// SPF Smart Gateway - Worker Mode
// Copyright 2026 Joseph Stone - All Rights Reserved
//
// BLOCK O — Headless worker node that runs transformer inference
// without a Claude API session. Accepts tasks via mesh pipeline,
// executes them locally, streams results back.
//
// Worker boot:
//   1. Load config (same as normal serve mode)
//   2. Load transformer checkpoint
//   3. Start mesh (accept pipeline streams)
//   4. Start HTTP (monitoring endpoints only)
//   5. Loop: receive task → transformer decides tool → execute → return result
//   6. Training signals captured by GateTrainingCollector listener
//
// CLI: spf-smart-gate worker [--role writer|researcher] [--checkpoint path]
//
// Depends on: Block E (transformer), Block I (config), Block J (gate training),
//             Block K (transformer tools), Block N (pipeline)

use serde_json::json;
use std::sync::{Arc, Mutex, RwLock};

use crate::config::TransformerConfig;
use crate::pipeline::PipelineState;
use crate::transformer_tools::TransformerState;

// ============================================================================
// WORKER CONFIGURATION
// ============================================================================

/// Worker-specific configuration (supplements TransformerConfig)
#[derive(Debug, Clone)]
pub struct WorkerConfig {
    /// Model role: "writer" or "researcher"
    pub role: String,
    /// Override checkpoint path (if different from config default)
    pub checkpoint_override: Option<String>,
    /// Max concurrent pipeline tasks
    pub max_concurrent: usize,
    /// Heartbeat interval in seconds (report status to orchestrator)
    pub heartbeat_interval_secs: u64,
    /// Auto-checkpoint interval in training steps
    pub auto_checkpoint_steps: u64,
    /// Enable training while serving (online learning)
    pub train_while_serving: bool,
}

impl Default for WorkerConfig {
    fn default() -> Self {
        Self {
            role: "writer".to_string(),
            checkpoint_override: None,
            max_concurrent: 4,
            heartbeat_interval_secs: 30,
            auto_checkpoint_steps: 1000,
            train_while_serving: true,
        }
    }
}

// ============================================================================
// WORKER STATE
// ============================================================================

/// Runtime state for the worker process
pub struct WorkerState {
    /// Worker configuration
    pub config: WorkerConfig,
    /// Transformer configuration
    pub transformer_config: TransformerConfig,
    /// Pipeline state for task management
    pub pipeline: Arc<Mutex<PipelineState>>,
    /// Tasks processed since boot
    pub tasks_processed: u64,
    /// Tasks failed since boot
    pub tasks_failed: u64,
    /// Worker uptime start
    pub started_at: std::time::Instant,
    /// Whether worker is accepting tasks
    pub accepting: bool,
}

impl WorkerState {
    pub fn new(config: WorkerConfig, transformer_config: TransformerConfig) -> Self {
        Self {
            config,
            transformer_config,
            pipeline: Arc::new(Mutex::new(PipelineState::new())),
            tasks_processed: 0,
            tasks_failed: 0,
            started_at: std::time::Instant::now(),
            accepting: true,
        }
    }

    /// Get worker status as JSON for monitoring/heartbeat
    pub fn status_json(&self) -> serde_json::Value {
        let uptime = self.started_at.elapsed().as_secs();
        let pipeline_status = self.pipeline.lock().unwrap().status_summary();

        json!({
            "mode": "worker",
            "role": self.config.role,
            "accepting": self.accepting,
            "uptime_secs": uptime,
            "tasks_processed": self.tasks_processed,
            "tasks_failed": self.tasks_failed,
            "max_concurrent": self.config.max_concurrent,
            "train_while_serving": self.config.train_while_serving,
            "pipeline": pipeline_status,
        })
    }
}

// ============================================================================
// WORKER BOOT SEQUENCE
// ============================================================================

/// Initialize transformer state for worker mode.
/// Loads checkpoint if available, otherwise creates fresh model.
pub fn init_transformer(
    transformer_config: &TransformerConfig,
    worker_config: &WorkerConfig,
) -> Result<TransformerState, String> {
    if !transformer_config.enabled {
        return Err("Transformer not enabled in config. Set enabled=true in transformer.json".to_string());
    }

