change character format
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04868e022d
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@ -3,4 +3,5 @@ DIALOG_PATH=AMUseBotFront/ai_talks/AMUseBotBackend/dialog/
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INTENT_DICT_PATH=ai_talks/AMUseBotBackend/utils/intent_dict.json
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MODEL_IDENTIFIER_PATH=ai_talks/AMUseBotBackend/models/NLU/roberta-base-cookdial.txt
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INGREDIENTS_RECIPES_MERGED=
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CHARACTERS_DICT=
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API_KEY=
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@ -11,33 +11,10 @@ import streamlit as st
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class DP:
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def __init__(self, dst: DST, llm_rephrasing=True, character='ramsay'): #TODO: a way to set llm_rephrasing status and a character
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def __init__(self, dst: DST, llm_rephrasing=True, character='default'): #TODO: a way to set llm_rephrasing status and a character
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self.dst_module = dst
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self.llm_rephrasing = llm_rephrasing
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with open('ai_talks/AMUseBotBackend/utils/characters_dict.json') as f:
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characters_dict = json.load(f)
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self.character = characters_dict[character]
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def llm_rephrase(self, character, response):
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model = character['model']
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prompt = character['prompt']
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input = character['leftside_input'] + response + character['rightside_input']
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message = [{'role': 'system', 'content': prompt}, {'role': 'user', 'content': input}]
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try:
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response = st.session_state.openai.ChatCompletion.create(
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model=model, messages=message, temperature=1, max_tokens=128
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)
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rephrased_response = response.choices[0].message.content
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except:
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print('OpenAI API call failed during response paraphrasing! Returning input response')
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rephrased_response = response
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return rephrased_response
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self.character = character
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def generate_response(self, intents: List[str]) -> str:
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@ -59,8 +36,7 @@ class DP:
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self.dst_module.set_next_step()
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if self.llm_rephrasing:
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return NLG.MESSAGE_CHOOSEN_RECIPE(recipe_name=recipe_name) + "\n" \
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+ self.llm_rephrase(self.character, self.dst_module.generate_state(c.STEPS_KEY)[
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self.dst_module.generate_state(c.CURR_STEP_KEY)])
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+ NLG.llm_rephrase_recipe(self.character, self.dst_module.generate_state(c.STEPS_KEY)[self.dst_module.generate_state(c.CURR_STEP_KEY)])
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else:
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return NLG.MESSAGE_CHOOSEN_RECIPE(recipe_name=recipe_name) + "\n" \
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+ self.dst_module.generate_state(c.STEPS_KEY)[self.dst_module.generate_state(c.CURR_STEP_KEY)]
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@ -73,6 +49,8 @@ class DP:
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# Recipe choosen
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if (None != self.dst_module.generate_state(c.RECIPE_ID_KEY) and "" != self.dst_module.generate_state(
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c.RECIPE_ID_KEY)):
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if ("req_substitute" in intents):
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return NLG.llm_substitute_product(self.character, self.dst_module.generate_state(c.DIALOG_HISTORY_KEY)[-1][c.USER_MESSAGE_KEY])
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if ("req_ingredient_list" in intents
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or "req_ingredient" in intents):
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return NLG.MESSAGE_INGREDIENTS(self.dst_module.generate_state(c.INGREDIENTS_KEY))
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@ -84,7 +62,7 @@ class DP:
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next_step = self.dst_module.set_next_step()
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if (next_step):
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if self.llm_rephrasing:
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return self.llm_rephrase(self.character, self.dst_module.generate_state(c.STEPS_KEY)[self.dst_module.generate_state(c.CURR_STEP_KEY)])
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return NLG.llm_rephrase_recipe(self.character, self.dst_module.generate_state(c.STEPS_KEY)[self.dst_module.generate_state(c.CURR_STEP_KEY)])
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else:
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return self.dst_module.generate_state(c.STEPS_KEY)[self.dst_module.generate_state(c.CURR_STEP_KEY)]
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if (not next_step):
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@ -1,3 +1,5 @@
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import streamlit as st
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class NLG:
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MESSAGE_PROMPT = "Hello! I'm AMUseBot, a virtual cooking assistant. Please tell me the name of the dish that you'd like to prepare today."
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MESSAGE_HI = "Hi! What do you want to make today?"
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@ -5,6 +7,7 @@ class NLG:
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BYE_ANSWER = "Bye, hope to see you soon!"
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RECIPE_OVER_ANSWER = "Congratulations! You finished preparing the dish, bon appetit!"
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NOT_UNDERSTAND_ANSWER = "I'm sorry, I don't understand. Could you rephrase?"
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CANNOT_HELP_ANSWER = "I'm sorry I can't help you with that."
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@staticmethod
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def MESSAGE_INGREDIENTS(ingr_list):
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@ -24,3 +27,38 @@ class NLG:
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suggestions = ", ".join(recipes_list[0:-1]) + f" or {recipes_list[-1]}"
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return f"I'm sorry, I don't know a recipe like that. Instead, I can suggest you {suggestions}."
