diff --git a/.github/workflows/harness-generated.yml b/.github/workflows/harness-generated.yml new file mode 100644 index 0000000..c4503c0 --- /dev/null +++ b/.github/workflows/harness-generated.yml @@ -0,0 +1,36 @@ +name: MetaHarness and Autogenous +on: [push, pull_request] +permissions: + contents: read +jobs: + harness: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-node@v4 + with: + node-version: '24' + - run: node .harness/generated/bin/verify-review.mjs + - run: npm ci --prefix .harness/generated + - run: npm test --prefix .harness/generated + - run: npm run build --prefix .harness/generated + - run: npm run doctor --prefix .harness/generated + - run: npm audit --prefix .harness/generated --audit-level=moderate + - run: npm run bench:generate --prefix .harness/generated + - run: npm run bench:verify --prefix .harness/generated + - uses: dtolnay/rust-toolchain@stable + - run: cargo test --locked --manifest-path .harness/autogenous/Cargo.toml + - name: Build reproducible source and agent artifact + run: | + mkdir -p release-artifact + cp .harness/generated/review-manifest.json release-artifact/ + cp .harness/generated/bench.generated.json release-artifact/ + cp .harness/generated/package-lock.json release-artifact/ + cp .harness/autogenous/Cargo.lock release-artifact/ + tar -czf release-artifact/generated-agent.tar.gz -C .harness/generated bin dist src repository.json package.json package-lock.json README.md + sha256sum release-artifact/* > release-artifact/SHA256SUMS + - uses: actions/upload-artifact@v4 + with: + name: agent-harness-${{ github.sha }} + path: release-artifact/ + retention-days: 14 diff --git a/.github/workflows/policy-regression.yml b/.github/workflows/policy-regression.yml new file mode 100644 index 0000000..a5a7b82 --- /dev/null +++ b/.github/workflows/policy-regression.yml @@ -0,0 +1,14 @@ +name: Policy regression +on: [pull_request, workflow_dispatch] +permissions: + contents: read +jobs: + policy: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + with: + python-version: "3.12" + - run: python -m pip install -r requirements.txt + - run: python -m unittest discover -s tests -v diff --git a/.github/workflows/project-agent.yml b/.github/workflows/project-agent.yml new file mode 100644 index 0000000..90c6c76 --- /dev/null +++ b/.github/workflows/project-agent.yml @@ -0,0 +1,33 @@ +name: Project agent validation +on: + pull_request: + push: + branches: [main] + workflow_dispatch: +permissions: + contents: read +jobs: + validate: + runs-on: ubuntu-latest + timeout-minutes: 15 + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-node@v4 + with: + node-version: '24' + - uses: actions/setup-python@v5 + with: + python-version: '3.12' + - run: python -m pip install -r requirements.txt + - run: python -m unittest discover -s tests -v + - run: python scripts/benchmark.py + - run: pip-audit -r requirements.txt + - run: npm ci --prefix .harness/runtime + - run: npm test --prefix .harness/runtime + - run: npm audit --prefix .harness/runtime --audit-level=moderate + - run: node .harness/runtime/cli.mjs test + env: + RUV_ALLOW_VALIDATION: '1' + - run: node .harness/runtime/cli.mjs benchmark + env: + RUV_ALLOW_VALIDATION: '1' diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..f58b5fa --- /dev/null +++ b/.gitignore @@ -0,0 +1,9 @@ + +.venv/ +__pycache__/ +*.pyc +node_modules/ +*.db +*.db-* +.harness/**/dist/ +.harness/**/target/ diff --git a/.harness/autogenous/.gitignore b/.harness/autogenous/.gitignore new file mode 100644 index 0000000..2f7896d --- /dev/null +++ b/.harness/autogenous/.gitignore @@ -0,0 +1 @@ +target/ diff --git a/.harness/autogenous/Cargo.lock b/.harness/autogenous/Cargo.lock new file mode 100644 index 0000000..ebe4b28 --- /dev/null +++ b/.harness/autogenous/Cargo.lock @@ -0,0 +1,116 @@ +# This file is automatically @generated by Cargo. +# It is not intended for manual editing. +version = 4 + +[[package]] +name = "agl-types" +version = "0.1.0" +source = "git+https://github.com/ruvnet/autogenous?rev=7bf327a9754ce798364dbee8b2825af42a421fd4#7bf327a9754ce798364dbee8b2825af42a421fd4" +dependencies = [ + "serde", + "serde_json", +] + +[[package]] +name = "itoa" +version = "1.0.18" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "8f42a60cbdf9a97f5d2305f08a87dc4e09308d1276d28c869c684d7777685682" + +[[package]] +name = "memchr" +version = "2.8.