v0.10.2: Fix remaining Windows/CPU issues from re-test

- ASCII progress bar in display.py (replace Unicode blocks with #/-)
- Catch UnicodeEncodeError from plotext in data stats (Windows fallback)
- Auto-disable 4bit/8bit quantization on CPU (bitsandbytes doesn't support it)
- Friendly error messages for CPU tensor/dtype/bf16/torchvision issues
- Fix diff.py: torch_dtype= -> dtype= (deprecation warning)
- Add torchvision version compatibility check to soup doctor

7 new tests (631 total), ruff clean.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

CLAUDE.md

@@ -182,4 +182,4 @@ Test suite lives in `tests/`:
 | `test_ui.py` | Web UI command, FastAPI endpoints, static files, config validation |
 | `test_vllm_serve.py` | vLLM backend detection, engine creation, serve --backend flag, FastAPI app |
 | `test_ppo.py` | PPO config, reward model config, data prep, RLHF template, routing, sweep |
-| `test_bugfixes.py` | v0.10.1 bugfixes: Windows Unicode, PPO params, compute dtype, diff dtype, wandb pin |
+| `test_bugfixes.py` | v0.10.1-v0.10.2 bugfixes: Unicode, PPO params, compute dtype, diff, CPU compat, doctor |

README.md

@@ -603,7 +603,7 @@ soup version
 
 # Full system info (useful for bug reports)
 soup version --full
-# -> soup v0.10.1 | Python 3.11.5 | CUDA 12.1 | extras: serve, data
+# -> soup v0.10.2 | Python 3.11.5 | CUDA 12.1 | extras: serve, data
 ```
 
 ## Web UI

plan.md

@@ -2,7 +2,7 @@
 
 **Repo:** https://github.com/MakazhanAlpamys/Soup
 **PyPI:** https://pypi.org/project/soup-cli/ (`pip install soup-cli`)
-**Version:** v0.10.1 | 624 tests | CI green
+**Version:** v0.10.2 | 631 tests | CI green
 
 ### How to publish
 
@@ -16,7 +16,7 @@ git push --tags
 
 ---
 
-## Completed (v0.1.0 – v0.10.1)
+## Completed (v0.0.1 – v0.10.2)
 
 - **CLI:** init, train, chat, push, merge, export, eval, serve, sweep, diff, doctor, quickstart, ui, version
 - **Data:** inspect, validate, convert, merge, dedup, stats, generate
@@ -30,100 +30,74 @@ git push --tags
 - **Community:** CONTRIBUTING.md, CODE_OF_CONDUCT.md, SECURITY.md, examples/, FUNDING.yml
 - **Tests:** 624 tests, 41 files, ruff lint, CI on Python 3.9/3.11/3.12
 - **v0.10.1 bugfixes:** Windows UnicodeEncodeError, PPO trl compat, compute dtype for CPU, diff torch_dtype, wandb version pin
+- **v0.10.2 bugfixes:** ASCII progress bar, plotext fallback, auto-disable 4bit on CPU, friendly CPU error messages, torchvision compat check in doctor
 
 ---
 
 ## Roadmap
 
-### P0 — Critical (v1.0–v1.1)
+### v0.11.0 — Alignment methods
 
-#### Community & Marketing
-- [ ] Discord server
-- [ ] First Reddit post (r/LocalLLaMA, r/MachineLearning)
-- [ ] HuggingFace models showcase ("trained-with-soup" tag)
-- [ ] 3-5 YouTube tutorials / blog posts with benchmarks (Soup vs LLaMA-Factory vs Axolotl)
-- [ ] Supported models page in README (Llama 4, Gemma 3, Qwen 2.5/3, Phi-4, DeepSeek R1/V3, Mistral, Mixtral)
+- [ ] KTO (`task: kto`) — unpaired preference data, wraps trl.KTOTrainer
+- [ ] ORPO (`task: orpo`) — no reference model needed, wraps trl.ORPOTrainer
+- [ ] SimPO (`task: simpo`) — simple preference optimization
+- [ ] IPO (`task: ipo`) — identity preference optimization
+- [ ] Templates: `soup init --template kto`, `--template orpo`
 
-#### Advanced PEFT methods
-- [ ] DoRA (`peft_type: dora`) — improved LoRA with magnitude decomposition
+### v0.12.0 — Advanced PEFT
+
+- [ ] DoRA (`use_dora: true`) — magnitude decomposition, already in PEFT
+- [ ] LoRA+ (`loraplus_lr_ratio`) — different lr for A and B matrices
