model_manager.rs 9.05 KB
Newer Older
1
2
3
4
5
6
7
// SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0

use dynamo_runtime::component::Component;

use crate::discovery::ModelEntry;

8
use crate::kv_router::{scheduler::DefaultWorkerSelector, KvRouterConfig};
9
10
11
12
13
14
15
use crate::{
    kv_router::KvRouter,
    types::openai::{
        chat_completions::OpenAIChatCompletionsStreamingEngine,
        completions::OpenAICompletionsStreamingEngine, embeddings::OpenAIEmbeddingsStreamingEngine,
    },
};
16
use std::collections::HashSet;
17
18
19
20
21
22
23
24
25
26
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
use std::sync::RwLock;
use std::{
    collections::HashMap,
    sync::{Arc, Mutex},
};

#[derive(Debug, thiserror::Error)]
pub enum ModelManagerError {
    #[error("Model not found: {0}")]
    ModelNotFound(String),

    #[error("Model already exists: {0}")]
    ModelAlreadyExists(String),
}

// Don't implement Clone for this, put it in an Arc instead.
pub struct ModelManager {
    // We read a lot and write rarely, so these three are RwLock
    completion_engines: RwLock<ModelEngines<OpenAICompletionsStreamingEngine>>,
    chat_completion_engines: RwLock<ModelEngines<OpenAIChatCompletionsStreamingEngine>>,
    embeddings_engines: RwLock<ModelEngines<OpenAIEmbeddingsStreamingEngine>>,

    // These two are Mutex because we read and write rarely and equally
    entries: Mutex<HashMap<String, ModelEntry>>,
    kv_choosers: Mutex<HashMap<String, Arc<KvRouter>>>,
}

impl Default for ModelManager {
    fn default() -> Self {
        Self::new()
    }
}

impl ModelManager {
    pub fn new() -> Self {
        Self {
            completion_engines: RwLock::new(ModelEngines::default()),
            chat_completion_engines: RwLock::new(ModelEngines::default()),
            embeddings_engines: RwLock::new(ModelEngines::default()),
            entries: Mutex::new(HashMap::new()),
            kv_choosers: Mutex::new(HashMap::new()),
        }
    }

61
62
63
64
    pub fn get_model_entries(&self) -> Vec<ModelEntry> {
        self.entries.lock().unwrap().values().cloned().collect()
    }

65
66
67
68
69
    pub fn has_model_any(&self, model: &str) -> bool {
        self.chat_completion_engines.read().unwrap().contains(model)
            || self.completion_engines.read().unwrap().contains(model)
    }

70
71
72
73
74
75
76
77
    pub fn model_display_names(&self) -> HashSet<String> {
        self.list_chat_completions_models()
            .into_iter()
            .chain(self.list_completions_models())
            .chain(self.list_embeddings_models())
            .collect()
    }

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
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
    pub fn list_chat_completions_models(&self) -> Vec<String> {
        self.chat_completion_engines.read().unwrap().list()
    }

    pub fn list_completions_models(&self) -> Vec<String> {
        self.completion_engines.read().unwrap().list()
    }

    pub fn list_embeddings_models(&self) -> Vec<String> {
        self.embeddings_engines.read().unwrap().list()
    }

    pub fn add_completions_model(
        &self,
        model: &str,
        engine: OpenAICompletionsStreamingEngine,
    ) -> Result<(), ModelManagerError> {
        let mut clients = self.completion_engines.write().unwrap();
        clients.add(model, engine)
    }

    pub fn add_chat_completions_model(
        &self,
        model: &str,
        engine: OpenAIChatCompletionsStreamingEngine,
    ) -> Result<(), ModelManagerError> {
        let mut clients = self.chat_completion_engines.write().unwrap();
        clients.add(model, engine)
    }

    pub fn add_embeddings_model(
        &self,
        model: &str,
        engine: OpenAIEmbeddingsStreamingEngine,
    ) -> Result<(), ModelManagerError> {
        let mut clients = self.embeddings_engines.write().unwrap();
        clients.add(model, engine)
    }

    pub fn remove_completions_model(&self, model: &str) -> Result<(), ModelManagerError> {
        let mut clients = self.completion_engines.write().unwrap();
        clients.remove(model)
    }

    pub fn remove_chat_completions_model(&self, model: &str) -> Result<(), ModelManagerError> {
        let mut clients = self.chat_completion_engines.write().unwrap();
        clients.remove(model)
    }

    pub fn remove_embeddings_model(&self, model: &str) -> Result<(), ModelManagerError> {
        let mut clients = self.embeddings_engines.write().unwrap();
        clients.remove(model)
    }

