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| import re | |
| from langchain_openai import ChatOpenAI | |
| from langchain.schema import ( | |
| AIMessage, | |
| HumanMessage, | |
| SystemMessage | |
| ) | |
| import os | |
| OPENAI_API_KEY=os.getenv('OPENAI_API_KEY') | |
| def get_api_response(content: str, max_tokens=None): | |
| response = None | |
| chat = ChatOpenAI( | |
| openai_api_key=OPENAI_API_KEY, | |
| #model='gpt-3', | |
| #model='gpt-3.5-turbo', | |
| #model='gpt-3.5-turbo-0613', | |
| #model='gpt-3.5-turbo-16k', | |
| model='gpt-3.5-turbo-16k-0613', | |
| #openai_proxy=OPENAI_Proxy, | |
| #model='gpt-4', | |
| #model='gpt-4-0613', | |
| #model='gpt-4-32k-0613', | |
| temperature=0.1) | |
| # response = openai.ChatCompletion.create( | |
| # model='gpt-3.5-turbo-16k-0613', | |
| # messages=[{ | |
| # 'role': 'system', | |
| # 'content': 'You are a helpful and creative assistant for writing novel.' | |
| # }, { | |
| # 'role': 'user', | |
| # 'content': content, | |
| # }], | |
| # temperature=0.5, | |
| # max_tokens=max_tokens | |
| # ) | |
| # response = None | |
| messages = [ | |
| SystemMessage(content="You are a helpful and creative assistant for writing novel."), | |
| HumanMessage(content=content) | |
| ] | |
| try: | |
| response = chat(messages) | |
| except: | |
| raise Exception("OpenAI Error") | |
| if response is not None: | |
| return response.content | |
| else: | |
| return "Error: response not found" | |
| def get_content_between_a_b(a,b,text): | |
| return re.search(f"{a}(.*?)\n{b}", text, re.DOTALL).group(1).strip() | |
| def get_init(init_text=None,text=None,response_file=None): | |
| """ | |
| init_text: if the title, outline, and the first 3 paragraphs are given in a .txt file, directly read | |
| text: if no .txt file is given, use init prompt to generate | |
| """ | |
| if not init_text: | |
| response = get_api_response(text) | |
| print(response) | |
| if response_file: | |
| with open(response_file, 'a', encoding='utf-8') as f: | |
| f.write(f"Init output here:\n{response}\n\n") | |
| else: | |
| with open(init_text,'r',encoding='utf-8') as f: | |
| response = f.read() | |
| f.close() | |
| paragraphs = { | |
| "name":"", | |
| "Outline":"", | |
| "Paragraph 1":"", | |
| "Paragraph 2":"", | |
| "Paragraph 3":"", | |
| "Summary": "", | |
| "Instruction 1":"", | |
| "Instruction 2":"", | |
| "Instruction 3":"" | |
| } | |
| paragraphs['name'] = get_content_between_a_b('Name:','Outline',response) | |
| paragraphs['Paragraph 1'] = get_content_between_a_b('Paragraph 1:','Paragraph 2:',response) | |
| paragraphs['Paragraph 2'] = get_content_between_a_b('Paragraph 2:','Paragraph 3:',response) | |
| paragraphs['Paragraph 3'] = get_content_between_a_b('Paragraph 3:','Summary',response) | |
| paragraphs['Summary'] = get_content_between_a_b('Summary:','Instruction 1',response) | |
| paragraphs['Instruction 1'] = get_content_between_a_b('Instruction 1:','Instruction 2',response) | |
| paragraphs['Instruction 2'] = get_content_between_a_b('Instruction 2:','Instruction 3',response) | |
| lines = response.splitlines() | |
| # content of Instruction 3 may be in the same line with I3 or in the next line | |
| if lines[-1] != '\n' and lines[-1].startswith('Instruction 3'): | |
| paragraphs['Instruction 3'] = lines[-1][len("Instruction 3:"):] | |
| elif lines[-1] != '\n': | |
| paragraphs['Instruction 3'] = lines[-1] | |
| # Sometimes it gives Chapter outline, sometimes it doesn't | |
| for line in lines: | |
| if line.startswith('Chapter'): | |
| paragraphs['Outline'] = get_content_between_a_b('Outline:','Chapter',response) | |
| break | |
| if paragraphs['Outline'] == '': | |
| paragraphs['Outline'] = get_content_between_a_b('Outline:','Paragraph',response) | |
| return paragraphs | |
| def get_chatgpt_response(model,prompt): | |
| response = "" | |
| for data in model.ask(prompt): | |
| response = data["message"] | |
| model.delete_conversation(model.conversation_id) | |
| model.reset_chat() | |
| return response | |
| def parse_instructions(instructions): | |
| output = "" | |
| for i in range(len(instructions)): | |
| output += f"{i+1}. {instructions[i]}\n" | |
| return output |