feat: generate the envelop for the given time series data.

tools/tdgpt/requirements_ess.txt

@@ -1,4 +1,5 @@
-pandas==1.5.3
+pandas==1.5.3 ; python_version <= "3.11"
+pandas==2.2.0 ; python_version >= "3.12"
 scipy==1.15.0
 scikit-learn==1.5.2
 outlier-utils==0.0.5

tools/tdgpt/script/install.sh

@@ -605,11 +605,6 @@ check_python3_env() {
     fi
   fi
 
-  if [[ $python_minor_ver -eq 12 ]]; then
-    echo "Python 3.12: Update Pandas from 1.5.3 to 2.2.0 in Requirements_ess.txt"
-    sed -i '1s/pandas==1.5.3/pandas==2.2.0/' ${script_dir}/requirements_ess.txt
-  fi
-
 #  echo -e "Python3 minor version is:${python_minor_ver}"
 
   # check the existence pip3.10/pip3.11/pip3.12

tools/tdgpt/taosanalytics/algo/anomaly.py

@@ -4,6 +4,7 @@
 
 from matplotlib import pyplot as plt
 from taosanalytics.conf import app_logger, conf
+from taosanalytics.error import failed_load_model_except
 from taosanalytics.servicemgmt import loader
 from taosanalytics.util import convert_results_to_windows
 
@@ -13,10 +14,8 @@ def do_ad_check(input_list, ts_list, algo_name, params):
     s = loader.get_service(algo_name)
 
     if s is None:
-        s = loader.get_service("ksigma")
-
-    if s is None:
-        raise ValueError(f"failed to load {algo_name} or ksigma analysis service")
+        app_logger.log_inst.error("specified model not found:%s" % (algo_name))
+        failed_load_model_except(algo_name)
 
     s.set_input_list(input_list, ts_list)
     s.set_params(params)