 - [ ] GaLore — memory-efficient full-parameter training on consumer GPUs
-- [ ] LoRA+ — different learning rates for A and B matrices
 
-#### More alignment methods
-- [ ] KTO (Kahneman-Tversky Optimization) — `task: kto`, doesn't need paired data
-- [ ] ORPO (Odds Ratio Preference Optimization) — `task: orpo`, no reference model needed
-- [ ] SimPO — `task: simpo`, simple preference optimization
-- [ ] IPO (Identity Preference Optimization) — `task: ipo`
+### v0.13.0 — Batch inference + TensorBoard
+
+- [ ] `soup infer --input prompts.jsonl --output results.jsonl` — batch inference (reuse diff.py code)
+- [ ] `--tensorboard` flag in train — `report_to="tensorboard"`, HF Trainer handles it
+- [ ] Supported models page in README (Llama 4, Gemma 3, Qwen 2.5/3, Phi-4, DeepSeek R1/V3)
+
+### v0.14.0 — Pre-training + MoE
 
-#### Pre-training / Continued pre-training
 - [ ] `task: pretrain` — continued pre-training on raw text
-- [ ] Support for plain text / tokenized datasets
+- [ ] Plain text / tokenized datasets support
+- [ ] MoE model support (Qwen3 30B-A3B, Mixtral, DeepSeek V3)
+- [ ] ScatterMoE LoRA
 
-#### Cloud GPU providers
-- [ ] `soup cloud run --provider runpod --gpu a100 --config soup.yaml`
-- [ ] RunPod, Vast.ai, Lambda Labs, Modal integration
-- [ ] Auto-setup: upload data → rent GPU → train → return adapter → teardown
-- [ ] Cost estimator and budget auto-stop
+### v0.15.0 — Performance + Long-context
 
----
-
-### P1 — Important (v1.2–v1.3)
-
-#### MoE support
-- [ ] Explicit MoE model support (Qwen3 30B-A3B, Mixtral, DeepSeek V3)
-- [ ] ScatterMoE LoRA for efficient MoE fine-tuning
-- [ ] Documentation and examples for MoE training
-
-#### Long-context training
-- [ ] Sequence parallelism via Ring FlashAttention
-- [ ] 128k+ context fine-tuning across multiple GPUs
-- [ ] Neat packing (contamination-free) for long sequences
-
-#### Embedding models
-- [ ] `task: embedding` — fine-tune sentence transformers, BGE, E5
-- [ ] `soup init --template embedding`
-- [ ] Contrastive loss, triplet loss support
-
-#### Advanced distributed training
-- [ ] FSDP2 support alongside DeepSpeed
-- [ ] Multi-node training via torchrun / Ray
-- [ ] Tensor Parallelism + Context Parallelism combined
-
-#### Performance optimizations
 - [ ] Liger Kernel integration (fused operations)
 - [ ] FlashAttention-3/4 auto-detection
-- [ ] SageAttention support
+- [ ] FSDP2 support alongside DeepSpeed
+- [ ] Sequence parallelism via Ring FlashAttention
+- [ ] 128k+ context fine-tuning
 
----
+### v0.16.0 — Embedding models + Export
 
-### P2 — Nice to have (v1.4+)
-
-#### Export formats
+- [ ] `task: embedding` — sentence transformers, BGE, E5
+- [ ] Contrastive loss, triplet loss
 - [ ] ONNX export (`soup export --format onnx`)
 - [ ] TensorRT-LLM export
+- [ ] Speculative decoding (`soup serve --speculative-decoding`)
+
+### v0.17.0 — Data + Audio
+
+- [ ] Local model as data generation provider
+- [ ] Quality filters (perplexity, coherence scoring)
+- [ ] `modality: audio` — Qwen2-Audio, Whisper fine-tuning
 - [ ] SGLang backend for serving
 
-#### Integrations
-- [ ] MLflow tracking (enterprise alternative to W&B)
-- [ ] TensorBoard integration
-- [ ] `uv` package manager support
+### v0.18.0 — Cloud GPU (monetization)
 
-#### Serving improvements
-- [ ] Speculative decoding (`soup serve --speculative-decoding`)
-- [ ] Batch inference mode (`soup infer --input prompts.jsonl --output results.jsonl`)
+Last step — all features are built, product is ready to sell.
