chore(amd): update default models and default behavior

livekit-agents/livekit/agents/voice/amd/detector.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import asyncio
+import os
 from types import TracebackType
 from typing import TYPE_CHECKING, Literal, TypedDict
 
@@ -16,6 +17,7 @@
 from ...telemetry import trace_types, tracer
 from ...types import NOT_GIVEN, NotGivenOr
 from ...utils import EventEmitter, aio, is_given
+from ...utils.misc import is_cloud
 from ...utils.participant import wait_for_track_publication
 from .classifier import (
     AMD_PROMPT,
@@ -35,7 +37,7 @@
     from ..agent_session import AgentSession
 
 EVALUATED_LLM_MODELS: set[str] = {
-    "google/gemini-3.1-flash-lite-preview",
+    "google/gemini-3.1-flash-lite",
     "google/gemini-3-flash-preview",
     "openai/gpt-4.1",
     "openai/gpt-5.2",
@@ -103,18 +105,24 @@ class AMD(EventEmitter[Literal["amd_prediction"]]):
         session: The :class:`AgentSession` to wire AMD to.
         llm: LLM used for greeting classification. Accepts an :class:`LLM`
             instance or an inference model string (e.g.
-            ``"openai/gpt-4.1-mini"``). Omit to fall back to the session's
-            own LLM.
+            ``"openai/gpt-4.1-mini"``). When omitted, AMD auto-selects:
+            if LiveKit inference credentials are available in the environment
+            it uses ``"google/gemini-3.1-flash-lite"`` via the
+            inference gateway; otherwise it falls back to the session's own
+            LLM.
         interrupt_on_machine: If ``True`` (default), interrupt any pending
             agent speech immediately when a machine is detected.
         ivr_detection: If ``True`` (default), automatically start IVR
             navigation when a ``machine-ivr`` result is returned.
         participant_identity: If set, only this participant's audio track
             subscription triggers the detection timers. If omitted, the first
             remote audio track wins.
-        stt: STT used for transcript generation. Required when the session
-            uses no STT (e.g. a realtime model). Omit to reuse the session's
-            STT transcripts.
+        stt: STT used for transcript generation. Accepts an :class:`STT`
+            instance or an inference model string (e.g.
+            ``"cartesia/ink-whisper"``). When omitted, AMD auto-selects:
+            if LiveKit inference credentials are available it uses
+            ``"cartesia/ink-whisper"`` via the inference gateway; otherwise
+            it reuses the session's existing STT transcripts.
         suppress_compatibility_warning: If ``True``, do not log a warning when
             the resolved STT or LLM is not among the bundled AMD-tested model
             strings. Has no effect on classification behavior.
@@ -123,19 +131,36 @@ class AMD(EventEmitter[Literal["amd_prediction"]]):
             omitted, library defaults apply.
     """
 
+    _DEFAULT_LLM_MODEL: str = "google/gemini-3.1-flash-lite"
+    _DEFAULT_STT_MODEL: str = "cartesia/ink-whisper"
+
     def __init__(
         self,
         session: AgentSession,
         *,
-        llm: NotGivenOr[LLM | LLMModels | str] = "google/gemini-3.1-flash-lite-preview",
-        stt: NotGivenOr[STT | str] = "cartesia/ink-whisper",
+        llm: NotGivenOr[LLM | LLMModels | str] = NOT_GIVEN,
+        stt: NotGivenOr[STT | str] = NOT_GIVEN,
         interrupt_on_machine: bool = True,
         ivr_detection: bool = True,
         participant_identity: NotGivenOr[str] = NOT_GIVEN,
         suppress_compatibility_warning: bool = False,
         detection_options: NotGivenOr[DetectionOptions] = NOT_GIVEN,
     ) -> None:
         super().__init__()
+
+        if not is_given(llm) or not is_given(stt):
+            api_key = os.getenv("LIVEKIT_INFERENCE_API_KEY") or os.getenv("LIVEKIT_API_KEY")
+            api_secret = os.getenv("LIVEKIT_INFERENCE_API_SECRET") or os.getenv(
+                "LIVEKIT_API_SECRET"
+            )
+            auto_select = (
+                is_cloud(os.getenv("LIVEKIT_URL", "")) and bool(api_key) and bool(api_secret)
+            )
+            if not is_given(llm):
+                llm = self._DEFAULT_LLM_MODEL if auto_select else NOT_GIVEN
+            if not is_given(stt):
+                stt = self._DEFAULT_STT_MODEL if auto_select else NOT_GIVEN
+
         self._llm_config: NotGivenOr[LLM | LLMModels | str] = llm
         self._session: AgentSession = session
         self._interrupt_on_machine = interrupt_on_machine
@@ -156,11 +181,12 @@ def __init__(
         )
 
         if not self._suppress_compatibility_warning:
-            _warn_if_not_evaluated(
-                self._stt.model if is_given(self._stt) else None,
-                EVALUATED_STT_MODELS,
-                model_kind="stt",
-            )
+            if is_given(self._stt):
+                _warn_if_not_evaluated(
+                    self._stt.model,
+                    EVALUATED_STT_MODELS,
+                    model_kind="stt",
+                )
 
         self._stt_task: asyncio.Task[None] | None = None
         self._audio_ch: aio.Chan[rtc.AudioFrame] | None = None