Remove CLI/app integrations and require Python 3.12+ (#86)

* Remove CLI and Tracer app integrations

* Require Python 3.12 and test through 3.14

* Require joblib with Python 3.12 compatibility

Author: adrida

.github/workflows/ci.yml

@@ -8,10 +8,15 @@ on:
 
 jobs:
   test:
+    name: Python ${{ matrix.python-version }} (${{ matrix.dependencies }})
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.12", "3.13", "3.14"]
+        dependencies: [latest]
+        include:
+          - python-version: "3.12"
+            dependencies: minimum
 
     steps:
       - uses: actions/checkout@v4
@@ -24,7 +29,28 @@ jobs:
       - name: Install package and dev dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -e ".[dev]"
+          if [ "${{ matrix.dependencies }}" = "minimum" ]; then
+            python -m pip install -e ".[dev]" "numpy==1.26.4" "scikit-learn==1.4.2" "joblib==1.3.2"
+          else
+            python -m pip install -e ".[dev]"
+          fi
+          python -m pip check
 
       - name: Run tests
         run: pytest tests/ -v --tb=short
+
+  watch-js:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: js
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-node@v4
+        with:
+          node-version: "20"
+          cache: npm
+          cache-dependency-path: js/package-lock.json
+      - run: npm ci
+      - run: npm test -- --maxWorkers=1 --minWorkers=1
+      - run: npm run build

.github/workflows/release.yml

@@ -17,7 +17,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.14"
       - name: Verify pushed tag matches package version
         run: |
           tag="${GITHUB_REF_NAME#v}"

AGENTS.md

@@ -14,7 +14,7 @@ pip install tracer-llm                # numpy, scikit-learn, joblib - that's it
 pip install tracer-llm[embeddings]    # adds sentence-transformers (if user needs text-in routing)
 ```
 
-No GPU required. No API keys required for fitting. Works on Python 3.9+.
+No GPU required. No API keys required for fitting. Requires Python 3.12+; CI tests 3.12, 3.13, and 3.14.
 
 ---
 
@@ -154,8 +154,8 @@ router = tracer.load_router(".tracer", embedder=my_embedder)
 ```
 
