Merge branch 'release-2026.0.0' into change_certs_permissions

Author: Irakus

education-ai-suite/smart-classroom/components/mindmap_component.py

@@ -39,8 +39,7 @@ def generate_mindmap(self, summary_text):
                 add_generation_prompt=True
             )
 
-            mindmap_streamer = self.model.generate(mindmap_prompt)
-            full_mindmap = "".join(token for token in mindmap_streamer)
+            full_mindmap = self.model.generate(mindmap_prompt, False)
             StorageManager.save(mindmap_path, full_mindmap, append=False)
             logger.info("Mindmap generation completed successfully.")
             return full_mindmap

education-ai-suite/smart-classroom/config.yaml

@@ -259,6 +259,7 @@ mindmap:
       10. Ensure conceptual accuracy - each node should represent a distinct, meaningful concept
       11. Do NOT include any markdown formatting, code fences, or explanatory text
       12. Output only the raw JSON structure
+      13. Always return a valid JSON structure.
 
       Example of GOOD specificity:
       {
@@ -321,12 +322,13 @@ mindmap:
       10. 确保概念准确性 - 每个节点应代表一个独特、有意义的概念
       11. 不要包含任何markdown格式、代码块或解释性文本
       12. 只输出原始JSON结构
+      13. 始终返回有效的JSON结构。
 
       良好特异性示例：
       {
         "meta": {
-          "name": "physics_lecture",
-          "author": "ai_assistant",
+          "name": "物理课程",
+          "author": "人工智能助手",
           "version": "1.0"
         },
         "format": "node_tree", 
@@ -335,21 +337,21 @@ mindmap:
           "topic": "量子力学与波动理论",
           "children": [
             {
-              "id": "wave_particle_duality",
+              "id": "波粒二象性",
               "topic": "波粒二象性",
               "children": [
-                {"id": "photon_behavior", "topic": "光子同时表现出波动和粒子特性"},
-                {"id": "double_slit", "topic": "双缝实验证明干涉现象"},
-                {"id": "measurement_effect", "topic": "测量导致波函数坍缩"}
+                {"id": "光子特性", "topic": "光子同时表现出波动和粒子特性"},
+                {"id": "双缝实验", "topic": "双缝实验证明干涉现象"},
+                {"id": "测量效应", "topic": "测量导致波函数坍缩"}
               ]
             },
             {
-              "id": "uncertainty_principle",
+              "id": "不确定性原理",
               "topic": "海森堡不确定性原理",
               "children": [
-                {"id": "position_momentum", "topic": "无法同时精确知道位置和动量"},
-                {"id": "mathematical_formulation", "topic": "Δx·Δp ≥ ℏ/2 数学关系"},
-                {"id": "quantum_limitations", "topic": "量子测量的基本限制"}
+                {"id": "位置动量", "topic": "无法同时精确知道位置和动量"},
+                {"id": "数学表达式", "topic": "Δx·Δp ≥ ℏ/2 数学关系"},
+                {"id": "量子限制", "topic": "量子测量的基本限制"}
               ]
             }
           ]

education-ai-suite/smart-classroom/docs/user-guide/get-started.md

@@ -108,7 +108,7 @@ Bring Up the Frontend:
 > The backend terminal stays busy serving requests.
 
 ```bash
-cd C:\path\to\edge-ai-suites\education-ai-suite\smart-classroom\ui
+cd <path-to>\edge-ai-suites\education-ai-suite\smart-classroom\ui
 npm install
 npm run dev -- --host 0.0.0.0 --port 5173
 ```

health-and-life-sciences-ai-suite/multi_modal_patient_monitoring/configs/model-config.yaml

@@ -4,12 +4,14 @@ ai-ecg:
       type: ai-ecg
       hub: hls
       target_dir: /models/ai-ecg
+      nodel_url: https://raw.githubusercontent.com/Einse57/OpenVINO_sample/master/ai-ecg-master
       ir_file: ecg_8960_ir10_fp16.xml
       video_dir: /videos/ai-ecg
     - name: ecg_17920_ir10_fp16
       type: ai-ecg
       hub: hls
       target_dir: /models/ai-ecg
+      nodel_url: https://raw.githubusercontent.com/Einse57/OpenVINO_sample/master/ai-ecg-master
       ir_file: ecg_17920_ir10_fp16.xml
       video_dir: /videos/ai-ecg
 