 
-#### Data improvements
-- [ ] Multi-agent synthetic data generation (GraphGen-style)
-- [ ] Quality filters for generated data (perplexity, coherence scoring)
-- [ ] Local model as data generation provider (not just OpenAI API)
-
-#### Audio modality
-- [ ] `modality: audio` — Qwen2-Audio, Whisper fine-tuning
-- [ ] Audio dataset formats and inspection
-
-#### Smart suggestions
-- [ ] Auto-detect hardware and recommend optimal config
-- [ ] "You have 2×H100 — recommend FSDP2 + Unsloth" style hints
+- [ ] `soup login` — user registration, Stripe card linking
+- [ ] `soup cloud run --config soup.yaml --gpu a100` — cloud training
+- [ ] Backend API (FastAPI on VPS) — pod management, billing
+- [ ] RunPod API integration (our account, 20-30% markup)
+- [ ] `soup cloud status` — usage, balance, history
+- [ ] Landing page soup.cloud
+- [ ] Cost estimator and budget auto-stop
+- [ ] Vast.ai, Lambda Labs, Modal — additional providers
 
 ---
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "soup-cli"
-version = "0.10.1"
+version = "0.10.2"
 description = "Fine-tune LLMs in one command. No SSH, no config hell."
 readme = "README.md"
 license = "MIT"

soup_cli/__init__.py

@@ -1,3 +1,3 @@
 """Soup CLI — Fine-tune LLMs in one command."""
 
-__version__ = "0.10.1"
+__version__ = "0.10.2"

soup_cli/commands/data.py

@@ -361,6 +361,11 @@ def stats(
             plt.ylabel("Count")
             plt.theme("dark")
             plt.show()
+    except UnicodeEncodeError:
+        console.print(
+            "\n[dim]Histogram skipped (Windows encoding).[/] "
+            "Set PYTHONIOENCODING=utf-8 to enable."
+        )
     except ImportError:
         console.print(
             "\n[dim]Install plotext for histograms:[/] [bold]pip install plotext[/]"

soup_cli/commands/diff.py

@@ -231,7 +231,7 @@ def _load_model(model_path: str, base_model: Optional[str], device: str):
             base_model,
             trust_remote_code=True,
             device_map="auto",
-            torch_dtype=torch.float16,
+            dtype=torch.float16,
         )
         model_obj = PeftModel.from_pretrained(base, model_path)
     else:
@@ -239,7 +239,7 @@ def _load_model(model_path: str, base_model: Optional[str], device: str):
             model_path,
             trust_remote_code=True,
             device_map="auto",
-            torch_dtype=torch.float16,
+            dtype=torch.float16,
         )
 
     model_obj.eval()

soup_cli/commands/doctor.py

@@ -100,6 +100,9 @@ def doctor():
 
     console.print(table)
 
+    # Check torchvision + torch compatibility
+    _check_torchvision_compat(issues)
+
     # Summary
     if issues:
         console.print(f"\n[yellow]Found {len(issues)} issue(s):[/]")
@@ -162,6 +165,34 @@ def _check_gpu():
         )
 
 
+def _check_torchvision_compat(issues: list):
+    """Check that torchvision version is compatible with torch."""
