vct-core 2.4.0

//! Aggregates per-model token usage across the file-backed provider session trees.
//!
//! Each provider directory is walked with the provider fixed by its *source
//! path* (never re-detected from file contents), parsed in
//! [`ParseMode::UsageOnly`] to skip the heavy file-operation payloads, and the
//! small per-model usage maps are merged into a [`UsageData`]. The provider is
//! tracked twice on purpose — once merged across providers (the per-model
//! table) and once kept per source directory (the per-provider footer) — see
//! [`UsageData`] for why.

use crate::config::ProvidersConfig;
use crate::constants::{FastHashMap, FastHashSet, capacity};
use crate::models::TimeRange;
use crate::models::{
    CodeAnalysis, ExtensionType, PerProviderUsage, Provider, ProviderActiveDays, UsageResult,
};
use crate::pricing::TierThresholds;
use crate::session::cursor::{
    discover_cursor_store_dbs, load_conversation_model_snapshot, read_cursor_usage_store,
};
use crate::session::diagnostics::DatabaseUsageRead;
use crate::session::hermes::read_hermes_usage_contributions;
use crate::session::opencode::read_opencode_usage_contributions;
use crate::session::sqlite::is_cacheable_sqlite_failure;
use crate::session::{
    ParseMode, parse_session_file_typed_as, read_cursor_usage, read_hermes_usage,
    read_opencode_usage,
};
use crate::summary_cache::{
    CompactSourceSummary, SourceFingerprint, SummaryCacheKey, SummaryKind, SummaryScanCache,
};
use crate::utils::directory::collect_provider_files_diagnostics;
use crate::utils::{
    COPILOT_SESSION_MAX_DEPTH, GROK_SESSION_MAX_DEPTH, HelperPaths, is_claude_session_file,
    is_codex_session_file, is_copilot_session_file, is_gemini_session_file, is_grok_session_file,
    merge_usage_values, resolve_paths,
};
use anyhow::Result;
use rayon::prelude::*;
use serde::Serialize;
use serde_json::Value;
use std::collections::HashSet;
use std::path::Path;
use std::sync::Arc;

/// Aggregated token usage plus the per-provider active-day counts.
///
/// Built only by [`aggregate_usage_from_home`]; all fields are public for the
/// display layer to read. Token totals are tracked two ways at once because the
/// two views need different attribution: [`models`](UsageData::models) merges a
/// shared model (e.g. `claude-sonnet-4-6` emitted by both Claude Code and
/// Copilot CLI) into one row, while [`per_provider`](UsageData::per_provider)
/// keeps the same tokens scoped to the source directory so the footer can
/// attribute them correctly. The shared tokens are merged, not summed, so they
/// are never double-counted across the two maps.
///
/// # Examples
///
/// ```no_run
/// use vct_core::{aggregate_usage_from_home, TimeRange};
///
/// let data = aggregate_usage_from_home(TimeRange::All)?;
/// // Total distinct days that contributed any usage, across all providers.
/// println!("active days: {}", data.provider_days.total);
/// # Ok::<(), anyhow::Error>(())
/// ```
#[derive(Debug, Clone, Serialize)]
pub struct UsageData {
    /// Tokens aggregated across *all* providers, keyed by model name.
    ///
    /// Drives the per-model summary table where, e.g., `claude-sonnet-4-6`
    /// tokens from Claude Code and Copilot CLI share a single row.
    pub models: UsageResult,
    /// Tokens kept separate per source directory, keyed by provider → model.
    ///
    /// Drives the per-provider totals in the summary footer. Keeping this
    /// split at aggregation time avoids the display layer from having to
    /// guess a model's provider from its name, which broke once Copilot CLI
    /// started emitting real (Claude / OpenAI / …) model names.
    pub per_provider: PerProviderUsage,
    /// Count of distinct calendar dates that contributed usage, per provider
    /// and overall.
    pub provider_days: ProviderActiveDays,
    /// Provider-authoritative per-model cost (USD), summed from the source.
    pub stored_costs: StoredCosts,
}

// Usage and analysis both report the one unified scan-diagnostics type; it is
// re-exported here so callers can reach it as `usage::ScanDiagnostics`.
pub use crate::scan::{ScanDiagnostics, ScanFailure};

/// Usage data paired with source-collection diagnostics.
pub struct UsageCollection {
    /// Successfully collected usage.
    pub data: UsageData,
    /// Candidate, success, and failure counts from the scan.
    pub diagnostics: ScanDiagnostics,
}

/// Provider-authoritative per-model costs, kept **separate per provider**.
///
/// OpenCode and Hermes record their own costs. The Cursor map is retained for
/// source compatibility, but the local Cursor estimate now carries zero stored
/// cost and is priced by an exact LiteLLM match in the display layer. Separate
/// maps prevent a colliding bare model name from cross-contaminating providers.
#[derive(Debug, Default, Clone, Serialize)]
pub struct StoredCosts {
    /// OpenCode's per-model stored cost, keyed by model name.
    pub opencode: FastHashMap<String, f64>,
    /// Cursor's per-model dashboard cost, keyed by model name.
    pub cursor: FastHashMap<String, f64>,
    /// Hermes's per-model stored cost, keyed by model name.
    pub hermes: FastHashMap<String, f64>,
}

