Kevin
71fbd39e32
feat(api)!: memory single chain — async MemoryService, strict eval closure
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Route all memory ingest/retrieve/enrichment/compaction through async MemoryService.
Remove legacy sync memory implementations (ingest/retrieve/compaction); Celery and
memoir Phase2 call asyncio.run into MemoryService-backed helpers.
Memoir Phase1 batch ingest uses MemoryService.ingest_transcripts_batch; drop chapters.
evidence_bundle_json mirror (Alembic 0015). Evaluation uses snapshot/link-only bundles;
raise EvidenceClosureMissing instead of partial/fallback lineage tiers.
Split memoir state into NarrativeCoverageState and InterviewControlState; delete the
_interview_meta_store adapter layer. Remove rolling-query and recent-fact fallback
settings from config and evidence assembly.
Update judges, docs, tests, and PlaygroundPage alignment.
Made-with: Cursor
2026-04-30 14:11:50 +08:00
Kevin
3121d1384d
WIP: memory system improvements (in progress)
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Interview/chat prompt layers, reply planner, style profiles, memory
injection, interview meta store, and related tests. Work not finished.
Made-with: Cursor
2026-04-22 16:56:28 +08:00
yangshilin
31fc1c24cf
fix: 优化模型提示词，照顾用户情绪
2026-04-09 18:18:28 +08:00
yangshilin
e1341c6d18
feat:
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1. 建立问题库大纲，对应每个人生阶段槽位
2. 鼓励使用更生活化的交流语言共情与总结
3. 降低评审模型可能发生截断的概率
4. 成稿质量维度强化情感表达和上下文连贯性
2026-04-09 15:32:35 +08:00
Kevin
064ad2161d
refactor(eval+memoir)：精简内部评测路由与服务，composite/对话摘要与 judge 能力补强
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- 访谈：新增 interview_state_hints，联动 orchestrator 与提示词
- 回忆录：story_pipeline_sync/state/memory/post_commit 与 Celery 任务调整
- 基建：开发用 celery broker、compose/development 脚本、依赖注入
- eval-web：移除数据集/实验/版本等页面与流式轮询，突出 Playground
- 文档与单测同步
2026-04-08 21:36:12 +08:00
Kevin
2a0c80987d
test/ 调整prompt，提高共情能力
2026-04-08 17:10:09 +08:00
Kevin
2fded6fbd9
refactor(chat): AI-native prompts, remove interview heuristics
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- Drop interview_reply_length and utterance_substance; always run stage LLM
and memory retrieval when enabled; trim Settings fields and .env.example.
- Replace guided/opening prompts with compact fact blocks plus unified
behavior guidance; slim background_voice and persona to tone hints.
- InterviewAgent uses fixed chat_interview max_tokens/chars/segments.
Also includes stacked work: profile followup/extract path, evaluation rubric
and judge schema updates, transcript SPLIT handling in execution service,
user export markdown split tests, and golden case fixture.
2026-04-06 22:23:46 +08:00
Kevin
69a673e6c6
feat(api): 访谈人格/回复长度策略、口述归一、背景语气与输入净稿全链路
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Chat 访谈
- 新增 persona 系统（default / warm_listener / curious_guide）与 background_voice 语气层
- 回复长度由 compute_reply_plan 统一决策（brief / standard / expanded），融合信息密度启发式
- 输入净稿（input_normalize）：编排层可选 rules/llm 归一用户口语后再喂模型与记忆检索
- 记忆证据注入：按用户话检索 memory evidence 并注入 prompt
Memoir 回忆录
- 口述归一（oral_normalize）：segment 原文保留，story 管线取派生净稿作叙事输入
- segment 入队批次门闸：累计字数 + 最长等待秒数，减少零碎提交
- fidelity_check / prompts / narrative_agent 微调
- Alembic 0005：清理跨章节 story 外键
Infra
- Dockerfile 加入 ffmpeg
- pyproject.toml 新增依赖并同步 uv.lock
- .env.example / .env.production 补全新配置项
Tests
- 新增 test_background_voice、test_chat_input_normalize、test_experience_regressions
- 扩展 test_interview_prompts、test_interview_reply_length、test_story_route_oral_invariant
Made-with: Cursor
2026-03-31 23:55:26 +08:00
