Kazeia-engine/dist/jni/EngineLlmEngine.kt

49 lines
2.2 KiB
Kotlin

package com.kazeia.llm
// Remplace ExecuTorchLlmEngine. Option C: prefill HTP / decode CPU (géré côté natif).
// Mono-tour: generate(sys, usr). Multi-tour: ChatSession (gère l'historique + le template ChatML).
class EngineJni {
external fun load(ggufPath: String, nCtx: Int): Long
external fun generate(h: Long, sys: String, usr: String, maxTok: Int): String
external fun generateRaw(h: Long, prompt: String, maxTok: Int): String // prompt complet déjà formaté
external fun reset(h: Long)
external fun free(h: Long)
companion object { init { System.loadLibrary("kazeia_engine") } }
}
class EngineLlmEngine(model: String, ctx: Int = 4096) {
private val jni = EngineJni()
private val h = jni.load(model, ctx)
init { require(h != 0L) { "Kazeia-Engine: échec du chargement du modèle ($model)" } }
// Mono-tour : system + un message user.
fun generate(sys: String, usr: String, max: Int = 96) = jni.generate(h, sys, usr, max)
// Multi-tour : prompt complet pré-formaté (voir ChatSession).
fun generateRaw(prompt: String, max: Int = 96) = jni.generateRaw(h, prompt, max)
fun newChat(system: String) = ChatSession(this, system)
fun reset() = jni.reset(h)
fun release() = jni.free(h)
}
// Conversation multi-tour : accumule l'historique et construit le ChatML Qwen3.5 + thinking-off.
// Structure identique à celle validée (jni/dual_ctx_mt.cpp) : mémoire conversationnelle correcte.
class ChatSession(private val engine: EngineLlmEngine, private val system: String) {
private val turns = StringBuilder() // "<|im_start|>role\ntext<|im_end|>\n" accumulés
fun ask(user: String, max: Int = 96): String {
val prompt = buildString {
append("<|im_start|>system\n").append(system).append("<|im_end|>\n")
append(turns)
append("<|im_start|>user\n").append(user).append("<|im_end|>\n")
append("<|im_start|>assistant\n<think>\n\n</think>\n\n") // thinking OFF déterministe
}
val resp = engine.generateRaw(prompt, max)
turns.append("<|im_start|>user\n").append(user).append("<|im_end|>\n")
.append("<|im_start|>assistant\n").append(resp).append("<|im_end|>\n")
return resp
}
fun clear() { turns.setLength(0) }
}