/// Extracts token usage data from a typed `CodeAnalysis`.
///
/// Reads directly from the typed `conversation_usage` map instead of walking
/// `Value` via `.get(...)`, so no intermediate `serde_json::Value` tree is
/// built or retained here.
fn extract_conversation_usage_from_analysis(analysis: CodeAnalysis) -> FastHashMap<String, Value> {
    let mut conversation_usage = FastHashMap::with_capacity(capacity::MODELS_PER_SESSION);

    let mut merge_into = |model: String, usage: Value| {
        conversation_usage
            .entry(model)
            .and_modify(|existing_usage| merge_usage_values(existing_usage, &usage))
            .or_insert(usage);
    };

    for record in analysis.records {
        for (model, usage) in record.conversation_usage {
            merge_into(model, usage);
        }
        // Claude advisor-message tokens live in a separate map so the
        // `analysis` aggregator ignores them; the `usage` path folds them in
        // here, attributed to the advisor's own model for correct pricing.
        for (model, usage) in record.advisor_usage {
            merge_into(model, usage);
        }
    }

    conversation_usage
}

/// Aggregates token usage from all AI provider session directories.
///
/// Scans the file-backed provider session trees resolved by [`resolve_paths`],
/// filtered by `time_range`, and rolls every session's
/// per-model usage into a [`UsageData`]. Missing provider directories are
/// skipped silently, and a source file or OpenCode database that fails to parse
/// logs a warning to stderr and is excluded rather than aborting the whole scan.
///
/// # Errors
///
/// Returns an error if [`resolve_paths`] cannot determine the provider
/// directories (e.g. the home directory is unavailable). Directory traversal
/// and metadata errors are currently skipped by the walker rather than
/// propagated.
///
/// # Examples
///
/// ```no_run
/// use vct_core::{aggregate_usage_from_home, TimeRange};
///
/// let data = aggregate_usage_from_home(TimeRange::All)?;
/// for model in data.models.keys() {
///     println!("{model}");
/// }
/// # Ok::<(), anyhow::Error>(())
/// ```
pub fn aggregate_usage_from_home(time_range: TimeRange) -> Result<UsageData> {
    aggregate_usage_from_home_with_providers(time_range, ProvidersConfig::default())
}

/// [`aggregate_usage_from_home`] with explicit per-provider toggles (from
/// `~/.vct/config.toml`). A disabled provider is skipped entirely.
pub fn aggregate_usage_from_home_with_providers(
    time_range: TimeRange,
    providers: ProvidersConfig,
) -> Result<UsageData> {
    aggregate_usage_from_paths_with_providers(&resolve_paths()?, time_range, providers)
}

/// Aggregates token usage from provider session directories rooted at an
/// explicit [`HelperPaths`].
///
/// The env-free, injectable counterpart of [`aggregate_usage_from_home`]:
/// every provider path comes from `paths` rather than the resolved home
/// directory, so tests can point them at a temp tree and exercise the real
/// aggregation without mutating process-global `HOME`. See
/// [`aggregate_usage_from_home`] for the aggregation semantics.
///
/// # Errors
///
/// Returns an error only under the same conditions as
/// [`aggregate_usage_from_home`].
pub fn aggregate_usage_from_paths(paths: &HelperPaths, time_range: TimeRange) -> Result<UsageData> {
    aggregate_usage_from_paths_with_providers(paths, time_range, ProvidersConfig::default())
}

/// [`aggregate_usage_from_paths`] with explicit provider toggles (the injectable core
/// used by the CLI once `config.toml` is loaded).
pub fn aggregate_usage_from_paths_with_providers(
    paths: &HelperPaths,
    time_range: TimeRange,
    providers: ProvidersConfig,
) -> Result<UsageData> {
    let mut result = FastHashMap::with_capacity(capacity::MODEL_COMBINATIONS);
    let mut per_provider = PerProviderUsage::default();
    let mut stored_costs = StoredCosts::default();

    let mut claude_dates: HashSet<String> = HashSet::new();
    let mut codex_dates: HashSet<String> = HashSet::new();
    let mut copilot_dates: HashSet<String> = HashSet::new();
    let mut gemini_dates: HashSet<String> = HashSet::new();
    let mut grok_dates: HashSet<String> = HashSet::new();
    let mut opencode_dates: HashSet<String> = HashSet::new();
    let mut cursor_dates: HashSet<String> = HashSet::new();
    let mut hermes_dates: HashSet<String> = HashSet::new();

    if providers.claude && paths.claude_session_dir.exists() {
        // Walks the projects tree recursively, so top-level `<session>.jsonl` logs
        // and `<session>/subagents/agent-*.jsonl` logs are both collected here.
        process_usage_directory(
            &[paths.claude_session_dir.as_path()],
            ExtensionType::ClaudeCode,
            &mut result,
            &mut per_provider.claude,
            &mut claude_dates,
            is_claude_session_file,
            time_range,
            None,
        );
    }

