feat: Implement Policy Engine Evaluation Service and Cache with unit tests
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# Advisory AI architecture
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> Captures the retrieval, guardrail, and inference packaging requirements defined in the Advisory AI implementation plan and related module guides.
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## 1) Goals
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- Summarise advisories/VEX evidence into operator-ready briefs with citations.
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- Explain conflicting statements with provenance and trust weights (using VEX Lens & Excititor data).
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- Suggest remediation plans aligned with Offline Kit deployment models and scheduler follow-ups.
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- Operate deterministically where possible; cache generated artefacts with digests for audit.
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## 2) Pipeline overview
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```
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+---------------------+
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Concelier/VEX Lens | Evidence Retriever |
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Policy Engine ----> | (vector + keyword) | ---> Context Pack (JSON)
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Zastava runtime +---------------------+
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|
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v
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+-------------+
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| Prompt |
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| Assembler |
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+-------------+
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|
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v
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+-------------+
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| Guarded LLM |
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| (local/host)|
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+-------------+
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|
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v
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+-----------------+
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| Citation & |
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| Validation |
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+-----------------+
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|
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v
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+----------------+
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| Output cache |
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| (hash, bundle) |
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+----------------+
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```
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## 3) Retrieval & context
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- Hybrid search: vector embeddings (SBERT-compatible) + keyword filters for advisory IDs, PURLs, CVEs.
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- Context packs include:
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- Advisory raw excerpts with highlighted sections and source URLs.
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- VEX statements (normalized tuples + trust metadata).
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- Policy explain traces for the affected finding.
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- Runtime/impact hints from Zastava (exposure, entrypoints).
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- Export-ready remediation data (fixed versions, patches).
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- **SBOM context retriever** (AIAI-31-002) hydrates:
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- Version timelines (first/last observed, status, fix availability).
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- Dependency paths (runtime vs build/test, deduped by coordinate chain).
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- Tenant environment flags (prod/stage toggles) with optional blast radius summary.
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- Service-side clamps: max 500 timeline entries, 200 dependency paths, with client-provided toggles for env/blast data.
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- `AddSbomContextHttpClient(...)` registers the typed HTTP client that calls `/v1/sbom/context`, while `NullSbomContextClient` remains the safe default for environments that have not yet exposed the SBOM service.
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**Sample configuration** (wire real SBOM base URL + API key):
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```csharp
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services.AddSbomContextHttpClient(options =>
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{
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options.BaseAddress = new Uri("https://sbom-service.internal");
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options.Endpoint = "/v1/sbom/context";
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options.ApiKey = configuration["SBOM_SERVICE_API_KEY"];
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options.UserAgent = "stellaops-advisoryai/1.0";
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options.Tenant = configuration["TENANT_ID"];
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});
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services.AddAdvisoryPipeline();
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```
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After configuration, issue a smoke request (e.g., `ISbomContextRetriever.RetrieveAsync`) during deployment validation to confirm end-to-end connectivity and credentials before enabling Advisory AI endpoints.
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Retriever requests and results are trimmed/normalized before hashing; metadata (counts, provenance keys) is returned for downstream guardrails. Unit coverage ensures deterministic ordering and flag handling.
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All context references include `content_hash` and `source_id` enabling verifiable citations.
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## 4) Guardrails
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- Prompt templates enforce structure: summary, conflicts, remediation, references.
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- Response validator ensures:
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- No hallucinated advisories (every fact must map to input context).
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- Citations follow `[n]` indexing referencing actual sources.
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- Remediation suggestions only cite policy-approved sources (fixed versions, vendor hotfixes).
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- Moderation/PII filters prevent leaking secrets; responses failing validation are rejected and logged.
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- Pre-flight guardrails redact secrets (AWS keys, generic API tokens, PEM blobs), block "ignore previous instructions"-style prompt injection attempts, enforce citation presence, and cap prompt payload length (default 16 kB). Guardrail outcomes and redaction counts surface via `advisory_guardrail_blocks` / `advisory_outputs_stored` metrics.
