Module: LLaMACpp
- Defined in:
- lib/llama_cpp.rb,
lib/llama_cpp/version.rb,
ext/llama_cpp/llama_cpp.cpp
Overview
llama_cpp.rb provides Ruby bindings for the llama.cpp.
Constant Summary collapse
- VERSION =
The version of llama_cpp.rb you install.
'0.9.4'
- LLAMA_CPP_VERSION =
The version of llama.cpp bundled with llama_cpp.rb.
'b1555'
- LLAMA_MAX_DEVICES =
INT2NUM(LLAMA_MAX_DEVICES)
- LLAMA_VOCAB_TYPE_SPM =
INT2NUM(LLAMA_VOCAB_TYPE_SPM)
- LLAMA_VOCAB_TYPE_BPE =
INT2NUM(LLAMA_VOCAB_TYPE_BPE)
- LLAMA_TOKEN_TYPE_UNDEFINED =
INT2NUM(LLAMA_TOKEN_TYPE_UNDEFINED)
- LLAMA_TOKEN_TYPE_NORMAL =
INT2NUM(LLAMA_TOKEN_TYPE_NORMAL)
- LLAMA_TOKEN_TYPE_UNKNOWN =
INT2NUM(LLAMA_TOKEN_TYPE_UNKNOWN)
- LLAMA_TOKEN_TYPE_CONTROL =
INT2NUM(LLAMA_TOKEN_TYPE_CONTROL)
- LLAMA_TOKEN_TYPE_USER_DEFINED =
INT2NUM(LLAMA_TOKEN_TYPE_USER_DEFINED)
- LLAMA_TOKEN_TYPE_UNUSED =
INT2NUM(LLAMA_TOKEN_TYPE_UNUSED)
- LLAMA_TOKEN_TYPE_BYTE =
INT2NUM(LLAMA_TOKEN_TYPE_BYTE)
- LLAMA_FTYPE_ALL_F32 =
INT2NUM(LLAMA_FTYPE_ALL_F32)
- LLAMA_FTYPE_MOSTLY_F16 =
INT2NUM(LLAMA_FTYPE_MOSTLY_F16)
- LLAMA_FTYPE_MOSTLY_Q4_0 =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q4_0)
- LLAMA_FTYPE_MOSTLY_Q4_1 =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q4_1)
- LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16 =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16)
- LLAMA_FTYPE_MOSTLY_Q8_0 =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q8_0)
- LLAMA_FTYPE_MOSTLY_Q5_0 =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q5_0)
- LLAMA_FTYPE_MOSTLY_Q5_1 =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q5_1)
- LLAMA_FTYPE_MOSTLY_Q2_K =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q2_K)
- LLAMA_FTYPE_MOSTLY_Q3_K_S =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q3_K_S)
- LLAMA_FTYPE_MOSTLY_Q3_K_M =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q3_K_M)
- LLAMA_FTYPE_MOSTLY_Q3_K_L =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q3_K_L)
- LLAMA_FTYPE_MOSTLY_Q4_K_S =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q4_K_S)
- LLAMA_FTYPE_MOSTLY_Q4_K_M =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q4_K_M)
- LLAMA_FTYPE_MOSTLY_Q5_K_S =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q5_K_S)
- LLAMA_FTYPE_MOSTLY_Q5_K_M =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q5_K_M)
- LLAMA_FTYPE_MOSTLY_Q6_K =
INT2NUM(LLAMA_FTYPE_MOSTLY_Q6_K)
- LLAMA_FTYPE_GUESSED =
INT2NUM(LLAMA_FTYPE_GUESSED)
- LLAMA_GRETYPE_END =
INT2NUM(LLAMA_GRETYPE_END)
- LLAMA_GRETYPE_ALT =
INT2NUM(LLAMA_GRETYPE_ALT)
- LLAMA_GRETYPE_RULE_REF =
INT2NUM(LLAMA_GRETYPE_RULE_REF)
- LLAMA_GRETYPE_CHAR =
INT2NUM(LLAMA_GRETYPE_CHAR)
- LLAMA_GRETYPE_CHAR_NOT =
INT2NUM(LLAMA_GRETYPE_CHAR_NOT)
- LLAMA_GRETYPE_CHAR_RNG_UPPER =
INT2NUM(LLAMA_GRETYPE_CHAR_RNG_UPPER)
- LLAMA_GRETYPE_CHAR_ALT =
INT2NUM(LLAMA_GRETYPE_CHAR_ALT)
- LLAMA_ROPE_SCALING_UNSPECIFIED =
INT2NUM(LLAMA_ROPE_SCALING_UNSPECIFIED)
- LLAMA_ROPE_SCALING_NONE =
INT2NUM(LLAMA_ROPE_SCALING_NONE)
- LLAMA_ROPE_SCALING_LINEAR =
INT2NUM(LLAMA_ROPE_SCALING_LINEAR)
- LLAMA_ROPE_SCALING_YARN =
INT2NUM(LLAMA_ROPE_SCALING_YARN)
- LLAMA_ROPE_SCALING_MAX_VALUE =
INT2NUM(LLAMA_ROPE_SCALING_MAX_VALUE)
- LLAMA_FILE_MAGIC_GGSN =
rb_str_new2(ss_magic.str().c_str())
- LLAMA_SESSION_MAGIC =
rb_str_new2(ss_magic.str().c_str())
- LLAMA_DEFAULT_SEED =
rb_str_new2(ss_magic.str().c_str())
- LLAMA_SESSION_VERSION =
rb_str_new2(std::to_string(LLAMA_SESSION_VERSION).c_str())
Class Method Summary collapse
- .backend_free ⇒ Object
-
.backend_init(*args) ⇒ Object
module functions.
