Fixes O(n²) write amplification during wiki ingest on large KBs. Previously
every ingest/retract op re-wrote the single `slug='log'` row end-to-end and
every batch re-wrote the entire `slug='index'` directory markdown. On a 40k-
doc KB the log row grew to tens of MB and the index row to several MB, so
each batch triggered giant TOAST updates that dominated ingest wall time.
Log: new `wiki_log_entries` event table (`id DESC` indexed per KB) replaces
the single TEXT row. Batch ingest now collects entries and flushes them
once per batch via `AppendBatch`. Each entry stores `pages_affected` as
JSONB `[{slug,title}]` so the UI can render real titles; custom Scan falls
back to legacy `[]string` so older rows still deserialize.
Index: `wiki_pages[slug=index].content` keeps only the LLM-generated intro
(a few KB). The directory is now served by a structured paginated API
(`GetIndexView`) that reads `slug/title/summary` per type with cursor
pagination, so the agent and the frontend only pull the slice they need.
`RebuildIndexPage` degrades to a no-op; agent `wiki_read_page('index')`
synthesizes a small top-K overview and points callers at `wiki_search`.
Ingest resilience: LLM calls wrap with 3-attempt exponential backoff on
transient errors (5xx/408/429, transport resets/timeouts). Summary/extract
failures now bubble up so the batch's failed-op requeue path runs instead
of silently dropping the doc.
Frontend: sidebar Index/Log entries switch to dedicated views. Index view
streams intro → Summary → Entity → Concept → Synthesis → Comparison via
IntersectionObserver (with a nextTick re-check so small KBs still load
every section). Log view uses cursor pagination; pages_affected renders
titles with slug tooltip.
- new migration: migrations/versioned/000040_wiki_log_entries.{up,down}.sql
- tests: log repo pagination + legacy Scan, ListByTypeLight windowing,
renderIndexOverviewForAgent output, isTransientLLMError classifier
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add explicit response logging for the branch where the model returns
finish=stop with zero tool calls. This makes it easier to identify the
natural-stop path early in logs and correlate rounds that are likely to
be treated as final-answer candidates by analyzeResponse.
- include `tool_calls=0` in the no-tool summary log
- emit a dedicated "Natural-stop candidate detected" info log when
finish_reason is stop and no tool calls are present
Scanned PDFs without a successful OCR pass (e.g. when no VLM is configured
on the KB, or when the VLM returned a "no text content" reply that the
sanitizer discarded) reach the summary and wiki-ingest pipelines with
nothing but markdown image references for content. The downstream LLM
prompts used to receive the filename, file type, and title alongside that
empty content, and the generate_summary template explicitly forbade the
model from refusing — so the model would invent a topic from the filename
alone, producing e.g. a "Canon scanner manual" summary for an MX5280.pdf
that is actually a scanned legal letter.
Two changes shut this down:
1. Drop filename / title / file-type from every LLM prompt input. The
wiki summary, knowledge extract, candidate slug, and chunk citation
prompts now see only the document content. The knowledge summary
path no longer prepends the "Document Type: X / File Name: Y" intro.
2. Add a content-sufficiency guard in front of the LLM call. A new
helper strips markdown image references and HTML image tags and
refuses to invoke the model when fewer than 50 real-text runes
remain. getSummary returns a sentinel error in that case and the
caller marks the knowledge as SummaryStatusFailed instead of
surfacing the first chunk's bare image reference. Wiki ingest skips
LLM extraction with a clear log message.
The generate_summary.yaml prompt is also updated: the "NEVER output
refusal phrases" clause is removed and replaced with an explicit
empty-content rule that returns a deterministic placeholder line.
Real OCR (Tesseract / PaddleOCR) and filename-pattern sanitisation are
intentionally left for separate PRs.
resolveFileServiceForKnowledge was reading os.Getenv("LOCAL_STORAGE_BASE_DIR")
on every request. This causes a mismatch when the variable is not in the
process environment at request time (e.g. it was set programmatically before
app startup but not exported, or the DI-constructed fileService uses a
different configured path).
Fix: store the value in a new localBaseDir field at NewDataAnalysisTool
construction time — the same moment the DI container assembles the local
FileService — and use t.localBaseDir in resolveFileServiceForKnowledge
instead. This guarantees the data-analysis tool always resolves files
under the same base directory that the local FileService was configured
with, eliminating the "path not found" errors when LOCAL storage is used
for a knowledge base while the global storage backend is minio/oss/cos.
