// Package kvcache implements a paged KV cache with global prefix caching.
package kvcache

import (
	"crypto/sha256"
	"encoding/binary"
	"fmt"
	"sync"

	"makarna/pkg/backend/cpu"
	"makarna/pkg/backend/cuda"
	"makarna/pkg/tensor"
)

// BlockHash is the hash of a block's token content for prefix caching.
type BlockHash [32]byte

// KVBlock represents a single block of KV cache memory.
type KVBlock struct {
	ID       int
	K        tensor.Tensor // [blockSize, kvDim]
	V        tensor.Tensor // [blockSize, kvDim]
	pk       []float32
	pv       []float32
	Hash     *BlockHash // nil if not cached/committed
	RefCount int        // number of requests using this block
	Layer    int        // which layer this block belongs to
	GPU      int
}

// BlockPoolConfig configures the block pool.
type BlockPoolConfig struct {
	NumLayers  int
	NumKVHeads int
	HeadDim    int
	BlockSize  int
	NumBlocks  int // total blocks per layer
	Device     tensor.DeviceType
	GPU        int
	LayerGPUs  []int
	// LayerPlacements optionally overrides per-layer device placement.
	// If provided, it must have length NumLayers and may mix CPU/CUDA layers.
	// When set, Device/GPU/LayerGPUs are treated as defaults for layers that
	// don't specify a valid placement.
	LayerPlacements []tensor.DevicePlacement
	Preallocate     bool
}

// BlockPool manages a pool of KV cache blocks with prefix caching.
type BlockPool struct {
	cfg BlockPoolConfig

	mu sync.RWMutex

	// blocks[layer][blockID] = *KVBlock
	blocks [][]*KVBlock

	// Free block IDs per layer (LIFO for locality)
	freeBlocks [][]int

	// Hash → block mapping for prefix caching (per layer)
	// hashToBlock[layer][hash] = blockID
	hashToBlock []map[BlockHash]int

	// Stats
	stats PrefixCacheStats

	// CUDA preallocation: one contiguous buffer per layer for K and V.
	// When set, ensureAllocatedLocked creates block views into these buffers.
	kvDim           int
	kBase           []*cuda.Tensor
	vBase           []*cuda.Tensor
	layerGPUs       []int
	layerPlacements []tensor.DevicePlacement
}

// PrefixCacheStats tracks cache performance.
type PrefixCacheStats struct {
	Hits        int64
	Misses      int64
	Evictions   int64
	Allocations int64
}

// NewBlockPool creates a new block pool.
func NewBlockPool(cfg BlockPoolConfig) (*BlockPool, error) {
	if cfg.BlockSize <= 0 {
		cfg.BlockSize = 16
	}
	if cfg.NumBlocks <= 0 {
		cfg.NumBlocks = 1024
	}

	bp := &BlockPool{
		cfg:         cfg,
		blocks:      make([][]*KVBlock, cfg.NumLayers),
		freeBlocks:  make([][]int, cfg.NumLayers),
		hashToBlock: make([]map[BlockHash]int, cfg.NumLayers),
		kvDim:       cfg.NumKVHeads * cfg.HeadDim,
	}
	if len(cfg.LayerPlacements) != 0 {
		if len(cfg.LayerPlacements) != cfg.NumLayers {
			return nil, fmt.Errorf("LayerPlacements length %d != NumLayers %d", len(cfg.LayerPlacements), cfg.NumLayers)
		}
		bp.layerPlacements = make([]tensor.DevicePlacement, cfg.NumLayers)
		for i := range cfg.LayerPlacements {
			bp.layerPlacements[i] = cfg.LayerPlacements[i].Normalize()
		}
	}

	if cfg.Device == tensor.CUDA || bp.layerPlacements != nil {
		if len(cfg.LayerGPUs) != 0 && len(cfg.LayerGPUs) != cfg.NumLayers {
			return nil, fmt.Errorf("LayerGPUs length %d != NumLayers %d", len(cfg.LayerGPUs), cfg.NumLayers)
		}
		if len(cfg.LayerGPUs) == cfg.NumLayers {
			bp.layerGPUs = append([]int(nil), cfg.LayerGPUs...)
		} else {
			bp.layerGPUs = make([]int, cfg.NumLayers)
			for i := range bp.layerGPUs {
				bp.layerGPUs[i] = cfg.GPU
			}
		}
	}

