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chat.py
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import chromadb
from chromadb.config import Settings
import openai
import yaml
from time import time, sleep
from uuid import uuid4
def save_yaml(filepath, data):
with open(filepath, 'w', encoding='utf-8') as file:
yaml.dump(data, file, allow_unicode=True)
def save_file(filepath, content):
with open(filepath, 'w', encoding='utf-8') as outfile:
outfile.write(content)
def open_file(filepath):
with open(filepath, 'r', encoding='utf-8', errors='ignore') as infile:
return infile.read()
def chatbot(messages, model="gpt-4", temperature=0):
max_retry = 7
retry = 0
while True:
try:
response = openai.ChatCompletion.create(model=model, messages=messages, temperature=temperature)
text = response['choices'][0]['message']['content']
### trim message object
debug_object = [i['content'] for i in messages]
debug_object.append(text)
save_yaml('api_logs/convo_%s.yaml' % time(), debug_object)
if response['usage']['total_tokens'] >= 7000:
a = messages.pop(1)
return text
except Exception as oops:
print(f'\n\nError communicating with OpenAI: "{oops}"')
if 'maximum context length' in str(oops):
a = messages.pop(1)
print('\n\n DEBUG: Trimming oldest message')
continue
retry += 1
if retry >= max_retry:
print(f"\n\nExiting due to excessive errors in API: {oops}")
exit(1)
print(f'\n\nRetrying in {2 ** (retry - 1) * 5} seconds...')
sleep(2 ** (retry - 1) * 5)
if __name__ == '__main__':
# instantiate ChromaDB
persist_directory = "chromadb"
chroma_client = chromadb.Client(Settings(persist_directory=persist_directory,chroma_db_impl="duckdb+parquet",))
collection = chroma_client.get_or_create_collection(name="knowledge_base")
# instantiate chatbot
openai.api_key = open_file('key_openai.txt')
conversation = list()
conversation.append({'role': 'system', 'content': open_file('system_default.txt')})
user_messages = list()
all_messages = list()
while True:
# get user input
text = input('\n\nUSER: ')
user_messages.append(text)
all_messages.append('USER: %s' % text)
conversation.append({'role': 'user', 'content': text})
save_file('chat_logs/chat_%s_user.txt' % time(), text)
# update main scratchpad
if len(all_messages) > 5:
all_messages.pop(0)
main_scratchpad = '\n\n'.join(all_messages).strip()
# search KB, update default system
current_profile = open_file('user_profile.txt')
kb = 'No KB articles yet'
if collection.count() > 0:
results = collection.query(query_texts=[main_scratchpad], n_results=1)
kb = results['documents'][0][0]
#print('\n\nDEBUG: Found results %s' % results)
default_system = open_file('system_default.txt').replace('<<PROFILE>>', current_profile).replace('<<KB>>', kb)
#print('SYSTEM: %s' % default_system)
conversation[0]['content'] = default_system
# generate a response
response = chatbot(conversation)
save_file('chat_logs/chat_%s_chatbot.txt' % time(), response)
conversation.append({'role': 'assistant', 'content': response})
all_messages.append('CHATBOT: %s' % response)
print('\n\nCHATBOT: %s' % response)
# update user scratchpad
if len(user_messages) > 3:
user_messages.pop(0)
user_scratchpad = '\n'.join(user_messages).strip()
# update user profile
print('\n\nUpdating user profile...')
profile_length = len(current_profile.split(' '))
profile_conversation = list()
profile_conversation.append({'role': 'system', 'content': open_file('system_update_user_profile.txt').replace('<<UPD>>', current_profile).replace('<<WORDS>>', str(profile_length))})
profile_conversation.append({'role': 'user', 'content': user_scratchpad})
profile = chatbot(profile_conversation)
save_file('user_profile.txt', profile)
# update main scratchpad
if len(all_messages) > 5:
all_messages.pop(0)
main_scratchpad = '\n\n'.join(all_messages).strip()
# Update the knowledge base
print('\n\nUpdating KB...')
if collection.count() == 0:
# yay first KB!
kb_convo = list()
kb_convo.append({'role': 'system', 'content': open_file('system_instantiate_new_kb.txt')})
kb_convo.append({'role': 'user', 'content': main_scratchpad})
article = chatbot(kb_convo)
new_id = str(uuid4())
collection.add(documents=[article],ids=[new_id])
save_file('db_logs/log_%s_add.txt' % time(), 'Added document %s:\n%s' % (new_id, article))
else:
results = collection.query(query_texts=[main_scratchpad], n_results=1)
kb = results['documents'][0][0]
kb_id = results['ids'][0][0]
# Expand current KB
kb_convo = list()
kb_convo.append({'role': 'system', 'content': open_file('system_update_existing_kb.txt').replace('<<KB>>', kb)})
kb_convo.append({'role': 'user', 'content': main_scratchpad})
article = chatbot(kb_convo)
collection.update(ids=[kb_id],documents=[article])
save_file('db_logs/log_%s_update.txt' % time(), 'Updated document %s:\n%s' % (kb_id, article))
# TODO - save more info in DB logs, probably as YAML file (original article, new info, final article)
# Split KB if too large
kb_len = len(article.split(' '))
if kb_len > 1000:
kb_convo = list()
kb_convo.append({'role': 'system', 'content': open_file('system_split_kb.txt')})
kb_convo.append({'role': 'user', 'content': article})
articles = chatbot(kb_convo).split('ARTICLE 2:')
a1 = articles[0].replace('ARTICLE 1:', '').strip()
a2 = articles[1].strip()
collection.update(ids=[kb_id],documents=[a1])
new_id = str(uuid4())
collection.add(documents=[a2],ids=[new_id])
save_file('db_logs/log_%s_split.txt' % time(), 'Split document %s, added %s:\n%s\n\n%s' % (kb_id, new_id, a1, a2))
chroma_client.persist()