ENH: Launch model by version

xinference/api/restful_api.py

@@ -263,6 +263,14 @@ def serve(self, logging_conf: Optional[dict] = None):
             if self.is_authenticated()
             else None,
         )
+        self._router.add_api_route(
+            "/v1/models/{model_type}/{model_name}/versions",
+            self.get_model_versions,
+            methods=["GET"],
+            dependencies=[Security(verify_token, scopes=["models:list"])]
+            if self.is_authenticated()
+            else None,
+        )
         self._router.add_api_route(
             "/v1/models",
             self.list_models,
@@ -280,6 +288,14 @@ def serve(self, logging_conf: Optional[dict] = None):
             if self.is_authenticated()
             else None,
         )
+        self._router.add_api_route(
+            "/v1/models/instance",
+            self.launch_model_by_version,
+            methods=["POST"],
+            dependencies=[Security(verify_token, scopes=["models:start"])]
+            if self.is_authenticated()
+            else None,
+        )
         self._router.add_api_route(
             "/v1/models",
             self.launch_model,
@@ -640,6 +656,44 @@ async def get_instance_info(
             raise HTTPException(status_code=500, detail=str(e))
         return JSONResponse(content=infos)
 
+    async def launch_model_by_version(
+        self, request: Request, wait_ready: bool = Query(True)
+    ) -> JSONResponse:
+        payload = await request.json()
+        model_uid = payload.get("model_uid")
+        model_type = payload.get("model_type")
+        model_version = payload.get("model_version")
+        replica = payload.get("replica", 1)
+        n_gpu = payload.get("n_gpu", "auto")
+
+        try:
+            model_uid = await (
+                await self._get_supervisor_ref()
+            ).launch_model_by_version(
+                model_uid=model_uid,
+                model_type=model_type,
+                model_version=model_version,
+                replica=replica,
+                n_gpu=n_gpu,
+                wait_ready=wait_ready,
+            )
+        except Exception as e:
+            logger.error(str(e), exc_info=True)
+            raise HTTPException(status_code=500, detail=str(e))
+        return JSONResponse(content={"model_uid": model_uid})
+
+    async def get_model_versions(
+        self, model_type: str, model_name: str
+    ) -> JSONResponse:
+        try:
+            content = await (await self._get_supervisor_ref()).get_model_versions(
+                model_type, model_name
+            )
+            return JSONResponse(content=content)
+        except Exception as e:
+            logger.error(e, exc_info=True)
+            raise HTTPException(status_code=500, detail=str(e))
+
     async def build_gradio_interface(
         self, model_uid: str, body: BuildGradioInterfaceRequest, request: Request
     ) -> JSONResponse:

xinference/core/cache_tracker.py

@@ -0,0 +1,99 @@
+# Copyright 2022-2024 XProbe Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from logging import getLogger
+from typing import Dict, List, Optional
+
+import xoscar as xo
+
+logger = getLogger(__name__)
+
+
+class CacheTrackerActor(xo.Actor):
+    def __init__(self):
+        super().__init__()
+        self._model_name_to_version_info: Dict[str, List[Dict]] = {}
+
+    @classmethod
+    def uid(cls) -> str:
+        return "cache_tracker"
+
+    @staticmethod
+    def _map_address_to_file_location(
+        model_version: Dict[str, List[Dict]], address: str
+    ):
+        for model_name, model_versions in model_version.items():
+            for info_dict in model_versions:
+                info_dict["model_file_location"] = (
+                    {address: info_dict["model_file_location"]}
+                    if info_dict["cache_status"]
+                    else None
+                )
+
+    @staticmethod
+    def _update_file_location(data: Dict, origin_version_info: Dict):
+        if origin_version_info["model_file_location"] is None:
+            origin_version_info["model_file_location"] = data
+        else:
+            assert isinstance(origin_version_info["model_file_location"], dict)
+            origin_version_info["model_file_location"].update(data)
+
+    def record_model_version(self, version_info: Dict[str, List[Dict]], address: str):
+        self._map_address_to_file_location(version_info, address)
+        for model_name, model_versions in version_info.items():
+            if model_name not in self._model_name_to_version_info:
+                self._model_name_to_version_info[model_name] = model_versions
+            else:
+                assert len(model_versions) == len(
+                    self._model_name_to_version_info[model_name]
+                ), "Model version info inconsistency between supervisor and worker"
+                for version, origin_version in zip(
+                    model_versions, self._model_name_to_version_info[model_name]
+                ):
+                    if (
+                        version["cache_status"]
+                        and version["model_file_location"] is not None
+                    ):
+                        origin_version["cache_status"] = True
+                        self._update_file_location(
+                            version["model_file_location"], origin_version
+                        )
+
+    def update_cache_status(
+        self,
+        address: str,
+        model_name: str,
+        model_version: Optional[str],
+        model_path: str,
+    ):
+        if model_name not in self._model_name_to_version_info:
+            logger.warning(f"Not record version info for {model_name} for now.")
+        else:
+            for version_info in self._model_name_to_version_info[model_name]:
+                if model_version is None:  # image model
+                    self._update_file_location({address: model_path}, version_info)
+                    version_info["cache_status"] = True
+                else:
+                    if version_info["model_version"] == model_version:
+                        self._update_file_location({address: model_path}, version_info)
+                        version_info["cache_status"] = True
+
+    def unregister_model_version(self, model_name: str):
+        self._model_name_to_version_info.pop(model_name, None)
+
+    def get_model_versions(self, model_name: str) -> List[Dict]:
+        if model_name not in self._model_name_to_version_info:
+            logger.warning(f"Not record version info for model_name: {model_name}")
+            return []
+        else:
+            return self._model_name_to_version_info[model_name]