Fixes#1040
The IM service applied a hard 120s deadline (`qaTimeout`) to the entire
QA pipeline context. Multi-round ReAct agents easily exceed this — when
the deadline fires mid-stream the LLM provider returns "context deadline
exceeded" which leaks into the user-visible answer (fixes#1000).
Changes:
- Replace `context.WithTimeout(ctx, qaTimeout)` with `context.WithCancel(ctx)`
in both `handleMessageStream` and `runQA`, matching the web handler's
approach. Each agent round still has its own per-call LLMCallTimeout
(default 120s) which is sufficient.
- Filter `ResponseTypeError` stream chunks in `streamLLMToEventBus` so
error messages (e.g. "context deadline exceeded") are never appended
to the LLM content. Instead they are captured in `StreamError` and
surfaced as a Go error when no usable content was produced.
- Bump Redis inflight mapping TTL from qaTimeout+30s to 10 minutes to
accommodate longer agent runs.
- Remove the now-unused `qaTimeout` constant.
The outer if/else in Execute claimed to prefer chatModel (LLM-based
reranking), but both branches called rerankResults which internally
prefers rerankModel first. This made the outer branching dead code
with a misleading comment.
Consolidate into a single branch that delegates entirely to
rerankResults, whose actual priority is: rerankModel → chatModel → none.
The existing Langfuse integration covered Chat / Embedding / Rerank / VLM /
ASR generations plus the HTTP + asynq spans, but the agent's own execution
tree was invisible: tool calls never appeared, multi-round ReAct iterations
were flat under the HTTP trace, and there was no single node representing
"one agent run".
This change adds three levels of agent-side spans:
- agent.execute — wraps AgentEngine.Execute, records query preview,
knowledge bases, allowed tools, final-answer length
and totals on finish.
- agent.round.<N> — wraps each ReAct iteration; records finish_reason,
tool-call count, token usage and duration.
- agent.tool.<name> — wraps each tool invocation; records arguments,
success, duration, output preview (rune-safe, 4KB
cap), error, data keys and image count.
To keep the loop's many exit paths (natural stop, stuck loop, empty-content
retry, final_answer, context cancellation) span-safe, the iteration body was
extracted into runReActIteration with a single defer span.Finish() and an
iterOutcome sentinel driving the outer loop. database_query arguments are
redacted (keys only) to avoid leaking raw SQL into the observability
backend, mirroring the existing UI hint policy.
Adds unit tests for the new helpers (truncateForLangfuse, argKeys, dataKeys,
finishToolSpan nil-safety, iterOutcome.String).
Dev-mode repro from the issue reporter's logs:
[Tool][DataAnalysis] Failed to create table from Excel: IO Error:
GDAL Error (4): Failed to open file
'local://10000/.../1777030910246871000.xlsx': No such file or directory
The local file service returns a custom 'local://' URL from GetFileURL,
which the duckdb spatial/excel extensions can't resolve (they expect
plain paths or http(s)/s3:// style URIs). Presigned HTTPS URLs from
cloud backends worked by accident; the 'local://' dev path has always
been broken for the Data Analysis tool.
Instead of per-scheme adapters, stream the file through
FileService.GetFile into a temp file and hand DuckDB the resulting
filesystem path. This works uniformly across every backend (local,
OSS, S3, MinIO, COS) and survives future scheme changes without any
changes to the Data Analysis tool.
- Preserve the original file extension on the temp file so DuckDB's
format auto-detection (csv / xlsx / xls) still kicks in.
- Clean up the temp file when LoadFromKnowledge returns, including on
every error branch. Cleanup is idempotent (double-invoke safe).
- New tests stub FileService to lock in that (a) we never leak a
provider:// URL to DuckDB, (b) GetFile errors propagate, (c) the
extension survives case normalization.
Refs: https://github.com/Tencent/WeKnora/issues/1007
Catching up on a real-world check: when a multi-sheet .xlsx fixture is
fed through LoadFromExcel against an in-memory DuckDB with the spatial
and excel extensions, the first iteration's sheet enumeration quietly
fell back because st_read_meta doesn't expose a scalar 'layer_name'
column — it returns a LIST<STRUCT> column called 'layers'. We now
UNNEST(layers).name so enumeration actually works, and assert the full
data path with three DuckDB-backed tests:
- multi-sheet workbook yields the sum of all rows and per-sheet
breakdown via __sheet_name (including schema drift: columns only
present in one sheet are NULL for the other)
- single-sheet workbook still works and tags rows with its sheet name
- sheet name containing a single quote (Q1'24) survives the SQL
literal round-trip
excelize/v2 is added as a test-time helper to build the fixtures
deterministically. If DuckDB's spatial/excel extensions can't be
installed (offline CI), the tests skip rather than fail.
