forked from open-webui/open-webui
530 lines
15 KiB
Python
530 lines
15 KiB
Python
import os
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import sys
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import logging
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import chromadb
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from chromadb import Settings
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from base64 import b64encode
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from bs4 import BeautifulSoup
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from pathlib import Path
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import json
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import yaml
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import markdown
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import requests
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import shutil
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from secrets import token_bytes
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from constants import ERROR_MESSAGES
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####################################
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# LOGGING
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####################################
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log_levels = ["CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG"]
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GLOBAL_LOG_LEVEL = os.environ.get("GLOBAL_LOG_LEVEL", "").upper()
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if GLOBAL_LOG_LEVEL in log_levels:
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logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL, force=True)
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else:
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GLOBAL_LOG_LEVEL = "INFO"
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log = logging.getLogger(__name__)
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log.info(f"GLOBAL_LOG_LEVEL: {GLOBAL_LOG_LEVEL}")
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log_sources = [
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"AUDIO",
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"COMFYUI",
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"CONFIG",
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"DB",
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"IMAGES",
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"LITELLM",
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"MAIN",
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"MODELS",
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"OLLAMA",
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"OPENAI",
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"RAG",
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"WEBHOOK",
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]
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SRC_LOG_LEVELS = {}
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for source in log_sources:
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log_env_var = source + "_LOG_LEVEL"
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SRC_LOG_LEVELS[source] = os.environ.get(log_env_var, "").upper()
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if SRC_LOG_LEVELS[source] not in log_levels:
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SRC_LOG_LEVELS[source] = GLOBAL_LOG_LEVEL
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log.info(f"{log_env_var}: {SRC_LOG_LEVELS[source]}")
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log.setLevel(SRC_LOG_LEVELS["CONFIG"])
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####################################
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# Load .env file
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####################################
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try:
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from dotenv import load_dotenv, find_dotenv
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load_dotenv(find_dotenv("../.env"))
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except ImportError:
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log.warning("dotenv not installed, skipping...")
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WEBUI_NAME = os.environ.get("WEBUI_NAME", "Open WebUI")
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WEBUI_FAVICON_URL = "https://openwebui.com/favicon.png"
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####################################
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# ENV (dev,test,prod)
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####################################
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ENV = os.environ.get("ENV", "dev")
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try:
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with open(f"../package.json", "r") as f:
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PACKAGE_DATA = json.load(f)
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except:
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PACKAGE_DATA = {"version": "0.0.0"}
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VERSION = PACKAGE_DATA["version"]
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# Function to parse each section
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def parse_section(section):
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items = []
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for li in section.find_all("li"):
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# Extract raw HTML string
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raw_html = str(li)
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# Extract text without HTML tags
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text = li.get_text(separator=" ", strip=True)
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# Split into title and content
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parts = text.split(": ", 1)
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title = parts[0].strip() if len(parts) > 1 else ""
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content = parts[1].strip() if len(parts) > 1 else text
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items.append({"title": title, "content": content, "raw": raw_html})
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return items
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try:
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with open("../CHANGELOG.md", "r") as file:
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changelog_content = file.read()
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except:
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changelog_content = ""
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# Convert markdown content to HTML
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html_content = markdown.markdown(changelog_content)
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# Parse the HTML content
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soup = BeautifulSoup(html_content, "html.parser")
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# Initialize JSON structure
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changelog_json = {}
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# Iterate over each version
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for version in soup.find_all("h2"):
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version_number = version.get_text().strip().split(" - ")[0][1:-1] # Remove brackets
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date = version.get_text().strip().split(" - ")[1]
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version_data = {"date": date}
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# Find the next sibling that is a h3 tag (section title)
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current = version.find_next_sibling()
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while current and current.name != "h2":
