litellm-mirror/litellm/exceptions.py

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## LiteLLM versions of the OpenAI Exception Types

from typing import Optional

import httpx
import openai

from litellm.types.utils import LiteLLMCommonStrings
from litellm.litellm_core_utils.sensitive_data_masker import SensitiveDataMasker

# Initialize a single SensitiveDataMasker instance to be used across all exception classes
_sensitive_data_masker = SensitiveDataMasker()

def _mask_message(message):
    """Helper function to mask sensitive data in exception messages"""
    if not message:
        return message
        
    # Directly process the message string to mask sensitive patterns
    import re
    
    # Common API key patterns (sk-, pk-, api-, etc.)
    patterns = [
        # OpenAI and similar keys
        r'sk-[a-zA-Z0-9]{10,}',
        r'sk_[a-zA-Z0-9]{10,}',
        # AWS keys
        r'AKIA[0-9A-Z]{16}',
        r'[a-zA-Z0-9+/]{40}',  # AWS secret key pattern
        # Azure keys
        r'[a-zA-Z0-9]{32}', 
        # Database connection strings
        r'(mongodb(\+srv)?:\/\/)[^:]+:[^@]+@[^\/]+',
        # API tokens and keys
        r'key-[a-zA-Z0-9]{24,}',
        r'token-[a-zA-Z0-9]{24,}',
        # Named keys and secrets
        r'secret_[a-zA-Z0-9]{5,}',
        r'pass[a-zA-Z0-9]{3,}word',
        # Generic patterns with capture groups
        r'(API key[:=]?\s*)[\'"]?([a-zA-Z0-9_\-\.]{6,})[\'"]?',
        r'(api[_-]?key[:=]?\s*)[\'"]?([a-zA-Z0-9_\-\.]{6,})[\'"]?',
        r'(secret[_-]?key[:=]?\s*)[\'"]?([a-zA-Z0-9_\-\.]{6,})[\'"]?',
        r'(access[_-]?key[:=]?\s*)[\'"]?([a-zA-Z0-9_\-\.]{6,})[\'"]?',
        r'(password[:=]?\s*)[\'"]?([a-zA-Z0-9_\-\.]{6,})[\'"]?',
        r'(token[:=]?\s*)[\'"]?([a-zA-Z0-9_\-\.]{6,})[\'"]?',
    ]
    
    # Apply masking
    masked_message = message
    for pattern in patterns:
        if '(' in pattern and ')' in pattern:  # Has capturing groups
            # For patterns with capturing groups, keep the prefix and mask the value
            def replace_func(match):
                if len(match.groups()) > 1:
                    return match.group(1) + _sensitive_data_masker._mask_value(match.group(2))
                return _sensitive_data_masker._mask_value(match.group(0))
            
            masked_message = re.sub(pattern, replace_func, masked_message)
        else:
            # For patterns without capturing groups, mask the entire match
            masked_message = re.sub(pattern, lambda m: _sensitive_data_masker._mask_value(m.group(0)), masked_message)
    
    return masked_message

class AuthenticationError(openai.AuthenticationError):  # type: ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 401
        self.message = _mask_message("litellm.AuthenticationError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        self.response = response or httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="GET", url="https://litellm.ai"
            ),  # mock request object
        )
        super().__init__(
            self.message, response=self.response, body=None
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


# raise when invalid models passed, example gpt-8
class NotFoundError(openai.NotFoundError):  # type: ignore
    def __init__(
        self,
        message,
        model,
        llm_provider,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 404
        self.message = _mask_message("litellm.NotFoundError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        self.response = response or httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="GET", url="https://litellm.ai"
            ),  # mock request object
        )
        super().__init__(
            self.message, response=self.response, body=None
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class BadRequestError(openai.BadRequestError):  # type: ignore
    def __init__(
        self,
        message,
        model,
        llm_provider,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
        body: Optional[dict] = None,
    ):
        self.status_code = 400
        self.message = _mask_message("litellm.BadRequestError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        response = httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="GET", url="https://litellm.ai"
            ),  # mock request object
        )
        self.max_retries = max_retries
        self.num_retries = num_retries
        super().__init__(
            self.message, response=response, body=body
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class UnprocessableEntityError(openai.UnprocessableEntityError):  # type: ignore
    def __init__(
        self,
        message,
        model,
        llm_provider,
        response: httpx.Response,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 422
        self.message = _mask_message("litellm.UnprocessableEntityError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        super().__init__(
            self.message, response=response, body=None
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class Timeout(openai.APITimeoutError):  # type: ignore
    def __init__(
        self,
        message,
        model,
        llm_provider,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
        headers: Optional[dict] = None,
    ):
        request = httpx.Request(
            method="POST",
            url="https://api.openai.com/v1",
        )
        super().__init__(
            request=request
        )  # Call the base class constructor with the parameters it needs
        self.status_code = 408
        self.message = _mask_message("litellm.Timeout: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        self.headers = headers

