ankn/Orchestrator
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Migrate all repos into monorepo context folders

Browse Source 
Bahn: aisupport, Analyse-O2C-C2S, awesome-bahn-mcp-servers, beam-mcp,
      Confluence_Bot, db-planet-mcp-server, O2C-Harness, project-audit,
      Projekt-KIQ-HP, teamlandkarte-mcp
Dhive: Jury-Voting
Privat: CV, NoteGraph (NOTE: NoteGraph needs complete redo after consolidation)
Shared: AI-Orchestrator, OrgMyLife, power_skills_and_more
Shared/references: symphony (read-only)

Bahn repos remain available as independent remotes - this monorepo
pulls them in via subtree, the originals are untouched.
This commit is contained in:
ankn
2026-06-30 20:39:52 +02:00
parent 2f2b295531
commit a5f8fb49ab
1717 changed files with 447332 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
bahn/teamlandkarte-mcp/openspec/changes/add-capacity-to-task-matching-tools/tasks.md
+149
View File
@@ -0,0 +1,149 @@
# Tasks: Add capacity→task matching tools and embedding-based inference
> Change: `add-capacity-to-task-matching-tools`
>
> Status: **Implemented**
## Phase 1: Requirements + Configuration decisions
- [x] 1.1 Define `list_free_capacities` ordering precisely:
- order by most recent `creation_date` (descending)
- [x] 1.2 Confirm “Owner/Team” display:
- use `owner_name` (contains the team name)
- [x] 1.3 Introduce a new role inference tool and remove the old:
- add `infer_primary_role(task_id? | task_text?)` that returns the single closest role as a Markdown table with `Role | Similarity` columns
- remove `infer_roles(...)` MCP tool completely (no deprecation period)
- remove `TaskAnalyzer.extract_ranked_roles()` method completely
- update `extract_requirements()` and other callers to use new primary-role inference
- [x] 1.4 Add configuration for competence inference:
- `matching.inference.max_competences` (int, default: 8; if not specified, no limit)
- `matching.inference.min_similarity` (float in [0,1], default: 0.4; if not specified, no threshold)
- at least one parameter MUST be specified to avoid unbounded results
- selection rule: pick top X among those >= threshold when both are set
- [x] 1.5 Define startup-only refresh behavior:
- on startup embed only cache-missing role/competence vocab entries
- on startup embed **all open tasks** (title+description by task_id)
- at runtime still embed on-demand for misses (strict failure semantics)
## Phase 2: Data Lake queries (roles, competences, capacities)
- [x] 2.0 Verify Data Lake schema:
- confirm `teamlandkarte_v_capacity_roles_latest` has columns: `name`, `active`, `staffing_board_relevant`
- confirm capacities view has `creation_date` column
- [x] 2.1 Add `TrinoClient.get_recent_free_capacities(limit)` query returning:
- `capacity_id`, `owner_name` (team), `role_name`, `creation_date`, `begin_date`, `end_date`, `competences[]`
- ordering: `creation_date DESC`
- [x] 2.2 Add `TrinoClient.get_capacity_by_id(capacity_id)` query returning the same fields.
- [x] 2.3 Add `TrinoClient.get_all_role_names()`:
- source: `teamlandkarte_v_capacity_roles_latest`
- filter: `active=true AND staffing_board_relevant=true`
- return unique, non-empty role names
- [x] 2.4 Add `TrinoClient.get_all_competence_names()`:
- source: `beschaffungstool_kmp_skill_latest.skillname__c`
- return unique, non-empty competence names
- [x] 2.5 Add unit tests for SQL read-only guard + query shape (where applicable).
