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

1. Starting broad to narrow down the possibilities. 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. Now to figure out if it's land-based, aquatic, or something else. Question: Does this mammal primarily live in water?

Iteration 1

PyFunc

Resulting in output: Does this mammal primarily live in water?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

3. A land mammal. Let's find out if it's domesticated or wild. Question: Is this mammal commonly found in the wild?

Iteration 2

PyFunc

Resulting in output: Is this mammal commonly found in the wild?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal commonly found in the wild? . 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 domesticated mammal. That narrows things down! Thinking about common domesticated mammals... Question: Is this mammal commonly kept as a pet?

Iteration 3

PyFunc

Resulting in output: Is this mammal 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 mammal 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. A domesticated mammal that isn't commonly kept as a pet... Could it be a farm animal? Question: Is this mammal used for agricultural purposes?

Iteration 4

PyFunc

Resulting in output: Is this mammal 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 mammal 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

6. An agricultural mammal... That gives me a good list to work with. To narrow it down further, Question: Is this mammal primarily raised for its meat?

Iteration 5

PyFunc

Resulting in output: Is this mammal 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 this mammal 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. Okay, so it's an agricultural mammal not primarily raised for meat. That makes me think of animals raised for other purposes, like dairy or labor. Question: Is this mammal used for its milk?

Iteration 6

PyFunc

Resulting in output: Is this mammal 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 mammal used for its milk? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

8. It's a mammal used for its milk and for agricultural purposes but not primarily for its meat... There's really only one answer that fits all of that. Question: Is the answer a cow?

Iteration 7

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

9. Hm, that's surprising! It fits the criteria so well. There must be another animal I'm not considering. Question: Is this animal primarily raised in North America?

Iteration 8

PyFunc

Resulting in output: Is this animal primarily raised 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 primarily raised 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

10. Not primarily raised in North America... Thinking about dairy animals found in other parts of the world... Question: Is this animal commonly found in mountainous regions?

Iteration 9

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

11. A dairy animal found in mountainous regions, not primarily in North America... This is getting interesting! It could be a goat or sheep, but there's another possibility... Question: Is this animal related to a camel?

Iteration 10

PyFunc

Resulting in output: Is this animal related to a camel?

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

12. It's related to a camel, found in mountainous regions, and provides milk! I think I've got it! Question: Is the answer a yak?

Iteration 11

PyFunc

Resulting in output: Is the answer a yak?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. Wow, not a yak! I was so sure. Let's see, it's a dairy animal, related to a camel, found in mountainous regions, but not a yak. That really narrows it down! Question: Is this animal primarily found in South America?

Iteration 12

PyFunc

Resulting in output: Is this animal primarily 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 primarily 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

14. South America, related to a camel, dairy animal... I think there's only one possibility! 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

1. Okay, let's start broad. 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. Alright, so it's a mammal. Let's narrow it down further. Question: Is it a domesticated animal?

Iteration 1

PyFunc

Resulting in output: Is it a domesticated animal?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. Interesting. So we're talking about a common household pet or farm animal. Question: Is it commonly kept as a pet?

Iteration 2

PyFunc

Resulting in output: Is it 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 it 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. Okay, so it's a domesticated mammal, but not usually a pet. That makes me think of animals used for work or food. Question: Is this animal primarily used for its milk?

Iteration 3

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

5. So it's a domesticated mammal, not usually a pet, and not primarily used for milk. That narrows it down a bit. Question: Is this animal used for its wool or fur?

Iteration 4

PyFunc

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

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. Okay, so it's a domesticated mammal used for its wool or fur. That brings a few animals to mind. Question: Is this animal a sheep?

Iteration 5

PyFunc

Resulting in output: Is this animal 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 a sheep? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. Alright, it's not a sheep, but it's domesticated and used for its wool or fur. Question: Is this animal a type of goat?

Iteration 6

PyFunc

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

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. Hmm, not a sheep or a goat, but still domesticated and prized for its wool or fur. Question: Is this animal an alpaca?

Iteration 7

PyFunc

Resulting in output: Is this animal an alpaca?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this 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

9. Okay, so we're looking for a domesticated mammal, not a pet, used for wool or fur, and it's not a sheep, goat, or alpaca. This is getting tricky! Question: Is this animal a rabbit?

Iteration 8

PyFunc

Resulting in output: Is this animal a rabbit?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this 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

10. This is a tough one! Let's see, it's a domesticated mammal, not a pet, used for wool or fur, and it's not a sheep, goat, alpaca, or rabbit. Question: Is this animal larger than a breadbox?

Iteration 9

PyFunc

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

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

11. Larger than a breadbox... so it's a fairly sizable animal. It's not a pet, but it's used for its wool or fur. That really narrows down the options. Question: Is this 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

1. Okay, let's start broad. Question: Is it a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is it a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is it 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. Lots of possibilities still. Question: Does it live in the water?

