"""
Cloud API Adapters for NEXUS OS v2.1

Implements generation adapters for all cloud providers:
  - DeepSeek (V4 Pro, V4 Flash)
  - Qwen (3 Coder Next)
  - Moonshot (Kimi K2.6)
  - Zhipu (GLM 5.1)
  - OpenAI (GPT-5, GPT-5.5)
  - Anthropic (Claude 4.7, Claude 4.6)

Each adapter normalizes the provider-specific API to a common interface:
  generate(prompt, max_tokens, temperature, system) -> (text, metadata)

API keys loaded from environment variables — NEVER committed to git.
"""
import os
import json
import time
from typing import Optional, Dict, Any, Tuple, List
from dataclasses import dataclass


@dataclass
class CloudResponse:
    """Normalized response from any cloud provider."""
    text: str
    model_used: str
    tokens_input: int = 0
    tokens_output: int = 0
    latency_ms: float = 0.0
    cost_cents: float = 0.0
    finish_reason: str = "stop"
    raw_metadata: Dict[str, Any] = None


class BaseCloudAdapter:
    """Base class for all cloud API adapters."""
    
    def __init__(self, api_key: Optional[str] = None):
        self.api_key = api_key
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        raise NotImplementedError
    
    def is_available(self) -> bool:
        return self.api_key is not None and len(self.api_key) > 10


class DeepSeekAdapter(BaseCloudAdapter):
    """
    DeepSeek API adapter.
    
    API key: DEEPSEEK_API_KEY
    Base URL: https://api.deepseek.com/v1/chat/completions
    Models: deepseek-chat (V4 Pro), deepseek-reasoner (V4 Flash)
    """
    
    BASE_URL = "https://api.deepseek.com/v1/chat/completions"
    
    def __init__(self, api_key: Optional[str] = None):
        super().__init__(api_key or os.environ.get("DEEPSEEK_API_KEY"))
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        import urllib.request
        import urllib.error
        
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        messages.append({"role": "user", "content": prompt})
        
        payload = json.dumps({
            "model": "deepseek-chat",
            "messages": messages,
            "max_tokens": max_tokens,
            "temperature": temperature,
            "stream": False,
        }).encode("utf-8")
        
        req = urllib.request.Request(
            self.BASE_URL,
            data=payload,
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {self.api_key}",
            },
            method="POST",
        )
        
        t0 = time.time()
        try:
            with urllib.request.urlopen(req, timeout=120) as resp:
                data = json.loads(resp.read().decode("utf-8"))
                elapsed = (time.time() - t0) * 1000
                
                choice = data.get("choices", [{}])[0]
                usage = data.get("usage", {})
                
                return CloudResponse(
                    text=choice.get("message", {}).get("content", ""),
                    model_used=data.get("model", "unknown"),
                    tokens_input=usage.get("prompt_tokens", 0),
                    tokens_output=usage.get("completion_tokens", 0),
                    latency_ms=elapsed,
                    finish_reason=choice.get("finish_reason", "stop"),
                    raw_metadata=data,
                )
        except urllib.error.HTTPError as e:
            error_body = e.read().decode("utf-8")
            raise RuntimeError(f"DeepSeek API error {e.code}: {error_body}")


class QwenAdapter(BaseCloudAdapter):
    """
    Qwen (Alibaba Cloud) API adapter.
    
    API key: QWEN_API_KEY
    Base URL: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation
    Models: qwen-coder-plus-latest, qwen-max, etc.
    """
    
    BASE_URL = "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation"
    
    def __init__(self, api_key: Optional[str] = None):
        super().__init__(api_key or os.environ.get("QWEN_API_KEY"))
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        import urllib.request
        import urllib.error
        
        payload = json.dumps({
            "model": "qwen-coder-plus-latest",
            "input": {
                "messages": [
                    *( [{"role": "system", "content": system}] if system else [] ),
                    {"role": "user", "content": prompt},
                ]
            },
            "parameters": {
                "max_tokens": max_tokens,
                "temperature": temperature,
            },
        }).encode("utf-8")
        
        req = urllib.request.Request(
            self.BASE_URL,
            data=payload,
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {self.api_key}",
            },
            method="POST",
        )
        
        t0 = time.time()
        try:
            with urllib.request.urlopen(req, timeout=120) as resp:
                data = json.loads(resp.read().decode("utf-8"))
                elapsed = (time.time() - t0) * 1000
                
                output = data.get("output", {})
                usage = data.get("usage", {})
                
                return CloudResponse(
                    text=output.get("text", ""),
                    model_used=output.get("model_id", "unknown"),
                    tokens_input=usage.get("input_tokens", 0),
                    tokens_output=usage.get("output_tokens", 0),
                    latency_ms=elapsed,
                    raw_metadata=data,
                )
        except urllib.error.HTTPError as e:
            error_body = e.read().decode("utf-8")
            raise RuntimeError(f"Qwen API error {e.code}: {error_body}")


class KimiAdapter(BaseCloudAdapter):
    """
    Moonshot AI (Kimi) API adapter.
    