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## 5) Deterministic tooling
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- **Version comparators** — offline semantic version + RPM EVR parsers with range evaluators. Supports chained constraints (`>=`, `<=`, `!=`) used by remediation advice and blast radius calcs.
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- Registered via `AddAdvisoryDeterministicToolset` for reuse across orchestrator, CLI, and services.
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- **Orchestration pipeline** — see `orchestration-pipeline.md` for prerequisites, task breakdown, and cross-guild responsibilities before wiring the execution flows.
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- **Planned extensions** — NEVRA/EVR comparators, ecosystem-specific normalisers, dependency chain scorers (AIAI-31-003 scope).
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- Exposed via internal interfaces to allow orchestrator/toolchain reuse; all helpers stay side-effect free and deterministic for golden testing.
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## 6) Output persistence
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- Cached artefacts stored in `advisory_ai_outputs` with fields:
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- `output_hash` (sha256 of JSON response).
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- `input_digest` (hash of context pack).
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- `summary`, `conflicts`, `remediation`, `citations`.
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- `generated_at`, `model_id`, `profile` (Sovereign/FIPS etc.).
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- `signatures` (optional DSSE if run in deterministic mode).
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- Offline bundle format contains `summary.md`, `citations.json`, `context_manifest.json`, `signatures/`.
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## 7) Profiles & sovereignty
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- **Profiles:** `default`, `fips-local` (FIPS-compliant local model), `gost-local`, `cloud-openai` (optional, disabled by default). Each profile defines allowed models, key management, and telemetry endpoints.
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- **CryptoProfile/RootPack integration:** generated artefacts can be signed using configured CryptoProfile to satisfy procurement/trust requirements.
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## 8) APIs
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- `POST /api/v1/advisory/{task}` — executes Summary/Conflict/Remediation pipeline (`task` ∈ `summary|conflict|remediation`). Requests accept `{advisoryKey, artifactId?, policyVersion?, profile, preferredSections?, forceRefresh}` and return sanitized prompt payloads, citations, guardrail metadata, provenance hash, and cache hints.
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- `GET /api/v1/advisory/outputs/{cacheKey}?taskType=SUMMARY&profile=default` — retrieves cached artefacts for downstream consumers (Console, CLI, Export Center). Guardrail state and provenance hash accompany results.
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All endpoints accept `profile` parameter (default `fips-local`) and return `output_hash`, `input_digest`, and `citations` for verification.
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## 9) Observability
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- Metrics: `advisory_ai_requests_total{profile,type}`, `advisory_ai_latency_seconds`, `advisory_ai_validation_failures_total`.
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- Logs: include `output_hash`, `input_digest`, `profile`, `model_id`, `tenant`, `artifacts`. Sensitive context is not logged.
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- Traces: spans for retrieval, prompt assembly, model inference, validation, cache write.
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## 10) Operational controls
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- Feature flags per tenant (`ai.summary.enabled`, `ai.remediation.enabled`).
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- Rate limits (per tenant, per profile) enforced by Orchestrator to prevent runaway usage.
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- Offline/air-gapped deployments run local models packaged with Offline Kit; model weights validated via manifest digests.
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## 11) Hosting surfaces
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- **WebService** — exposes `/v1/advisory-ai/pipeline/{task}` to materialise plans and enqueue execution messages.
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- **Worker** — background service draining the advisory pipeline queue (file-backed stub) pending integration with shared transport.
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- Both hosts register `AddAdvisoryAiCore`, which wires the SBOM context client, deterministic toolset, pipeline orchestrator, and queue metrics.
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- SBOM base address + tenant metadata are configured via `AdvisoryAI:SbomBaseAddress` and propagated through `AddSbomContext`.
