feat(stt): beam-search decoding + no prev-text conditioning for accuracy

Whisper was decoding with beam_size=1 (greedy), the least accurate setting,
which hurt recognition on short/accented/noisy Discord-mic speech. Switch the
default to beam search (5, Whisper's own default) and stop conditioning on the
previous clip's transcript (which causes repetition/drift on isolated short
utterances rather than helping). Both are env-tunable (STT_BEAM_SIZE,
STT_CONDITION_ON_PREV) so accuracy/latency can be traded without a code change;
wired into docker-compose and documented in .env.example.

.env.example

@@ -227,6 +227,7 @@ COMPOSE_FILE=docker-compose.yml:docker-compose.gpu-linux.yml
 # OLLAMA_CHAT_MODEL=qwen2.5:7b   # quality (needs ~5GB VRAM + whisper small)
 # OLLAMA_CHAT_MODEL=qwen2.5:3b   # speed (fits easily, faster on 8GB GPUs)
 # WHISPER_MODEL=small            # small frees VRAM for a bigger LLM; medium=more accurate
+# STT_BEAM_SIZE=5                # beam search (5) > greedy (1) for accuracy; lower for speed
 # MELO_DEVICE=cuda               # cpu if no GPU on the bot host
 
 # --- Settings web UI (http://localhost:8765/settings on the bot host) ---