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@ -10,16 +10,16 @@ env:
CARGO_TERM_COLOR: always CARGO_TERM_COLOR: always
RUSTFLAGS: "-D warnings" RUSTFLAGS: "-D warnings"
RUST_TOOLCHAIN: "1.86" RUST_TOOLCHAIN: "1.86"
CARGO_NET_GIT_FETCH_WITH_CLI: "true"
jobs: jobs:
ci: ci:
name: Linux x86_64 (Forgejo) name: Linux x86_64 (Forgejo)
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
# Manual external-URL checkout — see fai/platform CI for # See fai/platform docs/architecture/ci.md for why we
# background. Lays this repo at $GITHUB_WORKSPACE. # check out via the external URL instead of using
- name: Checkout text-extract via external URL # actions/checkout.
- name: Checkout via external URL
run: | run: |
set -eu set -eu
mkdir -p "$GITHUB_WORKSPACE" mkdir -p "$GITHUB_WORKSPACE"
@ -30,23 +30,6 @@ jobs:
git fetch --depth=1 origin "$GITHUB_SHA" git fetch --depth=1 origin "$GITHUB_SHA"
git checkout -q FETCH_HEAD git checkout -q FETCH_HEAD
# The chain-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.
# MODULE_SDK_PAT is a stored secret with read access to
# fai/module-sdk; we inject it into any outgoing
# https://git.flemming.ws/ URL via insteadOf so cargo's git
# fetch (driven by CARGO_NET_GIT_FETCH_WITH_CLI) authenticates
# transparently.
- 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.ws/.insteadOf" \
"https://git.flemming.ws/"
- name: Install system dependencies - name: Install system dependencies
run: | run: |
apt-get update -qq apt-get update -qq
@ -73,13 +56,13 @@ jobs:
run: cargo fmt --all -- --check run: cargo fmt --all -- --check
- name: Cargo clippy - name: Cargo clippy
run: cargo clippy --all-targets -- -D warnings run: cargo clippy --workspace --all-targets -- -D warnings
- name: Cargo build (host) - name: Cargo build (host)
run: cargo build --all-targets run: cargo build --workspace --all-targets
- name: Cargo test (host) - name: Cargo test (host)
run: cargo test --all-targets run: cargo test --workspace --all-targets
- name: Cargo build (wasm32-wasip2) - name: Cargo build (wasm32-wasip2)
run: cargo build --release --target wasm32-wasip2 run: cargo build --release --target wasm32-wasip2

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@ -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: orchestrator-llm
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}"

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@ -5,19 +5,19 @@
[package] [package]
name = "orchestrator_llm" name = "orchestrator_llm"
version = "0.3.2" version = "0.3.0"
edition = "2024" edition = "2024"
authors = ["Dr. Stefan Flemming <chain@flemming.ai>"] authors = ["Dr. Stefan Flemming <platform@flemming.ai>"]
license = "Apache-2.0" license = "Apache-2.0"
publish = false publish = false
description = "F∆I orchestrator module — turns natural-language goals into structured execution plans" description = "F∆I orchestrator module — turns natural-language goals into structured execution plans"
repository = "https://git.flemming.ws/chain-modules/orchestrator-llm" repository = "https://git.flemming.ws/fai-modules/orchestrator-llm"
[lib] [lib]
crate-type = ["cdylib", "rlib"] crate-type = ["cdylib", "rlib"]
[dependencies] [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 = { version = "1", features = ["derive"] }
serde_json = "1" serde_json = "1"
thiserror = "2" thiserror = "2"

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@ -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. 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"); Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License. you may not use this file except in compliance with the License.

Binary file not shown.

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@ -1,111 +1,44 @@
schema_version: 3 schema_version: 1
provider: chain
name: orchestrator-llm name: orchestrator-llm
version: 0.3.1 version: 0.2.0
# Capability provided by this module.
provides: provides:
- capability: orchestrator.plan - capability: orchestrator.plan
version: 0.3.0 version: 0.2.0
# Capabilities the plans this module emits typically reference.
# Advisory only — Studio surfaces "you'll also want X" when the
# operator installs orchestrator-llm; `fai admin doctor` flags
# unmet entries; the hub does NOT block install.
consumes:
- capability: llm.chat
version: "^0"
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."
