nataliehamptonn/Knowledge_Graph_RAG

1from langchain_openai import ChatOpenAI2from langchain_core.output_parsers import StrOutputParser3 4from langchain_core.messages import AIMessage, HumanMessage5from dotenv import load_dotenv6import os7from langchain.prompts import ChatPromptTemplate8 9 10load_dotenv()11os.environ["LANGCHAIN_TRACING_V2"] = "false"12langchain_api_key = os.environ.get('LANGCHAIN_API_KEY')13openai_api_key = os.environ.get('OPENAI_API_KEY')14langchain_project = os.environ.get('LANGCHAIN_PROJECT')15 16 17def answer_question_noRAG(question, chat_history):18    template = """19    You are a chatbot designed to answer students' questions. Give a useful, complete answer to the student's question. 20    Answer in as few words as possible.21 22    Q. {question}23    A. 24    """25 26    prompt = ChatPromptTemplate.from_template(template)27 28    llm = ChatOpenAI(streaming=True, model="gpt-3.5-turbo", 29        temperature=.7)30 31    chain = prompt | llm | StrOutputParser()32 33    result = chain.invoke({"question": question})34 35    chat_history.extend( 36        [ 37            HumanMessage(content=question), 38            AIMessage(content=result),39        ]40    )41 42    return result43 44