-
.generate(context, prompt, n_predict: 128, n_keep: 10, n_batch: 512, repeat_last_n: 64, repeat_penalty: 1.1, frequency: 0.0, presence: 0.0, top_k: 40, top_p: 0.95, tfs_z: 1.0, typical_p: 1.0, temperature: 0.8) ⇒ String
Generates sentences following the given prompt for operation check.
- .max_devices ⇒ Object
- .mlock_supported? ⇒ Boolean
- .mmap_supported? ⇒ Boolean
- .model_quantize(*args) ⇒ Object
- .print_system_info ⇒ Object
- .time_us ⇒ Object
Class Method Details
.backend_free ⇒ Object
2911 2912 2913 2914 2915 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2911 static VALUE rb_llama_llama_backend_free(VALUE self) { llama_backend_free(); return Qnil; } |
.backend_init(*args) ⇒ Object
module functions
2898 2899 2900 2901 2902 2903 2904 2905 2906 2907 2908 2909 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2898
static VALUE rb_llama_llama_backend_init(int argc, VALUE* argv, VALUE self) {
VALUE kw_args = Qnil;
ID kw_table[1] = { rb_intern("numa") };
VALUE kw_values[1] = { Qundef };
rb_scan_args(argc, argv, ":", &kw_args);
rb_get_kwargs(kw_args, kw_table, 0, 1, kw_values);
const bool numa = kw_values[0] == Qundef ? false : (RTEST(kw_values[0]) ? true : false);
llama_backend_init(numa);
return Qnil;
}
|
.generate(context, prompt, n_predict: 128, n_keep: 10, n_batch: 512, repeat_last_n: 64, repeat_penalty: 1.1, frequency: 0.0, presence: 0.0, top_k: 40, top_p: 0.95, tfs_z: 1.0, typical_p: 1.0, temperature: 0.8) ⇒ String
Generates sentences following the given prompt for operation check.
