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"""
Global constants.
"""
from enum import IntEnum
import os
REPO_PATH = os.path.dirname(os.path.dirname(__file__))
##### For the gradio web server
SERVER_ERROR_MSG = (
"**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**"
)
MODERATION_MSG = "$MODERATION$ YOUR INPUT VIOLATES OUR CONTENT MODERATION GUIDELINES."
CONVERSATION_LIMIT_MSG = "YOU HAVE REACHED THE CONVERSATION LENGTH LIMIT. PLEASE CLEAR HISTORY AND START A NEW CONVERSATION."
INACTIVE_MSG = "THIS SESSION HAS BEEN INACTIVE FOR TOO LONG. PLEASE REFRESH THIS PAGE."
SLOW_MODEL_MSG = "⚠️ Both models will show the responses all at once. Please stay patient as it may take over 30 seconds."
# Maximum input length
INPUT_CHAR_LEN_LIMIT = int(os.getenv("FASTCHAT_INPUT_CHAR_LEN_LIMIT", 12000))
# Maximum conversation turns
CONVERSATION_TURN_LIMIT = 50
# Session expiration time
SESSION_EXPIRATION_TIME = 3600
# The output dir of log files
LOGDIR = os.getenv("LOGDIR", ".")
# CPU Instruction Set Architecture
CPU_ISA = os.getenv("CPU_ISA")
##### For the controller and workers (could be overwritten through ENV variables.)
CONTROLLER_HEART_BEAT_EXPIRATION = int(
os.getenv("FASTCHAT_CONTROLLER_HEART_BEAT_EXPIRATION", 90)
)
WORKER_HEART_BEAT_INTERVAL = int(os.getenv("FASTCHAT_WORKER_HEART_BEAT_INTERVAL", 45))
WORKER_API_TIMEOUT = int(os.getenv("FASTCHAT_WORKER_API_TIMEOUT", 100))
WORKER_API_EMBEDDING_BATCH_SIZE = int(
os.getenv("FASTCHAT_WORKER_API_EMBEDDING_BATCH_SIZE", 4)
)
class ErrorCode(IntEnum):
"""
https://platform.openai.com/docs/guides/error-codes/api-errors
"""
VALIDATION_TYPE_ERROR = 40001
INVALID_AUTH_KEY = 40101
INCORRECT_AUTH_KEY = 40102
NO_PERMISSION = 40103
INVALID_MODEL = 40301
PARAM_OUT_OF_RANGE = 40302
CONTEXT_OVERFLOW = 40303
RATE_LIMIT = 42901
QUOTA_EXCEEDED = 42902
ENGINE_OVERLOADED = 42903
INTERNAL_ERROR = 50001
CUDA_OUT_OF_MEMORY = 50002
GRADIO_REQUEST_ERROR = 50003
GRADIO_STREAM_UNKNOWN_ERROR = 50004
CONTROLLER_NO_WORKER = 50005
CONTROLLER_WORKER_TIMEOUT = 50006
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