Adding updates to Festinger

plugins/festinger/festinger/main.py

@@ -495,17 +495,19 @@ async def process_prompt(body: dict, path: str, pool, cfg: dict) -> dict:
     salient_for_read: list[int] = []
     salient_for_write: list[str] = []
 
+    # Novel words found this prompt that aren't in the cache yet.
+    # We cap at MAX_NOVEL_PER_PROMPT to avoid flooding on large system prompts.
+    MAX_NOVEL_PER_PROMPT = 5
+    novel_this_prompt: list[str] = []
+
     for token in tokens:
         soas_row = cache.soas_by_token.get(token)
 
         if soas_row is None:
-            # Token is absent from the dictionary entirely → novel domain word.
-            # Give it an initial high saliency so recollection fires immediately
-            # and instructs the model to ask the user what it is.
-            soas_row = await create_novel_soas(pool, token)
-            salient_for_read.append(soas_row.id)
-            # Do NOT add to salient_for_write: we have no basis for LLM-inferred
-            # relationships yet — let the conversation teach us via cue scanner.
+            # Token absent from dictionary → candidate novel domain word.
+            # Collect for batch processing; apply a per-prompt cap.
+            if len(novel_this_prompt) < MAX_NOVEL_PER_PROMPT:
+                novel_this_prompt.append(token)
             continue
 
         if soas_row.saliency == 0.0 and soas_row.novelty == 0.0:
@@ -517,11 +519,21 @@ async def process_prompt(body: dict, path: str, pool, cfg: dict) -> dict:
         if soas_row.saliency >= read_threshold:
             salient_for_read.append(soas_row.id)
 
-        if soas_row.saliency >= write_threshold and soas_row.novelty > 0.0:
-            # Only enqueue domain-specific words for LLM relationship extraction,
-            # not freshly-created novel words (novelty=1.0 but just inserted).
+        # Only enqueue for LLM write if the concept already has URD edges —
+        # i.e. we know *something* about it and may want to expand that knowledge.
+        # Never enqueue freshly-novel words: let the conversation teach us instead.
+        if (
+            soas_row.saliency >= write_threshold
+            and soas_row.novelty > 0.0
+            and cache.urd_by_concept.get(soas_row.id)
+        ):
             salient_for_write.append(token)
 
+    # Create SOAS entries for novel words and add them to the read list.
+    for token in novel_this_prompt:
+        soas_row = await create_novel_soas(pool, token)
+        salient_for_read.append(soas_row.id)
+
     for token in salient_for_write:
         await enqueue_concept(token)