    let codex_dirs = paths.codex_session_dirs();
    if providers.codex && codex_dirs.iter().any(|dir| dir.exists()) {
        process_usage_directory(
            &codex_dirs,
            ExtensionType::Codex,
            &mut result,
            &mut per_provider.codex,
            &mut codex_dates,
            is_codex_session_file,
            time_range,
            None,
        );
    }

    if providers.copilot && paths.copilot_session_dir.exists() {
        // `events.jsonl` always lives exactly two levels under
        // `session-state/`. Bounding the walk here keeps per-session
        // snapshot subtrees (`rewind-snapshots/backups/*`, `files/*`, …)
        // out of the `WalkDir` iteration entirely, so the scan cost stays
        // linear in the number of sessions rather than total artifacts.
        process_usage_directory(
            &[paths.copilot_session_dir.as_path()],
            ExtensionType::Copilot,
            &mut result,
            &mut per_provider.copilot,
            &mut copilot_dates,
            is_copilot_session_file,
            time_range,
            Some(COPILOT_SESSION_MAX_DEPTH),
        );
    }

    if providers.gemini && paths.gemini_session_dir.exists() {
        process_usage_directory(
            &[paths.gemini_session_dir.as_path()],
            ExtensionType::Gemini,
            &mut result,
            &mut per_provider.gemini,
            &mut gemini_dates,
            is_gemini_session_file,
            time_range,
            None,
        );
    }

    if providers.grok && paths.grok_session_dir.exists() {
        process_usage_directory(
            &[paths.grok_session_dir.as_path()],
            ExtensionType::Grok,
            &mut result,
            &mut per_provider.grok,
            &mut grok_dates,
            is_grok_session_file,
            time_range,
            Some(GROK_SESSION_MAX_DEPTH),
        );
    }

    // OpenCode lives in a single SQLite database rather than a session
    // directory, so it is read directly instead of walked.
    if providers.opencode
        && paths.opencode_db.exists()
        && let Err(err) = process_opencode_usage(
            &paths.opencode_db,
            &mut result,
            &mut per_provider.opencode,
            &mut stored_costs.opencode,
            &mut opencode_dates,
            time_range,
        )
    {
        log::warn!(
            "failed to read OpenCode DB {}: {err}",
            paths.opencode_db.display()
        );
    }

    // Cursor's usage is a local estimate from its chat stores (read directly like
    // OpenCode, not a walked session directory), so it is only attempted when the
    // chat stores are present — matching the analysis path.
    if providers.cursor
        && paths.cursor_chats_dir.exists()
        && let Err(err) = process_cursor_usage(
            &paths.cursor_chats_dir,
            &paths.cursor_tracking_db,
            &mut result,
            &mut per_provider.cursor,
            &mut stored_costs.cursor,
            &mut cursor_dates,
            time_range,
        )
    {
        log::warn!("failed to read Cursor usage: {err}");
    }

    // Hermes, like OpenCode, is a single SQLite database read directly.
    if providers.hermes
        && paths.hermes_db.exists()
        && let Err(err) = process_hermes_usage(
            &paths.hermes_db,
            &mut result,
            &mut per_provider.hermes,
            &mut stored_costs.hermes,
            &mut hermes_dates,
            time_range,
        )
    {
        log::warn!(
            "failed to read Hermes DB {}: {err}",
            paths.hermes_db.display()
        );
    }

    let mut all_dates: HashSet<&String> = HashSet::new();
    all_dates.extend(claude_dates.iter());
    all_dates.extend(codex_dates.iter());
    all_dates.extend(copilot_dates.iter());
    all_dates.extend(gemini_dates.iter());
    all_dates.extend(grok_dates.iter());
    all_dates.extend(opencode_dates.iter());
    all_dates.extend(cursor_dates.iter());
    all_dates.extend(hermes_dates.iter());

    let provider_days = ProviderActiveDays {
        claude: claude_dates.len(),
        codex: codex_dates.len(),
        copilot: copilot_dates.len(),
        gemini: gemini_dates.len(),
        grok: grok_dates.len(),
        opencode: opencode_dates.len(),
        cursor: cursor_dates.len(),
        hermes: hermes_dates.len(),
        total: all_dates.len(),
    };

    Ok(UsageData {
        models: result,
        per_provider,
        provider_days,
        stored_costs,
    })
}

/// Optional knobs for a usage scan.
///
/// `tiers` is the per-request context-tier snapshot derived from the current
/// pricing map (see [`TierThresholds`]); `None` (the default) classifies
/// nothing and every request bills at base rates.
#[derive(Debug, Default, Clone)]
pub struct UsageScanOptions {
    /// "Model → lowest tier threshold" snapshot for per-request classification.
    pub tiers: Option<Arc<TierThresholds>>,
}

