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2cd1207e73
open-webui/backend/config.py
Pascal Lim c386d0b1a5 sort and fix backend imports
2024-08-30 22:26:22 +02:00

1497 lines
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Python
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import json
import logging
import os
import shutil
from datetime import datetime
from pathlib import Path
from typing import Generic, Optional, TypeVar
from urllib.parse import urlparse
import chromadb
import requests
import yaml
from apps.webui.internal.db import Base, get_db
from chromadb import Settings
from env import (
BACKEND_DIR,
CONFIG_DATA,
DATA_DIR,
ENV,
FRONTEND_BUILD_DIR,
WEBUI_AUTH,
WEBUI_FAVICON_URL,
WEBUI_NAME,
log,
)
from pydantic import BaseModel
from sqlalchemy import JSON, Column, DateTime, Integer, func
class EndpointFilter(logging.Filter):
def filter(self, record: logging.LogRecord) -> bool:
return record.getMessage().find("/health") == -1
# Filter out /endpoint
logging.getLogger("uvicorn.access").addFilter(EndpointFilter())
####################################
# Config helpers
####################################
# Function to run the alembic migrations
def run_migrations():
print("Running migrations")
try:
from alembic import command
from alembic.config import Config
alembic_cfg = Config(BACKEND_DIR / "alembic.ini")
command.upgrade(alembic_cfg, "head")
except Exception as e:
print(f"Error: {e}")
run_migrations()
class Config(Base):
__tablename__ = "config"
id = Column(Integer, primary_key=True)
data = Column(JSON, nullable=False)
version = Column(Integer, nullable=False, default=0)
created_at = Column(DateTime, nullable=False, server_default=func.now())
updated_at = Column(DateTime, nullable=True, onupdate=func.now())
def load_json_config():
with open(f"{DATA_DIR}/config.json", "r") as file:
return json.load(file)
def save_to_db(data):
with get_db() as db:
existing_config = db.query(Config).first()
if not existing_config:
new_config = Config(data=data, version=0)
db.add(new_config)
else:
existing_config.data = data
existing_config.updated_at = datetime.now()
db.add(existing_config)
db.commit()
# When initializing, check if config.json exists and migrate it to the database
if os.path.exists(f"{DATA_DIR}/config.json"):
data = load_json_config()
save_to_db(data)
os.rename(f"{DATA_DIR}/config.json", f"{DATA_DIR}/old_config.json")
def save_config():
try:
with open(f"{DATA_DIR}/config.json", "w") as f:
json.dump(CONFIG_DATA, f, indent="\t")
except Exception as e:
log.exception(e)
DEFAULT_CONFIG = {
"version": 0,
"ui": {
"default_locale": "",
"prompt_suggestions": [
{
"title": [
"Help me study",
"vocabulary for a college entrance exam",
],
"content": "Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option.",
},
{
"title": [
"Give me ideas",
"for what to do with my kids' art",
],
"content": "What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter.",
},
{
"title": ["Tell me a fun fact", "about the Roman Empire"],
"content": "Tell me a random fun fact about the Roman Empire",
},
{
"title": [
"Show me a code snippet",
"of a website's sticky header",
],
"content": "Show me a code snippet of a website's sticky header in CSS and JavaScript.",
},
{
"title": [
"Explain options trading",
"if I'm familiar with buying and selling stocks",
],
"content": "Explain options trading in simple terms if I'm familiar with buying and selling stocks.",
},
{
"title": ["Overcome procrastination", "give me tips"],
"content": "Could you start by asking me about instances when I procrastinate the most and then give me some suggestions to overcome it?",
},
{
"title": [
"Grammar check",
"rewrite it for better readability ",
],
"content": 'Check the following sentence for grammar and clarity: "[sentence]". Rewrite it for better readability while maintaining its original meaning.',
},
],
},
}
def get_config():
with get_db() as db:
config_entry = db.query(Config).order_by(Config.id.desc()).first()
return config_entry.data if config_entry else DEFAULT_CONFIG
CONFIG_DATA = get_config()
def get_config_value(config_path: str):
path_parts = config_path.split(".")
cur_config = CONFIG_DATA
for key in path_parts:
if key in cur_config:
cur_config = cur_config[key]
else:
return None
return cur_config
T = TypeVar("T")
class PersistentConfig(Generic[T]):
def __init__(self, env_name: str, config_path: str, env_value: T):
self.env_name = env_name
self.config_path = config_path
self.env_value = env_value
self.config_value = get_config_value(config_path)
if self.config_value is not None:
log.info(f"'{env_name}' loaded from the latest database entry")
self.value = self.config_value
else:
self.value = env_value
def __str__(self):
return str(self.value)
@property
def __dict__(self):
raise TypeError(
"PersistentConfig object cannot be converted to dict, use config_get or .value instead."
)
def __getattribute__(self, item):
if item == "__dict__":
raise TypeError(
"PersistentConfig object cannot be converted to dict, use config_get or .value instead."
)
return super().__getattribute__(item)
def save(self):
log.info(f"Saving '{self.env_name}' to the database")
path_parts = self.config_path.split(".")
