Rework sorting function to calculate keys instead of pre-sort the list

Rename added/changed variables to be clearer

scripts/tag_autocomplete_helper.py

@@ -25,40 +25,44 @@ except Exception as e: # Not supported.
     load_textual_inversion_embeddings = lambda *args, **kwargs: None
     print("Tag Autocomplete: Cannot reload embeddings instantly:", e)
 
-QUO = "\""
-EXTKEY = "tac"
-# EXTNAME = "Tag Autocomplete Helper"
-# Default values, because shared doesn't allocate a value automatically.
-# (id: def)
-DEXTSETV = {
-"sortModels": "default",
+# Sorting functions for extra networks / embeddings stuff
+sort_criteria = {
+    "Name": {
+        "key": lambda path, name: name.lower() if Path(name).parts > 1 else path.stem.lower(),
+        "reverse": False
+    },
+    "Date Modified": {
+        "key": lambda path, name: path.stat().st_mtime,
+        "reverse": True
+    },
 }
-fseti = lambda x: shared.opts.data.get(EXTKEY + "_" + x, DEXTSETV[x])
 
-def sort_models(lmodels, sort_method = None, indwrap = False):
-    """Sorts models according to setting.
+def sort_models(model_list, sort_method = None):
+    """Sorts models according to the setting.
     
     Input: list of (full_path, display_name, {hash}) models. 
-    Returns models in the standard temp file format (ie name, hash).
-    Default sort is lexicographical, mdate is by file modification date.
-    Hash is optional, can be any textual value written after the name (eg v1/v2 for embeddings).
-    For some reason only loras and lycos are wrapped in quote marks, so it's left to caller.
-    Creep: Requires sort modifications on js side to preserve order during merge.
+    Returns models in the format of name, sort key, meta.
+    Meta is optional and can be a hash, version string or other required info.
+    Whether the currently selected sort method needs to be reversed is provided
+    by an API endpoint to reduce duplication in temp files.
     """
-    if len(lmodels) == 0:
-        return lmodels
+    if len(model_list) == 0:
+        return model_list
+
     if sort_method is None:
-        sort_method = fseti("sortModels")
-    if sort_method == "modified_date":
-        lsorted = sorted(lmodels, key=lambda x: os.path.getmtime(x[0]), reverse = True)
-    else: 
-        lsorted = sorted(lmodels, key = lambda x: x[1].lower())
-    if len(lsorted[0]) > 2:
-        # lret = [f"\"{name}\",{hash}" for pt, name, hash in lsorted]
-        lret = [f"{name},{hash}" for pt, name, hash in lsorted]
+        sort_method = getattr(shared.opts, "tac_modelSortOrder", "Name")
+
+    # Get sorting method from dictionary
+    sorter = sort_criteria[sort_method] if sort_criteria[sort_method] else sort_criteria['Name']
+
+    # During merging on the JS side we need to re-sort anyway, so here only the sort criteria are calculated.
+    # The list itself doesn't need to get sorted at this point.
+    if len(model_list[0]) > 2:
+        results = [f'{name},"{sorter["key"](path, name)}",{meta}' for path, name, meta in model_list]
     else:
-        lret = [name for pt, name in lsorted]
-    return lret
+        results = [f'{name},"{sorter["key"](path, name)}"' for path, name in model_list]
+    return results
+
 
 def get_wildcards():
     """Returns a list of all wildcards. Works on nested folders."""
@@ -75,10 +79,10 @@ def get_ext_wildcards():
 
     for path in WILDCARD_EXT_PATHS:
         wildcard_files.append(path.as_posix())
-        lfiles = [(w, w.relative_to(path).as_posix())
-                  for w in path.rglob("*.txt")
-                  if w.name != "put wildcards here.txt"]
-        wildcard_files.extend(sort_models(lfiles))
+        resolved = [(w, w.relative_to(path).as_posix())
+                    for w in path.rglob("*.txt")
+                    if w.name != "put wildcards here.txt"]
+        wildcard_files.extend(sort_models(resolved))
         wildcard_files.append("-----")
 
     return wildcard_files
@@ -176,14 +180,14 @@ def get_embeddings(sd_model):
 
         # Add embeddings to the correct list
         if (emb_a_shape == V1_SHAPE):
-            emb_v1 = [(v.filename, k, "v1") for (k,v) in emb_type_a.items()]
+            emb_v1 = [(Path(v.filename), k, "v1") for (k,v) in emb_type_a.items()]
         elif (emb_a_shape == V2_SHAPE):
-            emb_v2 = [(v.filename, k, "v2") for (k,v) in emb_type_a.items()]
+            emb_v2 = [(Path(v.filename), k, "v2") for (k,v) in emb_type_a.items()]
 
         if (emb_b_shape == V1_SHAPE):
-            emb_v1 = [(v.filename, k, "v1") for (k,v) in emb_type_b.items()]
+            emb_v1 = [(Path(v.filename), k, "v1") for (k,v) in emb_type_b.items()]
         elif (emb_b_shape == V2_SHAPE):
-            emb_v2 = [(v.filename, k, "v2") for (k,v) in emb_type_b.items()]
+            emb_v2 = [(Path(v.filename), k, "v2") for (k,v) in emb_type_b.items()]
 
