Configuration

Environment Variables

It's highly recommended that you have a DANDY_SETTINGS_MODULE in your environment variables pointed towards your dandy settings module.

export DANDY_SETTINGS_MODULE=dandy_settings

If no environment variable is set, it will look for dandy_settings module in the current working directory, python path or sys path.

Creating a Settings File

In the virtual environment you can run the dandy cli with no arguments to create a settings file.

dandy

The default settings file will be created where the environment variable DANDY_SETTINGS_MODULE is set to.

If it is not set the default will be dandy_settings in the current working directory.

Default Settings File

default_settings.py

from pathlib import Path
from typing_extensions import Union


ALLOW_DEBUG_RECORDING: bool = False

BASE_PATH: Union[Path, str] = Path.cwd()

DEFAULT_LLM_TEMPERATURE: float = 0.7
DEFAULT_LLM_SEED: int = 77
DEFAULT_LLM_RANDOMIZE_SEED: bool = False
DEFAULT_LLM_MAX_INPUT_TOKENS: int = 8000
DEFAULT_LLM_MAX_OUTPUT_TOKENS: int = 4000
DEFAULT_LLM_CONNECTION_RETRY_COUNT: int = 10
DEFAULT_LLM_PROMPT_RETRY_COUNT: int = 2
DEFAULT_LLM_REQUEST_TIMEOUT: Union[int, None] = None

LLM_CONFIGS = {
    # 'DEFAULT': {
    #     'TYPE': 'ollama',
    #     'HOST': os.getenv("OLLAMA_HOST"),
    #     'PORT': int(os.getenv("OLLAMA_PORT", 11434)),
    #     'API_KEY': os.getenv("OLLAMA_API_KEY"),
    #     'MODEL': 'llama3.1:8b-instruct-q4_K_M',
    #     'TEMPERATURE': 0.5,
    #     'SEED': 77,
    #     'RANDOMIZE_SEED': False,
    #     'MAX_INPUT_TOKENS': 8000,
    #     'MAX_OUTPUT_TOKENS': 4000
    # },
}

You can also copy the default settings file from Github at https://github.com/stratusadv/dandy/blob/main/dandy/default_settings.py.

Your Settings File

After configuring your settings, your file should look something like this.

dandy_settings.py

import os
from pathlib import Path
from typing import Union

# This is used for controlling the debug recorder in development and should be set to false in production

ALLOW_DEBUG_RECORDING = True

# You should set this to the root directory of your project the default will be the current working directory

BASE_PATH = Path.resolve(Path(__file__)).parent

# These will override the default settings in the dandy settings module

# DEFAULT_LLM_TEMPERATURE: float = 0.7
# DEFAULT_LLM_SEED: int = 77
# DEFAULT_LLM_RANDOMIZE_SEED: bool = False
# DEFAULT_LLM_MAX_INPUT_TOKENS: int = 8000
# DEFAULT_LLM_MAX_OUTPUT_TOKENS: int = 4000
# DEFAULT_LLM_CONNECTION_RETRY_COUNT: int = 10
# DEFAULT_LLM_PROMPT_RETRY_COUNT: int = 2
# DEFAULT_LLM_REQUEST_TIMEOUT: Union[int, None] = None

# These are some example LLM configs you may only need one of these, you must have a "DEFAULT" LLM config

LLM_CONFIGS = {
    'DEFAULT': {
        'TYPE': 'ollama',
        'HOST': os.getenv("OLLAMA_HOST"),
        'PORT': int(os.getenv("OLLAMA_PORT", 11434)),
        'API_KEY': os.getenv("OLLAMA_API_KEY"),
        'MODEL': 'qwen2.5-coder:14b-instruct-q4_K_M',
        'TEMPERATURE': 0.0,
        'MAX_INPUT_TOKENS': 16000,
        'MAX_OUTPUT_TOKENS': 16000,
    },
    'LLAMA_3_1_8B': {
        # the default "TYPE", "HOST", "PORT" AND "API_KEY" from the "DEFAULT" config will flow to this config

        'MODEL': 'llama3.1:8b-instruct-q4_K_M',

        # You can override any of the default settings for each LLM config
        'MAX_INPUT_TOKENS': 16000,
        'MAX_OUTPUT_TOKENS': 16000,
    },
    'PHI_4_14B': {
        'MODEL': 'phi4:14b-q4_K_M',
    },
    'DEEPSEEK_R1_14B': {
        'MODEL': 'deepseek-r1:14b',
    },
    'GPT_3_5_TURBO': {
        'TYPE': 'openai',
        'HOST': os.getenv("OPENAI_HOST"),
        'PORT': int(os.getenv("OPENAI_PORT", 443)),
        'API_KEY': os.getenv("OPEN_API_KEY"),
        'MODEL': 'gpt-3.5-turbo',
    },
}