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| import openai | |
| import os | |
| # Define the Clauses class | |
| class Clauses: | |
| def __init__(self): | |
| """ | |
| Initialize the Extractor class. | |
| """ | |
| # Set OpenAI API key | |
| # os.environ["OPENAI_API_KEY"] = "" | |
| 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: | |
| # Prepare a prompt for GPT-3 that includes the extracted PDF text and instructions | |
| prompt = f""" | |
| Extract clauses and sub-clauses from the provided contract PDF: | |
| {extracted_summary} | |
| Instructions: Organize the extracted clauses and sub clauses in a readable format. | |
| """ | |
| # Use GPT-3 to process the prompt and generate clauses | |
| response = openai.Completion.create( | |
| engine="text-davinci-003", | |
| prompt=prompt, | |
| max_tokens=1000 | |
| ) | |
| # Extract the generated text from the GPT-3 response | |
| result = response['choices'][0]['text'].strip() | |
| return result | |
| 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 | |