sub_config = CONFIG_DATA
for key in path_parts[:-1]:
if key not in sub_config:
sub_config[key] = {}
sub_config = sub_config[key]
sub_config[path_parts[-1]] = self.value
save_to_db(CONFIG_DATA)
self.config_value = self.value
class AppConfig:
_state: dict[str, PersistentConfig]
def __init__(self):
super().__setattr__("_state", {})
def __setattr__(self, key, value):
if isinstance(value, PersistentConfig):
self._state[key] = value
else:
self._state[key].value = value
self._state[key].save()
def __getattr__(self, key):
return self._state[key].value
####################################
# WEBUI_AUTH (Required for security)
####################################
JWT_EXPIRES_IN = PersistentConfig(
"JWT_EXPIRES_IN", "auth.jwt_expiry", os.environ.get("JWT_EXPIRES_IN", "-1")
)
####################################
# OAuth config
####################################
ENABLE_OAUTH_SIGNUP = PersistentConfig(
"ENABLE_OAUTH_SIGNUP",
"oauth.enable_signup",
os.environ.get("ENABLE_OAUTH_SIGNUP", "False").lower() == "true",
)
OAUTH_MERGE_ACCOUNTS_BY_EMAIL = PersistentConfig(
"OAUTH_MERGE_ACCOUNTS_BY_EMAIL",
"oauth.merge_accounts_by_email",
os.environ.get("OAUTH_MERGE_ACCOUNTS_BY_EMAIL", "False").lower() == "true",
)
OAUTH_PROVIDERS = {}
GOOGLE_CLIENT_ID = PersistentConfig(
"GOOGLE_CLIENT_ID",
"oauth.google.client_id",
os.environ.get("GOOGLE_CLIENT_ID", ""),
)
GOOGLE_CLIENT_SECRET = PersistentConfig(
"GOOGLE_CLIENT_SECRET",
"oauth.google.client_secret",
os.environ.get("GOOGLE_CLIENT_SECRET", ""),
)
GOOGLE_OAUTH_SCOPE = PersistentConfig(
"GOOGLE_OAUTH_SCOPE",
"oauth.google.scope",
os.environ.get("GOOGLE_OAUTH_SCOPE", "openid email profile"),
)
GOOGLE_REDIRECT_URI = PersistentConfig(
"GOOGLE_REDIRECT_URI",
"oauth.google.redirect_uri",
os.environ.get("GOOGLE_REDIRECT_URI", ""),
)
MICROSOFT_CLIENT_ID = PersistentConfig(
"MICROSOFT_CLIENT_ID",
"oauth.microsoft.client_id",
os.environ.get("MICROSOFT_CLIENT_ID", ""),
)
MICROSOFT_CLIENT_SECRET = PersistentConfig(
"MICROSOFT_CLIENT_SECRET",
"oauth.microsoft.client_secret",
os.environ.get("MICROSOFT_CLIENT_SECRET", ""),
)
MICROSOFT_CLIENT_TENANT_ID = PersistentConfig(
"MICROSOFT_CLIENT_TENANT_ID",
"oauth.microsoft.tenant_id",
os.environ.get("MICROSOFT_CLIENT_TENANT_ID", ""),
)
MICROSOFT_OAUTH_SCOPE = PersistentConfig(
"MICROSOFT_OAUTH_SCOPE",
"oauth.microsoft.scope",
os.environ.get("MICROSOFT_OAUTH_SCOPE", "openid email profile"),
)
MICROSOFT_REDIRECT_URI = PersistentConfig(
"MICROSOFT_REDIRECT_URI",
"oauth.microsoft.redirect_uri",
os.environ.get("MICROSOFT_REDIRECT_URI", ""),
)
OAUTH_CLIENT_ID = PersistentConfig(
"OAUTH_CLIENT_ID",
"oauth.oidc.client_id",
os.environ.get("OAUTH_CLIENT_ID", ""),
)
OAUTH_CLIENT_SECRET = PersistentConfig(
"OAUTH_CLIENT_SECRET",
"oauth.oidc.client_secret",
os.environ.get("OAUTH_CLIENT_SECRET", ""),
)
OPENID_PROVIDER_URL = PersistentConfig(
"OPENID_PROVIDER_URL",
"oauth.oidc.provider_url",
os.environ.get("OPENID_PROVIDER_URL", ""),
)
OPENID_REDIRECT_URI = PersistentConfig(
"OPENID_REDIRECT_URI",
"oauth.oidc.redirect_uri",
os.environ.get("OPENID_REDIRECT_URI", ""),
)
OAUTH_SCOPES = PersistentConfig(
"OAUTH_SCOPES",
"oauth.oidc.scopes",
os.environ.get("OAUTH_SCOPES", "openid email profile"),
)
OAUTH_PROVIDER_NAME = PersistentConfig(
"OAUTH_PROVIDER_NAME",
"oauth.oidc.provider_name",
os.environ.get("OAUTH_PROVIDER_NAME", "SSO"),
)
OAUTH_USERNAME_CLAIM = PersistentConfig(
"OAUTH_USERNAME_CLAIM",
"oauth.oidc.username_claim",
os.environ.get("OAUTH_USERNAME_CLAIM", "name"),
)
OAUTH_PICTURE_CLAIM = PersistentConfig(
"OAUTH_USERNAME_CLAIM",
"oauth.oidc.avatar_claim",
os.environ.get("OAUTH_PICTURE_CLAIM", "picture"),
)
OAUTH_EMAIL_CLAIM = PersistentConfig(
"OAUTH_EMAIL_CLAIM",
"oauth.oidc.email_claim",
os.environ.get("OAUTH_EMAIL_CLAIM", "email"),
)
def load_oauth_providers():
OAUTH_PROVIDERS.clear()
if GOOGLE_CLIENT_ID.value and GOOGLE_CLIENT_SECRET.value:
OAUTH_PROVIDERS["google"] = {
"client_id": GOOGLE_CLIENT_ID.value,
"client_secret": GOOGLE_CLIENT_SECRET.value,
"server_metadata_url": "https://accounts.google.com/.well-known/openid-configuration",
