feat: rebuild as multi-user web agent

agent_platform/models.py

@@ -0,0 +1,61 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Literal
+
+Mode = Literal["chat", "work"]
+Strength = Literal["light", "medium", "high"]
+
+
+@dataclass(frozen=True, slots=True)
+class ModelSpec:
+    public_id: str
+    display_name: str
+    mode: Mode
+    strength: Strength
+    provider_model: str
+    max_iterations: int
+    context_char_budget: int
+
+
+_TIERS = {
+    "light": ("轻度", "ChatGPT-5.6:Luna", 8, 120_000),
+    "medium": ("中", "ChatGPT-5.6:Terra", 16, 240_000),
+    "high": ("高", "ChatGPT-5.6:Sol", 24, 400_000),
+}
+
+MODEL_SPECS: dict[str, ModelSpec] = {
+    f"{mode}-{strength}": ModelSpec(
+        public_id=f"{mode}-{strength}",
+        display_name=f"{'Chat' if mode == 'chat' else 'Work'} · {label}",
+        mode=mode,
+        strength=strength,
+        provider_model=provider,
+        max_iterations=max_iterations,
+        context_char_budget=context_budget,
+    )
+    for mode in ("chat", "work")
+    for strength, (label, provider, max_iterations, context_budget) in _TIERS.items()
+}
+
+
+def get_model_spec(model_id: str) -> ModelSpec:
+    try:
+        return MODEL_SPECS[model_id]
+    except KeyError as exc:
+        raise ValueError(f"Unsupported model: {model_id}") from exc
+
+
+def openai_model_list() -> dict:
+    return {
+        "object": "list",
+        "data": [
+            {
+                "id": spec.public_id,
+                "object": "model",
+                "owned_by": "k1412-agent",
+                "name": spec.display_name,
+            }
+            for spec in MODEL_SPECS.values()
+        ],
+    }