	// Initialize block metadata. K/V tensors are allocated lazily on first use.
	for layer := 0; layer < cfg.NumLayers; layer++ {
		bp.blocks[layer] = make([]*KVBlock, cfg.NumBlocks)
		bp.freeBlocks[layer] = make([]int, 0, cfg.NumBlocks)
		bp.hashToBlock[layer] = make(map[BlockHash]int)

		for b := 0; b < cfg.NumBlocks; b++ {
			p := bp.LayerDevice(layer)
			gpu := p.GPU
			if p.Type != tensor.CUDA {
				gpu = -1
			}
			bp.blocks[layer][b] = &KVBlock{ID: b, Layer: layer, GPU: gpu}
			bp.freeBlocks[layer] = append(bp.freeBlocks[layer], b)
		}
	}

	if cfg.Preallocate && cuda.Available() {
		if err := bp.preallocateCUDA(); err != nil {
			bp.Free()
			return nil, err
		}
	}

	return bp, nil
}

func (bp *BlockPool) preallocateCUDA() error {
	if bp.kvDim <= 0 {
		return fmt.Errorf("invalid kvDim %d", bp.kvDim)
	}
	if bp.cfg.BlockSize <= 0 || bp.cfg.NumBlocks <= 0 {
		return fmt.Errorf("invalid block pool sizes: blockSize=%d numBlocks=%d", bp.cfg.BlockSize, bp.cfg.NumBlocks)
	}

	totalTokens := bp.cfg.NumBlocks * bp.cfg.BlockSize
	shape := tensor.Shape{totalTokens, bp.kvDim}

	bp.kBase = make([]*cuda.Tensor, bp.cfg.NumLayers)
	bp.vBase = make([]*cuda.Tensor, bp.cfg.NumLayers)

	for layer := 0; layer < bp.cfg.NumLayers; layer++ {
		p := bp.LayerDevice(layer)
		if p.Type != tensor.CUDA {
			continue
		}
		gpu := p.GPU
		k, err := cuda.NewTensor(shape, tensor.Float16, gpu)
		if err != nil {
			return fmt.Errorf("preallocate K layer %d: %w", layer, err)
		}
		v, err := cuda.NewTensor(shape, tensor.Float16, gpu)
		if err != nil {
			k.Free()
			return fmt.Errorf("preallocate V layer %d: %w", layer, err)
		}
		bp.kBase[layer] = k
		bp.vBase[layer] = v
	}

	return nil
}

func (bp *BlockPool) ensureAllocatedLocked(layer, blockID int) (*KVBlock, error) {
	if layer < 0 || layer >= len(bp.blocks) {
		return nil, fmt.Errorf("invalid layer %d", layer)
	}
	if blockID < 0 || blockID >= len(bp.blocks[layer]) {
		return nil, fmt.Errorf("invalid blockID %d", blockID)
	}
	block := bp.blocks[layer][blockID]
	if block == nil {
		p := bp.LayerDevice(layer)
		gpu := p.GPU
		if p.Type != tensor.CUDA {
			gpu = -1
		}
		block = &KVBlock{ID: blockID, Layer: layer, GPU: gpu}
		bp.blocks[layer][blockID] = block
	}
	if block.K != nil && block.V != nil {
		return block, nil
	}

	kvDim := bp.kvDim
	p := bp.LayerDevice(layer)
	if p.Type == tensor.CUDA && bp.kBase != nil && bp.vBase != nil {
		if layer < len(bp.kBase) && layer < len(bp.vBase) && bp.kBase[layer] != nil && bp.vBase[layer] != nil {
			elemSize := uintptr(tensor.Float16.Size())
			blockElems := uintptr(bp.cfg.BlockSize * kvDim)
			offsetBytes := uintptr(blockID) * blockElems * elemSize

			k, err := bp.kBase[layer].ViewAt(tensor.Shape{bp.cfg.BlockSize, kvDim}, offsetBytes)
			if err != nil {
				return nil, fmt.Errorf("create K view: %w", err)
			}
			v, err := bp.vBase[layer].ViewAt(tensor.Shape{bp.cfg.BlockSize, kvDim}, offsetBytes)
			if err != nil {
				return nil, fmt.Errorf("create V view: %w", err)
			}
			block.K = k
			block.V = v
		}
	}
	if block.K == nil || block.V == nil {
		k, v, err := allocateBlock(bp.cfg.BlockSize, kvDim, p.Type, p.GPU)
		if err != nil {
			return nil, err
		}
		block.K = k
		block.V = v
	}
	if p.Type == tensor.CPU {
		bufSize := bp.cfg.NumKVHeads * bp.cfg.BlockSize * bp.cfg.HeadDim
		block.pk = make([]float32, bufSize)
		block.pv = make([]float32, bufSize)
	}
	return block, nil
}

func allocateBlock(blockSize, kvDim int, device tensor.DeviceType, gpu int) (tensor.Tensor, tensor.Tensor, error) {
	shape := tensor.Shape{blockSize, kvDim}

	if device == tensor.CUDA && cuda.Available() {
		k, err := cuda.NewTensor(shape, tensor.Float16, gpu)
		if err != nil {
			return nil, nil, err
		}
		v, err := cuda.NewTensor(shape, tensor.Float16, gpu)
		if err != nil {
			return nil, nil, err
		}
		return k, v, nil
	}

	k, err := cpu.NewTensorU16(shape, tensor.Float16, nil)
	if err != nil {
		return nil, nil, err
	}
	v, err := cpu.NewTensorU16(shape, tensor.Float16, nil)
	if err != nil {
		return nil, nil, err
	}
	return k, v, nil
}

