feat: configurable SubQuestions via Step 1.2 system prompt page
- Split 'Step 1: Query Decomposition' into Step 1.1 (prompt template) and Step 1.2 (format config with description + max_length) - Add create_subquestions_model() and parse_decompose_format() to decompose.py - QueryDecomposer reads decompose_format from DB, creates dynamic Pydantic model at runtime - PromptEditor renders Step 1.2 as textarea (description) + number input (max_length 1-5) - Graceful fallback to static SubQuestions when decompose_format unavailable
This commit is contained in:
Woody
parent
40b338d3ca
commit
76c3bec2ab
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@ -11,12 +11,18 @@ logger = logging.getLogger(__name__)
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_SEED_DECOMPOSE = (
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"Given this question: '{question}'\n\n"
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"Break it down into 2-5 simplified sub-questions that would help "
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"Break it down into 1-3 simplified sub-questions that would help "
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"search for relevant information. Each sub-question should be short "
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"and focused on one aspect.\n\n"
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'Return a JSON array of strings: ["sub-question 1", "sub-question 2", ...]'
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)
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_SEED_DECOMPOSE_FORMAT = (
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'{"description": "請將問題/任務拆解成 1-3 個簡化子問題，標籤式主題必須清楚、簡潔、具體，'
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'一看就明白（建議 3-8 個字），若涉及地點、地區、人物、時間、金額/財政 等關鍵資訊，必須包含在標籤中 。'
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'具體提問/要求要精準、完整 並全部轉換成以下固定格式：\\n「標籤式主題：具體提問/要求」", "max_length": 3}'
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)
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_SEED_FILTER = (
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"Given question '{question}' and these document chunks, rate each 0-10 for relevance. "
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"Return JSON array of scores.\n{chunks}\n"
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@ -68,6 +74,7 @@ _SEED_PROFILES = [
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_SEED_STEPS = [
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"decompose",
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"decompose_format",
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"filter",
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"generate",
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"generate_per_subq",
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@ -77,6 +84,7 @@ _SEED_STEPS = [
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]
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_SEED_TEMPLATES = {
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"decompose": _SEED_DECOMPOSE,
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"decompose_format": _SEED_DECOMPOSE_FORMAT,
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"filter": _SEED_FILTER,
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"generate": _SEED_GENERATE,
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"generate_per_subq": _SEED_GENERATE_PER_SUBQ,
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@ -1,11 +1,14 @@
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from pydantic import BaseModel, Field
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from typing import Any
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from pydantic import BaseModel, Field, create_model
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class SubQuestions(BaseModel):
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"""Structured output model for query decomposition.
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"""Structured output model for query decomposition — static fallback.
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Used with LangChain's with_structured_output() to guarantee
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the LLM returns a valid list of sub-questions.
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When ``decompose_format`` is available from PromptService, a dynamic
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model with DB-configured description and max_length is used instead.
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See ``create_subquestions_model()``.
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"""
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questions: list[str] = Field(
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@ -13,3 +16,54 @@ class SubQuestions(BaseModel):
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min_length=1,
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max_length=3,
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)
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def create_subquestions_model(description: str, max_length: int) -> type[BaseModel]:
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"""Create a dynamic SubQuestions model with configurable field constraints.
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Args:
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description: Field description text injected into the JSON format
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instruction sent to the LLM.
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max_length: Maximum number of sub-questions (1-5).
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Returns:
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A Pydantic BaseModel subclass with the configured constraints.
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"""
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return create_model(
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"SubQuestions",
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questions=(
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list[str],
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Field(
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description=description,
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min_length=1,
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max_length=max_length,
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),
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),
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)
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def parse_decompose_format(raw: str) -> dict[str, Any]:
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"""Parse the decompose_format JSON string into a validated config dict.
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Returns a dict with ``description`` (str) and ``max_length`` (int).
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Raises ``ValueError`` if the JSON is invalid or fields are missing/malformed.
