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open-webui/backend/open_webui/config.py
Timothy Jaeryang Baek cb3e01de8a enh: channels enable/disable option
2024-12-22 21:02:14 -07:00

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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 open_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,
DATABASE_URL,
OFFLINE_MODE,
)
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": [
"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
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)
####################################
ENABLE_API_KEY = PersistentConfig(
"ENABLE_API_KEY",
"auth.api_key.enable",
os.environ.get("ENABLE_API_KEY", "True").lower() == "true",
)
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_DRIVE_CLIENT_ID = PersistentConfig(
"GOOGLE_DRIVE_CLIENT_ID",
"google_drive.client_id",
os.environ.get("GOOGLE_DRIVE_CLIENT_ID", ""),
)
GOOGLE_DRIVE_API_KEY = PersistentConfig(
"GOOGLE_DRIVE_API_KEY",
"google_drive.api_key",
os.environ.get("GOOGLE_DRIVE_API_KEY", ""),
)
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_PICTURE_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"),
)
OAUTH_GROUPS_CLAIM = PersistentConfig(
"OAUTH_GROUPS_CLAIM",
"oauth.oidc.group_claim",
os.environ.get("OAUTH_GROUP_CLAIM", "groups"),
)
ENABLE_OAUTH_ROLE_MANAGEMENT = PersistentConfig(
"ENABLE_OAUTH_ROLE_MANAGEMENT",
"oauth.enable_role_mapping",
os.environ.get("ENABLE_OAUTH_ROLE_MANAGEMENT", "False").lower() == "true",
)
ENABLE_OAUTH_GROUP_MANAGEMENT = PersistentConfig(
"ENABLE_OAUTH_GROUP_MANAGEMENT",
"oauth.enable_group_mapping",
os.environ.get("ENABLE_OAUTH_GROUP_MANAGEMENT", "False").lower() == "true",
)
OAUTH_ROLES_CLAIM = PersistentConfig(
"OAUTH_ROLES_CLAIM",
"oauth.roles_claim",
os.environ.get("OAUTH_ROLES_CLAIM", "roles"),
)
OAUTH_ALLOWED_ROLES = PersistentConfig(
"OAUTH_ALLOWED_ROLES",
"oauth.allowed_roles",
[
role.strip()
for role in os.environ.get("OAUTH_ALLOWED_ROLES", "user,admin").split(",")
],
)
OAUTH_ADMIN_ROLES = PersistentConfig(
"OAUTH_ADMIN_ROLES",
"oauth.admin_roles",
[role.strip() for role in os.environ.get("OAUTH_ADMIN_ROLES", "admin").split(",")],
)
OAUTH_ALLOWED_DOMAINS = PersistentConfig(
"OAUTH_ALLOWED_DOMAINS",
"oauth.allowed_domains",
[
domain.strip()
for domain in os.environ.get("OAUTH_ALLOWED_DOMAINS", "*").split(",")
],
)
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
####################################
# STORAGE PROVIDER
####################################
STORAGE_PROVIDER = os.environ.get("STORAGE_PROVIDER", "") # defaults to local, s3
S3_ACCESS_KEY_ID = os.environ.get("S3_ACCESS_KEY_ID", None)
S3_SECRET_ACCESS_KEY = os.environ.get("S3_SECRET_ACCESS_KEY", None)
S3_REGION_NAME = os.environ.get("S3_REGION_NAME", None)
S3_BUCKET_NAME = os.environ.get("S3_BUCKET_NAME", None)
S3_ENDPOINT_URL = os.environ.get("S3_ENDPOINT_URL", None)
####################################
# 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)
####################################
# 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", "")
if OLLAMA_BASE_URL:
# Remove trailing slash
OLLAMA_BASE_URL = (
OLLAMA_BASE_URL[:-1] if OLLAMA_BASE_URL.endswith("/") else 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
)
OLLAMA_API_CONFIGS = PersistentConfig(
"OLLAMA_API_CONFIGS",
