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69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
"""Code block – generates a runnable code snippet plus brief explanation.
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Phase 2 implementation. Uses the unified LLM service with a strict JSON
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response. The frontend ``CodeBlock`` component renders the code and the
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explanation side-by-side; the playground "code_execution" tool can be
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hooked in later for live runs.
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Prompts live in ``deeptutor/book/prompts/{en,zh}/code.yaml``.
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"""
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from __future__ import annotations
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from typing import Any
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from ..models import BlockType, SourceAnchor
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from ._llm_writer import llm_json
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from ._prompts import get_book_prompt, load_book_prompts
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from .base import BlockContext, BlockGenerator, GenerationFailure
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class CodeGenerator(BlockGenerator):
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block_type = BlockType.CODE
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async def _generate(
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self, ctx: BlockContext
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) -> tuple[dict[str, Any], list[SourceAnchor], dict[str, Any]]:
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params = ctx.block.params
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chapter_title = params.get("chapter_title", ctx.chapter.title)
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chapter_summary = params.get("chapter_summary", ctx.chapter.summary)
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objectives = params.get("objectives") or ctx.chapter.learning_objectives
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language = str(params.get("language") or "python")
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intent = str(params.get("intent") or "demonstrate")
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prompts = load_book_prompts("code", ctx.language)
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none_label = "(无)" if ctx.language == "zh" else "(none)"
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user_prompt = get_book_prompt(prompts, "user_template").format(
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chapter_title=chapter_title,
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chapter_summary=chapter_summary or none_label,
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objectives_inline="; ".join(objectives) or none_label,
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intent=intent,
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language=language,
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)
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data = await llm_json(
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user_prompt=user_prompt,
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system_prompt=get_book_prompt(prompts, "system"),
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max_tokens=900,
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temperature=0.3,
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language=ctx.language,
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)
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code = str(data.get("code") or "").strip()
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if not code:
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raise GenerationFailure("LLM did not return any code.")
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if "<think" in code.lower() or "</think" in code.lower():
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raise GenerationFailure("prompt leak detected in generated code.")
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return (
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{
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"language": str(data.get("language") or language).strip() or language,
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"code": code,
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"explanation": str(data.get("explanation") or "").strip(),
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"intent": intent,
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},
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[],
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data.get("_metadata") if isinstance(data.get("_metadata"), dict) else {},
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)
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__all__ = ["CodeGenerator"]
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