    # custom function to convert to str
    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class PermissionDeniedError(openai.PermissionDeniedError):  # type:ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        response: httpx.Response,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 403
        self.message = _mask_message("litellm.PermissionDeniedError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        super().__init__(
            self.message, response=response, body=None
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class RateLimitError(openai.RateLimitError):  # type: ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 429
        self.message = _mask_message("litellm.RateLimitError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        _response_headers = (
            getattr(response, "headers", None) if response is not None else None
        )
        self.response = httpx.Response(
            status_code=429,
            headers=_response_headers,
            request=httpx.Request(
                method="POST",
                url=" https://cloud.google.com/vertex-ai/",
            ),
        )
        super().__init__(
            self.message, response=self.response, body=None
        )  # Call the base class constructor with the parameters it needs
        self.code = "429"
        self.type = "throttling_error"

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


# sub class of rate limit error - meant to give more granularity for error handling context window exceeded errors
class ContextWindowExceededError(BadRequestError):  # type: ignore
    def __init__(
        self,
        message,
        model,
        llm_provider,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
    ):
        self.status_code = 400
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        self.response = httpx.Response(status_code=400, request=request)
        super().__init__(
            message=message,
            model=self.model,  # type: ignore
            llm_provider=self.llm_provider,  # type: ignore
            response=self.response,
            litellm_debug_info=self.litellm_debug_info,
        )  # Call the base class constructor with the parameters it needs

        # set after, to make it clear the raised error is a context window exceeded error
        self.message = _mask_message("litellm.ContextWindowExceededError: {}".format(self.message))

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


# sub class of bad request error - meant to help us catch guardrails-related errors on proxy.
class RejectedRequestError(BadRequestError):  # type: ignore
    def __init__(
        self,
        message,
        model,
        llm_provider,
        request_data: dict,
        litellm_debug_info: Optional[str] = None,
    ):
        self.status_code = 400
        self.message = _mask_message("litellm.RejectedRequestError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        self.request_data = request_data
        request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        response = httpx.Response(status_code=400, request=request)
        super().__init__(
            message=self.message,
            model=self.model,  # type: ignore
            llm_provider=self.llm_provider,  # type: ignore
            response=response,
            litellm_debug_info=self.litellm_debug_info,
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class ContentPolicyViolationError(BadRequestError):  # type: ignore
    #  Error code: 400 - {'error': {'code': 'content_policy_violation', 'message': 'Your request was rejected as a result of our safety system. Image descriptions generated from your prompt may contain text that is not allowed by our safety system. If you believe this was done in error, your request may succeed if retried, or by adjusting your prompt.', 'param': None, 'type': 'invalid_request_error'}}
    def __init__(
        self,
        message,
        model,
        llm_provider,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
    ):
        self.status_code = 400
        self.message = _mask_message("litellm.ContentPolicyViolationError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        self.response = httpx.Response(status_code=400, request=request)
        super().__init__(
            message=self.message,
            model=self.model,  # type: ignore
            llm_provider=self.llm_provider,  # type: ignore
            response=self.response,
            litellm_debug_info=self.litellm_debug_info,
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class ServiceUnavailableError(openai.APIStatusError):  # type: ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 503
        self.message = _mask_message("litellm.ServiceUnavailableError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        self.response = httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="POST",
                url=" https://cloud.google.com/vertex-ai/",
            ),
        )
        super().__init__(
            self.message, response=self.response, body=None
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class InternalServerError(openai.InternalServerError):  # type: ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 500
        self.message = _mask_message("litellm.InternalServerError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        self.response = httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="POST",
                url=" https://cloud.google.com/vertex-ai/",
            ),
        )
        super().__init__(
            self.message, response=self.response, body=None
        )  # Call the base class constructor with the parameters it needs

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


# raise this when the API returns an invalid response object - https://github.com/openai/openai-python/blob/1be14ee34a0f8e42d3f9aa5451aa4cb161f1781f/openai/api_requestor.py#L401
class APIError(openai.APIError):  # type: ignore
    def __init__(
        self,
        status_code: int,
        message,
        llm_provider,
        model,
        request: Optional[httpx.Request] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = status_code
        self.message = _mask_message("litellm.APIError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        if request is None:
            request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        super().__init__(self.message, request=request, body=None)  # type: ignore

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


# raised if an invalid request (not get, delete, put, post) is made
class APIConnectionError(openai.APIConnectionError):  # type: ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        request: Optional[httpx.Request] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.message = _mask_message("litellm.APIConnectionError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.status_code = 500
        self.litellm_debug_info = litellm_debug_info
        self.request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        self.max_retries = max_retries
        self.num_retries = num_retries
        super().__init__(message=self.message, request=self.request)

