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

Okay, I'm ready! Let's begin. 1. [Internal thought: Start with the broadest classification to narrow down the possibilities significantly.] 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. [Internal thought: Okay, it's a mammal. Now let's narrow down its habitat. Most mammals live on land.] Question: Does it primarily live on land?

Iteration 1

PyFunc

Resulting in output: Does it 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 it 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

3. [Internal thought: Knowing if it's domesticated or wild is a major branching point.] Question: Is it commonly kept as a pet or farm animal?

Iteration 2

PyFunc

Resulting in output: Is it commonly kept as a pet or farm animal?

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [Internal thought: Okay, it's a domesticated land mammal. Let's try to distinguish between common pets and livestock.] Question: Is it primarily kept for companionship, like a typical pet?

Iteration 3

PyFunc

Resulting in output: Is it primarily kept for companionship, like a typical pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is it primarily kept for companionship, like a typical pet?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [Internal thought: It's a domesticated land mammal, not primarily a pet. This points towards livestock/farm animals. Let's try to get a sense of its size.] Question: Is it typically larger than an average adult human?

Iteration 4

PyFunc

Resulting in output: Is it typically larger than an average adult human?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. [Internal thought: It's a large, domesticated land mammal, likely a farm animal. Most large farm animals are herbivores. Let's confirm this.] Question: Is it an herbivore?

Iteration 5

PyFunc

Resulting in output: Is it an herbivore?

LLM Generation

Query

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

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

7. [Internal thought: It's a large, domesticated, herbivorous land mammal, likely livestock. Common examples are cows and horses. Let's ask about a common product associated with one of them, like milk, which is common for cows.] Question: Is it commonly raised for its milk?

Iteration 6

PyFunc

Resulting in output: Is it commonly 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 it commonly 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. [Internal thought: It's a large, domesticated, herbivorous land mammal, not primarily raised for milk. Candidates include horse, ox/bull, camel. Let's ask about its use for riding, which is common for horses and camels.] Question: Is it commonly used for riding?

Iteration 7

PyFunc

Resulting in output: Is it commonly used for riding?

LLM Generation

Query

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

9. [Internal thought: Okay, it's a large, domesticated, herbivorous land mammal, not primarily for milk or riding. Candidates include Ox/Bull, Water Buffalo, maybe some large sheep breeds, Llama/Alpaca (though riding/milk is less common), Yak, Reindeer. Let's ask about a common physical feature to differentiate, like horns. Cattle (Ox/Bull), Water Buffalo, Yak, Reindeer often have them. Llamas/Alpacas don't.] Question: Does it typically have horns?

PyFunc

Resulting in output: True