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"""
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import json
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try:
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config = json.loads(raw)
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except json.JSONDecodeError as exc:
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raise ValueError(f"decompose_format is not valid JSON: {exc}") from exc
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if not isinstance(config, dict):
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raise ValueError("decompose_format must be a JSON object")
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description = config.get("description")
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if not isinstance(description, str) or not description.strip():
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raise ValueError("decompose_format.description must be a non-empty string")
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max_length = config.get("max_length")
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if not isinstance(max_length, int) or max_length < 1 or max_length > 5:
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raise ValueError("decompose_format.max_length must be an integer between 1 and 5")
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return {"description": description.strip(), "max_length": max_length}
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@ -25,6 +25,7 @@ router = APIRouter(prefix="/api/v1/prompts", tags=["prompts"])
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_VALID_NAMES = {"A", "B", "C"}
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_VALID_STEPS = {
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"decompose",
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"decompose_format",
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"filter",
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"generate",
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"generate_per_subq",
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@ -14,6 +14,7 @@ logger = logging.getLogger(__name__)
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_VALID_NAMES = {"A", "B", "C"}
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_VALID_STEPS = {
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"decompose",
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"decompose_format",
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"filter",
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"generate",
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"generate_per_subq",
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@ -24,11 +24,21 @@ logger = logging.getLogger(__name__)
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# Fallback template used when prompt_service is not provided (tests, standalone).
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_BUILTIN_DECOMPOSE_TEMPLATE = (
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"Given this question: '{question}'\n\n"
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"Break it down into 2-5 simplified sub-questions that would help "
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"Break it down into 1-3 simplified sub-questions that would help "
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"search for relevant information. Each sub-question should be short "
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"and focused on one aspect. Return as a JSON array of strings."
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)
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_DEFAULT_DECOMPOSE_FORMAT = {
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"description": (
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"請將問題/任務拆解成 1-3 個簡化子問題，標籤式主題必須清楚、簡潔、具體，"
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"一看就明白（建議 3-8 個字），若涉及地點、地區、人物、時間、金額/財政 等關鍵資訊，"
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"必須包含在標籤中 。具體提問/要求要精準、完整 並全部轉換成以下固定格式：\n"
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"「標籤式主題：具體提問/要求」"
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),
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"max_length": 3,
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}
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def _extract_json_from_markdown(response: str) -> str:
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if not isinstance(response, str):
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@ -98,12 +108,32 @@ class QueryDecomposer:
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prompt = template.replace("{question}", question)
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from app.models.decompose import SubQuestions
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from app.models.decompose import SubQuestions, create_subquestions_model, parse_decompose_format
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pydantic_model = SubQuestions
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if self._prompt_service is not None:
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try:
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format_raw = self._prompt_service.get_prompt_template("decompose_format")
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format_config = parse_decompose_format(format_raw)
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pydantic_model = create_subquestions_model(
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description=format_config["description"],
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max_length=format_config["max_length"],
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)
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logger.info(
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"Decompose format loaded from DB: max_length=%d",
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format_config["max_length"],
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)
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except Exception as exc:
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logger.warning(
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"Failed to load decompose_format from DB: %s. Falling back to static SubQuestions.",
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exc,
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)
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try:
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result = await self.llm_client.complete_structured(
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prompt=prompt,
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pydantic_model=SubQuestions,
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pydantic_model=pydantic_model,
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step_name="QueryDecomposer",
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)
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return result.questions, prompt
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@ -14,7 +14,8 @@ export interface PromptEditorProps {
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}
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const STEPS = [
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{ key: 'decompose', label: 'Step 1: Query Decomposition', placeholders: ['question'] },
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{ key: 'decompose', label: 'Step 1.1: Query Decomposition', placeholders: ['question'] },
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{ key: 'decompose_format', label: 'Step 1.2: Query Decomposition Format', placeholders: [], type: 'format_config' },
