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Merge pull request #1 from Optimized-Coder/Optimized-Coder-patch-1

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Increase readability to chatbot.py
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Josh Shepherd 2023-03-31 01:39:58 +01:00 committed by GitHub
commit 975ed03a83
1 changed files with 47 additions and 20 deletions
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67
apps/chatbot-kickstarter/chatbot.py
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@ -2,24 +2,25 @@ import openai
from termcolor import colored
import streamlit as st
from database import get_redis_connection,get_redis_results
from database import get_redis_connection, get_redis_results
from config import CHAT_MODEL,COMPLETIONS_MODEL, INDEX_NAME
from config import CHAT_MODEL, COMPLETIONS_MODEL, INDEX_NAME
redis_client = get_redis_connection()
# A basic class to create a message as a dict for chat
class Message:
def __init__(self,role,content):
def __init__(self, role,content):
self.role = role
self.content = content
def message(self):
return {"role": self.role,"content": self.content}
return {
"role": self.role,
"content": self.content
}
# New Assistant class to add a vector database call to its responses
class RetrievalAssistant:
@ -28,7 +29,6 @@ class RetrievalAssistant:
self.conversation_history = []
def _get_assistant_response(self, prompt):
try:
completion = openai.ChatCompletion.create(
model=CHAT_MODEL,
@ -36,34 +36,57 @@ class RetrievalAssistant:
temperature=0.1
)
response_message = Message(completion['choices'][0]['message']['role'],completion['choices'][0]['message']['content'])
response_message = Message(
completion['choices'][0]['message']['role'],
completion['choices'][0]['message']['content']
)
return response_message.message()
except Exception as e:
return f'Request failed with exception {e}'
# The function to retrieve Redis search results
def _get_search_results(self,prompt):
latest_question = prompt
search_content = get_redis_results(redis_client,latest_question,INDEX_NAME)['result'][0]
search_content = get_redis_results(
redis_client,latest_question,
INDEX_NAME
)['result'][0]
return search_content
def ask_assistant(self, next_user_prompt):
[self.conversation_history.append(x) for x in next_user_prompt]
assistant_response = self._get_assistant_response(self.conversation_history)
# Answer normally unless the trigger sequence is used "searching_for_answers"
if 'searching for answers' in assistant_response['content'].lower():
question_extract = openai.Completion.create(model=COMPLETIONS_MODEL,prompt=f"Extract the user's latest question and the year for that question from this conversation: {self.conversation_history}. Extract it as a sentence stating the Question and Year")
question_extract = openai.Completion.create(
model = COMPLETIONS_MODEL,
prompt=f'''
Extract the user's latest question and the year for that question from this
conversation: {self.conversation_history}. Extract it as a sentence stating the Question and Year"
'''
)
search_result = self._get_search_results(question_extract['choices'][0]['text'])
# We insert an extra system prompt here to give fresh context to the Chatbot on how to use the Redis results
# In this instance we add it to the conversation history, but in production it may be better to hide
self.conversation_history.insert(-1,{"role": 'system',"content": f"Answer the user's question using this content: {search_result}. If you cannot answer the question, say 'Sorry, I don't know the answer to this one'"})
self.conversation_history.insert(
-1,{
"role": 'system',
"content": f'''
Answer the user's question using this content: {search_result}.
If you cannot answer the question, say 'Sorry, I don't know the answer to this one'
'''
}
)
assistant_response = self._get_assistant_response(self.conversation_history)
assistant_response = self._get_assistant_response(
self.conversation_history
)
self.conversation_history.append(assistant_response)
return assistant_response
@ -71,14 +94,18 @@ class RetrievalAssistant:
self.conversation_history.append(assistant_response)
return assistant_response
def pretty_print_conversation_history(
self,
colorize_assistant_replies=True):
def pretty_print_conversation_history(self, colorize_assistant_replies=True):
for entry in self.conversation_history:
if entry['role'] == 'system':
if entry['role']=='system':
pass
else:
prefix = entry['role']
content = entry['content']
output = colored(prefix +':\n' + content, 'green') if colorize_assistant_replies and entry['role'] == 'assistant' else prefix +':\n' + content
#prefix = entry['role']
print(output)
if colorize_assistant_replies and entry['role'] == 'assistant':
output = colored(f"{prefix}:\n{content}, green")
else:
output = colored(f"{prefix}:\n{content}")
print(output)