Always-on grounded retrieval with SearxNG and role-scoped Ollama models (#62).

Phases 1–3: split THINKING/FAST/UTILITY/EMBED models, structured search with
SearxNG primary + DDGS failover, fail-open grounding, citations on Prompt + WS
frames, single history window with prompt budgeting, and reindex_embeddings.

.env.prod.example

@@ -32,8 +32,22 @@ WEB_PORT=8003
 
 # Ollama on GPU host (ai-server-4080). Firewall must allow 10.0.0.0/24 → :11434.
 OLLAMA_BASE_URL=http://10.0.0.128:11434
-OLLAMA_MODEL=llama3.2
-OLLAMA_EMBED_MODEL=llama3.2
+# Role-scoped models (#62). After changing OLLAMA_EMBED_MODEL, run:
+#   python manage.py reindex_embeddings
+OLLAMA_MODEL=gpt-oss:20b
+OLLAMA_MODEL_THINKING=gpt-oss:20b
+OLLAMA_MODEL_FAST=gemma4:latest
+OLLAMA_MODEL_UTILITY=llama3.2
+OLLAMA_EMBED_MODEL=nomic-embed-text
+OLLAMA_NUM_CTX_THINKING=16384
+OLLAMA_NUM_CTX_FAST=8192
+
+# Web search (#62) — self-hosted SearxNG (recommended). DDGS is automatic failover.
+ALLOW_INTERNET_ACCESS=true
+SEARCH_PROVIDER=searxng
+SEARCH_FAILOVER_PROVIDER=ddgs
+# Point at the SearxNG container/service on the LAN (see README "SearxNG").
+SEARXNG_BASE_URL=http://10.0.0.128:8080
 
 # Email (SMTP2GO)
 EMAIL_HOST=mail.smtp2go.com