//! Kernel configuration
//!
//! Design principles:
//! - Model ID is passed directly to the API without any transformation
//! - No provider prefix or alias mapping
//! - Simple, unified configuration structure

use std::path::PathBuf;
use std::sync::Arc;
use serde::{Deserialize, Serialize};
use secrecy::SecretString;
use zclaw_types::Result;
use zclaw_runtime::{LlmDriver, AnthropicDriver, OpenAiDriver};

/// API protocol type
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
#[serde(rename_all = "lowercase")]
pub enum ApiProtocol {
    OpenAI,
    Anthropic,
}

impl Default for ApiProtocol {
    fn default() -> Self {
        Self::OpenAI
    }
}

/// LLM configuration - unified config for all providers
///
/// This is the single source of truth for LLM configuration.
/// Model ID is passed directly to the API without any transformation.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct LlmConfig {
    /// API base URL (e.g., "https://api.openai.com/v1")
    pub base_url: String,

    /// API key
    #[serde(skip_serializing)]
    pub api_key: String,

    /// Model identifier - passed directly to the API
    /// Examples: "gpt-4o", "glm-4-flash", "glm-4-plus", "claude-3-opus-20240229"
    pub model: String,

    /// API protocol (OpenAI-compatible or Anthropic)
    #[serde(default)]
    pub api_protocol: ApiProtocol,

    /// Maximum tokens per response
    #[serde(default = "default_max_tokens")]
    pub max_tokens: u32,

    /// Temperature
    #[serde(default = "default_temperature")]
    pub temperature: f32,

    /// Context window size in tokens (default: 128000)
    /// Used to calculate dynamic compaction threshold.
    #[serde(default = "default_context_window")]
    pub context_window: u32,
}

impl LlmConfig {
    /// Create a new LLM config
    pub fn new(base_url: impl Into<String>, api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self {
            base_url: base_url.into(),
            api_key: api_key.into(),
            model: model.into(),
            api_protocol: ApiProtocol::OpenAI,
            max_tokens: default_max_tokens(),
            temperature: default_temperature(),
            context_window: default_context_window(),
        }
    }

    /// Set API protocol
    pub fn with_protocol(mut self, protocol: ApiProtocol) -> Self {
        self.api_protocol = protocol;
        self
    }

    /// Set max tokens
    pub fn with_max_tokens(mut self, max_tokens: u32) -> Self {
        self.max_tokens = max_tokens;
        self
    }

    /// Set temperature
    pub fn with_temperature(mut self, temperature: f32) -> Self {
        self.temperature = temperature;
        self
    }

    /// Create driver from this config
    pub fn create_driver(&self) -> Result<Arc<dyn LlmDriver>> {
        match self.api_protocol {
            ApiProtocol::Anthropic => {
                if self.base_url.is_empty() {
                    Ok(Arc::new(AnthropicDriver::new(SecretString::new(self.api_key.clone()))))
                } else {
                    Ok(Arc::new(AnthropicDriver::with_base_url(
                        SecretString::new(self.api_key.clone()),
                        self.base_url.clone(),
                    )))
                }
            }
            ApiProtocol::OpenAI => {
                Ok(Arc::new(OpenAiDriver::with_base_url(
                    SecretString::new(self.api_key.clone()),
                    self.base_url.clone(),
                )))
            }
        }
    }
}

/// Kernel configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KernelConfig {
    /// Database URL (SQLite)
    #[serde(default = "default_database_url")]
    pub database_url: String,

    /// LLM configuration
    #[serde(flatten)]
    pub llm: LlmConfig,

    /// Skills directory path (optional, defaults to ./skills)
    #[serde(default)]
    pub skills_dir: Option<PathBuf>,
}

fn default_database_url() -> String {
    let home = dirs::home_dir().unwrap_or_else(|| std::path::PathBuf::from("."));
    let dir = home.join(".zclaw");
    format!("sqlite:{}/data.db?mode=rwc", dir.display())
}

fn default_max_tokens() -> u32 {
    4096
}

fn default_temperature() -> f32 {
    0.7
}

fn default_context_window() -> u32 {
    128000
}

impl Default for KernelConfig {
    fn default() -> Self {
        Self {
            database_url: default_database_url(),
            llm: LlmConfig {
                base_url: "https://api.openai.com/v1".to_string(),
                api_key: String::new(),
                model: "gpt-4o-mini".to_string(),
                api_protocol: ApiProtocol::OpenAI,
                max_tokens: default_max_tokens(),
                temperature: default_temperature(),
                context_window: default_context_window(),
            },
            skills_dir: default_skills_dir(),
        }
    }
}

