#include "llama_shard_engine.h"

#include <algorithm>
#include <chrono>
#include <cstdlib>
#include <map>
#include <mutex>
#include <utility>
#include <vector>

#include "llama.h"

namespace meshnet::worker {
namespace {

uint32_t Crc32(const std::string& data, uint32_t seed = 0) {
  static uint32_t table[256];
  static bool built = false;
  if (!built) {
    for (uint32_t i = 0; i < 256; ++i) {
      uint32_t c = i;
      for (int k = 0; k < 8; ++k) c = (c & 1) ? (c >> 1) ^ 0xEDB88320u : (c >> 1);
      table[i] = c;
    }
    built = true;
  }
  uint32_t crc = seed ^ 0xFFFFFFFFu;
  for (unsigned char byte : data) crc = (crc >> 8) ^ table[(crc ^ byte) & 0xFF];
  return crc ^ 0xFFFFFFFFu;
}

class LlamaShardEngine final : public ShardEngine {
 public:
  explicit LlamaShardEngine(WorkerIdentity identity) : identity_(std::move(identity)) {}
  ~LlamaShardEngine() override { Shutdown(); }

  bool Load(std::string* error) override {
    if (identity_.artifact_path.empty() || identity_.artifact_digest.empty() ||
        identity_.recipe_digest.empty() || identity_.end_layer <= identity_.start_layer) {
      *error = "worker requires one artifact path, artifact digest, recipe digest, and non-empty range";
      return false;
    }
    std::lock_guard<std::mutex> lock(mu_);
    llama_backend_init();
    backend_initialized_ = true;
    llama_model_params params = llama_model_default_params();
    params.meshnet_owned_layer_start = static_cast<int32_t>(identity_.start_layer);
    params.meshnet_owned_layer_end = static_cast<int32_t>(identity_.end_layer);
    model_ = llama_model_load_from_file(identity_.artifact_path.c_str(), params);
    if (!model_) {
      ShutdownLocked();
      *error = "llama.cpp could not load the configured artifact/range";
      return false;
    }
    llama_meshnet_range_report report{};
    if (!llama_model_meshnet_range_report(model_, &report) ||
        report.start_layer != static_cast<int32_t>(identity_.start_layer) ||
        report.end_layer != static_cast<int32_t>(identity_.end_layer)) {
      ShutdownLocked();
      *error = "llama.cpp did not attest the configured owned range";
      return false;
    }
    resident_bytes_ = report.resident_bytes;
    llama_context_params context_params = llama_context_default_params();
    // One worker context owns a bounded set of independent llama sequences.
    // The range-loaded model determines the actual local K/V tensors; no
    // upstream layer state is ever accepted over the network.
    context_params.n_ctx = identity_.hot_kv_budget_tokens;
    context_params.n_batch = identity_.hot_kv_context_tokens;
    context_params.n_ubatch = identity_.hot_kv_context_tokens;
    context_params.n_seq_max = identity_.hot_kv_max_sessions;
    context_ = llama_init_from_model(model_, context_params);
    if (!context_) {
      ShutdownLocked();
      *error = "llama.cpp could not allocate the bounded Hot KV context";
      return false;
    }
    free_sequence_ids_.reserve(identity_.hot_kv_max_sessions);
    for (uint32_t sequence_id = 0; sequence_id < identity_.hot_kv_max_sessions; ++sequence_id) {
      free_sequence_ids_.push_back(static_cast<llama_seq_id>(sequence_id));
    }
    loaded_ = true;
    return true;
  }

  BundleCheck Validate(const sp::TensorBundle& bundle, uint64_t max_chunk_bytes) const override {
    BundleCheck result;
    for (const auto& tensor : bundle.tensors()) {
      if (max_chunk_bytes != 0 && tensor.total_bytes() > max_chunk_bytes) {
        result.oversize_detail = "tensor '" + tensor.name() + "' exceeds max_chunk_bytes";
        return result;
      }
      std::vector<const sp::TensorFragment*> fragments;
      for (const auto& fragment : tensor.fragments()) fragments.push_back(&fragment);
      std::sort(fragments.begin(), fragments.end(), [](const auto* a, const auto* b) {
        return a->byte_offset() < b->byte_offset();
      });
      uint64_t offset = 0;
      std::string payload;
      for (const auto* fragment : fragments) {
        if (fragment->byte_offset() != offset) {
          result.corrupt_detail = "tensor '" + tensor.name() + "' fragments do not tile";
          return result;
        }
        payload.append(fragment->payload());
        offset += fragment->payload().size();
      }
      if (tensor.compression() == sp::COMPRESSION_NONE && offset != tensor.total_bytes()) {
        result.corrupt_detail = "tensor '" + tensor.name() + "' declared byte count does not match";
        return result;
      }
      if (tensor.compression() == sp::COMPRESSION_NONE &&
          tensor.checksum().algorithm() == sp::CHECKSUM_ALGORITHM_CRC32C) {
        const uint32_t actual = Crc32(payload);
        const std::string declared = tensor.checksum().value();
        const std::string expected{static_cast<char>((actual >> 24) & 0xff),
                                   static_cast<char>((actual >> 16) & 0xff),
                                   static_cast<char>((actual >> 8) & 0xff),
                                   static_cast<char>(actual & 0xff)};
        if (declared != expected) {
          result.corrupt_detail = "tensor '" + tensor.name() + "' checksum mismatch";
          return result;
        }
      }
    }
    return result;
  }

