ac436b87a2
- MemoryService 异步路径委托 MemoryIngestService / MemoryRetrievalService；富化派发经 MemoryEnrichmentScheduler - WebSocket pipeline 经 ChatTurnService 与显式 DTO 编排单轮对话；回忆录片段入队由 MemoirIngestScheduler 封装 - 新增 LlmGateway（LlmUseCase），各 agent、任务与适配器对齐 ports - 补充 memory 提示适配、runtime 类型、memory-retrieval 文档、ai-touchpoints 说明与扫描脚本及配套测试 Made-with: Cursor
78 lines
2.7 KiB
Python
78 lines
2.7 KiB
Python
"""由已抽取事实生成时间线事件（LLM + JSON）。"""
|
||
|
||
from __future__ import annotations
|
||
|
||
import json
|
||
from typing import Any
|
||
|
||
from app.core.langchain_llm import ainvoke_json_object, invoke_json_object
|
||
from app.core.llm_gateway import LlmGateway, LlmUseCase
|
||
from app.core.logging import get_logger
|
||
from app.features.memory.llm_schemas import (
|
||
TimelineEventsPayload,
|
||
parse_json_payload,
|
||
timeline_payload_to_dicts,
|
||
)
|
||
|
||
logger = get_logger(__name__)
|
||
|
||
MAX_FACTS_JSON = 20000
|
||
|
||
|
||
def build_timeline_events_from_facts_sync(llm: Any, facts: list[dict]) -> list[dict]:
|
||
"""facts 须含 id 字段（已落库）。"""
|
||
if not llm or not facts:
|
||
return []
|
||
payload = json.dumps(facts, ensure_ascii=False)[:MAX_FACTS_JSON]
|
||
prompt = (
|
||
"根据下列事实（含 id）生成时间线事件，用于回忆录展示。\n"
|
||
"每条含 event_year（整数或 null）、event_date（可选）、title、description、"
|
||
"source_fact_ids（必须来自输入中的 id 列表）。\n"
|
||
'只输出 JSON：{"events":[...]}，无事件则 {"events":[]}。最多 15 条。\n\n'
|
||
f"{payload}"
|
||
)
|
||
try:
|
||
raw = invoke_json_object(
|
||
llm, prompt, max_tokens=4096, agent="memory.timeline_events_sync"
|
||
)
|
||
parsed = parse_json_payload(raw, TimelineEventsPayload)
|
||
if parsed is None:
|
||
return []
|
||
return timeline_payload_to_dicts(parsed)
|
||
except (TypeError, ValueError) as e:
|
||
logger.warning("build_timeline_events_from_facts_sync 失败: {}", e)
|
||
return []
|
||
|
||
|
||
async def build_timeline_events_from_facts_async(
|
||
llm: Any, facts: list[dict]
|
||
) -> list[dict]:
|
||
if not llm or not facts:
|
||
return []
|
||
payload = json.dumps(facts, ensure_ascii=False)[:MAX_FACTS_JSON]
|
||
prompt = (
|
||
"根据下列事实（含 id）生成时间线事件。\n"
|
||
"每条含 event_year、event_date、title、description、source_fact_ids（来自输入 id）。\n"
|
||
'只输出 JSON：{"events":[...]}。\n\n'
|
||
f"{payload}"
|
||
)
|
||
try:
|
||
raw = await ainvoke_json_object(
|
||
llm, prompt, max_tokens=4096, agent="memory.timeline_events_async"
|
||
)
|
||
parsed = parse_json_payload(raw, TimelineEventsPayload)
|
||
if parsed is None:
|
||
return []
|
||
return timeline_payload_to_dicts(parsed)
|
||
except (TypeError, ValueError) as e:
|
||
logger.warning("build_timeline_events_from_facts_async 失败: {}", e)
|
||
return []
|
||
|
||
|
||
async def build_timeline_events(facts: list[dict]) -> list[dict]:
|
||
"""兼容旧接口。"""
|
||
llm = LlmGateway().langchain_llm_for(
|
||
LlmUseCase("memory.timeline_events.compat", fast=True)
|
||
)
|
||
return await build_timeline_events_from_facts_async(llm, facts)
|