--- /dev/null
+import Foundation
+
+// import llama
+
+enum LlamaError: Error {
+ case couldNotInitializeContext
+}
+
+actor LlamaContext {
+ private var model: OpaquePointer
+ private var context: OpaquePointer
+ private var batch: llama_batch
+ private var tokens_list: [llama_token]
+
+ var n_len: Int32 = 512
+ var n_cur: Int32 = 0
+ var n_decode: Int32 = 0
+
+ init(model: OpaquePointer, context: OpaquePointer) {
+ self.model = model
+ self.context = context
+ self.tokens_list = []
+ self.batch = llama_batch_init(512, 0, 1)
+ }
+
+ deinit {
+ llama_free(context)
+ llama_free_model(model)
+ llama_backend_free()
+ }
+
+ static func createContext(path: String) throws -> LlamaContext {
+ llama_backend_init(false)
+ let model_params = llama_model_default_params()
+
+ let model = llama_load_model_from_file(path, model_params)
+ guard let model else {
+ print("Could not load model at \(path)")
+ throw LlamaError.couldNotInitializeContext
+ }
+ var ctx_params = llama_context_default_params()
+ ctx_params.seed = 1234
+ ctx_params.n_ctx = 2048
+ ctx_params.n_threads = 8
+ ctx_params.n_threads_batch = 8
+
+ let context = llama_new_context_with_model(model, ctx_params)
+ guard let context else {
+ print("Could not load context!")
+ throw LlamaError.couldNotInitializeContext
+ }
+
+ return LlamaContext(model: model, context: context)
+ }
+
+ func get_n_tokens() -> Int32 {
+ return batch.n_tokens;
+ }
+
+ func completion_init(text: String) {
+ print("attempting to complete \"\(text)\"")
+
+ tokens_list = tokenize(text: text, add_bos: true)
+
+ let n_ctx = llama_n_ctx(context)
+ let n_kv_req = tokens_list.count + (Int(n_len) - tokens_list.count)
+
+ print("\n n_len = \(n_len), n_ctx = \(n_ctx), n_kv_req = \(n_kv_req)")
+
+ if n_kv_req > n_ctx {
+ print("error: n_kv_req > n_ctx, the required KV cache size is not big enough")
+ }
+
+ for id in tokens_list {
+ print(token_to_piece(token: id))
+ }
+
+ // batch = llama_batch_init(512, 0) // done in init()
+ batch.n_tokens = Int32(tokens_list.count)
+
+ for i1 in 0..<batch.n_tokens {
+ let i = Int(i1)
+ batch.token[i] = tokens_list[i]
+ batch.pos[i] = i1
+ batch.n_seq_id[Int(i)] = 1
+ batch.seq_id[Int(i)]![0] = 0
+ batch.logits[i] = 0
+ }
+ batch.logits[Int(batch.n_tokens) - 1] = 1 // true
+
+ if llama_decode(context, batch) != 0 {
+ print("llama_decode() failed")
+ }
+
+ n_cur = batch.n_tokens
+ }
+
+ func completion_loop() -> String {
+ var new_token_id: llama_token = 0
+
+ let n_vocab = llama_n_vocab(model)
+ let logits = llama_get_logits_ith(context, batch.n_tokens - 1)
+
+ var candidates = Array<llama_token_data>()
+ candidates.reserveCapacity(Int(n_vocab))
+
+ for token_id in 0..<n_vocab {
+ candidates.append(llama_token_data(id: token_id, logit: logits![Int(token_id)], p: 0.0))
+ }
+ candidates.withUnsafeMutableBufferPointer() { buffer in
+ var candidates_p = llama_token_data_array(data: buffer.baseAddress, size: buffer.count, sorted: false)
+
+ new_token_id = llama_sample_token_greedy(context, &candidates_p)
+ }
+
+ if new_token_id == llama_token_eos(context) || n_cur == n_len {
+ print("\n")
+ return ""
+ }
+
+ let new_token_str = token_to_piece(token: new_token_id)
+ print(new_token_str)
+ // tokens_list.append(new_token_id)
+
+ batch.n_tokens = 0
+
+ batch.token[Int(batch.n_tokens)] = new_token_id
+ batch.pos[Int(batch.n_tokens)] = n_cur
+ batch.n_seq_id[Int(batch.n_tokens)] = 1
+ batch.seq_id[Int(batch.n_tokens)]![0] = 0
+ batch.logits[Int(batch.n_tokens)] = 1 // true
+ batch.n_tokens += 1
+
+ n_decode += 1
+
+ n_cur += 1
+
+ if llama_decode(context, batch) != 0 {
+ print("failed to evaluate llama!")
+ }
+
+ return new_token_str
+ }
+
+ func clear() {
+ tokens_list.removeAll()
+ }
+
+ private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
+ let n_tokens = text.count + (add_bos ? 1 : 0)
+ let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens)
+ let tokenCount = llama_tokenize(model, text, Int32(text.count), tokens, Int32(n_tokens), add_bos, false)
+
+ var swiftTokens: [llama_token] = []
+ for i in 0..<tokenCount {
+ swiftTokens.append(tokens[Int(i)])
+ }
+
+ tokens.deallocate()
+
+ return swiftTokens
+ }
+
+ private func token_to_piece(token: llama_token) -> String {
+ let result = UnsafeMutablePointer<Int8>.allocate(capacity: 8)
+ result.initialize(repeating: Int8(0), count: 8)
+
+ let _ = llama_token_to_piece(model, token, result, 8)
+
+ let resultStr = String(cString: result)
+
+ result.deallocate()
+
+ return resultStr
+ }
+}
--- /dev/null
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