Commit Graph

24 Commits

Author SHA1 Message Date
Alpamys 9451b980d4 fix: rename shadowed builtins and add type annotations in infer.py
- Rename `input` param to `input_file` (avoid shadowing builtin)
- Rename `output` param to `output_file` for consistency
- Rename loop variable `line = line.strip()` to `raw_line`/`line`
- Add return type annotation to `_load_model() -> tuple`
2026-03-25 18:59:33 +05:00
Alpamys 6806cdd944 fix: address code review findings for v0.13.0
- Fix TensorBoard import check: use `import tensorboard` directly
  (not torch.utils.tensorboard shim) for accurate availability check
- Stream JSONL output during inference instead of buffering in memory
  (crash-safe, handles large prompt files)
- Return accurate token count from _generate via tensor shape instead
  of re-encoding decoded text
- Replace shallow tests with real trainer integration tests that
  verify report_to='tensorboard' is accepted by all trainer wrappers
2026-03-25 18:48:43 +05:00
Alpamys db19f64649 fix: cap max_tokens at 16384 and add trust_remote_code warning in infer
- Add min=1, max=16384 bounds to --max-tokens in soup infer (matches
  serve.py cap, prevents resource exhaustion)
- Add visible warning before loading model with trust_remote_code=True
2026-03-25 18:45:34 +05:00
Alpamys edaa208d73 v0.13.0: batch inference + TensorBoard logging + supported models
- Add `soup infer` command for batch inference on JSONL prompts
  (--model, --input, --output, --max-tokens, --temperature, --device)
- Add `--tensorboard` flag to `soup train` (report_to="tensorboard")
- Validate --wandb and --tensorboard mutual exclusivity
- Add supported models table to README (Llama 4, Gemma 3, Qwen 2.5/3,
  Phi-4, DeepSeek R1/V3, Mistral, CodeLlama)
- 906 tests (29 new), 44 test files, 56.32% coverage
2026-03-25 18:43:43 +05:00
Alpamys 0be8a03a8a v0.12.0: ORPO/SimPO/IPO trainers + DoRA/LoRA+/GaLore
v0.11.0 — Alignment methods:
- ORPO (task: orpo) — wraps trl.ORPOTrainer, no reference model needed
- SimPO (task: simpo) — wraps trl.CPOTrainer with loss_type='simpo'
- IPO (task: ipo) — wraps trl.DPOTrainer with loss_type='ipo'
- Templates: soup init --template orpo/simpo/ipo
- Init wizard, train routing, sweep shortcuts for all three

v0.12.0 — Advanced PEFT:
- DoRA (use_dora: true) — weight-decomposed LoRA in all 9 trainers
- LoRA+ (loraplus_lr_ratio) — different lr for A and B matrices
- GaLore (use_galore: true) — memory-efficient full-param training
- GaLore validation: incompatible with quantization and unsloth

Security:
- experiment_name path traversal validation (no / \ : null bytes)
- GaLore optim_args type enforcement before string interpolation

Tests: 877 passed (was 746), 42 test files, 56.98% coverage
2026-03-25 18:12:36 +05:00
Alpamys 7bee22052b v0.10.10: Security hardening — Web UI auth, CORS, SSRF, path traversal protection
Security fixes across all HTTP surfaces:
- Web UI: Bearer token auth on mutating endpoints, CORS restricted to served origin,
  path traversal protection on /api/data/inspect, config validated before training,
  removed user-controlled config_path from API
- Serve/vLLM: max_tokens capped at 16384, generic error messages (no stack traces)
- Generate: SSRF protection (--api-base blocks non-HTTPS for remote URLs),
  --api-key deprecated in favor of OPENAI_API_KEY env var
- Export: llama.cpp pinned to tag b5270 (supply-chain safety)
- Push: --token deprecated in favor of HF_TOKEN env var
- Rewards: warning before executing custom .py reward files
- Tests: all 40 UI tests updated with auth headers, 666 tests pass

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 12:14:10 +05:00
Alpamys 4fca7a9664 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>
2026-03-24 13:20:27 +05:00
Alpamys 428c0f09a4 v0.10.1: Fix 6 bugs from manual testing report
- BUG-001: Replace Unicode arrows/dashes with ASCII in all console output
  to fix UnicodeEncodeError on Windows cp1252 (~10 commands affected)
- BUG-002: PPO trainer uses inspect.signature to detect trl parameter names
  (ppo_epochs vs num_ppo_epochs) for trl 0.28.0 compatibility
- BUG-003: Add get_compute_dtype() - uses float32 on CPU, bfloat16/float16
  on CUDA. Fixes dtype mismatch in reward model and all trainers
- BUG-004: Add warning when using quantization on CPU
- BUG-005: Fix dtype -> torch_dtype in diff.py model loading
- BUG-006: Pin wandb<0.18.0 to avoid trl import conflict, add runtime guard

13 new tests (624 total), ruff clean.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-24 12:31:37 +05:00
Alpamys 83da7f071d Add PPO / Full RLHF pipeline (Phase 10) — v0.9.0
Three-stage RLHF training: SFT → Reward Model → PPO.

