llama_cpp_4/model/params.rs
1//! A safe wrapper around `llama_model_params`.
2
3use crate::model::params::kv_overrides::KvOverrides;
4use std::ffi::{c_char, CStr};
5use std::fmt::{Debug, Formatter};
6use std::pin::Pin;
7use std::ptr::null;
8
9pub mod kv_overrides;
10
11/// A safe wrapper around `llama_model_params`.
12#[allow(clippy::module_name_repetitions)]
13pub struct LlamaModelParams {
14 pub(crate) params: llama_cpp_sys_4::llama_model_params,
15 kv_overrides: Vec<llama_cpp_sys_4::llama_model_kv_override>,
16 #[cfg(feature = "mtp")]
17 override_arch: Option<std::ffi::CString>,
18}
19
20impl Debug for LlamaModelParams {
21 fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
22 f.debug_struct("LlamaModelParams")
23 .field("n_gpu_layers", &self.params.n_gpu_layers)
24 .field("main_gpu", &self.params.main_gpu)
25 .field("vocab_only", &self.params.vocab_only)
26 .field("use_mmap", &self.params.use_mmap)
27 .field("use_mlock", &self.params.use_mlock)
28 .field("kv_overrides", &"vec of kv_overrides")
29 .finish()
30 }
31}
32
33impl LlamaModelParams {
34 /// See [`KvOverrides`]
35 ///
36 /// # Examples
37 ///
38 /// ```rust
39 /// # use llama_cpp_4::model::params::LlamaModelParams;
40 /// let params = Box::pin(LlamaModelParams::default());
41 /// let kv_overrides = params.kv_overrides();
42 /// let count = kv_overrides.into_iter().count();
43 /// assert_eq!(count, 0);
44 /// ```
45 #[must_use]
46 pub fn kv_overrides(&self) -> KvOverrides<'_> {
47 KvOverrides::new(self)
48 }
49
50 /// Appends a key-value override to the model parameters. It must be pinned as this creates a self-referential struct.
51 ///
52 /// # Examples
53 ///
54 /// ```rust
55 /// # use std::ffi::{CStr, CString};
56 /// use std::pin::pin;
57 /// # use llama_cpp_4::model::params::LlamaModelParams;
58 /// # use llama_cpp_4::model::params::kv_overrides::ParamOverrideValue;
59 /// let mut params = pin!(LlamaModelParams::default());
60 /// let key = CString::new("key").expect("CString::new failed");
61 /// params.as_mut().append_kv_override(&key, ParamOverrideValue::Int(50));
62 ///
63 /// let kv_overrides = params.kv_overrides().into_iter().collect::<Vec<_>>();
64 /// assert_eq!(kv_overrides.len(), 1);
65 ///
66 /// let (k, v) = &kv_overrides[0];
67 /// assert_eq!(v, &ParamOverrideValue::Int(50));
68 ///
69 /// assert_eq!(k.to_bytes(), b"key", "expected key to be 'key', was {:?}", k);
70 /// ```
71 #[allow(clippy::missing_panics_doc)] // panics are just to enforce internal invariants, not user errors
72 pub fn append_kv_override(
73 mut self: Pin<&mut Self>,
74 key: &CStr,
75 value: kv_overrides::ParamOverrideValue,
76 ) {
77 let kv_override = self
78 .kv_overrides
79 .get_mut(0)
80 .expect("kv_overrides did not have a next allocated");
81
82 assert_eq!(kv_override.key[0], 0, "last kv_override was not empty");
83
84 // There should be some way to do this without iterating over everything.
85 for (i, &c) in key.to_bytes_with_nul().iter().enumerate() {
86 kv_override.key[i] = c_char::try_from(c).expect("invalid character in key");
87 }
88
89 kv_override.tag = value.tag();
90 kv_override.__bindgen_anon_1 = value.value();
91
92 // set to null pointer for panic safety (as push may move the vector, invalidating the pointer)
93 self.params.kv_overrides = null();
94
95 // push the next one to ensure we maintain the iterator invariant of ending with a 0
96 self.kv_overrides
97 .push(llama_cpp_sys_4::llama_model_kv_override {
98 key: [0; 128],
99 tag: 0,
100 __bindgen_anon_1: llama_cpp_sys_4::llama_model_kv_override__bindgen_ty_1 {
101 val_i64: 0,
102 },
103 });
104
105 // set the pointer to the (potentially) new vector
106 self.params.kv_overrides = self.kv_overrides.as_ptr();
107
108 eprintln!("saved ptr: {:?}", self.params.kv_overrides);
109 }
110}
111
112impl LlamaModelParams {
113 /// Get the number of layers to offload to the GPU.
