File size: 2,330 Bytes
eca5751 | 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 61 62 63 64 | """Code Generation Skill - Sinh code từ mô tả."""
from __future__ import annotations
from typing import List
from .base import Skill, SkillResult, SkillContext, SkillCategory, SkillPriority
class CodeGenerationSkill(Skill):
"""Sinh code Python/JS/Go/Rust/SQL từ mô tả tự nhiên."""
category = SkillCategory.CODE
priority = SkillPriority.HIGH
keywords: List[str] = [
"viết", "write", "code", "function", "hàm", "class", "lớp",
"implement", "tạo", "generate", "sinh", "snippet",
]
examples = [
"Viết hàm Python tính fibonacci",
"Write a function to reverse a linked list",
"Implement a binary search tree in Python",
]
@property
def name(self) -> str:
return "code_generation"
@property
def description(self) -> str:
return "Sinh code từ mô tả tự nhiên. Hỗ trợ Python, JavaScript, Go, Rust, SQL, C++, Java."
def can_handle(self, prompt: str, context: SkillContext = None) -> float:
prompt_lower = prompt.lower()
score = 0.0
for kw in self.keywords:
if kw in prompt_lower:
score += 0.2
if context and context.language:
score += 0.3
if "```" in prompt or "def " in prompt or "function " in prompt:
score += 0.3
return min(1.0, score)
def execute(self, context: SkillContext) -> SkillResult:
lang = context.language or "python"
system_prompt = (
f"You are Nexus Coder, an expert {lang} developer. "
f"Generate clean, production-ready code with proper error handling, "
f"type hints, and docstrings. Follow PEP-8 / best practices."
)
return SkillResult(
success=True,
output=f"[CodeGeneration/{lang}] Ready to generate code for: {context.prompt[:200]}",
metadata={
"skill": self.name,
"language": lang,
"system_prompt": system_prompt,
"max_tokens": context.max_tokens,
},
suggestions=[
f"Specify {lang} version if needed",
"Provide test cases for edge conditions",
"Consider error handling strategy",
],
)
|