mirror of https://github.com/open-webui/open-webui
301 lines
8.5 KiB
Python
301 lines
8.5 KiB
Python
import os
|
|
import chromadb
|
|
from chromadb import Settings
|
|
from base64 import b64encode
|
|
from bs4 import BeautifulSoup
|
|
|
|
from pathlib import Path
|
|
import json
|
|
import markdown
|
|
import requests
|
|
import shutil
|
|
|
|
from secrets import token_bytes
|
|
from constants import ERROR_MESSAGES
|
|
|
|
|
|
try:
|
|
from dotenv import load_dotenv, find_dotenv
|
|
|
|
load_dotenv(find_dotenv("../.env"))
|
|
except ImportError:
|
|
print("dotenv not installed, skipping...")
|
|
|
|
WEBUI_NAME = "Open WebUI"
|
|
shutil.copyfile("../build/favicon.png", "./static/favicon.png")
|
|
|
|
####################################
|
|
# ENV (dev,test,prod)
|
|
####################################
|
|
|
|
ENV = os.environ.get("ENV", "dev")
|
|
|
|
try:
|
|
with open(f"../package.json", "r") as f:
|
|
PACKAGE_DATA = json.load(f)
|
|
except:
|
|
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:
|
|
with open("../CHANGELOG.md", "r") as file:
|
|
changelog_content = file.read()
|
|
except:
|
|
changelog_content = ""
|
|
|
|
# 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()
|
|
|
|
print(current)
|
|
|
|
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
|
|
|
|
|
|
####################################
|
|
# 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:
|
|
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("./static/favicon.png", "wb") as f:
|
|
r.raw.decode_content = True
|
|
shutil.copyfileobj(r.raw, f)
|
|
|
|
WEBUI_NAME = data["name"]
|
|
except Exception as e:
|
|
print(e)
|
|
pass
|
|
|
|
|
|
####################################
|
|
# DATA/FRONTEND BUILD DIR
|
|
####################################
|
|
|
|
DATA_DIR = str(Path(os.getenv("DATA_DIR", "./data")).resolve())
|
|
FRONTEND_BUILD_DIR = str(Path(os.getenv("FRONTEND_BUILD_DIR", "../build")))
|
|
|
|
try:
|
|
with open(f"{DATA_DIR}/config.json", "r") as f:
|
|
CONFIG_DATA = json.load(f)
|
|
except:
|
|
CONFIG_DATA = {}
|
|
|
|
####################################
|
|
# 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 = f"{DATA_DIR}/docs"
|
|
Path(DOCS_DIR).mkdir(parents=True, exist_ok=True)
|
|
|
|
####################################
|
|
# OLLAMA_API_BASE_URL
|
|
####################################
|
|
|
|
OLLAMA_API_BASE_URL = os.environ.get(
|
|
"OLLAMA_API_BASE_URL", "http://localhost:11434/api"
|
|
)
|
|
|
|
if ENV == "prod":
|
|
if OLLAMA_API_BASE_URL == "/ollama/api":
|
|
OLLAMA_API_BASE_URL = "http://host.docker.internal:11434/api"
|
|
|
|
####################################
|
|
# OPENAI_API
|
|
####################################
|
|
|
|
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"
|
|
|
|
|
|
####################################
|
|
# WEBUI
|
|
####################################
|
|
|
|
ENABLE_SIGNUP = os.environ.get("ENABLE_SIGNUP", True)
|
|
DEFAULT_MODELS = os.environ.get("DEFAULT_MODELS", None)
|
|
|
|
|
|
DEFAULT_PROMPT_SUGGESTIONS = (
|
|
CONFIG_DATA["ui"]["prompt_suggestions"]
|
|
if "ui" in CONFIG_DATA
|
|
and "prompt_suggestions" in CONFIG_DATA["ui"]
|
|
and type(CONFIG_DATA["ui"]["prompt_suggestions"]) is list
|
|
else [
|
|
{
|
|
"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.",
|
|
},
|
|
]
|
|
)
|
|
|
|
|
|
DEFAULT_USER_ROLE = os.getenv("DEFAULT_USER_ROLE", "pending")
|
|
USER_PERMISSIONS = {"chat": {"deletion": True}}
|
|
|
|
|
|
####################################
|
|
# WEBUI_VERSION
|
|
####################################
|
|
|
|
WEBUI_VERSION = os.environ.get("WEBUI_VERSION", "v1.0.0-alpha.100")
|
|
|
|
####################################
|
|
# WEBUI_AUTH (Required for security)
|
|
####################################
|
|
|
|
WEBUI_AUTH = True
|
|
|
|
####################################
|
|
# 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"
|
|
# 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 (all-MiniLM-L6-v2)
|
|
RAG_EMBEDDING_MODEL = os.environ.get("RAG_EMBEDDING_MODEL", "all-MiniLM-L6-v2")
|
|
# device type ebbeding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
|
|
RAG_EMBEDDING_MODEL_DEVICE_TYPE = os.environ.get(
|
|
"RAG_EMBEDDING_MODEL_DEVICE_TYPE", "cpu"
|
|
)
|
|
CHROMA_CLIENT = chromadb.PersistentClient(
|
|
path=CHROMA_DATA_PATH,
|
|
settings=Settings(allow_reset=True, anonymized_telemetry=False),
|
|
)
|
|
CHUNK_SIZE = 1500
|
|
CHUNK_OVERLAP = 100
|
|
|
|
|
|
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]"""
|
|
|
|
####################################
|
|
# Transcribe
|
|
####################################
|
|
|
|
WHISPER_MODEL = os.getenv("WHISPER_MODEL", "base")
|
|
WHISPER_MODEL_DIR = os.getenv("WHISPER_MODEL_DIR", f"{CACHE_DIR}/whisper/models")
|
|
|
|
|
|
####################################
|
|
# Images
|
|
####################################
|
|
|
|
AUTOMATIC1111_BASE_URL = os.getenv("AUTOMATIC1111_BASE_URL", "")
|