// ComputeBlockHash computes hash for a sequence of token IDs.
// This is used for prefix caching - same tokens = same hash.
func ComputeBlockHash(tokens []int, parentHash *BlockHash) BlockHash {
	h := sha256.New()
	if parentHash != nil {
		h.Write(parentHash[:])
	}
	buf := make([]byte, 4)
	for _, t := range tokens {
		binary.LittleEndian.PutUint32(buf, uint32(t))
		h.Write(buf)
	}
	var hash BlockHash
	copy(hash[:], h.Sum(nil))
	return hash
}

// ComputeBlockHashes computes hashes for all blocks in a token sequence.
func ComputeBlockHashes(tokens []int, blockSize int) []BlockHash {
	numBlocks := (len(tokens) + blockSize - 1) / blockSize
	hashes := make([]BlockHash, numBlocks)

	var parentHash *BlockHash
	for i := 0; i < numBlocks; i++ {
		start := i * blockSize
		end := start + blockSize
		if end > len(tokens) {
			end = len(tokens)
		}
		hashes[i] = ComputeBlockHash(tokens[start:end], parentHash)
		parentHash = &hashes[i]
	}
	return hashes
}

// FindCachedBlocks finds the longest prefix of blocks that are already cached.
// Returns block IDs and the number of tokens covered.
func (bp *BlockPool) FindCachedBlocks(layer int, hashes []BlockHash) ([]int, int) {
	bp.mu.RLock()
	defer bp.mu.RUnlock()

	if layer < 0 || layer >= len(bp.hashToBlock) {
		return nil, 0
	}

	cached := make([]int, 0, len(hashes))
	for _, hash := range hashes {
		if blockID, ok := bp.hashToBlock[layer][hash]; ok {
			cached = append(cached, blockID)
			bp.stats.Hits++
		} else {
			bp.stats.Misses++
			break // prefix caching requires contiguous hits
		}
	}

	return cached, len(cached) * bp.cfg.BlockSize
}

// AllocateBlocks allocates new blocks for a request.
// If needed, evicts least-recently-used cached blocks.
func (bp *BlockPool) AllocateBlocks(layer int, count int) ([]int, error) {
	bp.mu.Lock()
	defer bp.mu.Unlock()

	if layer < 0 || layer >= len(bp.freeBlocks) {
		return nil, fmt.Errorf("invalid layer %d", layer)
	}

	allocated := make([]int, 0, count)

	// First try free blocks
	for len(allocated) < count && len(bp.freeBlocks[layer]) > 0 {
		n := len(bp.freeBlocks[layer])
		blockID := bp.freeBlocks[layer][n-1]
		bp.freeBlocks[layer] = bp.freeBlocks[layer][:n-1]
		if _, err := bp.ensureAllocatedLocked(layer, blockID); err != nil {
			// Return blockID to free list and fail.
			bp.freeBlocks[layer] = append(bp.freeBlocks[layer], blockID)
			return allocated, fmt.Errorf("allocate block %d: %w", blockID, err)
		}
		allocated = append(allocated, blockID)
		bp.stats.Allocations++
	}

	// If still need more, evict cached blocks with refcount=0
	if len(allocated) < count {
		for hash, blockID := range bp.hashToBlock[layer] {
			block := bp.blocks[layer][blockID]
			if block.RefCount == 0 {
				// Evict
				delete(bp.hashToBlock[layer], hash)
				block.Hash = nil
				if _, err := bp.ensureAllocatedLocked(layer, blockID); err != nil {
					return allocated, fmt.Errorf("allocate evicted block %d: %w", blockID, err)
				}
				allocated = append(allocated, blockID)
				bp.stats.Evictions++
				bp.stats.Allocations++
				if len(allocated) >= count {
					break
				}
			}
		}
	}

	if len(allocated) < count {
		return allocated, fmt.Errorf("not enough blocks: need %d, got %d", count, len(allocated))
	}

	// Increment ref counts
	for _, blockID := range allocated {
		bp.blocks[layer][blockID].RefCount++
	}

	return allocated, nil
}

// TouchBlocks increments ref count for cached blocks being reused.
func (bp *BlockPool) TouchBlocks(layer int, blockIDs []int) {
	bp.mu.Lock()
	defer bp.mu.Unlock()

	for _, blockID := range blockIDs {
		if blockID >= 0 && blockID < len(bp.blocks[layer]) {
			bp.blocks[layer][blockID].RefCount++
		}
	}
}

