Spaces:
Sleeping
Sleeping
File size: 2,486 Bytes
1ce1659 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
import openai
from dotenv import load_dotenv
import os
load_dotenv()
AZURE_OPENAI_API_KEY = os.getenv('AZURE_OPENAI_API_KEY')
AZURE_OPENAI_ENDPOINT = os.getenv('AZURE_OPENAI_ENDPOINT')
AZURE_OPENAI_API_VERSION = os.getenv('AZURE_OPENAI_API_VERSION')
client = openai.AzureOpenAI(
api_version = AZURE_OPENAI_API_VERSION,
api_key = AZURE_OPENAI_API_KEY,
azure_endpoint = AZURE_OPENAI_ENDPOINT,
)
def generate_content(text_generation_model, image_generation_model, title, content):
# Generate text using the selected models
full_content = ""
input_type = ""
if title and content:
full_content = title + "\n" + content
input_type = "title and content"
elif title:
full_content = title
input_type = "title"
elif content:
full_content = title
input_type = "content"
# Generate text using the text generation model
generated_text = generate_text(text_generation_model, full_content, input_type)
return title, generated_text
def generate_text(model, full_context, input_type):
# Generate text using the selected model
if input_type == "":
prompt = "Generate a random fake news article"
else:
prompt = f"Generate a fake news article (title and content) based on the following: # Title: {input_type}:\n\n# Content: {full_context}"
try:
response = client.chat.completions.create(
model=model,
messages = [{"role": "system", "content": prompt}],
)
print("Response from OpenAI API: ", response.choices[0].message.content)
return response.choices[0].message.content
except openai.OpenAIError as e:
print(f"Error interacting with OpenAI API: {e}")
return "An error occurred while processing your request."
def replace_text(news_title, news_content, replace_df):
"""
Replaces occurrences in the input text based on the provided DataFrame.
Args:
text: The input text.
replace_df: A pandas DataFrame with two columns: "find_what" and "replace_with".
Returns:
The text after all replacements have been made.
"""
for _, row in replace_df.iterrows():
find_what = row["Find what:"]
replace_with = row["Replace with:"]
news_content = news_content.replace(find_what, replace_with)
news_title = news_title.replace(find_what, replace_with)
return news_title, news_content |