added gram2vec cahcing url and download command; updated HRS data to reddit data on the UI; made wegmann model the default one;

app.py

@@ -29,6 +29,7 @@ cfg = load_config()
 download_file_override(cfg.get('background_authors_df_url'), cfg.get('background_authors_df_path'))
 download_file_override(cfg.get('instances_to_explain_url'), cfg.get('instances_to_explain_path'))
 download_file_override(cfg.get('gram2vec_feats_url'), cfg.get('gram2vec_feats_path'))
+download_file_override(cfg.get('gram2vec_cache_url'), cfg.get('gram2vec_cache_path'))
 download_file_override(cfg.get('embeddings_cache_url'), cfg.get('embeddings_cache_path'))
 download_file_override(cfg.get('zoom_cache_url'), cfg.get('zoom_cache_path'))
 download_file_override(cfg.get('region_cache_url'), cfg.get('region_cache_path'))
@@ -142,13 +143,13 @@ def app(share=False):
         # ── Model Selection ─────────────────────────────────
         model_radio = gr.Radio(
             choices=[
+                'AnnaWegmann/Style-Embedding',
                 'gabrielloiseau/LUAR-MUD-sentence-transformers',
                 'gabrielloiseau/LUAR-CRUD-sentence-transformers',
                 'miladalsh/light-luar',
-                'AnnaWegmann/Style-Embedding',
                 'Other'
             ],
-            value='gabrielloiseau/LUAR-MUD-sentence-transformers',
+            value='AnnaWegmann/Style-Embedding',
             label='Choose a Model to inspect'
         )
         print(f"Model choices: {model_radio.choices}")
@@ -168,8 +169,8 @@ def app(share=False):
 
         # ── Task Source Selection ─────────────────────────────────
         task_mode = gr.Radio(
-            choices=["Predefined HRS Task", "Upload Your Own Task"],
-            value="Predefined HRS Task",
+            choices=["Predefined Reddit Task", "Upload Your Own Task"],
+            value="Predefined Reddit Task",
             label="Select Task Source"
         )
 

config/config.yaml

@@ -9,6 +9,9 @@ background_authors_df_url:    "https://huggingface.co/datasets/miladalsh/explana
 gram2vec_feats_path:      "./datasets/gram2vec_feats.csv"
 gram2vec_feats_url:      "https://huggingface.co/datasets/miladalsh/explanation_tool_files/resolve/main/gram2vec_feats.csv?download=true"
 
+gram2vec_cache_url: "https://huggingface.co/datasets/miladalsh/explanation_tool_files/resolve/main/gram2vec_cache.zip?download=true"
+gram2vec_cache_path: "./datasets/gram2vec_cache/"
+
 embeddings_cache_url: "https://huggingface.co/datasets/miladalsh/explanation_tool_files/resolve/main/embeddings_cache.zip?download=true"
 embeddings_cache_path: "./datasets/embeddings_cache/"
 

utils/ui.py

@@ -81,14 +81,14 @@ def read_txt(f):
 def toggle_task(mode):
     print(mode)
     return (
-        gr.update(visible=(mode == "Predefined HRS Task")),
+        gr.update(visible=(mode == "Predefined Reddit Task")),
         gr.update(visible=(mode == "Upload Your Own Task"))
     )
 
 # Update displayed texts based on mode
 def update_task_display(mode, iid, instances, background_df, mystery_file, cand1_file, cand2_file, cand3_file, true_author, model_radio, custom_model_input):
     model_name = model_radio if model_radio != "Other" else custom_model_input
-    if mode == "Predefined HRS Task":
+    if mode == "Predefined Reddit Task":
         iid = int(iid.replace('Task ', ''))
         data = instances[iid]
         ground_truth_author = 100#data['gt_idx']