    API key: KIMI_API_KEY
    Base URL: https://api.moonshot.cn/v1/chat/completions
    Models: moonshot-v1-32k, moonshot-v1-128k
    """
    
    BASE_URL = "https://api.moonshot.cn/v1/chat/completions"
    
    def __init__(self, api_key: Optional[str] = None):
        super().__init__(api_key or os.environ.get("KIMI_API_KEY"))
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        import urllib.request
        import urllib.error
        
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        messages.append({"role": "user", "content": prompt})
        
        payload = json.dumps({
            "model": "moonshot-v1-128k",
            "messages": messages,
            "max_tokens": max_tokens,
            "temperature": temperature,
        }).encode("utf-8")
        
        req = urllib.request.Request(
            self.BASE_URL,
            data=payload,
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {self.api_key}",
            },
            method="POST",
        )
        
        t0 = time.time()
        try:
            with urllib.request.urlopen(req, timeout=120) as resp:
                data = json.loads(resp.read().decode("utf-8"))
                elapsed = (time.time() - t0) * 1000
                
                choice = data.get("choices", [{}])[0]
                usage = data.get("usage", {})
                
                return CloudResponse(
                    text=choice.get("message", {}).get("content", ""),
                    model_used=data.get("model", "unknown"),
                    tokens_input=usage.get("prompt_tokens", 0),
                    tokens_output=usage.get("completion_tokens", 0),
                    latency_ms=elapsed,
                    finish_reason=choice.get("finish_reason", "stop"),
                    raw_metadata=data,
                )
        except urllib.error.HTTPError as e:
            error_body = e.read().decode("utf-8")
            raise RuntimeError(f"Kimi API error {e.code}: {error_body}")


class GLMAdapter(BaseCloudAdapter):
    """
    Zhipu AI (GLM) API adapter.
    
    API key: GLM_API_KEY
    Base URL: https://open.bigmodel.cn/api/paas/v4/chat/completions
    Models: glm-4-plus, glm-4-flash
    """
    
    BASE_URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"
    
    def __init__(self, api_key: Optional[str] = None):
        super().__init__(api_key or os.environ.get("GLM_API_KEY"))
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        import urllib.request
        import urllib.error
        
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        messages.append({"role": "user", "content": prompt})
        
        payload = json.dumps({
            "model": "glm-4-plus",
            "messages": messages,
            "max_tokens": max_tokens,
            "temperature": temperature,
        }).encode("utf-8")
        
        req = urllib.request.Request(
            self.BASE_URL,
            data=payload,
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {self.api_key}",
            },
            method="POST",
        )
        
        t0 = time.time()
        try:
            with urllib.request.urlopen(req, timeout=120) as resp:
                data = json.loads(resp.read().decode("utf-8"))
                elapsed = (time.time() - t0) * 1000
                
                choice = data.get("choices", [{}])[0]
                usage = data.get("usage", {})
                
                return CloudResponse(
                    text=choice.get("message", {}).get("content", ""),
                    model_used=data.get("model", "unknown"),
                    tokens_input=usage.get("prompt_tokens", 0),
                    tokens_output=usage.get("completion_tokens", 0),
                    latency_ms=elapsed,
                    finish_reason=choice.get("finish_reason", "stop"),
                    raw_metadata=data,
                )
        except urllib.error.HTTPError as e:
            error_body = e.read().decode("utf-8")
            raise RuntimeError(f"GLM API error {e.code}: {error_body}")


class OpenAIAdapter(BaseCloudAdapter):
    """
    OpenAI API adapter (GPT-5, GPT-5.5).
    
