mirror of
https://github.com/kuhyx/WUT_Computer_Science.git
synced 2026-11-10 18:47:11 +01:00
Krzysztof kuhy Rudnicki
bd24dd57ea
kuhy overruled the "do not fix coursework to be better than it was submitted" rule: git history is the archive, so the working tree can be clean. This lands the config and the mechanical half of the cleanup -- 9,281 ruff findings under the fleet config down to 3,686, with no per-file-ignores anywhere. What is in here: - pyproject.toml, the first one in this repo. select = ["ALL"], mypy strict, and the vendored list mirrored into ruff exclude and coverage omit. Five rules are off and each says why; CPY001 is the only judgement call, because stamping a copyright header onto 137 university assignments would assert a licence that was never claimed. No hook is wired up yet -- a gate lands only once its subject is clean. - ruff format + the safe fixes, then a second pass over the docstring rules ruff marks unsafe (they only edit docstring text). 108 files. - TRAK/sightpy is vendored, not coursework: it is rafael-fuente/Python-Raytracer (BSD 3-Clause). Verified against a fresh upstream clone with line endings normalised -- 30 of 32 files byte-identical, ray.py and scene.py carrying a 12- and 13-line local patch that counts rays for the report. 35 files that should never have been linted, now excluded and restored. - WDWR, SPD, MOM and ECRYPT are fully clean, by hand and verified by running them: WDWR's three plot scripts print the same statistics as before, MOM's PuLP model solves to the same cost. WDWR's graph.py had a 342-character CSV header embedded as a string literal, which cannot be wrapped -- the data moved to data/pareto_front.csv. Two 0-byte .py stubs are deleted; an empty file is not a deliverable and git still has it. Three harness bugs found by actually running things: - `run` now forces MPLBACKEND=Agg. TRAK finished its ray trace in 37 seconds and then sat for 45 minutes: plt.show() had opened an image viewer and was waiting for someone to close the window. - TRAK's main.py only pops that viewer with --show now, and its runner writes to a gitignored build/ via the new --entry-args. The default output path is outputs/output.png, which is TRACKED -- a plain run overwrote a submitted deliverable. - course_lib.sh was 357 lines, over this repo's own cap. Split into course_probe.sh and course_run.sh. Verified: ECOTE 26 tests pass, ECRYPT_PROJECT 99 pass, TRAK renders cornell_box in 37s and exits 0, every module compiles, and every import ruff removed was checked to be genuinely unused. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0172dj34FDpao6wsix8ZuCzE
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
from openai import OpenAI
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def sentence_loop(sentences):
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# Process each sentence
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chunked_sentences = []
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for sentence in sentences:
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chunked_sentences = process_sentence(sentence, chunked_sentences)
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return chunked_sentences
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def process_sentence(sentence, chunked_sentences):
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response = client.chat.completions.create(
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messages=[
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{
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"role": "user",
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"content": "Please divide the following sentence into iSTS chunks. Format the response as: [[chunk 1]] [[chunk 2]] ... Ensure each chunk is enclosed in double square brackets and separated by a space. If you cannot correctly chunkify the sentence, return an error message in the format: 'ERROR: Cannot chunkify sentence: <sentence>'. Here is the sentence: "
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+ sentence,
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}
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],
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model="gpt-3.5-turbo",
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)
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chunked_sentence = response.choices[0].message.content
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print("chunked_sentence: ", chunked_sentence)
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chunked_sentences.append(chunked_sentence)
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return chunked_sentences
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def chunk_sentences(file_path, output_path, api_key):
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# Read the sentences from the file
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with open(file_path) as file:
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sentences = file.readlines()
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# Process each sentence
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chunk_sentences = sentence_loop(sentences)
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print(chunk_sentences)
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# Write the chunked sentences to a new file
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with open(output_path, "w") as output_file:
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output_file.writelines(sentence + "\n" for sentence in chunk_sentences)
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# Usage
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file_path = "student/STSint.testinput.answers-students.sent2.txt"
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output_path = "chunks_gpt_two.txt"
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# Replace me with os.environ['API_KEY']
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api_key = "REDACTED_OPENAI_API_KEY"
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client = OpenAI(api_key=api_key)
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chunk_sentences(file_path, output_path, api_key)
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