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# Advisory AI architecture
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> Captures the retrieval, guardrail, and inference packaging requirements defined in the Advisory AI implementation plan and related module guides.
|
||||
|
||||
## 1) Goals
|
||||
|
||||
- Summarise advisories/VEX evidence into operator-ready briefs with citations.
|
||||
- Explain conflicting statements with provenance and trust weights (using VEX Lens & Excititor data).
|
||||
- Suggest remediation plans aligned with Offline Kit deployment models and scheduler follow-ups.
|
||||
- Operate deterministically where possible; cache generated artefacts with digests for audit.
|
||||
|
||||
## 2) Pipeline overview
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||||
|
||||
```
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+---------------------+
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||||
Concelier/VEX Lens | Evidence Retriever |
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||||
Policy Engine ----> | (vector + keyword) | ---> Context Pack (JSON)
|
||||
Zastava runtime +---------------------+
|
||||
|
|
||||
v
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+-------------+
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| Prompt |
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| Assembler |
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+-------------+
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|
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v
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+-------------+
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| Guarded LLM |
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| (local/host)|
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+-------------+
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|
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v
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+-----------------+
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| Citation & |
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| Validation |
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+-----------------+
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|
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v
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+----------------+
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| Output cache |
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| (hash, bundle) |
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+----------------+
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```
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## 3) Retrieval & context
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||||
|
||||
- Hybrid search: vector embeddings (SBERT-compatible) + keyword filters for advisory IDs, PURLs, CVEs.
|
||||
- Context packs include:
|
||||
- Advisory raw excerpts with highlighted sections and source URLs.
|
||||
- VEX statements (normalized tuples + trust metadata).
|
||||
- Policy explain traces for the affected finding.
|
||||
- Runtime/impact hints from Zastava (exposure, entrypoints).
|
||||
- Export-ready remediation data (fixed versions, patches).
|
||||
- **SBOM context retriever** (AIAI-31-002) hydrates:
|
||||
- Version timelines (first/last observed, status, fix availability).
|
||||
- Dependency paths (runtime vs build/test, deduped by coordinate chain).
|
||||
- Tenant environment flags (prod/stage toggles) with optional blast radius summary.
|
||||
- Service-side clamps: max 500 timeline entries, 200 dependency paths, with client-provided toggles for env/blast data.
|
||||
- `AddSbomContextHttpClient(...)` registers the typed HTTP client that calls `/v1/sbom/context`, while `NullSbomContextClient` remains the safe default for environments that have not yet exposed the SBOM service.
|
||||
|
||||
**Sample configuration** (wire real SBOM base URL + API key):
|
||||
|
||||
```csharp
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services.AddSbomContextHttpClient(options =>
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{
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options.BaseAddress = new Uri("https://sbom-service.internal");
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options.Endpoint = "/v1/sbom/context";
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options.ApiKey = configuration["SBOM_SERVICE_API_KEY"];
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options.UserAgent = "stellaops-advisoryai/1.0";
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options.Tenant = configuration["TENANT_ID"];
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});
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||||
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services.AddAdvisoryPipeline();
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||||
```
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||||
|
||||
After configuration, issue a smoke request (e.g., `ISbomContextRetriever.RetrieveAsync`) during deployment validation to confirm end-to-end connectivity and credentials before enabling Advisory AI endpoints.
|
||||
|
||||
Retriever requests and results are trimmed/normalized before hashing; metadata (counts, provenance keys) is returned for downstream guardrails. Unit coverage ensures deterministic ordering and flag handling.
|
||||
|
||||
All context references include `content_hash` and `source_id` enabling verifiable citations.
|
||||
|
||||
## 4) Guardrails
|
||||
|
||||
- Prompt templates enforce structure: summary, conflicts, remediation, references.
|
||||
- Response validator ensures:
|
||||
- No hallucinated advisories (every fact must map to input context).
|
||||
- Citations follow `[n]` indexing referencing actual sources.
|
||||
- Remediation suggestions only cite policy-approved sources (fixed versions, vendor hotfixes).
|
||||
- Moderation/PII filters prevent leaking secrets; responses failing validation are rejected and logged.
|
||||
- Pre-flight guardrails redact secrets (AWS keys, generic API tokens, PEM blobs), block "ignore previous instructions"-style prompt injection attempts, enforce citation presence, and cap prompt payload length (default 16 kB). Guardrail outcomes and redaction counts surface via `advisory_guardrail_blocks` / `advisory_outputs_stored` metrics.