+    try:
+        import torch
+        import torchvision
+
+        torch_ver = torch.__version__.split("+")[0]
+        tv_ver = torchvision.__version__.split("+")[0]
+        torch_minor = ".".join(torch_ver.split(".")[:2])
+        tv_minor = ".".join(tv_ver.split(".")[:2])
+
+        # Known compatible pairs (torch minor -> torchvision minor)
+        compat = {
+            "2.6": "0.21", "2.5": "0.20", "2.4": "0.19",
+            "2.3": "0.18", "2.2": "0.17", "2.1": "0.16", "2.0": "0.15",
+        }
+        expected_tv = compat.get(torch_minor)
+        if expected_tv and not tv_minor.startswith(expected_tv):
+            msg = (
+                f"torchvision {tv_ver} may be incompatible with torch {torch_ver}. "
+                f"Expected torchvision {expected_tv}.x"
+            )
+            console.print(f"  [yellow]Warning:[/] {msg}")
+            issues.append(msg)
+    except ImportError:
+        pass
+
+
 def _version_ok(installed: str, minimum: str) -> bool:
     """Check if installed version meets minimum requirement."""
     try:

soup_cli/commands/train.py

@@ -107,12 +107,13 @@ def train(
     device, device_name = detect_device()
     gpu_info = get_gpu_info()
 
-    # Warn about quantization on CPU
+    # Auto-disable quantization on CPU (bitsandbytes doesn't support CPU)
     if device == "cpu" and cfg.training.quantization in ("4bit", "8bit"):
         console.print(
-            f"[yellow]Warning: {cfg.training.quantization} quantization on CPU "
-            "may cause errors. Consider using quantization: none for CPU.[/]"
+            f"[yellow]Warning: {cfg.training.quantization} quantization is not "
+            "supported on CPU. Switching to quantization: none.[/]"
         )
+        cfg.training.quantization = "none"
 
     backend_label = cfg.backend
     if cfg.backend == "unsloth":

soup_cli/monitoring/display.py

@@ -59,7 +59,7 @@ class TrainingDisplay:
             progress_pct = 0
         bar_width = 30
         filled = int(bar_width * progress_pct / 100)
-        bar = "\u2588" * filled + "\u2591" * (bar_width - filled)
+        bar = "#" * filled + "-" * (bar_width - filled)
 
         epochs = self.config.training.epochs
         epoch_str = f"Epoch {self.current_epoch:.1f}/{epochs}"

soup_cli/utils/errors.py

@@ -72,6 +72,27 @@ ERROR_MAP = [
         "BitsAndBytes is not installed (needed for quantization).",
         "Run: pip install bitsandbytes>=0.41.0",
     ),
+    # CPU / quantization issues
+    (
+        "expanded size of the tensor",
+        "Model generation failed (likely 4bit quantization on CPU).",
+        "Use a GPU, or set quantization: none in your config for CPU training.",
+    ),
+    (
+        "expected m1 and m2 to have the same dtype",
+        "Dtype mismatch (likely 4bit quantization on CPU).",
+        "Use a GPU, or set quantization: none in your config for CPU training.",
+    ),
+    (
+        "Your setup doesn't support bf16",
+        "This training task requires GPU with bf16 support.",
+        "Use a CUDA GPU, or try a simpler task (SFT/DPO work on CPU).",
+    ),
+    (
+        "nms does not exist",
+        "torchvision version is incompatible with torch.",
+        "Run: pip install torchvision --force-reinstall (or check soup doctor).",
+    ),
     # Connection errors
     (
         "ConnectionError",

tests/test_bugfixes.py

@@ -1,4 +1,4 @@
-"""Tests for v0.10.1 bug fixes - Windows Unicode, PPO params, dtype, diff."""
+"""Tests for v0.10.1/v0.10.2 bug fixes - Unicode, PPO, dtype, CPU compat."""
 
 from pathlib import Path
 from unittest.mock import patch
@@ -135,15 +135,15 @@ class TestComputeDtype:
 class TestDiffModelLoading:
     """Test diff command uses correct parameter names."""