# Inputs the invoke function accepts.
inputs: inputs:
goal: goal: text
type: text # LLM HTTP endpoint, e.g. "http://localhost:11434/api/chat"
description: # for Ollama, "https://api.openai.com/v1/chat/completions",
en: Operator-stated goal in natural language — what the resulting flow should accomplish. # or "https://api.anthropic.com/v1/messages".
de: Ziel in natürlicher Sprache — was der erzeugte Flow erreichen soll. llm_endpoint: text
llm_endpoint: # Model identifier, e.g. "qwen2.5:14b" for Ollama or "gpt-4o-mini".
type: text llm_model: text
description: # Optional bearer token for cloud providers. Empty string means
en: | # no Authorization header is sent.
LLM HTTP endpoint, e.g. "http://localhost:11434/api/chat" llm_api_key: text
for Ollama, "https://api.openai.com/v1/chat/completions", # Optional JSON-encoded list of installed capabilities. If
or "https://api.anthropic.com/v1/messages". # omitted or empty, the module plans without capability context.
de: | available_capabilities: text
LLM-HTTP-Endpunkt, z. B. "http://localhost:11434/api/chat" # Optional JSON-encoded list of all known store capabilities
für Ollama, "https://api.openai.com/v1/chat/completions" # (installed + planned + alpha). Used when the orchestrator
oder "https://api.anthropic.com/v1/messages". # needs to suggest installations.
llm_model: store_capabilities: text
type: text
description:
en: Model identifier, e.g. "qwen2.5:14b" for Ollama or "gpt-4o-mini".
de: Modell-Identifier, z. B. "qwen2.5:14b" (Ollama) oder "gpt-4o-mini".
llm_api_key:
type: text
description:
en: Optional bearer token for cloud providers. Empty = no Authorization header.
de: Optionaler Bearer-Token für Cloud-Provider. Leer = kein Authorization-Header.
available_capabilities:
type: text
description:
en: |
Optional JSON-encoded list of installed capabilities.
Omit or pass an empty string to plan without capability
context.
de: |
Optional JSON-codierte Liste der installierten
Capabilities. Leer = ohne Capability-Kontext planen.
store_capabilities:
type: text
description:
en: |
Optional JSON-encoded list of all known store
capabilities (installed + planned + alpha). Used when
the orchestrator needs to suggest installations.
de: |
Optional JSON-codierte Liste aller bekannten Store-
Capabilities (installiert + geplant + alpha). Nötig,
wenn der Orchestrator Installationen vorschlagen soll.
# Outputs produced.
outputs: outputs:
plan: # JSON-encoded Plan compatible with `fai_hub::plan::Plan`.
type: json plan: json
description:
en: JSON-encoded Plan compatible with `fai_hub::plan::Plan`.
de: JSON-codierter Plan, kompatibel mit `fai_hub::plan::Plan`.
model_endpoint:
type: text
description:
en: |
The endpoint the plan was generated against. Empty when
the deterministic stub path (no llm_endpoint) ran.
de: |
Endpunkt, gegen den der Plan erzeugt wurde. Leer beim
deterministischen Stub-Pfad (ohne llm_endpoint).
model_name:
type: text
description:
en: The model name as supplied to the LLM API.
de: An die LLM-API übergebener Modellname.
model_digest:
type: text
description:
en: |
SHA-256 digest of the served Ollama model, when
reachable. Empty for cloud providers (OpenAI / Anthropic
do not expose a digest API) and for the deterministic
stub path. Together with model_endpoint and model_name
this answers the audit question "which exact model
produced this plan?"
de: |
SHA-256-Digest des bedienten Ollama-Modells, wenn
erreichbar. Leer für Cloud-Provider (OpenAI / Anthropic
bieten keine Digest-API) und für den deterministischen
Stub-Pfad. Zusammen mit model_endpoint + model_name
beantwortet das die Audit-Frage "welches genaue Modell
hat diesen Plan erzeugt?"
# Permissions required. # Permissions required.
# #
# The module makes outbound HTTP to the configured LLM endpoint. # The module makes outbound HTTP to the configured LLM endpoint.
# Default declarations cover the common providers (cloud OpenAI,
# Anthropic, local Ollama on loopback). Operators with different
# LLM endpoints add a host-level entry via operator config
# (Phase 1+) — for Phase 0.5 they fork module.yaml.
permissions: permissions:
- "net: api.openai.com" - "net: api.openai.com"
- "net: api.anthropic.com" - "net: api.anthropic.com"

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@ -1,7 +1,7 @@
//! orchestrator-llm — turns natural-language goals into Plan JSON. //! orchestrator-llm — turns natural-language goals into Plan JSON.
//! //!
//! v0.3.0 migrates from a hand-written wit_bindgen scaffold to the //! v0.3.0 migrates from a hand-written wit_bindgen scaffold to the
//! `#[fai_module]` macro from `chain-module-sdk`. The behavior is //! `#[fai_module]` macro from `fai-module-sdk`. The behavior is
//! unchanged from v0.2.1: a configured Ollama-compatible endpoint //! unchanged from v0.2.1: a configured Ollama-compatible endpoint
//! drives a real plan when `llm_endpoint` is set, otherwise the //! drives a real plan when `llm_endpoint` is set, otherwise the
//! deterministic stub from v0.1.0 takes over. //! deterministic stub from v0.1.0 takes over.
@ -19,7 +19,7 @@ mod plan;
pub use plan::{Plan, PlanStep, build_stub_plan, parse_and_validate, validate}; pub use plan::{Plan, PlanStep, build_stub_plan, parse_and_validate, validate};
use chain_module_sdk::prelude::*; use fai_module_sdk::prelude::*;
#[fai_module] #[fai_module]
pub fn invoke(_ctx: Context, inputs: Inputs) -> Result<Outputs, ModuleError> { pub fn invoke(_ctx: Context, inputs: Inputs) -> Result<Outputs, ModuleError> {
@ -45,8 +45,8 @@ pub fn invoke(_ctx: Context, inputs: Inputs) -> Result<Outputs, ModuleError> {
.and_then(payload_text) .and_then(payload_text)
.unwrap_or_default(); .unwrap_or_default();
let (plan_json, model_digest) = if llm_endpoint.is_empty() { let plan_json = if llm_endpoint.is_empty() {
(build_stub_plan(goal), None) build_stub_plan(goal)
} else { } else {
let client = make_client(); let client = make_client();
let params = crate::llm::OllamaParams { let params = crate::llm::OllamaParams {
@ -57,16 +57,14 @@ pub fn invoke(_ctx: Context, inputs: Inputs) -> Result<Outputs, ModuleError> {
available_capabilities: &available_capabilities, available_capabilities: &available_capabilities,
store_capabilities: &store_capabilities, store_capabilities: &store_capabilities,
}; };
let result = crate::llm::generate_plan_with_identity(&client, &params) crate::llm::generate_plan(&client, &params)
.map_err(|e| ModuleError::internal(e.to_string()))?; .map_err(|e| ModuleError::internal(e.to_string()))?
(result.plan_json, result.model_digest)
}; };
Ok(Outputs::new() Ok(Outputs::new()
.with_json_str("plan", plan_json) .with_json_str("plan", plan_json)
.with_text("model_endpoint", llm_endpoint) .with_text("model_endpoint", llm_endpoint)
.with_text("model_name", llm_model) .with_text("model_name", llm_model))
.with_text("model_digest", model_digest.unwrap_or_default()))
} }
fn payload_text(p: &Payload) -> Option<String> { fn payload_text(p: &Payload) -> Option<String> {

View file

@ -127,43 +127,12 @@ pub fn extract_ollama_content(body: &str) -> Result<String, LlmError> {
.ok_or_else(|| LlmError::Decode("missing message.content".into())) .ok_or_else(|| LlmError::Decode("missing message.content".into()))
} }
/// Plan plus model identity captured at invocation time, for
/// audit logging.
#[derive(Debug, Clone)]
pub struct PlanWithIdentity {
/// The plan JSON the LLM produced.
pub plan_json: String,
/// SHA-256 digest of the served model, when reachable. `None`
/// for non-Ollama endpoints (OpenAI / Anthropic do not expose
/// a per-model digest API) or when the `/api/show` probe failed
/// for any reason. The audit trail records this verbatim;
/// `None` becomes an empty string in the module output.
pub model_digest: Option<String>,
}
/// Generate a plan via the configured LLM endpoint. Returns the /// Generate a plan via the configured LLM endpoint. Returns the
/// validated plan JSON ready to be emitted as the module output. /// validated plan JSON ready to be emitted as the module output.
