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import gradio as gr
import os
import openai
import gradio as gr
from gradio import ChatInterface
import time
# Get the value of the openai_api_key from environment variable
openai.api_key = os.getenv("OPENAI_API_KEY")
# Import things that are needed generically from langchain
from langchain import LLMMathChain, SerpAPIWrapper
from langchain.agents import AgentType, initialize_agent, load_tools
from langchain.chat_models import ChatOpenAI
from langchain.tools import BaseTool, StructuredTool, Tool, tool
from langchain.tools import MoveFileTool, format_tool_to_openai_function
from langchain.schema import (
AIMessage,
HumanMessage,
SystemMessage
)
from langchain.utilities import WikipediaAPIWrapper
from langchain.tools import AIPluginTool
# Question- how can one set up a system message for their Chatbot while using ChatInterface
# Example system message : system = SystemMessage(content = "You are a helpful AI assistant")
# driver
def predict_langchain(user_input, chatbot):
print(f"Chatbot : {chatbot}")
chat = ChatOpenAI(temperature=1.0, streaming=True, model='gpt-3.5-turbo-0613')
messages=[]
for conv in chatbot:
human = HumanMessage(content=conv[0])
ai = AIMessage(content=conv[1])
messages.append(human)
messages.append(ai)
messages.append(HumanMessage(content=user_input))
# getting gpt3.5's response
gpt_response = chat(messages)
return gpt_response.content
def predict(inputs, chatbot):
print(f"Chatbot : {chatbot}")
messages = []
for conv in chatbot:
user = conv[0]
messages.append({"role": "user", "content":user })
if conv[1] is None:
break
assistant = conv[1]
messages.append({"role": "assistant", "content":assistant})
# a ChatCompletion request
response = openai.ChatCompletion.create(
model='gpt-3.5-turbo',
messages= messages, # example : [{'role': 'user', 'content': "What is life? Answer in three words."}],
temperature=1.0,
stream=True # for streaming the output to chatbot
)
partial_message = ""
for chunk in response:
if len(chunk['choices'][0]['delta']) != 0:
print(chunk['choices'][0]['delta']['content'])
partial_message = partial_message + chunk['choices'][0]['delta']['content']
yield partial_message
title = "🤖ChatGPT Interface"
description = "Chatbots are a popular application of large language models. Using gradio, you can easily build a demo of your chatbot model and share that with your users, or try it yourself using an intuitive chatbot UI."
examples = ["How are you?","What is love?"]
gr.ChatInterface(predict,
title=title,
description=description,
theme='gstaff/xkcd').queue().launch() |