ElebobaandClaude Opus 5.5
9ec61b9a03
CI / ruff · pytest (pull_request) Successful in 2m5s
Live-tested on OpenRouter: Flash-Lite answers in 3–8 s with correct findings at ~$0.10/$0.40 per 1M tokens (qwen3.7-flash and gpt-oss-120b took 26–32 s). Force a tool call on the first turn, give the model the current prescription, let check_drug_for_patient default to it and return composition, intolerance check and general interactions (alcohol); retry once on an empty final message. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
201 lines
9.2 KiB
Python
201 lines
9.2 KiB
Python
"""Read-only tools of the chat agent. Every tool is bound to the current patient's token on the server side:
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the model never passes a token, so it cannot read another patient's data (medical secrecy, 323-FZ art. 13).
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Tool results contain clinical data only (no name, SNILS, phone) — they are sent to the LLM provider.
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"""
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import json
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import logging
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import re
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from dataclasses import dataclass, field
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from typing import Any
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from app.integrations.emias_record import PatientRecord, emias_records
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from app.llm.agent.drug_safety import check_patient, find_drug, load_db
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from app.llm.rag import retrieve
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from app.llm.rag.index import sentences
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log = logging.getLogger(__name__)
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RAG_TOP_K = 4
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PASSAGE_CHARS = 700
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# Patients never get dosages (SPEC §7): sentences with doses are dropped before the text reaches the LLM.
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_DOSE = re.compile(r"\d\s*(?:-|–)?\s*\d*\s*(?:мг|mg|мкг|г/сут|таблетк)|\bдоз(?:а|у|ы|е|ой|ировк)", re.I)
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TOOL_SPECS: list[dict[str, Any]] = [
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{
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"type": "function",
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"function": {
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"name": "search_guidelines",
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"description": (
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"Поиск по базе знаний: клинические рекомендации Минздрава РФ (депрессия 2024, ПТСР 2023). "
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"Возвращает фрагменты с источником и страницей. Используй для любых общих вопросов о состоянии, "
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"лечении, сроках действия терапии, побочных эффектах, отмене, образе жизни."
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),
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"parameters": {
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"type": "object",
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"properties": {"query": {"type": "string", "description": "Поисковый запрос на русском"}},
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"required": ["query"],
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},
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},
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},
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{
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"type": "function",
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"function": {
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"name": "get_patient_record",
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"description": (
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"Медицинская карта текущего пациента из ЕМИАС: диагнозы (МКБ-10), сопутствующие заболевания, "
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"аллергии и непереносимости, назначения других врачей и текущее назначение психиатра. "
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"Вызывай, когда ответ зависит от особенностей пациента или его лекарств."
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),
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"parameters": {"type": "object", "properties": {}},
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},
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},
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{
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"type": "function",
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"function": {
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"name": "get_drug_info",
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"description": (
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"Справка о препарате по инструкции ГРЛС: состав (действующее и вспомогательные вещества), "
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"противопоказания, взаимодействия, беременность. Аргумент — название препарата (МНН или торговое)."
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),
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"parameters": {
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"type": "object",
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"properties": {"drug": {"type": "string"}},
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"required": ["drug"],
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},
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},
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},
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{
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"type": "function",
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"function": {
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"name": "check_drug_for_patient",
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"description": (
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"Детерминированная проверка препарата для текущего пациента: сопутствующие заболевания, "
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"непереносимости по составу, взаимодействия с другими его лекарствами. Используй перед любым "
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"ответом о том, подходит ли пациенту препарат или сочетание препаратов."
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),
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"parameters": {
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"type": "object",
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"properties": {
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"drug": {"type": "string", "description": "Название препарата; пусто — текущее назначение пациента"}
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},
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},
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},
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},
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]
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@dataclass
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class ToolContext:
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token: str
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sources: list[str] = field(default_factory=list) # citations collected for the answer footer
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used: list[str] = field(default_factory=list)
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_record: PatientRecord | None = None
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_record_loaded: bool = False
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async def record(self) -> PatientRecord | None:
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if not self._record_loaded:
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self._record = await emias_records.get(self.token)
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self._record_loaded = True
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return self._record
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def cite(self, label: str) -> None:
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if label and label not in self.sources:
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self.sources.append(label)
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async def run_tool(ctx: ToolContext, name: str, args: dict[str, Any]) -> str:
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"""Execute a tool; always returns a JSON string (errors included) so the model can recover."""
