feat: schema_version 3 with DE/EN field descriptions

Editor renders the description in the active locale as a
tooltip on each port. EN remains the default; DE peer
provided for every field.

Signed-off-by: flemming-it <sf@flemming.it>

module.yaml

@@ -1,4 +1,4 @@
-schema_version: 2
+schema_version: 3
 provider: fai
 name: llm-chat
 version: 0.1.0
@@ -8,38 +8,81 @@ provides:
   - capability: llm.chat
     version: 0.1.0
 
-# Inputs the invoke function accepts.
+# Declared inputs in verbose v3 form. Studio renders the
+# description in the active locale as a tooltip on each
+# port; the editor falls back to the English description
+# when no peer is configured.
 inputs:
-  # The user-facing prompt text.
+  prompt:
-  prompt: text
+    type: text
-  # Ollama-shaped /api/chat endpoint, e.g.
+    description:
-  # "http://localhost:11434/api/chat".
+      en: The user-facing prompt text the model should respond to.
-  endpoint: text
+      de: Der vom Modell zu beantwortende Prompt-Text.
-  # Model identifier as registered with the endpoint, e.g.
+  endpoint:
-  # "qwen2.5:14b" or "llama3.1:8b".
+    type: text
-  model: text
+    description:
-  # Optional bearer token for cloud-hosted endpoints. Empty
+      en: |
-  # string means no Authorization header is sent.
+        Ollama-shaped /api/chat endpoint, e.g.
-  api_key: text
+        "http://localhost:11434/api/chat".
-  # Optional system prompt. Empty string omits the system
+      de: |
-  # message and lets the model use its built-in default.
+        Ollama-kompatibler /api/chat-Endpunkt, z. B.
-  system_prompt: text
+        "http://localhost:11434/api/chat".
+  model:
+    type: text
+    description:
+      en: Model identifier as registered with the endpoint, e.g. "qwen2.5:14b" or "llama3.1:8b".
+      de: Modell-Identifier wie beim Endpunkt registriert, z. B. "qwen2.5:14b" oder "llama3.1:8b".
+  api_key:
+    type: text
+    description:
+      en: |
+        Optional bearer token for cloud-hosted endpoints.
+        Empty string means no Authorization header is sent.
+      de: |
+        Optionaler Bearer-Token für Cloud-Endpunkte.
+        Leer = kein Authorization-Header gesendet.
+  system_prompt:
+    type: text
+    description:
+      en: |
+        Optional system prompt. Empty string omits the system
+        message and lets the model use its built-in default.
+      de: |
+        Optionaler System-Prompt. Leer = das Modell verwendet
+        seinen eingebauten Default.
 
 # Outputs produced.
 outputs:
-  # The assistant's plain-text reply.
+  response:
-  response: text
+    type: text
-  # The endpoint the response was generated against. Used for
+    description:
-  # audit correlation.
+      en: The assistant's plain-text reply.
-  model_endpoint: text
+      de: Die Klartext-Antwort des Modells.
-  # The model identifier as supplied to the LLM API.
+  model_endpoint:
-  model_name: text
+    type: text
-  # SHA-256 digest of the served Ollama model, when reachable.
+    description:
-  # Empty for non-Ollama endpoints (OpenAI / Anthropic do not
+      en: The endpoint the response was generated against. Used for audit correlation.
-  # expose a digest API). Together with model_endpoint and
+      de: Der Endpunkt, gegen den die Antwort erzeugt wurde — für Audit-Korrelation.
-  # model_name this answers the audit question "which exact
+  model_name:
-  # model produced this response?"
+    type: text
-  model_digest: text
+    description:
+      en: The model identifier as supplied to the LLM API.
+      de: Der an die LLM-API übergebene Modell-Identifier.
+  model_digest:
+    type: text
+    description:
+      en: |
+        SHA-256 digest of the served Ollama model, when reachable.
+        Empty for non-Ollama endpoints (OpenAI / Anthropic do not
+        expose a digest API). Together with model_endpoint and
+        model_name this answers the audit question "which exact
+        model produced this response?"
+      de: |
+        SHA-256-Digest des bedienten Ollama-Modells, wenn erreichbar.
+        Leer für Nicht-Ollama-Endpunkte (OpenAI / Anthropic stellen
+        keine Digest-API bereit). Zusammen mit model_endpoint und
+        model_name beantwortet das die Audit-Frage "welches genaue
+        Modell hat diese Antwort erzeugt?"
 
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