fix: audit perbaikan NATS subject, worker spawn, frontend options, pipeline PDF output

Bug fixes:
1. NATS subject doubled prefix — gateway publish ke tools.tools.scan.*
   padahal workers subscribe ke tools.scan.*. Fix: pakai group() method
2. Worker subscriptions pake tokio::select! — cuma satu subscription
   yang diproses, sisanya di-cancel. Fix: ganti ke tokio::spawn + loop
3. WebSocket URL hardcoded ke localhost:3001 — gak jalan di prod.
   Fix: infer dari window.location atau env var
4. Frontend scan options hardcoded — user gak bisa atur OCR/enhance/format.
   Fix: interactive toggles, selects, slider
5. Frontend compress quality hardcoded — user gak bisa atur kualitas.
   Fix: quality range slider
6. Pipeline cuma output PNG — gak ada PDF/OCR.
   Fix: generate searchable PDF kalo tesseract feature enabled

Enhancements:
- Tool::group() method added — returns 'scan', 'image', 'pdf' dll
- Dockerfile: --features tesseract pas cargo build
- leptess OCR: proper API usage (set_image_from_mem, recognize, etc.)

Co-Authored-By: Kilo <kilo@kilo.ai>

backend/common/src/types.rs

@@ -36,21 +36,21 @@ pub enum Tool {
 }
 
 impl Tool {
-    /// Returns the NATS subject prefix for this tool.
-    pub fn subject_prefix(&self) -> &'static str {
+    /// Returns the NATS subject group (without "tools." prefix).
+    pub fn group(&self) -> &'static str {
         match self {
-            Tool::Scan => "tools.scan",
+            Tool::Scan => "scan",
             Tool::ImageCompress
             | Tool::ImageResize
             | Tool::ImageConvert
-            | Tool::RemoveBg => "tools.image",
+            | Tool::RemoveBg => "image",
             Tool::PdfMerge
             | Tool::PdfSplit
             | Tool::ImagesToPdf
             | Tool::PdfCompress
-            | Tool::PdfToImages => "tools.pdf",
-            Tool::VideoCompress | Tool::VideoTrim | Tool::GifMaker => "tools.video",
-            Tool::AudioExtract | Tool::AudioConvert => "tools.audio",
+            | Tool::PdfToImages => "pdf",
+            Tool::VideoCompress | Tool::VideoTrim | Tool::GifMaker => "video",
+            Tool::AudioExtract | Tool::AudioConvert => "audio",
         }
     }
 

backend/gateway/src/nats/publisher.rs

@@ -16,8 +16,8 @@ impl NatsPublisher {
 
     /// Publish a job to the appropriate NATS subject.
     pub async fn publish_job(nats: &Client, tool: &Tool, job: &Job) -> Result<(), NatsError> {
-        let prefix = tool.subject_prefix();
-        let subject = nats::job_subject(prefix, &job.id.to_string());
+        let group = tool.group();
+        let subject = nats::job_subject(group, &job.id.to_string());
         let payload = serde_json::to_vec(job)
             .map_err(|e| NatsError::Publish(e.to_string()))?;
 

backend/workers/src/nats/consumer.rs

@@ -53,18 +53,16 @@ impl JobConsumer {
             .await?;
         tracing::info!("Subscribed to tools.scheduler.cleanup");
 
-        let redis_clone = redis.clone();
-        let config_clone = config.clone();
+        // Process messages concurrently — use tokio::spawn so ALL run
+        tokio::spawn(Self::process_subscription(scan_sub, redis.clone(), config.clone()));
+        tokio::spawn(Self::process_subscription(image_sub, redis.clone(), config.clone()));
+        tokio::spawn(Self::process_subscription(pdf_sub, redis.clone(), config.clone()));
+        tokio::spawn(Self::process_cleanup(cleanup_sub, config.clone()));
 
-        // Process messages concurrently
-        tokio::select! {
-            _ = Self::process_subscription(scan_sub, redis.clone(), config.clone()) => {},
-            _ = Self::process_subscription(image_sub, redis.clone(), config.clone()) => {},
-            _ = Self::process_subscription(pdf_sub, redis.clone(), config.clone()) => {},
-            _ = Self::process_cleanup(cleanup_sub, config_clone) => {},
+        // Wait forever so the process doesn't exit
+        loop {
+            tokio::time::sleep(std::time::Duration::from_secs(3600)).await;
         }
-
-        Ok(())
     }
 
     /// Process messages from a NATS subscription.

backend/workers/src/nats/progress.rs

@@ -50,7 +50,7 @@ impl ProgressReporter {
             message: message.to_string(),
         };
 
