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

Params =

Class alias to match interface of whispercpp gem.

ContextParams
VERSION =

The version of llama_cpp.rb you install.

'0.3.3'
LLAMA_CPP_VERSION =

The version of llama.cpp bundled with llama_cpp.rb.

'master-32c5411'
LLAMA_MAX_DEVICES = 
INT2NUM(LLAMA_MAX_DEVICES)
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_FILE_MAGIC_GGJT = 
rb_str_new2(ss_magic.str().c_str())
LLAMA_FILE_MAGIC_GGLA = 
rb_str_new2(ss_magic.str().c_str())
LLAMA_FILE_MAGIC_GGMF = 
rb_str_new2(ss_magic.str().c_str())
LLAMA_FILE_MAGIC_GGML = 
rb_str_new2(ss_magic.str().c_str())
LLAMA_FILE_MAGIC_GGSN = 
rb_str_new2(ss_magic.str().c_str())
LLAMA_FILE_MAGIC = 
rb_str_new2(ss_magic.str().c_str())
LLAMA_FILE_MAGIC_UNVERSIONED = 
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_FILE_VERSION = 
rb_str_new2(std::to_string(LLAMA_FILE_VERSION).c_str())
LLAMA_SESSION_VERSION = 
rb_str_new2(std::to_string(LLAMA_SESSION_VERSION).c_str())

Class Method Summary collapse

Class Method Details

.backend_free ⇒ Object 



2002
2003
2004
2005
2006
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2002

static VALUE rb_llama_llama_backend_free(VALUE self) {
  llama_backend_free();

  return Qnil;
}

.backend_init(*args) ⇒ Object

module functions



1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 1989

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 ? true : false);
  llama_backend_init(numa);

  return Qnil;
}

.generate(context, prompt, n_predict: 128, n_threads: 1, 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.

Parameters:

  • context (LLaMACpp::Context) —

    The context to use.

  • prompt (String) —

    The prompt to start generation with.

  • n_predict (Integer) (defaults to: 128) —

    The number of tokens to predict.

  • n_threads (Integer) (defaults to: 1) —

    The number of threads.

  • n_keep (Integer) (defaults to: 10) —

    The number of tokens to keep in the context.

  • n_batch (Integer) (defaults to: 512) —

    The number of tokens to process in a batch.

  • repeat_last_n (Integer) (defaults to: 64) —

    The number of tokens to consider for repetition penalty.

  • repeat_penalty (Float) (defaults to: 1.1) —

    The repetition penalty.

  • frequency (Float) (defaults to: 0.0) —

    The frequency penalty.

  • presence (Float) (defaults to: 0.0) —

    The presence penalty.

  • top_k (Integer) (defaults to: 40) —

    The number of tokens to consider for top-k sampling.

  • top_p (Float) (defaults to: 0.95) —

    The probability threshold for nucleus sampling.

  • tfs_z (Float) (defaults to: 1.0) —

    The z parameter for tail-free sampling.

  • typical_p (Float) (defaults to: 1.0) —

    The probability for typical sampling.

  • temperature (Float) (defaults to: 0.8) —

    The temperature for temperature sampling.

Returns:

  • (String)

Raises:

  • (ArgumentError) 


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
105
106
107
108
 
# File 'lib/llama_cpp.rb', line 31

def generate(context, prompt, # rubocop:disable Metrics/AbcSize, Metrics/CyclomaticComplexity, Metrics/MethodLength, Metrics/ParameterLists, Metrics/PerceivedComplexity
             n_predict: 128, n_threads: 1, 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.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.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, n_threads: n_threads)
    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_penalty(candidates, last_n_tokens[-last_n_repeat..], penalty: repeat_penalty)
      context.sample_frequency_and_presence_penalties(
        candidates, last_n_tokens[-last_n_repeat..], frequency: frequency, presence: 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.token_to_str(token) }

    break if !embd.empty? && embd[-1] == LLaMACpp.token_eos
  end

  output.join.delete_prefix(spaced_prompt).strip
end

.mlock_supported? ⇒ Boolean

Returns:

  • (Boolean) 


2061
2062
2063
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2061

static VALUE rb_llama_mlock_supported(VALUE self) {
  return llama_mlock_supported() ? Qtrue : Qfalse;
}

.mmap_supported? ⇒ Boolean

Returns:

  • (Boolean) 


2057
2058
2059
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2057

static VALUE rb_llama_mmap_supported(VALUE self) {
  return llama_mmap_supported() ? Qtrue : Qfalse;
}

.model_quantize(*args) ⇒ Object 



2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2008

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 



2052
2053
2054
2055
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2052

static VALUE rb_llama_print_system_info(VALUE self) {
  const char* result = llama_print_system_info();
  return rb_utf8_str_new_cstr(result);
}

.token_bos ⇒ Object 



2040
2041
2042
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2040

static VALUE rb_llama_token_bos(VALUE self) {
  return INT2NUM(llama_token_bos());
}

.token_eos ⇒ Object 



2044
2045
2046
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2044

static VALUE rb_llama_token_eos(VALUE self) {
  return INT2NUM(llama_token_eos());
}

.token_nl ⇒ Object 



2048
2049
2050
 
# File 'ext/llama_cpp/llama_cpp.cpp', line 2048

static VALUE rb_llama_token_nl(VALUE self) {
  return INT2NUM(llama_token_nl());
}