import os
import chromadb
from chromadb import Settings
from secrets import token_bytes
from base64 import b64encode
from constants import ERROR_MESSAGES
from pathlib import Path

try:
    from dotenv import load_dotenv, find_dotenv

    load_dotenv(find_dotenv("../.env"))
except ImportError:
    print("dotenv not installed, skipping...")


####################################
# ENV (dev,test,prod)
####################################

ENV = os.environ.get("ENV", "dev")


####################################
# 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")))

####################################
# 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_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 = os.environ.get(
    "DEFAULT_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.",
        },
    ],
)
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"
EMBED_MODEL = "all-MiniLM-L6-v2"
CHROMA_CLIENT = chromadb.PersistentClient(
    path=CHROMA_DATA_PATH,
    settings=Settings(allow_reset=True, anonymized_telemetry=False),
)
CHUNK_SIZE = 1500
CHUNK_OVERLAP = 100

####################################
# Transcribe
####################################

WHISPER_MODEL = os.getenv("WHISPER_MODEL", "base")
WHISPER_MODEL_DIR = os.getenv("WHISPER_MODEL_DIR", f"{CACHE_DIR}/whisper/models")
