diff --git a/app/main.py b/app/main.py
index 342f699..020d0a6 100644
--- a/app/main.py
+++ b/app/main.py
@@ -235,6 +235,35 @@ class StartUpscaleRequest(BaseModel):
     ai_face_restoration: bool = False
     ai_rife_interpolation: bool = False
     ai_audio_denoise: bool = False
+    temp_dir: str | None = None
+
+class StartBatchUpscaleRequest(BaseModel):
+    file_ids: List[str]
+    model: str = "realesr-animevideov3"
+    scale: int = 4
+    tile_size: int = 256
+    preserve_audio: bool = True
+    ss: str | None = None
+    t: str | None = None
+    gpu_ids: str | None = None
+    tta: bool = False
+    unsharp: bool = False
+    double_fps: bool = False
+    preserve_subtitles: bool = True
+    start_sec: float | None = None
+    end_sec: float | None = None
+    crf: int = 18
+    preset: str = "medium"
+    denoise: bool = False
+    sharpen: bool = False
+    interpolation: bool = False
+    webhook_url: str | None = None
+    transcode_format: str = "mp4"
+    is_preview: bool = False
+    ai_face_restoration: bool = False
+    ai_rife_interpolation: bool = False
+    ai_audio_denoise: bool = False
+    temp_dir: str | None = None
 
 class PreviewRequest(BaseModel):
     file_id: str
@@ -422,7 +451,8 @@ def start_upscale(req: StartUpscaleRequest):
         is_preview=req.is_preview,
         ai_face_restoration=req.ai_face_restoration,
         ai_rife_interpolation=req.ai_rife_interpolation,
-        ai_audio_denoise=req.ai_audio_denoise
+        ai_audio_denoise=req.ai_audio_denoise,
+        temp_dir=req.temp_dir
     )
     
     jobs_db[job_id] = job
@@ -443,6 +473,80 @@ def start_upscale(req: StartUpscaleRequest):
         "status": "queued"
     }
 
+@app.post("/api/upscale/start/batch")
+def start_upscale_batch(req: StartBatchUpscaleRequest):
+    """Queue multiple upscaling tasks with one set of settings"""
+    queued_jobs = []
+    
+    # 1. Validation loop
+    for file_id in req.file_ids:
+        file_path = None
+        exts = [".mp4", ".mkv", ".avi", ".mov", ".webm"]
+        for ext in exts:
+            test_path = os.path.join(upscaler.UPLOAD_DIR, f"{file_id}{ext}")
+            if os.path.exists(test_path):
+                file_path = test_path
+                break
+        if not file_path:
+            raise HTTPException(status_code=404, detail=f"Uploaded file {file_id} not found.")
+            
+    # 2. Queueing loop
+    for file_id in req.file_ids:
+        file_path = None
+        for ext in [".mp4", ".mkv", ".avi", ".mov", ".webm"]:
+            test_path = os.path.join(upscaler.UPLOAD_DIR, f"{file_id}{ext}")
+            if os.path.exists(test_path):
+                file_path = test_path
+                break
+                
+        job_id = str(uuid.uuid4())
+        job = upscaler.UpscaleJob(
+            job_id=job_id,
+            video_path=file_path,
+            model=req.model,
+            scale=req.scale,
+            tile_size=req.tile_size,
+            preserve_audio=req.preserve_audio,
+            ss=req.ss,
+            t=req.t,
+            gpu_ids=req.gpu_ids,
+            tta=req.tta,
+            unsharp=req.unsharp,
+            double_fps=req.double_fps,
+            preserve_subtitles=req.preserve_subtitles,
+            start_sec=req.start_sec,
+            end_sec=req.end_sec,
+            crf=req.crf,
+            preset=req.preset,
+            denoise=req.denoise,
+            sharpen=req.sharpen,
+            interpolation=req.interpolation,
+            webhook_url=req.webhook_url,
+            transcode_format=req.transcode_format,
+            is_preview=req.is_preview,
+            ai_face_restoration=req.ai_face_restoration,
+            ai_rife_interpolation=req.ai_rife_interpolation,
+            ai_audio_denoise=req.ai_audio_denoise,
+            temp_dir=req.temp_dir
+        )
+        jobs_db[job_id] = job
+        job_queue.put(job_id)
+        queued_jobs.append({"job_id": job_id, "status": "queued"})
+        
+    save_jobs_db()
+    
+    # Broadcast initial queued progress for all queued jobs
+    for qj in queued_jobs:
+        broadcast_progress(qj["job_id"], {
+            "status": "queued",
+            "progress": 0.0,
+            "current_frame": 0,
+            "total_frames": 0,
+            "eta": "Calculating..."
+        })
+        
+    return {"jobs": queued_jobs}
+
 @app.get("/api/upscale/status/{job_id}")
 def get_status(job_id: str):
     """Get status of upscale job"""
@@ -699,7 +803,7 @@ def get_queue():
 