Iteration 1

PyFunc

Resulting in output: Does it live in the water?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

3. Okay, so a land mammal. Question: Is it commonly found in the wild in North America?

Iteration 2

PyFunc

Resulting in output: Is it 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 it 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

4. Interesting. That narrows it down. Question: Is it a domesticated animal?

Iteration 3

PyFunc

Resulting in output: Is it a domesticated animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is it a domesticated animal? . 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 not commonly found in North America... Question: Is it a cat?

Iteration 4

PyFunc

Resulting in output: Is it a cat?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. Hmm, okay. Thinking about other common domesticated animals... Question: Is it a type of farm animal?

Iteration 5

PyFunc

Resulting in output: Is it a type of farm animal?

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

7. A farm animal not commonly found in North America... could it be something typically raised for wool or milk in other parts of the world? Question: Is it a sheep?

Iteration 6

PyFunc

Resulting in output: Is it a sheep?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. Okay, so not a sheep. Let's see... other farm animals not commonly found in North America... Question: Is it used for transportation?

Iteration 7

PyFunc

Resulting in output: Is it used for transportation?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. A farm animal, used for transportation, not commonly found in North America... This is getting interesting! Question: Is it a camel?

Iteration 8

PyFunc

Resulting in output: Is it a camel?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is it a camel? . 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 camel, but used for transportation... Let's try to narrow down the continent. Question: Is this animal commonly found in Asia?

Iteration 9

PyFunc

Resulting in output: Is this animal commonly 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 commonly 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

11. Not Asia... That's helpful. So, a domesticated, farm animal, used for transportation, not commonly found in North America or Asia... Question: Is this animal commonly found in South America?

Iteration 10

PyFunc

Resulting in output: Is this animal commonly 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 commonly 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

12. South America, used for transportation... this could be a species-specific question, but worth a shot... Question: Is it an alpaca?

Iteration 11

PyFunc

Resulting in output: Is it an alpaca?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. Alright, not an alpaca. Still thinking about South American domesticated animals used for transportation... Question: Is this animal typically larger than a dog?

Iteration 12

PyFunc

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

14. Larger than a dog, South American, farm animal, used for transportation... I'm starting to get an idea... Question: Is this animal known for carrying heavy loads?

Iteration 13

PyFunc

Resulting in output: Is this animal known for carrying heavy loads?

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

15. Okay, getting close now! A South American animal, used for transportation and carrying heavy loads... Question: Is it 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

1. Okay, let's start broad. 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. A mammal, alright. Is it domesticated?

Iteration 1

PyFunc

Resulting in output: 2. A mammal, alright. Is it domesticated?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 2. A mammal, alright. Is it domesticated? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. Okay, a domesticated mammal. Could it be found commonly on a farm? Question: Could it be found commonly on a farm?

Iteration 2

PyFunc

Resulting in output: Could it be found commonly on a farm?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Could it be found commonly on a farm? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

4. Interesting. So, a domesticated mammal, not found on a farm. That narrows it down. Is it a pet? Question: Is it a pet?

Iteration 3

PyFunc

Resulting in output: Is it a pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is it 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. Hmmm, a domesticated mammal that is not a pet nor found on a farm. Is it used for work or transportation? Question: Is it used for work or transportation?

Iteration 4

PyFunc

Resulting in output: Is it used for work or transportation?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. Used for work or transportation... Is it typically ridden by humans? Question: Is it typically ridden by humans?

Iteration 5

PyFunc

Resulting in output: Is it typically ridden by humans?

LLM Generation

Query

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

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. Okay, a domesticated mammal, used for work or transportation, but not typically ridden. Could it be a pack animal, like a llama? Question: Is it a pack animal?

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

1. Okay, let's start broad. Question: Is it a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is it a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is it 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. Lots of mammals out there... Is it domesticated?

Iteration 1

PyFunc

Resulting in output: 2. Lots of mammals out there... Is it domesticated?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 2. Lots of mammals out there... Is it domesticated? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. Okay, so a common pet... Is it commonly found in homes as a pet?

Iteration 2

PyFunc

Resulting in output: 3. Okay, so a common pet... Is it commonly found in homes as a pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 3. Okay, so a common pet... Is it commonly found in homes 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... Is it a working animal?

Iteration 3

PyFunc

Resulting in output: 4. Interesting... Is it a working animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 4. Interesting... Is it a working animal? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

5. A working mammal that is domesticated but not commonly found in homes... Is it a horse?

Iteration 4

PyFunc

Resulting in output: 5. A working mammal that is domesticated but not commonly found in homes... Is it a horse?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 5. A working mammal that is domesticated but not commonly found in homes... Is it a horse? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. Hmm... still a lot of possibilities. Does this animal typically live on a farm?

