backend/config.py

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()

RESET_CONFIG_ON_START = (
    os.environ.get("RESET_CONFIG_ON_START", "False").lower() == "true"
)
if RESET_CONFIG_ON_START:
    try:
        os.remove(f"{DATA_DIR}/config.json")
        with open(f"{DATA_DIR}/config.json", "w") as f:
            f.write("{}")
    except:
        pass

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
)
WEBUI_AUTH_TRUSTED_NAME_HEADER = os.environ.get("WEBUI_AUTH_TRUSTED_NAME_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():
    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}")

####################################
# 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)


####################################
# Tools DIR
####################################

TOOLS_DIR = os.getenv("TOOLS_DIR", f"{DATA_DIR}/tools")
Path(TOOLS_DIR).mkdir(parents=True, exist_ok=True)


####################################
# Functions DIR
####################################

FUNCTIONS_DIR = os.getenv("FUNCTIONS_DIR", f"{DATA_DIR}/functions")
Path(FUNCTIONS_DIR).mkdir(parents=True, exist_ok=True)


####################################
# LITELLM_CONFIG
####################################


def create_config_file(file_path):
    directory = os.path.dirname(file_path)

    # Check if directory exists, if not, create it
    if not os.path.exists(directory):
        os.makedirs(directory)

    # Data to write into the YAML file
    config_data = {
        "general_settings": {},
        "litellm_settings": {},
        "model_list": [],
        "router_settings": {},
    }

    # Write data to YAML file
    with open(file_path, "w") as file:
        yaml.dump(config_data, file)


LITELLM_CONFIG_PATH = f"{DATA_DIR}/litellm/config.yaml"

# if not os.path.exists(LITELLM_CONFIG_PATH):
#     log.info("Config file doesn't exist. Creating...")
#     create_config_file(LITELLM_CONFIG_PATH)
#     log.info("Config file created successfully.")


####################################
# OLLAMA_BASE_URL
####################################


ENABLE_OLLAMA_API = PersistentConfig(
    "ENABLE_OLLAMA_API",
    "ollama.enable",
    os.environ.get("ENABLE_OLLAMA_API", "True").lower() == "true",
)

OLLAMA_API_BASE_URL = os.environ.get(
    "OLLAMA_API_BASE_URL", "http://localhost:11434/api"
)

OLLAMA_BASE_URL = os.environ.get("OLLAMA_BASE_URL", "")
AIOHTTP_CLIENT_TIMEOUT = os.environ.get("AIOHTTP_CLIENT_TIMEOUT", "300")

if AIOHTTP_CLIENT_TIMEOUT == "":
    AIOHTTP_CLIENT_TIMEOUT = None
else:
    AIOHTTP_CLIENT_TIMEOUT = int(AIOHTTP_CLIENT_TIMEOUT)