/// Diagnostics-aware usage scan rooted at the current user's provider paths.
pub fn aggregate_usage_from_home_with_diagnostics(
    time_range: TimeRange,
    providers: ProvidersConfig,
) -> Result<UsageCollection> {
    aggregate_usage_from_home_with_diagnostics_opts(
        time_range,
        providers,
        &UsageScanOptions::default(),
    )
}

/// [`aggregate_usage_from_home_with_diagnostics`] with scan options.
pub fn aggregate_usage_from_home_with_diagnostics_opts(
    time_range: TimeRange,
    providers: ProvidersConfig,
    options: &UsageScanOptions,
) -> Result<UsageCollection> {
    let mut cache = SummaryScanCache::new();
    aggregate_usage_from_paths_with_cache_opts(
        &resolve_paths()?,
        time_range,
        providers,
        &mut cache,
        options,
    )
}

/// Diagnostics-aware usage scan rooted at explicit provider paths.
pub fn aggregate_usage_from_paths_with_diagnostics(
    paths: &HelperPaths,
    time_range: TimeRange,
    providers: ProvidersConfig,
) -> Result<UsageCollection> {
    let mut cache = SummaryScanCache::new();
    aggregate_usage_from_paths_with_cache(paths, time_range, providers, &mut cache)
}

/// Incremental usage scan backed by a process-local compact summary cache.
///
/// Reusing `cache` across calls reparses only sources whose fingerprint
/// changed. Cached schema failures retain their diagnostics, while metadata,
/// open, and read errors are not inserted and are retried next time.
pub fn aggregate_usage_from_paths_with_cache(
    paths: &HelperPaths,
    time_range: TimeRange,
    providers: ProvidersConfig,
    cache: &mut SummaryScanCache,
) -> Result<UsageCollection> {
    aggregate_usage_from_paths_with_cache_opts(
        paths,
        time_range,
        providers,
        cache,
        &UsageScanOptions::default(),
    )
}

/// [`aggregate_usage_from_paths_with_cache`] with scan options.
pub fn aggregate_usage_from_paths_with_cache_opts(
    paths: &HelperPaths,
    time_range: TimeRange,
    providers: ProvidersConfig,
    cache: &mut SummaryScanCache,
    options: &UsageScanOptions,
) -> Result<UsageCollection> {
    aggregate_usage_from_paths_with_cache_inner(paths, time_range, providers, cache, options)
}

fn aggregate_usage_from_paths_with_cache_inner(
    paths: &HelperPaths,
    time_range: TimeRange,
    providers: ProvidersConfig,
    cache: &mut SummaryScanCache,
    options: &UsageScanOptions,
) -> Result<UsageCollection> {
    // Cached summaries embed the tier classification, so a changed threshold
    // snapshot (daily pricing reload) invalidates every cached entry.
    let tiers = options.tiers.as_deref();
    cache.ensure_tier_fingerprint(tiers.map_or(0, TierThresholds::fingerprint));
    cache.begin_scan();
    let mut accumulator = UsageAccumulator::default();
    let mut diagnostics = ScanDiagnostics::default();
    let mut seen = FastHashSet::default();

    crate::scan::scan_all_cached_files(
        paths,
        providers,
        time_range,
        cache,
        &mut seen,
        &mut accumulator,
        &mut diagnostics,
        tiers,
    )?;

    if providers.opencode && paths.opencode_db.exists() {
        scan_usage_database(
            ExtensionType::OpenCode,
            &paths.opencode_db,
            SourceFingerprint::sqlite(&paths.opencode_db, &[]),
            time_range,
            cache,
            &mut seen,
            &mut accumulator,
            &mut diagnostics,
            || read_opencode_usage_contributions(&paths.opencode_db, time_range),
        );
    }
    if providers.cursor && paths.cursor_chats_dir.exists() {
        scan_cursor_usage_database(
            &paths.cursor_chats_dir,
            &paths.cursor_tracking_db,
            time_range,
            cache,
            &mut seen,
            &mut accumulator,
            &mut diagnostics,
        );
    }
    if providers.hermes && paths.hermes_db.exists() {
        scan_usage_database(
            ExtensionType::Hermes,
            &paths.hermes_db,
            SourceFingerprint::sqlite(&paths.hermes_db, &[]),
            time_range,
            cache,
            &mut seen,
            &mut accumulator,
            &mut diagnostics,
            || read_hermes_usage_contributions(&paths.hermes_db, time_range),
        );
    }

    cache.retain_kinds(&seen, &[SummaryKind::File, SummaryKind::UsageDatabase]);
    diagnostics.finalize();
    Ok(UsageCollection {
        data: accumulator.finish(),
        diagnostics,
    })
}

