### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.26.4 to v0.27.0
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
## Summary
- treat empty Markdown binaries as in-memory content instead of local
file paths
- add a regression test ensuring empty content does not access the
filesystem
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
### Summary
`AsyncExecutor.Execute` acquires a worker-pool slot, while
`ExecuteWithRetry` duplicated the task lifecycle without acquiring one.
Pregel supplies a retry configuration for every node, so those
executions
bypassed `WithMaxConcurrency`.
This change:
- routes retry execution through the shared `Execute` path;
- waits on the task-owned context and rechecks cancellation after slot
acquisition;
- adds deterministic regression coverage for worker-pool occupancy and
queued-task cancellation.
## Summary
- Frontend `Images` already includes `bmp`
(`web/src/constants/common.ts`), and picture parsing already accepts
`.bmp` (`internal/parser/parser/picture_parser.go`, `rag/app/picture.py`
via Pillow).
- This PR adds `bmp` to both whitelist sites and a small Go unit test.
Co-authored-by: zhangjiangshan1 <zhangjiangshan1@kingsoft.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Refactor the Extractor component into a pure, unified **5-in-1 modular extraction engine** across both Dataset (`knowledgebase.parser_config`) and Pipeline (Canvas DSL).
## Summary
- Disable DeepSeek V4 thinking (chain-of-thought) by default.
- litellm 1.82.x drops `thinking: disabled`; carry the toggle through
`extra_body.thinking.type` and strip `reasoning_effort` to avoid the
400.
- Use local timezone for agent `sys.date` instead of UTC.
Reference: https://api-docs.deepseek.com/guides/thinking_mode
---------
Co-authored-by: Claude <claude@example.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude <noreply@anthropic.com>
This PR fixes two issues with MinerU PDF parser where table and image chunks were not properly classified or associated:
1. **Table chunks** were incorrectly classified as `text` instead of `table`
2. **Image chunks** were missing image resource association and classified as `text`
### Summary
GaussDB DocEngine could return no chunks for conversational queries even
when relevant content was available. `Dealer.search()` supplies
`minimum_should_match` (30%, then 10% on retry), but the GaussDB adapter
discarded it and built a single `plainto_tsquery` from every token. This
effectively required all conversational filler terms to match.
## Summary
The TitleChunker (both `hierarchy` and `group` methods) had no
token-size ceiling, so a long section without sub-headings became one
giant chunk. This adds a configurable `chunk_token_cap` that guarantees
every text chunk stays within a token budget.
### Summary
1. It changes the fallback semantics of the locate phase. When no chunks
are found, the system stays in locate. If the same claim has two
consecutive locate rounds with neither evidence chunks nor newly routed
document scope, web_search is admitted to the candidate tool set on the
next locate round as an external fallback.
2. It makes locate_empty_streak claim-scoped instead of shared in the
global context. This prevents one claim’s empty locate rounds from
affecting sibling claims running in parallel.
3. On the config side, it only raises max_parallel_agents for high /
ultra to 4, without changing max_agent_cycles. This increases parallel
claim execution without deepening per-claim search.
