feat: four mode agent

custom_agent.py

@@ -42,7 +42,6 @@ logger = logging.getLogger("custom-agent")
 
 CUSTOM_ENV_PATH = Path(__file__).with_name(".env")
 load_dotenv(dotenv_path=CUSTOM_ENV_PATH)
-AGENT_NAME = os.getenv("CUSTOM_AGENT_NAME", "")
 
 ROOM_LOCATOR_INSTRUCTIONS = """
 你是一个房间物品定位助手。
@@ -72,6 +71,95 @@ VOICE_INPUT_MODE = "voice"
 VISION_VOICE_INPUT_MODE = "vision_voice"
 AUTO_INPUT_MODE = "auto"
 VISION_FRAME_TOPIC = "vision.frame"
+DEFAULT_AGENT_PROFILE = "normal"
+
+
+@dataclass(frozen=True)
+class AgentProfile:
+    agent_name: str
+    llm_provider: str
+    input_mode: str
+
+
+AGENT_PROFILES = {
+    "normal": AgentProfile(
+        agent_name="normal-agent",
+        llm_provider="openai-compatible",
+        input_mode=VOICE_INPUT_MODE,
+    ),
+    "beaver": AgentProfile(
+        agent_name="beaver-agent",
+        llm_provider="beaver",
+        input_mode=VOICE_INPUT_MODE,
+    ),
+    "vision-normal": AgentProfile(
+        agent_name="vision-normal-agent",
+        llm_provider="openai-compatible",
+        input_mode=VISION_VOICE_INPUT_MODE,
+    ),
+    "vision-beaver": AgentProfile(
+        agent_name="vision-beaver-agent",
+        llm_provider="beaver",
+        input_mode=VISION_VOICE_INPUT_MODE,
+    ),
+}
+AGENT_PROFILE_ALIASES = {
+    "default": "normal",
+    "openai": "normal",
+    "openai-compatible": "normal",
+    "llm": "normal",
+    "text": "normal",
+    "voice": "normal",
+    "vision": "vision-normal",
+    "vision-llm": "vision-normal",
+    "vision-openai": "vision-normal",
+    "vision-openai-compatible": "vision-normal",
+}
+
+
+def _normalize_agent_profile(value: str | None) -> str:
+    if not value or not value.strip():
+        return DEFAULT_AGENT_PROFILE
+
+    normalized = value.strip().lower().replace("_", "-")
+    profile = AGENT_PROFILE_ALIASES.get(normalized, normalized)
+    if profile in AGENT_PROFILES:
+        return profile
+
+    logger.warning(
+        "Invalid CUSTOM_AGENT_PROFILE=%r, using %s",
+        value,
+        DEFAULT_AGENT_PROFILE,
+    )
+    return DEFAULT_AGENT_PROFILE
+
+
+def _agent_profile_from_name(agent_name: str | None) -> str | None:
+    if not agent_name or not agent_name.strip():
+        return None
+
+    normalized = agent_name.strip().lower().replace("_", "-")
+    for profile_name, profile in AGENT_PROFILES.items():
+        if normalized == profile.agent_name:
+            return profile_name
+    return None
+
+
+def _selected_agent_profile_name() -> str:
+    configured_profile = os.getenv("CUSTOM_AGENT_PROFILE")
+    if configured_profile and configured_profile.strip():
+        return _normalize_agent_profile(configured_profile)
+
+    inferred_profile = _agent_profile_from_name(os.getenv("CUSTOM_AGENT_NAME"))
+    if inferred_profile is not None:
+        return inferred_profile
+
+    return DEFAULT_AGENT_PROFILE
+
+
+AGENT_PROFILE_NAME = _selected_agent_profile_name()
+AGENT_PROFILE = AGENT_PROFILES[AGENT_PROFILE_NAME]
+AGENT_NAME = os.getenv("CUSTOM_AGENT_NAME") or AGENT_PROFILE.agent_name
 
 DEFAULT_EMOTION = "neutral"
 EMOTION_LABELS = {
@@ -614,7 +702,25 @@ def _model_image_save_dir_from_env() -> Path | None:
     return Path(__file__).with_name("model_images")
 
 
-server = AgentServer()
+def _agent_server_from_env() -> AgentServer:
+    configured_port = os.getenv("CUSTOM_AGENT_HTTP_PORT")
+    if configured_port is None:
+        return AgentServer()
+
+    try:
+        port = int(configured_port)
+    except ValueError:
+        logger.warning("Invalid integer for CUSTOM_AGENT_HTTP_PORT=%r, using 0", configured_port)
+        port = 0
+
+    if port < 0 or port > 65535:
+        logger.warning("Invalid CUSTOM_AGENT_HTTP_PORT=%r, using 0", configured_port)
+        port = 0
+
+    return AgentServer(port=port)
+
+
+server = _agent_server_from_env()
 
 
 def prewarm(proc: JobProcess) -> None:
@@ -640,10 +746,10 @@ async def entrypoint(ctx: JobContext) -> None:
     LLM_BASE_URL = os.getenv("CUSTOM_LLM_BASE_URL")
     LLM_MODEL = os.getenv("CUSTOM_LLM_MODEL", "qwen-max")
     LLM_API_KEY = os.getenv("CUSTOM_LLM_API_KEY")
-    LLM_PROVIDER = os.getenv("CUSTOM_LLM_PROVIDER", "openai").strip().lower()
+    LLM_PROVIDER = os.getenv("CUSTOM_LLM_PROVIDER", AGENT_PROFILE.llm_provider).strip().lower()
     TEXT_LLM_MODEL = os.getenv("CUSTOM_TEXT_LLM_MODEL", LLM_MODEL)
     VISION_LLM_MODEL = os.getenv("CUSTOM_VISION_LLM_MODEL", LLM_MODEL)
-    INPUT_MODE = _normalize_input_mode(os.getenv("CUSTOM_AGENT_INPUT_MODE"))
+    INPUT_MODE = _normalize_input_mode(os.getenv("CUSTOM_AGENT_INPUT_MODE", AGENT_PROFILE.input_mode))
     if LLM_PROVIDER not in {
         "openai",
         "openai-compatible",
@@ -656,7 +762,10 @@ async def entrypoint(ctx: JobContext) -> None:
     if LLM_PROVIDER in {"openai", "openai-compatible"} and not LLM_API_KEY:
         raise RuntimeError(f"CUSTOM_LLM_API_KEY is not set in {CUSTOM_ENV_PATH}")
     logger.info(
-        "Using LLM provider=%s model=%s base_url=%s",
+        "Using agent profile=%s agent_name=%s input_mode=%s llm_provider=%s model=%s base_url=%s",
+        AGENT_PROFILE_NAME,
+        AGENT_NAME or "<automatic>",
+        INPUT_MODE,
         LLM_PROVIDER,
         LLM_MODEL,
         LLM_BASE_URL or "OpenAI default",