#chatgpt #dalle2 #python #pythonprogramming #openai
example call to the script:
===========================================================================
python chat.py –mtype com –temperature 1.0 –prompt “Tell me why its a really good idea to subscribe to this youtube channel.”
creds.json
==================
{
“org”: “your_org”,
“key”: “your_key”
}
chat.py
===================================
import os, re, argparse, json, openai
# setup openai
def init_openai():
f = open(‘creds.json’)
creds = json.load(f)
openai.organization = creds[“org”]
openai.api_key = creds[“key”]
f.close()
# parse args
def init_argparse():
parser = argparse.ArgumentParser(description=’Make calls the the OpenAI API.’)
parser.add_argument(“–mtype”, type=str, default=”com”, help=”The type of model to use. com, cod, img, or emb == completion, code, image, or embedded”)
parser.add_argument(“–temperature”, type=float, default=1.0, help=”The temperature of the model. Must be greater than 0.0 and less than 1.0, Zero provides ‘safer’ responses and One provides ‘riskier’ responses”)
parser.add_argument(“–prompt”, type=str, default=”I am a clown”, help=”The input string (prompt), which can vary depending on the type of model you are using.”)
args = parser.parse_args()
mtype = args.mtype
temperature = args.temperature
prompt = re.sub(r”(S{1,20})”, “”, args.prompt.replace(‘n’, ”).strip())
return {“mtype”: mtype, “temperature”: temperature, “prompt”: prompt}
# run model, based on args
def run_model(input_data):
if(input_data[“mtype”] == “com”):
”’
Completion Test
”’
res = openai.Completion.create(
model=”text-davinci-003″,
prompt=input_data[“prompt”],
max_tokens=3000,
temperature=input_data[“temperature”],
echo=True,
user=”session000″
)
txtResponse = res.choices[0].text
print(txtResponse)
elif(input_data[“mtype”] == “mar”):
”’
Marv Test
”’
res = openai.Completion.create(
model=”text-davinci-003″,
prompt=input_data[“prompt”],
temperature=0.5,
max_tokens=60,
top_p=0.3,
frequency_penalty=0.5,
presence_penalty=0.0
)
txtResponse = res.choices[0].text
print(txtResponse)
elif(input_data[“mtype”] == “cod”):
”’
Coding Test
”’
res = openai.Completion.create(
model=”code-davinci-002″,
prompt=input_data[“prompt”],
temperature=input_data[“temperature”],
max_tokens=3500,
top_p=1,
frequency_penalty=0,
presence_penalty=0
)
txtResponse = res.choices[0].text
print(txtResponse)
elif(input_data[“mtype”] == “img”):
”’
Image Test
”’
res = openai.Image.create(
prompt=input_data[“prompt”],
n=1,
size=”1024×1024″
)
image_url = res[‘data’][0][‘url’]
print(image_url)
elif(input_data[“mtype”] == “emb”):
”’
Embedding Test
”’
res = openai.Embedding.create(
model=”text-embedding-ada-002″,
input=input_data[“prompt”]
)
print(res)
elif(input_data[“mtype”] == “rec”):
”’
Recipe Test
”’
res = openai.Completion.create(
model=”text-davinci-003″,
prompt=input_data[“prompt”],
temperature=0.3,
max_tokens=2000,
top_p=1.0,
frequency_penalty=0.0,
presence_penalty=0.0
)
txtResponse = res.choices[0].text
print(txtResponse)
else:
print(“invalid input parameters”)
def main():
init_openai()
input_data = init_argparse()
run_model(input_data)
if __name__ == “__main__”:
main()