/// Default skills directory
///
/// Discovery order:
/// 1. ZCLAW_SKILLS_DIR environment variable (if set)
/// 2. Compile-time known workspace path (CARGO_WORKSPACE_DIR or relative from manifest dir)
/// 3. Current working directory/skills (for development)
/// 4. Executable directory and multiple levels up (for packaged apps)
fn default_skills_dir() -> Option<std::path::PathBuf> {
    // 1. Check environment variable override
    if let Ok(dir) = std::env::var("ZCLAW_SKILLS_DIR") {
        let path = std::path::PathBuf::from(&dir);
        tracing::debug!(target: "kernel_config", "ZCLAW_SKILLS_DIR env: {} (exists: {})", path.display(), path.exists());
        if path.exists() {
            return Some(path);
        }
        // Even if it doesn't exist, respect the env var
        return Some(path);
    }

    // 2. Try compile-time known paths (works for cargo build/test)
    // CARGO_MANIFEST_DIR is the crate directory (crates/zclaw-kernel)
    // We need to go up to find the workspace root
    let manifest_dir = std::path::PathBuf::from(env!("CARGO_MANIFEST_DIR"));
    tracing::debug!(target: "kernel_config", "CARGO_MANIFEST_DIR: {}", manifest_dir.display());

    // Go up from crates/zclaw-kernel to workspace root
    if let Some(workspace_root) = manifest_dir.parent().and_then(|p| p.parent()) {
        let workspace_skills = workspace_root.join("skills");
        tracing::debug!(target: "kernel_config", "Workspace skills: {} (exists: {})", workspace_skills.display(), workspace_skills.exists());
        if workspace_skills.exists() {
            return Some(workspace_skills);
        }
    }

    // 3. Try current working directory first (for development)
    if let Ok(cwd) = std::env::current_dir() {
        let cwd_skills = cwd.join("skills");
        tracing::debug!(target: "kernel_config", "Checking cwd: {} (exists: {})", cwd_skills.display(), cwd_skills.exists());
        if cwd_skills.exists() {
            return Some(cwd_skills);
        }

        // Also try going up from cwd (might be in desktop/src-tauri)
        let mut current = cwd.as_path();
        for i in 0..6 {
            if let Some(parent) = current.parent() {
                let parent_skills = parent.join("skills");
                tracing::debug!(target: "kernel_config", "CWD Level {}: {} (exists: {})", i, parent_skills.display(), parent_skills.exists());
                if parent_skills.exists() {
                    return Some(parent_skills);
                }
                current = parent;
            } else {
                break;
            }
        }
    }

    // 4. Try executable's directory and multiple levels up
    if let Ok(exe) = std::env::current_exe() {
        tracing::debug!(target: "kernel_config", "Current exe: {}", exe.display());
        if let Some(exe_dir) = exe.parent().map(|p| p.to_path_buf()) {
            // Same directory as exe
            let exe_skills = exe_dir.join("skills");
            tracing::debug!(target: "kernel_config", "Checking exe dir: {} (exists: {})", exe_skills.display(), exe_skills.exists());
            if exe_skills.exists() {
                return Some(exe_skills);
            }

            // Go up multiple levels to handle Tauri dev builds
            let mut current = exe_dir.as_path();
            for i in 0..6 {
                if let Some(parent) = current.parent() {
                    let parent_skills = parent.join("skills");
                    tracing::debug!(target: "kernel_config", "EXE Level {}: {} (exists: {})", i, parent_skills.display(), parent_skills.exists());
                    if parent_skills.exists() {
                        return Some(parent_skills);
                    }
                    current = parent;
                } else {
                    break;
                }
            }
        }
    }

    // 5. Fallback to current working directory/skills (may not exist)
    let fallback = std::env::current_dir()
        .ok()
        .map(|cwd| cwd.join("skills"));
    tracing::debug!(target: "kernel_config", "Fallback to: {:?}", fallback);
    fallback
}

impl KernelConfig {
    /// Load configuration from file.
    ///
    /// Search order:
    /// 1. Path from `ZCLAW_CONFIG` environment variable
    /// 2. `~/.zclaw/config.toml`
    /// 3. Fallback to `Self::default()`
    ///
    /// Supports `${VAR_NAME}` environment variable interpolation in string values.
    pub async fn load() -> Result<Self> {
        let config_path = Self::find_config_path();

        match config_path {
            Some(path) => {
                if !path.exists() {
                    tracing::debug!(target: "kernel_config", "Config file not found: {:?}, using defaults", path);
                    return Ok(Self::default());
                }

                tracing::info!(target: "kernel_config", "Loading config from: {:?}", path);
                let content = std::fs::read_to_string(&path).map_err(|e| {
                    zclaw_types::ZclawError::Internal(format!("Failed to read config {}: {}", path.display(), e))
                })?;

                let interpolated = interpolate_env_vars(&content);
                let mut config: KernelConfig = toml::from_str(&interpolated).map_err(|e| {
                    zclaw_types::ZclawError::Internal(format!("Failed to parse config {}: {}", path.display(), e))
                })?;

