File size: 2,245 Bytes
3962d8b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | class TaskClassifier:
NON_PYTHON_LANGUAGES = [
"java", "javascript", "typescript", "c++", "c#", "csharp", "rust",
"go", "golang", "ruby", "php", "swift", "kotlin", "scala", "matlab",
"haskell", "dart", "elixir", "clojure", "perl", "bash", "shell",
"sql", "html", "css", "lua", "r language", "r programming",
]
FRAMEWORKS = [
"react", "vue", "angular", "node", "express", "spring", "django",
"flask", "fastapi", "laravel", "rails", "asp.net", "tensorflow",
"pytorch", "keras", "scikit-learn", "pandas", "numpy", "jquery",
"bootstrap", "tailwind", "next.js", "nuxt", "svelte",
]
ANALYZE_KEYWORDS = [
"compare", "comparison", "versus", " vs ", "difference", "rate",
"rating", "difficulty", "multiple language", "all language",
"which is better", "pros and cons", "contrast",
]
LANGUAGE_LABEL_MAP = {
"c++": "C++",
"c#": "C#",
"csharp": "C#",
"golang": "Go",
"r language": "R",
"r programming": "R",
}
def classify(self, task: str) -> dict:
task_lower = task.lower()
languages = []
if "python" in task_lower:
languages.append("Python")
for lang in self.NON_PYTHON_LANGUAGES:
if lang in task_lower:
label = self.LANGUAGE_LABEL_MAP.get(lang, lang.title())
if label not in languages:
languages.append(label)
for fw in self.FRAMEWORKS:
if fw in task_lower:
label = fw.title() + " (framework)"
if label not in languages:
languages.append(label)
non_python = [l for l in languages if "Python" not in l and "framework" not in l]
has_analyze_keyword = any(kw in task_lower for kw in self.ANALYZE_KEYWORDS)
is_multi_language = len([l for l in languages if "framework" not in l]) > 1
needs_analyze = bool(non_python) or has_analyze_keyword or is_multi_language
return {
"mode": "analyze" if needs_analyze else "execute",
"languages": languages if languages else ["Python"],
"needs_execution": not needs_analyze,
}
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