"ollama.api_configs",
{},
)
####################################
# 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_CONFIGS = PersistentConfig(
"OPENAI_API_CONFIGS",
"openai.api_configs",
{},
)
# Get the actual OpenAI API key based on the base URL
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?",
},
],
)
MODEL_ORDER_LIST = PersistentConfig(
"MODEL_ORDER_LIST",
"ui.model_order_list",
[],
)
DEFAULT_USER_ROLE = PersistentConfig(
"DEFAULT_USER_ROLE",
"ui.default_user_role",
os.getenv("DEFAULT_USER_ROLE", "pending"),
)
USER_PERMISSIONS_WORKSPACE_MODELS_ACCESS = (
os.environ.get("USER_PERMISSIONS_WORKSPACE_MODELS_ACCESS", "False").lower()
== "true"
)
USER_PERMISSIONS_WORKSPACE_KNOWLEDGE_ACCESS = (
os.environ.get("USER_PERMISSIONS_WORKSPACE_KNOWLEDGE_ACCESS", "False").lower()
== "true"
)
USER_PERMISSIONS_WORKSPACE_PROMPTS_ACCESS = (
os.environ.get("USER_PERMISSIONS_WORKSPACE_PROMPTS_ACCESS", "False").lower()
== "true"
)
USER_PERMISSIONS_WORKSPACE_TOOLS_ACCESS = (
os.environ.get("USER_PERMISSIONS_WORKSPACE_TOOLS_ACCESS", "False").lower() == "true"
)
USER_PERMISSIONS_CHAT_FILE_UPLOAD = (
os.environ.get("USER_PERMISSIONS_CHAT_FILE_UPLOAD", "True").lower() == "true"
)
USER_PERMISSIONS_CHAT_DELETE = (
os.environ.get("USER_PERMISSIONS_CHAT_DELETE", "True").lower() == "true"
)
USER_PERMISSIONS_CHAT_EDIT = (
os.environ.get("USER_PERMISSIONS_CHAT_EDIT", "True").lower() == "true"
)
USER_PERMISSIONS_CHAT_TEMPORARY = (
os.environ.get("USER_PERMISSIONS_CHAT_TEMPORARY", "True").lower() == "true"
)
USER_PERMISSIONS = PersistentConfig(
"USER_PERMISSIONS",
"user.permissions",
{
"workspace": {
"models": USER_PERMISSIONS_WORKSPACE_MODELS_ACCESS,
"knowledge": USER_PERMISSIONS_WORKSPACE_KNOWLEDGE_ACCESS,
"prompts": USER_PERMISSIONS_WORKSPACE_PROMPTS_ACCESS,
"tools": USER_PERMISSIONS_WORKSPACE_TOOLS_ACCESS,
},
"chat": {
"file_upload": USER_PERMISSIONS_CHAT_FILE_UPLOAD,
"delete": USER_PERMISSIONS_CHAT_DELETE,
"edit": USER_PERMISSIONS_CHAT_EDIT,
"temporary": USER_PERMISSIONS_CHAT_TEMPORARY,
},
},
)
ENABLE_CHANNELS = PersistentConfig(
"ENABLE_CHANNELS",
"channels.enable",
os.environ.get("ENABLE_CHANNELS", "False").lower() == "true",
)
ENABLE_EVALUATION_ARENA_MODELS = PersistentConfig(
"ENABLE_EVALUATION_ARENA_MODELS",
"evaluation.arena.enable",
os.environ.get("ENABLE_EVALUATION_ARENA_MODELS", "True").lower() == "true",
)
EVALUATION_ARENA_MODELS = PersistentConfig(
"EVALUATION_ARENA_MODELS",
"evaluation.arena.models",
[],
)
DEFAULT_ARENA_MODEL = {
"id": "arena-model",
"name": "Arena Model",
"meta": {
"profile_image_url": "/favicon.png",
"description": "Submit your questions to anonymous AI chatbots and vote on the best response.",
"model_ids": None,
},
}
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", ""),
)
DEFAULT_TITLE_GENERATION_PROMPT_TEMPLATE = """Create a concise, 3-5 word title with an emoji as a title for the chat history, 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
<chat_history>
{{MESSAGES:END:2}}
</chat_history>"""
TAGS_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
"TAGS_GENERATION_PROMPT_TEMPLATE",
"task.tags.prompt_template",
os.environ.get("TAGS_GENERATION_PROMPT_TEMPLATE", ""),
)
DEFAULT_TAGS_GENERATION_PROMPT_TEMPLATE = """### Task:
Generate 1-3 broad tags categorizing the main themes of the chat history, along with 1-3 more specific subtopic tags.
