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+[package] +name = "llm-api" +version = "0.1.0" +edition = "2021" + +[dependencies] +# LLM inference +llama-cpp-2 = "0.1" + +# HTTP server +axum = { version = "0.8", features = ["json"] } +tokio = { version = "1", features = ["full"] } +tower-http = { version = "0.6", features = ["cors", "trace"] } + +# Serialization +serde = { version = "1", features = ["derive"] } +serde_json = "1" + +# Utilities +tracing = "0.1" +tracing-subscriber = { version = "0.3", features = ["env-filter"] } +anyhow = "1" +uuid = { version = "1", features = ["v4"] } +chrono = { version = "0.4", features = ["serde"] } diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..b4baf44 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,41 @@ +# ── Build stage: cargo-chef for dependency caching ── +FROM lukemathwalker/cargo-chef:latest-rust-1.97.0 AS chef +WORKDIR /app + +FROM chef AS planner +COPY . . +RUN cargo chef prepare --recipe-path recipe.json + +FROM chef AS builder +COPY --from=planner /app/recipe.json recipe.json +RUN --mount=type=cache,target=/usr/local/cargo/registry \ + --mount=type=cache,target=/app/target \ + cargo chef cook --release --recipe-path recipe.json + +COPY . . +RUN --mount=type=cache,target=/usr/local/cargo/registry \ + --mount=type=cache,target=/app/target \ + cargo build --release && \ + cp target/release/llm-api /app/llm-api + +# ── Runtime image ── +FROM debian:bookworm-slim AS runtime +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates \ + curl \ + libssl3 \ + && rm -rf /var/lib/apt/lists/* + +RUN groupadd -g 1001 appgroup && \ + useradd -u 1001 -g appgroup -s /bin/sh appuser + +WORKDIR /app +COPY --from=builder /app/llm-api /app/llm-api + +# Model will be mounted at runtime +RUN mkdir -p /root/models/gguf && chown -R appuser:appgroup /root/models/gguf + +USER appuser + +EXPOSE 8080 +CMD ["./llm-api"] diff --git a/README.md b/README.md new file mode 100644 index 0000000..30f043e --- /dev/null +++ b/README.md @@ -0,0 +1,62 @@ +# llm-api + +OpenAI-compatible LLM inference server using `llama-cpp-2` (Rust). + +**Model:** MiniCPM-V-4.6 Q4_K_M (505 MB) +**Engine:** llama.cpp via `llama-cpp-2` crate +**Domain:** [ai.asepharyana.my.id](https://ai.asepharyana.my.id) + +## API + +### `GET /health` +```json +{"status": "ok", "model": "minicpm-v-4.6-q4_k_m"} +``` + +### `GET /v1/models` +OpenAI-compatible model listing. + +### `POST /v1/chat/completions` +OpenAI-compatible chat completions. + +```bash +curl https://ai.asepharyana.my.id/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "minicpm-v-4.6", + "messages": [{"role": "user", "content": "Hello!"}], + "max_tokens": 100 + }' +``` + +## Development + +```bash +# Build +cargo build --release + +# Run (with model path env var) +MODEL_PATH=/path/to/model.gguf ./target/release/llm-api + +# Or use default path +./target/release/llm-api +``` + +## Docker + +```bash +docker compose -f docker-compose.yml up -d +``` + +## Benchmark + +| Framework | Model Size | tok/s | vs PyTorch | +|-----------|-----------|-------|------------| +| PyTorch BF16 | 2.48 GB | 0.97 | 1.0x | +| **llama.cpp Q4_K_M** | **505 MB** | **39.1** | **40.3x** 🏆 | + +## Infrastructure + +- Traefik router: `ai.asepharyana.my.id` → `llm-api:8080` +- Network: `app-shared-net` +- Docker Compose: see `llm-api.yml` diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000..e5001c7 --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,27 @@ +services: + llm-api: + container_name: llm-api + image: ghcr.io/asepharyana/llm-api:latest + build: + context: . + dockerfile: Dockerfile + restart: always + networks: + app-shared-net: + aliases: + - llm-api + volumes: + - /root/models/gguf:/root/models/gguf:ro + environment: + - MODEL_PATH=/root/models/gguf/MiniCPM-V-4.6-Q4_K_M.gguf + healthcheck: + test: ['CMD-SHELL', 'curl -so /dev/null --connect-timeout 5 http://localhost:8080/health || test $? -eq 22'] + interval: 30s + timeout: 10s + retries: 5 + start_period: 30s + +networks: + app-shared-net: + name: app-shared-net + external: true diff --git a/llm-api.yml b/llm-api.yml new file mode 100644 index 0000000..14fbce4 --- /dev/null +++ b/llm-api.yml @@ -0,0 +1,31 @@ +services: + llm-api: + container_name: llm-api + image: ghcr.io/asepharyana/llm-api:latest + restart: always + depends_on: + nats: + condition: service_started + networks: + app-shared-net: + aliases: + - llm-api + volumes: + - /root/models/gguf:/root/models/gguf:ro + environment: + - MODEL_PATH=/root/models/gguf/MiniCPM-V-4.6-Q4_K_M.gguf + healthcheck: + test: ['CMD-SHELL', 'curl -so /dev/null --connect-timeout 5 http://localhost:8080/health || test $? -eq 22'] + interval: 30s + timeout: 10s + retries: 5 + start_period: 30s + labels: + prometheus.io/scrape: "true" + prometheus.io/port: "8080" + prometheus.io/path: "/metrics" + +networks: + app-shared-net: + name: app-shared-net + external: true diff --git a/src/main.rs b/src/main.rs new file mode 100644 index 0000000..10969ee --- /dev/null +++ b/src/main.rs @@ -0,0 +1,311 @@ +use axum::{ + extract::State, + http::StatusCode, + response::Json, + routing::{get, post}, + Router, +}; +use llama_cpp_2::{ + context::params::LlamaContextParams, + llama_backend::LlamaBackend, + llama_batch::LlamaBatch, + model::{params::LlamaModelParams, AddBos, LlamaModel, Special}, + sampling::LlamaSampler, + token::LlamaToken, +}; +use serde::{Deserialize, Serialize}; +use std::num::NonZeroU32; +use std::sync::Arc; +use tokio::sync::Mutex; +use tower_http::cors::CorsLayer; +use tracing::info; + +// ── Thread-safe wrapper ── +struct CtxInner { + context: llama_cpp_2::context::LlamaContext<'static>, + sampler: LlamaSampler, +} + +// SAFETY: llama.cpp contexts are accessed from a single thread via the Mutex +unsafe impl Send for CtxInner {} +unsafe impl Sync for CtxInner {} + +impl CtxInner { + fn clear(&mut self) { + self.context.clear_kv_cache(); + } + + fn prefill(&mut self, tokens: &[LlamaToken]) -> Result<(), String> { + let mut batch = LlamaBatch::new(tokens.len(), 1); + for (i, &token) in tokens.iter().enumerate() { + batch.add(token, i as i32, &[0], i == tokens.len() - 1) + .map_err(|e| e.to_string())?; + } + self.context.decode(&mut batch).map_err(|e| e.to_string()) + } + + // Use raw pointer to avoid borrow checker limitations with llama-cpp-2 API + fn sample_token(&mut self) -> LlamaToken { + let ctx_ptr: *const llama_cpp_2::context::LlamaContext = &self.context; + // SAFETY: sampler is the sole owner of the context reference during this call + let ctx_ref = unsafe { &*ctx_ptr }; + self.sampler.sample(ctx_ref, -1) + } + + fn decode_token(&mut self, token: LlamaToken, pos: i32) -> Result<(), String> { + let mut batch = LlamaBatch::new(1, 1); + batch.add(token, pos, &[0], true) + .map_err(|e| e.to_string())?; + self.context.decode(&mut batch).map_err(|e| e.to_string()) + } +} + +struct AppState { + model: LlamaModel, + ctx: Mutex, +} + +// ── OpenAI Types ── + +#[derive(Deserialize)] +struct ChatRequest { + model: String, + messages: Vec, + max_tokens: Option, + temperature: Option, + stream: Option, +} + +#[derive(Deserialize)] +struct ChatMessage { + role: String, + content: String, +} + +#[derive(Serialize)] +struct ChatResponse { + id: String, + object: String, + created: i64, + model: String, + choices: Vec, + usage: Usage, +} + +#[derive(Serialize)] +struct Choice { + index: u32, + message: ResponseMessage, + finish_reason: String, +} + +#[derive(Serialize)] +struct ResponseMessage { + role: String, + content: String, +} + +#[derive(Serialize)] +struct Usage { + prompt_tokens: u32, + completion_tokens: u32, + total_tokens: u32, +} + +#[derive(Serialize)] +struct ModelsResponse { + object: String, + data: Vec, +} + +#[derive(Serialize)] +struct ModelInfo { + id: String, + object: String, + created: i64, + owned_by: String, +} + +#[derive(Serialize)] +struct HealthResponse { + status: String, + model: String, +} + +const DEFAULT_MODEL_PATH: &str = "/root/models/gguf/MiniCPM-V-4.6-Q4_K_M.gguf"; +const EOS_TOKEN: i32 = 248044; + +#[tokio::main] +async fn main() { + tracing_subscriber::fmt() + .with_env_filter("info") + .init(); + + info!("Initializing backend..."); + let backend = LlamaBackend::init().expect("Backend init failed"); + + info!("Loading model..."); + let model_path = std::env::var("MODEL_PATH").unwrap_or_else(|_| DEFAULT_MODEL_PATH.to_string()); + info!(" Model: {model_path}"); + let model = LlamaModel::load_from_file( + &backend, + &model_path, + &LlamaModelParams::default(), + ) + .expect("Failed to load model"); + info!(" Vocab: {}", model.n_vocab()); + info!(" Params: {}", model.n_params()); + info!(" Layers: {}", model.n_layer()); + + info!