llama.go 10 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409
  1. package llama
  2. /*
  3. #cgo CPPFLAGS: -O3 -Wall -Wextra -Werror -Wno-unused-function -Wno-unused-variable -DNDEBUG -DGGML_USE_K_QUANTS
  4. #cgo CXXFLAGS: -std=gnu++11
  5. #cgo darwin CPPFLAGS: -DGGML_USE_ACCELERATE -DGGML_USE_METAL -DGGML_METAL_NDEBUG
  6. #cgo darwin LDFLAGS: -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
  7. #include <stdlib.h>
  8. #include "llama.h"
  9. struct llama_sample_options
  10. {
  11. float repeat_penalty;
  12. float frequency_penalty;
  13. float presence_penalty;
  14. float temperature;
  15. int32_t top_k;
  16. float top_p;
  17. float tfs_z;
  18. float typical_p;
  19. int mirostat;
  20. float mirostat_tau;
  21. float mirostat_eta;
  22. bool penalize_newline;
  23. };
  24. llama_token llama_sample(
  25. struct llama_context *ctx,
  26. struct llama_token_data *candidates,
  27. size_t n_candidates,
  28. const llama_token *last_tokens,
  29. size_t n_last_tokens,
  30. struct llama_sample_options *opts)
  31. {
  32. llama_token_data_array candidates_p = {
  33. candidates,
  34. n_candidates,
  35. false,
  36. };
  37. struct llama_token_data newline = candidates_p.data[llama_token_nl()];
  38. llama_sample_repetition_penalty(
  39. ctx, &candidates_p,
  40. last_tokens, n_last_tokens,
  41. opts->repeat_penalty);
  42. llama_sample_frequency_and_presence_penalties(
  43. ctx, &candidates_p,
  44. last_tokens, n_last_tokens,
  45. opts->frequency_penalty, opts->presence_penalty);
  46. if (!opts->penalize_newline) {
  47. candidates_p.data[llama_token_nl()] = newline;
  48. }
  49. if (opts->temperature <= 0) {
  50. return llama_sample_token_greedy(ctx, &candidates_p);
  51. }
  52. if (opts->mirostat == 1) {
  53. int mirostat_m = 100;
  54. float mirostat_mu = 2.0f * opts->mirostat_tau;
  55. llama_sample_temperature(ctx, &candidates_p, opts->temperature);
  56. return llama_sample_token_mirostat(
  57. ctx, &candidates_p,
  58. opts->mirostat_tau, opts->mirostat_eta,
  59. mirostat_m, &mirostat_mu);
  60. } else if (opts->mirostat == 2) {
  61. float mirostat_mu = 2.0f * opts->mirostat_tau;
  62. llama_sample_temperature(ctx, &candidates_p, opts->temperature);
  63. return llama_sample_token_mirostat_v2(
  64. ctx, &candidates_p,
  65. opts->mirostat_tau, opts->mirostat_eta,
  66. &mirostat_mu);
  67. } else {
  68. llama_sample_top_k(ctx, &candidates_p, opts->top_k, 1);
  69. llama_sample_tail_free(ctx, &candidates_p, opts->tfs_z, 1);
  70. llama_sample_typical(ctx, &candidates_p, opts->typical_p, 1);
  71. llama_sample_top_p(ctx, &candidates_p, opts->top_p, 1);
  72. llama_sample_temperature(ctx, &candidates_p, opts->temperature);
  73. return llama_sample_token(ctx, &candidates_p);
  74. }
  75. }
  76. */
  77. import "C"
  78. import (
  79. "bytes"
  80. "errors"
  81. "fmt"
  82. "io"
  83. "log"
  84. "os"
  85. "strings"
  86. "sync"
  87. "unicode/utf8"
  88. "unsafe"
  89. "github.com/jmorganca/ollama/api"
  90. )
  91. type LLM struct {
  92. params *C.struct_llama_context_params
  93. model *C.struct_llama_model
  94. ctx *C.struct_llama_context
  95. last []C.llama_token
  96. embd []C.llama_token
  97. cursor int
  98. mu sync.Mutex
  99. gc bool
  100. api.Options
  101. }
  102. func New(model string, opts api.Options) (*LLM, error) {
  103. if _, err := os.Stat(model); err != nil {
  104. return nil, err
  105. }
  106. llm := LLM{Options: opts}
  107. C.llama_backend_init(C.bool(llm.UseNUMA))
  108. params := C.llama_context_default_params()
  109. params.seed = C.uint(llm.Seed)
  110. params.n_ctx = C.int(llm.NumCtx)
  111. params.n_batch = C.int(llm.NumBatch)
  112. params.n_gqa = C.int(llm.NumGQA)
  113. params.n_gpu_layers = C.int(llm.NumGPU)
  114. params.main_gpu = C.int(llm.MainGPU)
  115. params.low_vram = C.bool(llm.LowVRAM)
  116. params.f16_kv = C.bool(llm.F16KV)
  117. params.logits_all = C.bool(llm.LogitsAll)
  118. params.vocab_only = C.bool(llm.VocabOnly)
  119. params.use_mmap = C.bool(llm.UseMMap)