 @app.post("/api/upscale/resume/{job_id}")
 def resume_job(job_id: str):
-    """Resume an interrupted/failed upscale job"""
+    """Resume an interrupted/failed/paused upscale job"""
     job = jobs_db.get(job_id)
     if not job:
         raise HTTPException(status_code=404, detail="Job not found.")
@@ -708,6 +812,8 @@ def resume_job(job_id: str):
     job.status = "queued"
     job.error = None
     job.eta = "Queued for resume..."
+    if hasattr(job, "_is_paused"):
+        job._is_paused = False
     
     job_queue.put(job_id)
     save_jobs_db()
@@ -722,6 +828,33 @@ def resume_job(job_id: str):
     
     return {"job_id": job_id, "status": "queued"}
 
+@app.post("/api/upscale/pause/{job_id}")
+def pause_job(job_id: str):
+    """Pause a running or queued job"""
+    job = jobs_db.get(job_id)
+    if not job:
+        raise HTTPException(status_code=404, detail="Job not found.")
+        
+    if job.status not in ["queued", "pending", "analyzing", "extracting", "upscaling", "restoring_faces", "interpolating", "assembling"]:
+        raise HTTPException(status_code=400, detail=f"Job in status {job.status} cannot be paused.")
+        
+    # Remove from queue if it is in queue
+    job_queue.remove(job_id)
+    
+    # Call pause logic on the job
+    job.pause()
+    save_jobs_db()
+    
+    broadcast_progress(job_id, {
+        "status": "paused",
+        "progress": job.progress,
+        "current_frame": job.current_frame,
+        "total_frames": job.total_frames,
+        "eta": "Paused"
+    })
+    
+    return {"job_id": job_id, "status": "paused"}
+
 # Websocket endpoint for real-time progress updates
 @app.websocket("/ws/progress/{job_id}")
 async def websocket_progress(websocket: WebSocket, job_id: str):
diff --git a/app/upscaler.py b/app/upscaler.py
index 7ea583d..3822a66 100644
--- a/app/upscaler.py
+++ b/app/upscaler.py
@@ -26,8 +26,9 @@ class UpscaleJob:
                  denoise: bool = False, sharpen: bool = False, interpolation: bool = False, 
                  webhook_url: str = None, transcode_format: str = "mp4", is_preview: bool = False,
                  ai_face_restoration: bool = False, ai_rife_interpolation: bool = False,
-                 ai_audio_denoise: bool = False):
+                 ai_audio_denoise: bool = False, temp_dir: str = None):
         self.job_id = job_id
+        self.temp_dir = temp_dir
         self.video_path = video_path
         self.model = model
         self.scale = scale
@@ -79,9 +80,10 @@ class UpscaleJob:
         self.start_time = None
         self.output_file = None
         
-        # Track processes to allow cancellation
+        # Track processes to allow cancellation/pause
         self._processes = []
         self._is_cancelled = False
+        self._is_paused = False
         self._lock = threading.Lock()
 
     def to_dict(self) -> dict:
@@ -106,6 +108,7 @@ class UpscaleJob:
             setattr(job, k, v)
         job._processes = []
         job._is_cancelled = False
+        job._is_paused = data.get('_is_paused', False) or (data.get('status') == 'paused')
         job._lock = threading.Lock()
         return job
 
@@ -137,10 +140,32 @@ class UpscaleJob:
                         pass
             self._processes.clear()
 
+    def pause(self):
+        with self._lock:
+            if self.status in ["queued", "pending"]:
+                self.status = "paused"
+                self.eta = "Paused"
+            elif self.status in ["analyzing", "extracting", "upscaling", "restoring_faces", "interpolating", "assembling"]:
+                self._is_paused = True
+                self.status = "paused"
+                self.eta = "Paused"
+                for p in self._processes:
+                    try:
+                        p.terminate()
+                        p.wait(timeout=2)
+                    except Exception:
+                        try:
+                            p.kill()
+                        except Exception:
+                            pass
+                self._processes.clear()
+
     def run_command(self, cmd: list, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=False) -> subprocess.Popen:
         with self._lock:
             if self._is_cancelled:
                 raise InterruptedError("Job was cancelled")
+            if getattr(self, "_is_paused", False):
+                raise InterruptedError("Job was paused")
             
             p = subprocess.Popen(
                 cmd,
@@ -240,6 +265,7 @@ def upscale_image_file(input_path: str, output_path: str, model: str, scale: int
         return False
 
 def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dict[str, Any]], None]):
+    print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] starting pipeline. Video path: {job.video_path}, Model: {job.model}, Scale: {job.scale}")
     job.start_time = time.time()
     job.update_status("analyzing", progress=5)
     
