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from pydantic import BaseModel |
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import openai |
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from environs import Env |
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env = Env() |
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env.read_env("openai.env") |
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openai.api_key = env.str("OPENAI_API_KEY") |
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SYSTEM_PROMPT = env.str("SYSTEM_PROMPT", "generate 3 different friendly short conversation starter for a user to another unknown user.") |
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MODEL = env.str("MODEL", "gpt-3.5-turbo") |
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NUMBER_OF_MESSAGES_FOR_CONTEXT = min(env.int("NUMBER_OF_MESSAGES_FOR_CONTEXT", 4), 10) |
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AI_RESPONSE_TIMEOUT = env.int("AI_RESPONSE_TIMEOUT", 20) |
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class ConversationPayload(BaseModel): |
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fromusername: str |
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tousername: str |
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FromUserKavasQuestions: list |
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ToUserKavasQuestions: list |
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Chatmood: str |
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def create_conversation_starter_prompt(user_questions, chatmood): |
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formatted_info = " ".join([f"{qa['Question']} - {qa['Answer']}" for qa in user_questions if qa['Answer']]) |
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prompt = (f"Based on user profile info and a {chatmood} mood, " |
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f"generate 3 subtle and very short conversation starters. " |
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f"Explore various topics like travel, hobbies, movies, and not just culinary tastes. " |
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f"\nProfile Info: {formatted_info}") |
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return prompt |
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def generate_conversation_starters(prompt): |
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try: |
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response = openai.ChatCompletion.create( |
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model=MODEL, |
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messages=[{"role": "system", "content": prompt}], |
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temperature=0.7, |
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max_tokens=100, |
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n=1, |
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request_timeout=AI_RESPONSE_TIMEOUT |
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) |
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return response.choices[0].message["content"] |
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except openai.error.OpenAIError as e: |
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raise Exception(f"OpenAI API error: {str(e)}") |
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except Exception as e: |
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raise Exception(f"Unexpected error: {str(e)}") |
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