aljaz/Auto-GPT
1
0
Fork 0
mirror of https://github.com/aljazceru/Auto-GPT.git synced 2025-12-18 06:24:20 +01:00
Code Issues Packages Projects Releases Wiki Activity

feat(global): errors logs are logged as debug level and activated with program argument 'debug'

Browse Source
This commit is contained in:
Fabrice Hong
2023-04-08 01:05:08 +02:00
parent 0e004f5c14
commit 43c006d71c
5 changed files with 148 additions and 26 deletions
Download Patch File Download Diff File Expand all files Collapse all files

33
scripts/chat.py
View File

@@ -4,6 +4,8 @@ from dotenv import load_dotenv
from config import Config
import token_counter
from llm_utils import create_chat_completion
from logger import logger
import logging
cfg = Config()
@@ -64,15 +66,12 @@ def chat_with_ai(
model = cfg.fast_llm_model # TODO: Change model from hardcode to argument
# Reserve 1000 tokens for the response
if cfg.debug_mode:
print(f"Token limit: {token_limit}")
logger.log(content=f"Token limit: {token_limit}", level=logging.DEBUG)
send_token_limit = token_limit - 1000
relevant_memory = permanent_memory.get_relevant(str(full_message_history[-9:]), 10)
if cfg.debug_mode:
print('Memory Stats: ', permanent_memory.get_stats())
logger.log(content=f'Memory Stats: {permanent_memory.get_stats()}', level=logging.DEBUG)
next_message_to_add_index, current_tokens_used, insertion_index, current_context = generate_context(
prompt, relevant_memory, full_message_history, model)
@@ -110,19 +109,17 @@ def chat_with_ai(
# assert tokens_remaining >= 0, "Tokens remaining is negative. This should never happen, please submit a bug report at https://www.github.com/Torantulino/Auto-GPT"
# Debug print the current context
if cfg.debug_mode:
print(f"Token limit: {token_limit}")
print(f"Send Token Count: {current_tokens_used}")
print(f"Tokens remaining for response: {tokens_remaining}")
print("------------ CONTEXT SENT TO AI ---------------")
for message in current_context:
# Skip printing the prompt
if message["role"] == "system" and message["content"] == prompt:
continue
print(
f"{message['role'].capitalize()}: {message['content']}")
print()
print("----------- END OF CONTEXT ----------------")
logger.log(content=f"Token limit: {token_limit}", level=logging.DEBUG)
logger.log(content=f"Send Token Count: {current_tokens_used}", level=logging.DEBUG)
logger.log(content=f"Tokens remaining for response: {tokens_remaining}", level=logging.DEBUG)
logger.log(content="------------ CONTEXT SENT TO AI ---------------", level=logging.DEBUG)
for message in current_context:
# Skip printing the prompt
if message["role"] == "system" and message["content"] == prompt:
continue
logger.log(content=f"{message['role'].capitalize()}: {message['content']}", level=logging.DEBUG)
logger.log(content="", level=logging.DEBUG)
logger.log(content="----------- END OF CONTEXT ----------------", level=logging.DEBUG)
# TODO: use a model defined elsewhere, so that model can contain temperature and other settings we care about
assistant_reply = create_chat_completion(