### Guidelines:
- Start with high-level domains (e.g. Science, Technology, Philosophy, Arts, Politics, Business, Health, Sports, Entertainment, Education)
- Consider including relevant subfields/subdomains if they are strongly represented throughout the conversation
- If content is too short (less than 3 messages) or too diverse, use only ["General"]
- Use the chat's primary language; default to English if multilingual
- Prioritize accuracy over specificity
### Output:
JSON format: { "tags": ["tag1", "tag2", "tag3"] }
### Chat History:
<chat_history>
{{MESSAGES:END:6}}
</chat_history>"""
ENABLE_TAGS_GENERATION = PersistentConfig(
"ENABLE_TAGS_GENERATION",
"task.tags.enable",
os.environ.get("ENABLE_TAGS_GENERATION", "True").lower() == "true",
)
ENABLE_SEARCH_QUERY_GENERATION = PersistentConfig(
"ENABLE_SEARCH_QUERY_GENERATION",
"task.query.search.enable",
os.environ.get("ENABLE_SEARCH_QUERY_GENERATION", "True").lower() == "true",
)
ENABLE_RETRIEVAL_QUERY_GENERATION = PersistentConfig(
"ENABLE_RETRIEVAL_QUERY_GENERATION",
"task.query.retrieval.enable",
os.environ.get("ENABLE_RETRIEVAL_QUERY_GENERATION", "True").lower() == "true",
)
QUERY_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
"QUERY_GENERATION_PROMPT_TEMPLATE",
"task.query.prompt_template",
os.environ.get("QUERY_GENERATION_PROMPT_TEMPLATE", ""),
)
DEFAULT_QUERY_GENERATION_PROMPT_TEMPLATE = """### Task:
Analyze the chat history to determine the necessity of generating search queries, in the given language. By default, **prioritize generating 1-3 broad and relevant search queries** unless it is absolutely certain that no additional information is required. The aim is to retrieve comprehensive, updated, and valuable information even with minimal uncertainty. If no search is unequivocally needed, return an empty list.
### Guidelines:
- Respond **EXCLUSIVELY** with a JSON object. Any form of extra commentary, explanation, or additional text is strictly prohibited.
- When generating search queries, respond in the format: { "queries": ["query1", "query2"] }, ensuring each query is distinct, concise, and relevant to the topic.
- If and only if it is entirely certain that no useful results can be retrieved by a search, return: { "queries": [] }.
- Err on the side of suggesting search queries if there is **any chance** they might provide useful or updated information.
- Be concise and focused on composing high-quality search queries, avoiding unnecessary elaboration, commentary, or assumptions.
- Today's date is: {{CURRENT_DATE}}.
- Always prioritize providing actionable and broad queries that maximize informational coverage.
### Output:
Strictly return in JSON format:
{
"queries": ["query1", "query2"]
}
### Chat History:
<chat_history>
{{MESSAGES:END:6}}
</chat_history>
"""
ENABLE_AUTOCOMPLETE_GENERATION = PersistentConfig(
"ENABLE_AUTOCOMPLETE_GENERATION",
"task.autocomplete.enable",
os.environ.get("ENABLE_AUTOCOMPLETE_GENERATION", "True").lower() == "true",
)
AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH = PersistentConfig(
"AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH",
"task.autocomplete.input_max_length",
int(os.environ.get("AUTOCOMPLETE_GENERATION_INPUT_MAX_LENGTH", "-1")),
)
AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
"AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE",
"task.autocomplete.prompt_template",
os.environ.get("AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE", ""),
)
DEFAULT_AUTOCOMPLETE_GENERATION_PROMPT_TEMPLATE = """### Task:
You are an autocompletion system. Continue the text in `<text>` based on the **completion type** in `<type>` and the given language.
