ankn
a5f8fb49ab
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.
351 lines
10 KiB
Python
351 lines
10 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from datetime import date, datetime
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from typing import Any
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from unittest.mock import AsyncMock
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import pytest
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import teamlandkarte_mcp.mcp_server as mcp_mod
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from teamlandkarte_mcp.mcp_server import build_server
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def _result_to_text(result: Any) -> str:
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if isinstance(result, tuple) and len(result) == 2:
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content, structured = result
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if isinstance(structured, dict) and isinstance(structured.get("result"), str):
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return structured["result"]
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if isinstance(content, list) and content:
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text = getattr(content[0], "text", None)
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if isinstance(text, str):
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return text
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return str(result)
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async def _call_tool(
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srv: Any,
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name: str,
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args: dict[str, Any] | None = None,
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) -> str:
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if args is None:
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args = {}
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return _result_to_text(await srv.call_tool(name, args))
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@pytest.mark.asyncio
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async def test_integration_capacity_search_filter_and_pagination(
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monkeypatch,
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tmp_path,
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) -> None:
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cfg = tmp_path / "config.toml"
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cfg.write_text(
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"""
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[database]
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host='x'
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port=1
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username='u'
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password='p'
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backend='trino'
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[matching]
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competence_weight=0.8
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role_weight=0.2
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require_confirmation=false
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[cache]
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db_ttl_hours=1
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search_ttl_minutes=60
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max_size=100
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""".strip(),
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encoding="utf-8",
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)
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from teamlandkarte_mcp.models import Capacity
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class _FakeDB:
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def test_connection(self) -> None:
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return
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def get_table_columns(self, table: str) -> list[str]:
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if table == "teamlandkarte_v_capacity_roles_latest":
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return ["name", "active", "staffing_board_relevant"]
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if table == "teamlandkarte_v_capacities_latest":
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return ["creation_date"]
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if table == "teamlandkarte_v_teams_latest":
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return [
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"team_id",
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"ouid",
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"about_us",
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"offerings",
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"interests",
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"focus_name",
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]
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if table == "teamlandkarte_v_teammeter_organizational_units_latest":
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return ["id", "name"]
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if table == "teamlandkarte_v_teammeter_team_competences_latest":
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return ["ouid", "competence_id", "top_competency"]
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if table == "teamlandkarte_v_team_references_latest":
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return ["ouid", "partner_id", "projects"]
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return []
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def get_all_role_names(self) -> list[str]:
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return ["X"]
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def get_all_competence_names(self) -> list[str]:
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return ["A"]
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def get_open_tasks(self, limit: int = 20):
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return []
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def get_all_capacities_with_competences(self):
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return [
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Capacity(
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id=1,
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owner_name="A",
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role_name="X",
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role_level=None,
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begin_date=date(2025, 2, 1),
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end_date=date(2025, 7, 31),
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competences=["A"],
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),
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Capacity(
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id=2,
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owner_name="B",
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role_name="X",
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role_level=None,
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begin_date=date(2025, 3, 15),
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end_date=date(2025, 6, 15),
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competences=["A"],
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),
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]
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def get_recent_free_capacities(self, limit: int = 20):
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return []
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monkeypatch.setattr(
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mcp_mod,
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"create_db_client",
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lambda *_args, **_kwargs: _FakeDB(),
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)
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# Mock LLM chat_completion to avoid network calls.
