fix: llama-server-fast context-size exhaustion breaking Auto Mode classifier

Real failure: "Auto Mode couldn't classify this action (Classifier
stage 1 unavailable)". Reproduced directly against the server:

  {"error":{"message":"[400]: request (6186 tokens) exceeds the
  available context size (4096 tokens)"...

LLAMA_FAST_CTX_SIZE=8192 is the TOTAL across every LLAMA_FAST_PARALLEL
slot, not per-request — the main model's own .env.example comment
already calls this out, missed it when llama-server-fast was set up
(#44). With PARALLEL=2 that's 4096/slot, too small for a real
classifier call (hints + environment + recent tool-call history).

Fixed by dropping to a single slot (LLAMA_FAST_PARALLEL=1) rather than
raising ctx-size — this service doesn't need concurrent classifier
calls the way the main model needs concurrent chat sessions, so this
costs no extra VRAM. The full 8192 now goes to the one slot.

docker compose config -q validated.

Refs #5

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MrnMEdzeQzqZE5soVEXPCx

.env.example

@@ -116,11 +116,22 @@ LLAMA_FAST_MODEL_FILE=Qwen3-4B-Instruct-2507-UD-Q8_K_XL.gguf
 # Same reasoning as LLAMA_GPU_LAYERS above — full GPU offload, this model
 # is dense too.
 LLAMA_FAST_GPU_LAYERS=999
-# Classifier transcripts are truncated/bounded by qwen-code itself (see its
+# --ctx-size is the TOTAL across every LLAMA_FAST_PARALLEL slot, not per
-# own Auto Mode docs) — no need for anywhere near the 27B's huge context.
+# request — same halving already called out for the main model above.
-# 8192 keeps this instance's KV cache negligible.
+# Was PARALLEL=2, silently halving this to 4096/slot — too small: a real
+# classifier call (hints + environment + recent tool-call history) hit
+# "exceeds the available context size (4096 tokens)" in practice, which
+# qwen-code surfaces as "Auto Mode couldn't classify this action
+# (Classifier stage 1 unavailable)" — see issue #5. Fixed by dropping to
+# a single slot instead of raising ctx-size (no extra VRAM, and this
+# service doesn't need concurrent classifier calls the way the main
+# model needs concurrent chat sessions) — the full 8192 now goes to the
+# one slot. If hints.allow/softDeny/hardDeny ever approach their
+# 50-entries-each ceiling, raise LLAMA_FAST_CTX_SIZE instead — qwen-code
+# caps those at 200 chars x 150 entries plus 40,000 chars of
+# historical-action context, which can exceed 8192 tokens worst-case.
 LLAMA_FAST_CTX_SIZE=8192
-LLAMA_FAST_PARALLEL=2
+LLAMA_FAST_PARALLEL=1
 
 # --- ComfyUI diffusion model (Qwen-Image, FP8 — see docs/research/
 # image-generation-model-choice.md and issue #42) ---

docker-compose.yml

@@ -70,7 +70,7 @@ services:
       --port 8080
       --n-gpu-layers ${LLAMA_FAST_GPU_LAYERS:-999}
       --ctx-size ${LLAMA_FAST_CTX_SIZE:-8192}
-      --parallel ${LLAMA_FAST_PARALLEL:-2}
+      --parallel ${LLAMA_FAST_PARALLEL:-1}
       --flash-attn on
       --cache-type-k q8_0
       --cache-type-v q8_0