///
/// Convenience wrapper kept for callers that do not care about
/// the model digest. New code should call `generate_plan_with_identity`.
#[allow(dead_code)]
pub fn generate_plan<C: LlmClient>( pub fn generate_plan<C: LlmClient>(
client: &C, client: &C,
p: &OllamaParams, p: &OllamaParams,
) -> Result<String, OrchestratorError> { ) -> Result<String, OrchestratorError> {
generate_plan_with_identity(client, p).map(|r| r.plan_json)
}
/// Generate a plan AND probe the LLM endpoint for the model's
/// SHA-256 digest. The digest probe is best-effort: failures do
/// not propagate, the digest is simply absent from the result.
/// This gives compliance-grade audit on Ollama deployments while
/// staying compatible with cloud providers that do not expose
/// digests.
pub fn generate_plan_with_identity<C: LlmClient>(
client: &C,
p: &OllamaParams,
) -> Result<PlanWithIdentity, OrchestratorError> {
if p.endpoint.is_empty() { if p.endpoint.is_empty() {
return Err(OrchestratorError::MissingEndpoint); return Err(OrchestratorError::MissingEndpoint);
} }
@ -177,59 +146,7 @@ pub fn generate_plan_with_identity<C: LlmClient>(
.map_err(OrchestratorError::Llm)?; .map_err(OrchestratorError::Llm)?;
let plan_json = extract_ollama_content(&response_body).map_err(OrchestratorError::Llm)?; let plan_json = extract_ollama_content(&response_body).map_err(OrchestratorError::Llm)?;
crate::plan::parse_and_validate(&plan_json).map_err(OrchestratorError::Plan)?; crate::plan::parse_and_validate(&plan_json).map_err(OrchestratorError::Plan)?;
Ok(plan_json)
let model_digest = probe_model_digest(client, p);
Ok(PlanWithIdentity {
plan_json,
model_digest,
})
}
/// Best-effort probe of Ollama's `/api/show` for the model digest.
/// Any failure (non-Ollama endpoint, network error, parse failure)
/// returns `None` — never propagates as an error to the caller.
fn probe_model_digest<C: LlmClient>(client: &C, p: &OllamaParams) -> Option<String> {
let show_url = derive_show_url(p.endpoint)?;
let body = serde_json::to_string(&serde_json::json!({ "name": p.model })).ok()?;
let response = client.post_json(&show_url, &body, p.api_key).ok()?;
extract_show_digest(&response)
}
/// Convert an Ollama `/api/chat` URL into the matching
/// `/api/show` URL by suffix substitution. Returns `None` if the
/// endpoint does not end in `/api/chat` — that is the signal that
/// the endpoint is not Ollama-shaped, so a probe makes no sense.
pub fn derive_show_url(chat_endpoint: &str) -> Option<String> {
if chat_endpoint.ends_with("/api/chat") {
let head_len = chat_endpoint.len() - "/api/chat".len();
let mut url = String::with_capacity(head_len + "/api/show".len());
url.push_str(&chat_endpoint[..head_len]);
url.push_str("/api/show");
Some(url)
} else {
None
}
}
/// Extract the SHA-256 digest from a `/api/show` response body.
/// Looks for the field at top level, then under `details.digest`,
/// then under `model_info.digest`. Returns `None` if no candidate
/// resolves to a non-empty string.
