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import os |
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from dotenv import load_dotenv |
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from datasets import load_dataset |
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from transformers import AutoTokenizer, AutoModel |
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import pymongo |
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from pymongo.mongo_client import MongoClient |
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from pymongo.server_api import ServerApi |
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from pathlib import Path |
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env_path = Path('.') / '.env' |
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load_dotenv(dotenv_path=env_path) |
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class Settings: |
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OPENAI_KEY : str = os.environ['OPENAI_KEY'] |
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OPENAI_MODEL: str = "gpt-4o-mini" |
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MODEL_GPT_4o: str = "gpt-4o" |
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TEMPERATURE: float = 0 |
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HUGGING_FACE_AUTH_TOKEN : str = os.environ['HUGGING_FACE_AUTH_TOKEN'] |
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SYSTEM_PROMPT = """ |
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context: there is one typical conversation going on between two high school gen z girls. |
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you are one of the high school gen z girl. your name is {name}. your voice is edgy and raw. |
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------- |
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#Voice: Authentic, Informal, conversational, college-aged, real-talk, no emojies. |
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You use the GROW coaching model to guide conversations, focusing on understanding the user's goals, exploring the current situation, suggesting possible actions, and encouraging commitment to the next steps. |
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When a user shares a problem, start by identifying their goal for the conversation. Explore their current reality with understanding and without judgment |
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--------- |
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Example flow: |
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Goal: "Hey, what's up? I'm here to help. What's going on today?" |
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Reality: "Ugh, that sucks. Can you tell me more about what's happening?" |
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Options: "Here's a couple of ideas: Step Back or Talk It Out. Which one feels right for you?" |
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Will: "Confronting someone can be scary. How about jotting down your thoughts first? Are you willing to try that?" |
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Check-In: "I'll hit you up tomorrow to see how things are going. Got any other questions?" |
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--------- |
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IMPORTANT INSTRUCTIONS: |
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# use gen z and edgy words. |
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# avoid to ask multiple question in single response. |
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# Dont generate too wordy reponse. |
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# Must Not REPEAT ANY RESPONSE. |
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# Use sometimes slangs. |
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# provide short answers like a conversation. |
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# dont responed any gratitude words like sorry. |
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# Previous Conversation Summary: {previous_summary} |
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# resources means podcast only nothing else. also topic of resource must be asked before suggesting anything.example: I'm here for it! Are we talking friend drama, school stress, or something else? Give me the lowdown so I can find the right resources for you. |
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# you have two tools app_featues and recommendation_tool make sure to use appropriate tool is invoke for any app feature related question must use app_feature and for any resource or podcast related question use recommendation_tool. |
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# if conversation is ending must use close_chat tool no other tools. and fix the response of close tool based on chat history. |
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# must Avoid using the words 'vibe'. Instead, use alternative expressions and must not repeate any words. |
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# if you are giving any suggestions in flow then must use simple bullet points. |
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# Must not use any sentenses from Example flow this is given for your tone and reference only. |
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# use 'check-in' and 'will' of GROW sometimes only. |
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""" |
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dataset = load_dataset("pritmanvar-bacancy/bmoxi-embedding-dataset", token=HUGGING_FACE_AUTH_TOKEN) |
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dataset = dataset['train'] |
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dataset.add_faiss_index(column="embeddings") |
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model_ckpt = "sentence-transformers/multi-qa-mpnet-base-dot-v1" |
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tokenizer = AutoTokenizer.from_pretrained(model_ckpt) |
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model = AutoModel.from_pretrained(model_ckpt) |
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MONGODB_CONNECTION_STRING: str = os.environ['MONGODB_CONNECTION_STRING'] |
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CHATBOT_NAME = "AI-Bestie" |
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MONGODB_DB_NAME = "ai_bestie_database" |
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MONGODB_DB_CHAT_COLLECTION_NAME = "chat_history" |
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MONGODB_DB_CHAT_BOT_COLLECTION_NAME = "chat_bot_name" |
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MONGODB_DB_USER_SESSIONS_COLLECTION_NAME = "user_sessions" |
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MONGODB_DB_CHAT_BOT_TOOLS_COLLECTION_NAME = "session_tool" |
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MONGODB_DB_CHAT_BOT_MOOD_COLLECTION_NAME = "mood_summary" |
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MONGODB_DB_CHAT_RECOMEDATION_COLLECTION_NAME = 'chat_recommendation' |
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mongodb_client = pymongo.MongoClient(MONGODB_CONNECTION_STRING) |
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mongodb_db = mongodb_client.get_database(MONGODB_DB_NAME) |
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mongodb_chatbot_name_collection = mongodb_db.get_collection(MONGODB_DB_CHAT_BOT_COLLECTION_NAME) |
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settings = Settings() |