Refs: https://github.com/Tencent/WeKnora/issues/1007
DuckDB's st_read (spatial) only reads the first layer/sheet of a .xlsx
workbook, so every sheet beyond Sheet1 was silently dropped from the
DuckDB table the Data Analysis tool builds. Users trying to analyse
multi-sheet workbooks could only see the first sheet.
Switch to DuckDB's dedicated 'excel' extension (read_xlsx) for the
actual data load, enumerate sheets via the spatial extension's
st_read_meta, and UNION ALL BY NAME the rows of every sheet into one
table. A synthetic __sheet_name column records the source so the LLM
can still filter/aggregate per sheet; schema drift between sheets is
tolerated via UNION BY NAME. If enumeration fails (older DuckDB, local
filesystem errors, …) we fall back to reading the first sheet so the
tool stays usable.
- Install & LOAD the 'excel' extension alongside 'spatial' both at
startup (internal/container) and in the offline prefetch binary
(cmd/download/duckdb).
- Harden sheet/path handling against single quotes.
- Update the tool description so the agent knows about __sheet_name.
- Add unit tests for the CREATE TABLE SQL builder covering 0 / 1 / N
sheets and quote escaping.
Refs: https://github.com/Tencent/WeKnora/issues/1007
The agent loop previously kept running when the LLM emitted final_answer with
malformed JSON arguments: observe.analyzeResponse strictly json.Unmarshal'd the
raw args and returned isDone=false on failure, while act.runToolCall separately
repaired the JSON and executed the tool. The mismatch made final_answer
non-terminal, so the LLM saw its own answer in the next round's tool result
and re-emitted final_answer, surfacing near-identical answers multiple times
to the user (issue #1008).
Fix by unifying parsing in a new tools.ParseFinalAnswerArgs helper with three
fallbacks (strict -> RepairJSON -> regex extraction) and making final_answer
always terminal in analyzeResponse. When no answer can be recovered, emit a
user-visible fallback message and a Done=true event so the UI still resolves.
Also route final_answer.Execute through the same helper so tool execution and
loop termination stay consistent.
Adds regression tests in observe_test.go and final_answer_test.go covering
valid args, RepairJSON recovery, unrecoverable args, and garbage input.
Refs: Tencent/WeKnora#1008
- Introduced a unified capability requirements system for agent tools, ensuring consistent filtering of knowledge bases based on their capabilities.
- Implemented derived `kb_filter` logic to streamline compatibility checks between agent tools and knowledge bases, reducing redundancy in configuration.
- Updated frontend components to reflect new filtering logic, including improved handling of empty states and user feedback when no compatible knowledge bases are available.
- Enhanced internationalization support by adding relevant messages for tool compatibility issues across multiple languages.
- Changed `kb_selection_mode` in agent type presets from "selected" to "all" to allow agents to access all knowledge bases by default.
- Revised prompt templates to clarify the handling of bound knowledge bases, replacing the `{{knowledge_bases}}` placeholder with a reference to the `<bound_knowledge_bases>` block in the user message's `<runtime_context>`.
- Enhanced internal logic to ensure that only searchable knowledge bases are considered during retrieval, improving the efficiency of knowledge searches.
- Added new functions for better formatting and handling of knowledge base metadata in the runtime context.
- Updated documentation and comments for clarity on the changes made to knowledge base interactions.
- Introduced extraction granularity settings in the wiki configuration, allowing users to control the level of detail in entity and concept extraction (focused, standard, exhaustive).
- Updated the UI to reflect these new options, including tooltips for better user guidance.
- Refactored the knowledge base editor to support the new extraction granularity feature, ensuring a seamless user experience.
- Improved the backend logic for wiki ingest tasks to utilize the new granularity settings, enhancing the accuracy of extracted content.
- Added tests to validate the new extraction granularity functionality and ensure robust performance across different configurations.
- Updated the agent system prompt to emphasize the use of regex for chunk searches, improving retrieval accuracy and efficiency.
