//! BM25 keyword search implementation.
//!
//! **BM25 (Best Matching 25)** is a probabilistic ranking function for full-text search.
//! It ranks documents based on term frequency and inverse document frequency with
//! length normalization.
//!
//! # Algorithm Overview
//!
//! **Score formula:**
//! ```text
//! BM25(q, d) = Σ IDF(qᵢ) · (f(qᵢ, d) · (k₁ + 1)) / (f(qᵢ, d) + k₁ · (1 - b + b · |d| / avgdl))
//!
//! Where:
//! - q: query terms
//! - d: document
//! - f(qᵢ, d): frequency of term qᵢ in document d
//! - |d|: document length (number of terms)
//! - avgdl: average document length in collection
//! - k₁: term saturation parameter (typical: 1.2)
//! - b: length normalization parameter (typical: 0.75)
//! - IDF(qᵢ) = log((N - n(qᵢ) + 0.5) / (n(qᵢ) + 0.5))
//!   - N: total documents
//!   - n(qᵢ): documents containing qᵢ
//! ```
//!
//! # Why BM25?
//!
//! | Feature | TF-IDF | BM25 | Improvement |
//! |---------|--------|------|-------------|
//! | Term saturation | Linear | Logarithmic | Prevents over-weighting of repeated terms |
//! | Length normalization | None | Tunable (b parameter) | Fair comparison of short/long docs |
//! | Parameter tuning | Fixed | k₁, b adjustable | Customizable per domain |
//! | Ranking quality | Good | **Better** | State-of-art for keyword search |
//!
//! # Use Cases
//!
//! - **Hybrid search**: Combine with vector search (score fusion)
//! - **Keyword filtering**: Pre-filter before expensive semantic search
//! - **Explainable results**: Users understand keyword matches
//! - **Exact matching**: Find documents with specific terms
//!
//! # Example
//!
//! ```rust,ignore
//! use percolate_rocks::index::bm25::{BM25Index, BM25Params};
//!
//! // Build index from documents
//! let docs = vec![
//!     "Rust is a systems programming language",
//!     "Python is great for data science",
//!     "Rust has zero-cost abstractions",
//! ];
//! let index = BM25Index::build(&docs, BM25Params::default())?;
//!
//! // Search
//! let results = index.search("Rust programming", 10)?;
//! // Returns: [(0, 5.2), (2, 3.1)] - doc_id and BM25 score
//! ```

mod inverted_index;
mod scorer;
mod tokenizer;

pub use inverted_index::InvertedIndex;
pub use scorer::{BM25Scorer, BM25Params};
pub use tokenizer::{Tokenizer, TokenizerConfig};

use crate::types::error::Result;
use std::collections::HashMap;

/// BM25 full-text search index.
#[derive(Debug)]
pub struct BM25Index {
    /// Inverted index (term -> posting list)
    inverted_index: InvertedIndex,

    /// BM25 scorer
    scorer: BM25Scorer,

    /// Tokenizer
    tokenizer: Tokenizer,

    /// Document lengths (for normalization)
    doc_lengths: Vec<usize>,

    /// Average document length
    avg_doc_length: f64,
}

impl BM25Index {
    /// Build a BM25 index from documents.
    ///
    /// # Arguments
    ///
    /// * `documents` - Document texts (one per doc_id)
    /// * `params` - BM25 parameters (k₁, b)
    ///
    /// # Returns
    ///
    /// BM25 index ready for search
    ///
    /// # Errors
    ///
    /// Returns error if documents are empty
    ///
    /// # Example
    ///
    /// ```rust,ignore
    /// let params = BM25Params::default();
    /// let index = BM25Index::build(&docs, params)?;
    /// ```
    pub fn build(documents: &[String], params: BM25Params) -> Result<Self> {
        todo!("Build inverted index and compute statistics")
    }

    /// Search for documents matching a query.
    ///
    /// # Arguments
    ///
    /// * `query` - Query text
    /// * `top_k` - Number of results to return
    ///
    /// # Returns
    ///
    /// Vector of (doc_id, score) pairs, sorted by score (descending)
    ///
    /// # Example
    ///
    /// ```rust,ignore
    /// let results = index.search("Rust systems programming", 10)?;
    /// assert!(results[0].1 > results[1].1);  // Scores descending
    /// ```
    pub fn search(&self, query: &str, top_k: usize) -> Result<Vec<(u32, f64)>> {
        todo!("Tokenize query, score documents, return top-k")
    }

    /// Add a new document to the index.
    ///
    /// # Arguments
    ///
    /// * `doc_id` - Document ID
    /// * `text` - Document text
    ///
    /// # Errors
    ///
    /// Returns error if doc_id already exists
    pub fn add_document(&mut self, doc_id: u32, text: &str) -> Result<()> {
        todo!("Tokenize, update inverted index, recalculate avgdl")
    }

    /// Remove a document from the index.
    ///
    /// # Arguments
    ///
    /// * `doc_id` - Document ID to remove
    ///
    /// # Errors
    ///
    /// Returns error if doc_id not found
    pub fn remove_document(&mut self, doc_id: u32) -> Result<()> {
        todo!("Remove from inverted index, update avgdl")
    }

    /// Get index statistics.
    ///
    /// # Returns
    ///
    /// Statistics including doc count, term count, avg doc length
    pub fn stats(&self) -> IndexStats {
        todo!("Compute index statistics")
    }

    /// Save index to RocksDB.
    ///
    /// Uses column family "bm25_index" for storage.
    ///
    /// # Arguments
    ///
    /// * `storage` - RocksDB storage handle
    ///
    /// # Errors
    ///
    /// Returns error if serialization or storage fails
    pub fn save(&self, storage: &crate::storage::Storage) -> Result<()> {
        todo!("Serialize inverted index to RocksDB")
    }

    /// Load index from RocksDB.
    ///
    /// # Arguments
    ///
    /// * `storage` - RocksDB storage handle
    ///
    /// # Returns
    ///
    /// BM25 index loaded from storage
    ///
    /// # Errors
    ///
    /// Returns error if index not found or corrupted
    pub fn load(storage: &crate::storage::Storage) -> Result<Self> {
        todo!("Deserialize inverted index from RocksDB")
    }
}

/// BM25 index statistics.
#[derive(Debug, Clone)]
pub struct IndexStats {
    /// Total number of documents
    pub num_docs: usize,

    /// Total number of unique terms
    pub num_terms: usize,

    /// Average document length (in tokens)
    pub avg_doc_length: f64,

    /// Total number of postings (term occurrences)
    pub num_postings: usize,
}

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

    #[test]
    fn test_build_index() {
        todo!("Test index construction")
    }

    #[test]
    fn test_search_returns_relevant_docs() {
        todo!("Test search returns docs with query terms")
    }

    #[test]
    fn test_search_ranking() {
        todo!("Test that docs with more term matches rank higher")
    }

    #[test]
    fn test_add_document() {
        todo!("Test adding documents to index")
    }

    #[test]
    fn test_remove_document() {
        todo!("Test removing documents from index")
    }

    #[test]
    fn test_save_load_roundtrip() {
        todo!("Test serialization to RocksDB")
    }
}