### **Instructions**:
1. Analyze `<text>` for context and meaning.
2. Use `<type>` to guide your output:
- **General**: Provide a natural, concise continuation.
- **Search Query**: Complete as if generating a realistic search query.
3. Start as if you are directly continuing `<text>`. Do **not** repeat, paraphrase, or respond as a model. Simply complete the text.
4. Ensure the continuation:
- Flows naturally from `<text>`.
- Avoids repetition, overexplaining, or unrelated ideas.
5. If unsure, return: `{ "text": "" }`.
### **Output Rules**:
- Respond only in JSON format: `{ "text": "<your_completion>" }`.
### **Examples**:
#### Example 1:
Input:
<type>General</type>
<text>The sun was setting over the horizon, painting the sky</text>
Output:
{ "text": "with vibrant shades of orange and pink." }
#### Example 2:
Input:
<type>Search Query</type>
<text>Top-rated restaurants in</text>
Output:
{ "text": "New York City for Italian cuisine." }
---
### Context:
<chat_history>
{{MESSAGES:END:6}}
</chat_history>
<type>{{TYPE}}</type>
<text>{{PROMPT}}</text>
#### Output:
"""
TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = PersistentConfig(
"TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE",
"task.tools.prompt_template",
os.environ.get("TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE", ""),
)
DEFAULT_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."""
DEFAULT_EMOJI_GENERATION_PROMPT_TEMPLATE = """Your task is to reflect the speaker's likely facial expression through a fitting emoji. Interpret emotions from the message and reflect their facial expression using fitting, diverse emojis (e.g., 😊, 😢, 😡, 😱).
Message: ```{{prompt}}```"""
DEFAULT_MOA_GENERATION_PROMPT_TEMPLATE = """You have been provided with a set of responses from various models to the latest user query: "{{prompt}}"
Your task is to synthesize these responses into a single, high-quality response. It is crucial to critically evaluate the information provided in these responses, recognizing that some of it may be biased or incorrect. Your response should not simply replicate the given answers but should offer a refined, accurate, and comprehensive reply to the instruction. Ensure your response is well-structured, coherent, and adheres to the highest standards of accuracy and reliability.
Responses from models: {{responses}}"""
####################################
# 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"))
CHROMA_CLIENT_AUTH_PROVIDER = os.environ.get("CHROMA_CLIENT_AUTH_PROVIDER", "")
CHROMA_CLIENT_AUTH_CREDENTIALS = os.environ.get("CHROMA_CLIENT_AUTH_CREDENTIALS", "")
# 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")
# Qdrant
QDRANT_URI = os.environ.get("QDRANT_URI", None)
QDRANT_API_KEY = os.environ.get("QDRANT_API_KEY", None)
# OpenSearch
OPENSEARCH_URI = os.environ.get("OPENSEARCH_URI", "https://localhost:9200")
OPENSEARCH_SSL = os.environ.get("OPENSEARCH_SSL", True)
OPENSEARCH_CERT_VERIFY = os.environ.get("OPENSEARCH_CERT_VERIFY", False)
OPENSEARCH_USERNAME = os.environ.get("OPENSEARCH_USERNAME", None)
OPENSEARCH_PASSWORD = os.environ.get("OPENSEARCH_PASSWORD", None)
# Pgvector
PGVECTOR_DB_URL = os.environ.get("PGVECTOR_DB_URL", DATABASE_URL)
if VECTOR_DB == "pgvector" and not PGVECTOR_DB_URL.startswith("postgres"):
raise ValueError(
"Pgvector requires setting PGVECTOR_DB_URL or using Postgres with vector extension as the primary database."
