feat: schema_version 3 with DE/EN field descriptions
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Signed-off-by: flemming-it <sf@flemming.it>
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1 changed files with 85 additions and 40 deletions
125
module.yaml
125
module.yaml
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@ -1,9 +1,8 @@
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schema_version: 2
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schema_version: 3
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provider: fai
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name: orchestrator-llm
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version: 0.3.1
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# Capability provided by this module.
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provides:
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- capability: orchestrator.plan
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version: 0.3.0
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@ -11,56 +10,102 @@ provides:
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# Capabilities the plans this module emits typically reference.
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# Advisory only — Studio surfaces "you'll also want X" when the
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# operator installs orchestrator-llm; `fai admin doctor` flags
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# unmet entries; the hub does NOT block install. See
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# docs/architecture/store.md → "Module dependencies".
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# unmet entries; the hub does NOT block install.
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consumes:
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- capability: llm.chat
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version: "^0"
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why: "orchestrator-emitted plans dispatch llm.chat steps for downstream LLM-driven work; a flow that runs the plan unmodified needs an llm.chat provider installed."
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# Inputs the invoke function accepts.
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inputs:
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goal: text
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# LLM HTTP endpoint, e.g. "http://localhost:11434/api/chat"
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# for Ollama, "https://api.openai.com/v1/chat/completions",
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# or "https://api.anthropic.com/v1/messages".
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llm_endpoint: text
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# Model identifier, e.g. "qwen2.5:14b" for Ollama or "gpt-4o-mini".
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llm_model: text
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# Optional bearer token for cloud providers. Empty string means
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# no Authorization header is sent.
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llm_api_key: text
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# Optional JSON-encoded list of installed capabilities. If
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# omitted or empty, the module plans without capability context.
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available_capabilities: text
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# Optional JSON-encoded list of all known store capabilities
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# (installed + planned + alpha). Used when the orchestrator
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# needs to suggest installations.
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store_capabilities: text
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goal:
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type: text
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description:
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en: Operator-stated goal in natural language — what the resulting flow should accomplish.
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de: Ziel in natürlicher Sprache — was der erzeugte Flow erreichen soll.
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llm_endpoint:
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type: text
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description:
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en: |
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LLM HTTP endpoint, e.g. "http://localhost:11434/api/chat"
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for Ollama, "https://api.openai.com/v1/chat/completions",
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or "https://api.anthropic.com/v1/messages".
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de: |
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LLM-HTTP-Endpunkt, z. B. "http://localhost:11434/api/chat"
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für Ollama, "https://api.openai.com/v1/chat/completions"
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oder "https://api.anthropic.com/v1/messages".
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llm_model:
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type: text
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description:
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en: Model identifier, e.g. "qwen2.5:14b" for Ollama or "gpt-4o-mini".
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de: Modell-Identifier, z. B. "qwen2.5:14b" (Ollama) oder "gpt-4o-mini".
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llm_api_key:
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type: text
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description:
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en: Optional bearer token for cloud providers. Empty = no Authorization header.
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de: Optionaler Bearer-Token für Cloud-Provider. Leer = kein Authorization-Header.
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available_capabilities:
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type: text
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description:
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en: |
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Optional JSON-encoded list of installed capabilities.
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Omit or pass an empty string to plan without capability
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context.
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de: |
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Optional JSON-codierte Liste der installierten
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Capabilities. Leer = ohne Capability-Kontext planen.
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store_capabilities:
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type: text
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description:
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en: |
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Optional JSON-encoded list of all known store
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capabilities (installed + planned + alpha). Used when
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the orchestrator needs to suggest installations.
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de: |
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Optional JSON-codierte Liste aller bekannten Store-
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Capabilities (installiert + geplant + alpha). Nötig,
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wenn der Orchestrator Installationen vorschlagen soll.
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# Outputs produced.
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outputs:
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# JSON-encoded Plan compatible with `fai_hub::plan::Plan`.
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plan: json
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# The endpoint the plan was generated against. Empty when the
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# deterministic stub path (no llm_endpoint) ran.
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model_endpoint: text
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# The model name as supplied to the LLM API.
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model_name: text
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# SHA-256 digest of the served Ollama model, when reachable.
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# Empty for cloud providers (OpenAI / Anthropic do not expose
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# a digest API) and for the deterministic stub path. Together
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# with model_endpoint and model_name this answers the audit
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# question "which exact model produced this plan?"
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model_digest: text
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plan:
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type: json
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description:
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en: JSON-encoded Plan compatible with `fai_hub::plan::Plan`.
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de: JSON-codierter Plan, kompatibel mit `fai_hub::plan::Plan`.
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model_endpoint:
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type: text
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description:
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en: |
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The endpoint the plan was generated against. Empty when
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the deterministic stub path (no llm_endpoint) ran.
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de: |
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Endpunkt, gegen den der Plan erzeugt wurde. Leer beim
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deterministischen Stub-Pfad (ohne llm_endpoint).
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model_name:
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type: text
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description:
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en: The model name as supplied to the LLM API.
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de: An die LLM-API übergebener Modellname.
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model_digest:
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type: text
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description:
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en: |
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SHA-256 digest of the served Ollama model, when
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reachable. Empty for cloud providers (OpenAI / Anthropic
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do not expose a digest API) and for the deterministic
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stub path. Together with model_endpoint and model_name
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this answers the audit question "which exact model
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produced this plan?"
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de: |
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SHA-256-Digest des bedienten Ollama-Modells, wenn
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erreichbar. Leer für Cloud-Provider (OpenAI / Anthropic
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bieten keine Digest-API) und für den deterministischen
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Stub-Pfad. Zusammen mit model_endpoint + model_name
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beantwortet das die Audit-Frage "welches genaue Modell
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hat diesen Plan erzeugt?"
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# Permissions required.
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#
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# The module makes outbound HTTP to the configured LLM endpoint.
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# Default declarations cover the common providers (cloud OpenAI,
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# Anthropic, local Ollama on loopback). Operators with different
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# LLM endpoints add a host-level entry via operator config
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# (Phase 1+) — for Phase 0.5 they fork module.yaml.
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permissions:
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- "net: api.openai.com"
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- "net: api.anthropic.com"
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