Repository: instructlab/instructlab

Issue:
Add Confirmation and Next Steps for Model Download Command (ilab model download)
### Issue

Add Confirmation and Next Steps for Model Download Command (`ilab model download`)

## Overview
The `ilab model download` command currently completes without a clear success confirmation or next steps, leaving users uncertain if the download was successful. Additionally, users may not know how to verify the downloaded model or what commands to run to continue setup. This enhancement proposes adding a confirmation message after the download completes and potentially suggesting further actions, like running verification commands or initializing the model.

<img width="644" alt="image" src="https://github.com/user-attachments/assets/97683518-d478-416d-b50e-85d63aa1e5d3">

## Observations

### No Success Confirmation
- The output ends without a clear message indicating that the model was downloaded successfully. This lack of confirmation may leave users wondering if the process completed as expected.

### Lack of Next Steps or Verification Guidance
- Users might benefit from guidance on verifying the downloaded model or steps to initialize or use it. Without this, they may feel unsure of how to proceed or whether additional configuration is required.

## Suggestions for CLI Enhancement

### Add a Clear Success Confirmation
- Include a message at the end of the download process to confirm that the model has been downloaded successfully.
  - **Suggestion:** Display a message like "`✅ Model download completed successfully!`" to provide users with a sense of completion.

### Automatically Run `ilab model list`
- After the success message, automatically run `ilab model list` to display a list of all currently downloaded models, providing immediate visibility into available resources.

## Example Enhanced Output

```bash
ilab model download --hf-token <YOUR_HF_TOKEN>
Downloading model from Hugging Face: instructlab/merlinite-7b-lab-Q4_K_M.gguf...
[Download progress and file details here]
Model download completed successfully.
Moving file to /Users/jxhale/.cache/instructlab/models/merlinite-7b-lab-Q4_K_M.gguf...
✅ Model download completed successfully!

Available models (`ilab model list`):
+--------------------------------------------+---------------------+---------+
| Model Name 				                 | Last Modified 	   | Size    |
+--------------------------------------------+---------------------+---------+
| merlinite-7b-lab-Q4_K_M.gguf               | 2024-11-04 16:52:37 | 4.1 GB  |
| mistral-7b-instruct-v0.2.Q4_K_M.gguf       | 2024-11-04 16:54:39 | 4.1 GB  |
+--------------------------------------------+---------------------+---------+
```

## Benefits of This Enhancement
- Improves User Clarity and Confidence
-- With a clear confirmation and automatic listing of available models, users immediately know their download was successful and can see what models are ready for use.
- Enhances Workflow Efficiency
-- Automatically running ilab model list saves users a step, keeping them in the flow and providing immediate feedback without needing an additional command.

add a success message for different commands
**What is the current experience of ilab you've found issue with?**
<!-- A clear and concise description of what the experience you'd using ilab is -->

Based on [2651](https://github.com/instructlab/instructlab/issues/2651) and [2716](https://github.com/instructlab/instructlab/pull/2716) discussion, try to add success message for cmds.

**How do you think the described experience should be?**
<!-- A clear and concise description of how you think the experience you had should be -->

**What is the benefit of the change you are proposing?**
<!-- Justify your call to change the CLI here -->

**If applicable, how would backwards-compatability be handled?**
<!-- Feel free to remove this section if this does not apply -->

**Additional context**
<!-- Add any other context or screenshots about the design change here. -->



Discussion:
working on it
I think using ✅ looks nice but would need to be a thing we introduce in all commands to show success otherwise is just another different indicator
@cdoern 100% agree. Continuity across the CLI is ideal.
[2741](https://github.com/instructlab/instructlab/pull/2741/files)





Patch:
diff --git a/src/instructlab/cli/data/generate.py b/src/instructlab/cli/data/generate.py
index 4b27a962dd..d1f01344eb 100644
--- a/src/instructlab/cli/data/generate.py
+++ b/src/instructlab/cli/data/generate.py
@@ -280,6 +280,7 @@ def generate(
             system_prompt,
             legacy_pretraining_format,
         )
+        click.echo("ᕦ(òᴗóˇ)ᕤ Data generate completed successfully! ᕦ(òᴗóˇ)ᕤ")
     except Exception as exc:
         click.secho(f"failed to generate data with exception: {exc}", fg="red")
         raise click.exceptions.Exit(1)
diff --git a/src/instructlab/cli/model/train.py b/src/instructlab/cli/model/train.py
index 97b5087946..e764de3d77 100644
--- a/src/instructlab/cli/model/train.py
+++ b/src/instructlab/cli/model/train.py
@@ -498,6 +498,7 @@ def train(
         full_train.train(
             train_args=train_args, device=device, optimize_memory=optimize_memory
         )
+        click.echo("ᕦ(òᴗóˇ)ᕤ Full model training completed successfully! ᕦ(òᴗóˇ)ᕤ")
     elif pipeline == "simple":
         # First Party
         from instructlab.model import simple_train
@@ -518,6 +519,9 @@ def train(
                 device=device,
                 four_bit_quant=four_bit_quant,
             )
+            click.echo(
+                "ᕦ(òᴗóˇ)ᕤ Simple Model training completed successfully! ᕦ(òᴗóˇ)ᕤ"
+            )
         except Exception as exc:
             click.secho(f"{exc}", fg="red")
             raise click.exceptions.Exit(1)
diff --git a/src/instructlab/model/accelerated_train.py b/src/instructlab/model/accelerated_train.py
index 3775ce013d..cbc7bfe38a 100644
--- a/src/instructlab/model/accelerated_train.py
+++ b/src/instructlab/model/accelerated_train.py
@@ -483,7 +483,7 @@ def _run_phased_training(
         )
 