114 #[must_use]
115 pub fn n_gpu_layers(&self) -> i32 {
116 self.params.n_gpu_layers
117 }
118
119 /// The GPU that is used for scratch and small tensors
120 #[must_use]
121 pub fn main_gpu(&self) -> i32 {
122 self.params.main_gpu
123 }
124
125 /// only load the vocabulary, no weights
126 #[must_use]
127 pub fn vocab_only(&self) -> bool {
128 self.params.vocab_only
129 }
130
131 /// use mmap if possible
132 #[must_use]
133 pub fn use_mmap(&self) -> bool {
134 self.params.use_mmap
135 }
136
137 /// force system to keep model in RAM
138 #[must_use]
139 pub fn use_mlock(&self) -> bool {
140 self.params.use_mlock
141 }
142
143 /// sets the number of gpu layers to offload to the GPU.
144 /// ```
145 /// # use llama_cpp_4::model::params::LlamaModelParams;
146 /// let params = LlamaModelParams::default();
147 /// let params = params.with_n_gpu_layers(1);
148 /// assert_eq!(params.n_gpu_layers(), 1);
149 /// ```
150 #[must_use]
151 pub fn with_n_gpu_layers(mut self, n_gpu_layers: u32) -> Self {
152 // The only way this conversion can fail is if u32 overflows the i32 - in which case we set
153 // to MAX
154 let n_gpu_layers = i32::try_from(n_gpu_layers).unwrap_or(i32::MAX);
155 self.params.n_gpu_layers = n_gpu_layers;
156 self
157 }
158
159 /// sets the main GPU
160 #[must_use]
161 pub fn with_main_gpu(mut self, main_gpu: i32) -> Self {
162 self.params.main_gpu = main_gpu;
163 self
164 }
165
166 /// sets `vocab_only`
167 #[must_use]
168 pub fn with_vocab_only(mut self, vocab_only: bool) -> Self {
169 self.params.vocab_only = vocab_only;
170 self
171 }
172
173 /// sets `use_mlock`
174 #[must_use]
175 pub fn with_use_mlock(mut self, use_mlock: bool) -> Self {
176 self.params.use_mlock = use_mlock;
177 self
178 }
179
180 /// Override model architecture string used when loading.
181 ///
182 /// This is primarily used by MTP to load the draft head architecture
183 /// from the same GGUF (for example `qwen35_mtp` / `qwen35moe_mtp`).
184 ///
185 /// This API is only available when built with the `mtp` feature.
186 #[cfg(feature = "mtp")]
187 #[must_use]
188 pub fn with_override_arch(mut self, override_arch: Option<&str>) -> Self {
189 self.override_arch = override_arch
190 .map(|value| std::ffi::CString::new(value).expect("override_arch contains null bytes"));
191 self.params.override_arch = self
192 .override_arch
193 .as_ref()
194 .map_or(std::ptr::null(), |value| value.as_ptr());
195 self
196 }
197
198 /// Get the currently configured model architecture override.
199 ///
200 /// This API is only available when built with the `mtp` feature.
201 #[cfg(feature = "mtp")]
202 #[must_use]
203 pub fn override_arch(&self) -> Option<&str> {
204 self.override_arch
205 .as_ref()
206 .and_then(|value| value.to_str().ok())
207 }
208}
209
210/// Default parameters for `LlamaModel`. (as defined in llama.cpp by `llama_model_default_params`)
211/// ```
212/// # use llama_cpp_4::model::params::LlamaModelParams;
213/// let params = LlamaModelParams::default();
214/// #[cfg(not(target_os = "macos"))]
215/// assert_eq!(params.n_gpu_layers(), 0, "n_gpu_layers should be 0");
216/// #[cfg(target_os = "macos")]
217/// assert_eq!(params.n_gpu_layers(), -1, "n_gpu_layers should be -1 (all layers)");
218/// assert_eq!(params.main_gpu(), 0, "main_gpu should be 0");
219/// assert_eq!(params.vocab_only(), false, "vocab_only should be false");
220/// assert_eq!(params.use_mmap(), true, "use_mmap should be true");
221/// assert_eq!(params.use_mlock(), false, "use_mlock should be false");
222/// ```
223impl Default for LlamaModelParams {
224 fn default() -> Self {
225 let default_params = unsafe { llama_cpp_sys_4::llama_model_default_params() };
226 LlamaModelParams {
227 params: default_params,
228 // push the next one to ensure we maintain the iterator invariant of ending with a 0
229 kv_overrides: vec![llama_cpp_sys_4::llama_model_kv_override {
230 key: [0; 128],
231 tag: 0,
232 __bindgen_anon_1: llama_cpp_sys_4::llama_model_kv_override__bindgen_ty_1 {
233 val_i64: 0,
234 },
235 }],
236 #[cfg(feature = "mtp")]
237 override_arch: None,
238 }
239 }
240}