chore: import upstream snapshot with attribution

deeptutor/book/blocks/code.py

@@ -0,0 +1,68 @@
+"""Code block – generates a runnable code snippet plus brief explanation.
+
+Phase 2 implementation. Uses the unified LLM service with a strict JSON
+response. The frontend ``CodeBlock`` component renders the code and the
+explanation side-by-side; the playground "code_execution" tool can be
+hooked in later for live runs.
+
+Prompts live in ``deeptutor/book/prompts/{en,zh}/code.yaml``.
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+from ..models import BlockType, SourceAnchor
+from ._llm_writer import llm_json
+from ._prompts import get_book_prompt, load_book_prompts
+from .base import BlockContext, BlockGenerator, GenerationFailure
+
+
+class CodeGenerator(BlockGenerator):
+    block_type = BlockType.CODE
+
+    async def _generate(
+        self, ctx: BlockContext
+    ) -> tuple[dict[str, Any], list[SourceAnchor], dict[str, Any]]:
+        params = ctx.block.params
+        chapter_title = params.get("chapter_title", ctx.chapter.title)
+        chapter_summary = params.get("chapter_summary", ctx.chapter.summary)
+        objectives = params.get("objectives") or ctx.chapter.learning_objectives
+        language = str(params.get("language") or "python")
+        intent = str(params.get("intent") or "demonstrate")
+
+        prompts = load_book_prompts("code", ctx.language)
+        none_label = "(无)" if ctx.language == "zh" else "(none)"
+        user_prompt = get_book_prompt(prompts, "user_template").format(
+            chapter_title=chapter_title,
+            chapter_summary=chapter_summary or none_label,
+            objectives_inline="; ".join(objectives) or none_label,
+            intent=intent,
+            language=language,
+        )
+        data = await llm_json(
+            user_prompt=user_prompt,
+            system_prompt=get_book_prompt(prompts, "system"),
+            max_tokens=900,
+            temperature=0.3,
+            language=ctx.language,
+        )
+
+        code = str(data.get("code") or "").strip()
+        if not code:
+            raise GenerationFailure("LLM did not return any code.")
+        if "<think" in code.lower() or "</think" in code.lower():
+            raise GenerationFailure("prompt leak detected in generated code.")
+        return (
+            {
+                "language": str(data.get("language") or language).strip() or language,
+                "code": code,
+                "explanation": str(data.get("explanation") or "").strip(),
+                "intent": intent,
+            },
+            [],
+            data.get("_metadata") if isinstance(data.get("_metadata"), dict) else {},
+        )
+
+
+__all__ = ["CodeGenerator"]