v0.11.0 (#34)

- Summary (f6125144e9df803bac37023b6854f03c30d62a31)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (2f050c06a94348ba17660fdf0dd257a7a30f2f9a)
- Summary (8f52d543a1de5a77b59164e6f4f721696fc64299)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (fffa0062f0da04563ce8cd5b8c7e70e3ae783833)
- Summary (1717e06c53138f3eaf52e38f984035d5fbbceac5)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (cd90a1620005039e6998ca3d0ab34fe3bfe1f2dc)
- Summary (98c66eeb6760ebd60d0a4ae4d9d0ac8f896a59df)
- Update config.toml (91d9d7ef4e540930919833c79607c51fc294d60d)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (e6358979bef7df974cdd6c63aca029c57ac62af8)
- Summary (6de61f5802c0e3640047369ad08ecab73b331d34)
- Update config.toml (b5ed9ffe1ad1d0f500f794adbdaf154836c4f98b)
- Summary (32a92bfceec53fd471bc976cbb849fd9d927ad83)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (da47ac2a7b54d4ff7a69c19e9a2c785464ca5016)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (a38174b5323e173d29898a3d3914e1fff4956b23)
- Summary (fe195552c3857fb5eb2edd95cb44bc2702b5d340)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (1c886618681448e721a7e6daec1c567743446d5d)
- Summary (d02f294f9243051ee718760d8a7206211a67c88e)
- Summary (506641f920e1fe10df73fcf2b8c84b6425851043)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (78abcea91c2e552c225ed682431fe5b907286949)
- Update config.toml (7acc2de6f12e310f66417743f05268b0660c1deb)
- Summary (5907fd775e746f0a14b4384c34cfd3008edd2d74)
- Merge branch 'main' of https://huggingface.co/spaces/ElenaRyumina/OCEANAI (6d979e4e73b8013910323ed0915208792906c47c)


Co-authored-by: Dmitry Ryumin <[email protected]>

app.py

@@ -93,6 +93,6 @@ if __name__ == "__main__":
 
     create_gradio_app().queue(api_open=False).launch(
         share=False,
-        server_name=None,
-        server_port=None,
+        server_name=config_data.AppSettings_SERVER_NAME,
+        server_port=config_data.AppSettings_PORT,
     )

app/event_handlers/calculate_practical_tasks.py

@@ -576,8 +576,12 @@ def event_handler_calculate_practical_task_blocks(
     elif practical_subtasks.lower() == "professional skills":
         df_professional_skills = read_csv_file(config_data.Links_PROFESSIONAL_SKILLS)
 
+        pt_scores_copy = pt_scores.iloc[:, 1:].copy()
+
+        preprocess_scores_df(pt_scores_copy, config_data.Dataframes_PT_SCORES[0][0])
+
         b5._priority_skill_calculation(
-            df_files=pt_scores.iloc[:, 1:],
+            df_files=pt_scores_copy,
             correlation_coefficients=df_professional_skills,
             threshold=threshold_professional_skills,
             out=False,
@@ -607,13 +611,13 @@ def event_handler_calculate_practical_task_blocks(
             df_hidden = df_hidden.sort_values(
                 by=[dropdown_professional_skills], ascending=False
             )
+            df_hidden.reset_index(inplace=True)
         elif type_modes == config_data.Settings_TYPE_MODES[1]:
             df_hidden = df_hidden.melt(
                 var_name="Professional Skill", value_name="Summary Score"
             )
             df_hidden = df_hidden.sort_values(by=["Summary Score"], ascending=False)
-
-        df_hidden.reset_index(drop=True, inplace=True)
+            df_hidden.reset_index(drop=True, inplace=True)
 
         df_hidden.to_csv(config_data.Filenames_PT_SKILLS_SCORES)
 
@@ -726,25 +730,19 @@ def event_handler_calculate_practical_task_blocks(
 
         df_hidden.reset_index(inplace=True)
 
-        if (
-            practical_subtasks.lower()
-            != "finding a suitable colleague by personality types"
-        ):
-            person_id = (
-                int(
-                    df_hidden.iloc[
-                        (
-                            0
-                            if practical_subtasks.lower()
-                            != "finding a suitable colleague by personality types"
-                            else 1
-                        )
-                    ][config_data.Dataframes_PT_SCORES[0][0]]
-                )
-                - 1
+        person_id = (
+            int(
+                df_hidden.iloc[
+                    (
+                        0
+                        if practical_subtasks.lower()
+                        != "finding a suitable colleague by personality types"
+                        else 1
+                    )
+                ][config_data.Dataframes_PT_SCORES[0][0]]
             )
-        else:
-            person_id = 0
+            - 1
+        )
 
         person_metadata = create_person_metadata(person_id, files, video_metadata)
 
@@ -840,7 +838,7 @@ def event_handler_calculate_practical_task_blocks(
 
             df_hidden = df_hidden.reset_index()
 
-            df_hidden.columns = ["Category", "Priority"]
+            df_hidden.columns = ["Priority", "Category"]
 
         df_hidden.to_csv(consumer_preferences(practical_subtasks))
 

app/event_handlers/practical_task_sorted.py

@@ -37,7 +37,13 @@ def event_handler_practical_task_sorted(
         label = ""
     label += " " + config_data.Dataframes_PT_SCORES[0][0]
 
-    if Path(files[person_id]).name in video_metadata:
+    try:
+        is_filename = Path(files[person_id]).name in video_metadata
+    except IndexError:
+        is_filename = False
+        person_id = 0
+
+    if is_filename:
         person_metadata_list = video_metadata[Path(files[person_id]).name]
 
         person_metadata = (

config.toml

@@ -1,5 +1,5 @@
 [AppSettings]
-APP_VERSION = "0.10.10"
+APP_VERSION = "0.11.0"
 SERVER_NAME = "127.0.0.1"
 PORT = 7860
 CSS_PATH = "app.css"