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- 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]
- /// This variable is used to store temporarily invalid cchars
- private var temporary_invalid_cchars: [CChar]
- 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)
- self.temporary_invalid_cchars = []
- }
- 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)
- temporary_invalid_cchars = []
- 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(String(cString: token_to_piece(token: id) + [0]))
- }
- // 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")
- let new_token_str = String(cString: temporary_invalid_cchars + [0])
- temporary_invalid_cchars.removeAll()
- return new_token_str
- }
- let new_token_cchars = token_to_piece(token: new_token_id)
- temporary_invalid_cchars.append(contentsOf: new_token_cchars)
- let new_token_str: String
- if let string = String(validatingUTF8: temporary_invalid_cchars + [0]) {
- temporary_invalid_cchars.removeAll()
- new_token_str = string
- } else if (0 ..< temporary_invalid_cchars.count).contains(where: {$0 != 0 && String(validatingUTF8: Array(temporary_invalid_cchars.suffix($0)) + [0]) != nil}) {
- // in this case, at least the suffix of the temporary_invalid_cchars can be interpreted as UTF8 string
- let string = String(cString: temporary_invalid_cchars + [0])
- temporary_invalid_cchars.removeAll()
- new_token_str = string
- } else {
- new_token_str = ""
- }
- 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()
- temporary_invalid_cchars.removeAll()
- }
- private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
- let utf8Count = text.utf8.count
- let n_tokens = utf8Count + (add_bos ? 1 : 0)
- let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens)
- let tokenCount = llama_tokenize(model, text, Int32(utf8Count), 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
- }
- /// - note: The result does not contain null-terminator
- private func token_to_piece(token: llama_token) -> [CChar] {
- let result = UnsafeMutablePointer<Int8>.allocate(capacity: 8)
- result.initialize(repeating: Int8(0), count: 8)
- defer {
- result.deallocate()
- }
- let nTokens = llama_token_to_piece(model, token, result, 8)
- if nTokens < 0 {
- let newResult = UnsafeMutablePointer<Int8>.allocate(capacity: Int(-nTokens))
- newResult.initialize(repeating: Int8(0), count: Int(-nTokens))
- defer {
- newResult.deallocate()
- }
- let nNewTokens = llama_token_to_piece(model, token, newResult, -nTokens)
- let bufferPointer = UnsafeBufferPointer(start: newResult, count: Int(nNewTokens))
- return Array(bufferPointer)
- } else {
- let bufferPointer = UnsafeBufferPointer(start: result, count: Int(nTokens))
- return Array(bufferPointer)
- }
- }
- }
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