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- from langchain.chat_models import ChatOpenAI
- from langchain.document_loaders import TextLoader
- from langchain.embeddings import OpenAIEmbeddings
- from langchain.indexes import VectorstoreIndexCreator
-
- embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
- loader = TextLoader("openim.txt")
- index = VectorstoreIndexCreator(embedding=embedding).from_loaders([loader])
- llm = ChatOpenAI(model="gpt-3.5-turbo")
-
- questions = [
- "What is openim",
- "How many projects were announced",
- ]
-
- for query in questions:
- print("Query:", query)
- print("Answer:", index.query(query, llm=llm))
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