"scope": GOOGLE_OAUTH_SCOPE.value,
"redirect_uri": GOOGLE_REDIRECT_URI.value,
}
if (
MICROSOFT_CLIENT_ID.value
and MICROSOFT_CLIENT_SECRET.value
and MICROSOFT_CLIENT_TENANT_ID.value
):
OAUTH_PROVIDERS["microsoft"] = {
"client_id": MICROSOFT_CLIENT_ID.value,
"client_secret": MICROSOFT_CLIENT_SECRET.value,
"server_metadata_url": f"https://login.microsoftonline.com/{MICROSOFT_CLIENT_TENANT_ID.value}/v2.0/.well-known/openid-configuration",
"scope": MICROSOFT_OAUTH_SCOPE.value,
"redirect_uri": MICROSOFT_REDIRECT_URI.value,
}
if (
OAUTH_CLIENT_ID.value
and OAUTH_CLIENT_SECRET.value
and OPENID_PROVIDER_URL.value
):
OAUTH_PROVIDERS["oidc"] = {
"client_id": OAUTH_CLIENT_ID.value,
"client_secret": OAUTH_CLIENT_SECRET.value,
"server_metadata_url": OPENID_PROVIDER_URL.value,
"scope": OAUTH_SCOPES.value,
"name": OAUTH_PROVIDER_NAME.value,
"redirect_uri": OPENID_REDIRECT_URI.value,
}
load_oauth_providers()
####################################
# Static DIR
####################################
STATIC_DIR = Path(os.getenv("STATIC_DIR", BACKEND_DIR / "static")).resolve()
frontend_favicon = FRONTEND_BUILD_DIR / "static" / "favicon.png"
if frontend_favicon.exists():
try:
shutil.copyfile(frontend_favicon, STATIC_DIR / "favicon.png")
except Exception as e:
logging.error(f"An error occurred: {e}")
else:
logging.warning(f"Frontend favicon not found at {frontend_favicon}")
frontend_splash = FRONTEND_BUILD_DIR / "static" / "splash.png"
if frontend_splash.exists():
try:
shutil.copyfile(frontend_splash, STATIC_DIR / "splash.png")
except Exception as e:
logging.error(f"An error occurred: {e}")
else:
logging.warning(f"Frontend splash not found at {frontend_splash}")
####################################
# CUSTOM_NAME
####################################
CUSTOM_NAME = os.environ.get("CUSTOM_NAME", "")
if CUSTOM_NAME:
try:
r = requests.get(f"https://api.openwebui.com/api/v1/custom/{CUSTOM_NAME}")
data = r.json()
if r.ok:
if "logo" in data:
WEBUI_FAVICON_URL = url = (
f"https://api.openwebui.com{data['logo']}"
if data["logo"][0] == "/"
else data["logo"]
)
r = requests.get(url, stream=True)
if r.status_code == 200:
with open(f"{STATIC_DIR}/favicon.png", "wb") as f:
r.raw.decode_content = True
shutil.copyfileobj(r.raw, f)
if "splash" in data:
url = (
f"https://api.openwebui.com{data['splash']}"
if data["splash"][0] == "/"
else data["splash"]
)
r = requests.get(url, stream=True)
if r.status_code == 200:
with open(f"{STATIC_DIR}/splash.png", "wb") as f:
r.raw.decode_content = True
shutil.copyfileobj(r.raw, f)
WEBUI_NAME = data["name"]
except Exception as e:
log.exception(e)
pass
####################################
# File Upload DIR
####################################
UPLOAD_DIR = f"{DATA_DIR}/uploads"
Path(UPLOAD_DIR).mkdir(parents=True, exist_ok=True)
####################################
# Cache DIR
####################################
CACHE_DIR = f"{DATA_DIR}/cache"
Path(CACHE_DIR).mkdir(parents=True, exist_ok=True)
####################################
# Docs DIR
####################################
DOCS_DIR = os.getenv("DOCS_DIR", f"{DATA_DIR}/docs")
Path(DOCS_DIR).mkdir(parents=True, exist_ok=True)
####################################
# Tools DIR
####################################
TOOLS_DIR = os.getenv("TOOLS_DIR", f"{DATA_DIR}/tools")
Path(TOOLS_DIR).mkdir(parents=True, exist_ok=True)
####################################
# Functions DIR
####################################
FUNCTIONS_DIR = os.getenv("FUNCTIONS_DIR", f"{DATA_DIR}/functions")
Path(FUNCTIONS_DIR).mkdir(parents=True, exist_ok=True)
####################################
# LITELLM_CONFIG
####################################
def create_config_file(file_path):
directory = os.path.dirname(file_path)
# Check if directory exists, if not, create it
if not os.path.exists(directory):
os.makedirs(directory)
# Data to write into the YAML file
config_data = {
"general_settings": {},
"litellm_settings": {},
"model_list": [],
"router_settings": {},
}
# Write data to YAML file
with open(file_path, "w") as file:
yaml.dump(config_data, file)
LITELLM_CONFIG_PATH = f"{DATA_DIR}/litellm/config.yaml"
