Basic_LLM / 02_03.py
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from flask import Flask, render_template, request, jsonify
from langchain_openai import OpenAI
from langchain.prompts import PromptTemplate
prompt = open('website_text.txt', 'r').read()
hotel_assistant_template = prompt + """
You are the hotel manager of Landon Hotel, named "Mr. Landon".
Your expertise is exclusively in providing information and advice about anything related to Landon Hotel.
This includes any general Landon Hotel related queries.
You do not provide information outside of this scope.
If a question is not about Landon Hotel, respond with, "I can't assist you with that, sorry!"
Question: {question}
Answer:
"""
hotel_assistant_prompt_template = PromptTemplate(
input_variables=["question"],
template=hotel_assistant_template
)
llm = OpenAI(model='gpt-3.5-turbo-instruct', temperature=0)
llm_chain = hotel_assistant_prompt_template | llm
def query_llm(question):
response = llm_chain.invoke({'question': question})
return response
app = Flask(__name__)
@app.route("/")
def index():
return render_template("index.html")
@app.route("/chatbot", methods=["POST"])
def chatbot():
data = request.get_json()
question = data["question"]
response = query_llm(question)
return jsonify({"response": response})
if __name__ == "__main__":
app.run(debug=True)