is the animal domesticated?

Iteration 1

PyFunc

Resulting in output: Is the animal domesticated?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

3. [It's a domesticated mammal. That narrows it down quite a bit. Let's see if it's a common pet.] Question: Is the animal commonly kept as a pet?

Iteration 2

PyFunc

Resulting in output: Is the 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 the 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

4. [Not a common pet, but domesticated. Could be a farm animal or something less typical.] Question: Is the animal primarily used for agricultural purposes?

Iteration 3

PyFunc

Resulting in output: Is the animal primarily used for agricultural purposes?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

5. [A domesticated mammal used primarily for agriculture. Let's figure out its general size.] Question: Is the animal larger than a typical human?

Iteration 4

PyFunc

Resulting in output: Is the animal larger than a typical human?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

6. [A domesticated agricultural mammal smaller than a human. This narrows it down quite a lot.] Question: Is the animal primarily raised for its meat?

Iteration 5

PyFunc

Resulting in output: Is the animal primarily 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 the animal primarily 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

7. [Not primarily raised for meat. Maybe it's raised for another product like milk, wool, or labor.] Question: Is the animal primarily raised for its milk?

Iteration 6

PyFunc

Resulting in output: Is the animal primarily raised for its milk?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. [Not raised for meat or milk. Perhaps wool or some other product.] Question: Is the animal primarily raised for its wool or fiber?

Iteration 7

PyFunc

Resulting in output: Is the animal primarily raised for its wool or fiber?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

9. [A domesticated, agricultural mammal smaller than a human, raised primarily for its wool or fiber. This is quite specific.] Question: Is the animal a sheep?

Iteration 8

PyFunc

Resulting in output: Is the animal a sheep?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

10. [Not a sheep, but still raised for its wool or fiber. There are a few other possibilities.] Question: Is the animal an alpaca?

Iteration 9

PyFunc

Resulting in output: Is the animal an alpaca?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

11. [Not a sheep or an alpaca, but still a wool or fiber-producing animal. Let's think about other possibilities.] Question: Is the animal a goat?

Iteration 10

PyFunc

Resulting in output: Is the animal a goat?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

12. [Not a sheep, alpaca, or goat. Another fiber-producing animal, smaller than a human.] Question: Is the animal a rabbit?

Iteration 11

PyFunc

Resulting in output: Is the animal a rabbit?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. [Not a sheep, alpaca, goat, or rabbit. This is tricky. What other fiber-producing animals are there?] Question: Is it a type of camelid?

Iteration 12

PyFunc

Resulting in output: Is it a type of camelid?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

14. [It's a type of camelid, but not an alpaca. There are only a few other options.] Question: Is the animal 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

Great, let's get started! Here we go. 1. Hmm, let's start broad to narrow it down. Question: Is the animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is the animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is the 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. Okay, it's a mammal. Let's narrow it down further. Question: Is the animal domesticated?

Iteration 1

PyFunc

Resulting in output: Is the animal domesticated?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

3. Alright, it's a domesticated mammal. Let's see if it's commonly kept as a pet. Question: Is this animal commonly kept as a pet?

Iteration 2

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

4. Interesting, a domesticated mammal that is not commonly kept as a pet. Let's consider livestock or working animals. Question: Is this animal typically used for agricultural purposes?

Iteration 3

PyFunc

Resulting in output: Is this animal typically used for agricultural purposes?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

5. Great, it's a domesticated mammal used in agriculture. Let's narrow it down further by considering its size. Question: Is this animal larger than a sheep?

Iteration 4

PyFunc

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

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 sheep?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

6. Alright, it's larger than a sheep. Let's think about common large agricultural animals. Question: Is this animal used primarily for its meat?

Iteration 5

PyFunc

Resulting in output: Is this animal used primarily 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 used primarily 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

7. Not primarily for its meat. That suggests it might be used for milk, wool, or labor. Question: Is this animal primarily used for its milk?

Iteration 6

PyFunc

Resulting in output: Is this animal primarily used for its milk?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. Not for its meat or milk. That leaves labor or possibly wool/hide. Question: Is this animal primarily used for labor?

Iteration 7

PyFunc

Resulting in output: Is this animal primarily used for labor?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

9. Alright, so it's not primarily used for meat, milk, or labor. That suggests it's probably used for something else like wool or other products. Question: Is this animal primarily used for its wool or hide?

Iteration 8

PyFunc

Resulting in output: Is this animal primarily used for its wool or hide?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

10. Okay, it's used for its wool or hide. Let's narrow down which one. Question: Is this animal primarily used for its wool?

