.forgejo/workflows/ci.yml

@@ -30,7 +30,7 @@ jobs:
           git fetch --depth=1 origin "$GITHUB_SHA"
           git checkout -q FETCH_HEAD
 
-      # The chain-module-sdk dependency is a git dep against a repo
+      # The fai-module-sdk dependency is a git dep against a repo
       # that lives in another Forgejo org. The repo-scoped
       # GITHUB_TOKEN cannot read it, and the Forgejo instance has
       # REQUIRE_SIGNIN_VIEW=true so anonymous read is also denied.

.forgejo/workflows/sign.yml

@@ -1,223 +0,0 @@
-# F∆I module bundle signing workflow (cosign key-pinning model).
-#
-# Drop-in template for any module repo under chain-modules/.
-# Triggers on tag push (vX.Y.Z) — builds the module, packs the
-# .fai bundle, signs the bundle bytes with the Flemming.AI
-# signing key (ECDSA P-256), and attaches bundle + .sig sidecar
-# to the matching Forgejo Release.
-#
-# The hub-side verifier ships in 0.12.0+: when an operator sets
-# `require_signatures: true`, install downloads the .sig sidecar
-# from `<wasm_url>.sig` and verifies it against the pinned store
-# public key (built-in for `bundled` / `official`, per-store
-# config for everything else).
-#
-# Adopt by copying this file to `.forgejo/workflows/sign.yml` in
-# the module repo and replacing the MODULE_NAME placeholder.
-# Add the signing key to Forgejo secrets as FAI_SIGNING_KEY (PEM,
-# unencrypted, ECDSA P-256). Rotation is a 5-minute key-roll +
-# binary re-release; see infra/cosign/README.md.
-
-name: sign-bundle
-
-on:
-  push:
-    tags:
-      - 'v*.*.*'
-
-env:
-  CARGO_TERM_COLOR: always
-  RUST_TOOLCHAIN: "1.86"
-  CARGO_NET_GIT_FETCH_WITH_CLI: "true"
-
-jobs:
-  sign:
-    runs-on: ubuntu-latest
-    permissions:
-      contents: write    # attach signature to release
-
-    env:
-      # The canonical module name as written in module.yaml.
-      # Used in the bundle filename + wasm path.
-      MODULE_NAME: llm-chat
-
-    steps:
-      # See fai/platform CI for background on the manual external
-      # checkout: the DinD runner cannot resolve forgejo:3000, so
-      # we clone via the external URL with $GITHUB_TOKEN.
-      - name: Checkout via external URL
-        run: |
-          set -eu
-          mkdir -p "$GITHUB_WORKSPACE"
-          cd "$GITHUB_WORKSPACE"
-          git init -q
-          git remote add origin \
-            "https://x-access-token:${GITHUB_TOKEN}@git.flemming.ai/${GITHUB_REPOSITORY}.git"
-          git fetch --depth=1 origin "$GITHUB_SHA"
-          git checkout -q FETCH_HEAD
-
-      # The chain-module-sdk dependency lives in another Forgejo org
-      # behind REQUIRE_SIGNIN_VIEW. MODULE_SDK_PAT (org-level
-      # secret, read-only on fai/module-sdk) authenticates cargo's
-      # git fetch via insteadOf.
-      - name: Configure git URL rewrite for SDK fetch
-        env:
-          SDK_PAT: ${{ secrets.MODULE_SDK_PAT }}
-        run: |
-          git config --global \
-            "url.https://x-access-token:${SDK_PAT}@git.flemming.ai/.insteadOf" \
-            "https://git.flemming.ai/"
-
-      - name: Install system dependencies
-        run: |
-          apt-get update -qq
-          apt-get install -y --no-install-recommends \
-            curl \
-            ca-certificates \
-            build-essential \
-            pkg-config \
