| from llama_index.core import ( | |
| VectorStoreIndex, | |
| SimpleDirectoryReader, | |
| StorageContext, | |
| load_index_from_storage, | |
| ) | |
| from llama_index.llms.openai import OpenAI | |
| from llama_index.core.settings import Settings | |
| import os | |
| from dotenv import load_dotenv | |
| load_dotenv(override=True) | |
| Settings.llm = OpenAI(model="gpt-3.5-turbo", temperature=0.1) | |
| storage_path = "../vectorstore" | |
| documents_path = "../../documents" | |
| def initialize(): | |
| if not os.path.exists(storage_path): | |
| documents = SimpleDirectoryReader(documents_path).load_data() | |
| index = VectorStoreIndex.from_documents(documents) | |
| index.storage_context.persist(persist_dir=storage_path) | |
| else: | |
| storage_context = StorageContext.from_defaults(persist_dir=storage_path) | |
| index = load_index_from_storage(storage_context) | |
| return index | |
| index = initialize() | |
| chat_engine = index.as_chat_engine(chat_mode="condense_question", verbose=True) | |
| response = chat_engine.chat("hi tell me what i can ask you") | |
| print(response.response) |