#[allow(clippy::too_many_arguments)]
fn scan_usage_database<F>(
    provider: ExtensionType,
    source: &Path,
    fingerprint: Result<SourceFingerprint>,
    time_range: TimeRange,
    cache: &mut SummaryScanCache,
    seen: &mut FastHashSet<SummaryCacheKey>,
    accumulator: &mut UsageAccumulator,
    diagnostics: &mut ScanDiagnostics,
    loader: F,
) where
    F: FnOnce() -> Result<DatabaseUsageRead>,
{
    diagnostics.candidates += 1;
    let key = SummaryCacheKey::new(SummaryKind::UsageDatabase, provider, source, time_range);
    seen.insert(key.clone());
    let fingerprint = match fingerprint {
        Ok(value) => value,
        Err(error) => {
            diagnostics.failures.push(ScanFailure {
                provider,
                source: source.to_path_buf(),
                error: error.to_string(),
            });
            return;
        }
    };
    if let Some(cached) = cache.get(&key, &fingerprint) {
        crate::scan::fold_cached(provider, source, cached, accumulator, diagnostics);
        return;
    }

    cache.record_parse();
    match loader() {
        Ok(read) => {
            let complete_failure = read.expected_records > 0 && read.parsed_records == 0;
            let failed = read.failed_records();
            let mut summary = CompactSourceSummary::default();
            for contribution in read.rows {
                summary.add_usage_contribution(contribution);
            }
            let loaded = crate::scan::LoadedCompactSummary {
                summary,
                parsed: !complete_failure,
                failure: if complete_failure {
                    Some(format!(
                        "none of {} usage records used a supported schema",
                        read.expected_records
                    ))
                } else if failed > 0 {
                    Some(format!("{failed} usage records used an unsupported schema"))
                } else {
                    None
                },
            };
            crate::scan::fold_loaded(provider, source, &loaded, accumulator, diagnostics);
            cache.insert(
                key,
                fingerprint,
                loaded.summary,
                loaded.parsed,
                loaded.failure,
            );
        }
        Err(error) => {
            let failure = error.to_string();
            diagnostics.failures.push(ScanFailure {
                provider,
                source: source.to_path_buf(),
                error: failure.clone(),
            });
            if is_cacheable_sqlite_failure(&error) {
                cache.insert(
                    key,
                    fingerprint,
                    CompactSourceSummary::default(),
                    false,
                    Some(failure),
                );
            }
        }
    }
}

fn scan_cursor_usage_database(
    chats_dir: &Path,
    tracking_db: &Path,
    time_range: TimeRange,
    cache: &mut SummaryScanCache,
    seen: &mut FastHashSet<SummaryCacheKey>,
    accumulator: &mut UsageAccumulator,
    diagnostics: &mut ScanDiagnostics,
) {
    let provider = ExtensionType::Cursor;
    let discovery = discover_cursor_store_dbs(chats_dir);
    if !discovery.failures.is_empty() {
        cache.preserve_provider_keys(seen, SummaryKind::UsageDatabase, provider);
    }
    for failure in discovery.failures {
        diagnostics.candidates += 1;
        diagnostics.failures.push(ScanFailure {
            provider,
            source: failure.path,
            error: failure.error,
        });
    }

    let (conv_models, tracking_fingerprint, tracking_ok) =
        match load_conversation_model_snapshot(tracking_db) {
            Ok(snapshot) => (snapshot.models, snapshot.fingerprint, true),
            Err(error) => {
                diagnostics.failures.push(ScanFailure {
                    provider,
                    source: tracking_db.to_path_buf(),
                    error: error.to_string(),
                });
                (FastHashMap::default(), None, false)
            }
        };

    for store in discovery.stores {
        diagnostics.candidates += 1;
        let key = SummaryCacheKey::new(SummaryKind::UsageDatabase, provider, &store, time_range);
        seen.insert(key.clone());
        let fingerprint = if tracking_ok {
            SourceFingerprint::sqlite_with_dependency(
                &store,
                tracking_db,
                tracking_fingerprint.as_ref(),
            )
        } else {
            SourceFingerprint::sqlite(&store, &[])
        };
        let fingerprint = match fingerprint {
            Ok(fingerprint) => fingerprint,
            Err(error) => {
                diagnostics.failures.push(ScanFailure {
                    provider,
                    source: store,
                    error: error.to_string(),
                });
                continue;
            }
        };
        if tracking_ok && let Some(cached) = cache.get(&key, &fingerprint) {
            crate::scan::fold_cached(provider, &store, cached, accumulator, diagnostics);
            continue;
        }

        cache.record_parse();
        match read_cursor_usage_store(&store, &conv_models, time_range) {
            Ok(read) => {
                let complete_failure = read.expected_records > 0 && read.parsed_records == 0;
                let failed = read.failed_records();
                let mut summary = CompactSourceSummary::default();
                for contribution in read.rows {
                    summary.add_usage_contribution(contribution);
                }
                let loaded = crate::scan::LoadedCompactSummary {
                    summary,
                    parsed: !complete_failure,
                    failure: if complete_failure {
                        Some(format!(
                            "none of {} Cursor usage payloads used a supported schema",
                            read.expected_records
                        ))
                    } else if failed > 0 {
                        Some(format!(
                            "{failed} Cursor usage payloads used an unsupported schema"
                        ))
                    } else {
                        None
                    },
                };
                crate::scan::fold_loaded(provider, &store, &loaded, accumulator, diagnostics);
                if tracking_ok {
                    cache.insert(
                        key,
                        fingerprint,
                        loaded.summary,
                        loaded.parsed,
                        loaded.failure,
                    );
                }
            }
            Err(error) => {
                let failure = error.to_string();
                diagnostics.failures.push(ScanFailure {
                    provider,
                    source: store.clone(),
                    error: failure.clone(),
                });
                if tracking_ok && is_cacheable_sqlite_failure(&error) {
                    cache.insert(
                        key,
                        fingerprint,
                        CompactSourceSummary::default(),
                        false,
                        Some(failure),
                    );
                }
            }
        }
    }
}