    API key: OPENAI_API_KEY
    Base URL: https://api.openai.com/v1/chat/completions
    Models: gpt-5, gpt-5-turbo, gpt-5.5
    """
    
    BASE_URL = "https://api.openai.com/v1/chat/completions"
    
    def __init__(self, api_key: Optional[str] = None):
        super().__init__(api_key or os.environ.get("OPENAI_API_KEY"))
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        import urllib.request
        import urllib.error
        
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        messages.append({"role": "user", "content": prompt})
        
        payload = json.dumps({
            "model": "gpt-5",
            "messages": messages,
            "max_tokens": max_tokens,
            "temperature": temperature,
        }).encode("utf-8")
        
        req = urllib.request.Request(
            self.BASE_URL,
            data=payload,
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {self.api_key}",
            },
            method="POST",
        )
        
        t0 = time.time()
        try:
            with urllib.request.urlopen(req, timeout=120) as resp:
                data = json.loads(resp.read().decode("utf-8"))
                elapsed = (time.time() - t0) * 1000
                
                choice = data.get("choices", [{}])[0]
                usage = data.get("usage", {})
                
                return CloudResponse(
                    text=choice.get("message", {}).get("content", ""),
                    model_used=data.get("model", "unknown"),
                    tokens_input=usage.get("prompt_tokens", 0),
                    tokens_output=usage.get("completion_tokens", 0),
                    latency_ms=elapsed,
                    finish_reason=choice.get("finish_reason", "stop"),
                    raw_metadata=data,
                )
        except urllib.error.HTTPError as e:
            error_body = e.read().decode("utf-8")
            raise RuntimeError(f"OpenAI API error {e.code}: {error_body}")


class ClaudeAdapter(BaseCloudAdapter):
    """
    Anthropic Claude API adapter.
    
    API key: ANTHROPIC_API_KEY
    Base URL: https://api.anthropic.com/v1/messages
    Models: claude-sonnet-4-7, claude-opus-4-7
    """
    
    BASE_URL = "https://api.anthropic.com/v1/messages"
    
    def __init__(self, api_key: Optional[str] = None):
        super().__init__(api_key or os.environ.get("ANTHROPIC_API_KEY"))
    
    def generate(
        self,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        import urllib.request
        import urllib.error
        
        body = {
            "model": "claude-sonnet-4-7-20251001",
            "max_tokens": max_tokens,
            "temperature": temperature,
            "messages": [{"role": "user", "content": prompt}],
        }
        if system:
            body["system"] = system
        
        payload = json.dumps(body).encode("utf-8")
        
        req = urllib.request.Request(
            self.BASE_URL,
            data=payload,
            headers={
                "Content-Type": "application/json",
                "x-api-key": self.api_key,
                "anthropic-version": "2023-06-01",
            },
            method="POST",
        )
        
        t0 = time.time()
        try:
            with urllib.request.urlopen(req, timeout=120) as resp:
                data = json.loads(resp.read().decode("utf-8"))
                elapsed = (time.time() - t0) * 1000
                
                content = data.get("content", [{}])[0]
                usage = data.get("usage", {})
                
                return CloudResponse(
                    text=content.get("text", ""),
                    model_used=data.get("model", "unknown"),
                    tokens_input=usage.get("input_tokens", 0),
                    tokens_output=usage.get("output_tokens", 0),
                    latency_ms=elapsed,
                    finish_reason=data.get("stop_reason", "stop"),
                    raw_metadata=data,
                )
        except urllib.error.HTTPError as e:
            error_body = e.read().decode("utf-8")
            raise RuntimeError(f"Claude API error {e.code}: {error_body}")


class CloudAPIManager:
    """
    Unified manager for all cloud API adapters.
    Selects provider based on model_id or profile.
    """
    
    ADAPTERS = {
        "deepseek": DeepSeekAdapter,
        "qwen": QwenAdapter,
        "kimi": KimiAdapter,
        "glm": GLMAdapter,
        "openai": OpenAIAdapter,
        "claude": ClaudeAdapter,
    }
    
    def __init__(self):
        self._adapters: Dict[str, BaseCloudAdapter] = {}
        for name, cls in self.ADAPTERS.items():
            adapter = cls()
            if adapter.is_available():
                self._adapters[name] = adapter
    
    def get_adapter(self, model_family: str) -> Optional[BaseCloudAdapter]:
        """Get adapter by model family name."""
        family_lower = model_family.lower()
        for name, adapter in self._adapters.items():
            if name in family_lower or family_lower in name:
                return adapter
        return None
    
    def generate(
        self,
        model_family: str,
        prompt: str,
        max_tokens: int = 2048,
        temperature: float = 0.7,
        system: Optional[str] = None,
    ) -> CloudResponse:
        """Generate via the appropriate cloud adapter."""
        adapter = self.get_adapter(model_family)
        if not adapter:
            available = list(self._adapters.keys())
            raise RuntimeError(
                f"No cloud adapter available for '{model_family}'. "
                f"Available: {available}. Set API key env var."
            )
        return adapter.generate(prompt, max_tokens, temperature, system)
    
    def list_available(self) -> List[str]:
        """List available cloud providers (API keys configured)."""
        return list(self._adapters.keys())
    
    def is_available(self, model_family: str) -> bool:
        return self.get_adapter(model_family) is not None