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+# Vztor
+
+A high-performance key-value based vector database written in Zig.
+
+## Overview
+
+Vztor combines the power of [NMSLIB](https://github.com/nmslib/nmslib) for efficient approximate nearest neighbor search with [LMDB](https://github.com/LMDB/lmdb) for persistent key-value storage. It provides a simple API for storing, retrieving, and searching vectors with associated metadata.
+
+## Features
+
+- **Key-Value Storage**: Store vectors with associated data payloads
+- **Vector Search**: Fast approximate nearest neighbor search using HNSW algorithm
+- **Persistence**: Automatic persistence of both vectors and metadata to disk
+- **Sparse Vectors**: Support for sparse vector representations
+- **Auto-generated Keys**: Optional UUID generation for vector keys
+- **Batch Operations**: Efficient batch insert and retrieval operations
+
+## Requirements
+
+- Zig 0.16.0 or later
+
+Dependencies are managed via Zig's package manager:
+- [lmdbx-zig](https://github.com/theseyan/lmdbx-zig) - LMDBX wrapper for Zig
+- [nmslib-zig](https://github.com/B-R-P/nmslib-zig) - NMSLIB wrapper for Zig
+
+## Installation
+
+Add Vztor as a dependency in your `build.zig.zon`:
+
+```zig
+.dependencies = .{
+    .vztor = .{
+        .url = "https://github.com/B-R-P/Vztor/archive/refs/heads/main.tar.gz",
+        .hash = "...",
+    },
+},
+```
+
+## Usage
+
+### Initialize the Store
+
+```zig
+const std = @import("std");
+const VStore = @import("vztor").VStore;
+const nmslib = @import("nmslib");
+
+pub fn main() !void {
+    const allocator = std.heap.page_allocator;
+    
+    var store = try VStore.init(
+        allocator,
+        "my_database",           // Database path
+        "negdotprod_sparse",     // Space type
+        nmslib.DataType.SparseVector,
+        nmslib.DistType.Float,
+        1000,                    // Max readers
+    );
+    defer store.deinit() catch unreachable;
+}
+```
+
+### Insert Vectors
+
+```zig
+// Define sparse vectors
+const vectors = [_][]const nmslib.SparseElem{
+    &[_]nmslib.SparseElem{
+        .{ .id = 1, .value = 1.0 },
+        .{ .id = 5, .value = 2.0 },
+    },
+    &[_]nmslib.SparseElem{
+        .{ .id = 2, .value = 1.0 },
+        .{ .id = 10, .value = 3.0 },
+    },
+};
+
+// Associated data payloads
+const data = [_][]const u8{ "Vector 1", "Vector 2" };
+
+// Insert vectors (keys are auto-generated if null)
+const keys = try store.batchPut(&vectors, &data, null);
+```
+
+### Retrieve Vectors
+
+```zig
+// Get vector and data by key
+const result = try store.batchGet(keys[0]);
+std.debug.print("Data: {s}\n", .{result.data});
+```
+
+### Search Similar Vectors
+
+```zig
+// Search for k nearest neighbors
+const search_results = try store.search(query_vector, k);
+
+for (search_results) |result| {
+    std.debug.print("Key: {s}, Distance: {d}\n", .{ result.key, result.distance });
+}
+```
+
+### Persist to Disk
+
+```zig
+// Save the index and flush LMDBX to disk
+try store.save();
+```
+
+## API Reference
+
+### VStore
+
+#### `init(allocator, comptime db_path, space_type, vector_type, dist_type, max_readers)`
+
+Initializes a new VStore instance or loads an existing one from disk.
+
+- `allocator`: Memory allocator
+- `db_path`: Path to the database directory (comptime string)
+- `space_type`: Vector space type (e.g., "negdotprod_sparse")
+- `vector_type`: Type of vectors (e.g., `SparseVector`)
+- `dist_type`: Distance type (e.g., `Float`)
+- `max_readers`: Maximum number of concurrent readers
+
+#### `batchPut(vectors, data, keys)` (internal)
+
+Inserts multiple vectors with associated data.
+
+- `vectors`: Array of sparse vectors
+- `data`: Array of data payloads
+- `keys`: Optional array of keys (auto-generated if null)
+
+Returns: Array of keys for the inserted vectors
+
+#### `batchGet(key)` (internal)
+
+Retrieves a vector and its associated data by key.
+
+Returns: `getResult` struct with `vector` and `data` fields
+
+#### `search(vector, k)` (internal)
+
+Searches for the k nearest neighbors to the given vector.
+
+Returns: Array of `searchResult` structs with `key`, `data`, and `distance` fields
+
+#### `save()`
+
+Persists the index and flushes LMDBX to disk.
+
+#### `deinit()`
+
+Cleans up resources and closes the store. Returns an error union (`!void`).
+
+## Architecture
+
+Vztor uses a dual-storage architecture:
+
+1. **NMSLIB Index**: Stores vectors for fast approximate nearest neighbor search using the HNSW algorithm
+2. **LMDBX Database**: Stores key-value mappings and metadata for persistence
+
+Data is organized in three LMDBX databases:
+- `data`: Maps keys to data payloads
+- `index_to_key`: Maps numeric indices to key-position pairs
+- `metadata`: Stores configuration like random seeds
+
+## Building
+
+```bash
+zig build
+```
+
+## Testing
+
+```bash
+zig build test
+```
+
+## License
+
+See LICENSE file for details.