@@ -20,13 +22,17 @@ rppg:
       hub: hls
       target_dir: /models/rppg
       model_file: mtts_can.hdf5
+      model_url: https://github.com/xliucs/MTTS-CAN/raw/main/mtts_can.hdf5
       video_dir: /videos/rppg
+      video_url: https://github.com/opencv/opencv/raw/master/samples/data/vtest.avi
 
 pose-3d:
   models:
     - name: human-pose-estimation-3d-0001
       type: 3d-pose
       hub: hls
       target_dir: /models/3d-pose
+      model_url: https://storage.openvinotoolkit.org/repositories/open_model_zoo/public/2022.1/human-pose-estimation-3d-0001/human-pose-estimation-3d.tar.gz
       ir_file: human-pose-estimation-3d-0001.xml
       video_dir: /videos/3d-pose
+      video_url: https://www.pexels.com/download/video/6130537

health-and-life-sciences-ai-suite/multi_modal_patient_monitoring/services/patient-monitoring-assets/Dockerfile

@@ -26,7 +26,7 @@ WORKDIR /app
 # Python deps for asset generation
 # ----------------------------
 COPY requirements.txt /app/requirements.txt
-RUN pip install --no-cache-dir -r /app/requirements.txt
+RUN pip install --default-timeout=300 --retries 5 --no-cache-dir -r /app/requirements.txt
 
 # ----------------------------
 # App scripts used to build assets (model-config.yaml is mounted at runtime)
@@ -54,7 +54,6 @@ ARG HTTPS_PROXY
 ARG NO_PROXY
 
 
-
 WORKDIR /app
 
 # Minimal system deps (no heavy ML frameworks here)

health-and-life-sciences-ai-suite/multi_modal_patient_monitoring/services/patient-monitoring-assets/scripts/3d_pose_model_convert.py

@@ -15,14 +15,20 @@
 CONFIG_PATH = Path("/app/configs/model-config.yaml")
 
 
-def _load_pose_model_config() -> tuple[str, str, str]:
-    """Load 3D pose model name, target_dir, and video_dir from config.
+def _load_pose_model_config() -> tuple[str, str, str, str, str]:
+    """Load 3D pose model settings from config.
 
     This function expects /app/configs/model-config.yaml to exist and to
-    define pose-3d.models[0] with at least name, target_dir, and
-    video_dir. If any of these are missing or the file is not readable,
-    the script will raise and fail fast instead of using hardcoded
-    defaults.
+    define pose-3d.models[0] with at least:
+
+      - name
+      - target_dir
+      - model_url
+      - video_dir
+      - video_url
+
+    If any of these are missing or the file is not readable, the script
+    will raise and fail fast instead of using hardcoded defaults.
     """
     if not CONFIG_PATH.exists():
         raise FileNotFoundError(
@@ -45,17 +51,26 @@ def _load_pose_model_config() -> tuple[str, str, str]:
     first = models[0] or {}
     name = first.get("name")
     target_dir = first.get("target_dir")
+    model_url = first.get("model_url")
     video_dir = first.get("video_dir")
+    video_url = first.get("video_url")
 
-    if not name or not target_dir or not video_dir:
+    if not name or not target_dir or not model_url or not video_dir or not video_url:
         raise ValueError(
-            "pose-3d.models[0] must define name, target_dir, and video_dir in model-config.yaml."
+            "pose-3d.models[0] must define name, target_dir, model_url, "
+            "video_dir, and video_url in model-config.yaml."
         )
 
-    return str(name), str(target_dir), str(video_dir)
+    return (
+        str(name),
+        str(target_dir),
+        str(video_dir),
+        str(model_url),
+        str(video_url),
+    )
 
 
-MODEL_NAME, MODEL_TARGET_DIR, MODEL_VIDEO_DIR = _load_pose_model_config()
+MODEL_NAME, MODEL_TARGET_DIR, MODEL_VIDEO_DIR, MODEL_URL, VIDEO_URL = _load_pose_model_config()
 
 # Directory where the 3D pose model assets will be stored
 # Use the same default as omz-model-download.sh: /models/3d-pose
@@ -78,22 +93,14 @@ def _load_pose_model_config() -> tuple[str, str, str]:
 ov_model_path = base_model_dir / f"{MODEL_NAME}.xml"
 
 # Demo video path
-video_url = "https://storage.openvinotoolkit.org/data/test_data/videos/face-demographics-walking.mp4"
 video_path = videos_dir / "face-demographics-walking.mp4"
 