 
-    def test_load_model_uses_torch_dtype(self):
-        """_load_model should pass torch_dtype, not dtype."""
+    def test_load_model_uses_dtype(self):
+        """_load_model should pass dtype= (not the old torch_dtype=)."""
         import inspect
 
         from soup_cli.commands.diff import _load_model
 
         source = inspect.getsource(_load_model)
-        assert "torch_dtype=" in source
-        assert "dtype=" not in source or "torch_dtype=" in source
+        assert "dtype=torch.float16" in source
+        assert "torch_dtype=" not in source
 
 
 # --- BUG-006: wandb version pin ---
@@ -165,11 +165,98 @@ class TestWandbVersionPin:
 class TestCPUQuantWarning:
     """Test that CPU + quantization produces a warning."""
 
-    def test_train_source_has_cpu_quant_warning(self):
-        """train.py should warn about quantization on CPU."""
+    def test_train_auto_disables_quant_on_cpu(self):
+        """train.py should auto-disable quantization on CPU."""
         import inspect
 
         from soup_cli.commands import train
 
         source = inspect.getsource(train)
-        assert "quantization on CPU" in source
+        assert "quantization is not" in source
+        assert 'cfg.training.quantization = "none"' in source
+
+
+# --- v0.10.2: Display progress bar uses ASCII ---
+
+
+class TestDisplayASCII:
+    """Test that training display uses ASCII-safe progress bars."""
+
+    def test_progress_bar_uses_ascii_chars(self):
+        """Progress bar should use # and - instead of Unicode blocks."""
+        import inspect
+
+        from soup_cli.monitoring.display import TrainingDisplay
+
+        source = inspect.getsource(TrainingDisplay)
+        assert '"#"' in source
+        assert '"-"' in source
+        assert "\\u2588" not in source
+        assert "\\u2591" not in source
+
+
+# --- v0.10.2: Plotext UnicodeEncodeError handling ---
+
+
+class TestPlotextFallback:
+    """Test that plotext errors are caught gracefully."""
+
+    def test_stats_catches_unicode_error(self):
+        """data stats should catch UnicodeEncodeError from plotext."""
+        import inspect
+
+        from soup_cli.commands import data
+
+        source = inspect.getsource(data)
+        assert "UnicodeEncodeError" in source
+
+
+# --- v0.10.2: Error messages for CPU issues ---
+
+
+class TestCPUErrorMessages:
+    """Test friendly error messages for CPU-specific failures."""
+
+    def test_tensor_size_error_mapped(self):
+        """Tensor expansion error should have a friendly message."""
+        from soup_cli.utils.errors import ERROR_MAP
+
+        patterns = [pattern for pattern, _, _ in ERROR_MAP]
+        assert any("expanded size" in p for p in patterns)
+
+    def test_dtype_mismatch_error_mapped(self):
+        """Dtype mismatch error should have a friendly message."""
+        from soup_cli.utils.errors import ERROR_MAP
+
+        patterns = [pattern for pattern, _, _ in ERROR_MAP]
+        assert any("same dtype" in p for p in patterns)
+
+    def test_bf16_error_mapped(self):
+        """bf16 GPU error should have a friendly message."""
+        from soup_cli.utils.errors import ERROR_MAP
+
+        patterns = [pattern for pattern, _, _ in ERROR_MAP]
+        assert any("bf16" in p for p in patterns)
+
+    def test_torchvision_error_mapped(self):
+        """torchvision nms error should have a friendly message."""
+        from soup_cli.utils.errors import ERROR_MAP
+
+        patterns = [pattern for pattern, _, _ in ERROR_MAP]
+        assert any("nms" in p for p in patterns)
+
+
+# --- v0.10.2: Doctor torchvision check ---
+
+
+class TestDoctorTorchvisionCheck:
+    """Test that soup doctor checks torchvision compatibility."""
+
+    def test_doctor_has_torchvision_check(self):
+        """doctor.py should have torchvision compatibility check."""
+        import inspect
+
+        from soup_cli.commands import doctor
+
+        source = inspect.getsource(doctor)
+        assert "_check_torchvision_compat" in source