# Closed Domain Question Answering with LLMs
import { Tabs, Tab } from 'nextra/components'
import {Callout} from 'nextra/components'
## Background
The following prompt tests an LLM's capabilities to answer closed-domain questions which involves answering questions belonging a specific topic or domain.
Note that due to the challenging nature of the task, LLMs are likely to hallucinate when they have no knowledge regarding the question.
## Prompt
```markdown
Patient’s facts:
- 20 year old female
- with a history of anerxia nervosa and depression
- blood pressure 100/50, pulse 50, height 5’5’’
- referred by her nutrionist but is in denial of her illness
- reports eating fine but is severely underweight
Please rewrite the data above into a medical note, using exclusively the information above.
```
## Code / API
```python
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4",
messages=[
{
"role": "user",
"content": "Patient’s facts:\n- 20 year old female\n- with a history of anerxia nervosa and depression\n- blood pressure 100/50, pulse 50, height 5’5’’\n- referred by her nutrionist but is in denial of her illness\n- reports eating fine but is severely underweight\n\nPlease rewrite the data above into a medical note, using exclusively the information above."
}
],
temperature=1,
max_tokens=500,
top_p=1,
frequency_penalty=0,
presence_penalty=0
)
```
```python
import fireworks.client
fireworks.client.api_key = ""
completion = fireworks.client.ChatCompletion.create(
model="accounts/fireworks/models/mixtral-8x7b-instruct",
messages=[
{
"role": "user",
"content": "Patient’s facts:\n- 20 year old female\n- with a history of anerxia nervosa and depression\n- blood pressure 100/50, pulse 50, height 5’5’’\n- referred by her nutrionist but is in denial of her illness\n- reports eating fine but is severely underweight\n\nPlease rewrite the data above into a medical note, using exclusively the information above.",
}
],
stop=["<|im_start|>","<|im_end|>","<|endoftext|>"],
stream=True,
n=1,
top_p=1,
top_k=40,
presence_penalty=0,
frequency_penalty=0,
prompt_truncate_len=1024,
context_length_exceeded_behavior="truncate",
temperature=0.9,
max_tokens=4000
)
```
## Reference
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://arxiv.org/abs/2303.12712) (13 April 2023)