-            libssl-dev \
-            git \
-            jq \
-            openssl
-
-      - name: Install Rust toolchain
-        run: |
-          curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs \
-            | sh -s -- -y \
-              --profile minimal \
-              --default-toolchain "$RUST_TOOLCHAIN" \
-              --target wasm32-wasip2
-          echo "$HOME/.cargo/bin" >> "$GITHUB_PATH"
-
-      - name: Build module (wasm32-wasip2)
-        run: cargo build --release --target wasm32-wasip2
-
-      - name: Install fai CLI
-        # Pinned to the production channel; signing requires the
-        # `fai pack` command. Override FAI_VERSION when bundle
-        # format compatibility matters.
-        run: |
-          curl -fsSL https://get.chain.flemming.ai | sh -s -- --no-bootstrap
-          # The installer drops fai at $HOME/.local/bin
-          echo "$HOME/.local/bin" >> "$GITHUB_PATH"
-          export PATH="$HOME/.local/bin:$PATH"
-          fai --version
-
-      - name: Stage bundle inputs
-        # The wasm artefact is named after the Cargo package
-        # (underscored), which may differ from the module name
-        # in module.yaml (dashed). Resolve it from Cargo.toml so
-        # the template stays agnostic to the project's naming
-        # convention.
-        run: |
-          set -eu
-          CARGO_NAME=$(grep -E '^name *= *"' Cargo.toml \
-            | head -1 | sed 's/.*"\(.*\)".*/\1/')
-          mkdir -p staging
-          cp module.yaml staging/
-          cp "target/wasm32-wasip2/release/${CARGO_NAME}.wasm" staging/module.wasm
-          if [ -f sbom.cdx.json ]; then cp sbom.cdx.json staging/; fi
-          if [ -f MODULE.md ]; then cp MODULE.md staging/; fi
-          if [ -f MODULE.de.md ]; then cp MODULE.de.md staging/; fi
-
-      - name: Pack bundle
-        id: pack
-        run: |
-          export PATH="$HOME/.local/bin:$PATH"
-          BUNDLE="${{ env.MODULE_NAME }}-${{ github.ref_name }}.fai"
-          fai pack staging --output "$BUNDLE"
-          echo "bundle=$BUNDLE" >> "$GITHUB_OUTPUT"
-          ls -la "$BUNDLE"
-
-      - name: Sign bundle (Flemming.AI signing key)
-        env:
-          FAI_SIGNING_KEY_PEM: ${{ secrets.FAI_SIGNING_KEY }}
-        run: |
-          if [ -z "${FAI_SIGNING_KEY_PEM:-}" ]; then
-            cat >&2 <<'EOF'
-
-          FAI_SIGNING_KEY secret is empty or undefined.
-
-          This workflow signs module bundles with the Flemming.AI
-          module-signing key (ECDSA P-256, PKCS#8 PEM, unencrypted).
-          The matching public key is pinned in the fai-hub binary at
-          infra/cosign/official.pub — hubs that require_signatures
-          will reject anything not signed with this key.
-
-          To configure:
-            1. Forgejo -> chain-modules org -> Settings -> Secrets
-            2. Add secret FAI_SIGNING_KEY (org-level recommended)
-            3. Paste the unencrypted PEM (BEGIN PRIVATE KEY ...)
-          The encrypted source-of-truth lives on Stefan's Mac at
-          ~/.fai-secrets/flemming-ai-signing.key (passphrase in
-          mSecure under "Ch∆In — Module Signing Key (Private)").
-
-          See fai/platform infra/cosign/OPERATOR-HANDOFF.md for the
-          full setup runbook and rotation process.
