Adds the routing scaffold for the doc-centric pivot. Each new route
renders a placeholder page until E3/E4/E5 implement them; legacy
routes (/studio, /documents, /history, /search, /reasoning) keep
working in parallel.
New routes (Vue Router, history mode):
/docs library (placeholder, #211)
/docs/new import (placeholder, #214)
/docs/:id?mode= workspace (placeholder, #216)
/index stores list (placeholder, 0.7.0)
/index/:store store detail (placeholder)
/index/:store/query RAG playground (placeholder)
/runs run history (placeholder)
/runs/:id run detail (placeholder)
Mode parsing
- shared/routing/modes.ts: DocMode union ('ask'|'inspect'|'chunks'),
parseMode() returns the default ('ask') for missing or unknown
values. #210 will layer feature-flag-aware redirection on top.
Route names
- shared/routing/names.ts: ROUTES typed const so callers do
router.push({ name: ROUTES.DOC_WORKSPACE, ... }) instead of
stringly-typed names.
Pages
- ComingSoonShell shared component: card + back-home link, themed
with existing CSS tokens.
- 8 thin placeholder pages (one per new route) that compose the shell
and forward route params.
- i18n keys under comingSoon.* added in fr + en.
Tests
- shared/routing/modes.test.ts (10 cases): isDocMode + parseMode +
ALL_MODES invariants.
- app/router/router.test.ts (5 cases): every doc-centric route
resolves to a component, legacy routes still work, doc workspace
receives id and parsed mode as props, unknown mode falls back to
ask, unknown path redirects to home.
Routes table extracted to routes.ts so tests build a router with
createMemoryHistory() (no window required) instead of needing the
production createWebHistory() router.
Refs #207
CLI script to migrate existing tenants to the data model introduced
by #202-205. Idempotent and resumable — re-running is a no-op.
tools/migrate_06.py
- Step 1: backfill_lifecycle — infers documents.lifecycle_state from
analysis_jobs.status + chunks_json presence
Failed analyses, no completed -> Failed
Completed + chunks_json -> Chunked
Completed, no chunks_json -> Parsed
Otherwise -> Uploaded
- Step 2: materialize_chunks — promotes the latest chunks_json blob
for each doc into rows in the new chunks table. Stable id derivation
via uuid5(NAMESPACE_OID, '<doc>|<seq>|<text>') so re-running lands
on the same ids
- Step 3: backfill_links — for any doc that has chunks materialized,
creates a (doc, default-store) link in Ingested state with a freshly
computed chunkset_hash. Treats 'chunks exist' as proxy for 'doc was
ingested into the legacy single index' — sufficient for the typical
pre-0.6.0 deployment, with OpenSearch reindex documented separately
- Step 4: reaggregate — applies #203's aggregate_lifecycle rule so
doc-chunked transitions to Ingested
Persistence
- migration_progress table for resumability + per-step idempotency
CLI
python -m tools.migrate_06 # full migration
python -m tools.migrate_06 --dry-run # plan only, no writes
python -m tools.migrate_06 --only-step <name> # rerun a phase
Tests
- 9 tests: inference rule per (completed, failed, chunks_json) tuple,
end-to-end migration on a hand-built three-doc snapshot, idempotency
(second run = no writes), --dry-run writes nothing, deterministic
chunk ids across reruns
Refs #206
The data and domain layers for the chunks editor (#219-224 in 0.6.0).
Chunks were previously stored as a JSON blob in analysis_jobs.chunks_json;
this commit makes them first-class persisted entities with stable IDs,
soft-delete, and an immutable audit log.
Domain
- Chunk: persistent entity with id, document_id, sequence, text,
headings, source_page, bboxes, doc_items, token_count, timestamps,
deleted_at (soft delete)
- ChunkEdit: immutable audit row (action, actor, at, before, after,
parents, children, reason)
- ChunkPush: snapshot of which chunk_ids landed in which store at push
- ChunkEditAction enum: insert/update/delete/merge/split
- domain/chunk_editing.py: pure operations on a chunkset (insert,
update, delete, merge, split). Each returns a new chunkset and the
affected chunk(s); errors raise ChunkEditingError.
