app.py

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_old(user_input, 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'inputs is - {inputs}')
    print(f'chatbot is - {chatbot}')
    #if chatbot[0][-1]  is None: #[["hi there'", None]]
    #    chatbot=[]
    messages = []
    for conv in chatbot:
        user = conv[0]
        messages.append({"role": "user", "content":user })
        if chatbot[0][-1] is None: #[["hi there'", None]]
            #chatbot=[]
            break
        assistant = conv[1]
        messages.append({"role": "assistant", "content":assistant})
    
    #messages.append({"role": "user", "content":inputs})
    print(f'messages is - {messages}')

    # a ChatCompletion request
    response = openai.ChatCompletion.create(
        model='gpt-3.5-turbo',
        messages= messages, # [{'role': 'user', 'content': "What is life? Answer in three words."}],
        temperature=1.0,
        stream=True  # for streaming the output to chatbot
    )
    print(f'response is - {response}')

    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 
        #time.sleep(0.5)

def echo_stream(message, history):
    for i in range(len(message)):
        time.sleep(0.3)
        yield message[:i]

ChatInterface(predict, chatbot=[]).queue().launch(debug=True)

#chatbot = gr.Chatbot()
#gr.ChatInterface(predict, delete_last_btn="del").queue().launch(share=False, debug=True) #examples=["How are you?", "What's up?"],