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monkeypatch.setattr(
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"teamlandkarte_mcp.azure.openai_client.AzureOpenAIClient.chat_completion",
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AsyncMock(return_value='{"similarity": 1.0}'),
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)
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srv = build_server(str(cfg))
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res = await _call_tool(
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srv,
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"find_matching_capacities",
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{
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"role_name": "X",
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"competences": ["A"],
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"date_start": "2025-03-01",
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"date_end": "2025-06-30",
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},
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)
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assert "SEARCH_ID=" in res
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search_id = res.split("SEARCH_ID=")[1].splitlines()[0].strip()
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filtered = await _call_tool(
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srv,
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"filter_search_results",
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{"search_id": search_id, "is_fully_available": True},
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)
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assert "FILTER_ID=" in filtered
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filter_id = filtered.split("FILTER_ID=")[1].splitlines()[0].strip()
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assert "Filtered total results: 1" in filtered
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page = await _call_tool(
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srv,
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"get_results_by_category",
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{
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"search_id": search_id,
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"filter_id": filter_id,
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"category": "Low",
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"page": 1,
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"page_size": 20,
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},
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)
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assert "Total items in category: 1" in page
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assert "| 1 |" in page
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assert "| 2 |" not in page
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@pytest.mark.asyncio
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async def test_integration_task_search_filters_and_pagination(
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monkeypatch,
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tmp_path,
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) -> None:
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cfg = tmp_path / "config.toml"
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cfg.write_text(
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"""
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[database]
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host='x'
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port=1
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username='u'
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password='p'
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backend='trino'
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[matching]
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competence_weight=0.8
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role_weight=0.2
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require_confirmation=false
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[cache]
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db_ttl_hours=1
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search_ttl_minutes=60
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max_size=100
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""".strip(),
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encoding="utf-8",
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)
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@dataclass
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class _Task:
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id: str
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name: str | None = None
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title: str = ""
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description: str = ""
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created_date: datetime = datetime(2025, 1, 1)
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start_date: date | None = None
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end_date: date | None = None
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skills: list[str] = None # type: ignore[assignment]
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def __post_init__(self):
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if self.skills is None:
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self.skills = []
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class _FakeDB:
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def test_connection(self) -> None:
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return
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def get_table_columns(self, table: str) -> list[str]:
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if table == "teamlandkarte_v_capacity_roles_latest":
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return ["name", "active", "staffing_board_relevant"]
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if table == "teamlandkarte_v_capacities_latest":
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return ["creation_date"]
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if table == "teamlandkarte_v_teams_latest":
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return [
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"team_id",
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"ouid",
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"about_us",
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"offerings",
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"interests",
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"focus_name",
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]
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if table == "teamlandkarte_v_teammeter_organizational_units_latest":
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return ["id", "name"]
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if table == "teamlandkarte_v_teammeter_team_competences_latest":
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return ["ouid", "competence_id", "top_competency"]
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if table == "teamlandkarte_v_team_references_latest":
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return ["ouid", "partner_id", "projects"]
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return []
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def get_all_role_names(self) -> list[str]:
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return ["Frontend Developer", "Backend Engineer"]
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def get_all_competence_names(self) -> list[str]:
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return ["React", "TypeScript", "Python", "PostgreSQL"]
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def get_open_tasks(self, limit: int = 20):
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tasks = [
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_Task(
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id="T1",
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title="Frontend Developer",
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description="React and TypeScript",
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created_date=datetime(2025, 1, 1),
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start_date=date(2025, 5, 1),
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end_date=date(2025, 7, 31),
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skills=["React", "TypeScript"],
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),
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_Task(
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id="T2",
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title="Backend Engineer",
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description="Python and PostgreSQL",
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created_date=datetime(2025, 1, 1),
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start_date=date(2025, 5, 1),
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end_date=date(2025, 7, 31),
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skills=["Python"],
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),
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]
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return tasks if limit == 0 else tasks[:limit]
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def get_task_by_id(self, task_id: str): # pragma: no cover
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return None
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def get_task_by_name(self, name: str): # pragma: no cover
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return None
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def get_all_capacities_with_competences(self): # pragma: no cover
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return []
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def get_recent_free_capacities(
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self,
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limit: int = 20,
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): # pragma: no cover
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return []
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def get_capacity_by_id(self, capacity_id):
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from teamlandkarte_mcp.models import Capacity
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return Capacity(
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id=1,
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owner_name="A",
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role_name="Frontend Developer",
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role_level=None,
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begin_date=date(2025, 4, 1),
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end_date=date(2025, 8, 31),
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competences=["React", "TypeScript"],
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)
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monkeypatch.setattr(
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mcp_mod,
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"create_db_client",
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lambda *_args, **_kwargs: _FakeDB(),
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)
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# Mock LLM chat_completion to avoid network calls.
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monkeypatch.setattr(
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"teamlandkarte_mcp.azure.openai_client.AzureOpenAIClient.chat_completion",
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AsyncMock(return_value='{"similarity": 1.0}'),
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)
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srv = build_server(str(cfg))
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res = await _call_tool(srv, "find_matching_tasks", {"capacity_id": 1})
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assert "SEARCH_ID=" in res
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search_id = res.split("SEARCH_ID=")[1].splitlines()[0].strip()
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out = await _call_tool(
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srv,
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"filter_search_results",
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{"search_id": search_id, "task_text_filter": "typescript"},
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)
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assert "Filtered total results: 1" in out
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assert "T1" in out
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assert "T2" not in out
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out2 = await _call_tool(
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srv,
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"filter_search_results",
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{"search_id": search_id, "task_competence_filter": ["python"]},
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)
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assert "Filtered total results: 1" in out2
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assert "T2" in out2
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page = await _call_tool(
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srv,
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"get_results_by_category",
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{
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"search_id": search_id,
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"category": "Top",
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"page": 1,
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"page_size": 20,
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},
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)
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assert "Total items in category:" in page
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assert "task_id" in page
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