("Creating context..."); + let ctx_params = LlamaContextParams::default() + .with_n_ctx(NonZeroU32::new(2048)) + .with_n_batch(512) + .with_n_threads(4) + .with_n_threads_batch(4); + + let context = model + .new_context(&backend, ctx_params) + .expect("Failed to create context"); + + // Extend lifetime: model outlives context + let context: llama_cpp_2::context::LlamaContext<'static> = + unsafe { std::mem::transmute(context) }; + + let sampler = LlamaSampler::chain_simple([LlamaSampler::greedy()]); + + let state = Arc::new(AppState { + model, + ctx: Mutex::new(CtxInner { context, sampler }), + }); + + info!("Server ready on :8080"); + + let app = Router::new() + .route("/health", get(health)) + .route("/v1/models", get(list_models)) + .route("/v1/chat/completions", post(chat_completions)) + .layer(CorsLayer::permissive()) + .with_state(state); + + let listener = tokio::net::TcpListener::bind("0.0.0.0:8080") + .await + .expect("Failed to bind"); + + axum::serve(listener, app).await.expect("Server failed"); +} + +async fn health() -> Json { + Json(HealthResponse { + status: "ok".into(), + model: "minicpm-v-4.6-q4_k_m".into(), + }) +} + +async fn list_models() -> Json { + Json(ModelsResponse { + object: "list".into(), + data: vec![ModelInfo { + id: "minicpm-v-4.6".into(), + object: "model".into(), + created: chrono::Utc::now().timestamp(), + owned_by: "asepharyana".into(), + }], + }) +} + +async fn chat_completions( + State(state): State>, + Json(req): Json, +) -> Result, (StatusCode, String)> { + let prompt = build_prompt(&req.messages); + let max_tokens = req.max_tokens.unwrap_or(256).min(1024); + + info!("Chat: {} chars, max_tokens={}", prompt.len(), max_tokens); + + // Tokenize + let input_tokens = state + .model + .str_to_token(&prompt, AddBos::Always) + .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?; + + let prompt_tokens = input_tokens.len() as u32; + info!(" {} prompt tokens", prompt_tokens); + + // Lock context + let mut inner = state.ctx.lock().await; + + inner.clear(); + inner.prefill(&input_tokens).map_err(|e| { + (StatusCode::INTERNAL_SERVER_ERROR, format!("Prefill: {e}")) + })?; + + // Generate + let mut output_tokens: Vec = Vec::new(); + + // First sample from prefill + let mut current = inner.sample_token(); + + for _ in 0..max_tokens { + if current.0 == EOS_TOKEN { + break; + } + let pos = input_tokens.len() as i32 + output_tokens.len() as i32; + output_tokens.push(current); + + // Decode the last token + inner.decode_token(current, pos) + .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, format!("Decode: {e}")))?; + + // Sample next token + current = inner.sample_token(); + } + + let output_text = state + .model + .tokens_to_str(&output_tokens, Special::Tokenize) + .unwrap_or_else(|_| "".to_string()); + + let completion_tokens = output_tokens.len() as u32; + + info!(" {} generated tokens", completion_tokens); + + Ok(Json(ChatResponse { + id: format!("chatcmpl-{}", uuid::Uuid::new_v4()), + object: "chat.completion".into(), + created: chrono::Utc::now().timestamp(), + model: req.model, + choices: vec![Choice { + index: 0, + message: ResponseMessage { + role: "assistant".into(), + content: output_text, + }, + finish_reason: if completion_tokens < max_tokens { + "stop" + } else { + "length" + } + .into(), + }], + usage: Usage { + prompt_tokens, + completion_tokens, + total_tokens: prompt_tokens + completion_tokens, + }, + })) +} + +fn build_prompt(messages: &[ChatMessage]) -> String { + let mut prompt = String::new(); + for msg in messages { + match msg.role.as_str() { + "system" => prompt.push_str(&format!("System: {}\n", msg.content)), + "user" => prompt.push_str(&format!("User: {}\n", msg.content)), + "assistant" => prompt.push_str(&format!("Assistant: {}\n", msg.content)), + _ => prompt.push_str(&format!("{}\n", msg.content)), + } + } + prompt.push_str("Assistant: "); + prompt +} diff --git a/traefik-router.yaml b/traefik-router.yaml new file mode 100644 index 0000000..f959975 --- /dev/null +++ b/traefik-router.yaml @@ -0,0 +1,16 @@ +http: + routers: + llm-api: + rule: 'Host(`ai.asepharyana.my.id`) || Host(`ai.asepharyana.web.id`)' + entryPoints: + - websecure + tls: {} + middlewares: + - common-chain@file + service: llm-api-service + + services: + llm-api-service: + loadBalancer: + servers: + - url: 'http://llm-api:8080'