    // Determine checkpoint path
    let checkpoint_path = worker_config.checkpoint_override.clone()
        .unwrap_or_else(|| {
            let checkpoint_name = match worker_config.role.as_str() {
                "researcher" => &transformer_config.researcher_checkpoint,
                _ => &transformer_config.writer_checkpoint,
            };
            let models_dir = crate::paths::spf_root().join("LIVE/MODELS");
            models_dir.join(checkpoint_name).to_string_lossy().to_string()
        });

    // Create transformer state
    let mut state = TransformerState::from_config(transformer_config, &worker_config.role);

    // Try to load checkpoint
    let checkpoint_file = std::path::Path::new(&checkpoint_path);
    if checkpoint_file.exists() {
        match std::fs::read(checkpoint_file) {
            Ok(data) => {
                match crate::checkpoint::deserialize_weights(&data) {
                    Ok((checkpoint_weights, meta)) => {
                        let mut model_weights = state.model.weights_mut();
                        if let Err(e) = crate::checkpoint::apply_weights(&mut model_weights, &checkpoint_weights) {
                            eprintln!("[SPF-WORKER] WARNING: Failed to apply checkpoint weights: {}. Starting fresh.", e);
                        } else {
                            eprintln!("[SPF-WORKER] Checkpoint meta: model={}, step={}", meta.model_id, meta.step);
                        }
                        state.last_checkpoint = checkpoint_path.clone();
                        eprintln!("[SPF-WORKER] Loaded checkpoint: {} ({} bytes)",
                            checkpoint_path, data.len());
                    }
                    Err(e) => {
                        eprintln!("[SPF-WORKER] WARNING: Failed to deserialize checkpoint: {}. Starting fresh.", e);
                    }
                }
            }
            Err(e) => {
                eprintln!("[SPF-WORKER] WARNING: Failed to read checkpoint {}: {}. Starting fresh.",
                    checkpoint_path, e);
            }
        }
    } else {
        eprintln!("[SPF-WORKER] No checkpoint at {}. Starting with random weights.", checkpoint_path);
    }

    Ok(state)
}

/// Save a checkpoint of current transformer weights.
pub fn save_checkpoint(
    state: &TransformerState,
    transformer_config: &TransformerConfig,
    worker_config: &WorkerConfig,
) -> Result<String, String> {
    let models_dir = crate::paths::spf_root().join("LIVE/MODELS");
    std::fs::create_dir_all(&models_dir)
        .map_err(|e| format!("Failed to create MODELS dir: {}", e))?;

    let checkpoint_name = match worker_config.role.as_str() {
        "researcher" => &transformer_config.researcher_checkpoint,
        _ => &transformer_config.writer_checkpoint,
    };

    let path = models_dir.join(checkpoint_name);
    let weights_refs = state.model.weights();
    let data = crate::checkpoint::serialize_weights(
        &weights_refs,
        &worker_config.role,
        state.training_step,
    ).map_err(|e| format!("Serialize failed: {}", e))?;
    std::fs::write(&path, &data)
        .map_err(|e| format!("Failed to write checkpoint: {}", e))?;

    let path_str = path.to_string_lossy().to_string();
    eprintln!("[SPF-WORKER] Checkpoint saved: {} ({} bytes, step {})",
        path_str, data.len(), state.training_step);

    Ok(path_str)
}

// ============================================================================
// WORKER LOOP — process pipeline tasks
// ============================================================================

/// Process a single pipeline task using the transformer.
/// The transformer decides which tool to call based on the task,
/// then dispatch::call() executes it through the normal gate pipeline.
pub fn process_task(
    task: &crate::pipeline::PipelineTask,
    _transformer: &Arc<RwLock<TransformerState>>,
    state: &Arc<crate::http::ServerState>,
) -> crate::pipeline::PipelineResult {
    let start = std::time::Instant::now();

    // Execute the task's tool through normal dispatch
    let source = crate::dispatch::Source::Pipeline {
        stream_id: task.stream_id.clone(),
        peer_key: "self".to_string(),
    };

    let response = crate::dispatch::call(state, source, &task.tool, &task.args);

    let duration_ms = start.elapsed().as_millis() as u64;

