setup models

dmb/adapter.py

@@ -0,0 +1,50 @@
+"""Interface comum dos adaptadores JEV locais (tarefas 42–47)."""
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from pathlib import Path
+
+
+class Adapter(ABC):
+    """Um candidato servido atrás de POST /v1/systemone.
+
+    `decide` recebe o estado já serializado (texto) e as perguntas no formato JEV e
+    devolve as respostas JEV de cada pergunta, mais o total de tokens de entrada.
+    """
+
+    name: str
+    adapter_version = "0.1.0"
+    probabilities_source = "native"
+
+    def __init__(self, model_dir: str | Path, revision: str, device: str = "auto",
+                 context_limit: int | None = None):
+        self.model_dir = Path(model_dir)
+        self.revision = revision
+        self.device = device
+        self._context_limit = context_limit
+
+    @property
+    def model_id(self) -> str:
+        return f"{self.name}@{self.revision[:12]}"
+
+    @property
+    def context_limit(self) -> int:
+        return self._context_limit or self.native_context_limit()
+
+    @abstractmethod
+    def load(self) -> None: ...
+
+    @abstractmethod
+    def native_context_limit(self) -> int: ...
+
+    @abstractmethod
+    def count_tokens(self, text: str) -> int: ...
+
+    @abstractmethod
+    def decide(self, state: str, questions: dict) -> tuple[dict, int]: ...
+
+    def describe(self) -> dict:
+        return {"name": self.name, "model_id": self.model_id, "revision": self.revision,
+                "adapter_version": self.adapter_version, "device": self.device,
+                "context_limit": self.context_limit,
+                "probabilities_source": self.probabilities_source}