use anyhow::{Context, Result};
use chrono::Utc;
use clap::Parser;
use image_api::ai::LocalLlm;
use image_api::bin_progress;
use image_api::database::calendar_dao::{InsertCalendarEvent, SqliteCalendarEventDao};
use image_api::parsers::ical_parser::parse_ics_file;
use log::{error, info};

// Import the trait to use its methods
use image_api::database::CalendarEventDao;

#[derive(Parser, Debug)]
#[command(author, version, about = "Import Google Takeout Calendar data", long_about = None)]
struct Args {
    /// Path to the .ics calendar file
    #[arg(short, long)]
    path: String,

    /// Generate embeddings for calendar events (slower but enables semantic search)
    #[arg(long, default_value = "false")]
    generate_embeddings: bool,

    /// Skip events that already exist in the database
    #[arg(long, default_value = "true")]
    skip_existing: bool,

    /// Batch size for embedding generation
    #[arg(long, default_value = "128")]
    batch_size: usize,
}

#[tokio::main]
async fn main() -> Result<()> {
    dotenv::dotenv().ok();
    env_logger::init();

    let args = Args::parse();

    info!("Parsing calendar file: {}", args.path);
    let events = parse_ics_file(&args.path).context("Failed to parse .ics file")?;

    info!("Found {} calendar events", events.len());

    let context = opentelemetry::Context::current();

    // LocalLlm dispatches per LLM_BACKEND, so embeddings written here land
    // in the same vector space the query side searches.
    let llm = if args.generate_embeddings {
        Some(LocalLlm::from_env())
    } else {
        None
    };

    let mut inserted_count = 0usize;
    let mut skipped_count = 0usize;
    let mut error_count = 0usize;

    let pb = bin_progress::determinate(events.len() as u64, "importing");

    // Process events in batches
    // Can't use rayon with async, so process sequentially
    for event in &events {
        let mut dao_instance = SqliteCalendarEventDao::new();

        // Check if event exists
        if args.skip_existing
            && let Ok(exists) = dao_instance.event_exists(
                &context,
                event.event_uid.as_deref().unwrap_or(""),
                event.start_time,
            )
            && exists
        {
            skipped_count += 1;
            pb.inc(1);
            continue;
        }

        // Generate embedding if requested (blocking call)
        let embedding = if let Some(ref llm) = llm {
            let text = format!(
                "{} {} {}",
                event.summary,
                event.description.as_deref().unwrap_or(""),
                event.location.as_deref().unwrap_or("")
            );

            match tokio::task::block_in_place(|| {
                tokio::runtime::Handle::current().block_on(async { llm.embed(&text).await })
            }) {
                Ok(emb) => Some(emb),
                Err(e) => {
                    pb.println(format!("embedding failed for '{}': {}", event.summary, e));
                    None
                }
            }
        } else {
            None
        };

        // Insert into database
        let insert_event = InsertCalendarEvent {
            event_uid: event.event_uid.clone(),
            summary: event.summary.clone(),
            description: event.description.clone(),
            location: event.location.clone(),
            start_time: event.start_time,
            end_time: event.end_time,
            all_day: event.all_day,
            organizer: event.organizer.clone(),
            attendees: if event.attendees.is_empty() {
                None
            } else {
                Some(serde_json::to_string(&event.attendees).unwrap_or_default())
            },
            embedding,
            created_at: Utc::now().timestamp(),
            source_file: Some(args.path.clone()),
        };

        match dao_instance.store_event(&context, insert_event) {
            Ok(_) => inserted_count += 1,
            Err(e) => {
                pb.println(format!("store failed for '{}': {:?}", event.summary, e));
                error_count += 1;
            }
        }
        pb.set_message(format!(
            "inserted={} skipped={} errors={}",
            inserted_count, skipped_count, error_count
        ));
        pb.inc(1);
    }

    pb.finish_and_clear();

    info!("=== Import Summary ===");
    info!("Total events found: {}", events.len());
    info!("Successfully inserted: {}", inserted_count);
    info!("Skipped (already exist): {}", skipped_count);
    info!("Errors: {}", error_count);

    if args.generate_embeddings {
        info!("Embeddings were generated for semantic search");
    } else {
        info!("No embeddings generated (use --generate-embeddings to enable semantic search)");
    }

    if error_count > 0 {
        error!(
            "Completed with {} errors — review log output above",
            error_count
        );
    }

    Ok(())
}