[torchtune integration] post training + eval (#670)

## What does this PR do?

- Add related Apis in experimental-post-training template to enable eval
on the finetuned checkpoint in the template
- A small bug fix on meta reference eval
- A small error handle improvement on post training 


## Test Plan
From client side issued an E2E post training request
https://github.com/meta-llama/llama-stack-client-python/pull/70 and get
eval results successfully

<img width="1315" alt="Screenshot 2024-12-20 at 12 06 59 PM"
src="https://github.com/user-attachments/assets/a09bd524-59ae-490c-908f-2e36ccf27c0a"
/>

llama_stack/providers/inline/eval/meta_reference/eval.py

@@ -15,7 +15,7 @@ from llama_stack.apis.agents import Agents
 from llama_stack.apis.datasetio import DatasetIO
 from llama_stack.apis.datasets import Datasets
 from llama_stack.apis.eval_tasks import EvalTask
-from llama_stack.apis.inference import Inference
+from llama_stack.apis.inference import Inference, UserMessage
 from llama_stack.apis.scoring import Scoring
 from llama_stack.providers.datatypes import EvalTasksProtocolPrivate
 from llama_stack.providers.utils.kvstore import kvstore_impl

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

@@ -110,6 +110,10 @@ class LoraFinetuningSingleDevice:
             self.checkpoint_dir = config.checkpoint_dir
         else:
             model = resolve_model(self.model_id)
+            if model is None:
+                raise ValueError(
+                    f"{self.model_id} not found. Your model id should be in the llama models SKU list"
+                )
             self.checkpoint_dir = model_checkpoint_dir(model)
 
         self._output_dir = str(DEFAULT_CHECKPOINT_DIR)

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

@@ -4,10 +4,22 @@ distribution_spec:
   description: Experimental template for post training
   docker_image: null
   providers:
+    inference:
+    - inline::meta-reference
+    eval:
+    - inline::meta-reference
+    scoring:
+    - inline::basic
     post_training:
     - inline::torchtune
     datasetio:
     - remote::huggingface
     telemetry:
     - inline::meta-reference
+    agents:
+    - inline::meta-reference
+    safety:
+    - inline::llama-guard
+    memory:
+    - inline::faiss
 image_type: conda

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

@@ -3,9 +3,14 @@ image_name: experimental-post-training
 docker_image: null
 conda_env: experimental-post-training
 apis:
-- inference
-- telemetry
+- agents
 - datasetio
+- eval
+- inference
+- memory
+- safety
+- scoring
+- telemetry
 - post_training
 providers:
   inference:
@@ -14,6 +19,14 @@ providers:
     config:
       max_seq_len: 4096
       checkpoint_dir: null
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config: {}
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+    config: {}
   datasetio:
   - provider_id: huggingface-0
     provider_type: remote::huggingface
@@ -26,6 +39,26 @@ providers:
   - provider_id: torchtune-post-training
     provider_type: inline::torchtune
     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
+  safety:
+  - provider_id: llama-guard
+    provider_type: inline::llama-guard
+    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
 
 metadata_store:
   namespace: null