- task: ppo — PPO trainer with manual training loop (generate → score → optimize)
- task: reward_model — RewardTrainer for preference data (prompt/chosen/rejected)
- PPO config: ppo_epochs, ppo_clip_ratio, ppo_kl_penalty, reward_model
- Two reward sources: reward_model (pre-trained RM) and/or reward_fn (callable)
- soup init --template rlhf — generates PPO config with reward model
- Sweep shortcuts for all PPO parameters
- 51 new tests (611 total), ruff clean, all passing

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 22:17:55 +05:00
Alpamys 14f619cc00 Add vLLM backend for soup serve (Phase 9) — v0.8.0
- Add --backend vllm flag to soup serve for 2-4x better inference throughput
- Add --tensor-parallel and --gpu-memory flags for vLLM tuning
- Auto-detect vLLM and show hint when installed but not enabled
- New utils/vllm.py with engine creation, app factory, LoRA support
- Native token-by-token streaming via vLLM AsyncLLMEngine
- Add serve-fast extra: pip install 'soup-cli[serve-fast]'
- Add vllm detection to version --full
- 30 new tests (560 total), ruff clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 21:30:08 +05:00
Alpamys 823e36eea8 Add Web UI for experiment management (Phase 8) — v0.7.0
- `soup ui` command launches local web interface at http://127.0.0.1:7860
- FastAPI backend with REST API: runs, metrics, config validation, training
  control, data inspection, templates, system info
- Self-contained SPA frontend (Dashboard, New Training, Data Explorer,
  Model Chat) with Chart.js loss/LR charts
- Auto-opens browser on launch (--no-browser to disable)
- Config validation via new load_config_from_string() in config/loader.py
- 40 new tests (530 total), ruff clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 20:55:22 +05:00
Alpamys 5f77bc57da Add Quantization-Aware Training support (Phase 7) — v0.6.0
- Add `quantization_aware: true` config option (TrainingConfig)
- New `utils/qat.py` module: torchao Int8WeightOnlyConfig integration
  with `prepare_model_for_qat()`, `validate_qat_config()`, `is_qat_available()`
- QAT support in all trainers: SFT, DPO, GRPO (+ vision modality)
- Train command shows `+ QAT` in setup panel, validates QAT config
  (rejects unsloth backend, warns on 8bit)
- `pip install 'soup-cli[qat]'` optional dependency (torchao>=0.4.0)
- `torchao` added to `soup doctor` dependency checks
- 35 new tests (test_qat.py): config, validation, trainer integration,
  export compatibility, sweep, doctor
- Total: 490 tests across 37 files

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 20:35:35 +05:00
Alpamys 5b7ad3c358 Add multimodal vision fine-tuning support (Phase 6) — v0.5.0
- Add `modality: vision` config option for vision-language model training
- Add LLaVA and ShareGPT4V data format detection and conversion
- Add `image_dir` field in DataConfig for resolving image paths
- Add vision model loading via AutoModelForVision2Seq + AutoProcessor in SFT trainer
- Add `soup init --template vision` with LLaMA-3.2-Vision config
- Add image statistics display in `soup data inspect` for vision datasets
- Add Pillow as optional `vision` extra dependency
- Add Pillow to `soup doctor` dependency checks
- 51 new tests (455 total), ruff clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 20:16:24 +05:00
Alpamys 6de66fb28c Add Unsloth backend for 2-5x faster training (Phase 5) — v0.4.3
- Add `backend: unsloth` config option (default: transformers)
- Create utils/unsloth.py with FastLanguageModel integration
- Update SFT/DPO/GRPO trainers with _setup_unsloth() path
- Auto-detect unsloth and suggest enabling in `soup train`
- Add `fast` extra: pip install 'soup-cli[fast]'
- Add unsloth to `soup doctor` dependency check
- Add `backend` sweep shortcut
- 33 new tests (404 total), ruff clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 16:55:44 +05:00
Alpamys 5296b0019b Add GRPO reasoning training (Phase 4) — v0.4.2
- New `task: grpo` for Group Relative Policy Optimization (DeepSeek-R1 style)
- Reward function API: built-in (accuracy, format) + custom Python files
- Config fields: grpo_beta, num_generations, reward_fn
- `soup init --template reasoning` template
- GRPOTrainerWrapper with auto batch size scaling for multi-generation
- Sweep shortcuts for grpo_beta, num_generations, reward_fn
- 42 new tests (371 total), lint clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 16:29:25 +05:00
Alpamys df8c341b73 Add sweep early stopping, Rich download progress bars, fix click compat — v0.4.0
- Add --early-stop flag to soup sweep: skip remaining runs when loss exceeds best by threshold
- Add Rich progress bars for HuggingFace Hub model downloads in SFT/DPO trainers
- Pin click>=8.2.0 to fix typer compatibility (11 tests were failing)
- Bump version 0.3.2 → 0.4.0
- 329 tests passing, lint clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-23 15:59:27 +05:00
Alpamys df21329a52 Add Phase 3.1: friendly errors, soup doctor, soup quickstart, UX polish (v0.3.1)
- Friendly error messages: wrap all commands in try/except, map known errors
  (CUDA OOM, missing deps, connection errors) to 2-3 line messages with fix hints
- Global --verbose flag for full tracebacks
- soup doctor: check system info, GPU, all dependency versions with fix suggestions
- soup quickstart: one-command demo (creates data + config + trains TinyLlama)
- Confirmation prompts before train/sweep (skip with --yes)
- 40 new tests (321 total), all passing