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if current.name == "h3":
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section_title = current.get_text().lower() # e.g., "added", "fixed"
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section_items = parse_section(current.find_next_sibling("ul"))
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version_data[section_title] = section_items
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# Move to the next element
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current = current.find_next_sibling()
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changelog_json[version_number] = version_data
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CHANGELOG = changelog_json
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####################################
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# DATA/FRONTEND BUILD DIR
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####################################
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DATA_DIR = str(Path(os.getenv("DATA_DIR", "./data")).resolve())
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FRONTEND_BUILD_DIR = str(Path(os.getenv("FRONTEND_BUILD_DIR", "../build")))
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try:
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with open(f"{DATA_DIR}/config.json", "r") as f:
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CONFIG_DATA = json.load(f)
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except:
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CONFIG_DATA = {}
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####################################
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# Static DIR
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####################################
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STATIC_DIR = str(Path(os.getenv("STATIC_DIR", "./static")).resolve())
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shutil.copyfile(f"{FRONTEND_BUILD_DIR}/favicon.png", f"{STATIC_DIR}/favicon.png")
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####################################
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# CUSTOM_NAME
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####################################
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CUSTOM_NAME = os.environ.get("CUSTOM_NAME", "")
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if CUSTOM_NAME:
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try:
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r = requests.get(f"https://api.openwebui.com/api/v1/custom/{CUSTOM_NAME}")
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data = r.json()
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if r.ok:
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if "logo" in data:
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WEBUI_FAVICON_URL = url = (
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f"https://api.openwebui.com{data['logo']}"
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if data["logo"][0] == "/"
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else data["logo"]
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)
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r = requests.get(url, stream=True)
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if r.status_code == 200:
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with open(f"{STATIC_DIR}/favicon.png", "wb") as f:
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r.raw.decode_content = True
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shutil.copyfileobj(r.raw, f)
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WEBUI_NAME = data["name"]
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except Exception as e:
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log.exception(e)
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pass
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else:
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if WEBUI_NAME != "Open WebUI":
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WEBUI_NAME += " (Open WebUI)"
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####################################
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# File Upload DIR
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####################################
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UPLOAD_DIR = f"{DATA_DIR}/uploads"
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Path(UPLOAD_DIR).mkdir(parents=True, exist_ok=True)
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####################################
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# Cache DIR
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####################################
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CACHE_DIR = f"{DATA_DIR}/cache"
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Path(CACHE_DIR).mkdir(parents=True, exist_ok=True)
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####################################
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# Docs DIR
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####################################
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DOCS_DIR = f"{DATA_DIR}/docs"
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Path(DOCS_DIR).mkdir(parents=True, exist_ok=True)
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####################################
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# LITELLM_CONFIG
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####################################
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def create_config_file(file_path):
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directory = os.path.dirname(file_path)
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# Check if directory exists, if not, create it
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if not os.path.exists(directory):
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os.makedirs(directory)
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# Data to write into the YAML file
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config_data = {
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"general_settings": {},
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"litellm_settings": {},
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"model_list": [],
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"router_settings": {},
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}
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# Write data to YAML file
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with open(file_path, "w") as file:
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yaml.dump(config_data, file)
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LITELLM_CONFIG_PATH = f"{DATA_DIR}/litellm/config.yaml"
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if not os.path.exists(LITELLM_CONFIG_PATH):
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log.info("Config file doesn't exist. Creating...")
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create_config_file(LITELLM_CONFIG_PATH)
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log.info("Config file created successfully.")
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####################################
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# OLLAMA_BASE_URL
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####################################
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OLLAMA_API_BASE_URL = os.environ.get(
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"OLLAMA_API_BASE_URL", "http://localhost:11434/api"
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)
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OLLAMA_BASE_URL = os.environ.get("OLLAMA_BASE_URL", "")
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K8S_FLAG = os.environ.get("K8S_FLAG", "")
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USE_OLLAMA_DOCKER = os.environ.get("USE_OLLAMA_DOCKER", "false")
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if OLLAMA_BASE_URL == "" and OLLAMA_API_BASE_URL != "":