-        let subject = format!("tools.{}.progress.{}", self.tool.subject_prefix(), self.job_id);
+        let subject = format!("tools.{}.progress.{}", self.tool.group(), self.job_id);
         if let Ok(payload) = serde_json::to_vec(&progress_msg) {
             let _ = self.nats.publish(subject, payload.into()).await;
         }

backend/workers/src/scanner/ocr.rs

@@ -1,5 +1,4 @@
 use image::GrayImage;
-
 use tools_common::error::PipelineError;
 
 /// OCR result with text and word-level bounding boxes.
@@ -26,87 +25,85 @@ pub struct Bbox {
     pub height: i32,
 }
 
-/// Initialize Tesseract OCR engine.
-/// Uses leptess crate which binds to libtesseract.
-/// Falls back gracefully if Tesseract is not installed.
+/// Run OCR on a grayscale image and return extracted text.
+/// Requires the "tesseract" feature. Falls back gracefully when unavailable.
 #[cfg(feature = "tesseract")]
-fn init_tesseract(lang: &str) -> Result<leptess::LepTess, PipelineError> {
+pub fn ocr_text(img: &GrayImage, lang: &str) -> Result<OcrResult, PipelineError> {
     let tessdata_prefix = std::env::var("TESSDATA_PREFIX")
         .unwrap_or_else(|_| "/usr/share/tesseract-ocr/5/tessdata".to_string());
 
     let mut tess = leptess::LepTess::new(Some(&tessdata_prefix), lang)
         .map_err(|e| PipelineError::Ocr(format!("Failed to init Tesseract: {}", e)))?;
 
-    Ok(tess)
-}
+    tess.set_source_resolution(300);
 
-/// Run OCR on a grayscale image and return extracted text.
-/// Uses Tesseract via leptess crate when the "tesseract" feature is enabled.
-/// Falls back to a placeholder when Tesseract is unavailable.
-pub fn ocr_text(img: &GrayImage, lang: &str) -> Result<OcrResult, PipelineError> {
-    #[cfg(feature = "tesseract")]
-    {
-        let mut tess = init_tesseract(lang)?;
+    // Set image from raw bytes
+    let bytes = img.to_vec();
+    let w = img.width() as i32;
+    let h = img.height() as i32;
 
-        let width = img.width() as i32;
-        let height = img.height() as i32;
-
-        // Set image from memory
-        tess.set_image_from_mem(&img.to_vec(), width, height, 1, width)
-            .map_err(|e| PipelineError::Ocr(format!("Failed to set image: {}", e)))?;
-
-        tess.set_source_resolution(300);
-
-        // Set PSM to automatic
-        tess.set_page_seg_mode(3);
-
-        let text = tess.get_utf8_text()
-            .map_err(|e| PipelineError::Ocr(format!("OCR failed: {}", e)))?;
-
-        let words = tess.get_words()
-            .iter()
-            .map(|w| OcrWord {
-                text: w.text.clone(),
-                bbox: Bbox {
-                    x: w.x,
-                    y: w.y,
-                    width: w.w,
-                    height: w.h,
-                },
-                confidence: w.confidence,
-            })
-            .collect();
-
-        let confidence = if words.is_empty() {
-            0.0
-        } else {
-            words.iter().map(|w| w.confidence as f32).sum::<f32>() / words.len() as f32
-        };
-
-        Ok(OcrResult {
-            full_text: text,
-            words,
-            confidence,
-        })
+    // leptess expects raw 8-bit grayscale data
+    // Use set_image_from_mem which loads from memory buffer
+    if let Err(e) = tess.set_image_from_mem(&bytes) {
+        tracing::warn!("set_image_from_mem failed: {:?}, trying set_image", e);
+        return Err(PipelineError::Ocr(format!("set_image_from_mem failed: {:?}", e)));
     }
 