                // Resolve skills_dir if not explicitly set
                if config.skills_dir.is_none() {
                    config.skills_dir = default_skills_dir();
                }

                tracing::info!(
                    target: "kernel_config",
                    model = %config.llm.model,
                    base_url = %config.llm.base_url,
                    has_api_key = !config.llm.api_key.is_empty(),
                    "Config loaded successfully"
                );

                Ok(config)
            }
            None => Ok(Self::default()),
        }
    }

    /// Find the config file path.
    pub fn find_config_path() -> Option<PathBuf> {
        // 1. Environment variable override
        if let Ok(path) = std::env::var("ZCLAW_CONFIG") {
            return Some(PathBuf::from(path));
        }

        // 2. ~/.zclaw/config.toml
        if let Some(home) = dirs::home_dir() {
            let path = home.join(".zclaw").join("config.toml");
            if path.exists() {
                return Some(path);
            }
        }

        // 3. Project root config/config.toml (for development)
        let project_config = std::env::current_dir()
            .ok()
            .map(|cwd| cwd.join("config").join("config.toml"))?;

        if project_config.exists() {
            return Some(project_config);
        }

        None
    }

    /// Create the LLM driver
    pub fn create_driver(&self) -> Result<Arc<dyn LlmDriver>> {
        self.llm.create_driver()
    }

    /// Get the model ID (passed directly to API)
    pub fn model(&self) -> &str {
        &self.llm.model
    }

    /// Get max tokens
    pub fn max_tokens(&self) -> u32 {
        self.llm.max_tokens
    }

    /// Get temperature
    pub fn temperature(&self) -> f32 {
        self.llm.temperature
    }

    /// Get context window size in tokens
    pub fn context_window(&self) -> u32 {
        self.llm.context_window
    }

    /// Dynamic compaction threshold = context_window * 0.6
    /// Leaves 40% headroom for system prompt + response tokens
    pub fn compaction_threshold(&self) -> usize {
        (self.llm.context_window as f64 * 0.6) as usize
    }
}

// === Preset configurations for common providers ===

impl LlmConfig {
    /// OpenAI GPT-4
    pub fn openai(api_key: impl Into<String>) -> Self {
        Self::new("https://api.openai.com/v1", api_key, "gpt-4o")
    }

    /// Anthropic Claude
    pub fn anthropic(api_key: impl Into<String>) -> Self {
        Self::new("https://api.anthropic.com", api_key, "claude-sonnet-4-20250514")
            .with_protocol(ApiProtocol::Anthropic)
    }

    /// 智谱 GLM
    pub fn zhipu(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://open.bigmodel.cn/api/paas/v4", api_key, model)
    }

    /// 智谱 GLM Coding Plan
    pub fn zhipu_coding(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://open.bigmodel.cn/api/coding/paas/v4", api_key, model)
    }

    /// Kimi (Moonshot)
    pub fn kimi(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://api.moonshot.cn/v1", api_key, model)
    }

    /// Kimi Coding Plan
    pub fn kimi_coding(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://api.kimi.com/coding/v1", api_key, model)
    }

    /// 阿里云百炼 (Qwen)
    pub fn qwen(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://dashscope.aliyuncs.com/compatible-mode/v1", api_key, model)
    }

    /// 阿里云百炼 Coding Plan
    pub fn qwen_coding(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://coding.dashscope.aliyuncs.com/v1", api_key, model)
    }

    /// DeepSeek
    pub fn deepseek(api_key: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new("https://api.deepseek.com/v1", api_key, model)
    }

    /// Ollama / Local
    pub fn local(base_url: impl Into<String>, model: impl Into<String>) -> Self {
        Self::new(base_url, "", model)
    }
}

// === Backward compatibility ===

/// Provider type for backward compatibility
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum Provider {
    OpenAI,
    Anthropic,
    Gemini,
    Zhipu,
    Kimi,
    Qwen,
    DeepSeek,
    Local,
    Custom,
}

