dsh-lacan-knowledge-os
基于语料库的拉康精神分析研究环境，打包为 DeepSeek Harness 插件套件（MCP 工具接口，共 10 个工具）。
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add github:YanKaFei/Lacan-Knowledge-OS#b876e29f18bf8c31a74aa7afe3e10837b46eff3eLacan Knowledge Os 以 dsh-lacan-knowledge-os 发布，当前版本为 1.0.0。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
A corpus-grounded research environment for Lacanian psychoanalysis. Evidence first. Interpretation second. Fabrication never.
The one rule this system is built around
Every claim must land on a passage number.
If the corpus cannot support a question, the system abstains — it does not answer from model knowledge. An abstention is a result, not an error.
Lacan Knowledge OS is a local, offline-first research instrument for reading Lacan seriously. It turns a corpus of seminar and écrits text into a citable evidence store, and it puts a frozen scholarly core between your question and any answer.
Six things, one system:
| Capability | What it gives you | |
|---|---|---|
| 🔎 | Research | Ask a question → the core retrieves passages, builds an evidence contract, and only then synthesises an answer whose every claim survives citation + entailment validation |
| 📖 | Explore | Read the corpus directly: passages, sessions, seminars, concepts, terminology — no model involved |
| 🔬 | Evidence Inspector | Answer → Claim → Passage → Session → Seminar → Witness/Source, with the exact quoted span and its context window |
| 🗂️ | Research Projects | Turn repeated runs into a long-term topic (questions, hypotheses, passages, persons, cases, bibliography) |
| 📚 | Bibliography & citations | Review status, metadata completeness, per-style citation availability with the reason it is unavailable |
| ✍️ | Obsidian bridge | Evidence and validation stay here; your understanding, notes and writing live in your vault |
These refusals are the design, not limitations:
| Refusal | Why |
|---|---|
| No answering from model knowledge | The synthesis step may only use retrieved evidence. If the contract is insufficient, the output is ABSTAINED. |
| No silent repair of sources | SOURCE_TRACE_INCOMPLETE stays visible. Hiding it would misrepresent the source. |
| No invented bibliographic data | Publisher, year, ISBN, page numbers are never guessed. A style that cannot be produced says why. |
| No auto-promotion to canonical | Imported or AI-produced material enters as a candidate and stays one until a human promotes it. |
| No unspecified semantics | The 39 scholarly components are hash-pinned; an undeclared change fails the freeze check and the system refuses to start. |
This public edition ships the engine, not the corpus. See §8 Bring your own corpus and
CORPUS.md.
git clone https://github.com/YanKaFei/Lacan-Knowledge-OS.git
cd Lacan-Knowledge-OS
# 1) The interface boots with no corpus at all — Help Center + UI are fully usable:
python3 -m workspace_ui.server.cli --port 3090
# → http://127.0.0.1:3090/help 13-page Help Center
# → http://127.0.0.1:3090/research research surface (needs a corpus to answer)
# 2) Integrity checks (these are the contract, not decoration):
python3 _scripts/_tools/core_freeze.py --verify # 39 scholarly components
python3 _scripts/_tools/freeze_lineage.py --verify # semantic changes across phases
python3 _scripts/_tools/build_i18n.py --check # UI copy ↔ dictionary ↔ call sites
python3 _scripts/_tools/build_help.py --check # Help links, anchors, 0 fiction
# 3) Full regression (corpus-dependent suites need a corpus; see CORPUS.md)
bash _scripts/run_all_tests.sh
Requirements: Python 3.9+ (standard library only for the core path), a modern browser,
and — only if you want vector retrieval or a real LLM provider — the optional extras in
docs/EMBEDDING_PROVIDER.md. No bundler, no build step:
index.html loads ES modules directly.
Opening the system shows what you can do, not the system's internals:
Hero → [Start a research run] [First time here?]
Tasks → Ask a Lacanian question · Find text and sources · Study a concept
Study persons and cases · Build a long-term project · Manage sources
Workflow → ① Ask → ② Check evidence → ③ Read the original
→ ④ Save the material → ⑤ Sort sources → ⑥ Form your own knowledge
5 minutes → six steps to a finished first run
Every entry is a real link (/research, /explore, /projects, /bibliography,
/persons, /cases, /zotero, /help/...) — shareable, bookmarkable, openable in a new tab.
VALIDATED, VALIDATED_WITH_QUALIFICATIONS, PARTIALLY_SUPPORTED,
VALIDATION_FAILED, INSUFFICIENT_EVIDENCE, ABSTAINED. Read it literally.Add to Project, or Save to Obsidian./help is a 13-page centre with a sidebar, anchors, previous/next, and a topic search:
getting started, research, evidence, explore, research vs explore, projects,
persons & cases, bibliography, zotero, obsidian, languages, statuses, troubleshooting.
Every control name in Help is rendered from the real interface, and every functional
claim is machine-checked (HELP_CLAIM_VERIFICATION.json: 42/42 verified, 0 fiction, 0 pending).
| Setting | Scope | Example |
|---|---|---|
Language (English / 中文) | The product interface only | switches instantly, no reload |
Research language (any / zh / fr / en) | The question language sent with a research request | does not translate the UI, does not filter retrieval |
Interface = 中文 + Research language = Français is a perfectly valid combination.