- Introduced a new `Capabilities` field in the `KnowledgeBaseInfo` struct to define the retrieval surfaces available for each knowledge base, guiding the agent's strategy selection.
- Enhanced the `grep_chunks` tool to support regex queries, allowing for more flexible and powerful text pattern matching in knowledge base chunks.
- Improved JSON handling in the `RepairJSON` function to address invalid escape sequences, particularly for regex patterns, ensuring robust parsing and error handling.
- Updated documentation and comments across various files to clarify usage and expectations for regex and knowledge base capabilities.
These changes significantly enhance the agent's ability to retrieve relevant information while ensuring the integrity of input data handling.
- Improved the `getKbIdForWiki` function to better handle multiple knowledge bases associated with a single slug, ensuring the most recent tool call's mapping is prioritized.
- Updated the `buildRuntimeContextBlock` function to include active knowledge bases and pinned documents, providing a clearer context for multi-turn interactions and preventing prompt injection.
- Added `registerLinkedSlugs` function to track outbound and inbound links for wiki pages, facilitating better resolution of slugs in the frontend without additional requests.
These enhancements significantly improve the accuracy and safety of knowledge base retrieval and context management in the agent system.
- Added the `isStructuralPage` function to identify wiki-level structural/meta pages (index, log) that should not be filtered by knowledge IDs.
- Updated the `pageIntersectsKnowledgeIDs` function to incorporate logic for structural pages, ensuring they are always accessible regardless of filtering.
- Enhanced the handling of pages with no SourceRefs to allow them through the filter, improving the accuracy of content retrieval.
These changes enhance the filtering logic for wiki pages, ensuring that essential structural pages remain accessible while refining the overall content management process.
- Added the WikiScope struct to define the retrieval scope for wiki knowledge bases, allowing for optional filtering by specific document IDs.
- Implemented NewWikiScopesFromKBIDs constructor for easier creation of WikiScope instances.
- Enhanced the wikiReadPageTool and wikiSearchTool to utilize WikiScope, improving the handling of knowledge base IDs and document filtering during page retrieval.
- Updated the agent service to carry document whitelists into the wiki scopes, ensuring that only relevant pages are surfaced based on user mentions.
These changes significantly improve the flexibility and accuracy of wiki page retrieval, enhancing the overall user experience when interacting with wiki content.
- Modified the XML output structure in the wikiReadPageTool to replace title and slug elements with a unified link format, enhancing clarity and consistency in the representation of wiki pages.
- Adjusted the wikiSearchTool to align with the new output format, ensuring that search results maintain the same structure for better integration and usability.
These changes streamline the output format for wiki pages, contributing to a more coherent and user-friendly experience when accessing wiki content.
- Updated the chat component to include a new class for handling sidebar collapse, improving layout responsiveness.
- Enhanced the wiki page retrieval logic to support multiple knowledge bases for the same slug, allowing for more comprehensive results.
- Introduced a mechanism to track ambiguous slugs across knowledge bases, improving clarity in search results.
These changes significantly improve the user experience in the chat interface and enhance the functionality of the wiki page retrieval system.
- Updated the agent system prompt to require wiki-links in citations, improving user navigation to source pages.
- Implemented logic in AgentStreamDisplay to handle wiki link clicks and keyboard interactions, facilitating seamless navigation to knowledge base wiki pages.
- Enhanced WikiBrowser to auto-select pages based on query parameters, improving user experience when accessing specific wiki content.
- Added localization support for new error messages related to knowledge base identification, ensuring clarity in user interactions.
These changes significantly improve the usability and functionality of the wiki navigation system, providing users with a more intuitive experience when accessing and citing wiki content.
- Introduced `enrichChunkImageInfo` function to populate image information for text chunks by retrieving data from child chunks, ensuring that image-related content is not lost during processing.
- Updated `reconstructContent` to `reconstructEnrichedContent`, allowing for the inclusion of OCR text and captions from images, improving the quality of content sent to the LLM.
- Added `writeDedupItemXML` and `xmlEscape` functions to format entity and concept entries as structured XML, enhancing clarity and preventing nonsensical merges in deduplication prompts.
- Refined the `deduplicateExtractedBatch` method to utilize the new XML formatting for better output consistency.
These changes significantly improve the handling of image data and the overall clarity of deduplication prompts, contributing to a more effective wiki content management system.
- Added new tools for wiki page editing, including writing, replacing text, renaming, and deleting pages, with corresponding data structures for each action.