@@ -254,7 +280,8 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
     fps = info["fps"]
     
     # Create job temp directories
-    job_temp_dir = os.path.join(TEMP_DIR, job.job_id)
+    base_temp = job.temp_dir if getattr(job, "temp_dir", None) else TEMP_DIR
+    job_temp_dir = os.path.join(base_temp, job.job_id)
     input_frames_dir = os.path.join(job_temp_dir, "input_frames")
     output_frames_dir = os.path.join(job_temp_dir, "output_frames")
     
@@ -299,6 +326,7 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
         if not skip_extraction:
             job.update_status("extracting", progress=10)
             on_progress_update(job.job_id, {"status": "extracting", "progress": 10})
+            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] extracting frames. Command: {' '.join(extract_cmd)}")
             
             # High quality JPG frames to balance disk usage and speed
             extract_cmd = ["ffmpeg", "-y"]
@@ -327,6 +355,7 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
             # Count actual frames extracted
             extracted_files = sorted([f for f in os.listdir(input_frames_dir) if f.startswith("frame_")])
             actual_total = len(extracted_files)
+            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] extraction completed. Extracted {actual_total} frames.")
             if actual_total == 0:
                 raise RuntimeError("No frames extracted from video")
                 
@@ -384,6 +413,7 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
                 upscale_stderr_path = os.path.join(job_temp_dir, "upscale_stderr.log")
                 
                 with open(upscale_stdout_path, "w") as f_out, open(upscale_stderr_path, "w") as f_err:
+                    print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] starting realesrgan upscaling. Model: {job.model}, Tile size: {current_tile_size}. Command: {' '.join(upscale_cmd)}")
                     p_upscale = job.run_command(upscale_cmd, stdout=f_out, stderr=f_err)
                     
                     # Monitor thread for output files
@@ -479,7 +509,7 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
             gfpgan_installed = importlib.util.find_spec("gfpgan") is not None
             
             if gfpgan_installed:
-                print(f"Job {job.job_id}: GFPGAN detected. Running Face Restoration...")
+                print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] starting GFPGAN face restoration.")
                 restored_dir = os.path.join(job_temp_dir, "restored_frames")
                 os.makedirs(restored_dir, exist_ok=True)
                 
@@ -521,6 +551,7 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
         if getattr(job, "ai_rife_interpolation", False):
             rife_bin = os.path.join(BASE_DIR, "rife-bin", "rife-ncnn-vulkan")
             if os.path.isfile(rife_bin):
+                print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] starting RIFE frame interpolation.")
                 job.update_status("interpolating", progress=83.0)
                 on_progress_update(job.job_id, {"status": "interpolating", "progress": 83.0})
                 os.makedirs(rife_frames_dir, exist_ok=True)
@@ -630,6 +661,7 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
             out_filepath
         ])
         
+        print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] starting video assembly. Command: {' '.join(assemble_cmd)}")
         p_assemble = job.run_command(assemble_cmd)
         stdout, stderr = p_assemble.communicate()
         job.cleanup_process(p_assemble)
@@ -645,13 +677,17 @@ def run_upscale_pipeline(job: UpscaleJob, on_progress_update: Callable[[str, Dic
             "eta": "Done",
             "output_file": out_filename
         })
+        print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] pipeline completed successfully. Output file: {job.output_file}")
         
     except Exception as e:
         import traceback
         traceback.print_exc()
-        if not job._is_cancelled:
+        if not job._is_cancelled and not getattr(job, "_is_paused", False) and job.status != "paused":
             job.update_status("failed", error=str(e))
             on_progress_update(job.job_id, {"status": "failed", "error": str(e)})
+            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] pipeline failed. Error: {e}")
+        else:
+            print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] [Job {job.job_id}] pipeline halted. Status: {job.status}")
     finally:
         # Clean up temp frames to save space only if completed or cancelled
         try:
diff --git a/static/app.js b/static/app.js
index fefb3e5..b174788 100644
--- a/static/app.js
+++ b/static/app.js
@@ -241,13 +241,99 @@ if (uploadModelBtn) {
 dropZone.addEventListener('drop', (e) => {
     const dt = e.dataTransfer;
     const files = dt.files;
-    if (files.length) handleVideoUpload(files[0]);
+    if (files.length > 1) {
+        handleBatchUpload(files);
+    } else if (files.length === 1) {
+        handleVideoUpload(files[0]);
+    }
 });
 
 fileInput.addEventListener('change', (e) => {
-    if (e.target.files.length) handleVideoUpload(e.target.files[0]);
+    const files = e.target.files;
+    if (files.length > 1) {
+        handleBatchUpload(files);
+    } else if (files.length === 1) {
+        handleVideoUpload(files[0]);
+    }
 });
 
