From ff7629372fe311013499e5e128438f1d9b7d7518 Mon Sep 17 00:00:00 2001 From: Axy Date: Thu, 27 Aug 2026 17:59:29 +0200 Subject: [PATCH] Partial impl of inference --- pyproject.toml | 1 + src/rag/__init__.py | 41 ++++++++++++--- src/rag/_stoopid.py | 46 +++++++++++++++++ src/rag/answering.py | 117 +++++++++++++++++++++++++++++++++++++++++++ src/rag/chunking.py | 6 +-- src/rag/models.py | 4 +- src/rag/retrieval.py | 10 +++- uv.lock | 55 ++++++++++++++++++-- 8 files changed, 263 insertions(+), 17 deletions(-) create mode 100644 src/rag/_stoopid.py create mode 100644 src/rag/answering.py diff --git a/pyproject.toml b/pyproject.toml index cfca574..b712de9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,6 +5,7 @@ description = "Retrieval augmented generation" readme = "README.md" requires-python = ">=3.13" dependencies = [ + "accelerate>=1.14.0", "fire>=0.7.1", "pydantic>=2.13.4", "stopwordsiso>=0.7.1", diff --git a/src/rag/__init__.py b/src/rag/__init__.py index 7e66bb0..4157d8b 100644 --- a/src/rag/__init__.py +++ b/src/rag/__init__.py @@ -7,12 +7,13 @@ import pydantic from pydantic_core import ValidationError from tqdm import tqdm +from rag.answering import InferenceBackend from rag.chunking import FileType, chunk_file from rag.models import ( - MinimalSource, RagDataset, RetrievedQuestion, SearchResults, + Source, ) from rag.retrieval import BM25, BagOfWords, stopwords @@ -22,16 +23,15 @@ def main() -> None: storage_adapter = pydantic.TypeAdapter(dict[bytes, BagOfWords]) -key_adapter: pydantic.TypeAdapter[MinimalSource] = pydantic.TypeAdapter( - MinimalSource -) +key_adapter: pydantic.TypeAdapter[Source] = pydantic.TypeAdapter(Source) class RAG: """A retrieval augmented generation CLI""" def __init__(self) -> None: - self._bm25_store: BM25[MinimalSource] | None = None + self._bm25_store: BM25[Source] | None = None + self._inference_store: InferenceBackend | None = None def index( self, @@ -75,12 +75,12 @@ class RAG: exit(1) print(f"Successfully ingested: {data} -> {index}") - def _bm25(self, index: str) -> BM25[MinimalSource]: + def _bm25(self, index: str) -> BM25[Source]: if self._bm25_store: return self._bm25_store try: with open(index + "/index.json") as f: - bm25: BM25[MinimalSource] = BM25.from_storage( + bm25: BM25[Source] = BM25.from_storage( (key_adapter.validate_json(k), v) for k, v in tqdm( storage_adapter.validate_json(f.read()).items(), @@ -93,7 +93,7 @@ class RAG: logging.getLogger(__name__).error(f"Failed to open index {e}") exit(1) - def _search(self, query: str, k: int, index: str) -> list[MinimalSource]: + def _search(self, query: str, k: int, index: str) -> list[Source]: bm25 = self._bm25(index) return bm25.best_k(query, k) @@ -140,3 +140,28 @@ class RAG: except (OSError, ValidationError) as e: logging.getLogger(__name__).error(f"Failed to open dataset {e}") exit(1) + + def _inference(self) -> InferenceBackend: + if not self._inference_store: + self._inference_store = InferenceBackend("Qwen/Qwen3-0.6B") + return self._inference_store + + def answer( + self, + query: str, + /, + k: int = 5, + index: str = "data/processed", + max_tokens: int = 100, + ) -> None: + sources = self._search(query, k, index) + inference = self._inference() + print("Sources:") + for source in sources: + print(source) + print("") + inference.answer( + RetrievedQuestion(question=query, retrieved_sources=sources), + max_tokens, + cb=lambda s: print(s, end="", flush=True), + ) diff --git a/src/rag/_stoopid.py b/src/rag/_stoopid.py new file mode 100644 index 0000000..991966e --- /dev/null +++ b/src/rag/_stoopid.py @@ -0,0 +1,46 @@ +"""Useless module where I can shove the required but overcomplicated and +poorly designed pydantic classes.""" + +import uuid + +from pydantic import BaseModel, Field + + +class MinimalSource(BaseModel): + file_path: str + first_character_index: int + last_character_index: int + + +class UnansweredQuestion(BaseModel): + question_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + