# 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)