)
####################################
# Information Retrieval (RAG)
####################################
# If configured, Google Drive will be available as an upload option.
ENABLE_GOOGLE_DRIVE_INTEGRATION = PersistentConfig(
"ENABLE_GOOGLE_DRIVE_INTEGRATION",
"google_drive.enable",
os.getenv("ENABLE_GOOGLE_DRIVE_INTEGRATION", "False").lower() == "true",
)
# 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 = (
not OFFLINE_MODE
and os.environ.get("RAG_EMBEDDING_MODEL_AUTO_UPDATE", "True").lower() == "true"
)
RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE", "True").lower() == "true"
)
RAG_EMBEDDING_BATCH_SIZE = PersistentConfig(
"RAG_EMBEDDING_BATCH_SIZE",
"rag.embedding_batch_size",
int(
os.environ.get("RAG_EMBEDDING_BATCH_SIZE")
or 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 = (
not OFFLINE_MODE
and os.environ.get("RAG_RERANKING_MODEL_AUTO_UPDATE", "True").lower() == "true"
)
RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_RERANKING_MODEL_TRUST_REMOTE_CODE", "True").lower() == "true"
)
RAG_TEXT_SPLITTER = PersistentConfig(
"RAG_TEXT_SPLITTER",
"rag.text_splitter",
os.environ.get("RAG_TEXT_SPLITTER", ""),
)
TIKTOKEN_CACHE_DIR = os.environ.get("TIKTOKEN_CACHE_DIR", f"{CACHE_DIR}/tiktoken")
TIKTOKEN_ENCODING_NAME = PersistentConfig(
"TIKTOKEN_ENCODING_NAME",
"rag.tiktoken_encoding_name",
os.environ.get("TIKTOKEN_ENCODING_NAME", "cl100k_base"),
)
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 = """### Task:
Respond to the user query using the provided context, incorporating inline citations in the format [source_id] **only when the <source_id> tag is explicitly provided** in the context.
### Guidelines:
- If you don't know the answer, clearly state that.
- If uncertain, ask the user for clarification.
- Respond in the same language as the user's query.
- If the context is unreadable or of poor quality, inform the user and provide the best possible answer.
- If the answer isn't present in the context but you possess the knowledge, explain this to the user and provide the answer using your own understanding.
- **Only include inline citations using [source_id] when a <source_id> tag is explicitly provided in the context.**
- Do not cite if the <source_id> tag is not provided in the context.
- Do not use XML tags in your response.
- Ensure citations are concise and directly related to the information provided.
### Example of Citation:
If the user asks about a specific topic and the information is found in "whitepaper.pdf" with a provided <source_id>, the response should include the citation like so:
* "According to the study, the proposed method increases efficiency by 20% [whitepaper.pdf]."
If no <source_id> is present, the response should omit the citation.
### Output:
Provide a clear and direct response to the user's query, including inline citations in the format [source_id] only when the <source_id> tag is present in the context.
<context>
{{CONTEXT}}
</context>
<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),
)
RAG_OLLAMA_BASE_URL = PersistentConfig(
"RAG_OLLAMA_BASE_URL",
"rag.ollama.url",
os.getenv("RAG_OLLAMA_BASE_URL", OLLAMA_BASE_URL),
)
RAG_OLLAMA_API_KEY = PersistentConfig(
"RAG_OLLAMA_API_KEY",
"rag.ollama.key",
os.getenv("RAG_OLLAMA_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(","),
)
YOUTUBE_LOADER_PROXY_URL = PersistentConfig(
"YOUTUBE_LOADER_PROXY_URL",
"rag.youtube_loader_proxy_url",
os.getenv("YOUTUBE_LOADER_PROXY_URL", ""),
)
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", ""),
