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chore: ml-service port 8000 to 4012

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This commit is contained in:
asepharyana
2026-08-02 16:14:27 +07:00
parent 46d98a3544
commit e18ccab15f
3 changed files with 6 additions and 6 deletions
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apps/ml-service/README.md
+3 -3
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@@ -79,7 +79,7 @@ ML_SERVICE_PORT=9000 MODEL_PATH=/path/to/model.onnx cargo run
| Variable | Default | Keterangan |
|---|---|---|
| `ML_SERVICE_HOST` | `0.0.0.0` | Bind address |
| `ML_SERVICE_PORT` | `8000` | Bind port |
| `ML_SERVICE_PORT` | `4012` | Bind port |
| `MODEL_PATH` | `../../Machine_Learning/model/model.onnx` | Path ke file model ONNX |
| `MODEL_INPUT_SIZE` | `224` | Ukuran input gambar (224×224 untuk EfficientNetV2B0) |
| `RUST_LOG` | `info` | Level logging (debug, info, warn, error) |
@@ -157,7 +157,7 @@ cargo build --release
cargo test
```
### Verifikasi Manual (default port 8000)
### Verifikasi Manual (default port 4012)
```bash
# 1. Start service
@@ -182,7 +182,7 @@ Service dapat di-deploy via Docker. Build dari root repository karena Dockerfile
```bash
docker build -f apps/ml-service/Dockerfile -t zeavis-ml-service .
docker run -p 8000:4012 zeavis-ml-service
docker run -p 4012:4012 zeavis-ml-service
```
Pastikan `Machine_Learning/model/model.onnx` sudah dibuat sebelum build image.
apps/ml-service/src/config.rs
+2 -2
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@@ -30,7 +30,7 @@ impl Config {
pub fn from_env_with_base_dir(base_dir: &Path) -> Result<Self> {
let host = env::var("ML_SERVICE_HOST").unwrap_or_else(|_| "0.0.0.0".to_string());
let port = parse_env_u16("ML_SERVICE_PORT", 8000)?;
let port = parse_env_u16("ML_SERVICE_PORT", 4012)?;
let input_size = parse_env_u32("MODEL_INPUT_SIZE", DEFAULT_INPUT_SIZE)?;
let model_path = env::var("MODEL_PATH").unwrap_or_else(|_| DEFAULT_MODEL_PATH.to_string());
let temperature = parse_env_f32("MODEL_TEMPERATURE", DEFAULT_TEMPERATURE)?;
@@ -116,7 +116,7 @@ mod tests {
let config = Config::from_env_with_base_dir(Path::new("/repo/apps/ml-service")).unwrap();
assert_eq!(config.host, "0.0.0.0");
assert_eq!(config.port, 8000);
assert_eq!(config.port, 4012);
assert_eq!(config.input_size, 224);
assert_eq!(
config.model_path,
apps/web/src/pages/telemetry-page.tsx
+1 -1
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@@ -231,7 +231,7 @@ export function TelemetryPage() {
queryRange(`zeavis_api_http_requests_total{instance="${INST}:4006"}`, 60),
queryRange(`zeavis_api_http_request_duration_seconds_sum{instance="${INST}:4006"} / zeavis_api_http_request_duration_seconds_count{instance="${INST}:4006"}`, 60),
// ML
queryInstant(`zeavis_ml_zeavis_ml_model_load_status{instance="${INST}:8000"}`),
queryInstant(`zeavis_ml_zeavis_ml_model_load_status{instance="${INST}:4012"}`),
// NodeJS
queryInstant(`nodejs_heap_size_used_bytes{instance="${INST}:4006"}`),
queryInstant(`nodejs_heap_size_total_bytes{instance="${INST}:4006"}`),