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 19:10:36 +05:00
Alpamys 87fd760847 Add Phase 3: serve, data generate, sweep, diff, DeepSpeed (v0.3.0)
- soup serve: FastAPI inference server with OpenAI-compatible API, SSE streaming
- soup data generate: synthetic data generation via OpenAI API or local models
- soup sweep: grid/random hyperparameter search with experiment tracker integration
- soup diff: side-by-side model comparison with metrics
- Multi-GPU/DeepSpeed: ZeRO Stage 2/3 configs, --deepspeed flag in train command
- 95 new tests (281 total), all passing
- Removed TESTING_GUIDE.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 17:14:08 +05:00
Alpamys 8b1844d316 Fix deprecated torch_dtype and warmup_ratio warnings, add testing guide (v0.2.2)
- Replace torch_dtype with dtype in chat, merge, export commands (transformers deprecation)
- Replace warmup_ratio with warmup_steps in SFT/DPO trainers (transformers v5.2 deprecation)
- Add TESTING_GUIDE.md for local Windows testing workflow

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 13:29:07 +05:00
Alpamys f03b578428 Phase 2.5: add export GGUF, merge LoRA, resume training, W&B integration (v0.2.0)
New commands:
- soup export --model ./output --format gguf --quant q4_k_m
- soup merge --adapter ./output

New train flags:
- soup train --resume auto (or --resume ./checkpoint-500)
- soup train --wandb

184 tests passing (was 147), all lint clean.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-03 22:29:44 +05:00
Alpamys 2aaa87fb4e Phase 2: experiment tracking, data tools, model evaluation
- Add SQLite experiment tracker (~/.soup/experiments.db) with auto-logging
  of config, per-step metrics, hardware info, and eval results
- Add soup runs commands: list, show (with plotext loss curves), compare, delete
- Integrate tracker into soup train (auto start_run/finish_run/fail_run)
- Add soup data convert (alpaca/sharegpt/chatml bidirectional conversion)
- Add soup data merge (concatenate datasets with optional shuffle)
- Add soup data dedup (MinHash near-duplicate removal via datasketch)
- Add soup data stats (length percentiles, token counts, language detection)
- Add soup eval (lm-evaluation-harness wrapper with tracker integration)
- Add reverse format conversion: messages_to_format() in data/formats.py
- Add extended_stats() to data/validator.py
- Update monitoring callback to log metrics to tracker
- Add plotext to deps, datasketch as optional [data] dep
- Update README and CLAUDE.md with Phase 2 docs
- 70 tests passing, ruff clean

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 23:34:28 +05:00
Alpamys a2a0f2cab3 Phase 1.5: add soup chat, soup push, DPO trainer + smoke tests
- soup chat --model ./path: interactive terminal chat with LoRA adapters
  (auto-detects base model, supports /quit /clear /system commands)
- soup push --model ./path --repo user/model: upload to HuggingFace Hub
  (auto model card generation, token from env/cache/flag)
- DPO trainer: full DPOTrainerWrapper with LoRA + quantization support
  (configurable dpo_beta, preference data format {prompt, chosen, rejected})
- Smoke tests: real SFT + DPO training with tiny-gpt2 (pytest -m smoke)
- SFT trainer: fallback for models without chat_template
- Updated README, schema, formats, pyproject.toml, .gitignore

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 21:18:19 +05:00
Alpamys 7433029d19 Fix all ruff lint errors and failing test
- Fix 23 ruff errors: line too long, unused imports, ambiguous vars
- Fix validator: empty string is valid data, only count None as empty
- Remove unused imports in display.py and validator.py
- Rename ambiguous `l` vars to `part`, `entry`, `length`
- Break long lines in callback.py, display.py, sft.py, constants.py

All 20 tests passing, ruff clean.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 16:25:46 +05:00
Alpamys d6e932a1d3 Initial project setup: CLI skeleton + config + trainer + data pipeline
- Typer CLI: soup init, soup train, soup data inspect/validate
- Pydantic config schema with YAML loader and validation
- Data pipeline: JSONL/JSON/CSV/Parquet + HuggingFace datasets
- Format detection: Alpaca, ShareGPT, ChatML (auto-detect)
- SFT trainer wrapper over transformers + peft + trl
- QLoRA/LoRA support with auto batch size estimation
- GPU detection (CUDA/MPS/CPU) and memory calculation
- Rich live terminal dashboard for training monitoring
- Config templates: chat, code, medical
- Tests (pytest) + GitHub Actions CI
- MIT license

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 16:14:56 +05:00