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OLLAMA_BASE_URL = (
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OLLAMA_API_BASE_URL[:-4]
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if OLLAMA_API_BASE_URL.endswith("/api")
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else OLLAMA_API_BASE_URL
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)
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if ENV == "prod":
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if OLLAMA_BASE_URL == "/ollama" and not K8S_FLAG:
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if USE_OLLAMA_DOCKER.lower() == "true":
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# if you use all-in-one docker container (Open WebUI + Ollama)
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# with the docker build arg USE_OLLAMA=true (--build-arg="USE_OLLAMA=true") this only works with http://localhost:11434
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OLLAMA_BASE_URL = "http://localhost:11434"
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else:
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OLLAMA_BASE_URL = "http://host.docker.internal:11434"
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elif K8S_FLAG:
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OLLAMA_BASE_URL = "http://ollama-service.open-webui.svc.cluster.local:11434"
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OLLAMA_BASE_URLS = os.environ.get("OLLAMA_BASE_URLS", "")
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OLLAMA_BASE_URLS = OLLAMA_BASE_URLS if OLLAMA_BASE_URLS != "" else OLLAMA_BASE_URL
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OLLAMA_BASE_URLS = [url.strip() for url in OLLAMA_BASE_URLS.split(";")]
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####################################
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# OPENAI_API
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####################################
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OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", "")
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OPENAI_API_BASE_URL = os.environ.get("OPENAI_API_BASE_URL", "")
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if OPENAI_API_BASE_URL == "":
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OPENAI_API_BASE_URL = "https://api.openai.com/v1"
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OPENAI_API_KEYS = os.environ.get("OPENAI_API_KEYS", "")
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OPENAI_API_KEYS = OPENAI_API_KEYS if OPENAI_API_KEYS != "" else OPENAI_API_KEY
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OPENAI_API_KEYS = [url.strip() for url in OPENAI_API_KEYS.split(";")]
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OPENAI_API_BASE_URLS = os.environ.get("OPENAI_API_BASE_URLS", "")
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OPENAI_API_BASE_URLS = (
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OPENAI_API_BASE_URLS if OPENAI_API_BASE_URLS != "" else OPENAI_API_BASE_URL
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)
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OPENAI_API_BASE_URLS = [
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url.strip() if url != "" else "https://api.openai.com/v1"
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for url in OPENAI_API_BASE_URLS.split(";")
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]
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OPENAI_API_KEY = ""
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try:
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OPENAI_API_KEY = OPENAI_API_KEYS[
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OPENAI_API_BASE_URLS.index("https://api.openai.com/v1")
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]
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except:
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pass
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OPENAI_API_BASE_URL = "https://api.openai.com/v1"
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####################################
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# WEBUI
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####################################
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ENABLE_SIGNUP = os.environ.get("ENABLE_SIGNUP", "True").lower() == "true"
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DEFAULT_MODELS = os.environ.get("DEFAULT_MODELS", None)
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DEFAULT_PROMPT_SUGGESTIONS = (
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CONFIG_DATA["ui"]["prompt_suggestions"]
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if "ui" in CONFIG_DATA
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and "prompt_suggestions" in CONFIG_DATA["ui"]
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and type(CONFIG_DATA["ui"]["prompt_suggestions"]) is list
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else [
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{
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"title": ["Help me study", "vocabulary for a college entrance exam"],
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"content": "Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option.",
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},
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{
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"title": ["Give me ideas", "for what to do with my kids' art"],
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"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.",
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},
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{
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"title": ["Tell me a fun fact", "about the Roman Empire"],
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"content": "Tell me a random fun fact about the Roman Empire",
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},
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{
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"title": ["Show me a code snippet", "of a website's sticky header"],
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"content": "Show me a code snippet of a website's sticky header in CSS and JavaScript.",
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},
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]
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)
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DEFAULT_USER_ROLE = os.getenv("DEFAULT_USER_ROLE", "pending")
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USER_PERMISSIONS_CHAT_DELETION = (
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os.environ.get("USER_PERMISSIONS_CHAT_DELETION", "True").lower() == "true"
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)
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USER_PERMISSIONS = {"chat": {"deletion": USER_PERMISSIONS_CHAT_DELETION}}
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MODEL_FILTER_ENABLED = os.environ.get("MODEL_FILTER_ENABLED", "False").lower() == "true"
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MODEL_FILTER_LIST = os.environ.get("MODEL_FILTER_LIST", "")
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MODEL_FILTER_LIST = [model.strip() for model in MODEL_FILTER_LIST.split(";")]
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WEBHOOK_URL = os.environ.get("WEBHOOK_URL", "")
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ENABLE_ADMIN_EXPORT = os.environ.get("ENABLE_ADMIN_EXPORT", "True").lower() == "true"
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####################################
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# WEBUI_VERSION
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####################################
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WEBUI_VERSION = os.environ.get("WEBUI_VERSION", "v1.0.0-alpha.100")
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####################################
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# WEBUI_AUTH (Required for security)
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####################################