-          EOF
-            exit 1
-          fi
-          umask 077
-          echo "$FAI_SIGNING_KEY_PEM" > /tmp/signing-key.pem
-          openssl dgst -sha256 \
-            -sign /tmp/signing-key.pem \
-            -out "${{ steps.pack.outputs.bundle }}.sig.raw" \
-            "${{ steps.pack.outputs.bundle }}"
-          base64 < "${{ steps.pack.outputs.bundle }}.sig.raw" \
-            > "${{ steps.pack.outputs.bundle }}.sig"
-          rm "${{ steps.pack.outputs.bundle }}.sig.raw"
-          shred -u /tmp/signing-key.pem || rm -f /tmp/signing-key.pem
-          ls -la "${{ steps.pack.outputs.bundle }}.sig"
-
-      - name: Round-trip verify
-        # Sanity-check: the freshly-signed bundle must verify
-        # against the well-known public key before we publish it.
-        run: |
-          curl -fsSL https://git.flemming.ai/fai/platform/raw/branch/main/infra/cosign/official.pub \
-            -o /tmp/official.pub
-          openssl dgst -sha256 \
-            -verify /tmp/official.pub \
-            -signature <(base64 -d < "${{ steps.pack.outputs.bundle }}.sig") \
-            "${{ steps.pack.outputs.bundle }}"
-
-      - name: Attach bundle + signature to Forgejo Release
-        run: |
-          set -eu
-          BUNDLE="${{ steps.pack.outputs.bundle }}"
-          SIG="$BUNDLE.sig"
-          REL_JSON=$(curl -sS \
-            -H "Authorization: token ${GITHUB_TOKEN}" \
-            "https://git.flemming.ai/api/v1/repos/${GITHUB_REPOSITORY}/releases/tags/${GITHUB_REF_NAME}")
-          REL_ID=$(echo "$REL_JSON" | jq -r '.id // empty')
-          if [ -z "$REL_ID" ] || [ "$REL_ID" = "null" ]; then
-            REL_ID=$(curl -sS -X POST \
-              -H "Authorization: token ${GITHUB_TOKEN}" \
-              -H "Content-Type: application/json" \
-              "https://git.flemming.ai/api/v1/repos/${GITHUB_REPOSITORY}/releases" \
-              -d "{\"tag_name\":\"${GITHUB_REF_NAME}\",\"name\":\"${GITHUB_REF_NAME}\",\"draft\":false,\"prerelease\":false,\"body\":\"Auto-generated by sign-bundle workflow\"}" \
-              | jq -r '.id')
-          fi
-          upload_one() {
-            local asset_path="$1" asset
-            asset=$(basename "$asset_path")
-            EXISTING=$(curl -sS \
-              -H "Authorization: token ${GITHUB_TOKEN}" \
-              "https://git.flemming.ai/api/v1/repos/${GITHUB_REPOSITORY}/releases/${REL_ID}/assets" \
-              | jq -r ".[] | select(.name==\"${asset}\") | .id")
-            if [ -n "$EXISTING" ]; then
-              curl -sS -X DELETE \
-                -H "Authorization: token ${GITHUB_TOKEN}" \
-                "https://git.flemming.ai/api/v1/repos/${GITHUB_REPOSITORY}/releases/${REL_ID}/assets/${EXISTING}" \
-                || true
-            fi
-            curl -sS -X POST \
-              -H "Authorization: token ${GITHUB_TOKEN}" \
-              -F "attachment=@${asset_path}" \
-              "https://git.flemming.ai/api/v1/repos/${GITHUB_REPOSITORY}/releases/${REL_ID}/assets?name=${asset}" \
-              > /dev/null
-            echo "uploaded $asset"
-          }
-          upload_one "$BUNDLE"
-          upload_one "$SIG"
-          echo "release ${GITHUB_REF_NAME} ready: https://git.flemming.ai/${GITHUB_REPOSITORY}/releases/tag/${GITHUB_REF_NAME}"

