import logging
import os
from typing import Any, Callable, Optional, Tuple, Union

from llama_index.core.base.llms.generic_utils import get_from_param_or_env
from tenacity import (
    before_sleep_log,
    retry,
    retry_if_exception_type,
    stop_after_attempt,
    stop_after_delay,
    wait_exponential,
    wait_random_exponential,
)
from tenacity.stop import stop_base

import openai
from openai.types.chat import ChatCompletionMessageToolCall
from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall

DEFAULT_OPENAI_API_BASE = "https://api.openai.com/v1"
DEFAULT_OPENAI_API_VERSION = ""

MISSING_API_KEY_ERROR_MESSAGE = """No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or \
openai.api_key prior to initialization.
API keys can be found or created at \
https://platform.openai.com/account/api-keys
"""

logger = logging.getLogger(__name__)

OpenAIToolCall = Union[ChatCompletionMessageToolCall, ChoiceDeltaToolCall]


def create_retry_decorator(
    max_retries: int,
    random_exponential: bool = False,
    stop_after_delay_seconds: Optional[float] = None,
    min_seconds: float = 4,
    max_seconds: float = 10,
) -> Callable[[Any], Any]:
    wait_strategy = (
        wait_random_exponential(min=min_seconds, max=max_seconds)
        if random_exponential
        else wait_exponential(multiplier=1, min=min_seconds, max=max_seconds)
    )

    stop_strategy: stop_base = stop_after_attempt(max_retries)
    if stop_after_delay_seconds is not None:
        stop_strategy = stop_strategy | stop_after_delay(stop_after_delay_seconds)

    return retry(
        reraise=True,
        stop=stop_strategy,
        wait=wait_strategy,
        retry=(
            retry_if_exception_type(
                (
                    openai.APIConnectionError,
                    openai.APITimeoutError,
                    openai.RateLimitError,
                    openai.InternalServerError,
                )
            )
        ),
        before_sleep=before_sleep_log(logger, logging.WARNING),
    )


def resolve_openai_credentials(
    api_key: Optional[str] = None,
    api_base: Optional[str] = None,
    api_version: Optional[str] = None,
) -> Tuple[Optional[str], str, str]:
    """
    "Resolve OpenAI credentials.

    The order of precedence is:
    1. param
    2. env
    3. openai module
    4. default
    """
    # resolve from param or env
    api_key = get_from_param_or_env("api_key", api_key, "OPENAI_API_KEY", "")
    api_base = get_from_param_or_env("api_base", api_base, "OPENAI_API_BASE", "")
    api_version = get_from_param_or_env(
        "api_version", api_version, "OPENAI_API_VERSION", ""
    )

    # resolve from openai module or default
    final_api_key = api_key or openai.api_key or ""
    final_api_base = api_base or openai.base_url or DEFAULT_OPENAI_API_BASE
    final_api_version = api_version or openai.api_version or DEFAULT_OPENAI_API_VERSION

    return final_api_key, str(final_api_base), final_api_version


def validate_openai_api_key(api_key: Optional[str] = None) -> None:
    openai_api_key = api_key or os.environ.get("OPENAI_API_KEY", "")

    if not openai_api_key:
        raise ValueError(MISSING_API_KEY_ERROR_MESSAGE)

import logging
import os
from typing import Any, Callable, Optional, Tuple, Union

from llama_index.core.base.llms.generic_utils import get_from_param_or_env
from tenacity import (
    before_sleep_log,
    retry,
    retry_if_exception_type,
    stop_after_attempt,
    stop_after_delay,
    wait_exponential,
    wait_random_exponential,
)
from tenacity.stop import stop_base

import openai
from openai.types.chat import ChatCompletionMessageToolCall
from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall

DEFAULT_OPENAI_API_BASE = "https://api.openai.com/v1"
DEFAULT_OPENAI_API_VERSION = ""

MISSING_API_KEY_ERROR_MESSAGE = """No API key found for OpenAI.
Please set either the OPENAI_API_KEY environment variable or \
openai.api_key prior to initialization.
API keys can be found or created at \
https://platform.openai.com/account/api-keys
"""

logger = logging.getLogger(__name__)

OpenAIToolCall = Union[ChatCompletionMessageToolCall, ChoiceDeltaToolCall]


def create_retry_decorator(
    max_retries: int,
    random_exponential: bool = False,
    stop_after_delay_seconds: Optional[float] = None,
    min_seconds: float = 4,
    max_seconds: float = 10,
) -> Callable[[Any], Any]:
    wait_strategy = (
        wait_random_exponential(min=min_seconds, max=max_seconds)
        if random_exponential
        else wait_exponential(multiplier=1, min=min_seconds, max=max_seconds)
    )

    stop_strategy: stop_base = stop_after_attempt(max_retries)
    if stop_after_delay_seconds is not None:
        stop_strategy = stop_strategy | stop_after_delay(stop_after_delay_seconds)

    return retry(
        reraise=True,
        stop=stop_strategy,
        wait=wait_strategy,
        retry=(
            retry_if_exception_type(
                (
                    openai.APIConnectionError,
                    openai.APITimeoutError,
                    openai.RateLimitError,
                    openai.InternalServerError,
                )
            )
        ),
        before_sleep=before_sleep_log(logger, logging.WARNING),
    )


def resolve_openai_credentials(
    api_key: Optional[str] = None,
    api_base: Optional[str] = None,
    api_version: Optional[str] = None,
) -> Tuple[Optional[str], str, str]:
    """ "Resolve OpenAI credentials.

    The order of precedence is:
    1. param
    2. env
    3. openai module
    4. default
    """
    # resolve from param or env
    api_key = get_from_param_or_env("api_key", api_key, "OPENAI_API_KEY", "")
    api_base = get_from_param_or_env("api_base", api_base, "OPENAI_API_BASE", "")
    api_version = get_from_param_or_env(
        "api_version", api_version, "OPENAI_API_VERSION", ""
    )

    # resolve from openai module or default
    final_api_key = api_key or openai.api_key or ""
    final_api_base = api_base or openai.base_url or DEFAULT_OPENAI_API_BASE
    final_api_version = api_version or openai.api_version or DEFAULT_OPENAI_API_VERSION

    return final_api_key, str(final_api_base), final_api_version


def validate_openai_api_key(api_key: Optional[str] = None) -> None:
    openai_api_key = api_key or os.environ.get("OPENAI_API_KEY", "")

    if not openai_api_key:
        raise ValueError(MISSING_API_KEY_ERROR_MESSAGE)
