const gpu = abi.gpu;

var backend = try gpu.selectBackend(allocator);
defer backend.deinit();

### **Prerequisites**
- **Zig 0.16.0-dev.1225+bf9082518** (GitHub Actions uses `mlugg/setup-zig@v2` pinned to this version)
- GPU drivers (optional, for acceleration)
- OpenAI API key (for AI agent features)

## 🤝 Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.

pub fn main() !void {
    var gpa = std.heap.GeneralPurposeAllocator(.{}){};
    const allocator = gpa.allocator();
    defer _ = gpa.deinit();

    // Create a 384-dimensional vector database
    var db = try abi.wdbx.createDatabase(allocator, .{ .dimension = 384 });
    defer db.deinit();

    // Insert vectors
    try db.insertVector(1, &embedding1);
    try db.insertVector(2, &embedding2);

    // Search for similar vectors
    const results = try db.searchVectors(&query_embedding, 10);
    defer allocator.free(results);

    for (results) |result| {
        std.debug.print("ID: {d}, Score: {d:.4}\n", .{ result.id, result.score });
    }
}

const abi = @import("abi");

pub fn main() !void {
    var gpa = std.heap.GeneralPurposeAllocator(.{}){};
    const allocator = gpa.allocator();
    defer _ = gpa.deinit();

    // Auto-selects best available backend (CUDA > Vulkan > Metal > CPU)
    var gpu = try abi.Gpu.init(allocator, .{
        .enable_profiling = true,
        .memory_mode = .automatic,
    });
    defer gpu.deinit();

    const a = try gpu.createBufferFromSlice(f32, &[_]f32{ 1, 2, 3, 4 }, .{});
    const b = try gpu.createBufferFromSlice(f32, &[_]f32{ 4, 3, 2, 1 }, .{});
    const result = try gpu.createBuffer(4 * @sizeOf(f32), .{});
    defer { gpu.destroyBuffer(a); gpu.destroyBuffer(b); gpu.destroyBuffer(result); }

// Add embeddings
const embedding = [_]f32{0.1, 0.2, 0.3, /* ... */};
const row_id = try db.addEmbedding(&embedding);

    var output: [4]f32 = undefined;
    try result.read(f32, &output);
    // output = { 5, 5, 5, 5 }
}

const abi = @import("abi");

pub fn main() !void {
    var gpa = std.heap.GeneralPurposeAllocator(.{}){};
    const allocator = gpa.allocator();
    defer _ = gpa.deinit();

    const config = abi.features.ai.TrainingConfig{
        .epochs = 10,
        .batch_size = 32,
        .learning_rate = 0.001,
        .optimizer = .adamw,
    };

    var result = try abi.features.ai.trainWithResult(allocator, config);
    defer result.deinit();

    std.debug.print("Final loss: {d:.6}\n", .{result.report.final_loss});
}