impl KernelConfig {
    /// Create config from provider type (for backward compatibility with Tauri commands)
    pub fn from_provider(
        provider: &str,
        api_key: &str,
        model: &str,
        base_url: Option<&str>,
        api_protocol: &str,
    ) -> Self {
        let llm = match provider {
            "anthropic" => LlmConfig::anthropic(api_key).with_model(model),
            "openai" => {
                if let Some(url) = base_url.filter(|u| !u.is_empty()) {
                    LlmConfig::new(url, api_key, model)
                } else {
                    LlmConfig::openai(api_key).with_model(model)
                }
            }
            "gemini" => LlmConfig::new(
                base_url.unwrap_or("https://generativelanguage.googleapis.com/v1beta"),
                api_key,
                model,
            ),
            "zhipu" => {
                let url = base_url.unwrap_or("https://open.bigmodel.cn/api/paas/v4");
                LlmConfig::zhipu(api_key, model).with_base_url(url)
            }
            "zhipu-coding" => {
                let url = base_url.unwrap_or("https://open.bigmodel.cn/api/coding/paas/v4");
                LlmConfig::zhipu_coding(api_key, model).with_base_url(url)
            }
            "kimi" => {
                let url = base_url.unwrap_or("https://api.moonshot.cn/v1");
                LlmConfig::kimi(api_key, model).with_base_url(url)
            }
            "kimi-coding" => {
                let url = base_url.unwrap_or("https://api.kimi.com/coding/v1");
                LlmConfig::kimi_coding(api_key, model).with_base_url(url)
            }
            "qwen" => {
                let url = base_url.unwrap_or("https://dashscope.aliyuncs.com/compatible-mode/v1");
                LlmConfig::qwen(api_key, model).with_base_url(url)
            }
            "qwen-coding" => {
                let url = base_url.unwrap_or("https://coding.dashscope.aliyuncs.com/v1");
                LlmConfig::qwen_coding(api_key, model).with_base_url(url)
            }
            "deepseek" => LlmConfig::deepseek(api_key, model),
            "local" | "ollama" => {
                let url = base_url.unwrap_or("http://localhost:11434/v1");
                LlmConfig::local(url, model)
            }
            _ => {
                // Custom provider
                let protocol = if api_protocol == "anthropic" {
                    ApiProtocol::Anthropic
                } else {
                    ApiProtocol::OpenAI
                };
                LlmConfig::new(
                    base_url.unwrap_or("https://api.openai.com/v1"),
                    api_key,
                    model,
                )
                .with_protocol(protocol)
            }
        };

        Self {
            database_url: default_database_url(),
            llm,
            skills_dir: default_skills_dir(),
        }
    }
}

impl LlmConfig {
    /// Set model
    pub fn with_model(mut self, model: impl Into<String>) -> Self {
        self.model = model.into();
        self
    }

    /// Set base URL
    pub fn with_base_url(mut self, base_url: impl Into<String>) -> Self {
        self.base_url = base_url.into();
        self
    }
}

// === Environment variable interpolation ===

/// Replace `${VAR_NAME}` patterns in a string with environment variable values.
/// If the variable is not set, the pattern is left as-is.
fn interpolate_env_vars(content: &str) -> String {
    let mut result = String::with_capacity(content.len());
    let mut chars = content.char_indices().peekable();

    while let Some((_, ch)) = chars.next() {
        if ch == '$' && chars.peek().map(|(_, c)| *c == '{').unwrap_or(false) {
            chars.next(); // consume '{'

            let mut var_name = String::new();

            while let Some((_, c)) = chars.peek() {
                match c {
                    '}' => {
                        chars.next(); // consume '}'
                        if let Ok(value) = std::env::var(&var_name) {
                            result.push_str(&value);
                        } else {
                            result.push_str("${");
                            result.push_str(&var_name);
                            result.push('}');
                        }
                        break;
                    }
                    _ => {
                        var_name.push(*c);
                        chars.next();
                    }
                }
            }

            // Handle unclosed ${... at end of string
            if !content[result.len()..].contains('}') && var_name.is_empty() {
                // Already consumed, nothing to do
            }
        } else {
            result.push(ch);
        }
    }

    result
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_interpolate_env_vars_basic() {
        std::env::set_var("ZCLAW_TEST_VAR", "hello");
        let result = interpolate_env_vars("prefix ${ZCLAW_TEST_VAR} suffix");
        assert_eq!(result, "prefix hello suffix");
    }

    #[test]
    fn test_interpolate_env_vars_missing() {
        let result = interpolate_env_vars("${ZCLAW_NONEXISTENT_VAR_12345}");
        assert_eq!(result, "${ZCLAW_NONEXISTENT_VAR_12345}");
    }

    #[test]
    fn test_interpolate_env_vars_no_vars() {
        let result = interpolate_env_vars("no variables here");
        assert_eq!(result, "no variables here");
    }

    #[test]
    fn test_interpolate_env_vars_multiple() {
        std::env::set_var("ZCLAW_TEST_A", "alpha");
        std::env::set_var("ZCLAW_TEST_B", "beta");
        let result = interpolate_env_vars("${ZCLAW_TEST_A}-${ZCLAW_TEST_B}");
        assert_eq!(result, "alpha-beta");
    }
}