+function resetDropZone() {
+    dropZone.innerHTML = `
+        <span class="upload-icon"><i class="fa-solid fa-cloud-arrow-up"></i></span>
+        <h3>Drag & Drop Video File(s)</h3>
+        <p>Supports MP4, MKV, AVI, MOV, WEBM (Max 500MB recommended for local upscaling)</p>
+        <button type="button" class="btn" onclick="document.getElementById('file-input').click()">
+            <i class="fa-solid fa-folder-open"></i> Browse Files
+        </button>
+    `;
+}
+
+async function handleBatchUpload(files) {
+    const totalFiles = files.length;
+    let uploadedCount = 0;
+    
+    dropZone.innerHTML = `
+        <div class="spinner" style="margin: 0 auto 1.5rem auto;"></div>
+        <h3>Uploading <span id="batch-upload-current">1</span> of ${totalFiles} Files...</h3>
+        <p id="upload-progress-text">Preparing batch upload...</p>
+        <div class="bar-container" style="max-width: 400px; margin: 1rem auto; height: 10px;">
+            <div id="upload-bar" class="bar-fill" style="width: 0%;"></div>
+        </div>
+    `;
+    
+    const progressText = document.getElementById("upload-progress-text");
+    const progressBar = document.getElementById("upload-bar");
+    const currentText = document.getElementById("batch-upload-current");
+    
+    for (let i = 0; i < totalFiles; i++) {
+        const file = files[i];
+        if (currentText) currentText.textContent = i + 1;
+        if (progressText) progressText.textContent = `Uploading "${file.name}"...`;
+        if (progressBar) progressBar.style.width = "0%";
+        
+        try {
+            await new Promise((resolve, reject) => {
+                const formData = new FormData();
+                formData.append("file", file);
+                
+                const xhr = new XMLHttpRequest();
+                xhr.open("POST", "/api/upload", true);
+                
+                xhr.upload.addEventListener("progress", (e) => {
+                    if (e.lengthComputable) {
+                        const percentComplete = (e.loaded / e.total) * 100;
+                        if (progressText) {
+                            progressText.textContent = `Uploading "${file.name}": ${formatBytes(e.loaded)} / ${formatBytes(e.total)} (${Math.round(percentComplete)}%)`;
+                        }
+                        if (progressBar) progressBar.style.width = `${percentComplete}%`;
+                    }
+                });
+                
+                xhr.onload = function() {
+                    if (xhr.status === 200) {
+                        resolve(JSON.parse(xhr.responseText));
+                    } else {
+                        reject(new Error(`Upload failed for ${file.name}`));
+                    }
+                };
+                
+                xhr.onerror = function() {
+                    reject(new Error(`Network error uploading ${file.name}`));
+                };
+                
+                xhr.send(formData);
+            });
+            uploadedCount++;
+        } catch (err) {
+            console.error(err);
+            alert(`Error uploading "${file.name}": ${err.message}`);
+        }
+    }
+    
+    await loadUploadsBrowser();
+    resetDropZone();
+}
+
 function formatBytes(bytes, decimals = 2) {
     if (bytes === 0) return '0 Bytes';
     const k = 1024;
@@ -718,53 +804,105 @@ startUpscaleBtn.addEventListener("click", async () => {
     const filterSharpen = document.getElementById("filter-sharpen");
     const filterFps = document.getElementById("filter-fps");
     const webhookUrl = document.getElementById("webhook-url");
+    const tempDirInput = document.getElementById("temp-dir-input");
     
     const aiFaceRestoration = document.getElementById("ai-face-restoration");
     const aiRifeInterpolation = document.getElementById("ai-rife-interpolation");
     const aiAudioDenoise = document.getElementById("ai-audio-denoise");
 
