bamboo_compression/

limits.rs

//! Model context window limits registry.
//!
//! There is intentionally **no** built-in per-model table. Real per-model
//! values come from two sources, in priority order:
//!   1. provider runtime metadata (e.g. Copilot reports real context/output),
//!   2. user overrides persisted in `model_limits.json`.
//!
//! Anything without a match falls back to a single global default
//! (`DEFAULT_MAX_CONTEXT_TOKENS` / `DEFAULT_MAX_OUTPUT_TOKENS`). This keeps the
//! registry from going stale as models churn — see `token_budget.rs`.

use serde::{Deserialize, Serialize};
use serde_json::Value;
use std::collections::HashMap;
use std::path::PathBuf;

/// Sentinel pattern used for the single global fallback limit.
pub const DEFAULT_MODEL_PATTERN: &str = "default";

/// Global default context window applied to any model without a provider
/// metadata value or a user override. 1M reflects the current mainstream
/// range across frontier models (Claude 3.5, GPT-4o, Gemini 1.5, etc.).
pub const DEFAULT_MAX_CONTEXT_TOKENS: u32 = 1_000_000;

/// Global default maximum output tokens.
pub const DEFAULT_MAX_OUTPUT_TOKENS: u32 = 128_000;

/// Default safety margin for token counting errors (floor; scales with context
/// window via [`ModelLimit::get_safety_margin`]).
pub const DEFAULT_SAFETY_MARGIN: u32 = 1000;

/// Build the single global default limit (`1M` context / `128K` output).
pub fn default_model_limit() -> ModelLimit {
    builtin_limit(
        DEFAULT_MODEL_PATTERN,
        DEFAULT_MAX_CONTEXT_TOKENS,
        DEFAULT_MAX_OUTPUT_TOKENS,
    )
}

/// Whether a user override is a no-op — identical to the global default, so it
/// carries no information and need not be persisted (diff-only storage).
///
/// The `model_pattern` is irrelevant: any model pinned to exactly the default
/// context/output with no explicit safety margin resolves to the same budget
/// as having no override at all.
pub fn is_default_limit(limit: &ModelLimit) -> bool {
    limit.max_context_tokens == DEFAULT_MAX_CONTEXT_TOKENS
        && limit.max_output_tokens == Some(DEFAULT_MAX_OUTPUT_TOKENS)
        && limit.safety_margin.is_none()
}

/// Model limit configuration (user-overridable).
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ModelLimit {
    /// Model identifier (partial match supported, e.g., "gpt-4" matches "gpt-4o")
    pub model_pattern: String,
    /// Maximum context window size in tokens
    pub max_context_tokens: u32,
    /// Maximum output tokens (defaults to min(4096, max_context / 4))
    #[serde(default)]
    pub max_output_tokens: Option<u32>,
    /// Safety margin for token counting (defaults to 1000)
    #[serde(default)]
    pub safety_margin: Option<u32>,
}

impl ModelLimit {
    /// Create a new model limit with defaults.
    pub fn new(model_pattern: impl Into<String>, max_context_tokens: u32) -> Self {
        Self {
            model_pattern: model_pattern.into(),
            max_context_tokens,
            max_output_tokens: None,
            safety_margin: None,
        }
    }

    /// Get max output tokens with default calculation.
    pub fn get_max_output_tokens(&self) -> u32 {
        self.max_output_tokens
            .unwrap_or_else(|| (self.max_context_tokens / 4).min(4096))
    }

    /// Get safety margin, scaling proportionally with context window.
    pub fn get_safety_margin(&self) -> u32 {
        self.safety_margin
            .unwrap_or_else(|| (self.max_context_tokens / 100).max(DEFAULT_SAFETY_MARGIN))
    }
}

fn builtin_limit(pattern: &str, max_context_tokens: u32, max_output_tokens: u32) -> ModelLimit {
    let mut limit = ModelLimit::new(pattern.to_string(), max_context_tokens);
    limit.max_output_tokens = Some(max_output_tokens);
    limit
}

/// Registry for model limits with built-in defaults and user overrides.
#[derive(Debug, Clone)]
pub struct ModelLimitsRegistry {
    /// User-provided overrides (higher priority than built-in)
    user_limits: HashMap<String, ModelLimit>,
    /// Default path for user configuration file
    config_path: Option<PathBuf>,
}

impl ModelLimitsRegistry {
    /// Create a new registry with built-in defaults only.
    pub fn new() -> Self {
        Self {
            user_limits: HashMap::new(),
            config_path: None,
        }
    }