question: str + + +class AnsweredQuestion(UnansweredQuestion): + sources: list[MinimalSource] + answer: str + + +class RagDataset(BaseModel): + rag_questions: list[AnsweredQuestion | UnansweredQuestion] + + +class MinimalSearchResults(BaseModel): + question_id: str + question: str + retrieved_sources: list[MinimalSource] + + +class MinimalAnswer(MinimalSearchResults): + answer: str + + +class StudentSearchResults(BaseModel): + search_results: list[MinimalSearchResults] + k: int + + +class StudentSearchResultsAndAnswer(BaseModel): + search_results: list[MinimalAnswer] + k: int diff --git a/src/rag/answering.py b/src/rag/answering.py new file mode 100644 index 0000000..f201793 --- /dev/null +++ b/src/rag/answering.py @@ -0,0 +1,117 @@ +import logging +from collections.abc import Callable +from typing import Any, cast + +from transformers import AutoModelForCausalLM, AutoTokenizer +from transformers.generation import BaseStreamer # type:ignore + +from rag.models import AnsweredQuestion, RetrievedQuestion, Source + + +class InferenceBackend: + SYSTEM_PROMPT: str = """You are a codebase and document search assistant. + You answer querries factually using the provided sources. + Answer directly with no reasoning, no tags. + Answer simply, in a few short sentences, in a single line. + Assume the user cannot see the sources, they are your knowledge, \ + do not mention them. + End your answer with a newline.""" + + class _Streamer(BaseStreamer): + def __init__( + self, backend: "InferenceBackend", cb: Callable[[str], None] + ) -> None: + self.backend = backend + self.cb = cb + self.skip = True + + def put(self, value: Any) -> None: + if self.skip: + self.skip = False + return + s: str = cast( + str, + self.backend.tokenizer.decode(value, skip_special_tokens=True), + ) + self.cb(s.rstrip("\n")) + + def end(self) -> None: + self.cb("\n") + + def __init__(self, model: str) -> None: + self.model: Any = AutoModelForCausalLM.from_pretrained( + model, device_map="auto" + ) + self.tokenizer = AutoTokenizer.from_pretrained( + model, padding_side="left" + ) + + @staticmethod + def _fetch_range(source: Source) -> str | None: + try: + with open(source.file_path) as f: + s = f.read() + return s[ + source.first_character_index : source.last_character_index + + 1 + ] + except OSError as e: + logging.getLogger(__name__).error( + f"Failed to fetch source {source}: {e}" + ) + return None + + def _prompt(self, question: RetrievedQuestion) -> str: + sources = "\n\n".join( + s + for e in question.retrieved_sources + if (s := self._fetch_range(e)) + ) + sep = "\n\n\n" + return ( + "# System instructions\n" + + self.SYSTEM_PROMPT + + sep + + "# Context\n" + + sources + + "# Question\n" + + question.question + + sep + + "# Answer\n" + ) + + def _answer( + self, + question: RetrievedQuestion, + max_tokens: int, + cb: Callable[[str], None], + ) -> str: + prompt = self._prompt(question) + model_inputs = self.tokenizer([prompt], return_tensors="pt").to( + self.model.device + ) + generated_ids = self.model.generate( + **model_inputs, + max_new_tokens=max_tokens, + stop_strings="\n", + tokenizer=self.tokenizer, + streamer=self._Streamer(self, cb), + ) + full_response = self.tokenizer.batch_decode( + generated_ids, + skip_special_tokens=True, + )[0] + return full_response[len(prompt) :].strip() + + def answer( + self, + question: RetrievedQuestion, + max_tokens: int, + cb: Callable[[str], None] = lambda _s: None, + ) -> AnsweredQuestion: + return AnsweredQuestion( + question_id=question.question_id, + question=question.question, + retrieved_sources=question.retrieved_sources, + answer=self._answer(question, max_tokens, cb), + ) diff --git a/src/rag/chunking.py b/src/rag/chunking.py index 24e8fec..aabaf73 100644 --- a/src/rag/chunking.py +++ b/src/rag/chunking.py @@ -2,7 +2,7 @@ import logging from enum import Enum, auto from itertools import count -from rag.models import MinimalSource +from rag.models import Source class FileType(Enum): @@ -65,7 +65,7 @@ def chunk_by_depth( def chunk_file( path: str, max_chunk_size: int, by: FileType -) -> dict[MinimalSource, str]: +) -> dict[Source, str]: try: with open(path) as f: s = f.read() @@ -79,7 +79,7 @@ def chunk_file( res = {} for chunk in chunks: res[ - MinimalSource( + Source( first_character_index=total_len, last_character_index=total_len + len(chunk) - 1, file_path=path, diff --git a/src/rag/models.py b/src/rag/models.py index dada28d..cb67b17 100644 --- a/src/rag/models.py +++ b/src/rag/models.py @@ -3,7 +3,7 @@ import uuid from pydantic import BaseModel, Field -class MinimalSource(BaseModel, frozen=True): +class Source(BaseModel, frozen=True): file_path: str first_character_index: int last_character_index: int @@ -26,7 +26,7 @@ class RagDataset(BaseModel): class RetrievedQuestion(Question): - retrieved_sources: list[MinimalSource] + retrieved_sources: list[Source] class AnsweredQuestion(RetrievedQuestion): diff --git a/src/rag/retrieval.py b/src/rag/retrieval.py index 9240324..e62fb75 100644 --- a/src/rag/retrieval.py +++ b/src/rag/retrieval.py @@ -2,6 +2,8 @@ import math from collections.abc import Iterable from dataclasses import dataclass +import stopwordsiso + type Multiset[T] = dict[T, int] type BagOfWords = Multiset[str] @@ -27,8 +29,14 @@ def bag_of_words(s: str, stopwords: set[str]) -> BagOfWords: res[word] = res.get(word, 0) + 1 return res + def stopwords(lang: str | Iterable[str]) -> set[str]: - return {word for e in stopwords(lang) for word in words_normalize(e)} + return { + word + for e in stopwordsiso.stopwords(lang) + for word in words_normalize(e) + } + @dataclass class BM25[T]: diff --git a/uv.lock b/uv.lock index 46d2b45..6c12a84 100644 --- a/uv.lock +++ b/uv.lock @@ -5,17 +5,36 @@ resolution-markers = [ "python_full_version >= '3.15' and sys_platform == 'win32'", "python_full_version >= '3.15' and sys_platform == 'emscripten'", "python_full_version >= '3.15' and sys_platform != 'darwin' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version >= '3.15' and sys_platform == 'darwin'", "python_full_version == '3.14.*' and sys_platform == 'win32'", "python_full_version == '3.14.*' and sys_platform == 'emscripten'", "python_full_version == '3.14.*' and sys_platform != 'darwin' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version == '3.14.*' and sys_platform == 'darwin'", "python_full_version < '3.14' and sys_platform == 'win32'", "python_full_version < '3.14' and sys_platform == 'emscripten'", "python_full_version < '3.14' and sys_platform != 'darwin' and sys_platform != 'emscripten' and sys_platform != 'win32'", - "python_full_version >= '3.15' and sys_platform == 'darwin'", - "python_full_version == '3.14.*' and sys_platform == 'darwin'", "python_full_version < '3.14' and sys_platform == 'darwin'", ] +[[package]] +name = "accelerate" +version = "1.14.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "huggingface-hub" }, + { name = "numpy" }, + { name = "packaging" }, + { name = "psutil" }, + { name = "pyyaml" }, + { name = "safetensors" }, + { name = "torch", version = "2.13.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "python_full_version < '3.15' and sys_platform == 'darwin'" }, + { name = "torch", version = "2.13.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "python_full_version >= '3.15' or sys_platform != 'darwin'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/8d/75/94cd5d389649578aca399e5aa822637eec18319a1dadc400ffe2f9a7493f/accelerate-1.14.0.tar.gz", hash = "sha256:41b9c4377a54e0b460a959b0defa1b736e4ca0a2373252d9a539964c2afe3c8d", size = 412167, upload-time = "2026-06-11T13:45:52.326Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a8/db/253133d7e7cb40d3af384bb2f5c0b4a2b7fdcffbc95c688cc67a20a3c103/accelerate-1.14.0-py3-none-any.whl", hash = "sha256:e94390c2863b873be18f623f9df48a0d8fe5eff13ea7f1a00092b0a7904888c6", size = 389246, upload-time = "2026-06-11T13:45:50.477Z" }, +] + [[package]] name = "annotated-doc" version = "0.0.5" @@ -574,6 +593,34 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/f1/d9/7fb5aa316bc299258e68c73ba3bddbc499654a07f151cba08f6153988714/pathspec-1.1.1-py3-none-any.whl", hash = "sha256:a00ce642f577bf7f473932318056212bc4f8bfdf53128c78bbd5af0b9b20b189", size = 57328, upload-time = "2026-04-27T01:46:07.06Z" }, ] +[[package]] +name = "psutil" +version = "7.2.