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ctx.used.append(name)
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log.info("agent tool=%s", name) # no arguments: they may echo patient text
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try:
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if name == "search_guidelines":
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return _json(_search(ctx, str(args.get("query", ""))))
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if name == "get_patient_record":
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rec = await ctx.record()
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if rec is None:
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return _json({"found": False})
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ctx.cite("ЕМИАС: медицинская карта")
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return _json({"found": True, **rec.model_dump()})
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if name == "get_drug_info":
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return _json(_drug_info(ctx, str(args.get("drug", ""))))
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if name == "check_drug_for_patient":
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return _json(await _check(ctx, str(args.get("drug", ""))))
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return _json({"error": f"unknown tool {name}"})
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except Exception as exc: # noqa: BLE001 — a tool failure must not crash the chat
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log.error("agent tool=%s failed: %s", name, type(exc).__name__)
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return _json({"error": "tool failed"})
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def _search(ctx: ToolContext, query: str) -> dict[str, Any]:
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hits = retrieve(query, audience="patient", top_k=RAG_TOP_K) if query.strip() else []
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out = []
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for h in hits:
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label = h.chunk.citation.strip("[]")
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ctx.cite(label)
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text = " ".join(x for x in sentences(h.passage) if not _DOSE.search(x))[:PASSAGE_CHARS]
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if text:
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out.append({"source": label, "section": h.chunk.section, "text": text})
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return {"results": out, "found": bool(out)}
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def _drug_info(ctx: ToolContext, name: str) -> dict[str, Any]:
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entry = find_drug(name)
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if entry is None:
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return {"found": False, "drug": name}
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ctx.cite(entry.source)
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return {
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"found": True,
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"inn": entry.inn,
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"class": entry.drug_class,
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"composition": entry.composition.model_dump() if entry.composition else None,
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"contraindications": entry.contraindications,
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"interactions": [i.text for i in entry.interactions],
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"pregnancy": entry.pregnancy,
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"source": entry.source,
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}
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async def _check(ctx: ToolContext, name: str) -> dict[str, Any]:
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entry = find_drug(name) if name.strip() else None
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if entry is None:
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# "мои таблетки" / no name → the current psychiatric prescription from the record.
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rec = await ctx.record()
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current = [find_drug(p.drug) for p in (rec.current_prescriptions if rec else [])]
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entry = next((e for e in current if e is not None), None) if not find_drug(name) else None
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if entry is None:
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return {"found": False, "drug": name, "note": "Препарата нет в справочнике — отвечать «уточните у врача»."}
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rec = await ctx.record()
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if rec is None:
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return {"found": True, "inn": entry.inn, "record": False, "findings": []}
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ctx.cite(entry.source)
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ctx.cite("ЕМИАС: медицинская карта")
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db = load_db()
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findings = check_patient(entry, rec, db)
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comp = entry.composition
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intolerances = [a.name for a in rec.allergies]
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intolerance_check = None
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if comp is not None and intolerances:
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hit = {t for a in rec.allergies for t in a.tags} & set(comp.excipient_tags)
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intolerance_check = f"Непереносимость из карты ({', '.join(intolerances)}): " + (
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"вещество ЕСТЬ в составе."
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if hit
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else "в примере состава этого вещества нет; состав зависит от производителя."
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)
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return {
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"found": True,
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"inn": entry.inn,
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"record": True,
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"findings": [f.model_dump() for f in findings],
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"intolerance_check": intolerance_check,
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"composition": comp.model_dump(exclude={"excipient_tags"}) if comp else None,
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"general_interactions": [i.text for i in entry.interactions], # incl. alcohol — for questions about it
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"contraindications": entry.contraindications,
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"note": "Пустой findings не означает, что препарат безопасен: решение о приёме принимает врач.",
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}
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def _json(data: Any) -> str:
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return json.dumps(data, ensure_ascii=False)
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