// CacheBlocks registers blocks in the hash cache after they're computed.
func (bp *BlockPool) CacheBlocks(layer int, blockIDs []int, hashes []BlockHash) {
	bp.mu.Lock()
	defer bp.mu.Unlock()

	for i, blockID := range blockIDs {
		if i >= len(hashes) {
			break
		}
		block, err := bp.ensureAllocatedLocked(layer, blockID)
		if err != nil {
			continue
		}
		hash := hashes[i]
		block.Hash = &hash
		bp.hashToBlock[layer][hash] = blockID
	}
}

// FreeBlocks decrements ref counts; blocks with refcount=0 become eviction candidates.
func (bp *BlockPool) FreeBlocks(layer int, blockIDs []int) {
	bp.mu.Lock()
	defer bp.mu.Unlock()

	for _, blockID := range blockIDs {
		if blockID >= 0 && blockID < len(bp.blocks[layer]) {
			block := bp.blocks[layer][blockID]
			if block.RefCount > 0 {
				block.RefCount--
			}
			// Don't return to free list if cached (stays as eviction candidate)
			// Only truly free if not in hash cache
			if block.RefCount == 0 && block.Hash == nil {
				bp.freeBlocks[layer] = append(bp.freeBlocks[layer], blockID)
			}
		}
	}
}

// GetBlock returns a block by ID.
func (bp *BlockPool) GetBlock(layer, blockID int) *KVBlock {
	bp.mu.Lock()
	defer bp.mu.Unlock()
	block, err := bp.ensureAllocatedLocked(layer, blockID)
	if err != nil {
		return nil
	}
	return block
}

func (bp *BlockPool) LayerDevice(layer int) tensor.DevicePlacement {
	if bp == nil {
		return tensor.DevicePlacement{Type: tensor.CPU, GPU: -1}
	}
	if bp.layerPlacements != nil && layer >= 0 && layer < len(bp.layerPlacements) {
		p := bp.layerPlacements[layer].Normalize()
		// Defensive: normalize invalid CUDA GPU ids.
		if p.Type == tensor.CUDA && p.GPU < 0 {
			p.GPU = 0
		}
		return p
	}
	if bp.cfg.Device != tensor.CUDA {
		return tensor.DevicePlacement{Type: bp.cfg.Device, GPU: -1}
	}
	gpu := bp.cfg.GPU
	if bp.layerGPUs != nil && layer >= 0 && layer < len(bp.layerGPUs) {
		gpu = bp.layerGPUs[layer]
	}
	return tensor.DevicePlacement{Type: tensor.CUDA, GPU: gpu}
}

// Stats returns current cache statistics.
func (bp *BlockPool) Stats() PrefixCacheStats {
	bp.mu.RLock()
	defer bp.mu.RUnlock()
	return bp.stats
}

// NumFreeBlocks returns free block count for a layer.
func (bp *BlockPool) NumFreeBlocks(layer int) int {
	bp.mu.RLock()
	defer bp.mu.RUnlock()
	if layer < 0 || layer >= len(bp.freeBlocks) {
		return 0
	}
	return len(bp.freeBlocks[layer])
}

// Usage returns cache utilization (0.0 to 1.0).
func (bp *BlockPool) Usage() float64 {
	bp.mu.RLock()
	defer bp.mu.RUnlock()

	if bp.cfg.NumBlocks == 0 {
		return 0
	}
	// Average across layers
	totalFree := 0
	for _, free := range bp.freeBlocks {
		totalFree += len(free)
	}
	avgFree := float64(totalFree) / float64(len(bp.freeBlocks))
	return 1.0 - (avgFree / float64(bp.cfg.NumBlocks))
}

// Free releases all GPU memory.
func (bp *BlockPool) Free() {
	bp.mu.Lock()
	defer bp.mu.Unlock()

	// Free contiguous CUDA buffers first (if present).
	for i := range bp.kBase {
		if bp.kBase[i] != nil {
			bp.kBase[i].Free()
			bp.kBase[i] = nil
		}
	}
	for i := range bp.vBase {
		if bp.vBase[i] != nil {
			bp.vBase[i].Free()
			bp.vBase[i] = nil
		}
	}
	bp.kBase = nil
	bp.vBase = nil

	for _, layerBlocks := range bp.blocks {
		for _, block := range layerBlocks {
			if block == nil {
				continue
			}
			if ct, ok := block.K.(*cuda.Tensor); ok && ct != nil {
				ct.Free()
			}
			if ct, ok := block.V.(*cuda.Tensor); ok && ct != nil {
				ct.Free()
			}
		}
	}
	bp.blocks = nil
	bp.freeBlocks = nil
	bp.hashToBlock = nil
}