Port dataset-level wiki incremental compile and refactor splitByTokens
token budgeting. Includes replace-only wiki merge, KNN dedup routing,
and template/config wiring.
## What changed
- add an OceanBase/SeekDB Go document engine using `database/sql` and
the existing MySQL driver
- preserve the Python connector's configuration, physical table names,
schema, index names, and ARRAY/JSON/VECTOR encodings
- implement chunk, memory, document metadata, skill, SQL, full-text,
vector, and fusion search paths
- support `DBMS_HYBRID_SEARCH.SEARCH` behind the existing feature flag,
with SQL fallback only when the package is unavailable
- wire the engine into retrieval, memory, metadata, vector hydration,
and SQL chat flows
- add Python/Go compatibility contracts, SQL mock tests, and an
integration-tagged round-trip test
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Co-authored-by: Jin Hai <haijin.chn@gmail.com>
Re-materialize wiki page graph from merged wiki_page rows after each
batch merge. Adds ProjectWikiGraph/DropWikiGraph, full page_type/slug
identity, delete-then-insert, tests.
## Summary
- Add embedding batch-size metadata to model responses and tenant
overrides.
- Validate embedding dimensions and batch limits across provider
verification and embedding requests.
- Expand validation tests for defaults, limits, and missing metadata.
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
Ports dataset knowledge compilation (wiki/graph/tree/mindmap) to the Go
scheduler with a status contract, aligns wiki storage/retrieval with
Python, sizes prompts by content_length, and resolves embedding batch
size from provider capability.
Ports the dataset knowledge compilation (wiki/graph/tree/mindmap) to the
Go scheduler with a status contract, aligns wiki storage/retrieval with
Python, and sizes prompts by content_length.
- Prefer canonical `dataset_ids` over legacy `kb_ids` in Canvas
retrieval components.
- Cover selected and explicitly cleared dataset IDs with regression
tests.
- Add cross-language retrieval with dataset-specific embedding and
rerank models.
- Support vector and keyword similarity controls, metadata filtering,
TOC enhancement, and child-chunk expansion.
- Route Canvas retrieval across datasets and memories with compatible
embedding validation.
Port Python rag/advanced_rag agentic search to Go: ES-backed dataset-nav
service, agentic-search harness, and agent tools.
Includes agentic-search port plan and self-review docs.
## Summary
- Align Go agent logs access with the Python behavior by checking tenant
access to the target agent instead of requiring the token to be bound
to that agent.
- Marshal canvas lifecycle event payloads safely so non-serializable
inputs do not break Thinking expansion in the UI.
## Testing
- `CGO_ENABLED=0 go test -count=1 -v -run
"Handler|Attachment|Logs|Chatbot|Agentbot|BuildWorkflow|NodeLifecycle|VarRef|Resolve|Extract"./internal/handler/
./internal/agent/canvas/...` PASS
