gradio-langchain / main.py
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# Test langchain pulling from Turbo
import langchain
import openai
import gradio as gr
import os
from openai import OpenAI
openai.api_key = os.environ['OPENAI_API_KEY']
client = OpenAI()
#Assistants
# my_assistant = client.beta.assistants.retrieve("asst_9msH6Qr6Sb6JCQRwW3aqFDUi")
# print(my_assistant)
from langchain.chat_models import ChatOpenAI
from langchain.schema import AIMessage, HumanMessage
llm = ChatOpenAI(temperature=1.0, model='gpt-4-1106-preview')
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(share=True)