Files
OpenHands/opendevin/config.py
Robert Brennan 9fd7068204 Fix for setting LLM model, frontend settings refactor (#1169)
* simplify frontend settings management

* add debug info to llm.py

* always reinitialize agent

* remove old config stuff

* delint

* fix first initialize event

* refactor settings management

* remove logs

* change endpoint to remove litellm reference

* actually fix socket issues

* refactor a bit

* delint

* remove isFirstRun

* delint

* delint python

* fix export

* fix up socket handshake

* fix types

* fix lint errors

* delint

* fix test names

* moar lint

* fix build errors

* remove newline

* Update frontend/src/services/settingsService.test.ts

* Update frontend/src/services/settingsService.test.ts
2024-04-17 17:49:38 +00:00

87 lines
2.7 KiB
Python

import os
import argparse
import toml
from dotenv import load_dotenv
from opendevin.schema import ConfigType
load_dotenv()
DEFAULT_CONFIG: dict = {
ConfigType.LLM_API_KEY: None,
ConfigType.LLM_BASE_URL: None,
ConfigType.WORKSPACE_BASE: os.getcwd(),
ConfigType.WORKSPACE_MOUNT_PATH: None,
ConfigType.WORKSPACE_MOUNT_REWRITE: None,
ConfigType.LLM_MODEL: 'gpt-3.5-turbo-1106',
ConfigType.SANDBOX_CONTAINER_IMAGE: 'ghcr.io/opendevin/sandbox',
ConfigType.RUN_AS_DEVIN: 'true',
ConfigType.LLM_EMBEDDING_MODEL: 'local',
ConfigType.LLM_DEPLOYMENT_NAME: None,
ConfigType.LLM_API_VERSION: None,
ConfigType.LLM_NUM_RETRIES: 1,
ConfigType.LLM_COOLDOWN_TIME: 1,
ConfigType.MAX_ITERATIONS: 100,
# GPT-4 pricing is $10 per 1M input tokens. Since tokenization happens on LLM side,
# we cannot easily count number of tokens, but we can count characters.
# Assuming 5 characters per token, 5 million is a reasonable default limit.
ConfigType.MAX_CHARS: 5_000_000,
ConfigType.AGENT: 'MonologueAgent',
ConfigType.SANDBOX_TYPE: 'ssh',
ConfigType.USE_HOST_NETWORK: 'false',
ConfigType.SSH_HOSTNAME: 'localhost',
ConfigType.DISABLE_COLOR: 'false',
}
config_str = ''
if os.path.exists('config.toml'):
with open('config.toml', 'rb') as f:
config_str = f.read().decode('utf-8')
tomlConfig = toml.loads(config_str)
config = DEFAULT_CONFIG.copy()
for k, v in config.items():
if k in os.environ:
config[k] = os.environ[k]
elif k in tomlConfig:
config[k] = tomlConfig[k]
def parse_arguments():
parser = argparse.ArgumentParser(
description='Run an agent with a specific task')
parser.add_argument(
'-d',
'--directory',
type=str,
help='The working directory for the agent',
)
args, _ = parser.parse_known_args()
if args.directory:
config[ConfigType.WORKSPACE_BASE] = os.path.abspath(args.directory)
print(f'Setting workspace base to {config[ConfigType.WORKSPACE_BASE]}')
parse_arguments()
def finalize_config():
if config.get(ConfigType.WORKSPACE_MOUNT_REWRITE) and not config.get(ConfigType.WORKSPACE_MOUNT_PATH):
base = config.get(ConfigType.WORKSPACE_BASE) or os.getcwd()
parts = config[ConfigType.WORKSPACE_MOUNT_REWRITE].split(':')
config[ConfigType.WORKSPACE_MOUNT_PATH] = base.replace(parts[0], parts[1])
finalize_config()
def get(key: str, required: bool = False):
"""
Get a key from the environment variables or config.toml or default configs.
"""
value = config.get(key)
if not value and required:
raise KeyError(f"Please set '{key}' in `config.toml` or `.env`.")
return value