xinference/core/status_guard.py

@@ -33,6 +33,7 @@ class LaunchStatus(Enum):
 class InstanceInfo(BaseModel):
     model_name: str
     model_uid: str
+    model_version: Optional[str]
     model_ability: List[str]
     replica: int
     status: str

xinference/core/supervisor.py

@@ -32,6 +32,7 @@
     iter_replica_model_uid,
     log_async,
     log_sync,
+    parse_model_version,
     parse_replica_model_uid,
 )
 
@@ -89,37 +90,74 @@ async def __post_create__(self):
         # comment this line to avoid worker lost
         # self._check_dead_nodes_task = asyncio.create_task(self._check_dead_nodes())
         logger.info(f"Xinference supervisor {self.address} started")
+        from .cache_tracker import CacheTrackerActor
         from .status_guard import StatusGuardActor
 
         self._status_guard_ref: xo.ActorRefType[
             "StatusGuardActor"
         ] = await xo.create_actor(
             StatusGuardActor, address=self.address, uid=StatusGuardActor.uid()
         )
+        self._cache_tracker_ref: xo.ActorRefType[
+            "CacheTrackerActor"
+        ] = await xo.create_actor(
+            CacheTrackerActor, address=self.address, uid=CacheTrackerActor.uid()
+        )
 
         from ..model.embedding import (
             CustomEmbeddingModelSpec,
+            generate_embedding_description,
+            get_embedding_model_descriptions,
             register_embedding,
             unregister_embedding,
         )
-        from ..model.llm import register_llm, unregister_llm
-        from ..model.llm.llm_family import CustomLLMFamilyV1
-        from ..model.rerank.custom import (
+        from ..model.image import get_image_model_descriptions
+        from ..model.llm import (
+            CustomLLMFamilyV1,
+            generate_llm_description,
+            get_llm_model_descriptions,
+            register_llm,
+            unregister_llm,
+        )
+        from ..model.rerank import (
             CustomRerankModelSpec,
+            generate_rerank_description,
+            get_rerank_model_descriptions,
             register_rerank,
             unregister_rerank,
         )
 
         self._custom_register_type_to_cls: Dict[str, Tuple] = {
-            "LLM": (CustomLLMFamilyV1, register_llm, unregister_llm),
+            "LLM": (
+                CustomLLMFamilyV1,
+                register_llm,
+                unregister_llm,
+                generate_llm_description,
+            ),
             "embedding": (
                 CustomEmbeddingModelSpec,
                 register_embedding,
                 unregister_embedding,
+                generate_embedding_description,
+            ),
+            "rerank": (
+                CustomRerankModelSpec,
+                register_rerank,
+                unregister_rerank,
+                generate_rerank_description,
             ),
-            "rerank": (CustomRerankModelSpec, register_rerank, unregister_rerank),
         }
 
