✨ add llm matchers

.gitignore

@@ -160,3 +160,7 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 .idea/
+
+.entari/
+.vscode/
+data.db

entari.yml

@@ -7,6 +7,7 @@ basic:
     ignores:
       - httpx._client
       - httpcore._trace
+      - aiosqlite.core
   prefix:
     - /
   schema: true
@@ -18,12 +19,11 @@ plugins:
   .record_message:
     record_send: true
   ::echo: {}
-  ::help: {}
   ::inspect: {}
   ::auto_reload:
     watch_config: true
   entari_plugin_llm:
-    api_key: ${{ env.LLM_API_KEY }}
+    api_key: ${{ env.OPENAI_API_KEY }}
     base_url: https://api.openai.com/v1
     models:
       - name: "deepseek/deepseek-chat"
@@ -33,6 +33,7 @@ plugins:
         api_key: ${{ env.GEMINI_API_KEY }}
         base_url: https://generativelanguage.googleapis.com
       - name: "gpt-4.1-mini"
+        alias: "gpt"
 
     prompt: |
       你是一个由用户提供信息并回答问题的智能助手。请根据用户提供的信息，尽可能准确和简洁地回答他们的问题。如果信息不足以回答问题，请礼貌地告知用户需要更多信息。

pyproject.toml

@@ -10,6 +10,7 @@ dependencies = [
     "openai>=2.14.0",
     "docstring-parser>=0.17.0",
     "litellm>=1.80.9",
+    "entari-plugin-database>=0.2.3",
 ]
 requires-python = ">=3.10"
 readme = "README.md"

src/entari_plugin_llm/__init__.py

@@ -1,4 +1,4 @@
-from arclet.entari import declare_static, metadata
+from arclet.entari import declare_static, metadata
 
 from .config import Config
 from .events import LLMToolEvent as LLMToolEvent
@@ -14,5 +14,12 @@
 declare_static()
 _suppress_litellm_logging()
 
-from . import listeners as listeners
+from .handlers import chat as chat
+from .handlers import check as check
+from .handlers import command as command
 from .service import llm as llm
+
+__all__ = [
+    "llm",
+    "LLMToolEvent",
+]

src/entari_plugin_llm/_jsondata.py

@@ -0,0 +1,54 @@
+import json
+from dataclasses import asdict, dataclass
+from pathlib import Path
+from typing import Any
+
+from arclet.entari import local_data
+
+
+@dataclass(slots=True)
+class LLMState:
+    default_model: str | None = None
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "LLMState":
+        value = data.get("default_model")
+        default_model = value if isinstance(value, str) and value else None
+        return cls(default_model=default_model)
+
+    def to_dict(self) -> dict[str, Any]:
+        return asdict(self)
+
+
+def _state_path() -> Path:
+    return local_data.get_data_file("entari_plugin_llm", "state.json")
+
+
+def _read_state() -> LLMState:
+    path = _state_path()
+    if not path.exists():
+        return LLMState()
+    try:
+        data = json.loads(path.read_text(encoding="utf-8"))
+    except (OSError, json.JSONDecodeError):
+        return LLMState()
+    if not isinstance(data, dict):
+        return LLMState()
+    return LLMState.from_dict(data)
+
+
+def _write_state(data: LLMState) -> None:
+    path = _state_path()
+    path.write_text(
+        json.dumps(data.to_dict(), ensure_ascii=False, indent=2), encoding="utf-8"
+    )
+
+
+def get_default_model() -> str | None:
+    return _read_state().default_model
+
+
+def set_default_model(model_name: str | None) -> None:
+    state = _read_state()
+    state.default_model = model_name if model_name else None
+    _write_state(state)

src/entari_plugin_llm/config.py

@@ -3,6 +3,9 @@
 from arclet.entari import BasicConfModel, plugin_config
 from arclet.entari.config import model_field
 
