sapphire-retrieve 0.10.1

//! Unified retrieve store trait.
//!
//! [`RetrieveStore`] is a **synchronous** trait that abstracts over all
//! storage backends (SQLite-vec, LanceDB, and future backends such as
//! SurrealDB).
//!
//! All methods are **synchronous**.  Async backends must wrap their async
//! operations inside a dedicated Tokio runtime.

use std::collections::HashMap;
use std::path::Path;

use crate::{embed::Embedder, error::Result, vector_store::VecInfo};

// ── query structs ────────────────────────────────────────────────────────────

/// Full-text search query.
#[derive(Debug, Clone)]
pub struct FtsQuery<'a> {
    /// Query text.
    pub query: &'a str,
    /// Maximum number of file-level results.
    pub limit: usize,
    /// When set, restrict results to documents whose `path` starts with this
    /// absolute prefix.
    pub path_prefix: Option<&'a Path>,
}

impl<'a> FtsQuery<'a> {
    pub fn new(query: &'a str) -> Self {
        Self {
            query,
            limit: 10,
            path_prefix: None,
        }
    }

    pub fn limit(mut self, n: usize) -> Self {
        self.limit = n;
        self
    }

    pub fn path_prefix(mut self, p: &'a Path) -> Self {
        self.path_prefix = Some(p);
        self
    }
}

/// Vector (semantic) similarity query.
///
/// The backend embeds `query` using `embedder` internally, so callers don't
/// need to pre-compute the vector.
pub struct VectorQuery<'a> {
    pub query: &'a str,
    pub embedder: &'a dyn Embedder,
    pub limit: usize,
    pub path_prefix: Option<&'a Path>,
}

impl<'a> VectorQuery<'a> {
    pub fn new(query: &'a str, embedder: &'a dyn Embedder) -> Self {
        Self {
            query,
            embedder,
            limit: 10,
            path_prefix: None,
        }
    }

    pub fn limit(mut self, n: usize) -> Self {
        self.limit = n;
        self
    }

    pub fn path_prefix(mut self, p: &'a Path) -> Self {
        self.path_prefix = Some(p);
        self
    }
}

impl std::fmt::Debug for VectorQuery<'_> {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("VectorQuery")
            .field("query", &self.query)
            .field("limit", &self.limit)
            .field("path_prefix", &self.path_prefix)
            .finish_non_exhaustive()
    }
}

/// Hybrid (FTS + vector) search query, merged via Reciprocal Rank Fusion.
///
/// When `embedder` is `None`, falls back to FTS-only.
pub struct HybridQuery<'a> {
    pub query: &'a str,
    pub embedder: Option<&'a dyn Embedder>,
    pub limit: usize,
    pub path_prefix: Option<&'a Path>,
    pub rrf_k: f64,
    pub weight_fts: f64,
    pub weight_sem: f64,
}

impl<'a> HybridQuery<'a> {
    pub fn new(query: &'a str) -> Self {
        Self {
            query,
            embedder: None,
            limit: 10,
            path_prefix: None,
            rrf_k: 60.0,
            weight_fts: 1.0,
            weight_sem: 1.0,
        }
    }

    pub fn embedder(mut self, e: &'a dyn Embedder) -> Self {
        self.embedder = Some(e);
        self
    }

    pub fn limit(mut self, n: usize) -> Self {
        self.limit = n;
        self
    }

    pub fn path_prefix(mut self, p: &'a Path) -> Self {
        self.path_prefix = Some(p);
        self
    }

    pub fn rrf_k(mut self, k: f64) -> Self {
        self.rrf_k = k;
        self
    }

    pub fn weight_fts(mut self, w: f64) -> Self {
        self.weight_fts = w;
        self
    }

    pub fn weight_sem(mut self, w: f64) -> Self {
        self.weight_sem = w;
        self
    }
}

impl std::fmt::Debug for HybridQuery<'_> {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("HybridQuery")
            .field("query", &self.query)
            .field("limit", &self.limit)
            .field("path_prefix", &self.path_prefix)
            .field("rrf_k", &self.rrf_k)
            .field("weight_fts", &self.weight_fts)
            .field("weight_sem", &self.weight_sem)
            .finish_non_exhaustive()
    }
}

