Enhance run_training function in app.py to include run_out_dir in yield outputs. This update improves the tracking of the output directory throughout the training process and ensures consistent error handling by including run_out_dir in all yield statements, enhancing user feedback and clarity.

app.py

@@ -685,15 +685,16 @@ def run_training(
     log_buf = "[QIE] Start Training invoked.\n"
     ckpts: List[str] = []
     artifacts: List[str] = []
+    run_out_dir = ""
     # Emit an initial line so UI can confirm invocation
-    yield (log_buf, ckpts, artifacts)
+    yield (log_buf, ckpts, artifacts, run_out_dir)
     if not output_name.strip():
         log_buf += "[ERROR] OUTPUT NAME is required.\n"
-        yield (log_buf, ckpts, artifacts)
+        yield (log_buf, ckpts, artifacts, run_out_dir)
         return
     if not caption.strip():
         log_buf += "[ERROR] CAPTION is required.\n"
-        yield (log_buf, ckpts, artifacts)
+        yield (log_buf, ckpts, artifacts, run_out_dir)
         return
 
     # Ensure /auto holds helper files expected by the script
@@ -705,6 +706,7 @@ def run_training(
     import time
     ds_name = f"dataset_{int(time.time())}"
     ds_dir = os.path.join(DATA_ROOT_RUNTIME, ds_name)
+    run_out_dir = os.path.join(ds_dir, output_name.strip())
     img_folder_name = DEFAULT_IMAGE_FOLDER
     img_dir = os.path.join(ds_dir, img_folder_name)
     os.makedirs(img_dir, exist_ok=True)
@@ -713,11 +715,11 @@ def run_training(
     base_files = _extract_paths(image_uploads)
     if not base_files:
         log_buf += "[ERROR] No images uploaded for IMAGE_FOLDER.\n"
-        yield (log_buf, ckpts, artifacts)
+        yield (log_buf, ckpts, artifacts, run_out_dir)
         return
     base_filenames = _copy_uploads(base_files, img_dir)
     log_buf += f"[QIE] Copied {len(base_filenames)} base images to {img_dir}\n"
-    yield (log_buf, ckpts, artifacts)
+    yield (log_buf, ckpts, artifacts, run_out_dir)
 
     # Prepare control sets
     control_upload_sets = [
@@ -733,7 +735,7 @@ def run_training(
     # Require control_0; others optional
     if not control_upload_sets[0]:
         log_buf += "[ERROR] control_0 images are required.\n"
-        yield (log_buf, ckpts, artifacts)
+        yield (log_buf, ckpts, artifacts, run_out_dir)
         return
 
     control_dirs: List[Optional[str]] = []
@@ -748,7 +750,7 @@ def run_training(
         _copy_uploads(uploads, cdir)
         control_dirs.append(folder_name)
         log_buf += f"[QIE] Copied {len(uploads)} control_{i} images to {cdir}\n"
-        yield (log_buf, ckpts, artifacts)
+        yield (log_buf, ckpts, artifacts, run_out_dir)
 
     # Metadata.jsonl will be generated by create_image_caption_json.py in train_QIE.sh
 
@@ -813,6 +815,7 @@ def run_training(
     log_buf += f"[QIE] Using shell: {shell}\n"
     log_buf += f"[QIE] Running script: {tmp_script}\n"
     out_dir = os.path.join(out_base, output_name.strip())
+    run_out_dir = out_dir
     ckpts = _list_checkpoints(out_dir)
     # Copy the final script to dataset dir for download
     used_script_path = os.path.join(out_base, "train_QIE_used.sh")
@@ -826,7 +829,7 @@ def run_training(
             artifacts.append(used_script_path)
     except Exception:
         pass
-    yield (log_buf, ckpts, artifacts)
+    yield (log_buf, ckpts, artifacts, run_out_dir)
 
     # Run and stream output
     # Ensure child Python processes are unbuffered for real-time logs
@@ -863,7 +866,7 @@ def run_training(
                 metadata_json = os.path.join(out_base, "metadata.jsonl")
                 if os.path.isfile(metadata_json) and metadata_json not in artifacts:
                     artifacts.append(metadata_json)
-            yield (log_buf, ckpts, artifacts)
+            yield (log_buf, ckpts, artifacts, run_out_dir)
     finally:
         code = proc.wait()
         # Clear active process registration if this proc
@@ -889,7 +892,7 @@ def run_training(
         metadata_json = os.path.join(out_base, "metadata.jsonl")
         if os.path.isfile(metadata_json) and metadata_json not in artifacts:
             artifacts.append(metadata_json)
-        yield (log_buf, ckpts, artifacts)
+        yield (log_buf, ckpts, artifacts, run_out_dir)
 
 
 def _stop_active_training() -> None:
@@ -1069,6 +1072,7 @@ def build_ui() -> gr.Blocks:
                 # Models root / OUTPUT_DIR_BASE / DATASET_CONFIG are auto-resolved at runtime; no user input needed.
 
                 run_btn = gr.Button("Start Training", variant="primary")
+                run_out_dir_box = gr.Textbox(label="今回の出力フォルダ", lines=1, interactive=False)
                 logs = gr.Textbox(label="Logs", lines=20)
                 ckpt_files = gr.Files(label="Checkpoints (live)", interactive=False)
                 scripts_files = gr.Files(label="Scripts & Config (live)", interactive=False)
@@ -1105,7 +1109,7 @@ def build_ui() -> gr.Blocks:
                         tr_w, tr_h, train_bs, cr_w, cr_h, te_bs,
                         seed_input, max_epochs, save_every,
                     ],
-                    outputs=[logs, ckpt_files, scripts_files],
+                    outputs=[logs, ckpt_files, scripts_files, run_out_dir_box],
                 )
 
                 # 回収ボタン: 直近の dataset_ ディレクトリからチェックポイントとスクリプト/設定を再取得