    /// Create a registry with a specific config file path.
    pub fn with_config_path(path: impl Into<PathBuf>) -> Self {
        Self {
            user_limits: HashMap::new(),
            config_path: Some(path.into()),
        }
    }

    /// Load user overrides from the registry's configured path.
    ///
    /// No-op when the registry was created without a `config_path` (use
    /// [`Self::with_config_path`] — e.g. with [`get_default_config_path`] — to
    /// point it at `{bamboo_data_dir}/model_limits.json`).
    pub async fn load_user_config(&mut self) -> std::io::Result<()> {
        let Some(path) = self.config_path.clone() else {
            return Ok(());
        };

        if !path.exists() {
            return Ok(());
        }

        let content = tokio::fs::read_to_string(&path).await?;
        let limits: Vec<ModelLimit> = serde_json::from_str(&content)
            .map_err(|e| std::io::Error::new(std::io::ErrorKind::InvalidData, e.to_string()))?;

        for limit in limits {
            self.user_limits.insert(limit.model_pattern.clone(), limit);
        }

        tracing::info!(
            "Loaded {} user model limits from {:?}",
            self.user_limits.len(),
            path
        );
        Ok(())
    }

    /// Add a user limit override.
    pub fn add_limit(&mut self, limit: ModelLimit) {
        self.user_limits.insert(limit.model_pattern.clone(), limit);
    }

    /// Get limit for a model, with user overrides taking priority.
    ///
    /// Returns `None` if no matching limit is found.
    ///
    /// # Matching Strategy
    /// 1. Exact match (highest priority)
    /// 2. Model contains pattern (e.g., "gpt-4o-mini" contains "gpt-4o")
    /// 3. Pattern contains model (e.g., "gpt-4" contains "gpt")
    ///
    /// For partial matches, the longest (most specific) pattern wins.
    pub fn get(&self, model: &str) -> Option<ModelLimit> {
        // Exact user override match (highest priority).
        if let Some(limit) = self.user_limits.get(model) {
            return Some(limit.clone());
        }

        // Best partial match among user overrides. Longer (more specific)
        // patterns win for deterministic selection. There is no built-in table;
        // a miss returns None and the caller falls back to the global default.
        self.user_limits
            .iter()
            .filter(|(pattern, _)| model.contains(pattern.as_str()) || pattern.contains(model))
            .max_by_key(|(pattern, _)| pattern.len())
            .map(|(_, limit)| limit.clone())
    }

    /// Get limit for a model with fallback to default.
    pub fn get_or_default(&self, model: &str) -> ModelLimit {
        self.get(model).unwrap_or_else(default_model_limit)
    }

    /// Save current user limits to the configured file.
    ///
    /// No-op when the registry has no `config_path`.
    pub async fn save_user_config(&self) -> std::io::Result<()> {
        let Some(path) = self.config_path.clone() else {
            return Ok(());
        };

        // Ensure parent directory exists
        if let Some(parent) = path.parent() {
            tokio::fs::create_dir_all(parent).await?;
        }

        let limits: Vec<&ModelLimit> = self.user_limits.values().collect();
        let content = serde_json::to_string_pretty(&limits)
            .map_err(|e| std::io::Error::new(std::io::ErrorKind::InvalidData, e.to_string()))?;
        tokio::fs::write(&path, content).await?;

        Ok(())
    }

    /// List all user-defined limits.
    pub fn list_user_limits(&self) -> Vec<&ModelLimit> {
        self.user_limits.values().collect()
    }
}

impl Default for ModelLimitsRegistry {
    fn default() -> Self {
        Self::new()
    }
}

/// Get the default configuration file path.
///
/// Returns `{bamboo_data_dir}/model_limits.json`, given the Bamboo data dir.
///
/// The caller supplies the base directory so this crate stays free of any
/// infrastructure/filesystem-config dependency.
pub fn get_default_config_path(bamboo_dir: &std::path::Path) -> PathBuf {
    bamboo_dir.join("model_limits.json")
}

