config(litellm): apply canonical Qwen3.8 sampling; fix presence_penalty on the thinking alias

Sourced from upstream rather than tuned by hand. Qwen/Qwen3.8-27B card
'Best Practices' 1 and unsloth/Qwen3.8-27B 1 are byte-identical:

  Thinking: temperature=1.0 top_p=0.95 top_k=20 min_p=0.0
            presence_penalty=0.0 repetition_penalty=1.0
  Instruct: temperature=0.7 top_p=0.80 top_k=20 min_p=0.0
            presence_penalty=1.5 repetition_penalty=1.0

REAL BUG FIXED: gen-reasoning carried presence_penalty=1.5 -- the
INSTRUCT-mode value applied to a THINKING deployment, where canonical is
0.0. Corrected.

gen was already canonical; added the missing explicit min_p and
repetition_penalty so the full set is visible at the call site rather than
relying on backend defaults that happen to agree.

DELIBERATELY NOT canonicalised: summarizer, classifier, image-judge and
qwen-image-bench run temperature=0 (and the judges top_k=1,
repetition_penalty=1.05) because determinism is the point of those seats.
Forcing temperature=0.7 on a classifier to match a chat preset would break
their contract, so canonical is applied only where the alias is actually
doing open-ended generation.

Recorded against presence_penalty=1.5, which upstream itself hedges on
verbatim: 'you can adjust the presence_penalty parameter between 0 and 2
to reduce endless repetition. However, using a higher value may
occasionally result in language mixing and a slight decrease in model
performance.' 1.5 is high in that band and is the operator's suspected
trigger for the multi-turn degradation. Left at canonical so the baseline
is defensible, with the caveat and the 0.0-0.5 fallback documented inline
as the first dial to move if it recurs.

stacks/litellm/conf/config.yaml

@@ -131,6 +131,21 @@ model_list:
   #     thinking (dvalin-smithy canonical 2026-07-08, validated vs Qwen guidance). gen
   #     non-thinking temp 0.7/top_p 0.8; gen-reasoning thinking temp 1.0/top_p 0.95 (the
   #     GENERAL thinking profile, not the 0.6 coding sub-profile). docs/pfi/model-sampler-defaults.md. ---
+  # CANONICAL Qwen3.8 INSTRUCT (non-thinking) sampling set, verified 2026-08-16
+  # against BOTH upstreams, which are byte-identical on this:
+  #   Qwen/Qwen3.8-27B card "Best Practices" §1  and  unsloth/Qwen3.8-27B §1
+  #   temperature=0.7, top_p=0.80, top_k=20, min_p=0.0,
+  #   presence_penalty=1.5, repetition_penalty=1.0
+  #
+  # ⚠️ presence_penalty=1.5 is canonical BUT is the one value upstream itself
+  # hedges on, verbatim: "you can adjust the presence_penalty parameter between
+  # 0 and 2 to reduce endless repetition. However, using a higher value may
+  # occasionally result in LANGUAGE MIXING and a slight decrease in model
+  # performance." 1.5 sits high in that 0-2 band. If short/degraded replies
+  # reappear on long multi-turn conversations, THIS is the first dial to move
+  # (try 0.0-0.5) — operator's own hypothesis 2026-08-16, and upstream's caveat
+  # supports it. Left at canonical for now so the baseline is defensible rather
+  # than hand-tuned.
   - model_name: gen
     litellm_params:
       model: hosted_vllm/qwen3.8-27b-uncensored
@@ -141,6 +156,8 @@ model_list:
       top_p: 0.8
       extra_body:
         top_k: 20
+        min_p: 0.0
+        repetition_penalty: 1.0
         chat_template_kwargs:
           enable_thinking: false
     model_info:
@@ -152,11 +169,21 @@ model_list:
       model: hosted_vllm/qwen3.8-27b-uncensored-thinking
       api_base: http://10.250.50.54:8015/v1
       api_key: os.environ/VLLM_API_KEY
-      presence_penalty: 1.5
+      # CANONICAL Qwen3.8 THINKING sampling set (Qwen + unsloth "Best Practices"
+      # §1, identical in both): temperature=1.0, top_p=0.95, top_k=20,
+      # min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0.
+      #
+      # ⚠️ presence_penalty was 1.5 here until 2026-08-16 — the INSTRUCT-mode
+      # value applied to a THINKING deployment. Canonical for thinking mode is
+      # 0.0, and upstream warns a high presence_penalty can cause language
+      # mixing and degrade performance. Corrected to 0.0.
+      presence_penalty: 0.0
       temperature: 1.0
       top_p: 0.95
       extra_body:
         top_k: 20
+        min_p: 0.0
+        repetition_penalty: 1.0
         chat_template_kwargs:
           enable_thinking: true
     model_info: