feat(m1): scaffold tsmm package (T1.1)

- pyproject.toml (src-layout, deps per plan)
- src/tsmm/{data,model,train,eval} skeletons
- tests/test_smoke.py (RED->GREEN: importable + subpackages)
- configs/, scripts/, data/, checkpoints/ + .gitignore
- project venv (.venv) for reproducible env (M1 deps only; CUDA torch @ M2)

Verifications: import tsmm OK; pytest tests/ 3 passed.

.gitignore

@@ -4,6 +4,16 @@
 node_modules/
 jspm_packages/
 
+# Python
+.venv/
+venv/
+env/
+__pycache__/
+*.py[cod]
+*.egg-info/
+.pytest_cache/
+.ipynb_checkpoints/
+
 # ─────────────────────────────────────────────────────────────
 # Build output & caches
 # ─────────────────────────────────────────────────────────────

README.md

@@ -0,0 +1,33 @@
+# tsmm
+
+**Time-series as a Modality** — an experimental, single-GPU multimodal model that
+treats multivariate time series as an independent modality, jointly injected into a
+small LLM (Qwen2.5-0.5B) for time-series question answering and reasoning
+(ChatTS route).
+
+## Status
+
+M1 (data pipeline) under construction. See
+`docs/superpowers/specs/2026-06-29-ts-as-modality-design.md` for the design and
+`docs/superpowers/plans/2026-06-29-ts-as-modality-plan.md` for the task plan.
+
+## Layout
+
+```
+src/tsmm/   package (data, model, train, eval)
+configs/    training / data configs
+scripts/    offline generation & training entrypoints
+tests/      pytest suite
+data/       generated datasets (gitignored)
+checkpoints/ model checkpoints (gitignored)
+```
+
+## Install (dev)
+
+```bash
+python3 -m venv .venv
+. .venv/bin/activate
+pip install -e .            # full deps (incl. torch/transformers/peft/...)
+# M1-only lightweight install:
+pip install numpy tqdm pyyaml pytest && pip install -e . --no-deps
+```

checkpoints/.gitignore

@@ -0,0 +1,3 @@
+# Model checkpoints — never commit.
+*
+!.gitignore

configs/README.md

@@ -0,0 +1,3 @@
+# Configs directory
+
+YAML / Python configs for data generation and training live here.

data/.gitignore

@@ -0,0 +1,3 @@
+# Generated datasets — never commit.
+*
+!.gitignore

openspec/changes/ts-as-modality/tasks.md

@@ -5,7 +5,7 @@
 
 ## 1. M1 · 数据管线
 
-- [ ] 1.1 项目脚手架：创建 `pyproject.toml`（torch/transformers/peft/accelerate/datasets/numpy/tqdm/pyyaml/pytest）、`src/tsmm/` 模块骨架、`configs/`、`scripts/`、`tests/`，并建 `data/`、`checkpoints/` 加 `.gitignore`（验证：`python -c "import tsmm"` 不报错；`pytest tests/` 可跑）
+- [x] 1.1 项目脚手架：创建 `pyproject.toml`（torch/transformers/peft/accelerate/datasets/numpy/tqdm/pyyaml/pytest）、`src/tsmm/` 模块骨架、`configs/`、`scripts/`、`tests/`，并建 `data/`、`checkpoints/` 加 `.gitignore`（验证：`python -c "import tsmm"` 不报错；`pytest tests/` 可跑）
 - [ ] 1.2 属性词表与采样 `data/attributes.py`：定义变量名词表/单位/采样率档位，`sample_attributes(n_channels)` 返回结构化属性（验证：单测字段齐全、可复现）
 - [ ] 1.3 成分模型与时序合成 `data/synthesis.py`：`generate_series`（趋势+周期+基线+噪声）、`inject_anomaly`（尖刺/水平偏移/方差膨胀/缺失段/缓慢漂移，返回逐点 labels+段元数据）、`couple_event`（t 处阶跃+事件文本）、`add_missing`（NaN 占位）（验证：给定 seed 确定；异常段与 labels 一致；事件处有阶跃）
 - [ ] 1.4 指令与回答生成 `data/instruct.py`：6 类指令模板（描述/异常/根因/预测/比较/事件关联）+ Evol-Instruct 演化，`build_instruction` 产 JSON 区间/数值/文本回答（验证：异常类 JSON 可 `json.loads` 且段与 labels 吻合）

pyproject.toml

@@ -0,0 +1,35 @@
+[build-system]
+requires = ["setuptools>=68", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "tsmm"
+version = "0.0.1"
+description = "Time-series as a modality: multimodal TS-question-answering model (experimental, single-GPU)"
+readme = "README.md"
+requires-python = ">=3.10"
+license = { text = "MIT" }
+authors = [{ name = "tsmm contributors" }]
+dependencies = [
+    "torch",
+    "transformers",
+    "peft",
+    "accelerate",
+    "datasets",
+    "numpy",
+    "tqdm",
+    "pyyaml",
+    "pytest",
+]
+
+[project.optional-dependencies]
+# Heavy GPU deps installed on-demand at M2 (CUDA torch build, etc.)
+dev = ["pytest", "pytest-cov"]
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+pythonpath = ["src"]
+addopts = "-q"

scripts/README.md

@@ -0,0 +1,3 @@
+# Scripts directory
+
+Offline entrypoints: `gen_synthetic.py`, `train_stage1.sh`, `train_stage2.sh`, `run_eval.sh`.

src/tsmm/__init__.py

@@ -0,0 +1,7 @@
+"""tsmm — Time-series as a Modality (multimodal).
+
+Experimental, single-GPU implementation following the ChatTS "TS as a new
+modality" route. See `docs/superpowers/specs/2026-06-29-ts-as-modality-design.md`.
+"""
+
+__version__ = "0.0.1"

src/tsmm/data/__init__.py

@@ -0,0 +1 @@
+"""Data pipeline: attribute vocab, synthesis, instructions, collator, real benchmarks."""

src/tsmm/eval/__init__.py

@@ -0,0 +1 @@
+"""Evaluation: answer parsing, TS anomaly metrics, QA judging, baselines."""

src/tsmm/model/__init__.py

@@ -0,0 +1 @@
+"""Model components: TS encoder, projector, multimodal splice, training/inference wrapper."""

src/tsmm/train/__init__.py

@@ -0,0 +1 @@
+"""Training: stage-1 alignment, stage-2 SFT, losses."""

tests/test_smoke.py

@@ -0,0 +1,25 @@
+"""Smoke tests for the package boundary (T1.1).
+
+These guard the most basic contract: the package is importable and exposes
+a version. If these fail, the install / src-layout is broken.
+"""
+
+import tsmm
+
+
+def test_package_is_importable():
+    assert tsmm is not None
+
+
+def test_package_exposes_version():
+    assert isinstance(tsmm.__version__, str)
+    assert tsmm.__version__  # non-empty
+
+
+def test_subpackages_importable():
+    # M1 will populate these; the skeleton must already expose the namespaces.
+    import importlib
+
+    for sub in ("data", "model", "train", "eval"):
+        mod = importlib.import_module(f"tsmm.{sub}")
+        assert mod is not None