Merge branch 'UI2' of https://github.com/ebolam/KoboldAI into UI2

aiserver.py

@@ -5005,24 +5005,27 @@ def calcsubmit(txt):
         #subtxt, min, max = calcsubmitbudget(actionlen, winfo, mem, anotetxt, koboldai_vars.actions, submission=txt)
         subtxt, min, max, found_entries  = koboldai_vars.calc_ai_text(submitted_text=txt)
 
-        if koboldai_vars.experimental_features and koboldai_vars.memory_attn_bias > 1:
+        if koboldai_vars.experimental_features:
             offset = 0
-            bounds = None
+            applied_biases = []
             for c in koboldai_vars.context:
-                length = len(tokenizer.encode(c["text"]))
+                length = len(c["tokens"])
-                if c["type"] == "memory":
+                if c.get("attention_multiplier") and c["attention_multiplier"] != 1:
-                    bounds = [offset, offset + length]
+                    applied_biases.append({"start": offset, "end": offset + length, "multiplier": c.get("attention_multiplier", 1)})
-                    break
                 offset += length
 
-            print(f"Memory bounds: {bounds}")
+            logger.info(f"Applied Biases: {applied_biases}")
-            assert bounds
 
-            bias = [1] * bounds[0]
+            bias = []
-            bias += [koboldai_vars.memory_attn_bias] * bounds[1]
+            for b in applied_biases:
+                for i in range(b["start"], b["end"]):
+                    top_index = len(bias) - 1
+                    if i > top_index:
+                        bias += [1] * (i - top_index)
+                    bias[i] = b["multiplier"]
 
             attention_bias.attention_bias = torch.Tensor(bias).to(breakmodel.primary_device)
-            print(f"Bias by {koboldai_vars.memory_attn_bias} -- {attention_bias.attention_bias}")
+            logger.info(f"Bias by {koboldai_vars.memory_attn_bias} -- {attention_bias.attention_bias}")
         generate(subtxt, min, max, found_entries)
         attention_bias.attention_bias = None
 

koboldai_settings.py

@@ -241,7 +241,8 @@ class koboldai_vars(object):
         if len(memory_tokens) != 0:
             context.append({"type": "memory", 
                             "text": "".join([x[1] for x in memory_data]), 
-                            "tokens": memory_data})
+                            "tokens": memory_data,
+                            "attention_multiplier": self.memory_attn_bias})
             used_tokens += len(memory_tokens)
         
         
@@ -350,7 +351,7 @@ class koboldai_vars(object):
 
             #Add our author's note if we've hit andepth
             if not inserted_author_note and len(actions_seen) >= self.andepth and self.authornote != "":
-                game_context.insert(0, {"type": "authors_note", "text": authors_note_text, "tokens": authors_note_data})
+                game_context.insert(0, {"type": "authors_note", "text": authors_note_text, "tokens": authors_note_data, "attention_multiplier": self.an_attn_bias})
                 inserted_author_note = True
 
             action_data = [[x, self.tokenizer.decode(x)] for x in self.tokenizer.encode(action_text_split[i][0])]
@@ -426,7 +427,7 @@ class koboldai_vars(object):
         ######################################### Verify Author's Note Data in AI Text ########################################################
         #if we don't have enough actions to get to author's note depth then we just add it right before the game text
         if not inserted_author_note and self.authornote != "":
-            game_context.insert(0, {"type": "authors_note", "text": authors_note_text, "tokens": authors_note_data})
+            game_context.insert(0, {"type": "authors_note", "text": authors_note_text, "tokens": authors_note_data, "attention_multiplier": self.an_attn_bias})
         
         
         ######################################### Add our prompt data ########################################################
@@ -783,6 +784,7 @@ class story_settings(settings):
 
         # bias experiment
         self.memory_attn_bias = 1
+        self.an_attn_bias = 1
         
     def save_story(self):
         if not self.no_save:

templates/settings flyout.html

@@ -24,7 +24,7 @@
 		<icon class="material-icons-outlined" style="font-size:14px;position:relative;top:2px;">open_in_new</icon>
 	</span>
 </div>
-<span class="material-icons-outlined cursor search_icon" tooltip="Search Settings" onclick="open_finder();">search</span>
+<span class="material-icons-outlined cursor search_icon" tooltip="Finder" onclick="open_finder();">search</span>
 <div class="flyout_menu_contents">
 
 	<div id="setting_menu_home" class="settings_category_area tab-target tab-target-settings">

templates/story flyout.html

@@ -13,18 +13,18 @@
 			</div>
 			<textarea rows=20 id="memory" class="var_sync_story_memory var_sync_alt_story_memory_length fullwidth" onchange='sync_to_server(this);' oninput="autoResize(this)" autocomplete="off"></textarea>
 
-			<div id="Attention-Bias" class="var_sync_alt_system_experimental_features">
+			<div id="Mem-Attention-Bias" class="var_sync_alt_system_experimental_features">
-				<h4 class="section_header"><label for="Attention-Bias">Attention Bias Test</label></h4>
+				<h4 class="section_header"><label for="Mem-Attention-Bias">Attention Bias Test</label></h4>
 				<span class="help_text">
 					<b>Note: This only works on OPT models for now! Patches will be written for other models once it's known this actually has a positive effect. Upon first use of this bias, you should see "Applying attention bias" in the console.</b><br>
 					This setting <i>may</i> change how the AI pays attention to memory. Any high number in the ballpark of 15 may cause incoherence. The option to select higher numbers is present for experimentation.
 				</span>
-				<input type="range" oninput="memAttn(this.value);" onchange="sync_to_server(this);" class="var_sync_story_memory_attn_bias sync_as_float" value="1" min="1" max="50" step="0.1"></input>
+				<input type="range" oninput="memAttnInput(this.value);" onchange="sync_to_server(this);" class="var_sync_story_memory_attn_bias sync_as_float" value="1" min="1" max="50" step="0.1"></input>
 				<span id="memattnbiaslabel">1</span>
 				<script>
-					const label = document.querySelector("#memattnbiaslabel");
+					const memAttn = document.querySelector("#memattnbiaslabel");
-					function memAttn(val) {
+					function memAttnInput(val) {
-						label.innerText = val;
+						memAttn.innerText = val;
 					}
 				</script>
 			</div>
@@ -49,6 +49,20 @@
 			<input autocomplete="off" id=authors_notes_template type=text class="var_sync_story_authornotetemplate fullwidth" onchange='sync_to_server(this);'><br/>
 			<label for="authors_notes">Author's Notes:</label><br/>
 			<textarea autocomplete="off" rows=16 id="authors_notes" class="var_sync_story_authornote var_sync_alt_story_authornote_length fullwidth" oninput="autoResize(this)" onchange='sync_to_server(this);'></textarea><br/>
+
+			<div id="An-Attention-Bias" class="var_sync_alt_system_experimental_features">
+				<h4 class="section_header"><label for="An-Attention-Bias">Attention Bias Test</label></h4>
+				<span class="help_text">See disclaimer in memory page.</span>
+				<input type="range" oninput="anAttnInput(this.value);" onchange="sync_to_server(this);" class="var_sync_story_an_attn_bias sync_as_float" value="1" min="1" max="50" step="0.1"></input>
+				<span id="anattnbiaslabel">1</span>
+				<script>
+					const anAttn = document.querySelector("#anattnbiaslabel");
+					function anAttnInput(val) {
+						anAttn.innerText = val;
+					}
+				</script>
+			</div>
+
 			<div class="setting_tile_area">
 				{% with menu='author_notes' %}
 					{% with sub_path='' %}