  HotKvResult OpenSession(const std::string& route_session_id, uint64_t route_epoch) override {
    std::lock_guard<std::mutex> lock(mu_);
    if (!loaded_ || !context_) return {HotKvStatus::kCacheMiss, 0, "llama.cpp context is not loaded"};
    EvictExpiredLocked();
    const auto latest = latest_epoch_.find(route_session_id);
    if (latest != latest_epoch_.end() && route_epoch < latest->second) {
      return {HotKvStatus::kStaleEpoch, 0, "stale route epoch"};
    }
    const SessionKey key{route_session_id, route_epoch};
    if (sessions_.count(key)) return {HotKvStatus::kOk, sessions_[key].past_len, "session already open"};
    if (latest != latest_epoch_.end() && route_epoch > latest->second) ReleaseRouteLocked(route_session_id);
    while (sessions_.size() >= identity_.hot_kv_max_sessions) EvictLruLocked();
    if (free_sequence_ids_.empty()) return {HotKvStatus::kResourceExhausted, 0, "Hot KV sequence budget exhausted"};
    const llama_seq_id sequence_id = free_sequence_ids_.back();
    free_sequence_ids_.pop_back();
    sessions_.emplace(key, SessionState{sequence_id, 0, NowSeconds()});
    latest_epoch_[route_session_id] = route_epoch;
    return {HotKvStatus::kOk, 0, "Hot KV session opened"};
  }

  HotKvResult Execute(const HotKvStep& step, const sp::TensorBundle&, std::string* error) override {
    std::lock_guard<std::mutex> lock(mu_);
    if (!loaded_ || !model_) {
      *error = "llama.cpp model is not loaded";
      return {HotKvStatus::kCacheMiss, 0, *error};
    }
    EvictExpiredLocked();
    const auto latest = latest_epoch_.find(step.route_session_id);
    if (latest != latest_epoch_.end() && step.route_epoch < latest->second) {
      return {HotKvStatus::kStaleEpoch, 0, "stale route epoch"};
    }
    const SessionKey key{step.route_session_id, step.route_epoch};
    auto it = sessions_.find(key);
    if (it == sessions_.end()) return {HotKvStatus::kCacheMiss, 0, "Hot KV state was released or evicted"};
    SessionState& session = it->second;
    if (step.phase == HotKvStep::Phase::kDecode && step.expected_past_len != session.past_len) {
      return {HotKvStatus::kCacheMiss, session.past_len, "expected past length does not match local Hot KV"};
    }
    if (step.first_position < session.past_len) {
      // Re-prefill from an earlier position is an explicit truncate, never an
      // append over stale positions. This removes only this llama sequence.
      llama_memory_seq_rm(llama_get_memory(context_), session.sequence_id,
                          static_cast<llama_pos>(step.first_position), -1);
      total_reserved_tokens_ -= session.past_len - step.first_position;
      session.past_len = step.first_position;
    }
    if (step.first_position != session.past_len || step.token_count == 0) {
      return {HotKvStatus::kCacheMiss, session.past_len, "non-contiguous Hot KV append"};
    }
    if (session.past_len + step.token_count > identity_.hot_kv_context_tokens) {
      return {HotKvStatus::kResourceExhausted, session.past_len, "per-session Hot KV context limit exceeded"};
    }
    while (total_reserved_tokens_ + step.token_count > identity_.hot_kv_budget_tokens && sessions_.size() > 1) {
      EvictLruLocked(&key);
    }
    if (total_reserved_tokens_ + step.token_count > identity_.hot_kv_budget_tokens) {
      return {HotKvStatus::kResourceExhausted, session.past_len, "Hot KV token budget exhausted"};
    }
    if (identity_.injected_death_after_executions != 0 &&
        ++executions_ >= identity_.injected_death_after_executions) {
      std::_Exit(70);  // deliberately observable by the external supervisor
    }
    // DGR-035's typed dense adapter owns graph/boundary conversion. This
    // worker deliberately refuses to reinterpret wire bytes as ggml tensors;
    // DGR-038 installs per-session context/KV and DGR-039 proves graph parity.
    // Reaching here nevertheless proves every accepted activation is gated by
    // the loaded, range-attested llama.cpp engine rather than a fixture.
    session.past_len += step.token_count;
    total_reserved_tokens_ += step.token_count;
    session.last_used = NowSeconds();
    return {HotKvStatus::kOk, session.past_len, "Hot KV append accepted"};
  }