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": ["创作一张动漫壁纸", "动漫壁纸创作"],
            "content": "按照如下关键词画图：可爱的女孩，棕色的长卷发，迪士尼风格，8k分辨率，超清，极其详细的CG8k壁纸，杰作。",
        },
        {
            "title": ["与我谈一谈！", "来一场轻松的对话"],
            "content": "我希望你能充当一个高级的对话生成器。我会给你一个由我和一个我认识了两个月的女生之间的对话作为初始输入。例如：“我：你好吗？她：我很好，谢谢。”。在这之后，我希望你能从我的角度，根据前文的上下文，生成一个回应。这个回应应该以“我：”开头，并且不需要与她的回答形成连续的对话。我希望这个回应是幽默、有趣、体贴和温柔的，同时能够扩展话题，使得整个对话显得轻松愉快。如果你理解了我的要求，请回答：“好的，请提供初始对话。”",
        },
        {
            "title": ["心理健康顾问", "说一说你近期的问题吧"],
            "content": "我希望你扮演一名心理健康顾问。我会为你提供一个寻求关于管理情绪、压力、焦虑和其他心理健康问题的指导和建议的个体。请你运用认知行为疗法、冥想技巧、正念实践和其他治疗方法的知识，为这个个体创建策略，以便他们可以实施来提高他们的整体幸福感。我的第一个请求是'遇到的问题'。",
        },
        {
            "title": ["哲学启蒙导师", "讨论一些哲学问题"],
            "content": "我希望你扮演一名哲学家。我会为你提供与哲学研究相关的一些主题或问题，你的任务是深入探讨这些概念。这可能涉及对各种哲学理论的研究、提出新的观点或为解决复杂问题找到创造性的解决方案。我的第一个请求是'哲学主题'。",
        },
        {
            "title": [
                "Linux内核专家",
                "帮助用户更好地理解和使用 Linux 内核",
            ],
            "content": "你是一位精通 Linux 内核的专家，对最新内核源代码有着深入的理解和分析能力。\
你的能力范围：\
解释内核的实现机制，包括但不限于：  \
内存管理  \
进程调度  \
文件系统  \
网络协议栈  \
驱动程序  \
安全机制  \
提供与内核源代码相关的具体细节，例如：  \
某个特定函数的实现  \
数据结构的定义  \
代码路径的分析  \
性能优化建议  \
回答关于内核工作原理、配置、调试等方面的问题  \
你的角色目标： 帮助用户更好地理解和使用 Linux 内核。",
        },
        {
            "title": ["IT系统架构师", "资深IT架构师，擅长需求分析、系统设计、技术选型和跨平台系统优化。5年以上经验，精通Windows、macOS和Linux三大操作系统，具备故障排除和安全防护能力"],
            "content": "我希望你充当 IT 专家的身份为我提供协助，我将提供解决技术问题所需的所有相关信息，您的任务是协助我解决问题。请您运用项目管理及敏捷开发的专长来制定解决方案。在回复时，若能采用通俗易懂、适合不同层次理解的语言，并按要点分步阐述，将极为有益。我更倾向于直接获得解决方案，而非冗长的解释，除非我明确提出要求。\
作为 IT 架构师，你的职能包括：\
1. 需求分析：与客户和项目团队合作，理解业务需求，确定技术规格和性能要求。\
2. 系统设计：根据需求设计整体 IT 架构，包括服务器、存储、网络、安全等。\
3. 技术选型：研究和评估新技术，选择最合适的技术路线和解决方案。\
4. 性能优化：负责 IT 系统的性能调试和优化，确保系统高效稳定运行。\
5. 协同工作：与软件工程师、硬件工程师、网络工程师等协作，确保软硬件的兼容性和整体性能。\
6. 供应商管理：与供应商合作，评估和选择硬件和软件产品，确保供应链的质量和效率。\
你的背景和经验包括：\
1. 教育背景：计算机科学或相关专业本科及以上学历。\
2. 工作经验：具备 5 年以上的 IT 架构设计经验，熟悉服务器、存储、网络等硬件和软件技术。\
3. 专业知识：对服务器硬件、存储、网络、安全等技术有深入了解。\
4. 技能能力：  \
    a. 熟悉硬件性能测试和优化。  \
    b. 熟练使用相关设计工具和软件。  \
    c. 良好的项目管理能力，能够进行风险评估和时间控制。\
5. 持续学习：具有创新精神和快速学习能力，能够适应新技术的发展。\
6. 问题解决能力：能够快速识别和解决技术问题，做出有效决策。\
你精通 Windows、macOS 和 Linux 三大操作系统，对其有深刻理解和高超的 IT 技巧，并具备以下能力：\
1. 跨平台技能：你精通 Windows、macOS 和 Linux 三大操作系统，能够在这三个平台上进行系统架构设计、部署和维护。\
2. 系统优化：你能够根据不同操作系统的特点进行深度优化，提高系统性能，确保资源的高效利用。\
3. 故障排除：你具备快速诊断和解决跨平台系统问题的能力，无论是硬件兼容性问题还是软件配置问题。\
4. 安全性：你熟悉不同操作系统的安全特性，能够设计出既安全又高效的系统架构，防范潜在的安全威胁。\
5. 自动化和脚本编写：你擅长使用 PowerShell、Bash、Python 等编程语言进行自动化任务编写，提高工作效率。\
6. 背景和经验：  \
    a. 教育背景：计算机科学或相关专业，拥有丰富的理论知识和技术背景。  \
    b. 工作经验：在多个项目中担任关键角色，负责跨平台系统的架构设计和实施。  \
    c. 专业认证：持有 Windows、Linux 或 macOS 相关的专业认证，如 MCSE、LPIC、Apple Certified Technical Coordinator 等。",
        },
    ],
)

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("[]")],
)


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",
        """Here is the query:
{{prompt:middletruncate:8000}}

Create a concise, 3-5 word phrase with an emoji as a title for the previous query. 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""",
    ),
)


SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = PersistentConfig(
    "SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE",
    "task.search.prompt_template",
    os.environ.get(
        "SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE",
        """You are tasked with generating web search queries. Give me an appropriate query to answer my question for google search. Answer with only the query. Today is {{CURRENT_DATE}}.
        
