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import openai | |
import os | |
from dotenv import load_dotenv | |
load_dotenv() | |
openai.api_key = os.getenv("API_KEY") | |
#Takes in a sentence and returns a list of dicts consisiting of key-value pairs of masked words and lists of the possible replacements | |
def predict_masked_words(sentence, n_suggestions=5): | |
prompt = ( | |
f"Given a sentence with masked words, masked word can be one or more than one, indicated by [MASK], generate {n_suggestions} possible words to fill each mask. " | |
"Return the results as a list of dictionaries, where each dictionary key is a masked word and its value is a list of 5 potential words to fill that mask.\n\n" | |
"Example input: \"The [MASK] fox [MASK] over the [MASK] dog.\"\n\n" | |
"Example output:\n" | |
"[\n" | |
" {\n" | |
" \"[MASK]1\": [\"quick\", \"sly\", \"red\", \"clever\", \"sneaky\"]\n" | |
" },\n" | |
" {\n" | |
" \"[MASK]2\": [\"jumped\", \"leaped\", \"hopped\", \"sprang\", \"bounded\"]\n" | |
" },\n" | |
" {\n" | |
" \"[MASK]3\": [\"lazy\", \"sleeping\", \"brown\", \"tired\", \"old\"]\n" | |
" }\n" | |
"]\n\n" | |
"Example input: \"The [MASK] [MASK] ran swiftly across the [MASK] field.\"\n\n" | |
"Example output:\n" | |
"[\n" | |
" {\n" | |
" \"[MASK]1\": [\"tall\", \"fierce\", \"young\", \"old\", \"beautiful\"]\n" | |
" },\n" | |
" {\n" | |
" \"[MASK]2\": [\"lion\", \"tiger\", \"horse\", \"cheetah\", \"deer\"]\n" | |
" },\n" | |
" {\n" | |
" \"[MASK]3\": [\"green\", \"wide\", \"sunny\", \"open\", \"empty\"]\n" | |
" }\n" | |
"]\n\n" | |
"Example input: \"It was a [MASK] day when the train arrived at the station.\"\n\n" | |
"Example output:\n" | |
"[\n" | |
" {\n" | |
" \"[MASK]1\": [\"sunny\", \"rainy\", \"cloudy\", \"foggy\", \"stormy\"]\n" | |
" },\n" | |
"]\n\n" | |
"Now, please process the following sentence:\n" | |
f"{sentence}" | |
) | |
response = openai.ChatCompletion.create( | |
model="gpt-3.5-turbo", | |
messages=[ | |
{"role": "system", "content": "You are a helpful assistant."}, | |
{"role": "user", "content": prompt} | |
], | |
max_tokens=100, | |
n=1, | |
stop=None, | |
temperature=0.7 | |
) | |
print(response['choices'][0]['message']['content']) | |
# sentence = "Evacuations and storm [MASK] began on Sunday night as forecasters projected that Hurricane Dorian would hit into Florida’s west coast on Wednesday as a major hurricane packing life-threatening winds and storm surge." | |
# predict_masked_words(sentence, n_suggestions=5) |