Iteration 5

PyFunc

Resulting in output: 6. Hmm... still a lot of possibilities. Does this animal typically live on a farm?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 6. Hmm... still a lot of possibilities. Does this animal typically live on a farm? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

7. Okay, a farm animal that works... Is it used for its milk?

Iteration 6

PyFunc

Resulting in output: 7. Okay, a farm animal that works... Is it used for its milk?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 7. Okay, a farm animal that works... Is it 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. Alright, not a dairy animal. Is it used for its meat?

Iteration 7

PyFunc

Resulting in output: 8. Alright, not a dairy animal. Is it used for its meat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 8. Alright, not a dairy animal. Is it used for its meat? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. So a farm animal, used for its meat, and a working animal... Is it a pig?

Iteration 8

PyFunc

Resulting in output: 9. So a farm animal, used for its meat, and a working animal... Is it a pig?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 9. So a farm animal, used for its meat, and a working animal... Is it a pig? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

10. Okay, not a pig. Is this animal typically used for transportation or hauling?

Iteration 9

PyFunc

Resulting in output: 10. Okay, not a pig. Is this animal typically used for transportation or hauling?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 10. Okay, not a pig. Is this animal typically used for transportation or hauling? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

11. A farm animal, used for meat, and transportation/hauling... Is it a donkey?

Iteration 10

PyFunc

Resulting in output: 11. A farm animal, used for meat, and transportation/hauling... Is it a donkey?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 11. A farm animal, used for meat, and transportation/hauling... Is it a donkey? . 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 donkey, but similar line of work. Is this animal larger than a donkey?

Iteration 11

PyFunc

Resulting in output: 12. Not a donkey, but similar line of work. Is this animal larger than a donkey?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 12. Not a donkey, but similar line of work. Is this animal larger than a donkey? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

13. Larger than a donkey, used for meat, transportation, and hauling on a farm... Is it an ox?

Iteration 12

PyFunc

Resulting in output: 13. Larger than a donkey, used for meat, transportation, and hauling on a farm... Is it an ox?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 13. Larger than a donkey, used for meat, transportation, and hauling on a farm... Is it an ox? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. Hmm, this is tricky. It's not an ox, but shares a lot of similarities. Is this animal known for its strength?

Iteration 13

PyFunc

Resulting in output: 14. Hmm, this is tricky. It's not an ox, but shares a lot of similarities. Is this animal known for its strength?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 14. Hmm, this is tricky. It's not an ox, but shares a lot of similarities. Is this animal known for its strength? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. Not known for its strength... Is this animal known for its speed or agility?

Iteration 14

PyFunc

Resulting in output: 15. Not known for its strength... Is this animal known for its speed or agility?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 15. Not known for its strength... Is this animal known for its speed or agility? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

16. Okay, so not particularly strong, fast, or agile, but used for transportation and meat on a farm... Is this animal a sheep?

Iteration 15

PyFunc

Resulting in output: 16. Okay, so not particularly strong, fast, or agile, but used for transportation and meat on a farm... Is this animal a sheep?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 16. Okay, so not particularly strong, fast, or agile, but used for transportation and meat on a farm... Is this 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

17. Not a sheep... This is a tough one! Is this animal typically used for riding?

Iteration 16

PyFunc

Resulting in output: 17. Not a sheep... This is a tough one! Is this animal typically used for riding?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 17. Not a sheep... This is a tough one! Is this animal typically used for riding? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

18. Not for riding... Is this animal known for its wool or hair?

Iteration 17

PyFunc

Resulting in output: 18. Not for riding... Is this animal known for its wool or hair?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 18. Not for riding... Is this animal known for its wool or hair? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

19. So it's a farm animal, used for its meat, not known for strength, speed, or agility, but IS known for its wool/hair and is used for hauling... Is it an alpaca?

Iteration 18

PyFunc

Resulting in output: 19. So it's a farm animal, used for its meat, not known for strength, speed, or agility, but IS known for its wool/hair and is used for hauling... Is it an alpaca?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 19. So it's a farm animal, used for its meat, not known for strength, speed, or agility, but IS known for its wool/hair and is used for hauling... Is it an alpaca? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

20. This is so hard! Let's see... it's a domesticated, working farm animal, used for meat, hauling, and its wool/hair, but not known for strength, speed, agility, or riding... Is it a goat?

Iteration 19

PyFunc

Resulting in output: 20. This is so hard! Let's see... it's a domesticated, working farm animal, used for meat, hauling, and its wool/hair, but not known for strength, speed, agility, or riding... Is it a goat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: 20. This is so hard! Let's see... it's a domesticated, working farm animal, used for meat, hauling, and its wool/hair, but not known for strength, speed, agility, or riding... Is it a goat? . Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

You got me! Tell me, what animal were you thinking of? I'm very curious!

PyFunc

Resulting in output: False