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from openai import AzureOpenAI | |
import os | |
# Define the Clauses class | |
class Clauses: | |
def __init__(self): | |
# openai.api_type = os.getenv['api_type'] | |
# openai.api_base = os.getenv['api_base'] | |
# openai.api_version = os.getenv['api_version'] | |
# openai.api_key = os.getenv['api_key'] | |
pass | |
def get_extracted_clauses(extracted_summary): | |
""" | |
Gets extracted clauses using GPT-3 based on the provided PDF. | |
Args: | |
max_tokens (int, optional): Maximum number of tokens for GPT-3 response. | |
Returns: | |
str: Extracted clauses from GPT-3 response. | |
""" | |
try: | |
client = AzureOpenAI(api_key=os.getenv("AZURE_OPENAI_KEY"), | |
api_version="2023-07-01-preview", | |
azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") | |
) | |
conversation = [ | |
{"role": "system", "content": "You are a helpful Cluases and SubCluases Extracter From Given Content."}, | |
{"role": "user", "content": f"""Extract clauses and sub-clauses from the provided contract PDF | |
{extracted_summary}"""} | |
] | |
# Call OpenAI GPT-3.5-turbo | |
chat_completion = client.chat.completions.create( | |
model = "GPT-3", | |
messages = conversation, | |
max_tokens=1000, | |
temperature=0 | |
) | |
response = chat_completion.choices[0].message.content | |
return response | |
except Exception as e: | |
# If an error occurs during GPT-3 processing, log the error and raise an exception | |
print(f"Error occurred while processing PDF with GPT-3. Error message: {str(e)}") | |
raise | |