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def llm_create_response(character, input):
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model = st.session_state.characters_dict['model']
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prompt = st.session_state.characters_dict['characters'][character]['prompt']
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message = [{'role': 'system', 'content': prompt}, {'role': 'user', 'content': input}]
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response = st.session_state.openai.ChatCompletion.create(
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model=model, messages=message, temperature=1, max_tokens=128
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)
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rephrased_response = response.choices[0].message.content
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return rephrased_response
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def llm_rephrase_recipe(character, response):
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input = st.session_state.characters_dict['task_paraphrase'] + f'"{response}".' + st.session_state.characters_dict['characters'][character]['task_specification']
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try:
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return NLG.llm_create_response(character, input)
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except:
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print('OpenAI API call failed during response paraphrasing! Returning input response')
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return response
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def llm_substitute_product(character, user_message):
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input = st.session_state.characters_dict['task_substitute'] + f'"{user_message}".'
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try:
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return NLG.llm_create_response(character, input)
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except:
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print('OpenAI API call failed during response paraphrasing! Returning input response')
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return NLG.CANNOT_HELP_ANSWER
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@ -1,11 +1,16 @@
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{
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"default": {"model": "gpt-3.5-turbo-0613", "prompt":
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"You're a master chef known for treating everyone like your equal. You're currently reading steps of a recipe to your apprentice.",
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"leftside_input": "Rephrase this step of a recipe to make it sound more like a natural, full English sentence: '",
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"rightside_input": "'."},
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"task_paraphrase": "You're currently reading a step of a recipe, paraphrese it so that it matches your charater: ",
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"task_substitute": "A user has just asked for a substitute for a missing ingredient, answer him according to your character: ",
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"model": "gpt-3.5-turbo-0613",
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"characters": {
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"default": {
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"prompt": "You're a master chef known for treating everyone like your equal. ",
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"task_specification": " Give your answer as a natural sounding, full English sentence."
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"ramsay": {"model": "gpt-3.5-turbo-0613", "prompt":
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"You're Gordon Ramsay, a famous British chef known for his short temper and routinely insulting people. You're currently reading steps of a recipe to your apprentice.",
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"leftside_input": "Rephrase this step of a recipe to make it sound as if you said it, in your characteristic rude fashion: '",
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"rightside_input": "'."}
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},
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"ramsay": {
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"prompt": "You're Gordon Ramsay, a famous British chef known for his short temper and routinely insulting people. ",
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"task_specification": ""
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}
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}
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}
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@ -10,6 +10,8 @@ from PIL import Image
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from src.utils.conversation import get_user_input, show_chat_buttons, show_conversation
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from src.utils.lang import en
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import openai
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import copy
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import json
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import os
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from dotenv import load_dotenv
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@ -44,6 +46,7 @@ if __name__ == '__main__':
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DIALOG_PATH = os.getenv('DIALOG_PATH')
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RECIPE_PATH = os.getenv('RECIPE_PATH')
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CHARACTERS_DICT = os.getenv('CHARACTERS_DICT')
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API_KEY = os.getenv('API_KEY')
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# Storing The Context
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@ -72,24 +75,25 @@ if __name__ == '__main__':
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if "openai" not in st.session_state:
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st.session_state.openai = openai
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st.session_state.openai.api_key = API_KEY
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if "characters_dict" not in st.session_state:
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with open(CHARACTERS_DICT) as f:
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st.session_state.characters_dict = json.load(f)
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def show_graph():
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# Create a graphlib graph object
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if st.session_state.generated:
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user, chatbot = [], []
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graph = graphviz.Digraph()
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for i in range(len(st.session_state.past)):
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chatbot.append(st.session_state.generated[i])
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user.append(st.session_state.past[i])
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chatbot = copy.deepcopy(st.session_state.generated)
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user = copy.deepcopy(st.session_state.past)
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for x in range(len(user)):
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chatbot_text = [word + '\n' if i % 5 == 0 and i > 0 else word for i, word in enumerate(st.session_state.generated[x].split(' '))]
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user_text = [word + '\n' if i % 5 == 0 and i > 0 else word for i, word in enumerate(st.session_state.past[x].split(' '))]
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chatbot_text = [word + '\n' if i % 5 == 0 and i > 0 else word for i, word in enumerate(chatbot[x].split(' '))]
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user_text = [word + '\n' if i % 5 == 0 and i > 0 else word for i, word in enumerate(user[x].split(' '))]
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graph.edge(' '.join(chatbot_text), ' '.join(user_text))
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try:
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graph.edge(' '.join(user_text), ' '.join([word + '\n' if i % 5 == 0 and i > 0 else word for i, word in enumerate(st.session_state.generated[x + 1].split(' '))]))
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except:
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pass
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try:
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graph.edge(' '.join(user_text), ' '.join([word + '\n' if i % 5 == 0 and i > 0 else word for i, word in enumerate(chatbot[x + 1].split(' '))]))
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except:
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pass
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st.graphviz_chart(graph)
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