fix(gpt): update the test cases.

tools/tdgpt/taosanalytics/algo/fc/gpt.py

@@ -39,13 +39,13 @@ class _GPTService(AbstractForecastService):
             response = requests.post(self.service_host, data=json.dumps(data), headers=self.headers)
         except Exception as e:
             app_logger.log_inst.error(f"failed to connect the service: {self.service_host} ", str(e))
-            raise ValueError("error")
+            raise e
 
-        # print(response)
+        if response.status_code != 200:
+            app_logger.log_inst.error(f"failed to connect the service: {self.service_host} ")
+            raise ValueError("invalid host url")
 
         pred_y = response.json()['output']
-        # print(f"pred_y len:{len(pred_y)}")
-        # print(f"pred_y:{pred_y}")
 
         res =  {
             "res": [pred_y]
@@ -54,18 +54,6 @@ class _GPTService(AbstractForecastService):
         insert_ts_list(res["res"], self.start_ts, self.time_step, self.fc_rows)
         return res
 
-        # insert_ts_list(res, self.start_ts, self.time_step, self.fc_rows)
-        #
-        # if self.return_conf:
-        #     res1 = [res.tolist(), res.tolist(), res.tolist()], None
-        # else:
-        #     res1 = [res.tolist()], None
-        #
-        # # add the conf range if required
-        # return {
-        #     "mse": None,
-        #     "res": res1
-        # }
 
     def set_params(self, params):
         super().set_params(params)
@@ -73,7 +61,7 @@ class _GPTService(AbstractForecastService):
         if "host" not in params:
             raise ValueError("gpt service host needs to be specified")
 
-        self.service_host = params['host'].trim()
+        self.service_host = params['host']
 
         if self.service_host.startswith("https://"):
             self.service_host = self.service_host.replace("https://", "http://")

tools/tdgpt/taosanalytics/test/forecast_test.py

@@ -8,7 +8,7 @@ import pandas as pd
 sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../../")
 
 from taosanalytics.algo.forecast import draw_fc_results
-from taosanalytics.conf import setup_log_info
+from taosanalytics.conf import setup_log_info, app_logger
 from taosanalytics.servicemgmt import loader
 
 
@@ -30,7 +30,8 @@ class ForecastTest(unittest.TestCase):
         ts_list = data[['Passengers']].index.tolist()
         dst_list = [int(item.timestamp()) for item in ts_list]
 
-        return data[['Passengers']].values.tolist(), dst_list
+        return data['Passengers'].values.tolist(), dst_list
+
 
     def test_holt_winters_forecast(self):
         """ test holt winters forecast with invalid and then valid parameters"""
@@ -111,5 +112,20 @@ class ForecastTest(unittest.TestCase):
         draw_fc_results(data, len(r["res"]) > 1, r["res"], rows, "arima")
 
 
+    def test_gpt_fc(self):
+        """for local test only, disabled it in github action"""
+        data, ts = self.get_input_list()
+        pass
+
+        s = loader.get_service("td_gpt_fc")
+        s.set_input_list(data, ts)
+
+        s.set_params({"host":'192.168.2.90:5000/ds_predict', 'fc_rows': 10, 'start_ts': 171000000, 'time_step': 86400*30})
+        r = s.execute()
+
+        rows = len(r["res"][0])
+        draw_fc_results(data, False, r["res"], rows, "gpt")
+
+
 if __name__ == '__main__':
     unittest.main()