# if not os.path.exists(LITELLM_CONFIG_PATH):
# log.info("Config file doesn't exist. Creating...")
# create_config_file(LITELLM_CONFIG_PATH)
# log.info("Config file created successfully.")
####################################
# OLLAMA_BASE_URL
####################################
ENABLE_OLLAMA_API = PersistentConfig(
"ENABLE_OLLAMA_API",
"ollama.enable",
os.environ.get("ENABLE_OLLAMA_API", "True").lower() == "true",
)
OLLAMA_API_BASE_URL = os.environ.get(
"OLLAMA_API_BASE_URL", "http://localhost:11434/api"
)
OLLAMA_BASE_URL = os.environ.get("OLLAMA_BASE_URL", "")
AIOHTTP_CLIENT_TIMEOUT = os.environ.get("AIOHTTP_CLIENT_TIMEOUT", "")
if AIOHTTP_CLIENT_TIMEOUT == "":
AIOHTTP_CLIENT_TIMEOUT = None
else:
try:
AIOHTTP_CLIENT_TIMEOUT = int(AIOHTTP_CLIENT_TIMEOUT)
except Exception:
AIOHTTP_CLIENT_TIMEOUT = 300
K8S_FLAG = os.environ.get("K8S_FLAG", "")
USE_OLLAMA_DOCKER = os.environ.get("USE_OLLAMA_DOCKER", "false")
if OLLAMA_BASE_URL == "" and OLLAMA_API_BASE_URL != "":
OLLAMA_BASE_URL = (
OLLAMA_API_BASE_URL[:-4]
if OLLAMA_API_BASE_URL.endswith("/api")
else OLLAMA_API_BASE_URL
)
if ENV == "prod":
if OLLAMA_BASE_URL == "/ollama" and not K8S_FLAG:
if USE_OLLAMA_DOCKER.lower() == "true":
# if you use all-in-one docker container (Open WebUI + Ollama)
# with the docker build arg USE_OLLAMA=true (--build-arg="USE_OLLAMA=true") this only works with http://localhost:11434
OLLAMA_BASE_URL = "http://localhost:11434"
else:
OLLAMA_BASE_URL = "http://host.docker.internal:11434"
elif K8S_FLAG:
OLLAMA_BASE_URL = "http://ollama-service.open-webui.svc.cluster.local:11434"
OLLAMA_BASE_URLS = os.environ.get("OLLAMA_BASE_URLS", "")
OLLAMA_BASE_URLS = OLLAMA_BASE_URLS if OLLAMA_BASE_URLS != "" else OLLAMA_BASE_URL
OLLAMA_BASE_URLS = [url.strip() for url in OLLAMA_BASE_URLS.split(";")]
OLLAMA_BASE_URLS = PersistentConfig(
"OLLAMA_BASE_URLS", "ollama.base_urls", OLLAMA_BASE_URLS
)
####################################
# OPENAI_API
####################################
ENABLE_OPENAI_API = PersistentConfig(
"ENABLE_OPENAI_API",
"openai.enable",
os.environ.get("ENABLE_OPENAI_API", "True").lower() == "true",
)
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", "")
OPENAI_API_BASE_URL = os.environ.get("OPENAI_API_BASE_URL", "")
if OPENAI_API_BASE_URL == "":
OPENAI_API_BASE_URL = "https://api.openai.com/v1"
OPENAI_API_KEYS = os.environ.get("OPENAI_API_KEYS", "")
OPENAI_API_KEYS = OPENAI_API_KEYS if OPENAI_API_KEYS != "" else OPENAI_API_KEY
OPENAI_API_KEYS = [url.strip() for url in OPENAI_API_KEYS.split(";")]
OPENAI_API_KEYS = PersistentConfig(
"OPENAI_API_KEYS", "openai.api_keys", OPENAI_API_KEYS
)
OPENAI_API_BASE_URLS = os.environ.get("OPENAI_API_BASE_URLS", "")
OPENAI_API_BASE_URLS = (
OPENAI_API_BASE_URLS if OPENAI_API_BASE_URLS != "" else OPENAI_API_BASE_URL
)
OPENAI_API_BASE_URLS = [
url.strip() if url != "" else "https://api.openai.com/v1"
for url in OPENAI_API_BASE_URLS.split(";")
]
OPENAI_API_BASE_URLS = PersistentConfig(
"OPENAI_API_BASE_URLS", "openai.api_base_urls", OPENAI_API_BASE_URLS
)
OPENAI_API_KEY = ""
try:
OPENAI_API_KEY = OPENAI_API_KEYS.value[
OPENAI_API_BASE_URLS.value.index("https://api.openai.com/v1")
]
except Exception:
pass
OPENAI_API_BASE_URL = "https://api.openai.com/v1"
####################################
# WEBUI
####################################
ENABLE_SIGNUP = PersistentConfig(
"ENABLE_SIGNUP",
"ui.enable_signup",
(
False
if not WEBUI_AUTH
else os.environ.get("ENABLE_SIGNUP", "True").lower() == "true"
),
)
ENABLE_LOGIN_FORM = PersistentConfig(
"ENABLE_LOGIN_FORM",
"ui.ENABLE_LOGIN_FORM",
os.environ.get("ENABLE_LOGIN_FORM", "True").lower() == "true",
)
DEFAULT_LOCALE = PersistentConfig(
"DEFAULT_LOCALE",
"ui.default_locale",
os.environ.get("DEFAULT_LOCALE", ""),
)
DEFAULT_MODELS = PersistentConfig(
"DEFAULT_MODELS", "ui.default_models", os.environ.get("DEFAULT_MODELS", None)
)
DEFAULT_PROMPT_SUGGESTIONS = PersistentConfig(
"DEFAULT_PROMPT_SUGGESTIONS",
"ui.prompt_suggestions",
[
{
"title": ["Help me study", "vocabulary for a college entrance exam"],
"content": "Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option.",
},
{
"title": ["Give me ideas", "for what to do with my kids' art"],
"content": "What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter.",
},
{
"title": ["Tell me a fun fact", "about the Roman Empire"],
"content": "Tell me a random fun fact about the Roman Empire",
},
{
"title": ["Show me a code snippet", "of a website's sticky header"],
"content": "Show me a code snippet of a website's sticky header in CSS and JavaScript.",
},
{
"title": [
"Explain options trading",
"if I'm familiar with buying and selling stocks",
],
"content": "Explain options trading in simple terms if I'm familiar with buying and selling stocks.",
},
{
"title": ["Overcome procrastination", "give me tips"],
"content": "Could you start by asking me about instances when I procrastinate the most and then give me some suggestions to overcome it?",
},
],
)
DEFAULT_USER_ROLE = PersistentConfig(
"DEFAULT_USER_ROLE",
"ui.default_user_role",
os.getenv("DEFAULT_USER_ROLE", "pending"),
)
USER_PERMISSIONS_CHAT_DELETION = (
os.environ.get("USER_PERMISSIONS_CHAT_DELETION", "True").lower() == "true"
)
USER_PERMISSIONS_CHAT_EDITING = (
os.environ.get("USER_PERMISSIONS_CHAT_EDITING", "True").lower() == "true"
)
USER_PERMISSIONS_CHAT_TEMPORARY = (
os.environ.get("USER_PERMISSIONS_CHAT_TEMPORARY", "True").lower() == "true"
)
USER_PERMISSIONS = PersistentConfig(
"USER_PERMISSIONS",
"ui.user_permissions",
{
"chat": {
"deletion": USER_PERMISSIONS_CHAT_DELETION,
"editing": USER_PERMISSIONS_CHAT_EDITING,
"temporary": USER_PERMISSIONS_CHAT_TEMPORARY,
}
},
)
ENABLE_MODEL_FILTER = PersistentConfig(
"ENABLE_MODEL_FILTER",
"model_filter.enable",
os.environ.get("ENABLE_MODEL_FILTER", "False").lower() == "true",
)
MODEL_FILTER_LIST = os.environ.get("MODEL_FILTER_LIST", "")
MODEL_FILTER_LIST = PersistentConfig(
"MODEL_FILTER_LIST",
"model_filter.list",
[model.strip() for model in MODEL_FILTER_LIST.split(";")],
)
WEBHOOK_URL = PersistentConfig(
"WEBHOOK_URL", "webhook_url", os.environ.get("WEBHOOK_URL", "")
)
ENABLE_ADMIN_EXPORT = os.environ.get("ENABLE_ADMIN_EXPORT", "True").lower() == "true"
ENABLE_ADMIN_CHAT_ACCESS = (
os.environ.get("ENABLE_ADMIN_CHAT_ACCESS", "True").lower() == "true"
)
ENABLE_COMMUNITY_SHARING = PersistentConfig(
"ENABLE_COMMUNITY_SHARING",
"ui.enable_community_sharing",
os.environ.get("ENABLE_COMMUNITY_SHARING", "True").lower() == "true",
)
ENABLE_MESSAGE_RATING = PersistentConfig(
"ENABLE_MESSAGE_RATING",
"ui.enable_message_rating",
os.environ.get("ENABLE_MESSAGE_RATING", "True").lower() == "true",
)
def validate_cors_origins(origins):
for origin in origins:
if origin != "*":
validate_cors_origin(origin)
def validate_cors_origin(origin):
parsed_url = urlparse(origin)
# Check if the scheme is either http or https
if parsed_url.scheme not in ["http", "https"]:
raise ValueError(
f"Invalid scheme in CORS_ALLOW_ORIGIN: '{origin}'. Only 'http' and 'https' are allowed."