- Enhanced the frontend with a new `WikiEditResult` component to display results of wiki edits, supporting multiple languages for improved accessibility.
- Updated localization files for English and Chinese to include new strings related to wiki actions.
- Modified existing tools to return structured data for wiki actions, improving the clarity and usability of the output messages.
These changes significantly enhance the wiki editing capabilities, providing users with a more robust and user-friendly experience when managing wiki content.
- Updated the agent system prompt to refine the workflow for fixing issues, emphasizing the need to verify if issues still exist before making edits.
- Introduced a new `embeddedMode` prop in the frontend components to manage UI behavior based on the context of use.
- Simplified issue fix prompts in multiple languages for clarity, ensuring users receive concise instructions for resolving issues.
- Enhanced the WikiBrowser component to improve the display of issues and actions, including updated icons and streamlined interaction elements.
These changes significantly improve the user experience and functionality of the Wiki Fixer agent, fostering more efficient issue resolution and content management.
- Added a new built-in agent, "Wiki Fixer," designed to repair and optimize Wiki pages based on linter issues, with multilingual support for enhanced accessibility.
- Implemented a corresponding system prompt detailing the agent's role, mission, and workflow for effective issue resolution.
- Introduced new API functions for listing and updating wiki issues, allowing for better management of content conflicts and errors.
- Enhanced the frontend with new UI elements to display pending issues and facilitate auto-fixing, improving user interaction with the Wiki content.
These changes significantly enhance the agent's capabilities for maintaining the accuracy and quality of Wiki pages, fostering a more reliable knowledge base.
- Added a new tool, `wiki_flag_issue`, enabling users to report factual errors, mixed entities, or outdated information on wiki pages.
- Updated the agent system prompt and tool definitions to include the new tool, enhancing the agent's capabilities for maintaining wiki accuracy.
- Implemented backend functionality for creating, listing, and updating the status of flagged issues, ensuring effective tracking and resolution.
These changes significantly improve the agent's ability to manage and report issues within the wiki, fostering a more reliable knowledge base.
- Updated the `WikiPageModifyPrompt` to include a critical conflict check, ensuring that new information pertains to the same core entity before merging.
- Enhanced the `WikiDeduplicationPrompt` to emphasize the importance of not merging different products or versions, reinforcing the principle that related does not equal the same.
- These changes improve the accuracy of content updates and deduplication processes, ensuring better management of wiki information.
- Added a new tool, `wiki_read_source_doc`, allowing agents to access specific source documents for detailed information retrieval when wiki page content is insufficient.
- Updated the agent system prompt and tool definitions to incorporate the new tool, enhancing the agent's capabilities for in-depth knowledge extraction.
- Modified existing tools to support the new functionality, ensuring seamless integration within the agent's workflow.
These changes significantly improve the agent's ability to provide accurate and detailed responses by leveraging source documents alongside wiki content.
- Updated the agent system prompt to clarify the workflow for knowledge retrieval, emphasizing the use of `wiki_search` and `wiki_read_page` tools for specific queries and general overviews.
- Modified the `wikiReadPageTool` to support reading multiple wiki pages simultaneously, improving efficiency in fetching content.
- Enhanced the `wikiSearchTool` to utilize PostgreSQL POSIX regular expressions for more effective search queries, allowing for complex pattern matching.
- Adjusted the `wikiPageRepository` to replace `ILIKE` with regex matching for search queries, increasing the precision of search results.
These changes significantly improve the agent's ability to retrieve and synthesize information from the wiki, enhancing user interactions and response accuracy.
- Added a new constraint to the agent system prompt emphasizing the need for fresh searches and reads for each question, ensuring up-to-date information retrieval.
- Updated the agent tool configuration to include `ToolWikiSearch` and `ToolWikiReadPage`, enhancing the agent's capabilities for accessing and utilizing wiki content effectively.
These changes improve the agent's performance in providing accurate and current responses based on wiki knowledge.
- Introduced a new built-in agent, "Wiki Researcher," designed for navigating and answering questions based on Wiki knowledge bases, complete with multilingual support.
- Added a corresponding system prompt that outlines the agent's role, mission, and workflow for effective knowledge graph traversal.
- Updated the agent configuration to include specific tools and parameters tailored for the Wiki Researcher, enhancing its functionality and user interaction.
- Removed deprecated wiki tools from the agent service to streamline the toolset and improve performance.