         # Get shape of current model
         #vec = sd_model.cond_stage_model.encode_embedding_init_text(",", 1)
@@ -213,10 +217,8 @@ def get_hypernetworks():
 
     # Get a list of all hypernetworks in the folder
     hyp_paths = [Path(h) for h in glob.glob(HYP_PATH.joinpath("**/*").as_posix(), recursive=True)]
-    all_hypernetworks = [h for h in hyp_paths if h.suffix in {".pt"}]
-    # Remove file extensions
-    lfiles = [(h, os.path.splitext(h.name)[0]) for h in all_hypernetworks]
-    return sort_models(lfiles)
+    all_hypernetworks = [(h, h.stem) for h in hyp_paths if h.suffix in {".pt"}]
+    return sort_models(all_hypernetworks)
 
 model_keyword_installed = write_model_keyword_path()
 def get_lora():
@@ -227,17 +229,17 @@ def get_lora():
     lora_paths = [Path(l) for l in glob.glob(LORA_PATH.joinpath("**/*").as_posix(), recursive=True)]
     # Get hashes
     valid_loras = [lf for lf in lora_paths if lf.suffix in {".safetensors", ".ckpt", ".pt"}]
-    lhashes = []
+    loras_with_hash = []
     for l in valid_loras:
         name = l.relative_to(LORA_PATH).as_posix()
-        name = QUO + name + QUO # Wrapped in quote marks.
+        name = f'"{name}"'
         if model_keyword_installed:
-            vhash = get_lora_simple_hash(l)
+            hash = get_lora_simple_hash(l)
         else:
-            vhash = ""
-        lhashes.append((l, name, vhash))
+            hash = ""
+        loras_with_hash.append((l, name, hash))
     # Sort
-    return sort_models(lhashes)
+    return sort_models(loras_with_hash)
 
 
 def get_lyco():
@@ -248,18 +250,17 @@ def get_lyco():
 
     # Get hashes
     valid_lycos = [lyf for lyf in lyco_paths if lyf.suffix in {".safetensors", ".ckpt", ".pt"}]
-    lhashes = []
+    lycos_with_hash = []
     for ly in valid_lycos:
         name = ly.relative_to(LYCO_PATH).as_posix()
-        name = QUO + name + QUO
+        name = f'"{name}"'
         if model_keyword_installed:
-            vhash = get_lora_simple_hash(ly)
+            hash = get_lora_simple_hash(ly)
         else:
-            vhash = ""
-        lhashes.append((ly, name, vhash))
-
+            hash = ""
+        lycos_with_hash.append((ly, name, hash))
     # Sort
-    return sort_models(lhashes)
+    return sort_models(lycos_with_hash)
 
 def write_tag_base_path():
     """Writes the tag base path to a fixed location temporary file"""
@@ -415,6 +416,7 @@ def on_ui_settings():
         "tac_useLycos": shared.OptionInfo(True, "Search for LyCORIS/LoHa"),
         "tac_showWikiLinks": shared.OptionInfo(False, "Show '?' next to tags, linking to its Danbooru or e621 wiki page").info("Warning: This is an external site and very likely contains NSFW examples!"),
         "tac_showExtraNetworkPreviews": shared.OptionInfo(True, "Show preview thumbnails for extra networks if available"),
+        "tac_modelSortOrder": shared.OptionInfo("Name", "Model sort order", gr.Dropdown, lambda: {"choices": ["Name", "Date Modified"]}).info("Order for extra network models and wildcards in dropdown"),
         # Insertion related settings
         "tac_replaceUnderscores": shared.OptionInfo(True, "Replace underscores with spaces on insertion"),
         "tac_escapeParentheses": shared.OptionInfo(True, "Escape parentheses on insertion"),
@@ -437,7 +439,6 @@ def on_ui_settings():
         "tac_extra.addMode": shared.OptionInfo("Insert before", "Mode to add the extra tags to the main tag list", gr.Dropdown, lambda: {"choices": ["Insert before","Insert after"]}),
         # Chant settings
         "tac_chantFile": shared.OptionInfo("demo-chants.json", "Chant filename", gr.Dropdown, lambda: {"choices": json_files_withnone}, refresh=update_json_files).info("Chants are longer prompt presets"),
-        "tac_sortModels": shared.OptionInfo("name", "Model sort order", gr.Dropdown, lambda: {"choices": ["name", "modified_date"]}).info("WIP: Order of appearance for models in dropdown"),
     }
 
     # Add normal settings
@@ -524,6 +525,11 @@ def api_tac(_: gr.Blocks, app: FastAPI):
         except Exception as e:
             return JSONResponse({"error": e}, status_code=500)
 
+    @app.get("/tacapi/v1/sort-direction")
+    async def get_sort_direction():
+        criterium = getattr(shared.opts, "tac_modelSortOrder", "Name")
+        return sort_criteria[criterium]['reverse'] if sort_criteria[criterium] else sort_criteria['Name']['reverse']
+
     @app.get("/tacapi/v1/lora-info/{lora_name}")
     async def get_lora_info(lora_name):
         return await get_json_info(LORA_PATH, lora_name)