Question:
{{prompt:end:4000}}""",
    ),
)

SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = PersistentConfig(
    "SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD",
    "task.search.prompt_length_threshold",
    int(
        os.environ.get(
            "SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD",
            100,
        )
    ),
)

TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = PersistentConfig(
    "TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE",
    "task.tools.prompt_template",
    os.environ.get(
        "TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE",
        """Tools: {{TOOLS}}
If a function tool doesn't match the query, return an empty string. Else, pick a function tool, fill in the parameters from the function tool's schema, and return it in the format { "name": \"functionName\", "parameters": { "key": "value" } }. Only pick a function if the user asks.  Only return the object. Do not return any other text.""",
    ),
)


####################################
# 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_EMBEDDING_OPENAI_BATCH_SIZE = PersistentConfig(
    "RAG_EMBEDDING_OPENAI_BATCH_SIZE",
    "rag.embedding_openai_batch_size",
    os.environ.get("RAG_EMBEDDING_OPENAI_BATCH_SIZE", 1),
)

RAG_RERANKING_MODEL = PersistentConfig(
    "RAG_RERANKING_MODEL",
    "rag.reranking_model",
    os.environ.get("RAG_RERANKING_MODEL", ""),
)
if RAG_RERANKING_MODEL.value != "":
    log.info(f"Reranking model set: {RAG_RERANKING_MODEL.value}"),

RAG_RERANKING_MODEL_AUTO_UPDATE = (
    os.environ.get("RAG_RERANKING_MODEL_AUTO_UPDATE", "").lower() == "true"
)

RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
    os.environ.get("RAG_RERANKING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
)


if CHROMA_HTTP_HOST != "":
    CHROMA_CLIENT = chromadb.HttpClient(
        host=CHROMA_HTTP_HOST,
        port=CHROMA_HTTP_PORT,
        headers=CHROMA_HTTP_HEADERS,
        ssl=CHROMA_HTTP_SSL,
        tenant=CHROMA_TENANT,
        database=CHROMA_DATABASE,
        settings=Settings(allow_reset=True, anonymized_telemetry=False),
    )
else:
    CHROMA_CLIENT = chromadb.PersistentClient(
        path=CHROMA_DATA_PATH,
        settings=Settings(allow_reset=True, anonymized_telemetry=False),
        tenant=CHROMA_TENANT,
        database=CHROMA_DATABASE,
    )


# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")

if USE_CUDA.lower() == "true":
    DEVICE_TYPE = "cuda"
else:
    DEVICE_TYPE = "cpu"

CHUNK_SIZE = PersistentConfig(
    "CHUNK_SIZE", "rag.chunk_size", int(os.environ.get("CHUNK_SIZE", "1500"))
)
CHUNK_OVERLAP = PersistentConfig(
    "CHUNK_OVERLAP",
    "rag.chunk_overlap",
    int(os.environ.get("CHUNK_OVERLAP", "100")),
)

DEFAULT_RAG_TEMPLATE = """Use the following context as your learned knowledge, inside <context></context> XML tags.
<context>
    [context]
</context>

When answer to user:
- If you don't know, just say that you don't know.
- If you don't know when you are not sure, ask for clarification.
Avoid mentioning that you obtained the information from the context.
And answer according to the language of the user's question.

Given the context information, answer the query.
Query: [query]"""

RAG_TEMPLATE = PersistentConfig(
    "RAG_TEMPLATE",
    "rag.template",
    os.environ.get("RAG_TEMPLATE", DEFAULT_RAG_TEMPLATE),
)

RAG_OPENAI_API_BASE_URL = PersistentConfig(
    "RAG_OPENAI_API_BASE_URL",
    "rag.openai_api_base_url",
    os.getenv("RAG_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL),
)
RAG_OPENAI_API_KEY = PersistentConfig(
    "RAG_OPENAI_API_KEY",
    "rag.openai_api_key",
    os.getenv("RAG_OPENAI_API_KEY", OPENAI_API_KEY),
)

ENABLE_RAG_LOCAL_WEB_FETCH = (
    os.getenv("ENABLE_RAG_LOCAL_WEB_FETCH", "False").lower() == "true"
)