Cargo.lock

@@ -39,11 +39,17 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9330f8b2ff13f34540b44e946ef35111825727b38d33286ef986142615121801"
 
 [[package]]
-name = "chain-module-sdk"
+name = "equivalent"
+version = "1.0.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "877a4ace8713b0bcf2a4e7eec82529c029f1d0619886d18145fea96c3ffe5c0f"
+
+[[package]]
+name = "fai-module-sdk"
 version = "0.1.2"
-source = "git+https://git.flemming.ai/fai/chain-module-sdk-rust.git?branch=main#98e98e9371f7409560a1ef08bc0923d9a2506449"
+source = "git+https://git.flemming.ws/fai/module-sdk.git?branch=main#f209fbc86f531b53e576f3cdbdf75750eef3b07a"
 dependencies = [
- "chain-module-sdk-macros",
+ "fai-module-sdk-macros",
  "serde",
  "serde_json",
  "thiserror",
@@ -51,21 +57,15 @@ dependencies = [
 ]
 
 [[package]]
-name = "chain-module-sdk-macros"
+name = "fai-module-sdk-macros"
 version = "0.1.2"
-source = "git+https://git.flemming.ai/fai/chain-module-sdk-rust.git?branch=main#98e98e9371f7409560a1ef08bc0923d9a2506449"
+source = "git+https://git.flemming.ws/fai/module-sdk.git?branch=main#f209fbc86f531b53e576f3cdbdf75750eef3b07a"
 dependencies = [
  "proc-macro2",
  "quote",
  "syn",
 ]
 
-[[package]]
-name = "equivalent"
-version = "1.0.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "877a4ace8713b0bcf2a4e7eec82529c029f1d0619886d18145fea96c3ffe5c0f"
-
 [[package]]
 name = "form_urlencoded"
 version = "1.2.2"
@@ -140,7 +140,7 @@ checksum = "6cc46bac87ef8093eed6f272babb833b6443374399985ac8ed28471ee0918545"
 name = "llm_chat"
 version = "0.1.0"
 dependencies = [
- "chain-module-sdk",
+ "fai-module-sdk",
  "serde",
  "serde_json",
  "thiserror",

Cargo.toml

@@ -17,7 +17,7 @@ description = "F∆I module providing llm.chat"
 crate-type = ["cdylib", "rlib"]
 
 [dependencies]
-chain-module-sdk = { git = "https://git.flemming.ai/fai/chain-module-sdk-rust.git", branch = "main" }
+fai-module-sdk = { git = "https://git.flemming.ws/fai/module-sdk.git", branch = "main" }
 serde = { version = "1", features = ["derive"] }
 serde_json = "1"
 thiserror = "2"

LICENSE

@@ -58,7 +58,7 @@ APPENDIX: How to apply the Apache License to your work.
 
 To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!)  The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives.
 
-Copyright 2026 Flemming.AI
+Copyright 2026 fai-modules
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.

