feat: add configurable AI model pool

services/api/app/integrations/openai_compatible.py

@@ -4,48 +4,70 @@ from urllib.parse import urljoin
 
 import httpx
 
+from app.integrations.model_router import ModelRouter
+
 
 class OpenAICompatibleGateway:
-    """One adapter for OpenAI, lk666.ai and other OpenAI-compatible gateways."""
+    """Adapter for independently configured OpenAI-compatible model-pool items."""
 
     def __init__(self, values: Mapping[str, Any]) -> None:
         self.values = values
+        self.router = ModelRouter(values)
 
-    def _url(self, path_key: str, fallback: str) -> str:
-        base_url = str(self.values.get("ai_base_url", "")).rstrip("/") + "/"
-        path = str(self.values.get(path_key, fallback)).lstrip("/")
+    @staticmethod
+    def _url(item: Mapping[str, Any], path_key: str, fallback: str) -> str:
+        base_url = str(item.get("base_url", "")).rstrip("/") + "/"
+        path = str(item.get(path_key, fallback)).lstrip("/")
         return urljoin(base_url, path)
 
-    @property
-    def headers(self) -> dict[str, str]:
-        return {
-            "Authorization": f"Bearer {self.values.get('ai_api_key', '')}",
-            "Content-Type": "application/json",
-        }
+    @staticmethod
+    def _headers(item: Mapping[str, Any], *, json_content: bool = True) -> dict[str, str]:
+        headers = {"Authorization": f"Bearer {item.get('api_key', '')}"}
+        if json_content:
+            headers["Content-Type"] = "application/json"
+        return headers
 
-    async def list_models(self) -> list[str]:
+    async def list_models(self, model: Mapping[str, Any] | None = None) -> list[str]:
+        item = model or self.router.orchestrator()
         async with httpx.AsyncClient(timeout=15) as client:
-            response = await client.get(self._url("ai_models_path", "/models"), headers=self.headers)
+            response = await client.get(
+                self._url(item, "models_path", "/models"),
+                headers=self._headers(item),
+            )
             response.raise_for_status()
             payload = response.json()
-        return [item["id"] for item in payload.get("data", []) if isinstance(item, dict) and item.get("id")]
+        return [candidate["id"] for candidate in payload.get("data", []) if isinstance(candidate, dict) and candidate.get("id")]
 
-    async def chat(self, messages: list[dict[str, Any]], *, vision: bool = False) -> dict[str, Any]:
-        model_key = "vision_model" if vision else "orchestrator_model"
+    async def chat(
+        self,
+        messages: list[dict[str, Any]],
+        *,
+        vision: bool = False,
+        model_instance_id: str | None = None,
+    ) -> dict[str, Any]:
+        item = self.router.choose("spatial", model_instance_id) if vision else self.router.orchestrator()
         async with httpx.AsyncClient(timeout=120) as client:
             response = await client.post(
-                self._url("ai_chat_path", "/chat/completions"),
-                headers=self.headers,
-                json={"model": self.values[model_key], "messages": messages},
+                self._url(item, "chat_path", "/chat/completions"),
+                headers=self._headers(item),
+                json={"model": item["model_id"], "messages": messages},
             )
             response.raise_for_status()
             return response.json()
-    async def generate_image(self, prompt: str, **options: Any) -> dict[str, Any]:
-        payload = {"model": self.values["image_model"], "prompt": prompt, **options}
+
+    async def generate_image(
+        self,
+        prompt: str,
+        *,
+        model_instance_id: str | None = None,
+        **options: Any,
+    ) -> dict[str, Any]:
+        item = self.router.choose("image", model_instance_id)
+        payload = {"model": item["model_id"], "prompt": prompt, **options}
         async with httpx.AsyncClient(timeout=180) as client:
             response = await client.post(
-                self._url("ai_image_generation_path", "/images/generations"),
-                headers=self.headers,
+                self._url(item, "image_generation_path", "/images/generations"),
+                headers=self._headers(item),
                 json=payload,
             )
             response.raise_for_status()
@@ -58,19 +80,18 @@ class OpenAICompatibleGateway:
         *,
         filename: str = "image.png",
         mask: bytes | None = None,
+        model_instance_id: str | None = None,
         **options: Any,
     ) -> dict[str, Any]:
-        files: dict[str, tuple[str, bytes, str]] = {
-            "image": (filename, image, "image/png"),
-        }
+        item = self.router.choose("image", model_instance_id)
+        files: dict[str, tuple[str, bytes, str]] = {"image": (filename, image, "image/png")}
         if mask is not None:
             files["mask"] = ("mask.png", mask, "image/png")
-        data = {"model": self.values["image_model"], "prompt": prompt, **options}
-        headers = {"Authorization": self.headers["Authorization"]}
+        data = {"model": item["model_id"], "prompt": prompt, **options}
         async with httpx.AsyncClient(timeout=180) as client:
             response = await client.post(
-                self._url("ai_image_edit_path", "/images/edits"),
-                headers=headers,
+                self._url(item, "image_edit_path", "/images/edits"),
+                headers=self._headers(item, json_content=False),
                 data=data,
                 files=files,
             )