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.
85 lines
2.5 KiB
TOML
85 lines
2.5 KiB
TOML
# Teamlandkarte MCP configuration
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# Copy this file to `config.toml` and adjust values.
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#
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# Credentials are never stored in this file. Provide them via environment
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# variables (e.g. via `.env`):
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# - DATA_LAKE_USERNAME
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# - DATA_LAKE_PASSWORD
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# - AZURE_OPENAI_LLM_API_KEY
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[database]
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backend = "trino"
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host = "trino.example.local"
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port = 443
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http_scheme = "https"
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verify_ssl = true
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catalog = "hive"
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schema = "tier1_open_lake"
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connect_timeout = 10
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pool_size = 4
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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 = true
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# Default matching method used when callers do not pass `matching_method`.
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# Allowed values:
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# - "score" : BM25 + LLM role similarity (numeric scores).
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# - "llm_fulltext" : LLM-based full-text matching with rationale.
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default_method = "score"
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[matching.thresholds]
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top = 0.8
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good = 0.65
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partial = 0.5
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low = 0.3
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[matching.fuzzy]
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min_similarity = 0.7
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[matching.similarity]
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# When true, an LLM pre-expands each candidate's competence list with
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# canonical equivalents of required competences it already covers
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# (synonyms, abbreviations, cross-language). The expansion is ephemeral
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# and never persisted. Requires AZURE_OPENAI_LLM_API_KEY env var.
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# Default: false.
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use_auto_tagging = false
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[matching.team]
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# Gewichtungsfaktor für Top-Kompetenzen im Score-basierten Team-Matching.
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# Wird nur von `find_matching_teams` (Profile_Type = "team") verwendet und
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# beeinflusst die Capacity-Suche nicht.
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# Der Wert muss numerisch und >= 1.0 sein. Default: 1.5.
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top_competency_weight = 1.5
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[cache]
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db_ttl_hours = 12
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search_ttl_minutes = 60
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max_size = 100
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[azure_openai]
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# Azure OpenAI endpoint configuration.
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#
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# IMPORTANT:
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# - `endpoint` must be your Azure OpenAI resource endpoint.
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# - `chat_deployment` must be set to a valid Azure deployment name.
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#
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# Credentials are read from:
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# - AZURE_OPENAI_LLM_API_KEY
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endpoint = "https://YOUR-RESOURCE.openai.azure.com"
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# Azure OpenAI API version (must be supported by your resource).
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api_version = "2024-02-15-preview"
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# Chat/LLM deployment name (e.g. "gpt-4.1"). Required.
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# API key must be provided via AZURE_OPENAI_LLM_API_KEY environment variable.
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chat_deployment = ""
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# Optional: include a cost summary block in certain tool outputs.
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# This always remains approximate unless you configure prices in CostTracker.
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# Defaults to false.
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show_costs_in_output = false
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# Maximale Anzahl paralleler LLM-Anfragen (1-50, Standard: 5).
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# Höhere Werte beschleunigen das Matching, können aber Rate-Limits auslösen.
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max_concurrency = 25 |