    // FL-10: Store pipeline execution as training signal in LMDB.
    // handle_train() reads tlog:* keys — same path for all signal sources
    // (gate, mesh brain_sync, pipeline, evil/good labels).
    {
        let signal = crate::gate_training::TrainingSignal {
            tool: task.tool.clone(),
            source: "pipeline".to_string(),
            allowed: response.status == "ok",
            status: response.status.clone(),
            duration_ms,
            timestamp: chrono::Utc::now().to_rfc3339(),
            user_override: false,
            false_positive: false,
            recent_call_count: 0,
            preceding_tools: vec![],
            evil_score: 0.0,
        };
        let db_path = crate::paths::spf_root().join("LIVE/LMDB5/LMDB5.DB");
        if let Ok(db) = crate::agent_state::AgentStateDb::open(&db_path) {
            if let Ok(json) = serde_json::to_string(&signal) {
                let tlog_key = format!("tlog:{}", signal.timestamp);
                let _ = db.set_state(&tlog_key, &json);
            }
        }
    }

    let status = if response.status == "ok" {
        crate::pipeline::PipelineStatus::Ok
    } else {
        crate::pipeline::PipelineStatus::Blocked
    };

    crate::pipeline::PipelineResult {
        task_id: task.task_id.clone(),
        stream_id: task.stream_id.clone(),
        status,
        result: response.result,
        error: if response.status != "ok" {
            Some(response.status)
        } else {
            None
        },
        duration_ms,
        executed_by: "worker".to_string(),
    }
}

// ============================================================================
// WORKER MAIN LOOP — headless task processing (no stdio)
// ============================================================================

/// Run the worker main loop. Polls pipeline for tasks, processes them,
/// records results, and auto-checkpoints at configured intervals.
/// Blocks until shutdown signal (SIGTERM/SIGINT).
pub fn run_worker(
    worker_state: &mut WorkerState,
    transformer: &Arc<RwLock<TransformerState>>,
    server_state: &Arc<crate::http::ServerState>,
) {
    eprintln!("[SPF-WORKER] Worker started: role={}, max_concurrent={}",
        worker_state.config.role, worker_state.config.max_concurrent);

    let poll_interval = std::time::Duration::from_millis(100);
    let max_concurrent = worker_state.config.max_concurrent;
    let auto_checkpoint_steps = worker_state.config.auto_checkpoint_steps;

    loop {
        // Poll pipeline for available tasks
        let tasks = {
            let mut pipeline = worker_state.pipeline.lock().unwrap();
            pipeline.next_tasks(max_concurrent)
        };

        if tasks.is_empty() {
            // No work — sleep briefly before polling again
            std::thread::sleep(poll_interval);
            continue;
        }

        // Process each task through the normal dispatch pipeline
        for task in &tasks {
            let result = process_task(task, transformer, server_state);

            let succeeded = result.status == crate::pipeline::PipelineStatus::Ok;
            if succeeded {
                worker_state.tasks_processed += 1;
            } else {
                worker_state.tasks_failed += 1;
            }

            // Record result (may trigger chained tasks)
            let mut pipeline = worker_state.pipeline.lock().unwrap();
            if let Some(chained_task) = pipeline.record_result(result) {
                // Chained task returned — process immediately on next iteration
                drop(pipeline);
                let chain_result = process_task(&chained_task, transformer, server_state);
                let mut pipeline = worker_state.pipeline.lock().unwrap();
                pipeline.record_result(chain_result);
            }
        }

        // Auto-checkpoint at configured interval
        let current_step = {
            let state = transformer.read().unwrap();
            state.training_step
        };
        if auto_checkpoint_steps > 0 && current_step > 0 && current_step % auto_checkpoint_steps == 0 {
            let state = transformer.read().unwrap();
            if let Err(e) = save_checkpoint(&state, &worker_state.transformer_config, &worker_state.config) {
                eprintln!("[SPF-WORKER] Auto-checkpoint failed: {}", e);
            }
        }
    }
}

// ============================================================================
// TESTS
// ============================================================================