+from ._jsondata import get_default_model
+from .exception import ModelNotFoundError
+
 
 class ScopedModel(BasicConfModel):
     name: str
@@ -36,14 +39,22 @@ class Config(BasicConfModel):
 def get_model_config(model_name: str | None = None) -> ScopedModel:
     if model_name is None:
         if not _conf.models:
-            raise ValueError("No models configured.")
-        model_name = _conf.models[0].name
+            raise ModelNotFoundError("No models configured.")
+
+        model_name = get_default_model()
 
     for model in _conf.models:
         if model.name == model_name or model.alias == model_name:
             if model.api_key is None:
                 model.api_key = _conf.api_key
-            if model.base_url == "https://api.openai.com/v1" and _conf.base_url != "https://api.openai.com/v1":
+            if (
+                model.base_url == "https://api.openai.com/v1"
+                and _conf.base_url != "https://api.openai.com/v1"
+            ):
                 model.base_url = _conf.base_url
             return model
-    raise ValueError(f"Model {model_name} not found in config.")
+    raise ModelNotFoundError(f"Model {model_name} not found in config.")
+
+
+def get_model_list() -> set[str]:
+    return {m.name for m in _conf.models} | {m.alias for m in _conf.models if m.alias}

src/entari_plugin_llm/exception.py

@@ -0,0 +1,2 @@
+class ModelNotFoundError(Exception):
+    ...

src/entari_plugin_llm/handlers/chat.py

@@ -0,0 +1,40 @@
+from collections import deque
+
+from arclet.entari import MessageCreatedEvent, Session, filter_
+from arclet.entari.config import config_model_validate
+from arclet.entari.event.config import ConfigReload
+from arclet.entari.event.send import SendResponse
+from arclet.letoderea import BLOCK, on
+from arclet.letoderea.typing import Contexts
+
+from ..config import Config, _conf
+from .manager import LLMSessionManager
+
+RECORD = deque(maxlen=16)
+
+@on(SendResponse)
+async def _record(event: SendResponse):
+    if event.result and event.session:
+        RECORD.append(event.session.event.sn)
+
+
+@on(MessageCreatedEvent, priority=1000).if_(filter_.to_me)
+async def run_conversation(session: Session, ctx: Contexts):
+    if session.event.sn in RECORD:
+        return BLOCK
+
+    msg = session.elements.extract_plain_text()
+    answer = await LLMSessionManager.chat(user_input=msg, ctx=ctx, session=session)
+    await session.send(answer)
+    return BLOCK
+
+
+@on(ConfigReload)
+async def reload_config(event: ConfigReload):
+    if event.scope != "plugin":
+        return
+    if event.key not in ("entari_plugin_llm", "llm"):
+        return
+    new_conf = config_model_validate(Config, event.value)
+    _conf.models = new_conf.models
+    _conf.prompt = new_conf.prompt

src/entari_plugin_llm/handlers/check.py

@@ -0,0 +1,41 @@
+from arclet.entari.event.lifespan import Ready
+from arclet.letoderea import on
+
+from .._jsondata import get_default_model, set_default_model
+from ..config import _conf
+from ..log import logger
+
+
+@on(Ready)
+async def _():
+    if not _conf.models:
+        set_default_model(None)
+        logger.warning("未配置任何模型，已清空本地默认模型配置")
+        return
+
+    first_model = _conf.models[0].name
+    default_model = get_default_model()
+    if not default_model:
+        set_default_model(first_model)
+        logger.info(f"未检测到本地默认模型，已设置为首个模型: {first_model}")
+        return
+
+    matched = next(
+        (
+            m
+            for m in _conf.models
+            if m.name == default_model or m.alias == default_model
+        ),
+        None,
+    )
+    if matched is None:
+        set_default_model(first_model)
+        logger.warning(
+            f"本地默认模型不存在于当前配置: {default_model}，已重置为: {first_model}",
+        )
+        return
+
+    if matched.name != default_model:
+        set_default_model(matched.name)
+        logger.info(f"已将本地默认模型标准化为模型名: {matched.name}")
+