WeLe Agentic AI with Docker deployment

.env.example

@@ -55,3 +55,18 @@ RATE_LIMIT_MAX=40
 # --- Artifacts ---
 ARTIFACT_DIR=./storage/artifacts
 ARTIFACT_TTL_HOURS=72
+
+# --- Voice (speech-to-speech, CPU, in-process) ---
+# Models are ONNX via Transformers.js — no GPU, no Python, no second service.
+#   STT  onnx-community/whisper-base   Tamil + English + language detection
+#   TTS  assets/tts/mms-tts-tam        exported locally; no public ONNX exists
+#   TTS  Xenova/mms-tts-eng            from the Hub
+SPEECH_WARMUP=false
+STT_MODEL=onnx-community/whisper-base
+# Below this confidence, the user's preferred language beats the detector.
+DETECT_CONFIDENCE=0.6
+
+# Endpointing
+VAD_SILENCE_MS=700
+VAD_MIN_SPEECH_MS=250
+VAD_PREFIX_MS=300