MODULE.de.md

@@ -1,106 +0,0 @@
-# llm.chat
-
-Generischer Ollama-kompatibler LLM-Chat-Adapter. Das
-Baustein-Modul für jeden Flow, der eine LLM-Einzelantwort
-braucht — klassifizieren, Felder extrahieren, umformulieren,
-entscheiden — ohne einen eigenen HTTP-Client zu bauen.
-
-## Capability
-
-- `llm.chat@0.1.0`
-
-## Eingaben
-
-| Name             | Typ  | Beschreibung                                                              |
-| ---------------- | ---- | ------------------------------------------------------------------------- |
-| `prompt`         | text | Der User-Prompt.                                                          |
-| `endpoint`       | text | Ollama-förmiger `/api/chat`-URL (z.B. `http://localhost:11434/api/chat`). |
-| `model`          | text | Modell-ID (z.B. `qwen2.5:14b`, `llama3.1:8b`).                            |
-| `api_key`        | text | Optionaler Bearer-Token für Cloud-Endpunkte.                              |
-| `system_prompt`  | text | Optionale System-Nachricht. Leer = Default des Modells.                   |
-
-## Ausgaben
-
-| Name             | Typ  | Beschreibung                                                          |
-| ---------------- | ---- | --------------------------------------------------------------------- |
-| `response`       | text | Die Antwort des Assistants als Plain-Text.                            |
-| `model_endpoint` | text | URL, gegen die die Antwort erzeugt wurde.                             |
-| `model_name`     | text | Modell-ID wie an die LLM-API gesendet.                                |
-| `model_digest`   | text | SHA-256-Digest des bedienenden Ollama-Modells. Leer bei Cloud-APIs.   |
-
-Zusammen beantworten die drei `model_*`-Ausgaben die Audit-
-Frage: „Welches genaue Modell hat diese Antwort erzeugt?" —
-diese Spur ist der Grund, warum Flows dieses Modul nutzen statt
-eigene HTTP-Calls zu sprechen.
-
-## Berechtigungen
-
-```yaml
-permissions:
-  - "net: localhost"
-  - "net: 127.0.0.1"
-  - "net: api.openai.com"
-  - "net: api.anthropic.com"
-```
-
-Loopback (lokales Ollama) per Default. Cloud-Endpunkte brauchen
-einen Operator-Policy-Override in
-`~/.chain/config.yaml#security.max_permissions`.
-
-## Warum dieses Modul statt Inline-HTTP
-
-Drei Gründe:
-
-1. **Audit.** Jeder LLM-Aufruf erzeugt `model_endpoint`,
-   `model_name`, `model_digest` als separate Ausgaben, die
-   im hash-verketteten Audit-Log neben der Response landen.
-   Eine Aufsichts-Reproduzierbarkeits-Prüfung vergleicht
-   einfach das Digest-Feld mit dem Modell-Snapshot.
-2. **Permission-Posture.** Operator:innen sehen `llm.chat`
-   in den installierten Modulen + dessen deklarierte
-   `net:`-Liste. Ein hausgemachtes HTTP-Modul würde seine
-   Endpunkte entweder verstecken oder bei jeder Installation
-   eine frische Review-Oberfläche schaffen.
-3. **Endpunkt-Portabilität.** Endpunkt + Modell sind Flow-
-   Inputs, keine Compile-Time-Konstanten. Derselbe Flow läuft
-   in der Entwicklung gegen `localhost:11434` und in Produktion
-   gegen ein Inferenz-Cluster — nur die Eingabe wechselt.
-
-## Grenzen in v0.1.0
-
-- Kein Streaming. Die ganze Antwort wird gepuffert, bevor der
-  Output-Step feuert.
-- Keine Tool-Call- / Function-Call-Oberfläche. Ein Flow, der
-  Tool-Use braucht, kombiniert mehrere `llm.chat`-Schritte mit
-  Prompt-Engineering oder nutzt MCP via Bridge.
-- Cloud-Provider-Adapter für OpenAI und Anthropic kommen erst,
-  wenn ein Flow sie braucht. Heute ist das Ollama-Wire-Format
-  das einzige Ziel.
-
-## Beispiel-Flow
-
-```yaml
-name: classify-incoming
-inputs:
-  text: text
-steps:
-  - id: classify
-    use: llm.chat@^0
-    with:
-      prompt: $inputs.text
-      system_prompt: |
-        Klassifiziere den Text als: question, complaint,
-        feedback, spam. Antworte nur mit dem Label.
-      endpoint: "http://localhost:11434/api/chat"
-      model: "qwen2.5:14b"
-outputs:
-  category: $classify.response
-  audit_model: $classify.model_digest
-```
-
-## Build
-
-```bash
-cargo build --release --target wasm32-wasip2
-# Ausgabe: target/wasm32-wasip2/release/llm_chat.wasm
-```