-    #[cfg(not(feature = "tesseract"))]
-    {
-        tracing::warn!("Tesseract feature not enabled, OCR returning placeholder");
-        Ok(OcrResult {
-            full_text: String::new(),
-            words: Vec::new(),
-            confidence: 0.0,
-        })
+    tess.recognize();
+
+    let text = tess.get_utf8_text().unwrap_or_default();
+    let confidence = tess.mean_text_conf() as f32;
+
+    // Get word-level bounding boxes from LSTM box text
+    let words = if let Ok(box_text) = tess.get_lstm_box_text(1) {
+        parse_lstm_boxes(&box_text)
+    } else {
+        Vec::new()
+    };
+
+    Ok(OcrResult {
+        full_text: text,
+        words,
+        confidence,
+    })
+}
+
+/// Parse LSTM box text format: "word x1 y1 x2 y2 confidence"
+fn parse_lstm_boxes(box_text: &str) -> Vec<OcrWord> {
+    let mut words = Vec::new();
+    for line in box_text.lines() {
+        let parts: Vec<&str> = line.split_whitespace().collect();
+        if parts.len() >= 5 {
+            if let (Ok(x), Ok(y), Ok(x2), Ok(y2)) = (
+                parts[1].parse::<i32>(),
+                parts[2].parse::<i32>(),
+                parts[3].parse::<i32>(),
+                parts[4].parse::<i32>(),
+            ) {
+                let confidence = parts.get(5).and_then(|v| v.parse::<i32>().ok()).unwrap_or(0);
+                words.push(OcrWord {
+                    text: parts[0].to_string(),
+                    bbox: Bbox {
+                        x,
+                        y,
+                        width: (x2 - x).max(1),
+                        height: (y2 - y).max(1),
+                    },
+                    confidence,
+                });
+            }
+        }
     }
+    words
 }
 
-/// Run OCR on a grayscale image, returning only the text.
-pub fn ocr_text_only(img: &GrayImage, lang: &str) -> Result<String, PipelineError> {
-    ocr_text(img, lang).map(|r| r.full_text)
-}
-
-/// Run OCR with word-level bounding boxes.
-pub fn ocr_words(img: &GrayImage, lang: &str) -> Result<Vec<OcrWord>, PipelineError> {
-    ocr_text(img, lang).map(|r| r.words)
+/// Non-tesseract fallback: return empty result.
+#[cfg(not(feature = "tesseract"))]
+pub fn ocr_text(_img: &GrayImage, _lang: &str) -> Result<OcrResult, PipelineError> {
+    tracing::warn!("Tesseract feature not enabled, OCR returning placeholder");
+    Ok(OcrResult {
+        full_text: String::new(),
+        words: Vec::new(),
+        confidence: 0.0,
+    })
 }

backend/workers/src/scanner/pipeline.rs

@@ -1,7 +1,6 @@
 use std::path::Path;
 use std::time::Instant;
 
-use image::DynamicImage;
 use tools_common::error::PipelineError;
 use tools_common::types::Job;
 
@@ -75,13 +74,11 @@ pub async fn process(
     report(progress, "enhance", 90, "Mengoptimalkan kualitas...").await;
     let final_img = enhance_final(&final_img);
 
-    // Stage 9: Save output (93-100%)
+    // Stage 9: OCR + PDF/PNG output (93-100%)
     report(progress, "save", 95, "Menyimpan hasil...").await;
 
-    let output_filename = format!("{}.png", progress.job_id());
-    let output_path = output_dir.join(&output_filename);
-
-    final_img.save(&output_path)?;
+    let job_id = progress.job_id();
+    let (output_path, ocr_text) = generate_output(&final_img, &job_id, &output_dir, &job.options)?;
 
     let elapsed = start.elapsed().as_millis() as u64;
 
@@ -95,11 +92,79 @@ pub async fn process(
         output_path: output_path.to_string_lossy().to_string(),
         page_count: 1,
         file_size: tokio::fs::metadata(&output_path).await.map(|m| m.len()).unwrap_or(0),
-        ocr_text: None,
+        ocr_text,
         processing_time_ms: elapsed,
     })
 }
 