// ── shared domain types ───────────────────────────────────────────────────────

/// A document to be indexed for FTS and/or vector search.
#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
pub struct Document {
    /// Stable identifier assigned by the caller.
    pub id: i64,
    /// Full body text; used only as input to the chunker when `chunks` is `None`.
    /// Not persisted to the database.
    pub body: String,
    /// Absolute file path (shown in search results).
    pub path: String,
    /// Pre-computed text chunks with source-location ranges.
    ///
    /// Each element is `(line_start, line_end, embed_text)` where the line
    /// values are 0-based and inclusive.  When `None`, the storage backend
    /// falls back to auto-chunking `body` via [`crate::chunker::chunk_document`].
    #[serde(default, skip_serializing_if = "Option::is_none")]
    pub chunks: Option<Vec<(usize, usize, String)>>,
}

/// A single chunk match inside a [`FileSearchResult`].
#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
pub struct ChunkHit {
    /// First source line of the matched chunk (inclusive, 0-based).
    pub line_start: usize,
    /// Last source line of the matched chunk (inclusive, 0-based).
    pub line_end: usize,
    /// The chunk's extracted text.
    pub text: String,
    /// Per-chunk score: FTS rank (lower = better), vector L2 distance
    /// (lower = better), or RRF score (higher = better), depending on the
    /// search mode.
    pub score: f64,
}

/// File-level search result with one or more matched chunks.
#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
pub struct FileSearchResult {
    pub id: i64,
    pub path: String,
    /// Representative score for the file (best chunk for FTS/vector,
    /// aggregated RRF score for hybrid).
    pub score: f64,
    /// Matched chunks within this file, ordered by per-chunk score.
    pub chunks: Vec<ChunkHit>,
}

// ── trait ─────────────────────────────────────────────────────────────────────

/// Unified synchronous interface for retrieve storage backends.
///
/// Built-in implementations:
/// - [`SqliteStore`](crate::sqlite_store::SqliteStore) — SQLite-vec backend.
/// - [`LanceDbBackend`](crate::lancedb_store::LanceDbBackend) — LanceDB backend
///   (requires the `lancedb-store` feature).
pub trait RetrieveStore: Send + Sync {
    // ── file tracking ──────────────────────────────────────────────────────────

    fn file_mtimes(&self) -> Result<HashMap<String, i64>>;
    fn upsert_file(&self, path: &str, mtime: i64) -> Result<()>;
    fn remove_file(&self, path: &str) -> Result<()>;
    fn file_count(&self) -> Result<u64>;

    // ── document management ────────────────────────────────────────────────────

    fn upsert_document(&self, doc: &Document) -> Result<()>;
    fn remove_document(&self, id: i64) -> Result<()>;

    /// Rebuild the FTS index.  Call after a batch of upserts.
    fn rebuild_fts(&self) -> Result<()>;

    fn document_ids(&self) -> Result<Vec<i64>>;
    fn document_count(&self) -> Result<u64>;

    // ── embedding ──────────────────────────────────────────────────────────────

    /// Generate and store embeddings for all pending chunks.
    fn embed_pending(
        &self,
        embedder: &dyn Embedder,
        on_progress: &dyn Fn(usize, usize),
    ) -> Result<usize>;

    fn vec_info(&self) -> Result<VecInfo>;

    // ── search ─────────────────────────────────────────────────────────────────

    /// Full-text search at chunk granularity, grouped per file.
    fn search_fts(&self, q: &FtsQuery<'_>) -> Result<Vec<FileSearchResult>>;

    /// Semantic (vector) search at chunk granularity, grouped per file.
    ///
    /// The backend embeds `q.query` using `q.embedder` internally.
    fn search_similar(&self, q: &VectorQuery<'_>) -> Result<Vec<FileSearchResult>>;

    /// Hybrid search: runs FTS + vector and merges via RRF (default impl).
    ///
    /// If `q.embedder` is `None`, falls back to FTS-only.
    fn search_hybrid(&self, q: &HybridQuery<'_>) -> Result<Vec<FileSearchResult>> {
        crate::db::default_hybrid(self, q)
    }
}