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| import os | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN") | |
| FALCON_REPO_ID = "tiiuae/falcon-7b-instruct" | |
| FALCON_TEMPERATURE = 0.1 | |
| FALCON_MAX_TOKENS = 500 | |
| OPENAI_MODEL_NAME = "gpt-3.5-turbo" | |
| OPENAI_TEMPERATURE = 0.8 | |
| OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") | |
| EMBEDDING_MODEL_NAME = "sentence-transformers/all-distilroberta-v1" | |
| ITEM_KEYWORD_EMBEDDING = "item_vector" | |
| TOPK = 5 | |
| NUMBER_PRODUCTS = 1000 | |
| MAX_TEXT_LENGTH = 512 | |
| TEXT_EMBEDDING_DIMENSION = 768 | |
| DATA_PATH = "product_data.csv" | |
| TEMPLATE_1 = "Create comma separated product keywords to perform a query on amazon dataset for this user input: {product_description}" | |
| TEMPLATE_2 = """You are a salesman.Present the given product results in a nice way as answer to the user_msg. Don't ask questions back, | |
| if results are empty just say that we don't have such products, | |
| {chat_history} | |
| user:{user_msg} | |
| Chatbot:""" | |