)
KAGI_SEARCH_API_KEY = PersistentConfig(
"KAGI_SEARCH_API_KEY",
"rag.web.search.kagi_search_api_key",
os.getenv("KAGI_SEARCH_API_KEY", ""),
)
MOJEEK_SEARCH_API_KEY = PersistentConfig(
"MOJEEK_SEARCH_API_KEY",
"rag.web.search.mojeek_search_api_key",
os.getenv("MOJEEK_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", ""),
)
JINA_API_KEY = PersistentConfig(
"JINA_API_KEY",
"rag.web.search.jina_api_key",
os.getenv("JINA_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", ""),
)
BING_SEARCH_V7_ENDPOINT = PersistentConfig(
"BING_SEARCH_V7_ENDPOINT",
"rag.web.search.bing_search_v7_endpoint",
os.environ.get(
"BING_SEARCH_V7_ENDPOINT", "https://api.bing.microsoft.com/v7.0/search"
),
)
BING_SEARCH_V7_SUBSCRIPTION_KEY = PersistentConfig(
"BING_SEARCH_V7_SUBSCRIPTION_KEY",
"rag.web.search.bing_search_v7_subscription_key",
os.environ.get("BING_SEARCH_V7_SUBSCRIPTION_KEY", ""),
)
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")),
)
####################################
# 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_SAMPLER",
"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_API_KEY = PersistentConfig(
"COMFYUI_API_KEY",
"image_generation.comfyui.api_key",
os.getenv("COMFYUI_API_KEY", ""),
)
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
####################################
# Transcription
WHISPER_MODEL = PersistentConfig(
"WHISPER_MODEL",
"audio.stt.whisper_model",
os.getenv("WHISPER_MODEL", "base"),
)
WHISPER_MODEL_DIR = os.getenv("WHISPER_MODEL_DIR", f"{CACHE_DIR}/whisper/models")
WHISPER_MODEL_AUTO_UPDATE = (
not OFFLINE_MODE
and os.environ.get("WHISPER_MODEL_AUTO_UPDATE", "").lower() == "true"
)
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", ""),
)
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"
),
)
####################################
# LDAP
####################################
ENABLE_LDAP = PersistentConfig(
"ENABLE_LDAP",
"ldap.enable",
os.environ.get("ENABLE_LDAP", "false").lower() == "true",
)
LDAP_SERVER_LABEL = PersistentConfig(
"LDAP_SERVER_LABEL",
"ldap.server.label",
os.environ.get("LDAP_SERVER_LABEL", "LDAP Server"),
)
LDAP_SERVER_HOST = PersistentConfig(
"LDAP_SERVER_HOST",
"ldap.server.host",
os.environ.get("LDAP_SERVER_HOST", "localhost"),
)
LDAP_SERVER_PORT = PersistentConfig(
"LDAP_SERVER_PORT",
"ldap.server.port",
int(os.environ.get("LDAP_SERVER_PORT", "389")),
)
LDAP_ATTRIBUTE_FOR_USERNAME = PersistentConfig(
"LDAP_ATTRIBUTE_FOR_USERNAME",
"ldap.server.attribute_for_username",
os.environ.get("LDAP_ATTRIBUTE_FOR_USERNAME", "uid"),
)
LDAP_APP_DN = PersistentConfig(
"LDAP_APP_DN", "ldap.server.app_dn", os.environ.get("LDAP_APP_DN", "")
)
LDAP_APP_PASSWORD = PersistentConfig(
"LDAP_APP_PASSWORD",
"ldap.server.app_password",
os.environ.get("LDAP_APP_PASSWORD", ""),
)
LDAP_SEARCH_BASE = PersistentConfig(
"LDAP_SEARCH_BASE", "ldap.server.users_dn", os.environ.get("LDAP_SEARCH_BASE", "")
)
LDAP_SEARCH_FILTERS = PersistentConfig(
"LDAP_SEARCH_FILTER",
"ldap.server.search_filter",
os.environ.get("LDAP_SEARCH_FILTER", ""),
)
LDAP_USE_TLS = PersistentConfig(
"LDAP_USE_TLS",
"ldap.server.use_tls",
os.environ.get("LDAP_USE_TLS", "True").lower() == "true",
)
LDAP_CA_CERT_FILE = PersistentConfig(
"LDAP_CA_CERT_FILE",
"ldap.server.ca_cert_file",
os.environ.get("LDAP_CA_CERT_FILE", ""),
)
LDAP_CIPHERS = PersistentConfig(
"LDAP_CIPHERS", "ldap.server.ciphers", os.environ.get("LDAP_CIPHERS", "ALL")
)
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