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101 lines
3.7 KiB
Python
101 lines
3.7 KiB
Python
"""Interactive block – self-contained interactive HTML widget.
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Wraps :class:`deeptutor.agents.visualize.pipeline.VisualizePipeline` with
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``render_mode="html"``. The payload carries an HTML document the frontend
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renders in an isolated iframe.
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The draft is checked by the deterministic local ``validate_visualization``.
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HTML has no repair pass (full single-file documents are too large for a
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useful targeted fix), so an unrenderable document raises
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``GenerationFailure`` and lets the book engine retry — better than baking a
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placeholder page into the book.
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"""
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from __future__ import annotations
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import logging
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from typing import Any
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from ..models import BlockType, SourceAnchor
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from .base import BlockContext, BlockGenerator, GenerationFailure
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logger = logging.getLogger(__name__)
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class InteractiveGenerator(BlockGenerator):
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block_type = BlockType.INTERACTIVE
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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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focus = str(params.get("focus") or "")
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interaction = str(params.get("interaction") or "interactive")
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history_lines: list[str] = []
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if chapter_summary:
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history_lines.append(f"Chapter summary: {chapter_summary}")
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if objectives:
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history_lines.append("Learning objectives:")
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for obj in objectives:
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history_lines.append(f"- {obj}")
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history_context = "\n".join(history_lines)
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focus_clause = f" focusing on {focus}" if focus else ""
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user_input = (
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f"Build an {interaction} HTML page for the chapter "
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f'"{chapter_title}"{focus_clause}. The page should let the learner '
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"manipulate state, drag/click controls, or step through a guided "
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"demo to internalise the concept."
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)
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try:
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from deeptutor.agents.visualize.pipeline import VisualizePipeline
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from deeptutor.agents.visualize.utils import validate_visualization
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from deeptutor.services.llm.config import get_llm_config
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llm_config = get_llm_config()
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pipeline = VisualizePipeline(
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api_key=llm_config.api_key,
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base_url=llm_config.base_url,
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api_version=llm_config.api_version,
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language=ctx.language,
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)
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analysis = await pipeline.run_analysis(
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user_input=user_input,
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history_context=history_context,
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render_mode="html",
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)
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code = await pipeline.run_code_generation(
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user_input=user_input,
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history_context=history_context,
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analysis=analysis,
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)
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except Exception as exc:
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logger.warning(f"InteractiveGenerator failed: {exc}", exc_info=True)
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raise GenerationFailure(f"interactive generation failed: {exc}") from exc
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ok, validation_error = validate_visualization(code, "html")
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if not ok:
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raise GenerationFailure(f"interactive html failed validation: {validation_error}")
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return (
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{
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"render_type": "html",
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"code": {"language": "html", "content": code},
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"description": analysis.description,
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"chart_type": analysis.chart_type,
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},
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[],
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{
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"review_changed": False,
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"review_notes": "Passed local validation.",
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},
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)
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__all__ = ["InteractiveGenerator"]
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