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{ key: 'filter_intro', label: 'Step 2.1: Filter Intro (Preamble)', placeholders: [] },
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{ key: 'filter_section', label: 'Step 2.2: Filter Section (Per Sub-Q)', placeholders: ['subq_idx', 'subq_question', 'chunks'] },
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{ key: 'filter_outro', label: 'Step 2.3: Filter Outro (Format)', placeholders: [] },
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@ -23,6 +24,7 @@ const STEPS = [
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const VALID_PLACEHOLDERS: Record<string, string[]> = {
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decompose: ['{question}'],
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decompose_format: [],
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filter: ['{question}', '{chunks}'],
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generate: ['{question}', '{context}'],
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generate_per_subq: ['{context_sections}'],
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@ -37,6 +39,68 @@ const findUnknownPlaceholders = (template: string, stepKey: string): string[] =>
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return found.filter((p) => !valid.includes(p))
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}
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const DEFAULT_FORMAT_CONFIG = { description: '', max_length: 3 }
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function parseFormatConfig(raw: string): { description: string; max_length: number } {
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try {
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const parsed = JSON.parse(raw)
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return {
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description: typeof parsed.description === 'string' ? parsed.description : '',
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max_length: typeof parsed.max_length === 'number' ? parsed.max_length : 3,
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}
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} catch {
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return { ...DEFAULT_FORMAT_CONFIG }
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}
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}
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function serializeFormatConfig(description: string, max_length: number): string {
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return JSON.stringify({ description, max_length })
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}
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interface FormatConfigFieldsProps {
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value: string
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disabled: boolean
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onChange: (description: string, max_length: number) => void
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}
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const FormatConfigFields: React.FC<FormatConfigFieldsProps> = ({ value, disabled, onChange }) => {
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const config = parseFormatConfig(value)
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return (
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<div className="space-y-3 pl-1">
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<div className="space-y-1">
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<label className="text-xs font-medium text-gray-600">Description (field description for sub-question format)</label>
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<textarea
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value={config.description}
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onChange={(e) => onChange(e.target.value, config.max_length)}
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disabled={disabled}
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rows={5}
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className="w-full rounded border border-gray-300 px-3 py-2 font-mono text-sm focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent disabled:bg-gray-100 disabled:cursor-not-allowed resize-y"
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/>
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<span className="text-xs text-gray-500">{config.description.length} characters</span>
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</div>
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<div className="space-y-1">
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<label className="text-xs font-medium text-gray-600">Max Sub-Questions (1–5)</label>
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<input
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type="number"
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min={1}
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max={5}
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value={config.max_length}
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onChange={(e) => {
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const v = parseInt(e.target.value, 10)
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if (!isNaN(v) && v >= 1 && v <= 5) {
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onChange(config.description, v)
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}
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}}
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disabled={disabled}
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className="w-24 rounded border border-gray-300 px-3 py-1.5 text-sm focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent disabled:bg-gray-100 disabled:cursor-not-allowed"
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/>
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</div>
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</div>
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)
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}
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export const PromptEditor: React.FC<PromptEditorProps> = ({
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profileName,
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prompts,
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@ -80,7 +144,9 @@ export const PromptEditor: React.FC<PromptEditorProps> = ({
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{STEPS.map((step) => {
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const value = localPrompts[step.key] ?? ''
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const unknownPlaceholders = findUnknownPlaceholders(value, step.key)
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const unknownPlaceholders = step.type === 'format_config'
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? []
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: findUnknownPlaceholders(value, step.key)
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const placeholderBadges = step.placeholders.map((p) => `{${p}}`).join(', ')
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return (
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@ -99,6 +165,14 @@ export const PromptEditor: React.FC<PromptEditorProps> = ({
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</div>
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</div>
