Clean up monitoring TG Python adapter

.env.example

@@ -24,16 +24,17 @@ POSTGRES_PORT=5432
 POLL_INTERVAL_SECONDS=60
 POLL_HISTORY_LIMIT=50
 
-# API
+# Go public API
 API_HOST=0.0.0.0
 API_PORT=8000
+PUBLIC_BASE_PATH=/api/monitoring-tg
+PYTHON_BASE_URL=http://127.0.0.1:8001
 
 # Media (downloaded photos / small videos / docs from parsed messages)
 MEDIA_DIR=/data/media
 MEDIA_MAX_BYTES=20971520
 
-# OpenAI-compatible LLM endpoint. In production this can point to the same
-# vLLM server/model used by telephony.
+# OpenAI-compatible LLM endpoint used by the Go classifier.
 LLM_ENABLED=true
 LLM_BASE_URL=http://10.2.3.5:8002
 LLM_API_KEY=
@@ -41,8 +42,6 @@ LLM_MODEL=qwen2.5-14b
 LLM_TIMEOUT_SECONDS=120
 LLM_MAX_TOKENS=600
 LLM_MIN_TEXT_LENGTH=20
-LLM_CLASSIFIER_OWNER=python
-# How often the background classifier wakes up and how many messages it
-# processes per tick. With 5/20s ≈ 900 messages/hour at ~3-6s per call.
+LLM_CLASSIFIER_OWNER=go
 LLM_CLASSIFY_INTERVAL_SECONDS=20
 LLM_CLASSIFY_BATCH_SIZE=5