    // TODO: Remove this allow once `embeddings` is implemented in lib/llm/src/http/service/openai.rs
    #[allow(dead_code)]
    fn get_embeddings_engine(
        &self,
        model: &str,
    ) -> Result<OpenAIEmbeddingsStreamingEngine, ModelManagerError> {
        self.embeddings_engines
            .read()
            .unwrap()
            .get(model)
            .cloned()
            .ok_or(ModelManagerError::ModelNotFound(model.to_string()))
    }

    pub fn get_completions_engine(
        &self,
        model: &str,
    ) -> Result<OpenAICompletionsStreamingEngine, ModelManagerError> {
        self.completion_engines
            .read()
            .unwrap()
            .get(model)
            .cloned()
            .ok_or(ModelManagerError::ModelNotFound(model.to_string()))
    }

    pub fn get_chat_completions_engine(
        &self,
        model: &str,
    ) -> Result<OpenAIChatCompletionsStreamingEngine, ModelManagerError> {
        self.chat_completion_engines
            .read()
            .unwrap()
            .get(model)
            .cloned()
            .ok_or(ModelManagerError::ModelNotFound(model.to_string()))
    }

    /// Save a ModelEntry under an instance's etcd `models/` key so we can fetch it later when the key is
    /// deleted from etcd.
    pub fn save_model_entry(&self, key: &str, entry: ModelEntry) {
        self.entries.lock().unwrap().insert(key.to_string(), entry);
    }

    /// Remove and return model entry for this instance's etcd key. We do this when the instance stops.
    pub fn remove_model_entry(&self, key: &str) -> Option<ModelEntry> {
        self.entries.lock().unwrap().remove(key)
    }

    pub async fn kv_chooser_for(
        &self,
        model_name: &str,
        component: &Component,
185
        kv_cache_block_size: usize,
186
        kv_router_config: Option<KvRouterConfig>,
187
188
    ) -> anyhow::Result<Arc<KvRouter>> {
        if let Some(kv_chooser) = self.get_kv_chooser(model_name) {
189
190
191
192
193
194
195
196
197
198
            // Check if the existing router has a different block size
            if kv_chooser.block_size() != kv_cache_block_size {
                tracing::warn!(
                    model_name = %model_name,
                    existing_block_size = %kv_chooser.block_size(),
                    requested_block_size = %kv_cache_block_size,
                    "KV Router block size mismatch! Model is requesting a different kv_cache_block_size than the existing router. \
                     This will cause routing to fail silently. Consider using the same block size or restarting the router."
                );
            }
199
200
            return Ok(kv_chooser);
        }
201
        self.create_kv_chooser(model_name, component, kv_cache_block_size, kv_router_config)
202
            .await
203
204
205
206
207
208
209
210
211
212
213
    }

    fn get_kv_chooser(&self, model_name: &str) -> Option<Arc<KvRouter>> {
        self.kv_choosers.lock().unwrap().get(model_name).cloned()
    }

    /// Create and return a KV chooser for this component and model
    async fn create_kv_chooser(
        &self,
        model_name: &str,
        component: &Component,
214
        kv_cache_block_size: usize,
215
        kv_router_config: Option<KvRouterConfig>,
216
    ) -> anyhow::Result<Arc<KvRouter>> {
217
        let selector = Box::new(DefaultWorkerSelector::new(kv_router_config));
218
        let chooser = KvRouter::new(component.clone(), kv_cache_block_size, Some(selector)).await?;
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
        let new_kv_chooser = Arc::new(chooser);
        self.kv_choosers
            .lock()
            .unwrap()
            .insert(model_name.to_string(), new_kv_chooser.clone());
        Ok(new_kv_chooser)
    }
}

pub struct ModelEngines<E> {
    /// Optional default model name
    default: Option<String>,
    engines: HashMap<String, E>,
}

impl<E> Default for ModelEngines<E> {
    fn default() -> Self {
        Self {
            default: None,
            engines: HashMap::new(),
        }
    }
}

impl<E> ModelEngines<E> {
    #[allow(dead_code)]
    fn set_default(&mut self, model: &str) {
        self.default = Some(model.to_string());
    }

    #[allow(dead_code)]
    fn clear_default(&mut self) {
        self.default = None;
    }

    fn add(&mut self, model: &str, engine: E) -> Result<(), ModelManagerError> {
        if self.engines.contains_key(model) {
            return Err(ModelManagerError::ModelAlreadyExists(model.to_string()));
        }
        self.engines.insert(model.to_string(), engine);
        Ok(())
    }

    fn remove(&mut self, model: &str) -> Result<(), ModelManagerError> {
        if self.engines.remove(model).is_none() {
            return Err(ModelManagerError::ModelNotFound(model.to_string()));
        }
        Ok(())
    }

    fn get(&self, model: &str) -> Option<&E> {
        self.engines.get(model)
    }

    fn contains(&self, model: &str) -> bool {
        self.engines.contains_key(model)
    }

    pub fn list(&self) -> Vec<String> {
        self.engines.keys().map(|k| k.to_owned()).collect()
    }
}