remove unnecessary provider apis from expermental post training template

llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py

@@ -163,7 +163,7 @@ class LoraFinetuningSingleDevice:
         log.info(f"Model is initialized with precision {self._dtype}.")
 
         self._tokenizer = await self._setup_tokenizer()
-        log.info("Tokenizer is initialized from file.")
+        log.info("Tokenizer is initialized.")
 
         self._optimizer = await self._setup_optimizer(
             optimizer_config=self.training_config.optimizer_config

llama_stack/templates/experimental-post-training/build.yaml

@@ -8,16 +8,6 @@ distribution_spec:
     - inline::torchtune
     datasetio:
     - remote::huggingface
-    inference:
-    - inline::meta-reference
-    memory:
-    - inline::faiss
-    - remote::chromadb
-    - remote::pgvector
-    safety:
-    - inline::llama-guard
-    agents:
-    - inline::meta-reference
     telemetry:
     - inline::meta-reference
 image_type: conda

llama_stack/templates/experimental-post-training/run.yaml

@@ -3,45 +3,14 @@ image_name: experimental-post-training
 docker_image: null
 conda_env: experimental-post-training
 apis:
-- agents
-- inference
-- memory
-- safety
 - telemetry
 - datasetio
 - post_training
 providers:
-  inference:
-  - provider_id: meta-reference-inference
-    provider_type: inline::meta-reference
-    config:
-      model: ${env.INFERENCE_MODEL}
-      max_seq_len: 4096
-      checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:null}
   datasetio:
   - provider_id: huggingface-0
     provider_type: remote::huggingface
     config: {}
-  memory:
-  - provider_id: faiss
-    provider_type: inline::faiss
-    config:
-      kvstore:
-        type: sqlite
-        namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/faiss_store.db
-  safety:
-  - provider_id: llama-guard
-    provider_type: inline::llama-guard
-    config: {}
-  agents:
-  - provider_id: meta-reference
-    provider_type: inline::meta-reference
-    config:
-      persistence_store:
-        type: sqlite
-        namespace: null
-        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/agents_store.db
   telemetry:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -57,7 +26,7 @@ metadata_store:
   db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/registry.db
 models:
 - metadata: {}
-  model_id: ${env.INFERENCE_MODEL}
+  model_id: ${env.POST_TRAINING_MODEL}
   provider_id: meta-reference-inference
   provider_model_id: null
 shields: []