+        # record model version
+        model_version_infos: Dict[str, List[Dict]] = {}
+        model_version_infos.update(get_llm_model_descriptions())
+        model_version_infos.update(get_embedding_model_descriptions())
+        model_version_infos.update(get_rerank_model_descriptions())
+        model_version_infos.update(get_image_model_descriptions())
+        await self._cache_tracker_ref.record_model_version(
+            model_version_infos, self.address
+        )
+
     @staticmethod
     async def get_builtin_prompts() -> Dict[str, Any]:
         from ..model.llm.llm_family import BUILTIN_LLM_PROMPT_STYLE
@@ -420,6 +458,7 @@ async def register_model(self, model_type: str, model: str, persist: bool):
                 model_spec_cls,
                 register_fn,
                 unregister_fn,
+                generate_fn,
             ) = self._custom_register_type_to_cls[model_type]
 
             if not self.is_local_deployment():
@@ -430,6 +469,9 @@ async def register_model(self, model_type: str, model: str, persist: bool):
             model_spec = model_spec_cls.parse_raw(model)
             try:
                 register_fn(model_spec, persist)
+                await self._cache_tracker_ref.record_model_version(
+                    generate_fn(model_spec), self.address
+                )
             except Exception as e:
                 unregister_fn(model_spec.model_name, raise_error=False)
                 raise e
@@ -439,8 +481,9 @@ async def register_model(self, model_type: str, model: str, persist: bool):
     @log_async(logger=logger)
     async def unregister_model(self, model_type: str, model_name: str):
         if model_type in self._custom_register_type_to_cls:
-            _, _, unregister_fn = self._custom_register_type_to_cls[model_type]
+            _, _, unregister_fn, _ = self._custom_register_type_to_cls[model_type]
             unregister_fn(model_name)
+            await self._cache_tracker_ref.unregister_model_version(model_name)
 
             if not self.is_local_deployment():
                 workers = list(self._worker_address_to_worker.values())
@@ -457,6 +500,44 @@ def _gen_model_uid(self, model_name: str) -> str:
         )
         return f"{model_name}-{gen_random_string(8)}"
 
+    @log_async(logger=logger)
+    async def get_model_versions(self, model_type: str, model_name: str) -> List[Dict]:
+        logger.debug(
+            f"Get model versions of model_name: {model_name}, model_type: {model_type}"
+        )
+        return await self._cache_tracker_ref.get_model_versions(model_name)
+
+    @log_async(logger=logger)
+    async def launch_model_by_version(
+        self,
+        model_uid: Optional[str],
+        model_type: str,
+        model_version: str,
+        replica: int = 1,
+        n_gpu: Optional[Union[int, str]] = "auto",
+        wait_ready: bool = True,
+    ):
+        parse_results = parse_model_version(model_version, model_type)
+
+        if model_type == "image" and len(parse_results) == 2:
+            kwargs = {"controlnet": parse_results[1]}
+        else:
+            kwargs = {}
+
+        return await self.launch_builtin_model(
+            model_uid=model_uid,
+            model_name=parse_results[0],
+            model_size_in_billions=parse_results[1] if model_type == "LLM" else None,
+            model_format=parse_results[2] if model_type == "LLM" else None,
+            quantization=parse_results[3] if model_type == "LLM" else None,
+            model_type=model_type,
+            replica=replica,
+            n_gpu=n_gpu,
+            wait_ready=wait_ready,
+            model_version=model_version,
+            **kwargs,
+        )
+
     async def launch_speculative_llm(
         self,
         model_uid: Optional[str],
@@ -529,6 +610,7 @@ async def launch_builtin_model(
         n_gpu: Optional[Union[int, str]] = "auto",
         request_limits: Optional[int] = None,
         wait_ready: bool = True,
+        model_version: Optional[str] = None,
         **kwargs,
     ) -> str:
         if model_uid is None:
@@ -601,6 +683,7 @@ async def _launch_model():
         instance_info = InstanceInfo(
             model_name=model_name,
             model_uid=model_uid,
+            model_version=model_version,
             model_ability=[],
             replica=replica,
             status=LaunchStatus.CREATING.name,