 
 # 1) Download and extract the .pth checkpoint if needed
 if not ckpt_file.exists():
-    # URL still points to the default OMZ model; MODEL_NAME controls
-    # the local file naming via config.
-    url = (
-        "https://storage.openvinotoolkit.org/repositories/open_model_zoo/public/2022.1/"
-        "human-pose-estimation-3d-0001/human-pose-estimation-3d.tar.gz"
-    )
-
     if not tar_path.exists():
-        print(f"Downloading 3D pose checkpoint from {url}")
-        urllib.request.urlretrieve(url, tar_path)
+        print(f"Downloading 3D pose checkpoint from {MODEL_URL}")
+        urllib.request.urlretrieve(MODEL_URL, tar_path)
         print(f"Saved checkpoint archive to {tar_path}")
 
     print(f"Extracting checkpoint archive into {base_model_dir}")
@@ -104,8 +111,19 @@ def _load_pose_model_config() -> tuple[str, str, str]:
 
 # 1b) Download the demo video if needed
 if not video_path.exists():
-    print(f"Downloading 3D pose demo video from {video_url}")
-    urllib.request.urlretrieve(video_url, video_path)
+    print(f"Downloading 3D pose demo video from {VIDEO_URL}")
+    # Pexels blocks the default Python user-agent; mimic a browser and
+    # send a valid Referer so the request matches typical browser usage.
+    req = urllib.request.Request(
+        VIDEO_URL,
+        headers={
+            "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
+            "(KHTML, like Gecko) Chrome/120.0 Safari/537.36",
+            "Referer": "https://www.pexels.com/",
+        },
+    )
+    with urllib.request.urlopen(req) as resp, video_path.open("wb") as out_f:
+        shutil.copyfileobj(resp, out_f)
     print(f"Saved 3D pose demo video to {video_path}")
 
 
@@ -141,4 +159,4 @@ def _load_pose_model_config() -> tuple[str, str, str]:
         except FileNotFoundError:
             pass
 
-print("✅ OpenVINO IR model saved:", ov_model_path)
+print("✅ OpenVINO IR model saved:", ov_model_path)

health-and-life-sciences-ai-suite/multi_modal_patient_monitoring/services/patient-monitoring-assets/scripts/ecg_download_assets.py

@@ -28,10 +28,10 @@ def download_file(url: str, dest: Path, desc: str) -> None:
         raise
 
 
-def load_ecg_models_from_config() -> list[tuple[Path, str, str]]:
+def load_ecg_models_from_config() -> list[tuple[Path, str, str, str]]:
     """Load ECG model directories and filenames from model-config.yaml.
 
-    Returns a list of tuples: (target_dir, xml_filename, bin_filename).
+    Returns a list of tuples: (target_dir, xml_filename, bin_filename, model_url).
     This function expects /app/configs/model-config.yaml to exist and to
     define ai-ecg.models[*] entries with at least target_dir and
     ir_file or name. If the file is missing or malformed, it will
@@ -61,6 +61,7 @@ def load_ecg_models_from_config() -> list[tuple[Path, str, str]]:
         target_dir_val = m.get("target_dir")
         ir_file_val = m.get("ir_file")
         name_val = m.get("name")
+        model_url_val = m.get("model_url")
 
         if not target_dir_val:
             raise ValueError(
@@ -86,7 +87,19 @@ def load_ecg_models_from_config() -> list[tuple[Path, str, str]]:
             )
 
         bin_file = xml_file.replace(".xml", ".bin")
-        result.append((target_dir, xml_file, bin_file))
+
+        # model_url is optional in config for backward compatibility; if
+        # omitted, fall back to the legacy BASE_URL.
+        if not model_url_val:
+            logger.warning(
+                "ai-ecg.models entry missing model_url; falling back to BASE_URL %s",
+                BASE_URL,
+            )
+            model_url = BASE_URL
+        else:
+            model_url = str(model_url_val)
+
+        result.append((target_dir, xml_file, bin_file, model_url))
 
     return result
 
@@ -96,7 +109,7 @@ def main() -> int:
 
     models = load_ecg_models_from_config()
 
-    for target_dir, xml_name, bin_name in models:
+    for target_dir, xml_name, bin_name, model_url in models:
         target_dir.mkdir(parents=True, exist_ok=True)
         logger.info("Using ECG model directory: %s", target_dir)
 
@@ -106,7 +119,7 @@ def main() -> int:
                 logger.info("%s already exists, skipping", dest)
                 continue
 
-            url = f"{BASE_URL}/{fname}"
+            url = f"{model_url}/{fname}"
             download_file(url, dest, fname)
 
     logger.info("ECG models ready")