#[derive(Default)]
struct UsageAccumulator {
    models: UsageResult,
    per_provider: PerProviderUsage,
    stored_costs: StoredCosts,
    claude_dates: HashSet<String>,
    codex_dates: HashSet<String>,
    copilot_dates: HashSet<String>,
    gemini_dates: HashSet<String>,
    grok_dates: HashSet<String>,
    opencode_dates: HashSet<String>,
    cursor_dates: HashSet<String>,
    hermes_dates: HashSet<String>,
}

impl crate::scan::CompactSink for UsageAccumulator {
    fn fold(&mut self, provider: ExtensionType, summary: &CompactSourceSummary) {
        self.add(provider, summary);
    }
}

impl UsageAccumulator {
    fn add(&mut self, provider: ExtensionType, summary: &CompactSourceSummary) {
        let provider_result = match provider {
            ExtensionType::ClaudeCode => &mut self.per_provider.claude,
            ExtensionType::Codex => &mut self.per_provider.codex,
            ExtensionType::Copilot => &mut self.per_provider.copilot,
            ExtensionType::Gemini => &mut self.per_provider.gemini,
            ExtensionType::Grok => &mut self.per_provider.grok,
            ExtensionType::OpenCode => &mut self.per_provider.opencode,
            ExtensionType::Cursor => &mut self.per_provider.cursor,
            ExtensionType::Hermes => &mut self.per_provider.hermes,
        };
        // Clone the model key only on a miss (an insert genuinely needs an owned
        // key); a merge into an existing row needs no allocation at all.
        for (model, usage) in &summary.usage {
            match provider_result.get_mut(model) {
                Some(existing) => merge_usage_values(existing, usage),
                None => {
                    provider_result.insert(model.clone(), usage.clone());
                }
            }
            match self.models.get_mut(model) {
                Some(existing) => merge_usage_values(existing, usage),
                None => {
                    self.models.insert(model.clone(), usage.clone());
                }
            }
        }
        for (model, tokens) in &summary.database_usage {
            let usage = tokens.into_value();
            match provider_result.get_mut(model) {
                Some(existing) => merge_usage_values(existing, &usage),
                None => {
                    provider_result.insert(model.clone(), usage.clone());
                }
            }
            match self.models.get_mut(model) {
                Some(existing) => merge_usage_values(existing, &usage),
                None => {
                    // Last use of `usage`, so move it in rather than clone.
                    self.models.insert(model.clone(), usage);
                }
            }
        }

        let stored = match provider {
            ExtensionType::OpenCode => Some(&mut self.stored_costs.opencode),
            ExtensionType::Cursor => Some(&mut self.stored_costs.cursor),
            ExtensionType::Hermes => Some(&mut self.stored_costs.hermes),
            _ => None,
        };
        if let Some(stored) = stored {
            for (model, cost) in &summary.stored_costs {
                *stored.entry(model.clone()).or_insert(0.0) += cost;
            }
        }

        let dates = match provider {
            ExtensionType::ClaudeCode => &mut self.claude_dates,
            ExtensionType::Codex => &mut self.codex_dates,
            ExtensionType::Copilot => &mut self.copilot_dates,
            ExtensionType::Gemini => &mut self.gemini_dates,
            ExtensionType::Grok => &mut self.grok_dates,
            ExtensionType::OpenCode => &mut self.opencode_dates,
            ExtensionType::Cursor => &mut self.cursor_dates,
            ExtensionType::Hermes => &mut self.hermes_dates,
        };
        dates.extend(summary.usage_dates.iter().cloned());
    }

    fn finish(self) -> UsageData {
        // Only the union's cardinality is needed, so union references rather
        // than cloning every date string across the eight per-provider sets.
        let mut all_dates: HashSet<&String> = HashSet::new();
        all_dates.extend(self.claude_dates.iter());
        all_dates.extend(self.codex_dates.iter());
        all_dates.extend(self.copilot_dates.iter());
        all_dates.extend(self.gemini_dates.iter());
        all_dates.extend(self.grok_dates.iter());
        all_dates.extend(self.opencode_dates.iter());
        all_dates.extend(self.cursor_dates.iter());
        all_dates.extend(self.hermes_dates.iter());
        let total_days = all_dates.len();
        UsageData {
            models: self.models,
            per_provider: self.per_provider,
            provider_days: ProviderActiveDays {
                claude: self.claude_dates.len(),
                codex: self.codex_dates.len(),
                copilot: self.copilot_dates.len(),
                gemini: self.gemini_dates.len(),
                grok: self.grok_dates.len(),
                opencode: self.opencode_dates.len(),
                cursor: self.cursor_dates.len(),
                hermes: self.hermes_dates.len(),
                total: total_days,
            },
            stored_costs: self.stored_costs,
        }
    }
}