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

    #[test]
    fn test_worker_config_default() {
        let config = WorkerConfig::default();
        assert_eq!(config.role, "writer");
        assert!(config.checkpoint_override.is_none());
        assert_eq!(config.max_concurrent, 4);
        assert_eq!(config.heartbeat_interval_secs, 30);
        assert!(config.train_while_serving);
    }

    #[test]
    fn test_worker_state_new() {
        let wc = WorkerConfig::default();
        let tc = TransformerConfig::default();
        let state = WorkerState::new(wc, tc);
        assert_eq!(state.tasks_processed, 0);
        assert_eq!(state.tasks_failed, 0);
        assert!(state.accepting);
    }

    #[test]
    fn test_worker_status_json() {
        let wc = WorkerConfig {
            role: "researcher".to_string(),
            ..Default::default()
        };
        let tc = TransformerConfig::default();
        let mut state = WorkerState::new(wc, tc);
        state.tasks_processed = 42;
        state.tasks_failed = 3;

        let status = state.status_json();
        assert_eq!(status["mode"], "worker");
        assert_eq!(status["role"], "researcher");
        assert_eq!(status["tasks_processed"], 42);
        assert_eq!(status["tasks_failed"], 3);
        assert_eq!(status["accepting"], true);
    }

    #[test]
    fn test_worker_config_custom() {
        let config = WorkerConfig {
            role: "researcher".to_string(),
            checkpoint_override: Some("/custom/path.spfc".to_string()),
            max_concurrent: 8,
            heartbeat_interval_secs: 60,
            auto_checkpoint_steps: 500,
            train_while_serving: false,
        };
        assert_eq!(config.role, "researcher");
        assert_eq!(config.checkpoint_override.unwrap(), "/custom/path.spfc");
        assert_eq!(config.max_concurrent, 8);
        assert!(!config.train_while_serving);
    }

    #[test]
    fn test_worker_state_uptime() {
        let wc = WorkerConfig::default();
        let tc = TransformerConfig::default();
        let state = WorkerState::new(wc, tc);

        // Uptime should be very small (just created)
        let status = state.status_json();
        let uptime = status["uptime_secs"].as_u64().unwrap();
        assert!(uptime < 2, "Uptime should be near zero, got {}", uptime);
    }

    #[test]
    fn test_worker_state_pipeline_integration() {
        let wc = WorkerConfig::default();
        let tc = TransformerConfig::default();
        let state = WorkerState::new(wc, tc);

        // Pipeline should be accessible and empty
        let pipeline = state.pipeline.lock().unwrap();
        let summary = pipeline.status_summary();
        assert_eq!(summary["active_streams"], 0);
        assert_eq!(summary["total_submitted"], 0);
    }

    #[test]
    fn test_init_transformer_disabled() {
        let tc = TransformerConfig {
            enabled: false,
            ..TransformerConfig::default()
        };
        let wc = WorkerConfig::default();

        let result = init_transformer(&tc, &wc);
        assert!(result.is_err());
        assert!(result.unwrap_err().contains("not enabled"));
    }

    #[test]
    fn test_init_transformer_no_checkpoint() {
        let tc = TransformerConfig {
            enabled: true,
            writer_checkpoint: "nonexistent_checkpoint.spfc".to_string(),
            d_model: 32,
            n_heads: 2,
            n_layers: 1,
            vocab_size: 64,
            max_seq_len: 16,
            d_ff: 128,
            ..TransformerConfig::default()
        };
        let wc = WorkerConfig::default();

        // Should succeed with fresh random weights (no checkpoint file)
        let result = init_transformer(&tc, &wc);
        assert!(result.is_ok());
        let state = result.unwrap();
        assert_eq!(state.role, "writer");
        assert!(state.last_checkpoint.is_empty());
    }

    #[test]
    fn test_init_transformer_researcher_role() {
        let tc = TransformerConfig {
            enabled: true,
            d_model: 32,
            n_heads: 2,
            n_layers: 1,
            vocab_size: 64,
            max_seq_len: 16,
            d_ff: 128,
            ..TransformerConfig::default()
        };
        let wc = WorkerConfig {
            role: "researcher".to_string(),
            ..Default::default()
        };

        let result = init_transformer(&tc, &wc);
        assert!(result.is_ok());
        assert_eq!(result.unwrap().role, "researcher");
    }
}