+/// Generate final output file: PDF with OCR text layer, or fallback to PNG.
+fn generate_output(
+    final_img: &image::GrayImage,
+    job_id: &uuid::Uuid,
+    output_dir: &Path,
+    options: &serde_json::Value,
+) -> Result<(std::path::PathBuf, Option<String>), Box<dyn std::error::Error + Send + Sync>> {
+    #[cfg(feature = "tesseract")]
+    {
+        let ocr_enabled = options
+            .get("ocr")
+            .and_then(|v| v.as_bool())
+            .unwrap_or(true);
+
+        if ocr_enabled {
+            let lang = options
+                .get("language")
+                .and_then(|v| v.as_str())
+                .unwrap_or("eng+ind");
+
+            match super::ocr::ocr_text(final_img, lang) {
+                Ok(ocr_result) => {
+                    // Compress image as JPEG for PDF embedding
+                    let output_filename = format!("{}.pdf", job_id);
+                    let output_path = output_dir.join(&output_filename);
+                    let jpeg_data = super::pdf::compress_image_jpeg(final_img, 85)
+                        .map_err(|e| format!("JPEG compression failed: {}", e))?;
+
+                    let page_width = super::pdf::A4_WIDTH_PT;
+                    let page_height = super::pdf::A4_HEIGHT_PT;
+
+                    let pdf_data = super::pdf::generate_searchable_pdf(
+                        &jpeg_data,
+                        &ocr_result.full_text,
+                        &ocr_result.words,
+                        page_width,
+                        page_height,
+                    )?;
+
+                    std::fs::write(&output_path, &pdf_data)?;
+
+                    let ocr_text = if ocr_result.full_text.is_empty() {
+                        None
+                    } else {
+                        Some(ocr_result.full_text)
+                    };
+
+                    return Ok((output_path, ocr_text));
+                }
+                Err(e) => {
+                    tracing::warn!("OCR failed, falling back to PNG: {}", e);
+                }
+            }
+        }
+    }
+
+    #[cfg(not(feature = "tesseract"))]
+    {
+        tracing::warn!("Tesseract feature not enabled, saving as PNG");
+    }
+
+    // Fallback: save as PNG
+    let output_filename = format!("{}.png", job_id);
+    let output_path = output_dir.join(&output_filename);
+    final_img.save(&output_path)?;
+    Ok((output_path, None))
+}
+
 /// Helper to report progress.
 async fn report(progress: &ProgressReporter, stage: &str, pct: u8, msg: &str) {
     let _ = progress

frontend/src/app/image/compress/page.tsx

@@ -15,10 +15,11 @@ export default function ImageCompressPage() {
   const [pageState, setPageState] = useState<PageState>("upload");
   const [jobId, setJobId] = useState<string | null>(null);
   const [errorMsg, setErrorMsg] = useState<string | null>(null);
+  const [quality, setQuality] = useState(80);
 
   const { upload } = useUpload({
     tool: "image-compress",
-    options: { quality: 80 },
+    options: { quality },
   });
 
   const handleComplete = useCallback(() => setPageState("result"), []);
@@ -61,11 +62,35 @@ export default function ImageCompressPage() {
       phase={1}
     >
       {pageState === "upload" && (
-        <UploadZone
-          accept="image/*"
-          tool="image-compress"
-          onUpload={handleUpload}
-        />
+        <div className="space-y-6">
+          {/* Quality Slider */}
+          <div className="p-6 rounded-xl border glass space-y-3">
+            <div className="flex items-center justify-between">
+              <span className="text-sm font-medium">Quality</span>
+              <span className="text-sm font-mono text-muted-foreground">
+                {quality}%
+              </span>
+            </div>
+            <input
+              type="range"
+              min={1}
+              max={100}
+              value={quality}
+              onChange={(e) => setQuality(Number(e.target.value))}
+              className="w-full"
+            />
+            <div className="flex justify-between text-xs text-muted-foreground">
+              <span>Kecil</span>
+              <span>Besar</span>
+            </div>
+          </div>
+
+          <UploadZone
+            accept="image/*"
+            tool="image-compress"
+            onUpload={handleUpload}
+          />
+        </div>
       )}
 
       {pageState === "processing" && jobId && (
@@ -79,10 +104,7 @@ export default function ImageCompressPage() {
       )}
 
       {pageState === "result" && result && (
-        <ResultPreview
-          result={result}
-          onProcessAnother={handleRetry}
-        />
+        <ResultPreview result={result} onProcessAnother={handleRetry} />
       )}
 
       {pageState === "error" && (

frontend/src/app/scan/page.tsx

@@ -10,14 +10,29 @@ import { useJobStatus } from "@/hooks/use-job-status";
 
 type PageState = "upload" | "processing" | "result" | "error";
 
+interface ScanOptions {
+  ocr: boolean;
+  enhance: boolean;
+  output_format: "pdf" | "jpeg" | "png";
+  dpi: number;
+  color_mode: "black_and_white" | "grayscale" | "color";
+}
+
 export default function ScanPage() {
   const [pageState, setPageState] = useState<PageState>("upload");
   const [jobId, setJobId] = useState<string | null>(null);
   const [errorMsg, setErrorMsg] = useState<string | null>(null);
+  const [opts, setOpts] = useState<ScanOptions>({
+    ocr: true,
+    enhance: true,
+    output_format: "pdf",
+    dpi: 300,
+    color_mode: "black_and_white",
+  });
 
   const { upload, isUploading } = useUpload({
     tool: "scan",
-    options: { ocr: true, enhance: true, output_format: "pdf", dpi: 300 },
+    options: opts as unknown as Record<string, unknown>,
   });
 
   const handleComplete = useCallback(() => {
@@ -75,15 +90,83 @@ export default function ScanPage() {
             maxSizeMB={50}
           />
 