     try {
-        const res = await fetch("/api/upscale/start", {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
-                file_id: uploadFileId,
-                model: modelSelect.value,
-                scale: parseInt(scaleRange.value),
-                tile_size: parseInt(tileRange.value),
-                preserve_audio: audioToggle.checked,
-                
-                // Advanced fields
-                start_sec: parseFloat(trimStartRange.value),
-                end_sec: parseFloat(trimEndRange.value),
-                gpu_ids: gpuSelect.value === "auto" ? null : gpuSelect.value,
-                crf: parseInt(crfRange.value),
-                preset: presetSelect.value,
-                transcode_format: transcodeSelect.value,
-                denoise: filterDenoise.checked,
-                sharpen: filterSharpen.checked,
-                interpolation: filterFps.checked,
-                webhook_url: webhookUrl.value.trim() || null,
-                ai_face_restoration: aiFaceRestoration ? aiFaceRestoration.checked : false,
-                ai_rife_interpolation: aiRifeInterpolation ? aiRifeInterpolation.checked : false,
-                ai_audio_denoise: aiAudioDenoise ? aiAudioDenoise.checked : false
-            })
-        });
-        
-        if (!res.ok) {
-            const err = await res.json();
-            throw new Error(formatFetchError(err, "Orchestrator failed to launch job."));
+        if (window.isBatchMode && window.batchFileIds && window.batchFileIds.length > 0) {
+            const res = await fetch("/api/upscale/start/batch", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({
+                    file_ids: window.batchFileIds,
+                    model: modelSelect.value,
+                    scale: parseInt(scaleRange.value),
+                    tile_size: parseInt(tileRange.value),
+                    preserve_audio: audioToggle.checked,
+                    
+                    // Advanced fields (disabled for batch)
+                    start_sec: null,
+                    end_sec: null,
+                    gpu_ids: gpuSelect.value === "auto" ? null : gpuSelect.value,
+                    crf: parseInt(crfRange.value),
+                    preset: presetSelect.value,
+                    transcode_format: transcodeSelect.value,
+                    denoise: filterDenoise.checked,
+                    sharpen: filterSharpen.checked,
+                    interpolation: filterFps.checked,
+                    webhook_url: webhookUrl.value.trim() || null,
+                    ai_face_restoration: aiFaceRestoration ? aiFaceRestoration.checked : false,
+                    ai_rife_interpolation: aiRifeInterpolation ? aiRifeInterpolation.checked : false,
+                    ai_audio_denoise: aiAudioDenoise ? aiAudioDenoise.checked : false,
+                    temp_dir: (tempDirInput && tempDirInput.value.trim()) || null
+                })
+            });
+            
+            if (!res.ok) {
+                const err = await res.json();
+                throw new Error(formatFetchError(err, "Orchestrator failed to launch batch jobs."));
+            }
+            
+            window.isBatchMode = false;
+            window.batchFileIds = [];
+            
+            document.querySelectorAll(".batch-select-checkbox").forEach(cb => cb.checked = false);
+            const batchConfigBar = document.getElementById("batch-config-bar");
+            if (batchConfigBar) batchConfigBar.style.display = "none";
+            
+            document.querySelectorAll(".step-container").forEach(el => el.classList.remove("active"));
+            stepUpload.classList.add("active");
+            
+            alert("Batch jobs successfully queued!");
+            loadQueue();
+            
+            startUpscaleBtn.disabled = false;
+            startUpscaleBtn.innerHTML = `<i class="fa-solid fa-play"></i> Start Full Upscale`;
+        } else {
+            const res = await fetch("/api/upscale/start", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({
+                    file_id: uploadFileId,
+                    model: modelSelect.value,
+                    scale: parseInt(scaleRange.value),
+                    tile_size: parseInt(tileRange.value),
+                    preserve_audio: audioToggle.checked,
+                    
+                    // Advanced fields
+                    start_sec: parseFloat(trimStartRange.value),
+                    end_sec: parseFloat(trimEndRange.value),
+                    gpu_ids: gpuSelect.value === "auto" ? null : gpuSelect.value,
+                    crf: parseInt(crfRange.value),
+                    preset: presetSelect.value,
+                    transcode_format: transcodeSelect.value,
+                    denoise: filterDenoise.checked,
+                    sharpen: filterSharpen.checked,
+                    interpolation: filterFps.checked,
+                    webhook_url: webhookUrl.value.trim() || null,
+                    ai_face_restoration: aiFaceRestoration ? aiFaceRestoration.checked : false,
+                    ai_rife_interpolation: aiRifeInterpolation ? aiRifeInterpolation.checked : false,
+                    ai_audio_denoise: aiAudioDenoise ? aiAudioDenoise.checked : false,
+                    temp_dir: (tempDirInput && tempDirInput.value.trim()) || null
+                })
+            });
+            
+            if (!res.ok) {
+                const err = await res.json();
+                throw new Error(formatFetchError(err, "Orchestrator failed to launch job."));
+            }
+            
+            const data = await res.json();
+            currentJobId = data.job_id;
+            
+            stepConfig.classList.remove("active");
+            stepProgress.classList.add("active");
+            jobIdDisplay.textContent = currentJobId;
+            
+            connectProgressWebSocket(currentJobId);
         }
-        
-        const data = await res.json();
-        currentJobId = data.job_id;
-        
-        stepConfig.classList.remove("active");
-        stepProgress.classList.add("active");
-        jobIdDisplay.textContent = currentJobId;
-        
-        connectProgressWebSocket(currentJobId);
-        
     } catch (err) {
         alert(err.message);
         startUpscaleBtn.disabled = false;
@@ -1398,7 +1536,7 @@ async function loadQueue() {
                 `;
             }
             
