open-webui / backend /config.py
github-actions[bot]
GitHub deploy: b6b71c08f3e1811b819a8d8f68cb4d83e57163d0
498a7b8
import os
import sys
import logging
import importlib.metadata
import pkgutil
import chromadb
from chromadb import Settings
from base64 import b64encode
from bs4 import BeautifulSoup
from typing import TypeVar, Generic, Union
from pydantic import BaseModel
from typing import Optional
from pathlib import Path
import json
import yaml
import markdown
import requests
import shutil
from secrets import token_bytes
from constants import ERROR_MESSAGES
####################################
# Load .env file
####################################
BACKEND_DIR = Path(__file__).parent # the path containing this file
BASE_DIR = BACKEND_DIR.parent # the path containing the backend/
print(BASE_DIR)
try:
from dotenv import load_dotenv, find_dotenv
load_dotenv(find_dotenv(str(BASE_DIR / ".env")))
except ImportError:
print("dotenv not installed, skipping...")
####################################
# LOGGING
####################################
log_levels = ["CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG"]
GLOBAL_LOG_LEVEL = os.environ.get("GLOBAL_LOG_LEVEL", "").upper()
if GLOBAL_LOG_LEVEL in log_levels:
logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL, force=True)
else:
GLOBAL_LOG_LEVEL = "INFO"
log = logging.getLogger(__name__)
log.info(f"GLOBAL_LOG_LEVEL: {GLOBAL_LOG_LEVEL}")
log_sources = [
"AUDIO",
"COMFYUI",
"CONFIG",
"DB",
"IMAGES",
"MAIN",
"MODELS",
"OLLAMA",
"OPENAI",
"RAG",
"WEBHOOK",
]
SRC_LOG_LEVELS = {}
for source in log_sources:
log_env_var = source + "_LOG_LEVEL"
SRC_LOG_LEVELS[source] = os.environ.get(log_env_var, "").upper()
if SRC_LOG_LEVELS[source] not in log_levels:
SRC_LOG_LEVELS[source] = GLOBAL_LOG_LEVEL
log.info(f"{log_env_var}: {SRC_LOG_LEVELS[source]}")
log.setLevel(SRC_LOG_LEVELS["CONFIG"])
WEBUI_NAME = os.environ.get("WEBUI_NAME", "Open WebUI")
if WEBUI_NAME != "Open WebUI":
WEBUI_NAME += " (Open WebUI)"
WEBUI_URL = os.environ.get("WEBUI_URL", "http://localhost:3000")
WEBUI_FAVICON_URL = "https://openwebui.com/favicon.png"
####################################
# ENV (dev,test,prod)
####################################
ENV = os.environ.get("ENV", "dev")
try:
PACKAGE_DATA = json.loads((BASE_DIR / "package.json").read_text())
except:
try:
PACKAGE_DATA = {"version": importlib.metadata.version("open-webui")}
except importlib.metadata.PackageNotFoundError:
PACKAGE_DATA = {"version": "0.0.0"}
VERSION = PACKAGE_DATA["version"]
# Function to parse each section
def parse_section(section):
items = []
for li in section.find_all("li"):
# Extract raw HTML string
raw_html = str(li)
# Extract text without HTML tags
text = li.get_text(separator=" ", strip=True)
# Split into title and content
parts = text.split(": ", 1)
title = parts[0].strip() if len(parts) > 1 else ""
content = parts[1].strip() if len(parts) > 1 else text
items.append({"title": title, "content": content, "raw": raw_html})
return items
try:
changelog_path = BASE_DIR / "CHANGELOG.md"
with open(str(changelog_path.absolute()), "r", encoding="utf8") as file:
changelog_content = file.read()
except:
changelog_content = (pkgutil.get_data("open_webui", "CHANGELOG.md") or b"").decode()
# Convert markdown content to HTML
html_content = markdown.markdown(changelog_content)
# Parse the HTML content
soup = BeautifulSoup(html_content, "html.parser")
# Initialize JSON structure
changelog_json = {}
# Iterate over each version
for version in soup.find_all("h2"):
version_number = version.get_text().strip().split(" - ")[0][1:-1] # Remove brackets
date = version.get_text().strip().split(" - ")[1]
version_data = {"date": date}
# Find the next sibling that is a h3 tag (section title)
current = version.find_next_sibling()
while current and current.name != "h2":
if current.name == "h3":
section_title = current.get_text().lower() # e.g., "added", "fixed"
section_items = parse_section(current.find_next_sibling("ul"))
version_data[section_title] = section_items
# Move to the next element
current = current.find_next_sibling()
changelog_json[version_number] = version_data
CHANGELOG = changelog_json
####################################
# WEBUI_BUILD_HASH
####################################
WEBUI_BUILD_HASH = os.environ.get("WEBUI_BUILD_HASH", "dev-build")
####################################
# DATA/FRONTEND BUILD DIR
####################################
DATA_DIR = Path(os.getenv("DATA_DIR", BACKEND_DIR / "data")).resolve()
FRONTEND_BUILD_DIR = Path(os.getenv("FRONTEND_BUILD_DIR", BASE_DIR / "build")).resolve()
try:
CONFIG_DATA = json.loads((DATA_DIR / "config.json").read_text())
except:
CONFIG_DATA = {}
####################################
# Config helpers
####################################
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)
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 config.json")
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):
# Don't save if the value is the same as the env value and the config value
if self.env_value == self.value:
if self.config_value == self.value:
return
log.info(f"Saving '{self.env_name}' to config.json")
path_parts = self.config_path.split(".")