Persistence
- Three new tables: chunks, chunk_edits, chunk_pushes (FK + indexes)
- SqliteChunkRepository (insert, insert_many, update, soft_delete,
find_for_document, find_by_id; respects deleted_at)
- SqliteChunkEditRepository (append-only audit log; paginated reads
ordered newest-first; per-chunk history)
- SqliteChunkPushRepository (per-(doc, store) latest snapshot)
Ports
- ChunkRepository, ChunkEditRepository, ChunkPushRepository protocols
added to domain/ports.py
Tests
- 17 tests for the pure chunk-editing operations covering insert /
update / delete / merge / split, sequence shifts, lineage, error
paths (out-of-range, missing id, deleted target, cross-document)
- 11 tests for the three repositories: round-trips, soft-delete
filtering, history ordering, lineage round-trip, cascade-delete with
document, find_latest semantics
Service orchestration (ChunkEditingService — atomic chunk + audit
write) and the API endpoints land in a follow-up commit on the same
feature branch / next release. The data + domain foundation here is
what unblocks #219-224.
Refs #205
Adds the pure-domain hash function that summarises a chunkset for
stale-detection purposes. Recorded on each DocumentStoreLink at push
time (#203 ships the column slot); compared against the recomputed
current hash to flip a link to Stale when the source has drifted.
domain/hashing.py
- chunkset_hash(chunks: Iterable[ChunkResult]) -> str
- SHA-256 over (text, source_page, headings) per chunk
- Excludes bboxes / doc_items / token_count by design
- 0x1F separator between chunks defends against the join-attack
(split A+B vs concat AB)
Tests
- 9 tests: determinism, sensitivity per included field, exclusion of
rendering-only fields, join-attack resistance, order sensitivity,
empty-input invariant
- Locked fixture: a hand-built 3-chunk input has a fixed expected hash;
CI fails loud if anyone changes the canonical inputs without updating
the fixture deliberately (and the release notes)
Service integration (recompute on chunk write, set on push) lands with
#205 once chunks are first-class — direct integration on the legacy
chunks_json path is deliberately deferred to keep #204 focused.
Refs #204
Introduces the data layer for multi-store ingestion. Documents can now
live in multiple stores, each with its own Ingested/Stale/Failed state.
The doc-level lifecycle (#202) becomes the aggregate over all per-store
links, computed by a pure domain function.
Domain
- Store entity (name, slug, kind, embedder, config, is_default)
- DocumentStoreLink entity with mark_ingested / mark_stale / mark_failed
helpers
- StoreKind and DocumentStoreLinkState enums
- aggregate_lifecycle(): pure function — Failed > Stale > Ingested
> fallback (the doc's pre-link Uploaded/Parsed/Chunked state)
Persistence
- New tables 'stores' and 'document_store_links' with the right indexes
(doc_id, store_id, state) and a UNIQUE (doc, store) on the link
- Default 'opensearch' store seeded idempotently in init_db, embedder
pulled from DEFAULT_EMBEDDER (fallback bge-m3)
- SqliteStoreRepository (find_by_slug, find_by_id, get_default, …)
- SqliteDocumentStoreLinkRepository with ON CONFLICT … DO UPDATE upsert
Ports
- StoreRepository and DocumentStoreLinkRepository protocols added
Tests
- 14 new tests: seed idempotency, insert/find round-trips, UNIQUE
constraint, cascade delete with the document, every link state
round-trips, aggregation rule with all branches
Refs #203
Adds a first-class lifecycle state to every document, distinct from
AnalysisJob.status. The lifecycle describes the document as a whole and
is the foundation for the doc-centric pivot in 0.6.0.