/// Load user model limits from the unified `config.json` `model_limits` value.
///
/// The caller extracts the raw `model_limits` JSON value (e.g. from
/// `config.extra.get("model_limits")`) and passes it here, keeping this crate
/// independent of the concrete `Config` type.
///
/// Returns:
/// - `Ok(None)` when `model_limits` is absent.
/// - `Ok(Some(vec))` when present and valid (including empty array).
/// - `Err(...)` when present but not a valid `Vec<ModelLimit>`.
pub fn load_model_limits_from_unified_config(
    raw_limits: Option<&Value>,
) -> Result<Option<Vec<ModelLimit>>, String> {
    let Some(raw_limits) = raw_limits else {
        return Ok(None);
    };

    if raw_limits.is_null() {
        return Ok(Some(Vec::new()));
    }

    match raw_limits {
        Value::Array(_) => serde_json::from_value::<Vec<ModelLimit>>(raw_limits.clone())
            .map(Some)
            .map_err(|error| format!("invalid config.model_limits format: {error}")),
        _ => Err("invalid config.model_limits format: expected array".to_string()),
    }
}

/// Create a token budget for a specific model.
///
/// This is a convenience function that creates a budget with appropriate defaults.
pub fn create_budget_for_model(model: &str, strategy: crate::BudgetStrategy) -> crate::TokenBudget {
    let registry = ModelLimitsRegistry::default();
    let limit = registry.get_or_default(model);

    crate::TokenBudget {
        max_context_tokens: limit.max_context_tokens,
        max_output_tokens: limit.get_max_output_tokens(),
        strategy,
        safety_margin: limit.get_safety_margin(),
        compression_trigger_percent: 85, // legacy — only used when working_reserve_tokens == 0
        compression_target_percent: 45,
        working_reserve_tokens: 50_000,
        fallback_trigger_percent: 75,
        prompt_cache_min_tool_output_chars: 1_200,
        prompt_cache_head_chars: 280,
        prompt_cache_tail_chars: 180,
        prompt_cache_recent_user_turns: 2,
        prompt_cache_recent_tool_chains: 2,
        max_tool_output_tokens: 0,
    }
}

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

    #[test]
    fn default_limit_is_1m_128k() {
        let limit = default_model_limit();
        assert_eq!(limit.model_pattern, DEFAULT_MODEL_PATTERN);
        assert_eq!(limit.max_context_tokens, 1_000_000);
        assert_eq!(limit.get_max_output_tokens(), 128_000);
    }

    #[test]
    fn is_default_limit_detects_no_op_overrides() {
        // A row pinned to exactly the default values (any pattern) is a no-op.
        let mut noop = ModelLimit::new("gpt-4o", DEFAULT_MAX_CONTEXT_TOKENS);
        noop.max_output_tokens = Some(DEFAULT_MAX_OUTPUT_TOKENS);
        assert!(is_default_limit(&noop));

        // The synthesized global default is itself a no-op override.
        assert!(is_default_limit(&default_model_limit()));

        // A different context window is a real override.
        let mut smaller = ModelLimit::new("gpt-4o", 128_000);
        smaller.max_output_tokens = Some(DEFAULT_MAX_OUTPUT_TOKENS);
        assert!(!is_default_limit(&smaller));

        // An explicit safety margin is a real override even at default size.
        let mut custom_margin = ModelLimit::new("gpt-4o", DEFAULT_MAX_CONTEXT_TOKENS);
        custom_margin.max_output_tokens = Some(DEFAULT_MAX_OUTPUT_TOKENS);
        custom_margin.safety_margin = Some(500);
        assert!(!is_default_limit(&custom_margin));
    }

    #[test]
    fn registry_returns_none_for_unknown_without_overrides() {
        // No built-in table: an unknown model with no user override has no match.
        let registry = ModelLimitsRegistry::new();
        assert!(registry.get("gpt-5.2-codex").is_none());
        assert!(registry.get("some-brand-new-model").is_none());
    }

    #[test]
    fn registry_returns_default_for_unknown() {
        let registry = ModelLimitsRegistry::new();
        let limit = registry.get_or_default("unknown-model-xyz");
        assert_eq!(limit.model_pattern, DEFAULT_MODEL_PATTERN);
        assert_eq!(limit.max_context_tokens, 1_000_000);
        assert_eq!(limit.get_max_output_tokens(), 128_000);
    }

    #[test]
    fn user_override_exact_match_wins() {
        let mut registry = ModelLimitsRegistry::new();
        registry.add_limit(ModelLimit::new("gpt-5.2-codex", 64_000)); // Override with smaller limit

        let limit = registry
            .get("gpt-5.2-codex")
            .expect("Should find overridden limit");
        assert_eq!(limit.max_context_tokens, 64_000);
    }

    #[test]
    fn user_override_partial_match_longest_wins() {
        let mut registry = ModelLimitsRegistry::new();
        registry.add_limit(ModelLimit::new("gpt-5", 111_000));
        registry.add_limit(ModelLimit::new("gpt-5.2-codex", 222_000));