  120. params.use_mlock = C.bool(llm.UseMLock)
  121. params.embedding = C.bool(llm.EmbeddingOnly)
  122. llm.params = &params
  123. cModel := C.CString(model)
  124. defer C.free(unsafe.Pointer(cModel))
  125. llm.model = C.llama_load_model_from_file(cModel, params)
  126. if llm.model == nil {
  127. return nil, errors.New("failed to load model")
  128. }
  129. llm.ctx = C.llama_new_context_with_model(llm.model, params)
  130. if llm.ctx == nil {
  131. return nil, errors.New("failed to create context")
  132. }
  133. // warm up the model
  134. bos := []C.llama_token{C.llama_token_bos()}
  135. C.llama_eval(llm.ctx, unsafe.SliceData(bos), C.int(len(bos)), 0, C.int(opts.NumThread))
  136. C.llama_reset_timings(llm.ctx)
  137. return &llm, nil
  138. }
  139. func (llm *LLM) Close() {
  140. llm.gc = true
  141. llm.mu.Lock()
  142. defer llm.mu.Unlock()
  143. defer C.llama_free_model(llm.model)
  144. defer C.llama_free(llm.ctx)
  145. C.llama_print_timings(llm.ctx)
  146. }
  147. var errNeedMoreData = errors.New("need more data")
  148. func (llm *LLM) Predict(ctx []int, prompt string, fn func(api.GenerateResponse)) error {
  149. C.llama_reset_timings(llm.ctx)
  150. tokens := make([]C.llama_token, len(ctx))
  151. for i := range tokens {
  152. tokens[i] = C.llama_token(ctx[i])
  153. }
  154. if len(tokens) == 0 {
  155. tokens = llm.tokenize(" ")
  156. }
  157. llm.marshalPrompt(tokens, prompt)
  158. C.llama_set_rng_seed(llm.ctx, C.uint(llm.Seed))
  159. var b bytes.Buffer
  160. for {
  161. token, err := llm.next()
  162. if llm.gc {
  163. return nil
  164. } else if errors.Is(err, io.EOF) {
  165. break
  166. } else if err != nil {
  167. return err
  168. }
  169. b.WriteString(llm.detokenize(token))
  170. if err := llm.checkStopConditions(b); err != nil {
  171. if errors.Is(err, io.EOF) {
  172. break
  173. } else if errors.Is(err, errNeedMoreData) {
  174. continue
  175. }
  176. return err
  177. }
  178. if utf8.Valid(b.Bytes()) || b.Len() >= utf8.UTFMax {
  179. fn(api.GenerateResponse{Response: b.String()})
  180. b.Reset()
  181. }
  182. }
  183. last := make([]int, 0, len(llm.last))
  184. for _, i := range llm.last {
  185. if i != 0 {
  186. last = append(last, int(i))
  187. }
  188. }
  189. timings := C.llama_get_timings(llm.ctx)
  190. fn(api.GenerateResponse{
  191. Done: true,
  192. Context: last,
  193. SampleCount: int(timings.n_sample),
  194. SampleDuration: parseDurationMs(float64(timings.t_sample_ms)),
  195. PromptEvalCount: int(timings.n_p_eval),
  196. PromptEvalDuration: parseDurationMs(float64(timings.t_p_eval_ms)),
  197. EvalCount: int(timings.n_eval),
  198. EvalDuration: parseDurationMs(float64(timings.t_eval_ms)),
  199. })
  200. return nil
  201. }
  202. func (llm *LLM) checkStopConditions(b bytes.Buffer) error {
  203. for _, stopCondition := range llm.StopConditions {
  204. if stopCondition == b.String() {
  205. return io.EOF
  206. } else if strings.HasPrefix(stopCondition, b.String()) {
  207. return errNeedMoreData
  208. }
  209. }
  210. return nil
  211. }
  212. func (llm *LLM) marshalPrompt(ctx []C.llama_token, prompt string) []C.llama_token {
  213. tokens := append(ctx, llm.tokenize(prompt)...)
  214. if llm.NumKeep < 0 {
  215. llm.NumKeep = len(tokens)
  216. }
  217. // min(llm.NumCtx - 4, llm.NumKeep)
  218. if llm.NumCtx-4 < llm.NumKeep {
  219. llm.NumKeep = llm.NumCtx - 4
  220. }
  221. if len(tokens) >= llm.NumCtx {
  222. // truncate input
  223. numLeft := (llm.NumCtx - llm.NumKeep) / 2
  224. truncated := tokens[:llm.NumKeep]
  225. erasedBlocks := (len(tokens) - llm.NumKeep - numLeft - 1) / numLeft
  226. truncated = append(truncated, tokens[llm.NumKeep+erasedBlocks*numLeft:]...)
  227. copy(llm.last, tokens[len(tokens)-llm.NumCtx:])
  228. tokens = truncated
  229. log.Printf("input truncated: num_ctx=%d num_keep=%d num_left=%d num_tokens=%d", llm.NumCtx, llm.NumKeep, numLeft, len(truncated))
  230. } else {
  231. llm.last = make([]C.llama_token, llm.NumCtx-len(tokens))
  232. llm.last = append(llm.last, tokens...)