Domain
- DocumentLifecycleState enum (Uploaded/Parsed/Chunked/Ingested/Stale/Failed)
- Document.lifecycle_state and lifecycle_state_at fields
- Document.transition_to() validates against a transition table
(domain/lifecycle.py) and returns a DocumentLifecycleChanged event
- InvalidLifecycleTransitionError on disallowed transitions
Persistence
- ALTER TABLE documents to add the two columns (default 'Uploaded')
- New index idx_documents_lifecycle_state for filter perf
- _COLUMN_MIGRATIONS refactored to support multiple tables
- _POST_MIGRATION_DDL list for indexes on freshly-added columns
- SqliteDocumentRepository.update_lifecycle()
Services
- AnalysisService drives transitions on parse / chunk / re-chunk / fail
via _transition_document(); idempotent and resilient (logs WARN and
continues if a stale state is somehow encountered)
API
- DocumentResponse exposes lifecycleState + lifecycleStateAt
(additive — existing 'status' field kept for backwards compat)
Frontend
- Document type extended with lifecycleState and lifecycleStateAt
- DocumentLifecycleState union literal mirroring the backend enum
Tests
- 24 new tests in test_lifecycle.py covering transitions, idempotency,
invariant preservation, and event emission
- test_repos.py: round-trip + every-enum-value check + update_lifecycle
- test_chunking.py: rechunk path now mocks document_repo correctly
Refs #202
Adds technical design docs for the foundation of the doc-centric ingest pivot:
- 202 — Document lifecycle state machine
- 203 — Per (document, store) ingestion state
- 204 — Auto-detect Stale state via chunk content hash
- 205 — Audit trail for chunk edits (chunks → first-class entity)
- 206 — Migration of existing documents to the new model
Status: Accepted on all five. Each doc spells out the domain entities,
persistence schema, services orchestration, API contract, alternatives
considered, risks, and testing strategy. ADR placeholders called out
where load-bearing decisions warrant a follow-up document.
Refs #202#203#204#205#206
The previous tweak only set unrecognized_links: info but the actual
warnings are 'target X is not found among documentation files' which
is the not_found validator. Setting both to info so strict-mode build
passes on the audit reports' source-file references.
The audit reports under docs/audit/reports/release-*/ reference repo
source files (e.g. `[file.py:line](file.py:line)`) on purpose — they
are read with the repo open, not as standalone published pages. MkDocs
in strict mode treats those as unrecognized links and aborts the build.
Set `validation.links.unrecognized_links: info` so the warning still
prints but doesn't fail the build. Real broken doc links (anchors,
absolute paths) keep their existing levels.
Refs the doc deploy run that broke just after the v0.5.0 tag was pushed.
aquasecurity/trivy-action@v0.35.0 defaults to Trivy CLI v0.69.3, but
that tag was removed from GitHub releases mid-run on 2026-04-29 — the
HIGH step on Security scan — local started failing at setup time:
aquasecurity/trivy info checking GitHub for tag 'v0.69.3'
aquasecurity/trivy crit unable to find 'v0.69.3'
##[error]Process completed with exit code 1.
The CRITICAL step still passed (binary was in cache from a prior run),
so this only surfaced as a HIGH-step failure — but the job exit code
still propagates and breaks the gate.
Following `latest` rather than chasing a specific tag that upstream
can yank without notice.
Refs #189
Trivy reports OS-package CVEs against the package name (libgbm1,
libgl1-mesa-dri, libglx-mesa0, mesa-libgallium) — not against
installed file paths. The previous `paths:` filter silently failed
to match, so the ignore was a no-op and the gate kept failing on a
CVE we explicitly chose to defer.
Trace from the failing run (#25097385670):
Using YAML ignorefile '.trivyignore.yaml':
- id: CVE-2026-40393
...
libgbm1 CVE-2026-40393 CRITICAL affected 25.0.7-2
...
##[error]Process completed with exit code 1.
Removing `paths:` lets the ID-only match apply across all 4 affected
Mesa packages until 2026-06-30.
Refs #189
The CRITICAL + HIGH Trivy steps in release-gate.yml were invoking
aquasecurity/trivy-action without the `trivyignores` input, so the
.trivyignore.yaml at the repo root (committed in #190 to mitigate
CVE-2026-40393 / Mesa) was silently ignored — the gate kept failing
on a CVE we explicitly chose to defer.
Pass `trivyignores: .trivyignore.yaml` to both Trivy steps so the file
takes effect. The HIGH step also gets it for consistency (it doesn't
fail the gate, but reporting a CVE we ignore as HIGH would be noise).
Refs #189
Two patterns in Docling's serialization were mirrored 1:1 by the graph
projection and produced node explosions on real documents:
- An InlineGroup (paragraph of mixed style runs) emits one `groups[]`
entry plus N `texts[]` runs. Naive iteration created one Paragraph
node per run.
- A Picture's `children` carry internal text labels extracted by the
layout model (flowchart boxes, chart axis labels, diagram callouts).
Each child became its own Paragraph node, drowning the figure.
`build_collapse_index` (in the shared `infra.docling_tree` helper) now
returns the `skip_refs` set + `inline_meta` overrides for both cases.
The Neo4j `tree_writer` and the in-memory `docling_graph` consume the
same index, so both projections stay in sync.