27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 |
# File 'lib/llama_cpp.rb', line 27 def generate(context, prompt, # rubocop:disable Metrics/AbcSize, Metrics/CyclomaticComplexity, Metrics/MethodLength, Metrics/ParameterLists, Metrics/PerceivedComplexity n_predict: 128, n_keep: 10, n_batch: 512, repeat_last_n: 64, repeat_penalty: 1.1, frequency: 0.0, presence: 0.0, top_k: 40, top_p: 0.95, tfs_z: 1.0, typical_p: 1.0, temperature: 0.8) raise ArgumentError, 'context must be an instance of LLaMACpp::Context' unless context.is_a?(LLaMACpp::Context) raise ArgumentError, 'prompt must be a String' unless prompt.is_a?(String) spaced_prompt = " #{prompt}" embd_input = context.model.tokenize(text: spaced_prompt, add_bos: true) n_ctx = context.n_ctx raise ArgumentError, "prompt is too long #{embd_input.size} tokens, maximum is #{n_ctx - 4}" if embd_input.size > n_ctx - 4 last_n_tokens = [0] * n_ctx embd = [] n_consumed = 0 n_past = 0 n_remain = n_predict n_vocab = context.model.n_vocab output = [] while n_remain != 0 unless embd.empty? if n_past + embd.size > n_ctx n_left = n_past - n_keep n_past = n_keep embd.insert(0, last_n_tokens[(n_ctx - (n_left / 2) - embd.size)...-embd.size]) end context.eval(tokens: embd, n_past: n_past) end n_past += embd.size embd.clear if embd_input.size <= n_consumed logits = context.logits base_candidates = Array.new(n_vocab) { |i| LLaMACpp::TokenData.new(id: i, logit: logits[i], p: 0.0) } candidates = LLaMACpp::TokenDataArray.new(base_candidates) # apply penalties last_n_repeat = [last_n_tokens.size, repeat_last_n, n_ctx].min context.sample_repetition_penalties( candidates, last_n_tokens[-last_n_repeat..], penalty_repeat: repeat_penalty, penalty_freq: frequency, penalty_present: presence ) # temperature sampling context.sample_top_k(candidates, k: top_k) context.sample_tail_free(candidates, z: tfs_z) context.sample_typical(candidates, prob: typical_p) context.sample_top_p(candidates, prob: top_p) context.sample_temperature(candidates, temperature: temperature) id = context.sample_token(candidates) last_n_tokens.shift last_n_tokens.push(id) embd.push(id) n_remain -= 1 else while embd_input.size > n_consumed embd.push(embd_input[n_consumed]) last_n_tokens.shift last_n_tokens.push(embd_input[n_consumed]) n_consumed += 1 break if embd.size >= n_batch end end embd.each { |token| output << context.model.token_to_piece(token) } break if !embd.empty? && embd[-1] == context.model.token_eos end output.join.scrub('?').strip.delete_prefix(prompt).strip end |
.max_devices ⇒ Object
2966 2967 2968 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2966 static VALUE rb_llama_max_devices(VALUE self) { return INT2NUM(llama_max_devices()); } |
.mlock_supported? ⇒ Boolean
2962 2963 2964 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2962 static VALUE rb_llama_mlock_supported(VALUE self) { return llama_mlock_supported() ? Qtrue : Qfalse; } |
.mmap_supported? ⇒ Boolean
2958 2959 2960 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2958 static VALUE rb_llama_mmap_supported(VALUE self) { return llama_mmap_supported() ? Qtrue : Qfalse; } |
.model_quantize(*args) ⇒ Object
2917 2918 2919 2920 2921 2922 2923 2924 2925 2926 2927 2928 2929 2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944 2945 2946 2947 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2917
static VALUE rb_llama_model_quantize(int argc, VALUE* argv, VALUE self) {
VALUE kw_args = Qnil;
ID kw_table[3] = { rb_intern("input_path"), rb_intern("output_path"), rb_intern("params") };
VALUE kw_values[3] = { Qundef, Qundef, Qundef };
rb_scan_args(argc, argv, ":", &kw_args);
rb_get_kwargs(kw_args, kw_table, 3, 0, kw_values);
if (!RB_TYPE_P(kw_values[0], T_STRING)) {
rb_raise(rb_eArgError, "input_path must be a string");
return Qnil;
}
if (!RB_TYPE_P(kw_values[1], T_STRING)) {
rb_raise(rb_eArgError, "output_path must be a string");
return Qnil;
}
if (!rb_obj_is_kind_of(kw_values[2], rb_cLLaMAModelQuantizeParams)) {
rb_raise(rb_eArgError, "params must be a ModelQuantizeParams");
return Qnil;
}
const char* input_path = StringValueCStr(kw_values[0]);
const char* output_path = StringValueCStr(kw_values[1]);
LLaMAModelQuantizeParamsWrapper* wrapper = RbLLaMAModelQuantizeParams::get_llama_model_quantize_params(kw_values[2]);
if (llama_model_quantize(input_path, output_path, &(wrapper->params)) != 0) {
rb_raise(rb_eRuntimeError, "Failed to quantize model");
return Qnil;
}
return Qnil;
}
|
.print_system_info ⇒ Object
2949 2950 2951 2952 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2949 static VALUE rb_llama_print_system_info(VALUE self) { const char* result = llama_print_system_info(); return rb_utf8_str_new_cstr(result); } |
.time_us ⇒ Object
2954 2955 2956 |
# File 'ext/llama_cpp/llama_cpp.cpp', line 2954 static VALUE rb_llama_time_us(VALUE self) { return LONG2NUM(llama_time_us()); } |