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/aa/c6/d1ddf4abb55e93cebc4f2ed8b5d6dbad109ecb8d63748dd2b20ab5e57ebe/psutil-7.2.2.tar.gz", hash = "sha256:0746f5f8d406af344fd547f1c8daa5f5c33dbc293bb8d6a16d80b4bb88f59372", size = 493740, upload-time = "2026-01-28T18:14:54.428Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/51/08/510cbdb69c25a96f4ae523f733cdc963ae654904e8db864c07585ef99875/psutil-7.2.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:2edccc433cbfa046b980b0df0171cd25bcaeb3a68fe9022db0979e7aa74a826b", size = 130595, upload-time = "2026-01-28T18:14:57.293Z" }, + { url = "https://files.pythonhosted.org/packages/d6/f5/97baea3fe7a5a9af7436301f85490905379b1c6f2dd51fe3ecf24b4c5fbf/psutil-7.2.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:e78c8603dcd9a04c7364f1a3e670cea95d51ee865e4efb3556a3a63adef958ea", size = 131082, upload-time = "2026-01-28T18:14:59.732Z" }, + { url = "https://files.pythonhosted.org/packages/37/d6/246513fbf9fa174af531f28412297dd05241d97a75911ac8febefa1a53c6/psutil-7.2.2-cp313-cp313t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1a571f2330c966c62aeda00dd24620425d4b0cc86881c89861fbc04549e5dc63", size = 181476, upload-time = "2026-01-28T18:15:01.884Z" }, + { url = "https://files.pythonhosted.org/packages/b8/b5/9182c9af3836cca61696dabe4fd1304e17bc56cb62f17439e1154f225dd3/psutil-7.2.2-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:917e891983ca3c1887b4ef36447b1e0873e70c933afc831c6b6da078ba474312", size = 184062, upload-time = "2026-01-28T18:15:04.436Z" }, + { url = "https://files.pythonhosted.org/packages/16/ba/0756dca669f5a9300d0cbcbfae9a4c30e446dfc7440ffe43ded5724bfd93/psutil-7.2.2-cp313-cp313t-win_amd64.whl", hash = "sha256:ab486563df44c17f5173621c7b198955bd6b613fb87c71c161f827d3fb149a9b", size = 139893, upload-time = "2026-01-28T18:15:06.378Z" }, + { url = "https://files.pythonhosted.org/packages/1c/61/8fa0e26f33623b49949346de05ec1ddaad02ed8ba64af45f40a147dbfa97/psutil-7.2.2-cp313-cp313t-win_arm64.whl", hash = "sha256:ae0aefdd8796a7737eccea863f80f81e468a1e4cf14d926bd9b6f5f2d5f90ca9", size = 135589, upload-time = "2026-01-28T18:15:08.03Z" }, + { url = "https://files.pythonhosted.org/packages/81/69/ef179ab5ca24f32acc1dac0c247fd6a13b501fd5534dbae0e05a1c48b66d/psutil-7.2.2-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:eed63d3b4d62449571547b60578c5b2c4bcccc5387148db46e0c2313dad0ee00", size = 130664, upload-time = "2026-01-28T18:15:09.469Z" }, + { url = "https://files.pythonhosted.org/packages/7b/64/665248b557a236d3fa9efc378d60d95ef56dd0a490c2cd37dafc7660d4a9/psutil-7.2.2-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:7b6d09433a10592ce39b13d7be5a54fbac1d1228ed29abc880fb23df7cb694c9", size = 131087, upload-time = "2026-01-28T18:15:11.724Z" }, + { url = "https://files.pythonhosted.org/packages/d5/2e/e6782744700d6759ebce3043dcfa661fb61e2fb752b91cdeae9af12c2178/psutil-7.2.2-cp314-cp314t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1fa4ecf83bcdf6e6c8f4449aff98eefb5d0604bf88cb883d7da3d8d2d909546a", size = 182383, upload-time = "2026-01-28T18:15:13.445Z" }, + { url = "https://files.pythonhosted.org/packages/57/49/0a41cefd10cb7505cdc04dab3eacf24c0c2cb158a998b8c7b1d27ee2c1f5/psutil-7.2.2-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e452c464a02e7dc7822a05d25db4cde564444a67e58539a00f929c51eddda0cf", size = 185210, upload-time = "2026-01-28T18:15:16.002Z" }, + { url = "https://files.pythonhosted.org/packages/dd/2c/ff9bfb544f283ba5f83ba725a3c5fec6d6b10b8f27ac1dc641c473dc390d/psutil-7.2.2-cp314-cp314t-win_amd64.whl", hash = "sha256:c7663d4e37f13e884d13994247449e9f8f574bc4655d509c3b95e9ec9e2b9dc1", size = 141228, upload-time = "2026-01-28T18:15:18.385Z" }, + { url = "https://files.pythonhosted.org/packages/f2/fc/f8d9c31db14fcec13748d373e668bc3bed94d9077dbc17fb0eebc073233c/psutil-7.2.2-cp314-cp314t-win_arm64.whl", hash = "sha256:11fe5a4f613759764e79c65cf11ebdf26e33d6dd34336f8a337aa2996d71c841", size = 136284, upload-time = "2026-01-28T18:15:19.912Z" }, + { url = "https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ed0cace939114f62738d808fdcecd4c869222507e266e574799e9c0faa17d486", size = 129090, upload-time = "2026-01-28T18:15:22.168Z" }, + { url = "https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:1a7b04c10f32cc88ab39cbf606e117fd74721c831c98a27dc04578deb0c16979", size = 129859, upload-time = "2026-01-28T18:15:23.795Z" }, + { url = "https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9", size = 155560, upload-time = "2026-01-28T18:15:25.976Z" }, + { url = "https://files.pythonhosted.org/packages/63/65/37648c0c158dc222aba51c089eb3bdfa238e621674dc42d48706e639204f/psutil-7.2.2-cp36-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b0726cecd84f9474419d67252add4ac0cd9811b04d61123054b9fb6f57df6e9e", size = 156997, upload-time = "2026-01-28T18:15:27.794Z" }, + { url = "https://files.pythonhosted.org/packages/8e/13/125093eadae863ce03c6ffdbae9929430d116a246ef69866dad94da3bfbc/psutil-7.2.2-cp36-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:fd04ef36b4a6d599bbdb225dd1d3f51e00105f6d48a28f006da7f9822f2606d8", size = 148972, upload-time = "2026-01-28T18:15:29.342Z" }, + { url = "https://files.pythonhosted.org/packages/04/78/0acd37ca84ce3ddffaa92ef0f571e073faa6d8ff1f0559ab1272188ea2be/psutil-7.2.2-cp36-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:b58fabe35e80b264a4e3bb23e6b96f9e45a3df7fb7eed419ac0e5947c61e47cc", size = 148266, upload-time = "2026-01-28T18:15:31.597Z" }, + { url = "https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl", hash = "sha256:eb7e81434c8d223ec4a219b5fc1c47d0417b12be7ea866e24fb5ad6e84b3d988", size = 137737, upload-time = "2026-01-28T18:15:33.849Z" }, + { url = "https://files.pythonhosted.org/packages/8c/c7/7bb2e321574b10df20cbde462a94e2b71d05f9bbda251ef27d104668306a/psutil-7.2.2-cp37-abi3-win_arm64.whl", hash = "sha256:8c233660f575a5a89e6d4cb65d9f938126312bca76d8fe087b947b3a1aaac9ee", size = 134617, upload-time = "2026-01-28T18:15:36.514Z" }, +] + [[package]] name = "pycodestyle" version = "2.14.0" @@ -713,6 +760,7 @@ name = "rag" version = "0.1.0" source = { editable = "." } dependencies = [ + { name = "accelerate" }, { name = "fire" }, { name = "pydantic" }, { name = "stopwordsiso" }, @@ -732,6 +780,7 @@ dev = [ [package.metadata] requires-dist = [ + { name = "accelerate", specifier = ">=1.14.0" }, { name = "fire", specifier = ">=0.7.1" }, { name = "pydantic", specifier = ">=2.13.4" }, { name = "stopwordsiso", specifier = ">=0.7.1" }, @@ -987,13 +1036,13 @@ resolution-markers = [ "python_full_version >= '3.15' and sys_platform == 'win32'", "python_full_version >= '3.15' and sys_platform == 'emscripten'", "python_full_version >= '3.15' and sys_platform != 'darwin' and sys_platform != 'emscripten' and sys_platform != 'win32'", + "python_full_version >= '3.15' and sys_platform == 'darwin'", "python_full_version == '3.14.*' and sys_platform == 'win32'", "python_full_version == '3.14.*' and sys_platform == 'emscripten'", "python_full_version == '3.14.*' and sys_platform != 'darwin' and sys_platform != 'emscripten' and sys_platform != 'win32'", "python_full_version < '3.14' and sys_platform == 'win32'", "python_full_version < '3.14' and sys_platform == 'emscripten'", "python_full_version < '3.14' and sys_platform != 'darwin' and sys_platform != 'emscripten' and sys_platform != 'win32'", - "python_full_version >= '3.15' and sys_platform == 'darwin'", ] dependencies = [ { name = "filelock" }, -- 2.53.0