  233. }
  234. var i int
  235. for i = 0; i < len(llm.embd) && i < len(tokens) && llm.embd[i] == tokens[i]; i++ {
  236. // noop
  237. }
  238. llm.embd = tokens
  239. if i == len(tokens) {
  240. // evaluate at least one token to generate logits
  241. i--
  242. }
  243. llm.cursor = i
  244. log.Printf("prompt: num_past=%d cached=%v eval=%v", i, len(llm.embd[:i]), len(llm.embd[i:]))
  245. return tokens
  246. }
  247. func (llm *LLM) tokenize(prompt string) []C.llama_token {
  248. cPrompt := C.CString(prompt)
  249. defer C.free(unsafe.Pointer(cPrompt))
  250. tokens := make([]C.llama_token, len(prompt)+1)
  251. if n := C.llama_tokenize(llm.ctx, cPrompt, unsafe.SliceData(tokens), C.int(len(tokens)), true); n > 0 {
  252. return tokens[:n]
  253. }
  254. return nil
  255. }
  256. func (llm *LLM) detokenize(tokens ...C.llama_token) string {
  257. var sb strings.Builder
  258. for _, token := range tokens {
  259. sb.WriteString(C.GoString(C.llama_token_to_str(llm.ctx, token)))
  260. }
  261. return sb.String()
  262. }
  263. func (llm *LLM) next() (C.llama_token, error) {
  264. llm.mu.Lock()
  265. defer llm.mu.Unlock()
  266. if len(llm.embd) >= llm.NumCtx {
  267. numLeft := (llm.NumCtx - llm.NumKeep) / 2
  268. truncated := llm.embd[:llm.NumKeep]
  269. truncated = append(truncated, llm.embd[len(llm.embd)-numLeft:]...)
  270. llm.embd = truncated
  271. llm.cursor = llm.NumKeep
  272. log.Printf("input truncated: num_ctx=%d num_keep=%d num_left=%d num_tokens=%d cursor=%d", llm.NumCtx, llm.NumKeep, numLeft, len(truncated), llm.cursor)
  273. }
  274. for {
  275. if llm.gc {
  276. return 0, io.EOF
  277. }
  278. if llm.cursor >= len(llm.embd) {
  279. break
  280. }
  281. numEval := len(llm.embd) - llm.cursor
  282. if numEval > llm.NumBatch {
  283. numEval = llm.NumBatch
  284. }
  285. if retval := C.llama_eval(llm.ctx, unsafe.SliceData(llm.embd[llm.cursor:]), C.int(numEval), C.int(llm.cursor), C.int(llm.NumThread)); retval != 0 {
  286. return 0, fmt.Errorf("llama_eval: %d", retval)
  287. }
  288. llm.cursor += numEval
  289. }
  290. var sampleOpts C.struct_llama_sample_options
  291. sampleOpts.repeat_penalty = C.float(llm.RepeatPenalty)
  292. sampleOpts.frequency_penalty = C.float(llm.FrequencyPenalty)
  293. sampleOpts.presence_penalty = C.float(llm.PresencePenalty)
  294. sampleOpts.temperature = C.float(llm.Temperature)
  295. sampleOpts.top_k = C.int(llm.TopK)
  296. sampleOpts.top_p = C.float(llm.TopP)
  297. sampleOpts.tfs_z = C.float(llm.TFSZ)
  298. sampleOpts.typical_p = C.float(llm.TypicalP)
  299. sampleOpts.mirostat = C.int(llm.Mirostat)
  300. sampleOpts.mirostat_tau = C.float(llm.MirostatTau)
  301. sampleOpts.mirostat_eta = C.float(llm.MirostatEta)
  302. sampleOpts.penalize_newline = C.bool(llm.PenalizeNewline)
  303. numVocab := C.llama_n_vocab(llm.ctx)
  304. logits := unsafe.Slice(C.llama_get_logits(llm.ctx), numVocab)
  305. // TODO: logit bias
  306. candidates := make([]C.llama_token_data, numVocab)
  307. for i := range logits {
  308. candidates[i] = C.llama_token_data{
  309. id: C.int(i),
  310. logit: logits[i],
  311. p: 0,
  312. }
  313. }
  314. repeatLastN := llm.RepeatLastN
  315. if len(llm.last) < repeatLastN {
  316. repeatLastN = len(llm.last)
  317. }
  318. if llm.NumCtx < repeatLastN {
  319. repeatLastN = llm.NumCtx
  320. }
  321. lastN := llm.last[len(llm.last)-repeatLastN:]
  322. token := C.llama_sample(
  323. llm.ctx,
  324. unsafe.SliceData(candidates), C.size_t(len(candidates)),
  325. unsafe.SliceData(lastN), C.size_t(len(lastN)),
  326. &sampleOpts,
  327. )
  328. llm.last = append(llm.last, token)
  329. llm.embd = append(llm.embd, token)
  330. if token == C.llama_token_eos() {
  331. return 0, io.EOF
  332. }
  333. return token, nil
  334. }