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{step.type === 'format_config' ? (
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<FormatConfigFields
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value={value}
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disabled={isSaving}
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onChange={(desc, ml) => handleChange(step.key, serializeFormatConfig(desc, ml))}
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/>
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) : (
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<>
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<div className="flex items-center gap-2 flex-wrap">
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<span className="text-xs text-gray-500">Placeholders:</span>
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{step.placeholders.map((p) => (
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@ -132,6 +206,8 @@ export const PromptEditor: React.FC<PromptEditorProps> = ({
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</div>
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)}
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</div>
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</>
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)}
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</div>
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)
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})}
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@ -4,6 +4,7 @@ import { PromptEditor } from '../../components/PromptEditor'
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const mockPrompts: Record<string, string> = {
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decompose: 'Decompose template with {question}',
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decompose_format: '{"description": "test description", "max_length": 3}',
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filter_intro: 'Evaluate each chunk for relevance',
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filter_section: 'Sub-question {subq_idx}: "{subq_question}"\n{chunks}',
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filter_outro: 'Return JSON object mapping sub-question indices to scores.',
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@ -31,15 +32,16 @@ describe('PromptEditor', () => {
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defaultProps.onCancel.mockClear()
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})
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it('renders 5 textareas for the active steps', () => {
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it('renders 6 textareas for the active steps (5 regular + 1 format description)', () => {
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render(<PromptEditor {...defaultProps} />)
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const textareas = screen.getAllByRole('textbox')
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expect(textareas).toHaveLength(5)
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expect(textareas).toHaveLength(6)
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})
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it('renders labels for each step', () => {
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render(<PromptEditor {...defaultProps} />)
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expect(screen.getByText('Step 1: Query Decomposition')).toBeInTheDocument()
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expect(screen.getByText('Step 1.1: Query Decomposition')).toBeInTheDocument()
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expect(screen.getByText('Step 1.2: Query Decomposition Format')).toBeInTheDocument()
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expect(screen.getByText('Step 2.1: Filter Intro (Preamble)')).toBeInTheDocument()
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expect(screen.getByText('Step 2.2: Filter Section (Per Sub-Q)')).toBeInTheDocument()
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expect(screen.getByText('Step 2.3: Filter Outro (Format)')).toBeInTheDocument()
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@ -66,18 +68,21 @@ describe('PromptEditor', () => {
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render(<PromptEditor {...defaultProps} />)
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const resetButtons = screen.getAllByTitle(/reset.*to default/i)
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expect(resetButtons).toHaveLength(5)
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expect(resetButtons).toHaveLength(6)
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fireEvent.click(resetButtons[0])
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expect(defaultProps.onResetStep).toHaveBeenCalledWith('decompose')
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fireEvent.click(resetButtons[1])
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expect(defaultProps.onResetStep).toHaveBeenCalledWith('decompose_format')
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fireEvent.click(resetButtons[2])
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expect(defaultProps.onResetStep).toHaveBeenCalledWith('filter_intro')
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fireEvent.click(resetButtons[3])
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fireEvent.click(resetButtons[4])
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expect(defaultProps.onResetStep).toHaveBeenCalledWith('filter_outro')
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fireEvent.click(resetButtons[4])
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fireEvent.click(resetButtons[5])
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expect(defaultProps.onResetStep).toHaveBeenCalledWith('generate_per_subq')
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confirmSpy.mockRestore()
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@ -143,10 +148,11 @@ describe('PromptEditor', () => {
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const textareas = screen.getAllByRole('textbox')
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expect(textareas[0]).toHaveValue('Decompose template with {question}')
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expect(textareas[1]).toHaveValue('Evaluate each chunk for relevance')
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expect(textareas[2]).toHaveValue('Sub-question {subq_idx}: "{subq_question}"\n{chunks}')
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expect(textareas[3]).toHaveValue('Return JSON object mapping sub-question indices to scores.')
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expect(textareas[4]).toHaveValue('Generate per-subq with {context_sections}')
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expect(textareas[1]).toHaveValue('test description')
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expect(textareas[2]).toHaveValue('Evaluate each chunk for relevance')
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expect(textareas[3]).toHaveValue('Sub-question {subq_idx}: "{subq_question}"\n{chunks}')
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expect(textareas[4]).toHaveValue('Return JSON object mapping sub-question indices to scores.')
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expect(textareas[5]).toHaveValue('Generate per-subq with {context_sections}')
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})
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it('calls onUpdate when typing in a textarea', () => {
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