from langchain.chains.query_constructor.schema import AttributeInfo from langchain.schema import Document # Qdrant collection name DEFAULT_COLLECTION_NAME = "restaurants" # Here is a description of the dataset and metadata attributes. Metadata attributes will # be used to filter the results of the query beyond the semantic search. DEFAULT_DOCUMENT_CONTENTS = ( "Dishes served at different restaurants, along with the restaurant information" ) DEFAULT_METADATA_FIELD_INFO = [ AttributeInfo( name="price", description="The price of the dish", type="float", ), AttributeInfo( name="restaurant.name", description="The name of the restaurant", type="string", ), AttributeInfo( name="restaurant.location", description="Name of the city where the restaurant is located", type="string or list[string]", ), ] # A default set of documents to use for the vector store. This is a list of Document # objects, which have a page_content field and a metadata field. The metadata field is a # dictionary of metadata attributes compatible with the metadata field info above. DEFAULT_DOCUMENTS = [ Document( page_content="Pepperoni pizza with extra cheese, crispy crust", metadata={ "price": 10.99, "restaurant": { "name": "Pizza Hut", "location": ["New York", "Chicago"], }, }, ), Document( page_content="Spaghetti with meatballs and tomato sauce", metadata={ "price": 12.99, "restaurant": { "name": "Olive Garden", "location": ["New York", "Chicago", "Los Angeles"], }, }, ), Document( page_content="Chicken tikka masala with naan", metadata={ "price": 14.99, "restaurant": { "name": "Indian Oven", "location": ["New York", "Los Angeles"], }, }, ), Document( page_content="Chicken teriyaki with rice", metadata={ "price": 11.99, "restaurant": { "name": "Sakura", "location": ["New York", "Chicago", "Los Angeles"], }, }, ), Document( page_content="Scabbard fish with banana and passion fruit sauce", metadata={ "price": 19.99, "restaurant": { "name": "A Concha", "location": ["San Francisco"], }, }, ), Document( page_content="Pielmieni with sour cream", metadata={ "price": 13.99, "restaurant": { "name": "Russian House", "location": ["New York", "Chicago"], }, }, ), Document( page_content="Chicken biryani with raita", metadata={ "price": 14.99, "restaurant": { "name": "Indian Oven", "location": ["Los Angeles"], }, }, ), Document( page_content="Tomato soup with croutons", metadata={ "price": 7.99, "restaurant": { "name": "Olive Garden", "location": ["New York", "Chicago", "Los Angeles"], }, }, ), Document( page_content="Vegan burger with sweet potato fries", metadata={ "price": 12.99, "restaurant": { "name": "Burger King", "location": ["New York", "Los Angeles"], }, }, ), Document( page_content="Chicken nuggets with french fries", metadata={ "price": 9.99, "restaurant": { "name": "McDonald's", "location": ["San Francisco", "New York", "Los Angeles"], }, }, ), ]