These changes significantly enhance the capabilities of the agent framework, providing users with a specialized tool for in-depth Wiki-based research.
- Introduced a new built-in agent, "Wiki Researcher," designed for navigating and answering questions based on Wiki knowledge bases, complete with multilingual support.
- Added a corresponding system prompt that outlines the agent's role, mission, and workflow for effective knowledge graph traversal.
- Updated the agent configuration to include specific tools and parameters tailored for the Wiki Researcher, enhancing its functionality and user interaction.
- Removed deprecated wiki tools from the agent service to streamline the toolset and improve performance.
These changes significantly enhance the capabilities of the agent system, providing users with a specialized tool for in-depth research and information retrieval from Wiki sources.
- Updated the `WikiDeduplicationPrompt` to clarify the criteria for identifying exact duplicates, emphasizing strict matching of real-world entities and concepts.
- Improved the `appendLogEntry` method to include a summary parameter for better context in log entries, enhancing traceability of operations.
- Consolidated log entry creation for both retraction and ingestion operations, ensuring chronological clarity in the log.
- Implemented validation for slug merges to prevent mismatches based on entity types, improving the accuracy of deduplication.
These changes enhance the clarity and reliability of the wiki ingestion process, leading to more accurate content management.
- Renamed `WikiPageUpdatePrompt` to `WikiPageModifyPrompt` to better reflect its functionality of adding new information and removing outdated content in a single operation.
- Enhanced the instructions for both `WikiPageModifyPrompt` and `WikiPageRetractPrompt` to clarify the handling of additions and retractions, ensuring accurate content updates.
- Consolidated the logic for enqueuing retraction tasks in the `cleanupWikiOnKnowledgeDelete` method to streamline the process of managing affected pages.
- Removed the `rebuildWikiIndexSimple` function to simplify the codebase, as its functionality is no longer needed with the new ingestion approach.
These changes improve the clarity and efficiency of the wiki content management process, enhancing overall system performance.
- Introduced `pending_tasks` and `is_active` fields in the `WikiStats` interface to track the number of tasks waiting for processing and the current activity status of the wiki ingestion.
- Updated localization files for English, Korean, Russian, and Chinese to include a new message for displaying the number of pending tasks in the wiki queue.
- Enhanced the `WikiBrowser` component to display the queue status, improving user awareness of ongoing tasks.
- Implemented polling logic to refresh wiki stats periodically when there are pending tasks or active ingestion, ensuring up-to-date information is presented.
These changes enhance the functionality and user experience of the wiki management system by providing real-time insights into task status.
- Modified the `extractEntitiesAndConcepts` method to return a map of slugs to extracted items, including aliases for improved wiki-link generation.
- Updated the `processOneDocument` method to handle slug items with aliases, enhancing the clarity of generated summaries.
- Adjusted the `injectCrossLinks` method to utilize match text for cross-linking, ensuring accurate references in content.
These changes improve the accuracy and usability of wiki links and summaries by incorporating alias management.
- Updated the `picture-preview.vue` component to conditionally render images based on the `reviewUrl` prop, improving performance and usability.
- Integrated image preview functionality into the `WikiBrowser` component, allowing users to view images in a modal when clicked.
- Added references for `drawerBodyRef` and `readerBodyRef` to facilitate image loading and hydration, ensuring images are displayed correctly.
- Enhanced the `prompts_wiki.go` file to include new image handling rules for summaries, ensuring images are contextually relevant in generated content.
These changes improve the user experience by providing a seamless image viewing option within the WikiBrowser interface.
- Enhanced the `renderMarkdown` function to support the new `[[slug|display name]]` format for wiki links, improving link clarity and usability.
- Adjusted CSS styles for wiki links to provide a more intuitive hover effect and visual distinction.
- Updated prompts in the `prompts_wiki.go` file to reflect the new wiki link syntax, ensuring consistency across the application.
These changes improve the overall user experience by making wiki links more informative and visually appealing.
- Updated the WikiSummaryPrompt to clarify the wiki-link syntax, specifying the use of slugs for referenced names.
- Modified the extractEntitiesAndConcepts method to return a mapping of slugs to display names, improving the accuracy of wiki-link references in summaries.
- Adjusted the summary content generation to include display names alongside slugs, enhancing the readability and context of generated summaries.
These changes improve the clarity and usability of wiki summaries by ensuring accurate and consistent link references.
wizardchen