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from langchain.chat_models import ChatOpenAI
from langchain.schema import AIMessage, HumanMessage
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
import openai, os
import gradio as gr
from dotenv import load_dotenv
load_dotenv()
OPENAI_API_KEY = os.environ['GROQ_API_KEY']
llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
# llm = ChatOpenAI(temperature=1.0, model='gpt-4-turbo')
# llm = openai(temperature=1.0, model='gpt-4o')
def predict(message, history):
history_langchain_format = []
for human, ai in history:
history_langchain_format.append(HumanMessage(content=human))
history_langchain_format.append(AIMessage(content=ai))
history_langchain_format.append(HumanMessage(content=message))
gpt_response = llm(history_langchain_format)
return gpt_response.content
gr.ChatInterface(predict).launch() |