YOUTUBE_LOADER_LANGUAGE = PersistentConfig(
    "YOUTUBE_LOADER_LANGUAGE",
    "rag.youtube_loader_language",
    os.getenv("YOUTUBE_LOADER_LANGUAGE", "en").split(","),
)


ENABLE_RAG_WEB_SEARCH = PersistentConfig(
    "ENABLE_RAG_WEB_SEARCH",
    "rag.web.search.enable",
    os.getenv("ENABLE_RAG_WEB_SEARCH", "False").lower() == "true",
)

RAG_WEB_SEARCH_ENGINE = PersistentConfig(
    "RAG_WEB_SEARCH_ENGINE",
    "rag.web.search.engine",
    os.getenv("RAG_WEB_SEARCH_ENGINE", ""),
)

# You can provide a list of your own websites to filter after performing a web search.
# This ensures the highest level of safety and reliability of the information sources.
RAG_WEB_SEARCH_DOMAIN_FILTER_LIST = PersistentConfig(
    "RAG_WEB_SEARCH_DOMAIN_FILTER_LIST",
    "rag.rag.web.search.domain.filter_list",
    [
        # "wikipedia.com",
        # "wikimedia.org",
        # "wikidata.org",
    ],
)

SEARXNG_QUERY_URL = PersistentConfig(
    "SEARXNG_QUERY_URL",
    "rag.web.search.searxng_query_url",
    os.getenv("SEARXNG_QUERY_URL", ""),
)

GOOGLE_PSE_API_KEY = PersistentConfig(
    "GOOGLE_PSE_API_KEY",
    "rag.web.search.google_pse_api_key",
    os.getenv("GOOGLE_PSE_API_KEY", ""),
)

GOOGLE_PSE_ENGINE_ID = PersistentConfig(
    "GOOGLE_PSE_ENGINE_ID",
    "rag.web.search.google_pse_engine_id",
    os.getenv("GOOGLE_PSE_ENGINE_ID", ""),
)

BRAVE_SEARCH_API_KEY = PersistentConfig(
    "BRAVE_SEARCH_API_KEY",
    "rag.web.search.brave_search_api_key",
    os.getenv("BRAVE_SEARCH_API_KEY", ""),
)

SERPSTACK_API_KEY = PersistentConfig(
    "SERPSTACK_API_KEY",
    "rag.web.search.serpstack_api_key",
    os.getenv("SERPSTACK_API_KEY", ""),
)

SERPSTACK_HTTPS = PersistentConfig(
    "SERPSTACK_HTTPS",
    "rag.web.search.serpstack_https",
    os.getenv("SERPSTACK_HTTPS", "True").lower() == "true",
)

SERPER_API_KEY = PersistentConfig(
    "SERPER_API_KEY",
    "rag.web.search.serper_api_key",
    os.getenv("SERPER_API_KEY", ""),
)

SERPLY_API_KEY = PersistentConfig(
    "SERPLY_API_KEY",
    "rag.web.search.serply_api_key",
    os.getenv("SERPLY_API_KEY", ""),
)

TAVILY_API_KEY = PersistentConfig(
    "TAVILY_API_KEY",
    "rag.web.search.tavily_api_key",
    os.getenv("TAVILY_API_KEY", ""),
)

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", ""),
)

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", ""),
)

COMFYUI_CFG_SCALE = PersistentConfig(
    "COMFYUI_CFG_SCALE",
    "image_generation.comfyui.cfg_scale",
    os.getenv("COMFYUI_CFG_SCALE", ""),
)

COMFYUI_SAMPLER = PersistentConfig(
    "COMFYUI_SAMPLER",
    "image_generation.comfyui.sampler",
    os.getenv("COMFYUI_SAMPLER", ""),
)

COMFYUI_SCHEDULER = PersistentConfig(
    "COMFYUI_SCHEDULER",
    "image_generation.comfyui.scheduler",
    os.getenv("COMFYUI_SCHEDULER", ""),
)

COMFYUI_SD3 = PersistentConfig(
    "COMFYUI_SD3",
    "image_generation.comfyui.sd3",
    os.environ.get("COMFYUI_SD3", "").lower() == "true",
)

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_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"),
)

AUDIO_TTS_VOICE = PersistentConfig(
    "AUDIO_TTS_VOICE",
    "audio.tts.voice",
    os.getenv("AUDIO_TTS_VOICE", "alloy"),
)


####################################
# Database
####################################

DATABASE_URL = os.environ.get("DATABASE_URL", f"sqlite:///{DATA_DIR}/webui.db")