Ch2

.env.example

@@ -89,6 +89,13 @@ SEARXNG_URL=
 BRAIN_ARTICLE_SYNTHESIS_ENABLED=true
 # Language tag for generated KB drafts (for example de-DE or en-US).
 BRAIN_ARTICLE_LANGUAGE=de-DE
+# Generate-then-review pipeline. Use a dedicated author model if it is available
+# on at least one healthy Ollama pool node, e.g. gemma3:12b.
+# The review model should be different from the author model when possible.
+BRAIN_ARTICLE_SYNTHESIS_MODEL=qwen3:8b
+BRAIN_ARTICLE_REVIEW_MODEL=qwen3:8b
+# Number of targeted research + rewrite loops after the reviewer finds unsupported claims.
+BRAIN_ARTICLE_REVIEW_REPAIR_ROUNDS=1
 BRAIN_ARTICLE_MIN_SOURCES=3
 BRAIN_ARTICLE_MAX_SOURCES=8
 BRAIN_ARTICLE_MIN_PRODUCTION_RATIO=0.70
@@ -100,14 +107,16 @@ BRAIN_ARTICLE_MIN_ANSWER_CHARS=420
 BRAIN_ARTICLE_MAX_RESEARCH_QUERIES=6
 # Raw SearXNG candidates per query.
 BRAIN_ARTICLE_RESEARCH_RESULTS=12
-# Iterative search/reformulation rounds.
+# Upper research-planning budget. The active article pipeline performs one broad
+# initial collection cycle; later targeted searches are driven by the reviewer.
 BRAIN_ARTICLE_RESEARCH_ROUNDS=3
 # Highest-ranked pages whose full content is downloaded.
 BRAIN_ARTICLE_RESEARCH_FETCH_RESULTS=6
-# Reserve up to this many fetch slots for promising candidates below the final
-# relevance threshold. They are re-evaluated against the extracted full text.
+# Legacy/autonomous evidence mode and cached-material reuse still use these
+# thresholds. The active generate-then-review article path itself fills its
+# fetch budget from the highest-ranked SearXNG results without a semantic
+# acceptance gate before drafting.
 BRAIN_ARTICLE_RESEARCH_EXPLORATION_RESULTS=3
-# Lower title/snippet threshold used only before the full-text fetch.
 BRAIN_ARTICLE_RESEARCH_PREFETCH_MIN_RELEVANCE=0.25
 BRAIN_ARTICLE_RESEARCH_MIN_RELEVANCE=0.55
 BRAIN_ARTICLE_RESEARCH_MIN_QUALITY=0.35