 ### Pattern 4: HTTP server (zero deps)
-```bash
-tracer serve .tracer --port 8000
+```python
+tracer.serve(".tracer", port=8000)
 # POST /predict {"embedding": [...]} → {"label", "decision", "accept_score"}
 ```
 
@@ -173,7 +173,7 @@ tracer serve .tracer --port 8000
 ## Things you CAN do autonomously
 
 - Install `tracer-llm` (it's lightweight, MIT licensed)
-- Run `tracer demo` to show the user what it does
+- Follow `notebooks/01-quickstart.ipynb` for a worked example
 - Write traces to JSONL from any data source
 - Fit a policy if traces + embeddings are available
 - Generate the HTML report
@@ -195,7 +195,6 @@ tracer serve .tracer --port 8000
 | `Embedder.from_endpoint(url)` | External embedding API | Needs URL + auth from human |
 | `tracer.generate_html_report(dir)` | Visual audit | No |
 | `tracer.serve(dir, port=8000)` | HTTP server | No |
-| `tracer demo` | Interactive demo | No |
 
 ---
 

CHANGELOG.md

@@ -3,6 +3,26 @@
 All notable changes to TRACER are recorded here. This project follows semantic
 versioning.
 
+## Unreleased
+
+### Changed (breaking)
+- Require Python 3.12 or newer; drop support for Python 3.9–3.11. CI tests
+  Python 3.12, 3.13, and 3.14, plus the minimum core dependencies on 3.12.
+- Allow NumPy 1.26.4 through 2.x so Python 3.14 can install compatible wheels.
+  Require scikit-learn 1.4.2+ and joblib 1.3.2+ in core, and PyTorch 2.4.1+
+  for the optional embedding extras. Remove the obsolete NumPy downgrade advice.
+- Build releases and run the documented Python sidecar on Python 3.14.
+
+### Removed (breaking)
+- The `tracer` command-line executable and command implementations. Use the
+  Python APIs for fitting, scanning, updating, reports, and serving predictions.
+- The Tracer app client, authentication, and automatic app telemetry exporters
+  in both Python and JavaScript. Existing app credentials no longer trigger
+  uploads. Local recording, custom sinks, and explicitly configured generic
+  HTTP exports remain available.
+- App connection instructions and command-line documentation. All current
+  examples use the library APIs.
+
 ## 0.3.3 (2026-06)
 
 ### Fixed
@@ -20,48 +40,27 @@ versioning.
   `ValueError` messages. Previously the count excluded blank lines, so
   the reported line was lower than the actual position of the bad record.
 
-## 0.3.1 (2026-06)
-
-### Changed
-- `tracer cloud` commands that take a tracer (`get`, `training`, `analytics`,
-  `label-space`, `traces`, ...) now accept either the tracer slug or its id.
-- `tracer cloud scan` works without logging in, matching the public web scan.
-
-### Fixed
-- `tracer cloud keys create` and `tracer cloud ingest-keys create` now honor
-  `--json` and emit the created record (including the one-time secret) as JSON.
-
 ## 0.3.0 (2026-06)
 
 ### Added
-- `tracer.watch`: a decorator (and HTTP fallback) that observes the LLM calls
-  your pipeline already makes and ships them, free, to Tracer Cloud, where they
-  accumulate and auto-optimize once there are enough. Captures the full request
-  and response on the OpenTelemetry GenAI (`gen_ai.*`) schema, with pluggable
-  sinks (local file, Tracer Cloud, OTLP, or several at once).
+- `tracer.watch`: a decorator that records LLM calls on the OpenTelemetry
+  GenAI (`gen_ai.*`) schema, with pluggable local and generic export sinks.
 - `@tracer-llm/watch`: a zero-dependency JavaScript/TypeScript mirror of the watch
   decorator (async-context aware), so JS pipelines get the same one-line
   observability as Python.
-- `tracer cloud`: a full command-line interface for Tracer Cloud, at parity with
-  the dashboard. Browser or password login, then manage tracers (create, quick
-  and bulk uploads, agentic `onboard`, rename, delete), training (retrain,
-  auto-retrain, promote/rollback, live status), routing (`route`), test
-  batteries, the model library, API keys, observability ingest keys, billing,
-  analytics, trace selection (`traces`), and a public `scan`.
 - Lazy package initialization so `import tracer` stays fast and only pulls in the
   heavy pieces when you actually use them.
 
 ### Changed
-- `tracer scan` is more robust on messy uploads: tolerant input/label aliasing
-  and a clarification path so ambiguous files still produce a result.
+- Trace ingestion accepts additional input and label aliases.
 
 ### Docs
-- New guides for the watch decorator and the `tracer cloud` CLI.
+- New guide for the watch decorator.
 
 ## 0.2.0 (2026-06)
 
 ### Added
-- `tracer scan`: a fast, conservative day-one read of a traces file, before any
+- `tracer.scan()`: a fast, conservative day-one read of a traces file, before any
   training. It groups traffic by similarity and measures, on a held-out slice it
   never saw, how much a near-free model can answer at your target agreement,
   using exact Clopper-Pearson bounds, with an optional per-1k and monthly savings
@@ -72,24 +71,20 @@ versioning.
   far from the training distribution (kNN distance, global and per-predicted-label
   thresholds) regardless of surrogate confidence, so off-distribution traffic goes
   to the teacher instead of getting a confident guess.
-- `tracer fit --trees` to opt in the tree surrogates, and `--skip` to drop named
-  candidates from the zoo.
+- `FitConfig.skip_candidates` to drop named candidates from the zoo, including
+  tree surrogates when a lighter sweep is desired.
 - Trace loaders accept common key aliases for both input and label
   (`input/query/text/prompt/question` and
   `teacher/teacher_output/label/intent/output/answer`).
-- Bring-your-own embeddings for `tracer scan`: local sentence-transformers by
-  default (`--embed-model`), a precomputed `.npy` (`--embeddings`), or your own
-  HTTP embedding endpoint (`--embed-url`, with header and response-key options).
+- Bring-your-own embeddings for `tracer.scan()`: pass a precomputed array with
+  `embeddings=`, or select a local sentence-transformers model with `model=`.
 
 ### Changed
 - The parity gate now certifies on an exact held-out lower bound instead of an
   in-sample point estimate, so a policy cannot clear the target by in-sample luck
   and then break the contract on real traffic. Coverage is now monotonic in the
   target, and a hybrid select-then-verify procedure recovers coverage at strict
   targets that a plain held-out split discarded.
-- Tree surrogates (decision tree, random forest, extra-trees, gradient boosting)
-  are now off by default in `tracer fit`; the default zoo is the fast linear and
-  MLP heads. Use `--trees` for hard, high-class-count tasks.
 - The HTML report is restyled to the light Tracer theme, and the word "audit" is
   dropped across the report and docs.
 

CONTRIBUTING.md

@@ -56,6 +56,9 @@ we're optimizing for.
 
 ## Setup
 
+Use Python 3.12 or newer. CI tests 3.12, 3.13, and 3.14 with current
+dependencies, plus 3.12 with the minimum supported core dependencies.
+
 ```bash
 git clone https://github.com/adrida/tracer
 cd tracer
@@ -68,13 +71,20 @@ pip install -e ".[dev]"
 pytest tests/ -v
 ```
 
-Tests use synthetic data and run in temporary directories. No external
-dependencies or API keys required.
+Tests use synthetic data and run in temporary directories. No model downloads
+or API keys are required. To check the JavaScript recorder:
+
+```bash
+cd js
+npm ci
+npm test -- --maxWorkers=1 --minWorkers=1
+npm run build
+```
 
 ## Quick sanity check
 
 ```bash
-tracer demo
+pytest tests/test_router.py tests/test_watch.py -q
 ```
 
 ## Project structure
@@ -101,9 +111,8 @@ src/tracer/
   runtime/
     router.py            <- production Router class
     serve.py             <- lightweight HTTP prediction server (stdlib only)
-  cli/
-    main.py              <- tracer CLI entry point (fit, report, update, demo, serve)
-    _ui.py               <- terminal formatting and progress display
+  scanner.py             <- pre-training traffic diagnostics and reports
+  watch.py               <- local trace recording and generic export sinks
 ```
 
 ## Adding a new surrogate model