     click.secho(
-        f"Training finished! Best final checkpoint: {output_checkpoint.checkpoint} with score: {output_checkpoint.score}\nJournal: {str(journal.journalfile)}",
+        f"ᕦ(òᴗóˇ)ᕤ Accelerated model training completed successfully! ᕦ(òᴗóˇ)ᕤ\nBest final checkpoint: {output_checkpoint.checkpoint} with score: {output_checkpoint.score}\nJournal: {str(journal.journalfile)}",
         fg="green",
     )
 
diff --git a/src/instructlab/model/convert.py b/src/instructlab/model/convert.py
index d5c57b0ef6..bbfe14faaf 100644
--- a/src/instructlab/model/convert.py
+++ b/src/instructlab/model/convert.py
@@ -124,3 +124,4 @@ def convert(
 
     logger.info(f"deleting {source_model_dir}...")
     shutil.rmtree(source_model_dir)
+    click.echo("ᕦ(òᴗóˇ)ᕤ Model convert completed successfully! ᕦ(òᴗóˇ)ᕤ")
diff --git a/src/instructlab/model/evaluate.py b/src/instructlab/model/evaluate.py
index edff2bf3af..2d0697ca6a 100644
--- a/src/instructlab/model/evaluate.py
+++ b/src/instructlab/model/evaluate.py
@@ -639,6 +639,7 @@ def evaluate(
                 turn2_score = round(turn2_score, 2)
             print(turn2_score)
             display_error_rate(error_rate)
+            click.echo("\nᕦ(òᴗóˇ)ᕤ Model evaluate with MTBench completed! ᕦ(òᴗóˇ)ᕤ")
 
         elif benchmark == Benchmark.MT_BENCH_BRANCH:
             # Third Party
@@ -777,6 +778,9 @@ def evaluate(
                 new_qnas,
             )
             display_error_rate((error_rate + base_error_rate) / 2)
+            click.echo(
+                "\nᕦ(òᴗóˇ)ᕤ Model evaluate with MTBenchBranch completed! ᕦ(òᴗóˇ)ᕤ"
+            )
 
         elif benchmark == Benchmark.MMLU:
             # Third Party
@@ -822,6 +826,7 @@ def evaluate(
             for task, score in individual_scores.items():
                 s = round(score["score"], 2)
                 print(f"{task} - {s}")
+            click.echo("\nᕦ(òᴗóˇ)ᕤ Model evaluate with MMLU completed! ᕦ(òᴗóˇ)ᕤ")
 
         elif benchmark == Benchmark.MMLU_BRANCH:
             # Third Party
@@ -901,6 +906,7 @@ def evaluate(
             display_branch_eval_summary(
                 Benchmark.MMLU_BRANCH, improvements, regressions, no_changes
             )
+            click.echo("\nᕦ(òᴗóˇ)ᕤ Model evaluate with MMLUBranch completed! ᕦ(òᴗóˇ)ᕤ")
     except EvalError as ee:
         print(ee.message)
         logger.debug("Traceback", exc_info=True)


Test patch:
diff --git a/src/instructlab/model/test.py b/src/instructlab/model/test.py
index 62684f8b0f..e444153758 100644
--- a/src/instructlab/model/test.py
+++ b/src/instructlab/model/test.py
@@ -133,6 +133,7 @@ def test(
                     max_tokens=100,
                     prompt=prompt,
                 )
+        click.echo("ᕦ(òᴗóˇ)ᕤ MacOS model test completed successfully! ᕦ(òᴗóˇ)ᕤ")
     else:
         logger.debug("")
         # pylint: disable=import-outside-toplevel
@@ -164,6 +165,7 @@ def test(
                     print()
                     print(f"{mod}: {answer}")
                 print()
+            click.echo("ᕦ(òᴗóˇ)ᕤ Linux model test completed successfully! ᕦ(òᴗóˇ)ᕤ")
         except Exception as exc:
             click.secho(
                 f"Testing models failed with the following error: {exc}", fg="red"
diff --git a/tests/test_lab_evaluate.py b/tests/test_lab_evaluate.py
index 24aee9440f..34d76f2df0 100644
--- a/tests/test_lab_evaluate.py
+++ b/tests/test_lab_evaluate.py
@@ -129,6 +129,7 @@ def run_mt_bench(cli_runner, error_rate):
             {round(error_rate, 2)}
             """
         )
+    expected += "\nᕦ(òᴗóˇ)ᕤ Model evaluate with MTBench completed! ᕦ(òᴗóˇ)ᕤ\n"
     assert result.output == expected
 
 
@@ -195,6 +196,7 @@ def run_mt_bench_branch(cli_runner, error_rate):
             {round(error_rate, 2)}
             """
         )
+    expected += "\nᕦ(òᴗóˇ)ᕤ Model evaluate with MTBenchBranch completed! ᕦ(òᴗóˇ)ᕤ\n"
     assert result.output == expected
 
 
@@ -304,6 +306,7 @@ def test_evaluate_mmlu(
         task2 - 0.9
         """
     )
+    expected += "\nᕦ(òᴗóˇ)ᕤ Model evaluate with MMLU completed! ᕦ(òᴗóˇ)ᕤ\n"
     assert result.output == expected
 
 
@@ -364,6 +367,7 @@ def test_evaluate_mmlu_branch(
         1. task5 (0.5)
         """
     )
+    expected += "\nᕦ(òᴗóˇ)ᕤ Model evaluate with MMLUBranch completed! ᕦ(òᴗóˇ)ᕤ\n"
     assert result.output == expected