InlineGroups are projected as a single :Paragraph carrying the
concatenated text and the union of children's provs (re-indexed).
Pictures keep their :Figure node and prov; their descendants are
dropped. Captions live in the picture's separate `captions` field, not
in `children`, so they are unaffected.
* docs: rename Clean Architecture → Hexagonal Architecture (ports & adapters)
Le backend suit le pattern ports & adapters (ports dans domain/ports.py,
adaptateurs dans infra/), pas Clean Architecture au sens Uncle Bob.
Aligne la terminologie dans README, docs/architecture.md, ADR guide,
audit master, fiche audit 01, et la nav mkdocs.
Les noms de fichiers et la commande /audit:clean-architecture restent
stables pour preserver les liens croises et les skills existants.
* feat(settings): add paste-image size/type limits surfaced via /api/health
Introduces MAX_PASTE_IMAGE_SIZE_MB (default 10) and
PASTE_ALLOWED_IMAGE_TYPES (default image/png,image/jpeg,image/webp)
env vars so the upcoming Verify-mode clipboard-paste handler can
validate client-side against the same limits the backend enforces.
Follows the existing MAX_FILE_SIZE_MB pattern. Ships the accepted
design doc at docs/design/195-copy-paste-image-verify-mode.md.
Refs #195
The watch-based plumbing from iteration click to PDF scroll relied on a
"flip via null" pattern (assign null then the value) to coerce Vue into
re-firing the watcher. Vue 3 collapses synchronous mutations of the same
ref and only delivers the final value, so the trick was a no-op: a second
click on the same iteration left the document view stuck on the previous
page. The bug only showed when the trace had a single iteration — with
several, the user naturally clicks different ones and the value really
changes.
Replace the watch chain with imperative dispatch. ReasoningPanel now just
emits iterationFocus; ReasoningWorkspace handles it by calling the graph
focus and the new StructureViewer.scrollToFocused method directly. Both
side effects fire on every click regardless of state.
Propagate Docling `self_ref` through PageElement so bboxes and graph nodes
share a stable identity. Add a Document/Graph mode switch to the reasoning
workspace; selecting a node highlights its bbox (numbered badge, focus ring,
optional dim of non-visited) and clicking a bbox re-centers the graph.
Backend — live runner
- New `POST /api/documents/:id/rag` endpoint. Loads `document_json` from
SQLite, reconstructs the DoclingDocument, wraps the model id in
`ModelIdentifier(ollama_name=...)`, and calls `agent._rag_loop`
off-thread (blocking sync call). Returns a `RAGResult` in the shape
the existing v1 import path already consumes, so the frontend overlay
is fully reused.
- `_rag_loop` is private upstream; we call it because `run()` wraps the
answer in a synthetic DoclingDocument and drops the iteration trace.
- Settings: `RAG_ENABLED`, `OLLAMA_HOST`, `RAG_MODEL_ID`. Router mounts
unconditionally; handler 503s when the flag is off or deps aren't
installed. `rag_available` surfaced in `/api/health`.
- Maps known docling-agent bugs to readable HTTP errors: 502 with
"the model couldn't produce a parseable answer" when `_rag_loop`
raises `IndexError` from `find_json_dicts([])[0]` after 3 + 3
rejection-sampling retries (model-dependent).
- Tests: 11 cases (flag off, query empty, no analysis, happy path,
model_id wrap, Ollama env, IndexError → 502, other errors → 500,
deps missing → 503).
Backend — bug fix
- Default `BATCH_PAGE_SIZE` flipped from `10` to `0` to match the
dataclass default. The old default silently dropped `document_json`
(see `domain/services.merge_results`) for any doc > 10 pages, which
broke the reasoning tunnel. Set `BATCH_PAGE_SIZE>0` explicitly on
memory-constrained deploys if batching is wanted.
Frontend — runner UX
- `features/reasoning/api.ts:runReasoning()` — POST wrapper.
- `RunReasoningDialog.vue` — query textarea + optional model_id
override. Blocks close while running, 20-40s loading state,
synthesises a sidecar-shaped envelope so the panel surfaces query +
model the same way an imported trace would.
- `ReasoningWorkspace.vue` — primary "Run reasoning" button; "Import
trace" relegated to ghost secondary.
- Store: `runDialogOpen`, `running`, `setRunning`.
Frontend — answer polish
- Answer rendered through `marked` + DOMPurify (models emit markdown
lists; `pre-wrap` rendered them as plain "1. …" strings).