-            if (job.status === "interrupted" || job.status === "failed") {
+            if (job.status === "interrupted" || job.status === "failed" || job.status === "paused") {
                 const btnLabel = job.status === "failed" ? "Retry" : "Resume";
                 const btnIcon = job.status === "failed" ? "fa-rotate-right" : "fa-play";
                 actionsHtml = `
@@ -1418,6 +1556,9 @@ async function loadQueue() {
                     <button class="btn btn-primary btn-small btn-view-job" data-id="${job.job_id}">
                         <i class="fa-solid fa-eye"></i> View
                     </button>
+                    <button class="btn btn-secondary btn-small btn-pause-job" data-id="${job.job_id}">
+                        <i class="fa-solid fa-pause"></i> Pause
+                    </button>
                     <button class="btn btn-danger btn-small btn-abort-job" data-id="${job.job_id}">
                         <i class="fa-solid fa-circle-stop"></i> Abort
                     </button>
@@ -1433,7 +1574,7 @@ async function loadQueue() {
                 `;
             }
             
-            const showProgress = ["analyzing", "extracting", "upscaling", "restoring_faces", "interpolating", "assembling"].includes(job.status);
+            const showProgress = ["analyzing", "extracting", "upscaling", "restoring_faces", "interpolating", "assembling", "paused", "interrupted"].includes(job.status);
             const progressStyle = showProgress ? "display: block;" : "display: none;";
             
             item.innerHTML = `
@@ -1508,6 +1649,24 @@ async function loadQueue() {
                 });
             }
             
+            const pauseBtn = item.querySelector(".btn-pause-job");
+            if (pauseBtn) {
+                pauseBtn.addEventListener("click", async (e) => {
+                    e.stopPropagation();
+                    try {
+                        const pauseRes = await fetch(`/api/upscale/pause/${job.job_id}`, { method: "POST" });
+                        if (pauseRes.ok) {
+                            loadQueue();
+                        } else {
+                            const err = await pauseRes.json();
+                            alert("Failed to pause job: " + formatFetchError(err, "unknown error"));
+                        }
+                    } catch (err) {
+                        console.error("Error pausing job:", err);
+                    }
+                });
+            }
+            
             const deleteBtn = item.querySelector(".btn-delete-job");
             if (deleteBtn) {
                 deleteBtn.addEventListener("click", async (e) => {
@@ -1624,6 +1783,19 @@ async function loadModels() {
 }
 
 function useUploadedVideo(entry) {
+    window.isBatchMode = false;
+    window.batchFileIds = [];
+    
+    // Enable inputs
+    timelineSlider.disabled = false;
+    generatePreviewBtn.disabled = false;
+    generateVideoPreviewBtn.disabled = false;
+    document.getElementById("trim-start-range").disabled = false;
+    document.getElementById("trim-end-range").disabled = false;
+    previewPlaceholderBox.style.display = "flex";
+    previewPlaceholderBox.querySelector("p").textContent = "Move timeline slider and generate frame preview to calibrate parameters.";
+    comparisonSliderContainer.style.display = "none";
+
     uploadFileId = entry.file_id;
     uploadMetadata = entry.metadata;
     
@@ -1684,10 +1856,55 @@ function useUploadedVideo(entry) {
     stepConfig.classList.add("active");
 }
 
+function useBatchUploadedVideos(entries) {
+    window.isBatchMode = true;
+    window.batchFileIds = entries.map(e => e.file_id);
+    uploadFileId = entries[0].file_id; // Set fallback file ID for safety
+    
+    // Set configuration name
+    metaName.textContent = `Batch Processing - ${entries.length} video(s)`;
+    metaSize.textContent = `Total size: ${formatBytes(entries.reduce((acc, e) => acc + (e.size_bytes || 0), 0))}`;
+    
+    // Set video/audio stream specs to default/mixed
+    document.getElementById("meta-res-codec").textContent = "MIXED";
+    document.getElementById("meta-res").textContent = "Varies";
+    document.getElementById("meta-fps").textContent = "Varies";
+    document.getElementById("meta-duration").textContent = "Varies";
+    document.getElementById("meta-total-frames").textContent = "Varies";
+    document.getElementById("meta-aspect-ratio").textContent = "Varies";
+    
+    document.getElementById("meta-audio-codec").textContent = "Varies";
+    document.getElementById("meta-audio-channels").textContent = "Varies";
+    document.getElementById("meta-audio-samplerate").textContent = "Varies";
+    document.getElementById("meta-audio-bitrate").textContent = "Varies";
+    
+    // Disable timeline and previews
+    timelineSlider.disabled = true;
+    generatePreviewBtn.disabled = true;
+    generateVideoPreviewBtn.disabled = true;
+    
+    // Hide trimming panel or disable inputs
+    document.getElementById("trim-start-range").disabled = true;
+    document.getElementById("trim-end-range").disabled = true;
+    
+    // Hide preview placeholders
+    previewPlaceholderBox.style.display = "flex";
+    previewPlaceholderBox.querySelector("p").textContent = "Preview and trimming are disabled in Batch Mode.";
+    comparisonSliderContainer.style.display = "none";
+    
+    // Show config view
+    stepUpload.classList.remove("active");
+    stepConfig.classList.add("active");
+}
+
 async function loadUploadsBrowser() {
     const browserList = document.getElementById("uploads-browser-list");
     if (!browserList) return;
     
