_botex.env

# botex can be configured by 
#
#  - using the dialog of the command line interface `botex`,
#  - setting the required parameters via its function arguments, or
#  - setting the required parameters as environment variables.
#  
# You can use the file below to set the environment variables.
# For this, copy it to `botex.env` and edit the values.

# ___ DO NOT COMMIT 'botex.env' ___
# See https://pypi.org/project/python-dotenv/
# for more information on the file format.

# ------------------------------------------------------------------------------
# General configuration
# ------------------------------------------------------------------------------

# botex stores all its data in a SQLite database. You can set the path of the
# database file here. The respective file will be created if it does not exist. 

BOTEX_DB="botex.sqlite3"


# ------------------------------------------------------------------------------
# oTree configuration
# ------------------------------------------------------------------------------

# You can either configure botex to use an already running oTree instance 
# or let it start an instance for you.

# If you want to use an already running oTree instance, you need to set the
# URL endpoint of the server. The below is the oTree default.

OTREE_SERVER_URL='http://localhost:8000'


# If you want botex to start oTree for you, as we do in the tests,
# you need to set the path of your oTree project folder instead

# OTREE_PROJECT_PATH="tests/otree"

# You can then also change the default port of 8000 
# not to infer with any other oTree instances 

# OTREE_PORT=8000

# By default, botex make oTree log to a file 'otree.log' in the project folder.
# You can change this here.

# OTREE_LOG_FILE="otree.log"

# By default, botex mimics the bahavior of 'otree devserver' and starts 
# oTree without elevated authentication level. You can change this here 
# by setting oTree authentication level to either "DEMO" or "STUDY".

# OTREE_AUTH_LEVEL="STUDY"


# Regardless whether you use an already running oTree instance or let botex 
# start one for you, if you are using oTree in authentication levels 
# "DEMO" or "STUDY", you need to set an oTree REST key for botex to communicate 
# with the the oTree API.

# Also, you will need an oTree admin user name and password if you want to
# use botex to download oTree data via the oTree web frontend.

# If you let botex start oTree for you, it will configure oTree with the
# values that you set here.

# OTREE_REST_KEY="a fancy rest key"
# OTREE_ADMIN_PASSWORD="a fancy password"


# ------------------------------------------------------------------------------
# LiteLLM configuration
# ------------------------------------------------------------------------------

# You will need to configure the following section if you want to
# use commercial LLM APIs like OpenAI or Google Gemini via the 
# LiteLLM interface. This will apply to most use cases.

# For commercial LLM APIs, you need API keys.
# botex uses the environment variable system of LiteLLM to 
# send the API keys to the LLM servers.

OPENAI_API_KEY="akey"
GEMINI_API_KEY="akey"
# Add and edit API keys as needed.
# See https://docs.litellm.ai/docs/set_keys for more detail.


# ------------------------------------------------------------------------------
# llama.cpp configuration
# ------------------------------------------------------------------------------

# Everything below is only needed if you want to use llama.cpp for local LLMs 

# If you are accessing a running llama.cpp sever, you only need to set its URL 
# The below is the default if you start llama.cpp locally.

# LLAMA_SERVER_URL="http://localhost:8080"

# Instead, You can call botex.start_llamacpp_server() to start a llama.cpp 
# instance locally. For this you need to set at least the two following 
# arguments

LLAMACPP_SERVER_PATH="path/to/llama-server"
LLAMACPP_LOCAL_LLM_PATH="path/to/model.gguf"

# In this case, you should also configure the following if you have a GPU
# that you want llama.cpp to use.

LLAMACPP_NUMBER_OF_LAYERS_TO_OFFLOAD_TO_GPU=0

# You can also increase the number of slots for more parallelism if 
# you have plenty of GPU memory.

LLAMACPP_NUM_SLOTS=1

# The below are some additional llama.cpp settings that you can can use
# to configure llama.cpp if you let botex start the server. 
# The values below are the defaults that botex uses.

# LLAMACPP_CONTEXT_LENGTH=None # Uses the default of the respective LLM
# LLAMACPP_TEMPERATURE=0.7
# LLAMACPP_MAXIMUM_TOKENS_TO_PREDICT=10000