This might be a repeated question. But i already explored existing questions.
I just started the DeepLearning + OpenAI course on Prompt Engineering for devs, and tried replicating what they were doing with my own api key. I keep getting the no api key error.
Code given below. Api key is cut out coz secret ofc.
import openai
import os
from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
openai.api_key = os.getenv("sk-Gy")
# openai.api_key=("sk-G0")
model = "gpt-3.5-turbo"
def get_completion(prompt,model='gpt-3.5-turbo'):
messages = [{"role":"user","content": prompt}]
response = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=0,#this is the degree of randomness of the model's output
)
return responses.choices[0].message["content"]
text = f"""
You should express what you want a model to do by \
providing instructions that are as clear and \
specific as you can possibly make them. \
This will guide the model towards the desired output, \
and reduce the chances of receiving irrelevant \
or incorrect responses. Don't confuse writing a \
clear prompt with writing a short prompt. \
In many cases, longer prompts provide more clarity \
and context for the model, which can lead to \
more detailed and relevant outputs.
"""
prompt = f"""
Summarize the text delimited by triple backticks \
into a single sentence.
```{text}```
"""
response = get_completion(prompt)
print(response)