)
# Ensure that the netloc (domain + port) is present, indicating it's a valid URL
if not parsed_url.netloc:
raise ValueError(f"Invalid URL structure in CORS_ALLOW_ORIGIN: '{origin}'.")
# For production, you should only need one host as
# fastapi serves the svelte-kit built frontend and backend from the same host and port.
# To test CORS_ALLOW_ORIGIN locally, you can set something like
# CORS_ALLOW_ORIGIN=http://localhost:5173;http://localhost:8080
# in your .env file depending on your frontend port, 5173 in this case.
CORS_ALLOW_ORIGIN = os.environ.get("CORS_ALLOW_ORIGIN", "*").split(";")
if "*" in CORS_ALLOW_ORIGIN:
log.warning(
"\n\nWARNING: CORS_ALLOW_ORIGIN IS SET TO '*' - NOT RECOMMENDED FOR PRODUCTION DEPLOYMENTS.\n"
)
validate_cors_origins(CORS_ALLOW_ORIGIN)
class BannerModel(BaseModel):
id: str
type: str
title: Optional[str] = None
content: str
dismissible: bool
timestamp: int
try:
banners = json.loads(os.environ.get("WEBUI_BANNERS", "[]"))
banners = [BannerModel(**banner) for banner in banners]
except Exception as e:
print(f"Error loading WEBUI_BANNERS: {e}")
banners = []
WEBUI_BANNERS = PersistentConfig("WEBUI_BANNERS", "ui.banners", banners)
SHOW_ADMIN_DETAILS = PersistentConfig(
"SHOW_ADMIN_DETAILS",
"auth.admin.show",
os.environ.get("SHOW_ADMIN_DETAILS", "true").lower() == "true",
)
ADMIN_EMAIL = PersistentConfig(
"ADMIN_EMAIL",
"auth.admin.email",
os.environ.get("ADMIN_EMAIL", None),
)
####################################
# TASKS
####################################
TASK_MODEL = PersistentConfig(
"TASK_MODEL",
"task.model.default",
os.environ.get("TASK_MODEL", ""),
)
TASK_MODEL_EXTERNAL = PersistentConfig(
"TASK_MODEL_EXTERNAL",
"task.model.external",
os.environ.get("TASK_MODEL_EXTERNAL", ""),
)
TITLE_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
"TITLE_GENERATION_PROMPT_TEMPLATE",
"task.title.prompt_template",
os.environ.get(
"TITLE_GENERATION_PROMPT_TEMPLATE",
"""Create a concise, 3-5 word title with an emoji as a title for the prompt in the given language. Suitable Emojis for the summary can be used to enhance understanding but avoid quotation marks or special formatting. RESPOND ONLY WITH THE TITLE TEXT.
Examples of titles:
📉 Stock Market Trends
🍪 Perfect Chocolate Chip Recipe
Evolution of Music Streaming
Remote Work Productivity Tips
Artificial Intelligence in Healthcare
🎮 Video Game Development Insights
Prompt: {{prompt:middletruncate:8000}}""",
),
)
SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
"SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE",
"task.search.prompt_template",
os.environ.get(
"SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE",
"""You are tasked with generating web search queries. Give me an appropriate query to answer my question for google search. Answer with only the query. Today is {{CURRENT_DATE}}.