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WEBUI_AUTH = True
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WEBUI_AUTH_TRUSTED_EMAIL_HEADER = os.environ.get(
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"WEBUI_AUTH_TRUSTED_EMAIL_HEADER", None
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)
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####################################
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# WEBUI_SECRET_KEY
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####################################
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WEBUI_SECRET_KEY = os.environ.get(
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"WEBUI_SECRET_KEY",
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os.environ.get(
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"WEBUI_JWT_SECRET_KEY", "t0p-s3cr3t"
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), # DEPRECATED: remove at next major version
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)
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if WEBUI_AUTH and WEBUI_SECRET_KEY == "":
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raise ValueError(ERROR_MESSAGES.ENV_VAR_NOT_FOUND)
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####################################
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# RAG
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####################################
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CHROMA_DATA_PATH = f"{DATA_DIR}/vector_db"
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# 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)
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RAG_TOP_K = int(os.environ.get("RAG_TOP_K", "5"))
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RAG_RELEVANCE_THRESHOLD = float(os.environ.get("RAG_RELEVANCE_THRESHOLD", "0.0"))
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RAG_EMBEDDING_ENGINE = os.environ.get("RAG_EMBEDDING_ENGINE", "")
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RAG_EMBEDDING_MODEL = os.environ.get(
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"RAG_EMBEDDING_MODEL", "sentence-transformers/all-MiniLM-L6-v2"
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)
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log.info(f"Embedding model set: {RAG_EMBEDDING_MODEL}"),
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RAG_EMBEDDING_MODEL_AUTO_UPDATE = (
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os.environ.get("RAG_EMBEDDING_MODEL_AUTO_UPDATE", "").lower() == "true"
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)
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RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE = (
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os.environ.get("RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
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)
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RAG_RERANKING_MODEL = os.environ.get("RAG_RERANKING_MODEL", "")
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if not RAG_RERANKING_MODEL == "":
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log.info(f"Reranking model set: {RAG_RERANKING_MODEL}"),
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RAG_RERANKING_MODEL_AUTO_UPDATE = (
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os.environ.get("RAG_RERANKING_MODEL_AUTO_UPDATE", "").lower() == "true"
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)
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RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
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os.environ.get("RAG_RERANKING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
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)
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# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
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USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")
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if USE_CUDA.lower() == "true":
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DEVICE_TYPE = "cuda"
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else:
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DEVICE_TYPE = "cpu"
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CHROMA_CLIENT = chromadb.PersistentClient(
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path=CHROMA_DATA_PATH,
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settings=Settings(allow_reset=True, anonymized_telemetry=False),
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)
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CHUNK_SIZE = int(os.environ.get("CHUNK_SIZE", "1500"))
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CHUNK_OVERLAP = int(os.environ.get("CHUNK_OVERLAP", "100"))
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DEFAULT_RAG_TEMPLATE = """Use the following context as your learned knowledge, inside <context></context> XML tags.
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<context>
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[context]
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</context>
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When answer to user:
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- If you don't know, just say that you don't know.
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- If you don't know when you are not sure, ask for clarification.
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Avoid mentioning that you obtained the information from the context.
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And answer according to the language of the user's question.
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Given the context information, answer the query.
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Query: [query]"""
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RAG_TEMPLATE = os.environ.get("RAG_TEMPLATE", DEFAULT_RAG_TEMPLATE)
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RAG_OPENAI_API_BASE_URL = os.getenv("RAG_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL)
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RAG_OPENAI_API_KEY = os.getenv("RAG_OPENAI_API_KEY", OPENAI_API_KEY)
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####################################
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# Transcribe
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####################################
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WHISPER_MODEL = os.getenv("WHISPER_MODEL", "base")
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WHISPER_MODEL_DIR = os.getenv("WHISPER_MODEL_DIR", f"{CACHE_DIR}/whisper/models")
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WHISPER_MODEL_AUTO_UPDATE = (
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os.environ.get("WHISPER_MODEL_AUTO_UPDATE", "").lower() == "true"
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)
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|
|
|
|
|
####################################
|
|
# Images
|
|
####################################
|
|
|
|
ENABLE_IMAGE_GENERATION = (
|
|
os.environ.get("ENABLE_IMAGE_GENERATION", "").lower() == "true"
|
|
)
|
|
AUTOMATIC1111_BASE_URL = os.getenv("AUTOMATIC1111_BASE_URL", "")
|
|
COMFYUI_BASE_URL = os.getenv("COMFYUI_BASE_URL", "")
|
|
|
|
|
|
IMAGES_OPENAI_API_BASE_URL = os.getenv(
|
|
"IMAGES_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL
|
|
)
|
|
IMAGES_OPENAI_API_KEY = os.getenv("IMAGES_OPENAI_API_KEY", OPENAI_API_KEY)
|
|
|
|
|
|
####################################
|
|
# Audio
|
|
####################################
|
|
|
|
AUDIO_OPENAI_API_BASE_URL = os.getenv("AUDIO_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL)
|
|
AUDIO_OPENAI_API_KEY = os.getenv("AUDIO_OPENAI_API_KEY", OPENAI_API_KEY)
|
|
|
|
####################################
|
|
# LiteLLM
|
|
####################################
|
|
|
|
LITELLM_PROXY_PORT = int(os.getenv("LITELLM_PROXY_PORT", "14365"))
|
|
if LITELLM_PROXY_PORT < 0 or LITELLM_PROXY_PORT > 65535:
|
|
raise ValueError("Invalid port number for LITELLM_PROXY_PORT")
|
|
LITELLM_PROXY_HOST = os.getenv("LITELLM_PROXY_HOST", "127.0.0.1")
|