MODULE.md

@@ -1,104 +0,0 @@
-# llm.chat
-
-Generic Ollama-compatible LLM chat adapter. The building-block
-module any flow uses when it needs a one-shot LLM completion —
-classify, extract-fields, rewrite, decide — instead of rolling
-its own HTTP client.
-
-## Capability
-
-- `llm.chat@0.1.0`
-
-## Inputs
-
-| Name             | Type | Description                                                     |
-| ---------------- | ---- | --------------------------------------------------------------- |
-| `prompt`         | text | The user-facing prompt.                                         |
-| `endpoint`       | text | Ollama-shaped `/api/chat` URL (e.g. `http://localhost:11434/api/chat`). |
-| `model`          | text | Model identifier (e.g. `qwen2.5:14b`, `llama3.1:8b`).           |
-| `api_key`        | text | Optional bearer token for cloud-hosted endpoints.               |
-| `system_prompt`  | text | Optional system message. Empty = use the model's default.       |
-
-## Outputs
-
-| Name             | Type | Description                                                         |
-| ---------------- | ---- | ------------------------------------------------------------------- |
-| `response`       | text | The assistant's plain-text reply.                                   |
-| `model_endpoint` | text | The endpoint the response was generated against.                    |
-| `model_name`     | text | The model identifier as supplied to the LLM API.                    |
-| `model_digest`   | text | SHA-256 digest of the served Ollama model. Empty for cloud APIs.    |
-
-Together the three `model_*` outputs answer the audit
-question: "which exact model produced this response?" — that
-audit trail is the reason flows use this module rather than
-spawning their own HTTP calls.
-
-## Permissions
-
-```yaml
-permissions:
-  - "net: localhost"
-  - "net: 127.0.0.1"
-  - "net: api.openai.com"
-  - "net: api.anthropic.com"
-```
-
-Loopback (local Ollama) by default. Cloud endpoints require an
-operator-policy override in `~/.chain/config.yaml#security.max_permissions`.
-
-## Why this module instead of inline HTTP
-
-Three reasons:
-
-1. **Audit.** Every LLM call surfaces `model_endpoint`,
-   `model_name`, `model_digest` as separate outputs that land
-   in the hash-chained audit log alongside the response. A
-   regulator-facing reproducibility check just compares the
-   digest field to the model snapshot.
-2. **Permission posture.** The operator sees `llm.chat` in
-   the installed modules + its declared `net:` list. A
-   home-grown HTTP module would either hide its endpoints
-   or be a fresh review surface every time.
-3. **Endpoint portability.** The endpoint + model are flow
-   inputs, not compile-time constants. The same flow runs
-   against `localhost:11434` in dev and a production
-   inference cluster in prod just by swapping the input.
-
-## Limits in v0.1.0
-
-- No streaming. The whole reply is buffered before the output
-  step fires.
-- No tool-call / function-call surface. A flow needing tool
-  use composes multiple `llm.chat` steps with prompt
-  engineering, or uses MCP via the bridge.
-- Cloud-provider adapters for OpenAI and Anthropic are
-  deferred until a flow actually needs them. Today the
-  Ollama wire-format is the only target.
-
-## Example flow
-
-```yaml
-name: classify-incoming
-inputs:
-  text: text
-steps:
-  - id: classify
-    use: llm.chat@^0
-    with:
-      prompt: $inputs.text
-      system_prompt: |
-        Classify the text as one of: question, complaint,
-        feedback, spam. Answer with the label only.
-      endpoint: "http://localhost:11434/api/chat"
-      model: "qwen2.5:14b"
-outputs:
-  category: $classify.response
-  audit_model: $classify.model_digest
-```
-
-## Build
-
-```bash
-cargo build --release --target wasm32-wasip2
-# Output: target/wasm32-wasip2/release/llm_chat.wasm
-```

README.md

@@ -29,7 +29,7 @@ on every successful invocation. Together they answer the audit
 question "which exact model produced this response?" The digest
 probe targets Ollama's `/api/show` and is best-effort — non-
 Ollama endpoints and transient probe failures yield an empty
-digest rather than blocking the response. Cf. Ch∆In
+digest rather than blocking the response. Cf. F∆I Platform
 `docs/advanced/compliance-gaps.md` Gap 1.
 