Question:
{{prompt:end:4000}}""",
),
)
SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = PersistentConfig(
"SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD",
"task.search.prompt_length_threshold",
int(
os.environ.get(
"SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD",
100,
)
),
)
TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = PersistentConfig(
"TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE",
"task.tools.prompt_template",
os.environ.get(
"TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE",
"""Available Tools: {{TOOLS}}\nReturn an empty string if no tools match the query. If a function tool matches, construct and return a JSON object in the format {\"name\": \"functionName\", \"parameters\": {\"requiredFunctionParamKey\": \"requiredFunctionParamValue\"}} using the appropriate tool and its parameters. Only return the object and limit the response to the JSON object without additional text.""",
),
)
####################################
# RAG document content extraction
####################################
CONTENT_EXTRACTION_ENGINE = PersistentConfig(
"CONTENT_EXTRACTION_ENGINE",
"rag.CONTENT_EXTRACTION_ENGINE",
os.environ.get("CONTENT_EXTRACTION_ENGINE", "").lower(),
)
TIKA_SERVER_URL = PersistentConfig(
"TIKA_SERVER_URL",
"rag.tika_server_url",
os.getenv("TIKA_SERVER_URL", "http://tika:9998"), # Default for sidecar deployment
)
####################################
# RAG
####################################
CHROMA_DATA_PATH = f"{DATA_DIR}/vector_db"
CHROMA_TENANT = os.environ.get("CHROMA_TENANT", chromadb.DEFAULT_TENANT)
CHROMA_DATABASE = os.environ.get("CHROMA_DATABASE", chromadb.DEFAULT_DATABASE)
CHROMA_HTTP_HOST = os.environ.get("CHROMA_HTTP_HOST", "")
CHROMA_HTTP_PORT = int(os.environ.get("CHROMA_HTTP_PORT", "8000"))
# Comma-separated list of header=value pairs
CHROMA_HTTP_HEADERS = os.environ.get("CHROMA_HTTP_HEADERS", "")
if CHROMA_HTTP_HEADERS:
CHROMA_HTTP_HEADERS = dict(
[pair.split("=") for pair in CHROMA_HTTP_HEADERS.split(",")]
)
else:
CHROMA_HTTP_HEADERS = None
CHROMA_HTTP_SSL = os.environ.get("CHROMA_HTTP_SSL", "false").lower() == "true"
# this uses the model defined in the Dockerfile ENV variable. If you dont use docker or docker based deployments such as k8s, the default embedding model will be used (sentence-transformers/all-MiniLM-L6-v2)
RAG_TOP_K = PersistentConfig(
"RAG_TOP_K", "rag.top_k", int(os.environ.get("RAG_TOP_K", "5"))
)
RAG_RELEVANCE_THRESHOLD = PersistentConfig(
"RAG_RELEVANCE_THRESHOLD",
"rag.relevance_threshold",
float(os.environ.get("RAG_RELEVANCE_THRESHOLD", "0.0")),
)
ENABLE_RAG_HYBRID_SEARCH = PersistentConfig(
"ENABLE_RAG_HYBRID_SEARCH",
"rag.enable_hybrid_search",
os.environ.get("ENABLE_RAG_HYBRID_SEARCH", "").lower() == "true",
)
RAG_FILE_MAX_COUNT = PersistentConfig(
"RAG_FILE_MAX_COUNT",
"rag.file.max_count",
(
int(os.environ.get("RAG_FILE_MAX_COUNT"))
if os.environ.get("RAG_FILE_MAX_COUNT")
else None
),
)
RAG_FILE_MAX_SIZE = PersistentConfig(
"RAG_FILE_MAX_SIZE",
"rag.file.max_size",
(
int(os.environ.get("RAG_FILE_MAX_SIZE"))
if os.environ.get("RAG_FILE_MAX_SIZE")
else None
),
)
ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION = PersistentConfig(
"ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION",
"rag.enable_web_loader_ssl_verification",
os.environ.get("ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION", "True").lower() == "true",
)
RAG_EMBEDDING_ENGINE = PersistentConfig(
"RAG_EMBEDDING_ENGINE",
"rag.embedding_engine",
os.environ.get("RAG_EMBEDDING_ENGINE", ""),
)
PDF_EXTRACT_IMAGES = PersistentConfig(
"PDF_EXTRACT_IMAGES",
"rag.pdf_extract_images",
os.environ.get("PDF_EXTRACT_IMAGES", "False").lower() == "true",
)
RAG_EMBEDDING_MODEL = PersistentConfig(
"RAG_EMBEDDING_MODEL",
"rag.embedding_model",
os.environ.get("RAG_EMBEDDING_MODEL", "sentence-transformers/all-MiniLM-L6-v2"),
)
log.info(f"Embedding model set: {RAG_EMBEDDING_MODEL.value}")
RAG_EMBEDDING_MODEL_AUTO_UPDATE = (
os.environ.get("RAG_EMBEDDING_MODEL_AUTO_UPDATE", "").lower() == "true"
)
RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
)
RAG_EMBEDDING_OPENAI_BATCH_SIZE = PersistentConfig(
"RAG_EMBEDDING_OPENAI_BATCH_SIZE",
"rag.embedding_openai_batch_size",
int(os.environ.get("RAG_EMBEDDING_OPENAI_BATCH_SIZE", "1")),
)
RAG_RERANKING_MODEL = PersistentConfig(
"RAG_RERANKING_MODEL",
"rag.reranking_model",
os.environ.get("RAG_RERANKING_MODEL", ""),
)
if RAG_RERANKING_MODEL.value != "":
log.info(f"Reranking model set: {RAG_RERANKING_MODEL.value}")
RAG_RERANKING_MODEL_AUTO_UPDATE = (
os.environ.get("RAG_RERANKING_MODEL_AUTO_UPDATE", "").lower() == "true"
)
RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_RERANKING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
)
if CHROMA_HTTP_HOST != "":
CHROMA_CLIENT = chromadb.HttpClient(
host=CHROMA_HTTP_HOST,
port=CHROMA_HTTP_PORT,
headers=CHROMA_HTTP_HEADERS,
ssl=CHROMA_HTTP_SSL,
tenant=CHROMA_TENANT,
database=CHROMA_DATABASE,
settings=Settings(allow_reset=True, anonymized_telemetry=False),
)
else:
CHROMA_CLIENT = chromadb.PersistentClient(
path=CHROMA_DATA_PATH,
settings=Settings(allow_reset=True, anonymized_telemetry=False),
tenant=CHROMA_TENANT,
database=CHROMA_DATABASE,
)
# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")
if USE_CUDA.lower() == "true":
DEVICE_TYPE = "cuda"
else:
DEVICE_TYPE = "cpu"
CHUNK_SIZE = PersistentConfig(
"CHUNK_SIZE", "rag.chunk_size", int(os.environ.get("CHUNK_SIZE", "1500"))
)
CHUNK_OVERLAP = PersistentConfig(
"CHUNK_OVERLAP",
"rag.chunk_overlap",
int(os.environ.get("CHUNK_OVERLAP", "100")),
)
DEFAULT_RAG_TEMPLATE = """Use the following context as your learned knowledge, inside <context></context> XML tags.
<context>
[context]
</context>
When answer to user:
- If you don't know, just say that you don't know.