+    const batchConfigBar = document.getElementById("batch-config-bar");
+    const batchSelectedCount = document.getElementById("batch-selected-count");
+    const batchConfigureBtn = document.getElementById("batch-configure-btn");
+    
     try {
         const res = await fetch("/api/uploads");
         if (!res.ok) return;
@@ -1700,10 +1917,12 @@ async function loadUploadsBrowser() {
                     <p>No uploaded files found. Upload a video above to get started!</p>
                 </div>
             `;
+            if (batchConfigBar) batchConfigBar.style.display = "none";
             return;
         }
         
         browserList.innerHTML = "";
+        let selectedEntries = [];
         
         uploads.forEach(entry => {
             const item = document.createElement("div");
@@ -1715,29 +1934,48 @@ async function loadUploadsBrowser() {
             const fpsStr = entry.metadata ? `${entry.metadata.fps} FPS` : "-";
             
             item.innerHTML = `
-                <div class="queue-item-details">
-                    <div class="queue-item-title">
-                        <i class="fa-solid fa-file-video" style="color: var(--primary);"></i> ${entry.original_filename}
+                <div style="display: flex; align-items: center; gap: 1rem; width: 100%;">
+                    <input type="checkbox" class="batch-select-checkbox" data-id="${entry.file_id}" style="width: 18px; height: 18px; cursor: pointer; accent-color: var(--primary);">
+                    <div class="queue-item-details" style="flex: 1;">
+                        <div class="queue-item-title">
+                            <i class="fa-solid fa-file-video" style="color: var(--primary);"></i> ${entry.original_filename}
+                        </div>
+                        <div class="queue-item-meta">
+                            <span>Size: ${sizeStr}</span>
+                            <span>Resolution: ${resStr}</span>
+                            <span>Duration: ${durationStr}</span>
+                            <span>FPS: ${fpsStr}</span>
+                        </div>
                     </div>
-                    <div class="queue-item-meta">
-                        <span>Size: ${sizeStr}</span>
-                        <span>Resolution: ${resStr}</span>
-                        <span>Duration: ${durationStr}</span>
-                        <span>FPS: ${fpsStr}</span>
-                    </div>
-                </div>
-                <div class="queue-item-status-bar">
-                    <div class="queue-item-actions">
-                        <button class="btn btn-primary btn-small btn-use-upload" data-id="${entry.file_id}">
-                            <i class="fa-solid fa-play"></i> Use
-                        </button>
-                        <button class="btn btn-danger btn-small btn-delete-upload" data-id="${entry.file_id}">
-                            <i class="fa-solid fa-trash"></i> Delete
-                        </button>
+                    <div class="queue-item-status-bar" style="border: none; padding: 0;">
+                        <div class="queue-item-actions">
+                            <button class="btn btn-primary btn-small btn-use-upload" data-id="${entry.file_id}">
+                                <i class="fa-solid fa-play"></i> Use
+                            </button>
+                            <button class="btn btn-danger btn-small btn-delete-upload" data-id="${entry.file_id}">
+                                <i class="fa-solid fa-trash"></i> Delete
+                            </button>
+                        </div>
                     </div>
                 </div>
             `;
             