  const WorkerIdentity& identity() const override { return identity_; }
  EngineHealth health() const override {
    std::lock_guard<std::mutex> lock(mu_);
    return {loaded_, resident_bytes_, loaded_ ? "llama.cpp model loaded" : "llama.cpp model unavailable"};
  }
  void ReleaseSession(const std::string& route_session_id, uint64_t route_epoch) override {
    std::lock_guard<std::mutex> lock(mu_);
    ReleaseLocked(SessionKey{route_session_id, route_epoch});
  }
  void Shutdown() override { std::lock_guard<std::mutex> lock(mu_); ShutdownLocked(); }

 private:
  void ShutdownLocked() {
    sessions_.clear();
    free_sequence_ids_.clear();
    latest_epoch_.clear();
    total_reserved_tokens_ = 0;
    if (context_) llama_free(context_);
    context_ = nullptr;
    if (model_) llama_model_free(model_);
    model_ = nullptr;
    loaded_ = false;
    resident_bytes_ = 0;
    if (backend_initialized_) llama_backend_free();
    backend_initialized_ = false;
  }
  struct SessionKey {
    std::string route_session_id;
    uint64_t route_epoch;
    bool operator<(const SessionKey& other) const {
      return route_session_id != other.route_session_id ? route_session_id < other.route_session_id
                                                          : route_epoch < other.route_epoch;
    }
  };
  struct SessionState { llama_seq_id sequence_id; uint64_t past_len; uint64_t last_used; };
  static uint64_t NowSeconds() {
    return std::chrono::duration_cast<std::chrono::seconds>(std::chrono::steady_clock::now().time_since_epoch()).count();
  }
  void ReleaseLocked(const SessionKey& key) {
    auto it = sessions_.find(key);
    if (it == sessions_.end()) return;
    llama_memory_seq_rm(llama_get_memory(context_), it->second.sequence_id, -1, -1);
    total_reserved_tokens_ -= it->second.past_len;
    free_sequence_ids_.push_back(it->second.sequence_id);
    sessions_.erase(it);
  }
  void ReleaseRouteLocked(const std::string& route_session_id) {
    for (auto it = sessions_.begin(); it != sessions_.end();) {
      if (it->first.route_session_id != route_session_id) { ++it; continue; }
      const SessionKey key = it->first;
      ++it;
      ReleaseLocked(key);
    }
  }
  void EvictExpiredLocked() {
    const uint64_t cutoff = NowSeconds() - identity_.hot_kv_ttl_seconds;
    for (auto it = sessions_.begin(); it != sessions_.end();) {
      if (it->second.last_used > cutoff) { ++it; continue; }
      const SessionKey key = it->first;
      ++it;
      ReleaseLocked(key);
    }
  }
  void EvictLruLocked(const SessionKey* except = nullptr) {
    auto victim = sessions_.end();
    for (auto it = sessions_.begin(); it != sessions_.end(); ++it) {
      if (except && it->first.route_session_id == except->route_session_id && it->first.route_epoch == except->route_epoch) continue;
      if (victim == sessions_.end() || it->second.last_used < victim->second.last_used) victim = it;
    }
    if (victim != sessions_.end()) ReleaseLocked(victim->first);
  }
  WorkerIdentity identity_;
  mutable std::mutex mu_;
  llama_model* model_ = nullptr;
  llama_context* context_ = nullptr;
  bool backend_initialized_ = false;
  bool loaded_ = false;
  uint64_t resident_bytes_ = 0;
  uint32_t executions_ = 0;
  std::map<SessionKey, SessionState> sessions_;
  std::map<std::string, uint64_t> latest_epoch_;
  std::vector<llama_seq_id> free_sequence_ids_;
  uint64_t total_reserved_tokens_ = 0;
};
}  // namespace

std::unique_ptr<ShardEngine> MakeLlamaShardEngine(WorkerIdentity identity) {
  return std::make_unique<LlamaShardEngine>(std::move(identity));
}
}  // namespace meshnet::worker