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https://github.com/rohitg00/ai-engineering-from-scratch.git
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Rohit Ghumare
8050434e5c
* fix(phase-13/06): bootstrap sys.path so the documented test command runs The lesson doc says to run unittest discovery over code/tests, but the test imported main with no path setup, so discovery from the lesson root failed with ImportError. Insert the code directory on sys.path the way the later protocol lessons already do. Passes from the lesson root and from code/. * fix(phase-13/07): bootstrap sys.path so the documented test command runs Discovery over code/tests failed with ImportError because the test imported main with no path setup. Insert the code directory on sys.path to match the later protocol lessons. * fix(phase-13/08): bootstrap sys.path so the documented test command runs The documented discovery command raised ImportError on import main. Add the sys.path bootstrap used by the sibling lessons so the test runs from the lesson root and from code/. * fix(phase-13/09): bootstrap sys.path so the documented test command runs The documented discovery command raised ImportError on import main. Add the sys.path bootstrap used by the sibling lessons so the test runs from the lesson root and from code/. * fix(phase-19/29): make the fixture tests directory an importable package The demo fixture ships a namespace-style tests directory with no __init__.py, so a regular tests package elsewhere on sys.path could shadow it and the in-repo test runner failed to import the fixture module. Add an empty __init__.py so the fixture tests resolve regardless of what else is installed. * fix(phase-19/39): bound generation by chars and gate the demo on loss decode_response replaces invalid UTF-8 bytes, so a 4-byte generation can re-encode to more than 4 bytes; the test now bounds the decoded character count, which is the real invariant that generate enforces. The demo's success gate keyed on exact-match improvement, which the documented padding mask makes unreachable, so it now checks that training loss decreased. * fix(phase-19/59): test patch-projection grad via a nonzero reduction Summing the CLS token straight out of the final LayerNorm is an algebraic zero for any input, so the gradient reaching the patch projection was always zero and the test failed for a reason unrelated to the encoder. Reduce with a sum of squares, which the demo already uses, so the test exercises a real gradient path. * fix(phase-19/47): load checkpoints weights-only, jail shard paths torch.load ran with weights_only=False, so restoring an untrusted checkpoint executes whatever the pickle names. Store RNG state as primitives so it survives the weights-only loader, load every payload with weights_only=True, reject shard paths that resolve outside the checkpoint directory, and raise ValueError on integrity failures instead of assert. Add regression tests for a pickled object and a shard path escape, and update the docs, skill, and quiz. * fix(phase-11/09): guard run_code with an AST check, not a blocklist The substring blocklist read the snippet as text, so an attribute chain such as the object-subclass walk reached the real interpreter through __globals__. Parse the snippet and walk the tree, rejecting import statements, dunder attribute access, and unsafe builtin names by structure. Add regression tests for the escape, and make the tool description and docs state plainly that this is a teaching filter, not real isolation. Align the TypeScript port's wording and block the constructor and globalThis gadgets in its blocklist. * fix(site): serve markdown at / before the static file wins The homepage markdown-negotiation rewrite lost to the static index.html, so requesting text/markdown at / returned cached HTML. Move it into a legacy route, which is evaluated before the filesystem. Add a readiness-test guard that fails if any negotiation rewrite is shadowed by a static file, and assert the root route. * fix(phase-19/86): parse nested sequences in the stdlib YAML fallback The PyYAML-free fallback stopped gathering a rule's lines at the first nested sequence item, so a rule with an any_of block lost that block and every field after it, and the engine rejected the rule for a missing explanation. The gather now ends on indentation alone, so a deeper sequence stays part of its rule. Verified the fallback matches PyYAML byte for byte on rules.yml, which restores this lesson and the end-to-end safety gate that composes it on a standard Python install. * test(ci): run each lesson's own tests on push and pull request CI executed the certification labs but never the 523 lessons, so a lesson that could not import its own module reached main unnoticed. Adds scripts/run_lesson_tests.py, which discovers each lesson's tests across the four layouts in the repo and runs them the way the lesson docs say, and a lesson-tests job that runs it. The runner installs no scientific dependencies: a lesson that needs one is skipped by scanning its source, so the job stays green while the stdlib lessons run for real. Documents the command in CONTRIBUTING. * test(ci): gate quiz answer-length bias and ratchet it down The quizzes de-bias answer position but not answer length: on 84% of questions the correct option is the longest by a wide margin, so a reader can guess it without knowing the material. Adds scripts/check_quiz_bias.py, which measures the share of length-biased questions and, in --check, fails when a change pushes the rate above a baseline set to today's level. New or edited quizzes cannot add bias, and the baseline ratchets down as quizzes are rebalanced. Wires it into the curriculum workflow next to the position gate and documents the rule in AGENTS.md. Reducing the existing rate is a separate content pass; this stops it getting worse and makes it measurable. * fix(phase-11/09): add module docstring, honest TS wording, ast import Address review: give function_calling.py a module docstring like the sibling lessons, align the TypeScript run_code tool description with the honest wording already used on the Python side (a teaching filter, not real isolation), and add the missing ast import to the docs example's import block so the example runs. * fix(phase-19/39): fail the demo on a non-finite final loss The success gate compared the final loss to the first with >=, so a NaN final loss made the comparison false and the demo exited 0. Require the final loss to be finite before comparing, so a diverged run is reported as a failure. * docs(phase-19/47): note the torch 2.6 requirement for weights_only Before torch 2.6 the weights_only loader had a known bypass (CVE-2025-32434), so the security guarantee this lesson relies on holds only from 2.6 on. Say so next to the weights_only explanation. * fix(site): match the root markdown Accept header case-insensitively Media types are case-insensitive, so a client sending Text/Markdown should still reach the markdown route. Add the (?i) flag to the root route's Accept matcher. * fix(ci): fail a lesson when a real test fails next to a missing dep The lesson-test runner skipped a suite whenever its output mentioned a missing optional module, which could hide a genuine assertion failure in the same run. Only skip when the output shows no test failure alongside the missing module. * fix(ci): fail the quiz-bias check on an unreadable quiz file The scan skipped a quiz.json it could not parse and carried on, so a malformed file would leave the gate green on an incomplete scan. Collect read and parse errors, report each file, and exit non-zero when any are found.