pub fn extract_show_digest(body: &str) -> Option<String> {
let v: serde_json::Value = serde_json::from_str(body).ok()?;
let candidates = [
v.get("digest"),
v.get("details").and_then(|d| d.get("digest")),
v.get("model_info").and_then(|d| d.get("digest")),
];
for cand in candidates {
if let Some(s) = cand.and_then(|v| v.as_str()) {
if !s.is_empty() {
return Some(s.to_string());
}
}
}
None
} }
#[derive(Debug, thiserror::Error)] #[derive(Debug, thiserror::Error)]
@ -434,123 +351,4 @@ mod tests {
Err(OrchestratorError::Llm(LlmError::MissingInput("llm_model"))) Err(OrchestratorError::Llm(LlmError::MissingInput("llm_model")))
)); ));
} }
// === Compliance Gap 1: model digest probe ===
#[test]
fn derive_show_url_swaps_chat_suffix() {
assert_eq!(
derive_show_url("http://localhost:11434/api/chat").as_deref(),
Some("http://localhost:11434/api/show")
);
assert_eq!(
derive_show_url("https://example.com/v1/api/chat").as_deref(),
Some("https://example.com/v1/api/show")
);
}
#[test]
fn derive_show_url_returns_none_for_non_ollama_endpoints() {
assert!(derive_show_url("https://api.openai.com/v1/chat/completions").is_none());
assert!(derive_show_url("https://api.anthropic.com/v1/messages").is_none());
assert!(derive_show_url("http://localhost:11434/api/chats").is_none());
assert!(derive_show_url("/api/chat-something").is_none());
}
#[test]
fn extract_show_digest_finds_top_level_field() {
let body = r#"{"digest":"sha256:abcdef","details":{"format":"gguf"}}"#;
assert_eq!(extract_show_digest(body).as_deref(), Some("sha256:abcdef"));
}
#[test]
fn extract_show_digest_falls_back_to_nested_locations() {
let nested_details = r#"{"details":{"digest":"sha256:nested-details"}}"#;
assert_eq!(
extract_show_digest(nested_details).as_deref(),
Some("sha256:nested-details")
);
let nested_info = r#"{"model_info":{"digest":"sha256:nested-info"}}"#;
assert_eq!(
extract_show_digest(nested_info).as_deref(),
Some("sha256:nested-info")
);
}
#[test]
fn extract_show_digest_returns_none_when_absent_or_empty() {
assert!(extract_show_digest(r#"{"modelfile":"..."}"#).is_none());
assert!(extract_show_digest(r#"{"digest":""}"#).is_none());
assert!(extract_show_digest("not even json").is_none());
}
#[test]
fn generate_plan_with_identity_records_digest_when_show_responds() {
let canned_plan =
r#"{"schema_version":1,"goal":"x","steps":[{"kind":"explain","text":"ok"}]}"#;
let canned_chat = format!(
r#"{{"message":{{"content":{}}},"done":true}}"#,
serde_json::to_string(canned_plan).unwrap(),
);
let canned_show = r#"{"digest":"sha256:deadbeef"}"#.to_string();
// Mock pops from the end — so push show first, chat second.
let client = MockClient::new(vec![Ok(canned_show), Ok(canned_chat)]);
let p = OllamaParams {
endpoint: "http://localhost:11434/api/chat",
model: "qwen",
api_key: "",
goal: "x",
available_capabilities: "",
store_capabilities: "",
};
let result = generate_plan_with_identity(&client, &p).unwrap();
assert_eq!(result.model_digest.as_deref(), Some("sha256:deadbeef"));
assert!(!result.plan_json.is_empty());
}
#[test]
fn generate_plan_with_identity_returns_none_digest_for_non_ollama_endpoint() {
// Endpoint does not end in /api/chat: probe is skipped
// entirely. Only one mock response is consumed.
let canned_plan =
r#"{"schema_version":1,"goal":"x","steps":[{"kind":"explain","text":"ok"}]}"#;
let canned_chat = format!(
r#"{{"message":{{"content":{}}}}}"#,
serde_json::to_string(canned_plan).unwrap(),
);
let client = MockClient::new(vec![Ok(canned_chat)]);
let p = OllamaParams {
endpoint: "https://api.openai.com/v1/chat/completions",
model: "gpt",
api_key: "k",
goal: "x",
available_capabilities: "",
store_capabilities: "",
};
let result = generate_plan_with_identity(&client, &p).unwrap();
assert_eq!(result.model_digest, None);
}
#[test]
fn generate_plan_with_identity_swallows_show_failures() {
// The /api/show probe fails (e.g. 500). The plan still
// succeeds with `model_digest = None`.
let canned_plan =
r#"{"schema_version":1,"goal":"x","steps":[{"kind":"explain","text":"ok"}]}"#;
let canned_chat = format!(
r#"{{"message":{{"content":{}}}}}"#,
serde_json::to_string(canned_plan).unwrap(),
);
let client = MockClient::new(vec![Err(LlmError::Status(500)), Ok(canned_chat)]);
let p = OllamaParams {
endpoint: "http://localhost:11434/api/chat",
model: "qwen",
api_key: "",
goal: "x",
available_capabilities: "",
store_capabilities: "",
};
let result = generate_plan_with_identity(&client, &p).unwrap();
assert_eq!(result.model_digest, None);
}
} }