- Dedicated answer block with orange border, "ANSWER" label, "Copy"
button (clipboard + "Copied ✓" feedback).
- IterationCard: drop the duplicate `response` block (the main answer
is authoritative); style reasons equal to `"fallback"` (docling-agent
`select_from_failure` placeholder) as italic muted "— no structured
rationale".
Frontend — node details contents
- Clicking a SectionHeader (or any node with compound children) lists
its contained elements in `NodeDetailsPanel` under a new "Contents"
block. Children come from the same `parentMap` used for Cytoscape
compound parenting (explicit PARENT_OF + synthetic section scope),
inverted once and cached as a computed.
- Click a child row → pan the viewport to it + swap the selection.
Housekeeping
- `cytoscape-navigator` removed from `package-lock.json` (follow-up
from the minimap removal in the previous commit).
Adds the `docling-agent` reasoning-trace viewer as a Studio tunnel, per
`docs/design/reasoning-trace.md`. Users pick an analyzed document, import
a RAGResult JSON, and the iterations are overlaid on the document graph.
Graph source is decoupled from Neo4j: a new pure builder
(`infra/docling_graph.build_graph_payload`) reads `document_json` from
SQLite and emits the same Cytoscape-shaped payload that `fetch_graph`
returns from Neo4j. Neo4j stays exclusive to the Maintain ingestion
pipeline. Shared DoclingDocument helpers live in `infra/docling_tree.py`
so TreeWriter and the builder can't drift on label taxonomy or tree walks.
Also removes the Cytoscape minimap (cytoscape-navigator) from GraphView:
second render instance hurt perf on large documents for no UX win.
Backend
- new `GET /api/documents/:id/reasoning-graph` (SQLite-only)
- new `infra/docling_tree.py`, `infra/docling_graph.py`
- `analysis_repo.find_latest_completed_by_document`
- tests: `test_docling_graph.py` (builder), `test_graph_api.py` (endpoint)
Frontend
- `features/reasoning/` — store, overlay, types, panel, import dialog,
workspace, doc picker
- new `ReasoningPage` + `/reasoning` and `/reasoning/:docId` routes
- `GraphView` gains a `fetcher` prop so reasoning can inject the
SQLite-backed fetcher while Maintain keeps using the Neo4j one
- drops minimap (nav container, dep, CSS)
- legend filters + section parenting extracted for reuse
- i18n base strings (FR + EN)
The `doc_items` field was added to `ChunkResult` earlier in the
feature branch (used by ChunkWriter for DERIVED_FROM edges), but the
test fixture was never updated. CI caught it now that the PR is open.
Fixes: tests/test_chunking.py::TestChunkResult::test_serializable
Move the graph view from a Verify-tab (where it sat post-analysis, off
the main flow) to a dedicated Maintain step after Ingest, so the graph
result is visible at the natural end of the Configure → Verify →
Prepare → Ingest → Maintain pipeline.
- StudioPage: new 'maintain' mode toggle + panel rendering GraphView
- ResultTabs: remove obsolete graph tab
- i18n: add studio.maintain (fr + en)
- GraphView: fix init order — flip loading off and await nextTick before
renderGraph so the canvas <div> is mounted when cytoscape reads its
container ref (previous code bailed silently on null ref)
Previous query chained 6 OPTIONAL MATCH clauses for edges with no
intervening WITH collect(), producing a cartesian product. At 6 pages
(~60 elements, ~300 edges) Neo4j hit 102% CPU and hung > 5min.
Rewritten with one CALL {} subquery per node/edge type: each block
returns a single row with its collected list — no multiplication across
types. 6-page doc now returns in 213ms (was: no return).
Python reshape code (queries.py:137-210) untouched — record keys and
edge map shape preserved.
Refs: https://neo4j.com/developer/kb/using-subqueries-to-control-the-scope-of-aggregations/
ChunkWriter mirrors chunks into Neo4j after OpenSearch indexing, creating
HAS_CHUNK edges and DERIVED_FROM back-references to the source Elements
(via doc_items propagated from the local chunker).
Graph API: GET /api/documents/{id}/graph returns a cytoscape-shaped
payload with nodes + edges for Document / Element / Page / Chunk.
Hard cap at 200 pages returns HTTP 413 per design §8.4.