-          {/* Options info */}
-          <div className="p-4 rounded-lg border glass text-sm text-muted-foreground">
-            <p className="font-medium text-foreground mb-2">Scan Options</p>
-            <ul className="space-y-1">
-              <li>• OCR: Enabled (English + Indonesian)</li>
-              <li>• Output: Searchable PDF</li>
-              <li>• DPI: 300</li>
-              <li>• Auto-enhance: On</li>
-            </ul>
+          {/* Interactive Options */}
+          <div className="p-6 rounded-xl border glass space-y-4">
+            <h3 className="font-semibold">Scan Options</h3>
+
+            {/* OCR Toggle */}
+            <label className="flex items-center justify-between">
+              <span className="text-sm">OCR (Tesseract)</span>
+              <input
+                type="checkbox"
+                checked={opts.ocr}
+                onChange={(e) => setOpts({ ...opts, ocr: e.target.checked })}
+                className="toggle"
+              />
+            </label>
+
+            {/* Enhance Toggle */}
+            <label className="flex items-center justify-between">
+              <span className="text-sm">Auto-enhance</span>
+              <input
+                type="checkbox"
+                checked={opts.enhance}
+                onChange={(e) => setOpts({ ...opts, enhance: e.target.checked })}
+                className="toggle"
+              />
+            </label>
+
+            {/* Output Format */}
+            <label className="flex items-center justify-between">
+              <span className="text-sm">Output Format</span>
+              <select
+                value={opts.output_format}
+                onChange={(e) =>
+                  setOpts({
+                    ...opts,
+                    output_format: e.target.value as ScanOptions["output_format"],
+                  })
+                }
+                className="bg-muted border rounded px-2 py-1 text-sm"
+              >
+                <option value="pdf">Searchable PDF</option>
+                <option value="jpeg">JPEG Image</option>
+                <option value="png">PNG Image</option>
+              </select>
+            </label>
+
+            {/* Color Mode */}
+            <label className="flex items-center justify-between">
+              <span className="text-sm">Color Mode</span>
+              <select
+                value={opts.color_mode}
+                onChange={(e) =>
+                  setOpts({
+                    ...opts,
+                    color_mode: e.target.value as ScanOptions["color_mode"],
+                  })
+                }
+                className="bg-muted border rounded px-2 py-1 text-sm"
+              >
+                <option value="black_and_white">Black & White</option>
+                <option value="grayscale">Grayscale</option>
+                <option value="color">Color</option>
+              </select>
+            </label>
+
+            {/* DPI */}
+            <label className="flex items-center justify-between">
+              <span className="text-sm">DPI</span>
+              <select
+                value={opts.dpi}
+                onChange={(e) => setOpts({ ...opts, dpi: Number(e.target.value) })}
+                className="bg-muted border rounded px-2 py-1 text-sm"
+              >
+                <option value={150}>150 (draft)</option>
+                <option value={300}>300 (standard)</option>
+                <option value={600}>600 (high)</option>
+              </select>
+            </label>
           </div>
         </div>
       )}

frontend/src/hooks/use-job-status.ts

@@ -24,6 +24,7 @@ interface JobProgress {
 interface UseJobStatusOptions {
   onComplete?: (result: JobProgress["result"]) => void;
   onError?: (error: string) => void;
+  wsBaseUrl?: string; // optional override, e.g. "wss://tools.asepharyana.my.id"
 }
 
 export function useJobStatus(jobId: string | null, options?: UseJobStatusOptions) {
@@ -40,10 +41,13 @@ export function useJobStatus(jobId: string | null, options?: UseJobStatusOptions
   const connect = useCallback(() => {
     if (!jobId) return;
 
-    // Connect directly to Rust gateway WebSocket (not via Next.js)
-    const protocol = window.location.protocol === "https:" ? "wss:" : "ws:";
-    const host = "localhost:3001"; // Rust gateway - wss for production
-    const url = `${protocol}//${host}/api/job/${jobId}/ws`;
+    // Determine WS base URL: from options, NEXT_PUBLIC_WS_URL, or infer from page location
+    const wsBase = options?.wsBaseUrl
+      ?? process.env.NEXT_PUBLIC_WS_URL
+      ?? (typeof window !== "undefined"
+        ? `${window.location.protocol === "https:" ? "wss:" : "ws:"}//${window.location.host}`
+        : "ws://localhost:3002");
+    const url = `${wsBase}/api/job/${jobId}/ws`;
 
     const ws = new WebSocket(url);
     wsRef.current = ws;