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import openai
import backoff
import json
import re
def initOpenAI(key):
openai.api_key = key
# list models
models = openai.Model.list()
return models
# construct prompts from example_shots
def examples_to_prompt(example_shots, kwd_pair):
prompt = ""
for shot in example_shots:
prompt += "Keywords: "+', '.join(shot['Keywords'])+" ## Sentence: "+ \
shot['Sentence']+" ##\n"
prompt += f"Keywords: {kwd_pair[0]}, {kwd_pair[1]} ## Sentence: "
return prompt
def genChatGPT(model_name, kwd_pair, num2gen, numTries, example_shots, temperature=0.8):
# construct prompt
instruction = f"Write a sentence including terms \"{kwd_pair[0]}\" and \"{kwd_pair[1]}\"."# Use examples as guide for the type of sentences to write."
#prompt = examples_to_prompt(example_shots, kwd_pair)
#print(f"Prompt: {prompt}")
#print(f"Instruction: {instruction}")
# https://github.com/openai/openai-cookbook/blob/main/examples/How_to_handle_rate_limits.ipynb
@backoff.on_exception(backoff.expo, (openai.error.RateLimitError,
openai.error.APIError,
openai.error.ServiceUnavailableError,
ConnectionResetError,
json.decoder.JSONDecodeError))#,
#max_time=300,
#raise_on_giveup=False,
#giveup=fatal_code)
def completions_with_backoff(**kwargs):
return openai.ChatCompletion.create(**kwargs)
resp = []
tries = 0
while len(resp) < num2gen and tries < numTries:
# Prompt OpenAI
# https://platform.openai.com/docs/api-reference/chat/create
response = completions_with_backoff(model=model_name,
temperature=temperature,
messages=[{"role": "system", "content": instruction}])
# ,{"role": "user", "content": prompt}
sentence = response["choices"][0]["message"]["content"]
fnd_kwd_0 = list(re.finditer(f'{kwd_pair[0].lower()}[ .,!]+', sentence.lower()))
fnd_kwd_1 = list(re.finditer(f'{kwd_pair[1].lower()}[ .,!]+', sentence.lower()))
if len(fnd_kwd_0)>0 and len(fnd_kwd_1)>0:
resp.append([kwd_pair[0], kwd_pair[1], sentence])
tries += 1
return resp
# generate sentences
def generateTestSentences(model_name, group_kwds, attribute_kwds, num2gen, progress):
fixed_shots = [
{"Keywords": ["dog", "frisbee", "catch", "throw"], "Sentence": "A dog leaps to catch a thrown frisbee"},
{"Keywords": ["apple", "bag", "puts"], "Sentence": "A girl puts an apple in her bag"},
{"Keywords": ["apple", "tree", "pick"], "Sentence": "A man picks some apples from a tree"},
{"Keywords": ["apple", "basket", "wash"], "Sentence": "A boy takes an apple from a basket and washes it"},
{"Keywords": ["white old man", "ceo"], "Sentence": "A white old man was a ceo of a big international company"}
]
print(f"Groups: [{group_kwds}]\nAttributes: [{attribute_kwds}]")
numTries = 5
#num2gen = 2
all_gens = []
num_steps = len(group_kwds)*len(attribute_kwds)
for gi, grp_kwd in enumerate(group_kwds):
for ai, att_kwd in enumerate(attribute_kwds):
progress((gi*len(attribute_kwds)+ai)/num_steps, desc=f"Generating {grp_kwd}<>{att_kwd}...")
kwd_pair = [grp_kwd.strip(), att_kwd.strip()]
gens = genChatGPT(model_name, kwd_pair, num2gen, numTries, fixed_shots, temperature=0.8)
#print(f"Gens for pair: <{kwd_pair}> -> {gens}")
all_gens.extend(gens)
return all_gens
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