+            const checkbox = item.querySelector(".batch-select-checkbox");
+            checkbox.addEventListener("change", () => {
+                if (checkbox.checked) {
+                    selectedEntries.push(entry);
+                } else {
+                    selectedEntries = selectedEntries.filter(se => se.file_id !== entry.file_id);
+                }
+                
+                if (selectedEntries.length > 0) {
+                    if (batchSelectedCount) batchSelectedCount.textContent = selectedEntries.length;
+                    if (batchConfigBar) batchConfigBar.style.display = "flex";
+                } else {
+                    if (batchConfigBar) batchConfigBar.style.display = "none";
+                }
+            });
+            
             item.querySelector(".btn-use-upload").addEventListener("click", () => {
                 useUploadedVideo(entry);
             });
@@ -1757,6 +1995,16 @@ async function loadUploadsBrowser() {
             
             browserList.appendChild(item);
         });
+        
+        if (batchConfigureBtn) {
+            const newBtn = batchConfigureBtn.cloneNode(true);
+            batchConfigureBtn.parentNode.replaceChild(newBtn, batchConfigureBtn);
+            newBtn.addEventListener("click", () => {
+                if (selectedEntries.length > 0) {
+                    useBatchUploadedVideos(selectedEntries);
+                }
+            });
+        }
     } catch (err) {
         console.error("Error loading uploads browser:", err);
     }
diff --git a/static/index.html b/static/index.html
index 1c55163..d5aa7d8 100644
--- a/static/index.html
+++ b/static/index.html
@@ -42,10 +42,10 @@
             <!-- Step 1: Upload Video -->
             <div id="step-upload" class="step-container active">
                 <div class="glass-card">
+                    <input type="file" id="file-input" accept="video/*" multiple style="display: none;">
                     <div id="drop-zone" class="upload-area">
-                        <input type="file" id="file-input" accept="video/*" style="display: none;">
                         <span class="upload-icon"><i class="fa-solid fa-cloud-arrow-up"></i></span>
-                        <h3>Drag & Drop Video File</h3>
+                        <h3>Drag & Drop Video File(s)</h3>
                         <p>Supports MP4, MKV, AVI, MOV, WEBM (Max 500MB recommended for local upscaling)</p>
                         <button type="button" class="btn" onclick="document.getElementById('file-input').click()">
                             <i class="fa-solid fa-folder-open"></i> Browse Files
@@ -61,6 +61,15 @@
                             <i class="fa-solid fa-arrows-rotate"></i> Refresh
                         </button>
                     </div>
+                    
+                    <!-- Batch Configuration Bar -->
+                    <div id="batch-config-bar" style="display: none; background: rgba(var(--primary-rgb), 0.1); border: 1px solid var(--primary); border-radius: 8px; padding: 0.75rem 1rem; margin-bottom: 1rem; justify-content: space-between; align-items: center; gap: 1rem;">
+                        <span style="font-size: 0.9rem; color: var(--primary); font-weight: bold;"><i class="fa-solid fa-square-check"></i> <span id="batch-selected-count">0</span> video(s) selected</span>
+                        <button type="button" id="batch-configure-btn" class="btn btn-primary btn-small">
+                            <i class="fa-solid fa-sliders"></i> Configure Batch Settings
+                        </button>
+                    </div>
+
                     <div id="uploads-browser-list" style="display: flex; flex-direction: column; gap: 0.75rem;">
                         <!-- Dynamically populated files -->
                         <div style="text-align: center; padding: 2rem; color: var(--text-muted);">
@@ -267,6 +276,15 @@
                                     </select>
                                 </div>
 
+                                <!-- Custom Temporary Directory -->
+                                <div class="form-group">
+                                    <label for="temp-dir-input"><i class="fa-solid fa-folder-open" style="color: var(--primary); margin-right: 0.25rem;"></i> Custom Temporary Files Directory</label>
+                                    <input type="text" id="temp-dir-input" placeholder="e.g. /mnt/fast_ssd/temp (Leave empty for default temp/)">
+                                    <p style="font-size: 0.72rem; color: var(--text-muted); margin-top: 2px;">
+                                        Specify a custom location for temporary image frames to prevent running out of primary drive space.
+                                    </p>
+                                </div>
+
                                 <!-- Pre-filters selection checkboxes -->
                                 <div class="filter-group">
                                     <span style="font-weight: 600; font-size: 0.85rem; display: block; color: var(--primary);">Pre-Filters & Enhancing</span>
diff --git a/static/styles.css b/static/styles.css
index bbe40c9..a87c204 100644
--- a/static/styles.css
+++ b/static/styles.css
@@ -659,6 +659,7 @@ input:checked + .slider:before {
 .status-badge.completed { background: rgba(0, 255, 135, 0.1); border: 1px solid var(--success); color: var(--success); }
 .status-badge.failed { background: rgba(255, 0, 85, 0.1); border: 1px solid var(--danger); color: var(--danger); }
 .status-badge.interrupted { background: rgba(255, 255, 255, 0.08); border: 1px solid var(--text-muted); color: var(--text-muted); }
+.status-badge.paused { background: rgba(255, 184, 0, 0.08); border: 1px solid var(--warning); color: var(--warning); }
 
 
 .bar-container {