github-actions[bot]
GitHub deploy: 91d8cc550245fd3a29cdb13ec42b241dcaaaa56a
d0f2f6a
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 open_webui.apps.webui.internal.db import Base, get_db
from open_webui.env import (
OPEN_WEBUI_DIR,
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(OPEN_WEBUI_DIR / "alembic.ini")
# Set the script location dynamically
migrations_path = OPEN_WEBUI_DIR / "migrations"
alembic_cfg.set_main_option("script_location", str(migrations_path))
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()
def reset_config():
with get_db() as db:
db.query(Config).delete()
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")
DEFAULT_CONFIG = {
"version": 0,
"ui": {
"default_locale": "",
"prompt_suggestions": [
{
"title": [
"帮我复习",
"大学入学考试词汇",
],
"content": "帮我复习词汇:给我造个句子让我填空,我来选择正确的答案。",
},
{
"title": [
"弱智吧考验",
"钢丝球炒西红柿",
],
"content": "钢丝球炒西红柿怎么做?",
},
{
"title": ["说个趣事", "罗马帝国趣闻"],
"content": "随便说个关于罗马帝国的有趣小知识",
},
{
"title": [
"写个代码示例",
"网页的固定顶栏",
],
"content": "用CSS和JavaScript写个网页固定顶栏的代码示例。",
},
{
"title": [
"名词解释",
"用通俗语言解释期权交易",
],
"content": "我对买卖股票有些了解,你能用通俗的话解释一下什么是期权交易吗?",
},
{
"title": ["提供建议", "克服拖延症"],
"content": "我老爱拖延,你能先问问我什么时候最容易拖延,然后给我一些克服它的建议吗?",
},
{
"title": [
"语法检查",
"重写以提高可读性",
],
"content": '检查以下句子的语法和清晰度:"[sentence]"。在保持其原意的同时重写它以提高可读性。',
},
],
},
}
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
PERSISTENT_CONFIG_REGISTRY = []
def save_config(config):
global CONFIG_DATA
global PERSISTENT_CONFIG_REGISTRY
try:
save_to_db(config)
CONFIG_DATA = config
# Trigger updates on all registered PersistentConfig entries
for config_item in PERSISTENT_CONFIG_REGISTRY:
config_item.update()
except Exception as e:
log.exception(e)
return False
return True
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
PERSISTENT_CONFIG_REGISTRY.append(self)
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 update(self):
new_value = get_config_value(self.config_path)
if new_value is not None:
self.value = new_value
log.info(f"Updated {self.env_name} to new value {self.value}")
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", OPEN_WEBUI_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)
####################################
# 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)
####################################
# 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 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", ""),
)
ENABLE_SEARCH_QUERY = PersistentConfig(
"ENABLE_SEARCH_QUERY",
"task.search.enable",
os.environ.get("ENABLE_SEARCH_QUERY", "True").lower() == "true",
)
SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
"SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE",
"task.search.prompt_template",
os.environ.get("SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE", ""),
)
TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = PersistentConfig(
"TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE",
"task.tools.prompt_template",
os.environ.get("TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE", ""),
)
####################################
# Vector Database
####################################
VECTOR_DB = os.environ.get("VECTOR_DB", "chroma")
# Chroma
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)
# Milvus
MILVUS_URI = os.environ.get("MILVUS_URI", f"{DATA_DIR}/vector_db/milvus.db")
####################################
# Information Retrieval (RAG)
####################################
# RAG 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_TOP_K = PersistentConfig(
"RAG_TOP_K", "rag.top_k", int(os.environ.get("RAG_TOP_K", "3"))
)
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"
)
CHUNK_SIZE = PersistentConfig(
"CHUNK_SIZE", "rag.chunk_size", int(os.environ.get("CHUNK_SIZE", "1000"))
)
CHUNK_OVERLAP = PersistentConfig(
"CHUNK_OVERLAP",
"rag.chunk_overlap",
int(os.environ.get("CHUNK_OVERLAP", "100")),
)
DEFAULT_RAG_TEMPLATE = """You are given a user query, some textual context and rules, all inside xml tags. You have to answer the query based on the context while respecting the rules.
<context>
[context]
</context>
<rules>
- If you don't know, just say so.
- If you are not sure, ask for clarification.
- Answer in the same language as the user query.
- If the context appears unreadable or of poor quality, tell the user then answer as best as you can.
- If the answer is not in the context but you think you know the answer, explain that to the user then answer with your own knowledge.
- Answer directly and without using xml tags.
</rules>
<user_query>
[query]
</user_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", ""),
)
AUTOMATIC1111_CFG_SCALE = PersistentConfig(
"AUTOMATIC1111_CFG_SCALE",
"image_generation.automatic1111.cfg_scale",
(
float(os.environ.get("AUTOMATIC1111_CFG_SCALE"))
if os.environ.get("AUTOMATIC1111_CFG_SCALE")
else None
),
)
AUTOMATIC1111_SAMPLER = PersistentConfig(
"AUTOMATIC1111_SAMPLERE",
"image_generation.automatic1111.sampler",
(
os.environ.get("AUTOMATIC1111_SAMPLER")
if os.environ.get("AUTOMATIC1111_SAMPLER")
else None
),
)
AUTOMATIC1111_SCHEDULER = PersistentConfig(
"AUTOMATIC1111_SCHEDULER",
"image_generation.automatic1111.scheduler",
(
os.environ.get("AUTOMATIC1111_SCHEDULER")
if os.environ.get("AUTOMATIC1111_SCHEDULER")
else None
),
)
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"),
)
AUDIO_TTS_AZURE_SPEECH_REGION = PersistentConfig(
"AUDIO_TTS_AZURE_SPEECH_REGION",
"audio.tts.azure.speech_region",
os.getenv("AUDIO_TTS_AZURE_SPEECH_REGION", "eastus"),
)
AUDIO_TTS_AZURE_SPEECH_OUTPUT_FORMAT = PersistentConfig(
"AUDIO_TTS_AZURE_SPEECH_OUTPUT_FORMAT",
"audio.tts.azure.speech_output_format",
os.getenv(
"AUDIO_TTS_AZURE_SPEECH_OUTPUT_FORMAT", "audio-24khz-160kbitrate-mono-mp3"
),
)