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# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/01_app.ipynb.
# %% auto 0
__all__ = ['ConversationBot', 'launch_demo']
# %% ../nbs/01_app.ipynb 3
import os
import gradio as gr
from fastcore.utils import in_jupyter
from langchain.chains import ConversationChain
from langchain.chat_models import ChatOpenAI
from langchain.memory import ConversationBufferMemory
from langchain.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
)
from .engineer_prompt import init_prompt
# %% ../nbs/01_app.ipynb 4
class ConversationBot:
def __init__(
self,
):
self.chat = ChatOpenAI(temperature=1, verbose=True)
self.memory = ConversationBufferMemory(return_messages=True)
self.init_prompt_msgs = init_prompt.messages
self.ai_prompt_questions = {
"ingredients": self.init_prompt_msgs[1],
"allergies": self.init_prompt_msgs[3],
"recipe_open_params": self.init_prompt_msgs[5],
}
def respond(self, user_msg, chat_history):
response = self._get_bot_response(user_msg, chat_history)
chat_history.append((user_msg, response))
return "", chat_history
def init_conversation(self, formatted_chat_prompt):
self.conversation = ConversationChain(
llm=self.chat,
memory=self.memory,
prompt=formatted_chat_prompt,
verbose=True,
)
def reset(self):
self.memory.clear()
def _get_bot_response(self, user_msg: str, chat_history) -> str:
if len(chat_history) < 2:
return self.ai_prompt_questions["allergies"].prompt.template
if len(chat_history) < 3:
return self.ai_prompt_questions["recipe_open_params"].prompt.template
if len(chat_history) < 4:
user = 0
ai = 1
user_msgs = [msg_pair[user] for msg_pair in chat_history[1:]]
f_init_prompt = init_prompt.format_prompt(
ingredients=user_msgs[0],
allergies=user_msgs[1],
recipe_freeform_input=user_msg,
)
chat_msgs = f_init_prompt.to_messages()
results = self.chat.generate([chat_msgs])
chat_msgs.extend(
[
results.generations[0][0].message,
MessagesPlaceholder(variable_name="history"),
HumanMessagePromptTemplate.from_template("{input}"),
]
)
open_prompt = ChatPromptTemplate.from_messages(chat_msgs)
# prepare the open conversation chain from this point
self.init_conversation(open_prompt)
return results.generations[0][0].message.content
response = self.conversation.predict(input=user_msg)
return response
# %% ../nbs/01_app.ipynb 5
def launch_demo():
with gr.Blocks() as demo:
bot = ConversationBot()
chatbot = gr.Chatbot(
value=[(None, bot.ai_prompt_questions["ingredients"].prompt.template)]
)
msg = gr.Textbox()
clear = gr.Button("Clear")
msg.submit(
fn=bot.respond, inputs=[msg, chatbot], outputs=[msg, chatbot], queue=False
)
clear.click(lambda: None, None, chatbot, queue=False).then(bot.reset)
demo.launch(
auth=(
os.environ["GRADIO_DEMO_USERNAME"],
os.environ["GRADIO_DEMO_PASSWORD"],
)
)
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