accommodating new API.

Signed-off-by: Ye, Xinyu <xinyu.ye@intel.com>
opea-project · Jan 7, 2025 · fd0832f · fd0832f
1 parent c35de47
commit fd0832f
Showing 5 changed files with 50 additions and 55 deletions.
diff --git a/comps/finetuning/src/README.md b/comps/finetuning/src/README.md
@@ -244,7 +244,7 @@ curl http://${your_ip}:8015/v1/finetune/list_checkpoints -X POST -H "Content-Typ
 
 ### 3.4 Leverage fine-tuned model
 
-After fine-tuning job is done, fine-tuned model can be chosen from listed checkpoints, then the fine-tuned model can be used in other microservices. For example, fine-tuned reranking model can be used in [reranks](../../reranks/fastrag/README.md) microservice by assign its path to the environment variable `RERANK_MODEL_ID`, fine-tuned embedding model can be used in [embeddings](../../embeddings/README.md) microservice by assign its path to the environment variable `model`, LLMs after instruction tuning can be used in [llms](../../llms/text-generation/README.md) microservice by assign its path to the environment variable `your_hf_llm_model`.
+After fine-tuning job is done, fine-tuned model can be chosen from listed checkpoints, then the fine-tuned model can be used in other microservices. For example, fine-tuned reranking model can be used in [reranks](../../reranks/src/README.md) microservice by assign its path to the environment variable `RERANK_MODEL_ID`, fine-tuned embedding model can be used in [embeddings](../../embeddings/src/README.md) microservice by assign its path to the environment variable `model`, LLMs after instruction tuning can be used in [llms](../../llms/text-generation/README.md) microservice by assign its path to the environment variable `your_hf_llm_model`.
 
 ## 🚀4. Descriptions for Finetuning parameters
 

diff --git a/comps/finetuning/src/integrations/opea.py b/comps/finetuning/src/integrations/opea.py
@@ -14,7 +14,7 @@
 from pydantic_yaml import to_yaml_file
 from ray.job_submission import JobSubmissionClient
 
-from comps import CustomLogger, OpeaComponent
+from comps import CustomLogger, OpeaComponent, OpeaComponentRegistry
 from comps.cores.proto.api_protocol import (
     FileObject,
     FineTuningJob,
@@ -85,6 +85,7 @@ async def upload_file(purpose: str = Form(...), file: UploadFile = File(...)):
     return UploadFileRequest(purpose=purpose, file=file)
 
 
+@OpeaComponentRegistry.register("OPEA_FINETUNING")
 class OpeaFinetuning(OpeaComponent):
     """A specialized finetuning component derived from OpeaComponent for finetuning services."""
 

diff --git a/comps/finetuning/src/opea_finetuning_controller.py b/comps/finetuning/src/opea_finetuning_controller.py
diff --git a/comps/finetuning/src/opea_finetuning_loader.py b/comps/finetuning/src/opea_finetuning_loader.py
@@ -0,0 +1,32 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from comps import CustomLogger, OpeaComponentLoader
+
+logger = CustomLogger("opea_finetuning_loader")
+
+
+class OpeaFinetuningLoader(OpeaComponentLoader):
+    def __init__(self, component_name, **kwargs):
+        super().__init__(component_name=component_name, **kwargs)
+
+    def invoke(self, *args, **kwargs):
+        pass
+
+    def create_finetuning_jobs(self, *args, **kwargs):
+        return self.component.create_finetuning_jobs(*args, **kwargs)
+
+    def cancel_finetuning_job(self, *args, **kwargs):
+        return self.component.cancel_finetuning_job(*args, **kwargs)
+
+    def list_finetuning_checkpoints(self, *args, **kwargs):
+        return self.component.list_finetuning_checkpoints(*args, **kwargs)
+
+    def list_finetuning_jobs(self, *args, **kwargs):
+        return self.component.list_finetuning_jobs(*args, **kwargs)
+
+    def retrieve_finetuning_job(self, *args, **kwargs):
+        return self.component.retrieve_finetuning_job(*args, **kwargs)
+
+    async def upload_training_files(self, *args, **kwargs):
+        return await self.component.upload_training_files(*args, **kwargs)
diff --git a/comps/finetuning/src/opea_finetuning_microservice.py b/comps/finetuning/src/opea_finetuning_microservice.py
@@ -1,56 +1,50 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
+import os
+
 from fastapi import BackgroundTasks, Depends
 