- If you don't know when you are not sure, ask for clarification.
Avoid mentioning that you obtained the information from the context.
And answer according to the language of the user's question.
Given the context information, answer the query.
Query: [query]"""
RAG_TEMPLATE = PersistentConfig(
"RAG_TEMPLATE",
"rag.template",
os.environ.get("RAG_TEMPLATE", DEFAULT_RAG_TEMPLATE),
)
RAG_OPENAI_API_BASE_URL = PersistentConfig(
"RAG_OPENAI_API_BASE_URL",
"rag.openai_api_base_url",
os.getenv("RAG_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL),
)
RAG_OPENAI_API_KEY = PersistentConfig(
"RAG_OPENAI_API_KEY",
"rag.openai_api_key",
os.getenv("RAG_OPENAI_API_KEY", OPENAI_API_KEY),
)
ENABLE_RAG_LOCAL_WEB_FETCH = (
os.getenv("ENABLE_RAG_LOCAL_WEB_FETCH", "False").lower() == "true"
)
YOUTUBE_LOADER_LANGUAGE = PersistentConfig(
"YOUTUBE_LOADER_LANGUAGE",
"rag.youtube_loader_language",
os.getenv("YOUTUBE_LOADER_LANGUAGE", "en").split(","),
)
ENABLE_RAG_WEB_SEARCH = PersistentConfig(
"ENABLE_RAG_WEB_SEARCH",
"rag.web.search.enable",
os.getenv("ENABLE_RAG_WEB_SEARCH", "False").lower() == "true",
)
RAG_WEB_SEARCH_ENGINE = PersistentConfig(
"RAG_WEB_SEARCH_ENGINE",
"rag.web.search.engine",
os.getenv("RAG_WEB_SEARCH_ENGINE", ""),
)
# You can provide a list of your own websites to filter after performing a web search.
# This ensures the highest level of safety and reliability of the information sources.
RAG_WEB_SEARCH_DOMAIN_FILTER_LIST = PersistentConfig(
"RAG_WEB_SEARCH_DOMAIN_FILTER_LIST",
"rag.rag.web.search.domain.filter_list",
[
# "wikipedia.com",
# "wikimedia.org",
# "wikidata.org",
],
)
SEARXNG_QUERY_URL = PersistentConfig(
"SEARXNG_QUERY_URL",
"rag.web.search.searxng_query_url",
os.getenv("SEARXNG_QUERY_URL", ""),
)
GOOGLE_PSE_API_KEY = PersistentConfig(
"GOOGLE_PSE_API_KEY",
"rag.web.search.google_pse_api_key",
os.getenv("GOOGLE_PSE_API_KEY", ""),
)
GOOGLE_PSE_ENGINE_ID = PersistentConfig(
"GOOGLE_PSE_ENGINE_ID",
"rag.web.search.google_pse_engine_id",
os.getenv("GOOGLE_PSE_ENGINE_ID", ""),
)
BRAVE_SEARCH_API_KEY = PersistentConfig(
"BRAVE_SEARCH_API_KEY",
"rag.web.search.brave_search_api_key",
os.getenv("BRAVE_SEARCH_API_KEY", ""),
)
SERPSTACK_API_KEY = PersistentConfig(
"SERPSTACK_API_KEY",
"rag.web.search.serpstack_api_key",
os.getenv("SERPSTACK_API_KEY", ""),
)
SERPSTACK_HTTPS = PersistentConfig(
"SERPSTACK_HTTPS",
"rag.web.search.serpstack_https",
os.getenv("SERPSTACK_HTTPS", "True").lower() == "true",
)
SERPER_API_KEY = PersistentConfig(
"SERPER_API_KEY",
"rag.web.search.serper_api_key",
os.getenv("SERPER_API_KEY", ""),
)
SERPLY_API_KEY = PersistentConfig(
"SERPLY_API_KEY",
"rag.web.search.serply_api_key",
os.getenv("SERPLY_API_KEY", ""),
)
TAVILY_API_KEY = PersistentConfig(
"TAVILY_API_KEY",
"rag.web.search.tavily_api_key",
os.getenv("TAVILY_API_KEY", ""),
)
SEARCHAPI_API_KEY = PersistentConfig(
"SEARCHAPI_API_KEY",
"rag.web.search.searchapi_api_key",
os.getenv("SEARCHAPI_API_KEY", ""),
)
SEARCHAPI_ENGINE = PersistentConfig(
"SEARCHAPI_ENGINE",
"rag.web.search.searchapi_engine",
os.getenv("SEARCHAPI_ENGINE", ""),
)
RAG_WEB_SEARCH_RESULT_COUNT = PersistentConfig(
"RAG_WEB_SEARCH_RESULT_COUNT",
"rag.web.search.result_count",
int(os.getenv("RAG_WEB_SEARCH_RESULT_COUNT", "3")),
)
RAG_WEB_SEARCH_CONCURRENT_REQUESTS = PersistentConfig(
"RAG_WEB_SEARCH_CONCURRENT_REQUESTS",
"rag.web.search.concurrent_requests",
int(os.getenv("RAG_WEB_SEARCH_CONCURRENT_REQUESTS", "10")),
)
####################################
# Transcribe
####################################
WHISPER_MODEL = os.getenv("WHISPER_MODEL", "base")
WHISPER_MODEL_DIR = os.getenv("WHISPER_MODEL_DIR", f"{CACHE_DIR}/whisper/models")
WHISPER_MODEL_AUTO_UPDATE = (
os.environ.get("WHISPER_MODEL_AUTO_UPDATE", "").lower() == "true"
)
####################################
# Images
####################################
IMAGE_GENERATION_ENGINE = PersistentConfig(
"IMAGE_GENERATION_ENGINE",
"image_generation.engine",
os.getenv("IMAGE_GENERATION_ENGINE", "openai"),
)
ENABLE_IMAGE_GENERATION = PersistentConfig(
"ENABLE_IMAGE_GENERATION",
"image_generation.enable",
os.environ.get("ENABLE_IMAGE_GENERATION", "").lower() == "true",
)