Iteration 9

PyFunc

Resulting in output: Is this animal primarily used for its wool?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

11. A large domesticated mammal used for its wool. This is pointing towards a specific animal. Question: Is the answer an alpaca?

Iteration 10

PyFunc

Resulting in output: Is the answer an alpaca?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

12. Alright, not an alpaca. Another large domesticated wool-producing animal. 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

Great! Let's get started. 1. I should narrow it down by habitat first. Question: Does this animal live primarily on land?

Looping until done

Iteration 0

PyFunc

Resulting in output: Does this animal live primarily on land?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

2. Since it's a land animal, I'll narrow it down further by size. Question: Is this animal larger than a human?

Iteration 1

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

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

3. It's smaller than a human, so I'll consider its diet next. Question: Is this animal a carnivore?

Iteration 2

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

4. It's not a carnivore; it could be an herbivore or an omnivore. Question: Is this animal an herbivore?

Iteration 3

PyFunc

Resulting in output: Is this animal an herbivore?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

5. Since it's an herbivore, I'll think about its general characteristics. Question: Does this animal primarily have fur or hair?

Iteration 4

PyFunc

Resulting in output: Does this animal primarily have fur or hair?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

6. It's a furry or hairy herbivore. Let's consider where it might be found. Question: Is this animal commonly found in the wild in North America?

Iteration 5

PyFunc

Resulting in output: Is this animal commonly found in the wild 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 commonly found in the wild 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. It's not commonly found in North America. Let's consider its activity pattern. Question: Is this animal primarily active during the day (diurnal)?

Iteration 6

PyFunc

Resulting in output: Is this animal primarily active during the day (diurnal)?

LLM Generation

Query

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

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

8. A diurnal, furry herbivore not commonly found in North America. Let's think about its group behavior. Question: Does this animal typically live in groups?

Iteration 7

PyFunc

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

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?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. It lives in groups. I'll narrow it down by its general appearance and features. Question: Does this animal have a long tail?

Iteration 8

PyFunc

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

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 tail?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

10. No long tail. Let's think about its size and specific features. Question: Is this animal smaller than a cat?

Iteration 9

PyFunc

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

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 cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

11. It's between the size of a cat and a human. Let's think about its specific type. Question: Is this animal a type of rodent?

Iteration 10

PyFunc

Resulting in output: Is this animal a type of rodent?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

12. It's not a rodent. Let's consider other types of herbivores. Question: Is this animal commonly kept as a pet?

Iteration 11

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

13. Not commonly kept as a pet. Let's think about its habitat again. Question: Is this animal typically found in forests?

Iteration 12

PyFunc

Resulting in output: Is this animal typically found in forests?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

14. Not found in forests. Let's consider other environments. Question: Is this animal typically found in grasslands or savannas?

Iteration 13

PyFunc

Resulting in output: Is this animal typically found in grasslands or savannas?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

15. It's not found in forests, grasslands, or savannas. Let's consider more environments. Question: Is this animal commonly found in mountainous regions?

Iteration 14

PyFunc

Resulting in output: Is this animal commonly found in mountainous regions?

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 in mountainous regions?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

16. A diurnal, furry herbivore that lives in mountainous regions and is not found in North America. Let’s think about specific animals that fit this profile. Question: Is this animal known for its climbing abilities?

Iteration 15

PyFunc

Resulting in output: Is this animal known for its climbing abilities?

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 climbing abilities?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

17. Not known for its climbing abilities. Let's think about other characteristics. Question: Is this animal known for its strong jumping abilities?

Iteration 16

PyFunc

Resulting in output: Is this animal known for its strong jumping abilities?

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 strong jumping abilities?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

18. Not known for jumping. Let's think about its physical characteristics. Question: Does this animal have horns or antlers?

Iteration 17

PyFunc

Resulting in output: Does this animal have horns or antlers?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

19. No horns or antlers. Let's consider another unique feature. Question: Is this animal known for its wool or fur being used by humans?

Iteration 18

PyFunc

Resulting in output: Is this animal known for its wool or fur being used by humans?

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 wool or fur being used by humans?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

20. An herbivorous, furry animal found in mountainous regions, known for its wool, and not in North America. Question: Is the answer an alpaca?

Iteration 19

PyFunc

Resulting in output: Is the answer an alpaca?

LLM Generation

Query

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

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

It seems like I didn't get it this time. What was the animal you were thinking of?

PyFunc

Resulting in output: False