 from comps import CustomLogger, opea_microservices, register_microservice
 from comps.cores.proto.api_protocol import FineTuningJobIDRequest, UploadFileRequest
 from comps.finetuning.src.integrations.finetune_config import FineTuningParams
 from comps.finetuning.src.integrations.opea import OpeaFinetuning, upload_file
-from comps.finetuning.src.opea_finetuning_controller import OpeaFinetuningController
+from comps.finetuning.src.opea_finetuning_loader import OpeaFinetuningLoader
 
 logger = CustomLogger("opea_finetuning_microservice")
 
-# Initialize Controller
-controller = OpeaFinetuningController()
-
-
-# Register components
-try:
-    # Instantiate Finetuning components
-    finetuning = OpeaFinetuning(name="OpeaFinetuning", description="OPEA Finetuning Service")
-    controller.register(finetuning)
-
-    # Discover and activate a healthy component
-    controller.discover_and_activate()
-except Exception as e:
-    logger.error(f"Failed to initialize components: {e}")
+finetuning_component_name = os.getenv("FINETUNING_COMPONENT_NAME", "OPEA_FINETUNING")
+# Initialize OpeaComponentLoader
+loader = OpeaFinetuningLoader(
+    finetuning_component_name,
+    description=f"OPEA FINETUNING Component: {finetuning_component_name}",
+)
 
 
 @register_microservice(name="opea_service@finetuning", endpoint="/v1/fine_tuning/jobs", host="0.0.0.0", port=8015)
 def create_finetuning_jobs(request: FineTuningParams, background_tasks: BackgroundTasks):
-    return controller.create_finetuning_jobs(request, background_tasks)
+    return loader.create_finetuning_jobs(request, background_tasks)
 
 
 @register_microservice(
     name="opea_service@finetuning", endpoint="/v1/fine_tuning/jobs", host="0.0.0.0", port=8015, methods=["GET"]
 )
 def list_finetuning_jobs():
-    return controller.list_finetuning_jobs()
+    return loader.list_finetuning_jobs()
 
 
 @register_microservice(
     name="opea_service@finetuning", endpoint="/v1/fine_tuning/jobs/retrieve", host="0.0.0.0", port=8015
 )
 def retrieve_finetuning_job(request: FineTuningJobIDRequest):
-    job = controller.retrieve_finetuning_job(request)
+    job = loader.retrieve_finetuning_job(request)
     return job
 
 
 @register_microservice(
     name="opea_service@finetuning", endpoint="/v1/fine_tuning/jobs/cancel", host="0.0.0.0", port=8015
 )
 def cancel_finetuning_job(request: FineTuningJobIDRequest):
-    job = controller.cancel_finetuning_job(request)
+    job = loader.cancel_finetuning_job(request)
     return job
 
 
@@ -61,15 +55,15 @@ def cancel_finetuning_job(request: FineTuningJobIDRequest):
     port=8015,
 )
 async def upload_training_files(request: UploadFileRequest = Depends(upload_file)):
-    uploadFileInfo = await controller.upload_training_files(request)
+    uploadFileInfo = await loader.upload_training_files(request)
     return uploadFileInfo
 
 
 @register_microservice(
     name="opea_service@finetuning", endpoint="/v1/finetune/list_checkpoints", host="0.0.0.0", port=8015
 )
 def list_checkpoints(request: FineTuningJobIDRequest):
-    checkpoints = controller.list_finetuning_checkpoints(request)
+    checkpoints = loader.list_finetuning_checkpoints(request)
     return checkpoints