/// Walks one provider's session roots and merges their usage into both result maps.
///
/// Files matching `filter_fn` (and within `max_depth`, when set) are parsed in
/// parallel with the provider fixed to `provider` — never re-detected from
/// contents — and each session's per-model tokens are merged into both
/// `global_result` (cross-provider view) and `provider_result` (source-scoped
/// view). Every contributing session's modified date is inserted into
/// `unique_dates` for the active-day count. Traversal and metadata errors are
/// skipped by the collector, and a file that fails to parse logs a warning and
/// is skipped, so this is best-effort by construction and cannot fail.
#[allow(clippy::too_many_arguments)] // per-provider helper; struct-wrapping the args would hurt readability
fn process_usage_directory<F>(
    dirs: &[&Path],
    provider: ExtensionType,
    global_result: &mut UsageResult,
    provider_result: &mut UsageResult,
    unique_dates: &mut HashSet<String>,
    filter_fn: F,
    time_range: TimeRange,
    max_depth: Option<usize>,
) where
    F: Copy + Fn(&Path) -> bool + Sync + Send,
{
    // This entry point has no diagnostics channel, so discovery failures are
    // dropped here; the `*_with_diagnostics` scanners are the ones that report them.
    let files = collect_provider_files_diagnostics(dirs, filter_fn, time_range, max_depth).files;

    // Parse each file directly in `UsageOnly` mode, extract the small
    // per-model usage map, then drop the analysis. The provider is fixed by
    // the source directory — we do not re-detect from file contents, which
    // would mis-classify Claude sessions whose first line is a metadata
    // sentinel (`permission-mode`, `file-history-snapshot`) and silently drop
    // their usage. We also deliberately bypass the global file cache here:
    // the `usage` path never needs the heavy `write_file_details` /
    // `edit_file_details` payloads, so caching the full analysis would waste
    // the memory win from `UsageOnly`.
    let file_results: Vec<(String, FastHashMap<String, Value>)> = files
        .into_par_iter()
        .filter_map(|file_info| {
            match parse_session_file_typed_as(&file_info.path, provider, ParseMode::UsageOnly) {
                Ok(analysis) => {
                    let conversation_usage = extract_conversation_usage_from_analysis(analysis);
                    Some((file_info.modified_date, conversation_usage))
                }
                Err(e) => {
                    log::warn!("failed to analyze {}: {e}", file_info.path.display());
                    None
                }
            }
        })
        .collect();

    // Merge parallel results sequentially (this part is fast). Every
    // per-model usage value is merged into *both* maps:
    //   - `global_result` keeps the cross-provider view used by the main
    //     per-model table,
    //   - `provider_result` keeps the same tokens scoped to this provider
    //     so the summary footer can attribute them to the right source
    //     directory without having to guess from the model name.
    for (date, conversation_usage) in file_results {
        if usage_map_has_activity(&conversation_usage, 0.0) {
            unique_dates.insert(date);
        }

        for (model, usage_value) in conversation_usage {
            provider_result
                .entry(model.clone())
                .and_modify(|existing| merge_usage_values(existing, &usage_value))
                .or_insert_with(|| usage_value.clone());

            global_result
                .entry(model)
                .and_modify(|existing| merge_usage_values(existing, &usage_value))
                .or_insert(usage_value);
        }
    }
}

/// Reads OpenCode's SQLite database and merges its per-model usage into both
/// the global and OpenCode-scoped maps.
///
/// Mirrors the tail of [`process_usage_directory`] but sources sessions from
/// the database (via [`read_opencode_usage`]) instead of a directory walk. Each
/// row's date comes from the assistant message timestamp (falling back to
/// `session.time_updated` on legacy schemas) and is recorded in `unique_dates`
/// for the active-day count.
///
/// # Errors
///
/// Returns an error if the database cannot be opened or queried.
fn process_opencode_usage(
    db_path: &Path,
    global_result: &mut UsageResult,
    provider_result: &mut UsageResult,
    stored_costs: &mut FastHashMap<String, f64>,
    unique_dates: &mut HashSet<String>,
    time_range: TimeRange,
) -> Result<()> {
    let sessions = read_opencode_usage(db_path, time_range)?;
    fold_stored_cost_sessions(
        sessions,
        global_result,
        provider_result,
        stored_costs,
        unique_dates,
    );
    Ok(())
}