Frontend: new Graph tab in Studio results, rendered with Cytoscape.js +
dagre layout (lazy-loaded, ~175 KB gz). Legend, node styling per element
label, directional edges styled per edge type.
README gains a Neo4j section with the schema, three demo Cypher
queries, and env vars. Backend tests skip cleanly when the neo4j python
package is not installed locally.
Refs #186
Serialize a DoclingDocument to a Neo4j graph: Document + Page + Element
nodes with dynamic specific labels (SectionHeader, Paragraph, Table,
Figure, …), plus HAS_ROOT / PARENT_OF / NEXT / ON_PAGE edges. Replace-on-
write for idempotent re-ingestion.
The reader returns the verbatim document_json stored on the Document
node — reconstruction from graph nodes is deferred to v0.6.
Wired into AnalysisService._finalize_analysis: runs after conversion,
degrades gracefully by default, fails fast when neo4j_required is set.
Refs #186
Document the Cytoscape.js vs vis-network / Neovis / D3 / Reagraph analysis
for the graph view, and make the 200-page cap on /api/documents/{id}/graph
explicit (HTTP 413 + truncated flag beyond the cap).
Refs #186
Add Neo4j as an optional graph-native storage layer (ingestion profile).
Introduces infra/neo4j with a singleton async driver wrapper and an
idempotent bootstrap of constraints + indexes, wired into the FastAPI
lifespan. Integration tests skip when no live Neo4j is reachable.
Refs #186
Hybrid approach: reuse LocalChunker to chunk the DoclingDocument JSON
returned by Serve, so chunking works identically in both local and
remote modes without calling Serve's chunk endpoint.
Backend:
- _build_chunker() always returns LocalChunker (remove engine guard)
- Use docling-core[chunking] extra for required dependencies
- Skip client-side batching in remote mode (Serve manages its own
resources, and batching discards document_json needed for chunking)
- Fix Serve form fields: remove generate_page_images (not a Serve
field), use repeated form keys for to_formats and page_range
- Log Serve error response body on 4xx/5xx for diagnosis
- Fix FastAPI 204 DELETE routes missing response_model=None
Frontend:
- Update chunking feature flag to enable Prepare UI in remote mode
Closes#51
CI was missing pytestarch dependency, causing test_architecture.py to fail
at collection time. Switch to requirements-test.txt which includes all
test dependencies.
- Move DEFAULT_PAGE_WIDTH/HEIGHT to domain/value_objects.py and import in both converters
- Add opensearch_default_limit to Settings (configurable via OPENSEARCH_DEFAULT_LIMIT env var)
- Pass settings.conversion_timeout to ServeConverter, removing independent _DEFAULT_TIMEOUT
- Update OpenSearchStore to accept default_limit from Settings via constructor
ChunkPanel emitted 'rechunked' which triggered an async re-fetch via
analysisStore.select() — but Vue does not await async emit handlers,
so chunk-cards never appeared before the E2E 30s timeout.
Now rechunk/edit/delete write returned chunks directly into the
analysis store via updateChunks(), removing the async round-trip.
Default value of 5 is now in the application code (settings.py) instead
of only in the Docker image ENV. Consistent across all deployment modes
(dev local, Docker, tests). Aligned docker-compose files and docs.
- Conditionally mount ingestion router only when OpenSearch + embedding are configured
- Add `ingestionAvailable` field to /api/health response
- Add `ingestion` feature flag to frontend (hides Search nav, Ingest button,
OpenSearch badge, indexed badges/filters when disabled)
- Skip ingestion polling when flag is off
- Make OpenSearch + embedding optional in docker-compose via profiles
- Add docker-compose.ingestion.yml override for full-stack ingestion
- Set BATCH_PAGE_SIZE=5 default in Docker local image
- Lead Quick Start with one-liner docker run command
- Document ingestion as opt-in with dedicated section
- Add BATCH_PAGE_SIZE, MAX_FILE_SIZE_MB, MAX_PAGE_COUNT, RATE_LIMIT_RPM to config tables
- Update test counts (380 backend, 159 frontend)
- Date CHANGELOG 0.4.0, bump frontend version to 0.4.0
- Sync CONTRIBUTING.md with E2E Karate test sections
Closes#180
analysis.feature and full-ui-path.feature still used exact-match
[data-e2e=toggle-btn] which broke after #178 changed the attribute to
compound values. Switch to [data-e2e~=configure-btn].