|
||||
|
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## 5) Deterministic tooling
|
||||
|
||||
- **Version comparators** — offline semantic version + RPM EVR parsers with range evaluators. Supports chained constraints (`>=`, `<=`, `!=`) used by remediation advice and blast radius calcs.
|
||||
- Registered via `AddAdvisoryDeterministicToolset` for reuse across orchestrator, CLI, and services.
|
||||
- **Orchestration pipeline** — see `orchestration-pipeline.md` for prerequisites, task breakdown, and cross-guild responsibilities before wiring the execution flows.
|
||||
- **Planned extensions** — NEVRA/EVR comparators, ecosystem-specific normalisers, dependency chain scorers (AIAI-31-003 scope).
|
||||
- Exposed via internal interfaces to allow orchestrator/toolchain reuse; all helpers stay side-effect free and deterministic for golden testing.
|
||||
|
||||
## 6) Output persistence
|
||||
|
||||
- Cached artefacts stored in `advisory_ai_outputs` with fields:
|
||||
- `output_hash` (sha256 of JSON response).
|
||||
- `input_digest` (hash of context pack).
|
||||
- `summary`, `conflicts`, `remediation`, `citations`.
|
||||
- `generated_at`, `model_id`, `profile` (Sovereign/FIPS etc.).
|
||||
- `signatures` (optional DSSE if run in deterministic mode).
|
||||
- Offline bundle format contains `summary.md`, `citations.json`, `context_manifest.json`, `signatures/`.
|
||||
|
||||
## 7) Profiles & sovereignty
|
||||
|
||||
- **Profiles:** `default`, `fips-local` (FIPS-compliant local model), `gost-local`, `cloud-openai` (optional, disabled by default). Each profile defines allowed models, key management, and telemetry endpoints.
|
||||
- **CryptoProfile/RootPack integration:** generated artefacts can be signed using configured CryptoProfile to satisfy procurement/trust requirements.
|
||||
|
||||
## 8) APIs
|
||||
|
||||
- `POST /api/v1/advisory/{task}` — executes Summary/Conflict/Remediation pipeline (`task` ∈ `summary|conflict|remediation`). Requests accept `{advisoryKey, artifactId?, policyVersion?, profile, preferredSections?, forceRefresh}` and return sanitized prompt payloads, citations, guardrail metadata, provenance hash, and cache hints.
|
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- `GET /api/v1/advisory/outputs/{cacheKey}?taskType=SUMMARY&profile=default` — retrieves cached artefacts for downstream consumers (Console, CLI, Export Center). Guardrail state and provenance hash accompany results.
|
||||
|
||||
All endpoints accept `profile` parameter (default `fips-local`) and return `output_hash`, `input_digest`, and `citations` for verification.
|
||||
|
||||
## 9) Observability
|
||||
|
||||
- Metrics: `advisory_ai_requests_total{profile,type}`, `advisory_ai_latency_seconds`, `advisory_ai_validation_failures_total`.
|
||||
- Logs: include `output_hash`, `input_digest`, `profile`, `model_id`, `tenant`, `artifacts`. Sensitive context is not logged.
|
||||
- Traces: spans for retrieval, prompt assembly, model inference, validation, cache write.
|
||||
|
||||
## 10) Operational controls
|
||||
|
||||
- Feature flags per tenant (`ai.summary.enabled`, `ai.remediation.enabled`).
|
||||
- Rate limits (per tenant, per profile) enforced by Orchestrator to prevent runaway usage.
|
||||
- Offline/air-gapped deployments run local models packaged with Offline Kit; model weights validated via manifest digests.
|
||||
|
||||
## 11) Hosting surfaces
|
||||
|
||||
- **WebService** — exposes `/v1/advisory-ai/pipeline/{task}` to materialise plans and enqueue execution messages.
|
||||
- **Worker** — background service draining the advisory pipeline queue (file-backed stub) pending integration with shared transport.
|
||||
- Both hosts register `AddAdvisoryAiCore`, which wires the SBOM context client, deterministic toolset, pipeline orchestrator, and queue metrics.
|
||||
- SBOM base address + tenant metadata are configured via `AdvisoryAI:SbomBaseAddress` and propagated through `AddSbomContext`.
|
||||
|
||||
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