/// Reads Cursor's per-model usage (a local estimate from the chat stores) and
/// merges it into both the global and Cursor-scoped maps.
///
/// Mirrors [`process_opencode_usage`]: the estimate carries its own per-model
/// tuple shape as stored-cost readers. Its zero stored cost lets the display
/// layer accept only an exact LiteLLM match rather than a fuzzy price guess.
fn process_cursor_usage(
    chats_dir: &Path,
    tracking_db: &Path,
    global_result: &mut UsageResult,
    provider_result: &mut UsageResult,
    stored_costs: &mut FastHashMap<String, f64>,
    unique_dates: &mut HashSet<String>,
    time_range: TimeRange,
) -> Result<()> {
    let sessions = read_cursor_usage(chats_dir, tracking_db, time_range)?;
    fold_stored_cost_sessions(
        sessions,
        global_result,
        provider_result,
        stored_costs,
        unique_dates,
    );
    Ok(())
}

/// Reads Hermes's per-model usage from its SQLite database and merges it into
/// both the global and Hermes-scoped maps.
///
/// Mirrors [`process_opencode_usage`]: Hermes stores its own per-model cost, so
/// it uses the same stored-cost path rather than a fuzzy price guess.
///
/// # Errors
///
/// Returns an error if the database cannot be opened or queried.
fn process_hermes_usage(
    db_path: &Path,
    global_result: &mut UsageResult,
    provider_result: &mut UsageResult,
    stored_costs: &mut FastHashMap<String, f64>,
    unique_dates: &mut HashSet<String>,
    time_range: TimeRange,
) -> Result<()> {
    let sessions = read_hermes_usage(db_path, time_range)?;
    fold_stored_cost_sessions(
        sessions,
        global_result,
        provider_result,
        stored_costs,
        unique_dates,
    );
    Ok(())
}

/// Folds `(date, analysis, cost)` rows from a stored-cost provider (OpenCode /
/// Cursor) into the global + provider-scoped maps and the stored-cost table.
fn fold_stored_cost_sessions(
    sessions: Vec<(String, CodeAnalysis, f64)>,
    global_result: &mut UsageResult,
    provider_result: &mut UsageResult,
    stored_costs: &mut FastHashMap<String, f64>,
    unique_dates: &mut HashSet<String>,
) {
    for (date, analysis, session_cost) in sessions {
        let conversation_usage = extract_conversation_usage_from_analysis(analysis);
        if usage_map_has_activity(&conversation_usage, session_cost) {
            unique_dates.insert(date);
        }
        for (model, usage_value) in conversation_usage {
            *stored_costs.entry(model.clone()).or_insert(0.0) += session_cost;

            provider_result
                .entry(model.clone())
                .and_modify(|existing| merge_usage_values(existing, &usage_value))
                .or_insert_with(|| usage_value.clone());

            global_result
                .entry(model)
                .and_modify(|existing| merge_usage_values(existing, &usage_value))
                .or_insert(usage_value);
        }
    }
}

fn usage_map_has_activity(usage: &FastHashMap<String, Value>, stored_cost: f64) -> bool {
    stored_cost != 0.0
        || usage
            .values()
            .any(|value| crate::utils::extract_token_counts(value).has_activity())
}

impl UsageData {
    /// Returns the per-provider usage slice for `provider`, or `None`
    /// when the provider has no dedicated bucket (e.g. `Provider::Unknown`
    /// — the display layer's fallthrough view is fed by the global
    /// `models` map instead).
    pub fn provider_usage(&self, provider: Provider) -> Option<&UsageResult> {
        self.per_provider.get(provider)
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::utils::TokenCounts;
    use serde_json::json;

    #[test]
    fn merge_preserves_tokens_across_mixed_shapes() {
        use crate::utils::extract_token_counts;

        // A Codex `total_token_usage` value (input 1000 includes 200 cached).
        let codex = json!({
            "total_token_usage": {
                "input_tokens": 1000,
                "cached_input_tokens": 200,
                "output_tokens": 500,
                "total_tokens": 1500
            }
        });
        // A Cursor / flat value for the same model name.
        let flat = json!({
            "input_tokens": 100,
            "output_tokens": 20,
            "cache_read_input_tokens": 50,
            "cache_creation_input_tokens": 10
        });

        // Codex disjoint counts: input 800, cache_read 200, output 500, total 1500.
        // Flat counts: input 100, output 20, cache_read 50, cache_creation 10.
        let expect = |c: TokenCounts| {
            assert_eq!(c.input_tokens, 800 + 100);
            assert_eq!(c.output_tokens, 500 + 20);
            assert_eq!(c.cache_read, 200 + 50);
            assert_eq!(c.cache_creation, 10);
            // Bucket sum: 1500 (Codex) + 180 (flat) = 1680; no tokens dropped.
            assert_eq!(c.total, 1680);
        };

        // Merging is order-independent: neither side's tokens are dropped.
        let mut existing = codex.clone();
        merge_usage_values(&mut existing, &flat);
        expect(extract_token_counts(&existing));

        let mut existing = flat.clone();
        merge_usage_values(&mut existing, &codex);
        expect(extract_token_counts(&existing));
    }
}