mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 13:58:46 +01:00
209 lines
6.9 KiB
Swift
209 lines
6.9 KiB
Swift
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)
|
|
}
|
|
}
|
|
}
|