AUTOMATIC1111_BASE_URL = PersistentConfig(
"AUTOMATIC1111_BASE_URL",
"image_generation.automatic1111.base_url",
os.getenv("AUTOMATIC1111_BASE_URL", ""),
)
AUTOMATIC1111_API_AUTH = PersistentConfig(
"AUTOMATIC1111_API_AUTH",
"image_generation.automatic1111.api_auth",
os.getenv("AUTOMATIC1111_API_AUTH", ""),
)
COMFYUI_BASE_URL = PersistentConfig(
"COMFYUI_BASE_URL",
"image_generation.comfyui.base_url",
os.getenv("COMFYUI_BASE_URL", ""),
)
COMFYUI_DEFAULT_WORKFLOW = """
{
"3": {
"inputs": {
"seed": 0,
"steps": 20,
"cfg": 8,
"sampler_name": "euler",
"scheduler": "normal",
"denoise": 1,
"model": [
"4",
0
],
"positive": [
"6",
0
],
"negative": [
"7",
0
],
"latent_image": [
"5",
0
]
},
"class_type": "KSampler",
"_meta": {
"title": "KSampler"
}
},
"4": {
"inputs": {
"ckpt_name": "model.safetensors"
},
"class_type": "CheckpointLoaderSimple",
"_meta": {
"title": "Load Checkpoint"
}
},
"5": {
"inputs": {
"width": 512,
"height": 512,
"batch_size": 1
},
"class_type": "EmptyLatentImage",
"_meta": {
"title": "Empty Latent Image"
}
},
"6": {
"inputs": {
"text": "Prompt",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"7": {
"inputs": {
"text": "",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"8": {
"inputs": {
"samples": [
"3",
0
],
"vae": [
"4",
2
]
},
"class_type": "VAEDecode",
"_meta": {
"title": "VAE Decode"
}
},
"9": {
"inputs": {
"filename_prefix": "ComfyUI",
"images": [
"8",
0
]
},
"class_type": "SaveImage",
"_meta": {
"title": "Save Image"
}
}
}
"""
COMFYUI_WORKFLOW = PersistentConfig(
"COMFYUI_WORKFLOW",
"image_generation.comfyui.workflow",
os.getenv("COMFYUI_WORKFLOW", COMFYUI_DEFAULT_WORKFLOW),
)
COMFYUI_WORKFLOW_NODES = PersistentConfig(
"COMFYUI_WORKFLOW",
"image_generation.comfyui.nodes",
[],
)
IMAGES_OPENAI_API_BASE_URL = PersistentConfig(
"IMAGES_OPENAI_API_BASE_URL",
"image_generation.openai.api_base_url",
os.getenv("IMAGES_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL),
)
IMAGES_OPENAI_API_KEY = PersistentConfig(
"IMAGES_OPENAI_API_KEY",
"image_generation.openai.api_key",
os.getenv("IMAGES_OPENAI_API_KEY", OPENAI_API_KEY),
)
IMAGE_SIZE = PersistentConfig(
"IMAGE_SIZE", "image_generation.size", os.getenv("IMAGE_SIZE", "512x512")
)
IMAGE_STEPS = PersistentConfig(
"IMAGE_STEPS", "image_generation.steps", int(os.getenv("IMAGE_STEPS", 50))
)
IMAGE_GENERATION_MODEL = PersistentConfig(
"IMAGE_GENERATION_MODEL",
"image_generation.model",
os.getenv("IMAGE_GENERATION_MODEL", ""),
)
####################################
# Audio
####################################
AUDIO_STT_OPENAI_API_BASE_URL = PersistentConfig(
"AUDIO_STT_OPENAI_API_BASE_URL",
"audio.stt.openai.api_base_url",
os.getenv("AUDIO_STT_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL),
)
AUDIO_STT_OPENAI_API_KEY = PersistentConfig(
"AUDIO_STT_OPENAI_API_KEY",
"audio.stt.openai.api_key",
os.getenv("AUDIO_STT_OPENAI_API_KEY", OPENAI_API_KEY),
)
AUDIO_STT_ENGINE = PersistentConfig(
"AUDIO_STT_ENGINE",
"audio.stt.engine",
os.getenv("AUDIO_STT_ENGINE", ""),
)
AUDIO_STT_MODEL = PersistentConfig(
"AUDIO_STT_MODEL",
"audio.stt.model",
os.getenv("AUDIO_STT_MODEL", "whisper-1"),
)
AUDIO_TTS_OPENAI_API_BASE_URL = PersistentConfig(
"AUDIO_TTS_OPENAI_API_BASE_URL",
"audio.tts.openai.api_base_url",
os.getenv("AUDIO_TTS_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL),
)
AUDIO_TTS_OPENAI_API_KEY = PersistentConfig(
"AUDIO_TTS_OPENAI_API_KEY",
"audio.tts.openai.api_key",
os.getenv("AUDIO_TTS_OPENAI_API_KEY", OPENAI_API_KEY),
)
AUDIO_TTS_API_KEY = PersistentConfig(
"AUDIO_TTS_API_KEY",
"audio.tts.api_key",
os.getenv("AUDIO_TTS_API_KEY", ""),
)
AUDIO_TTS_ENGINE = PersistentConfig(
"AUDIO_TTS_ENGINE",
"audio.tts.engine",
os.getenv("AUDIO_TTS_ENGINE", ""),
)
AUDIO_TTS_MODEL = PersistentConfig(
"AUDIO_TTS_MODEL",
"audio.tts.model",
os.getenv("AUDIO_TTS_MODEL", "tts-1"), # OpenAI default model
)
AUDIO_TTS_VOICE = PersistentConfig(
"AUDIO_TTS_VOICE",
"audio.tts.voice",
os.getenv("AUDIO_TTS_VOICE", "alloy"), # OpenAI default voice
)
AUDIO_TTS_SPLIT_ON = PersistentConfig(
"AUDIO_TTS_SPLIT_ON",
"audio.tts.split_on",
os.getenv("AUDIO_TTS_SPLIT_ON", "punctuation"),
)
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