wip context viewer

aiserver.py

@@ -39,6 +39,8 @@ import traceback
 import inspect
 import warnings
 import multiprocessing
+from enum import Enum
+from dataclasses import dataclass
 from collections.abc import Iterable
 from collections import OrderedDict
 from typing import Any, Callable, TypeVar, Tuple, Union, Dict, Set, List, Optional, Type
@@ -3970,6 +3972,19 @@ def check_for_backend_compilation():
             break
     koboldai_vars.checking = False
 
+class ContextType(Enum):
+    SOFT_PROMPT = 1
+    STORY = 2
+    WORLD_INFO = 3
+    MEMORY = 4
+    HEADER = 5
+
+@dataclass
+class ContextChunk:
+    def __init__(self, value, context_type: ContextType) -> None:
+        self.value = value
+        self.context_type = context_type
+
 def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False, disable_recentrng=False, no_generate=False):
     # Ignore new submissions if the AI is currently busy
     if(koboldai_vars.aibusy):
@@ -4226,14 +4241,18 @@ def apiactionsubmit(data, use_memory=False, use_world_info=False, use_story=Fals
         mem = koboldai_vars.memory + "\n"
     else:
         mem = koboldai_vars.memory
+
     if(use_authors_note and koboldai_vars.authornote != ""):
         anotetxt  = ("\n" + koboldai_vars.authornotetemplate + "\n").replace("<|>", koboldai_vars.authornote)
     else:
         anotetxt = ""
+
     MIN_STORY_TOKENS = 8
     story_tokens = []
     mem_tokens = []
     wi_tokens = []
+    context = []
+
     story_budget = lambda: koboldai_vars.max_length - koboldai_vars.sp_length - koboldai_vars.genamt - len(tokenizer._koboldai_header) - len(story_tokens) - len(mem_tokens) - len(wi_tokens)
     budget = lambda: story_budget() + MIN_STORY_TOKENS
     if budget() < 0:
@@ -4241,15 +4260,20 @@ def apiactionsubmit(data, use_memory=False, use_world_info=False, use_story=Fals
             "msg": f"Your Max Tokens setting is too low for your current soft prompt and tokenizer to handle. It needs to be at least {koboldai_vars.max_length - budget()}.",
             "type": "token_overflow",
         }}), mimetype="application/json", status=500))
+
     if use_memory:
         mem_tokens = tokenizer.encode(utils.encodenewlines(mem))[-budget():]
+
     if use_world_info:
         world_info, _ = checkworldinfo(data, force_use_txt=True, scan_story=use_story)
         wi_tokens = tokenizer.encode(utils.encodenewlines(world_info))[-budget():]
+
     if use_story:
         if koboldai_vars.useprompt:
             story_tokens = tokenizer.encode(utils.encodenewlines(koboldai_vars.prompt))[-budget():]
+
     story_tokens = tokenizer.encode(utils.encodenewlines(data))[-story_budget():] + story_tokens
+
     if use_story:
         for i, action in enumerate(reversed(koboldai_vars.actions.values())):
             if story_budget() <= 0:
@@ -4260,6 +4284,23 @@ def apiactionsubmit(data, use_memory=False, use_world_info=False, use_story=Fals
                 story_tokens = tokenizer.encode(utils.encodenewlines(anotetxt))[-story_budget():] + story_tokens
         if not koboldai_vars.useprompt:
             story_tokens = tokenizer.encode(utils.encodenewlines(koboldai_vars.prompt))[-budget():] + story_tokens
+
+    # Context tracker
+    if koboldai_vars.sp:
+        context.append(ContextChunk(koboldai_vars.sp, ContextType.SOFT_PROMPT))
+
+    if tokenizer._koboldai_header:
+        context.append(ContextChunk(tokenizer._koboldai_header, ContextType.HEADER))
+    
+    if mem_tokens:
+        context.append(ContextChunk(mem_tokens, ContextType.MEMORY))
+
+    if wi_tokens:
+        context.append(ContextChunk(wi_tokens, ContextType.WORLD_INFO))
+
+    if story_tokens:
+        context.append(ContextChunk(story_tokens, ContextType.STORY))
+
     tokens = tokenizer._koboldai_header + mem_tokens + wi_tokens + story_tokens
     assert story_budget() >= 0
     minimum = len(tokens) + 1
@@ -4270,6 +4311,8 @@ def apiactionsubmit(data, use_memory=False, use_world_info=False, use_story=Fals
     elif(koboldai_vars.use_colab_tpu or koboldai_vars.model in ("TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX")):
         genout = apiactionsubmit_tpumtjgenerate(tokens, minimum, maximum)
 
+    koboldai_vars.context = context
+    print(context)
     return genout
 
 #==================================================================#