File size: 2,934 Bytes
2f6ea1f
 
 
7cc3907
 
8c18b31
 
 
7cc3907
2f6ea1f
7cc3907
2f6ea1f
014336b
7d676de
 
 
 
 
 
014336b
00ed004
014336b
7d676de
 
014336b
2f6ea1f
8c18b31
 
014336b
 
 
 
 
 
 
 
 
2f6ea1f
014336b
2f6ea1f
014336b
8c18b31
7cc3907
014336b
 
7cc3907
 
 
 
014336b
 
 
 
 
 
 
 
 
 
8c18b31
 
 
014336b
8c18b31
 
014336b
 
 
2f6ea1f
 
 
014336b
7cc3907
014336b
2f6ea1f
7cc3907
 
 
2f6ea1f
 
014336b
 
 
 
 
2f6ea1f
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python)

# OpenAI Chat completion
import os
from openai import AsyncOpenAI  # importing openai for API usage
import chainlit as cl  # importing chainlit for our app
from chainlit.prompt import Prompt, PromptMessage  # importing prompt tools
from chainlit.playground.providers import ChatOpenAI  # importing ChatOpenAI tools
from dotenv import load_dotenv

load_dotenv()

# ChatOpenAI Templates
system_template = """
You will be roleplaying Poppy, an FAQ AI chat assistant for pediatric dentistry.
Respond to the user's questions in a warm and engaging manner. Always summarize your response to be as brief as possible. 
Your responses should be fewer than a couple of sentences. Do not provide medical advice or make any diagnosis. 
If you are unsure about a question, politely inform the user that you are unable to provide an answer.
Do not answer if the question is not related to pediatric dentistry. Reply with I am just a pediatric dentistry chat assistant and I am unable to provide an answer to that question.
"""

user_template = """{input}
Think through your response step by step. 
Be concise and funny in your response. I am a child.
"""


@cl.on_chat_start  # marks a function that will be executed at the start of a user session
async def start_chat():
    settings = {
        "model": "gpt-3.5-turbo",
        "temperature": 0,
        "max_tokens": 500,
        "top_p": 1,
        "frequency_penalty": 0,
        "presence_penalty": 0,
    }

    cl.user_session.set("settings", settings)


@cl.on_message  # marks a function that should be run each time the chatbot receives a message from a user
async def main(message: cl.Message):
    settings = cl.user_session.get("settings")

    client = AsyncOpenAI()

    print(message.content)

    prompt = Prompt(
        provider=ChatOpenAI.id,
        messages=[
            PromptMessage(
                role="system",
                template=system_template,
                formatted=system_template,
            ),
            PromptMessage(
                role="user",
                template=user_template,
                formatted=user_template.format(input=message.content),
            ),
        ],
        inputs={"input": message.content},
        settings=settings,
    )

    print([m.to_openai() for m in prompt.messages])

    msg = cl.Message(content="")

    # Call OpenAI
    async for stream_resp in await client.chat.completions.create(
        messages=[m.to_openai() for m in prompt.messages], stream=True, **settings
    ):
        token = stream_resp.choices[0].delta.content
        if not token:
            token = ""
        await msg.stream_token(token)

    # Update the prompt object with the completion
    prompt.completion = msg.content
    msg.prompt = prompt

    # Send and close the message stream
    await msg.send()