config = CONFIG_DATA
for key in path_parts[:-1]:
if key not in config:
config[key] = {}
config = config[key]
config[path_parts[-1]] = self.value
save_config()
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)
####################################
WEBUI_AUTH = os.environ.get("WEBUI_AUTH", "True").lower() == "true"
WEBUI_AUTH_TRUSTED_EMAIL_HEADER = os.environ.get(
"WEBUI_AUTH_TRUSTED_EMAIL_HEADER", None
)
JWT_EXPIRES_IN = PersistentConfig(
"JWT_EXPIRES_IN", "auth.jwt_expiry", os.environ.get("JWT_EXPIRES_IN", "-1")
)
####################################
# Static DIR
####################################
STATIC_DIR = Path(os.getenv("STATIC_DIR", BACKEND_DIR / "static")).resolve()
frontend_favicon = FRONTEND_BUILD_DIR / "favicon.png"
if frontend_favicon.exists():
shutil.copyfile(frontend_favicon, STATIC_DIR / "favicon.png")
else:
logging.warning(f"Frontend favicon not found at {frontend_favicon}")
####################################
# 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)
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)
####################################
# 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", "")
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:
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"
),
)
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 = PersistentConfig(
"USER_PERMISSIONS",
"ui.user_permissions",
{"chat": {"deletion": USER_PERMISSIONS_CHAT_DELETION}},
)
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_COMMUNITY_SHARING = PersistentConfig(
"ENABLE_COMMUNITY_SHARING",
"ui.enable_community_sharing",
os.environ.get("ENABLE_COMMUNITY_SHARING", "True").lower() == "true",
)
class BannerModel(BaseModel):
id: str
type: str
title: Optional[str] = None
content: str
dismissible: bool
timestamp: int
WEBUI_BANNERS = PersistentConfig(
"WEBUI_BANNERS",
"ui.banners",
[BannerModel(**banner) for banner in json.loads("[]")],
)
####################################
# WEBUI_SECRET_KEY
####################################
WEBUI_SECRET_KEY = os.environ.get(
"WEBUI_SECRET_KEY",
os.environ.get(
"WEBUI_JWT_SECRET_KEY", "t0p-s3cr3t"
), # DEPRECATED: remove at next major version
)
if WEBUI_AUTH and WEBUI_SECRET_KEY == "":
raise ValueError(ERROR_MESSAGES.ENV_VAR_NOT_FOUND)
####################################
# 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",
)
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_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(","),
)
####################################
# 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", ""),
)
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", ""),
)
COMFYUI_BASE_URL = PersistentConfig(
"COMFYUI_BASE_URL",
"image_generation.comfyui.base_url",
os.getenv("COMFYUI_BASE_URL", ""),
)
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_OPENAI_API_BASE_URL = PersistentConfig(
"AUDIO_OPENAI_API_BASE_URL",
"audio.openai.api_base_url",
os.getenv("AUDIO_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL),
)
AUDIO_OPENAI_API_KEY = PersistentConfig(
"AUDIO_OPENAI_API_KEY",
"audio.openai.api_key",
os.getenv("AUDIO_OPENAI_API_KEY", OPENAI_API_KEY),
)
AUDIO_OPENAI_API_MODEL = PersistentConfig(
"AUDIO_OPENAI_API_MODEL",
"audio.openai.api_model",
os.getenv("AUDIO_OPENAI_API_MODEL", "tts-1"),
)
AUDIO_OPENAI_API_VOICE = PersistentConfig(
"AUDIO_OPENAI_API_VOICE",
"audio.openai.api_voice",
os.getenv("AUDIO_OPENAI_API_VOICE", "alloy"),
)
####################################
# Database
####################################
DATABASE_URL = os.environ.get("DATABASE_URL", f"sqlite:///{DATA_DIR}/webui.db")