 ## Build
@@ -47,7 +47,7 @@ cargo build --release --target wasm32-wasip2
 
 ## SDK source
 
-The Cargo.toml git-deps `chain-module-sdk` from
+The Cargo.toml git-deps `fai-module-sdk` from
 `https://git.flemming.ws/fai/module-sdk.git`. The Forgejo
 instance has `REQUIRE_SIGNIN_VIEW=true`, so anonymous clones
 fail; CI uses the `MODULE_SDK_PAT` actions secret + `git config
@@ -58,5 +58,5 @@ transparently. Local dev uses the same pattern via env vars.
 
 Apache-2.0.
 
-Author: Dr. Stefan Flemming, Flemming.AI <chain@flemming.ai>
+Author: Dr. Stefan Flemming, Flemming.AI <platform@flemming.ai>
-Repository: https://git.flemming.ws/chain-modules/llm-chat
+Repository: https://git.flemming.ws/fai-modules/llm-chat

module.yaml

@@ -1,5 +1,4 @@
-schema_version: 3
+schema_version: 1
-provider: chain
 name: llm-chat
 version: 0.1.0
 
@@ -8,81 +7,38 @@ provides:
   - capability: llm.chat
     version: 0.1.0
 
-# Declared inputs in verbose v3 form. Studio renders the
+# Inputs the invoke function accepts.
-# 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:
-  prompt:
+  # The user-facing prompt text.
-    type: text
+  prompt: text
-    description:
+  # Ollama-shaped /api/chat endpoint, e.g.
-      en: The user-facing prompt text the model should respond to.
+  # "http://localhost:11434/api/chat".
-      de: Der vom Modell zu beantwortende Prompt-Text.
+  endpoint: text
-  endpoint:
+  # Model identifier as registered with the endpoint, e.g.
-    type: text
+  # "qwen2.5:14b" or "llama3.1:8b".
-    description:
+  model: text
-      en: |
+  # Optional bearer token for cloud-hosted endpoints. Empty
-        Ollama-shaped /api/chat endpoint, e.g.
+  # string means no Authorization header is sent.
-        "http://localhost:11434/api/chat".
+  api_key: text
-      de: |
+  # Optional system prompt. Empty string omits the system
-        Ollama-kompatibler /api/chat-Endpunkt, z. B.
+  # message and lets the model use its built-in default.
-        "http://localhost:11434/api/chat".
+  system_prompt: text
-  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:
-  response:
+  # The assistant's plain-text reply.
-    type: text
+  response: text
-    description:
+  # The endpoint the response was generated against. Used for
-      en: The assistant's plain-text reply.
+  # audit correlation.
-      de: Die Klartext-Antwort des Modells.
+  model_endpoint: text
-  model_endpoint:
+  # The model identifier as supplied to the LLM API.
-    type: text
+  model_name: text
-    description:
+  # SHA-256 digest of the served Ollama model, when reachable.
-      en: The endpoint the response was generated against. Used for audit correlation.
+  # Empty for non-Ollama endpoints (OpenAI / Anthropic do not
-      de: Der Endpunkt, gegen den die Antwort erzeugt wurde — für Audit-Korrelation.
+  # expose a digest API). Together with model_endpoint and
-  model_name:
+  # model_name this answers the audit question "which exact
-    type: text
+  # model produced this response?"
-    description:
+  model_digest: text
-      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?"
 
 # Permissions required.
 #

src/lib.rs

@@ -10,7 +10,7 @@
 
 mod llm;
 
-use chain_module_sdk::prelude::*;
+use fai_module_sdk::prelude::*;
 
 #[fai_module]
 pub fn invoke(_ctx: Context, inputs: Inputs) -> Result<Outputs, ModuleError> {