Lacan's original text, quoted passages and bibliographic metadata are never translated.
your question
│
┌──────────▼───────────┐
│ PRODUCT LAYER │ workspace_ui/ · browse_api/ · project_api/
│ (may change freely) │ export_system/ · bibliography/ · obsidian_adapter/
└──────────┬───────────┘
│ scholarly_api v1 (product boundary — 3 hashed components)
┌──────────▼───────────┐
│ FROZEN CORE │ 39 hash-pinned components
│ (cannot drift) │ retrieval · evidence contract · sufficiency ·
└──────────┬───────────┘ synthesis boundary · citation · entailment · abstention
│
┌──────────▼───────────┐
│ CORPUS │ passage store · witnesses · ontology · indexes
│ (bring your own) │ NOT included in this repository
└──────────────────────┘
mcp_server/ exposes 10 tools over stdio
(protocol 2025-11-25); the UI is just one client of that same contract.core_freeze.py --verify recomputes 39 component hashes;
freeze_lineage.py --verify proves zero semantic change across seven phases.Read more: docs/ARCHITECTURE.md ·
docs/MCP_ARCHITECTURE.md ·
HELP_SYSTEM_ARCHITECTURE.md.
The repository is a DeepSeek Harness plugin target: it ships an MCP server, a portable row, and an installable DSH bundle.
# A. As a DSH plugin (installs the MCP row for you)
dsh plugin --profile web add github:YanKaFei/Lacan-Knowledge-OS
# B. Or paste the row yourself — integrations/lacan-kb-mcp.row.yml
# (tools then appear as mcp__lacan-kb__search_passages, …)
# C. Or run the server standalone
python3 _scripts/_tools/lacan-kb-mcp
Proven with DSH's own MCP SDK (_data/mcp/DSH_CLIENT_PROOF.json, 14/14 checks):
stdio handshake, 10 tools with schemas, mcp__lacan-kb__<tool> naming, structured evidence
returns, independent re-verification of returned passage ids, and a protocol error — not a
crash — for unknown tools. See docs/MCP_DSH_INTEGRATION.md.
Handing the corpus to a colleague. Build a pack and send it over a channel you control
(a private repo's release asset, your own server, a USB stick) — hash-verified and ~215 MB for
the reference corpus: docs/CORPUS_PACK.md
(tools/pack-corpus.py → tools/fetch-corpus.py).
This repository deliberately contains no source text:
| Not included | Why |
|---|---|
| Seminar/écrits full text (fr + zh) | Copyright of the rights holders |
Passage store (passages.jsonl, 249,105 records, ~384 MB) | Corpus text |
Witness realizations & witnesses (~152 MB) | Corpus text |
| Vector/lexical indexes | Large, rebuildable from your own corpus |
What is included: the schemas, the freeze contract, the builders, the validators and the tests — i.e. everything needed to ingest text you are allowed to use (your own scans, licensed editions, public-domain material, or your own translations).
python3 _scripts/build.py --help # corpus inventory & build entry points
python3 _scripts/inventory_corpus.py --help # canonical inventory + hashes
The public edition is produced and verified by
_scripts/_tools/build_public_edition.py:
an allow-list copy, then a negative verification (corpus N-gram probes, secret scan,
absolute-path scan, size gates). See docs/PUBLIC_EDITION.md.
| ✅ Advantages | ⚠️ Disadvantages / limits |
|---|---|
|
Verifiability over fluency. Every claim is tied to a passage id; you can audit the chain by hand. Honest failure. Abstention, An executable contract. The 39-component freeze and the seven-segment lineage are checked by code, not by a promise in a document. Offline-first. One contract, many clients. The same MCP surface serves the web UI, DSH, and any editor with an MCP client. Auditable history. Every research run is an immutable snapshot; re-running a question creates a new item instead of overwriting the old one. Bilingual by construction. UI copy is dictionary-driven with 0 missing keys; source text is deliberately never translated. |
It needs a corpus you have the right to use. Out of the box it can show its interface, its Help Centre and its contracts — but it cannot answer questions until you supply text. It is opinionated about scope. It answers about a corpus. Questions about publication history, attendees or dates will abstain, because the corpus does not carry that metadata. No quality score. There is no "confidence %" anywhere; interpretation quality remains your judgement. Heavy for a laptop-scale workflow. The reference corpus is ~2.5 GB on disk including derived indexes and embeddings. Vector retrieval is optional and partial. Without the embedding extras, retrieval falls back to lexical matching (the UI says which one is active). Real-LLM synthesis is a single blocking call. Long runs take 45–60 s; the UI shows real elapsed time, and "stop waiting" does not cancel the backend job. Fast-moving product layer, frozen scholarly layer. Convenience features change often; changing the semantics requires a formal Core Change Request. Presupposes familiarity with the domain. The system will not teach you Lacan. |
SCHOLARLY_CORE_READY); the product layer
is complete for daily use (research, explore, evidence, projects, bibliography, Zotero
import, Obsidian bridge, export, 6-language README, Help Centre).docs/ROADMAP.md.CONTRIBUTING.md — the one non-negotiable rule is
do not change scholarly semantics without a Core Change Request.SECURITY.md — credentials never pass through the product API.License — code: Apache-2.0 · source texts: not distributed (NOTICE)
If this system saves you a week of citation checking, it did its job.