## Phase 3: Startup embedding preload (vocabularies + tasks)
- [x] 3.1 Define stable cache-key scheme (explicit format as documented in design.md):
- role vocab entries: `f"role_vocab:{model}:{dims}:{normalized_role_name}"`
- competence vocab entries: `f"comp_vocab:{model}:{dims}:{normalized_competence_name}"`
- task text embeddings by task_id: `f"task_id:{model}:{dims}:{task_id}"`
- [x] 3.2 Implement `VocabularyCache` component (`src/teamlandkarte_mcp/matching/vocabulary.py`):
- fetch role vocabulary + competence vocabulary from Trino
- normalize/deduplicate
- embed only cache-missing entries (batch + chunking via `SimilarityEngine.prefetch_embeddings(...)`)
- store into SQLite embedding cache
- keep in-memory memoization for fast repeated inference
- invoked from `build_server()` after DB + similarity engine init
- [x] 3.3 Implement a “task embedding preload” routine executed on startup:
- fetch **all open tasks** (no limit)
- build `task_text = title + "\n\n" + description` (title optional)
- embed only cache-missing `task_id` vectors
- store into SQLite embedding cache
- [x] 3.4 Runtime fallback:
- if a role/competence/task embedding is missing during a tool call, embed on-demand (strict semantics)
- [x] 3.5 Tests:
- preload embeds only cache misses
- preload writes to SQLite
- missing-at-runtime triggers on-demand embedding
## Phase 4: Embedding-only inference (roles + competences)
- [x] 4.1 Implement primary role inference against role vocabulary:
- input: combined `title+description` (or description-only for ad-hoc)
- output: single closest role with similarity score as Markdown table: `Role | Similarity`
- [x] 4.2 Add a new MCP tool:
- `infer_primary_role(task_id? | task_text?)`
- returns: Markdown table `Role | Similarity` (single best matching role)
- validation: exactly one of `task_id` or `task_text` must be provided
- [x] 4.3 Remove deprecated tools and methods:
- remove `infer_roles(...)` MCP tool completely
- remove `TaskAnalyzer.extract_ranked_roles()` method completely
- [x] 4.4 Update callers to use new primary-role inference:
- update `get_task_details` to use `infer_primary_role`
- update `extract_requirements()` to use new primary-role inference
- update any internal helpers relying on `TaskAnalyzer.extract_ranked_roles()`
## Phase 5: Rework task validation (embedding-only)
- [x] 5.1 Replace chat-based extraction in `validate_task_requirements` / `extract_requirements_from_task` with embedding-based inference:
- roles: infer primary role via role vocabulary (Markdown table output)
- competences: infer competences via competence vocabulary with max X and threshold (Markdown table output)
- [x] 5.2 Update output format:
- keep current table-first display
- add inferred primary role as Markdown table: `Role | Similarity` (single row)
- add inferred competences as Markdown table: `Competence | Similarity` (descending order by similarity)
- [x] 5.3 Tests:
- validation uses embeddings path only (no chat calls)
- respects max X and threshold rules
- output includes role and competence similarity tables
## Phase 6: New MCP tools (capacity browsing + capacity→task matching)
- [x] 6.1 Implement `list_free_capacities(limit=20)`:
- ordering: `creation_date DESC`
- Markdown table columns: `capacity_id`, `Owner/Team`, `Role`, `Competences`, `Availability`
- stable empty-table handling (dummy row)
- [x] 6.2 Implement `get_capacity_details(capacity_id)`:
- table-first, same fields as list
- include a “Next steps” pointer to `find_matching_tasks(capacity_id=...)`
- [x] 6.3 Implement `find_matching_tasks(capacity_id)`:
- signature: takes only `capacity_id` (no optional params)
- fetch capacity + all open tasks
- infer each task’s primary role via embedding similarity (title+description)
- infer each task’s competences via embedding similarity (title+description) with max/threshold
- compute a similarity score (role + competences) and categorize results
- return output as Markdown table with columns:
- `task_id`, `Title`, `Required Competences`, `Availability`, `Score`, `Category`
- results are sorted by similarity score (descending)
- output structure matches `find_matching_capacities` (includes summary counts table + results table for first non-empty category)
- paginated via same search session conventions used by `find_matching_capacities`
- [x] 6.4 Tests for new tools:
- `list_free_capacities`: ordering by `creation_date DESC`, empty-table handling
- `get_capacity_details`: not-found handling, "Next steps" section
- `find_matching_tasks`: categorization (Top/Good/Partial/Low), search session conventions, table structure, score sorting
## Phase 7: Remove Azure chat API
- [x] 7.1 Remove chat config fields and environment variables if no longer needed (`AZURE_OPENAI_LLM_API_KEY`, chat deployment, chat codepaths).
- [x] 7.2 Delete/retire chat client methods and `TaskAnalyzer` chat-based methods.
- [x] 7.3 Update docs to remove chat setup instructions.
- [x] 7.4 Ensure all gates pass (ruff/mypy/pytest).
## Phase 8: Documentation + assistant prompt + architecture
- [x] 8.1 Update `README.md`:
- describe new tools and capacity→task workflow
- document startup embedding preload and inference config knobs
- [x] 8.2 Update `docs/assistant_system_prompt.md`:
- add guidance for new tools and matching direction
- update role/competence inference description (embeddings-only)
- [x] 8.3 Update architecture docs (Arc42 / design docs):
- reflect removal of chat API
- describe vocab/task embedding preload and cache keys
## Phase 9: OpenSpec hygiene
- [x] 9.1 Update spec deltas to reflect confirmed tool shapes + config.
- [x] 9.2 Run `openspec validate add-capacity-to-task-matching-tools --strict`.