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


# raised if an invalid request (not get, delete, put, post) is made
class APIResponseValidationError(openai.APIResponseValidationError):  # type: ignore
    def __init__(
        self,
        message,
        llm_provider,
        model,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.message = _mask_message("litellm.APIResponseValidationError: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        response = httpx.Response(status_code=500, request=request)
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        super().__init__(response=response, body=None, message=message)

    def __str__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message

    def __repr__(self):
        _message = self.message
        if self.num_retries:
            _message += f" LiteLLM Retried: {self.num_retries} times"
        if self.max_retries:
            _message += f", LiteLLM Max Retries: {self.max_retries}"
        return _message


class JSONSchemaValidationError(APIResponseValidationError):
    def __init__(
        self, model: str, llm_provider: str, raw_response: str, schema: str
    ) -> None:
        self.raw_response = raw_response
        self.schema = schema
        self.model = model
        message = _mask_message("litellm.JSONSchemaValidationError: model={}, returned an invalid response={}, for schema={}.\nAccess raw response with `e.raw_response`".format(
            model, raw_response, schema
        ))
        self.message = message
        super().__init__(model=model, message=message, llm_provider=llm_provider)


class OpenAIError(openai.OpenAIError):  # type: ignore
    def __init__(self, original_exception=None):
        super().__init__()
        self.llm_provider = "openai"


class UnsupportedParamsError(BadRequestError):
    def __init__(
        self,
        message,
        llm_provider: Optional[str] = None,
        model: Optional[str] = None,
        status_code: int = 400,
        response: Optional[httpx.Response] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = 400
        self.message = _mask_message("litellm.UnsupportedParamsError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        self.litellm_debug_info = litellm_debug_info
        response = response or httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="GET", url="https://litellm.ai"
            ),  # mock request object
        )
        self.max_retries = max_retries
        self.num_retries = num_retries


LITELLM_EXCEPTION_TYPES = [
    AuthenticationError,
    NotFoundError,
    BadRequestError,
    UnprocessableEntityError,
    UnsupportedParamsError,
    Timeout,
    PermissionDeniedError,
    RateLimitError,
    ContextWindowExceededError,
    RejectedRequestError,
    ContentPolicyViolationError,
    InternalServerError,
    ServiceUnavailableError,
    APIError,
    APIConnectionError,
    APIResponseValidationError,
    OpenAIError,
    InternalServerError,
    JSONSchemaValidationError,
]


class BudgetExceededError(Exception):
    def __init__(
        self, current_cost: float, max_budget: float, message: Optional[str] = None
    ):
        self.current_cost = current_cost
        self.max_budget = max_budget
        message = (
            message
            or _mask_message(f"Budget has been exceeded! Current cost: {current_cost}, Max budget: {max_budget}")
        )
        self.message = message
        super().__init__(message)


## DEPRECATED ##
class InvalidRequestError(openai.BadRequestError):  # type: ignore
    def __init__(self, message, model, llm_provider):
        self.status_code = 400
        self.message = _mask_message("litellm.InvalidRequestError: {}".format(message))
        self.model = model
        self.llm_provider = llm_provider
        response = httpx.Response(
            status_code=self.status_code,
            request=httpx.Request(
                method="GET", url="https://litellm.ai"
            ),  # mock request object
        )
        super().__init__(
            self.message, response=response, body=None
        )  # Call the base class constructor with the parameters it needs


class MockException(openai.APIError):
    # used for testing
    def __init__(
        self,
        status_code: int,
        message,
        llm_provider,
        model,
        request: Optional[httpx.Request] = None,
        litellm_debug_info: Optional[str] = None,
        max_retries: Optional[int] = None,
        num_retries: Optional[int] = None,
    ):
        self.status_code = status_code
        self.message = _mask_message("litellm.MockException: {}".format(message))
        self.llm_provider = llm_provider
        self.model = model
        self.litellm_debug_info = litellm_debug_info
        self.max_retries = max_retries
        self.num_retries = num_retries
        if request is None:
            request = httpx.Request(method="POST", url="https://api.openai.com/v1")
        super().__init__(self.message, request=request, body=None)  # type: ignore


class LiteLLMUnknownProvider(BadRequestError):
    def __init__(self, model: str, custom_llm_provider: Optional[str] = None):
        self.message = _mask_message(LiteLLMCommonStrings.llm_provider_not_provided.value.format(
            model=model, custom_llm_provider=custom_llm_provider
        ))
        super().__init__(
            self.message, model=model, llm_provider=custom_llm_provider, response=None
        )

    def __str__(self):
        return self.message