        // "gpt-5.2-codex-preview" contains both patterns; the longest wins.
        let limit = registry
            .get("gpt-5.2-codex-preview")
            .expect("Should partial-match a user override");
        assert_eq!(limit.max_context_tokens, 222_000);
    }

    #[test]
    fn model_limit_calculates_default_output_tokens() {
        let limit = ModelLimit::new("test", 100_000);
        // Default is min(max_context / 4, 4096) = min(25000, 4096) = 4096
        assert_eq!(limit.get_max_output_tokens(), 4096);
    }

    #[test]
    fn model_limit_uses_custom_output_tokens() {
        let mut limit = ModelLimit::new("test", 100_000);
        limit.max_output_tokens = Some(8192);
        assert_eq!(limit.get_max_output_tokens(), 8192);
    }

    #[test]
    fn model_limit_calculates_small_context_output() {
        let limit = ModelLimit::new("test", 8_192);
        // Default is min(8192 / 4, 4096) = 2048
        assert_eq!(limit.get_max_output_tokens(), 2048);
    }

    #[test]
    fn unified_config_loader_returns_none_when_absent() {
        let loaded = load_model_limits_from_unified_config(None).expect("should parse");
        assert!(loaded.is_none());
    }

    #[test]
    fn unified_config_loader_reads_valid_model_limits() {
        let raw = serde_json::json!([
            {
                "model_pattern": "gpt-5.2-codex",
                "max_context_tokens": 64000,
                "max_output_tokens": 2048,
                "safety_margin": 512
            }
        ]);

        let loaded = load_model_limits_from_unified_config(Some(&raw))
            .expect("should parse")
            .expect("should exist");
        assert_eq!(loaded.len(), 1);
        assert_eq!(loaded[0].model_pattern, "gpt-5.2-codex");
        assert_eq!(loaded[0].max_context_tokens, 64_000);
        assert_eq!(loaded[0].max_output_tokens, Some(2048));
        assert_eq!(loaded[0].safety_margin, Some(512));
    }

    #[test]
    fn unified_config_loader_errors_on_invalid_shape() {
        let raw = serde_json::json!({"unexpected": true});
        let error = load_model_limits_from_unified_config(Some(&raw)).expect_err("should error");
        assert!(error.contains("expected array"));
    }

    #[test]
    fn safety_margin_scales_with_context_window() {
        // Small context → floor at DEFAULT_SAFETY_MARGIN (1000)
        let small = ModelLimit::new("test", 8_192);
        assert_eq!(small.get_safety_margin(), 1000);

        // Medium context → proportional
        let medium = ModelLimit::new("test", 200_000);
        assert_eq!(medium.get_safety_margin(), 2000);

        // Large context → proportional
        let large = ModelLimit::new("test", 1_050_000);
        assert_eq!(large.get_safety_margin(), 10_500);

        // Explicit override takes precedence
        let mut custom = ModelLimit::new("test", 200_000);
        custom.safety_margin = Some(500);
        assert_eq!(custom.get_safety_margin(), 500);
    }

    #[tokio::test]
    async fn persisted_overrides_drive_runtime_resolution() {
        // Integration: a `model_limits.json` on disk → registry load → resolve.
        let dir = tempfile::tempdir().expect("tempdir");
        let path = dir.path().join("model_limits.json");
        tokio::fs::write(
            &path,
            r#"[{"model_pattern":"gpt-4o","max_context_tokens":128000,"max_output_tokens":16384}]"#,
        )
        .await
        .expect("seed overrides");

        let mut registry = ModelLimitsRegistry::with_config_path(path);
        registry.load_user_config().await.expect("load user config");

        // Persisted override is applied at runtime.
        let gpt4o = registry.get("gpt-4o").expect("override present");
        assert_eq!(gpt4o.max_context_tokens, 128_000);
        assert_eq!(gpt4o.get_max_output_tokens(), 16_384);

        // Unknown model with no override falls back to the single global default.
        let unknown = registry.get_or_default("brand-new-frontier-model");
        assert_eq!(unknown.model_pattern, DEFAULT_MODEL_PATTERN);
        assert_eq!(unknown.max_context_tokens, 1_000_000);
        assert_eq!(unknown.get_max_output_tokens(), 128_000);
    }

    #[test]
    fn create_budget_for_model_uses_global_default_for_any_model() {
        let budget = create_budget_for_model("anything-at-all", crate::BudgetStrategy::default());
        assert_eq!(budget.max_context_tokens, 1_000_000);
        assert_eq!(budget.max_output_tokens, 128_000);
    }
}