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"""
LLM Service for RAG Application

This module provides integration with Large Language Models through multiple
providers including OpenRouter and Groq, with fallback capabilities and
comprehensive error handling.

Updated: October 18, 2025 - CI/CD pipeline compatibility verification
"""

import logging
import os
import time
from dataclasses import dataclass
from typing import Any, Dict, List, Optional

import requests

from src.llm.llm_configuration_error import LLMConfigurationError

logger = logging.getLogger(__name__)


@dataclass
class LLMConfig:
    """Configuration for LLM providers."""

    provider: str  # "openrouter" or "groq"
    api_key: str
    model_name: str
    base_url: str
    max_tokens: int = 1000
    temperature: float = 0.1
    timeout: int = 30


@dataclass
class LLMResponse:
    """Standardized response from LLM providers."""

    content: str
    provider: str
    model: str
    usage: Dict[str, Any]
    response_time: float
    success: bool
    error_message: Optional[str] = None


class LLMService:
    """
    Service for interacting with Large Language Models.

    Supports multiple providers with automatic fallback and retry logic.
    Designed for corporate policy Q&A with appropriate guardrails.
    """

    def __init__(self, configs: List[LLMConfig]):
        """
        Initialize LLMService with provider configurations.

        Args:
            configs: List of LLMConfig objects for different providers

        Raises:
            ValueError: If no valid configurations provided
        """
        if not configs:
            raise ValueError("At least one LLM configuration must be provided")

        self.configs = configs
        self.current_config_index = 0
        logger.info(f"LLMService initialized with {len(configs)} provider(s)")

    @classmethod
    def from_environment(cls) -> "LLMService":
        """
        Create LLMService instance from environment variables.

        Expected environment variables:
        - OPENROUTER_API_KEY: API key for OpenRouter
        - GROQ_API_KEY: API key for Groq

        Returns:
            LLMService instance with available providers

        Raises:
            ValueError: If no API keys found in environment
        """
        configs = []

        # OpenRouter configuration
        openrouter_key = os.getenv("OPENROUTER_API_KEY")
        if openrouter_key:
            configs.append(
                LLMConfig(
                    provider="openrouter",
                    api_key=openrouter_key,
                    model_name="microsoft/wizardlm-2-8x22b",  # Free tier model
                    base_url="https://openrouter.ai/api/v1",
                    max_tokens=1000,
                    temperature=0.1,
                )
            )

        # Groq configuration
        groq_key = os.getenv("GROQ_API_KEY")
        if groq_key:
            configs.append(
                LLMConfig(
                    provider="groq",
                    api_key=groq_key,
                    model_name="llama3-8b-8192",  # Free tier model
                    base_url="https://api.groq.com/openai/v1",
                    max_tokens=1000,
                    temperature=0.1,
                )
            )

        if not configs:
            raise LLMConfigurationError(
                "No LLM API keys found in environment. " "Please set OPENROUTER_API_KEY or GROQ_API_KEY"
            )

        return cls(configs)

    def generate_response(self, prompt: str, max_retries: int = 2) -> LLMResponse:
        """
        Generate response from LLM with fallback support.

        Args:
            prompt: Input prompt for the LLM
            max_retries: Maximum retry attempts per provider

        Returns:
            LLMResponse with generated content or error information
        """
        last_error = None

        # Try each provider configuration
        for attempt in range(len(self.configs)):
            config = self.configs[self.current_config_index]

            try:
                logger.debug(f"Attempting generation with {config.provider}")
                response = self._call_provider(config, prompt, max_retries)

                if response.success:
                    logger.info(f"Successfully generated response using {config.provider}")
                    return response

                last_error = response.error_message
                logger.warning(f"Provider {config.provider} failed: {last_error}")

            except Exception as e:
                last_error = str(e)
                logger.error(f"Error with provider {config.provider}: {last_error}")

            # Move to next provider
            self.current_config_index = (self.current_config_index + 1) % len(self.configs)

        # All providers failed
        logger.error("All LLM providers failed")
        return LLMResponse(
            content="",
            provider="none",
            model="none",
            usage={},
            response_time=0.0,
            success=False,
            error_message=f"All providers failed. Last error: {last_error}",
        )

    def _call_provider(self, config: LLMConfig, prompt: str, max_retries: int) -> LLMResponse:
        """
        Make API call to specific provider with retry logic.

        Args:
            config: Provider configuration
            prompt: Input prompt
            max_retries: Maximum retry attempts

        Returns:
            LLMResponse from the provider
        """
        start_time = time.time()

        for attempt in range(max_retries + 1):
            try:
                headers = {
                    "Authorization": f"Bearer {config.api_key}",
                    "Content-Type": "application/json",
                }

                # Add provider-specific headers
                if config.provider == "openrouter":
                    referer_url = "https://github.com/sethmcknight/msse-ai-engineering"
                    headers["HTTP-Referer"] = referer_url
                    headers["X-Title"] = "MSSE RAG Application"

                payload = {
                    "model": config.model_name,
                    "messages": [{"role": "user", "content": prompt}],
                    "max_tokens": config.max_tokens,
                    "temperature": config.temperature,
                }

                response = requests.post(
                    f"{config.base_url}/chat/completions",
                    headers=headers,
                    json=payload,
                    timeout=config.timeout,
                )

                response.raise_for_status()
                data = response.json()

                # Extract response content
                content = data["choices"][0]["message"]["content"]
                usage = data.get("usage", {})

                response_time = time.time() - start_time

                return LLMResponse(
                    content=content,
                    provider=config.provider,
                    model=config.model_name,
                    usage=usage,
                    response_time=response_time,
                    success=True,
                )

            except requests.exceptions.RequestException as e:
                logger.warning(f"Request failed for {config.provider} (attempt {attempt + 1}): {e}")
                if attempt < max_retries:
                    time.sleep(2**attempt)  # Exponential backoff
                    continue

                return LLMResponse(
                    content="",
                    provider=config.provider,
                    model=config.model_name,
                    usage={},
                    response_time=time.time() - start_time,
                    success=False,
                    error_message=str(e),
                )

            except Exception as e:
                logger.error(f"Unexpected error with {config.provider}: {e}")
                return LLMResponse(
                    content="",
                    provider=config.provider,
                    model=config.model_name,
                    usage={},
                    response_time=time.time() - start_time,
                    success=False,
                    error_message=str(e),
                )

    def health_check(self) -> Dict[str, Any]:
        """
        Check health status of all configured providers.

        Returns:
            Dictionary with provider health status
        """
        health_status = {}

        for config in self.configs:
            try:
                # Simple test prompt
                test_response = self._call_provider(
                    config,
                    "Hello, this is a test. Please respond with 'OK'.",
                    max_retries=1,
                )

                health_status[config.provider] = {
                    "status": "healthy" if test_response.success else "unhealthy",
                    "model": config.model_name,
                    "response_time": test_response.response_time,
                    "error": test_response.error_message,
                }

            except Exception as e:
                health_status[config.provider] = {
                    "status": "unhealthy",
                    "model": config.model_name,
                    "response_time": 0.0,
                    "error": str(e),
                }

        return health_status

    def get_available_providers(self) -> List[str]:
        """Get list of available provider names."""
        return [config.provider for config in self.configs]