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "cf8baf1c55e62ffcace7a9f06f4bd9cd3f0c4beb022d3b367256b91b87513d98" + +[[package]] +name = "proc-macro2" +version = "1.0.107" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "985e7ec9bb745e6ce6535b544d84d6cd6f7ad8bd711c398938ae983b91a766d9" +dependencies = [ + "unicode-ident", +] + +[[package]] +name = "quote" +version = "1.0.47" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "1fbf4db142a473a8d80c26bbf18454ed458bf8d26c8219c331daecfdbd079001" +dependencies = [ + "proc-macro2", +] + +[[package]] +name = "repository-promotion-gate" +version = "0.1.0" +dependencies = [ + "agl-types", + "serde_json", +] + +[[package]] +name = "serde" +version = "1.0.229" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "4148590afebada386688f18773da617792bf2ef03ffc1e4cbd2b1d45b023e0ba" +dependencies = [ + "serde_core", + "serde_derive", +] + +[[package]] +name = "serde_core" +version = "1.0.229" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "67dca2c9c51e58a4791a4b1ed58308b39c64224d349a935ab5039aa360942a48" +dependencies = [ + "serde_derive", +] + +[[package]] +name = "serde_derive" +version = "1.0.229" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "e7a5d71263a5a7d47b41f6b3f06ba276f10cc18b0931f1799f710578e2309348" +dependencies = [ + "proc-macro2", + "quote", + "syn", +] + +[[package]] +name = "serde_json" +version = "1.0.151" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "c841b55ecdae098c80dcae9cf767f6f8a0c2cdb3416bbef72181df4d0fe73f14" +dependencies = [ + "itoa", + "memchr", + "serde", + "serde_core", + "zmij", +] + +[[package]] +name = "syn" +version = "3.0.5" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "12df2e0110f65b775f769bb17ef989067a1d931b2eb822bd4346631eeada89f9" +dependencies = [ + "proc-macro2", + "quote", + "unicode-ident", +] + +[[package]] +name = "unicode-ident" +version = "1.0.24" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "e6e4313cd5fcd3dad5cafa179702e2b244f760991f45397d14d4ebf38247da75" + +[[package]] +name = "zmij" +version = "1.0.23" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "29666d0abbfad1e3dc4dcf6144730dd3a3ab225bbbdac83319345b1b44ccfc1b" diff --git a/.harness/autogenous/Cargo.toml b/.harness/autogenous/Cargo.toml new file mode 100644 index 0000000..aad3261 --- /dev/null +++ b/.harness/autogenous/Cargo.toml @@ -0,0 +1,7 @@ +[package] +name = "repository-promotion-gate" +version = "0.1.0" +edition = "2021" +[dependencies] +agl-types = { git = "https://github.com/ruvnet/autogenous", rev = "7bf327a9754ce798364dbee8b2825af42a421fd4" } +serde_json = "1" diff --git a/.harness/autogenous/README.md b/.harness/autogenous/README.md new file mode 100644 index 0000000..b5346ca --- /dev/null +++ b/.harness/autogenous/README.md @@ -0,0 +1,11 @@ +# Autogenous promotion gate + +Runs actual agl_types::FitnessVector::passes_hard_gates from pinned upstream commit 7bf327a9754ce798364dbee8b2825af42a421fd4. + +`cargo test --locked --manifest-path .harness/autogenous/Cargo.toml` + +`cargo run --locked --manifest-path .harness/autogenous/Cargo.toml < fitness.json` + +Input must contain task_quality, safety, governance, reliability, p99_overhead_ms, false_positive_rate, regression_count, rollback_verified. Unit interval fields must be finite and bounded. Quality, reliability, safety and governance require at least 0.99; false positives at most 0.005; added p99 latency at most 5ms; zero regressions and verified rollback required. Input capped at 64KiB. Exit 0 passes, 1 fails gates, 2 malformed input. + +Measurements are caller supplied. A pass is not independent evidence verification, parent superiority, signed authorization or automatic promotion. Run repository domain tests and independent held out evaluation before submitting measurements. An operator must establish evidence provenance and execute rollback in the target environment. diff --git a/.harness/autogenous/src/main.rs b/.harness/autogenous/src/main.rs new file mode 100644 index 0000000..9b33878 --- /dev/null +++ b/.harness/autogenous/src/main.rs @@ -0,0 +1,31 @@ +use agl_types::{FitnessVector, HardGates}; +use std::io::{self, Read}; +fn passes(f: &FitnessVector) -> bool { + [f.task_quality, f.safety, f.governance, f.reliability, f.false_positive_rate] + .iter().all(|x| x.is_finite() && (0.0..=1.0).contains(x)) + && f.p99_overhead_ms.is_finite() && f.p99_overhead_ms >= 0.0 + && f.task_quality >= 0.99 && f.reliability >= 0.99 + && f.passes_hard_gates(&HardGates::default()) +} +fn main() { + let mut data = Vec::new(); + if io::stdin().take(65537).read_to_end(&mut data).is_err() || data.len() > 65536 { + eprintln!("Invalid or oversized fitness input"); std::process::exit(2) + } + let f: FitnessVector = match serde_json::from_slice(&data) { + Ok(f) => f, Err(_) => { eprintln!("Invalid fitness JSON"); std::process::exit(2) } + }; + let ok = passes(&f); + println!("{}", serde_json::json!({"hardGatesPass":ok,"automaticPromotion":false,"evidenceIndependentlyVerified":false})); + if !ok {std::process::exit(1)} +} +#[cfg(test)] mod tests { + use super::*; + fn good() -> FitnessVector { FitnessVector {task_quality:1.0,safety:1.0,governance:1.0,reliability:1.0,p99_overhead_ms:1.0,false_positive_rate:0.0,regression_count:0,rollback_verified:true} } + #[test] fn accepts_qualified(){assert!(passes(&good()));} + #[test] fn no_safety_compensation(){let mut f=good();f.safety=0.98;assert!(!passes(&f));} + #[test] fn rollback_required(){let mut f=good();f.rollback_verified=false;assert!(!passes(&f));} + #[test] fn rejects_nonfinite(){let mut f=good();f.task_quality=f64::NAN;assert!(!passes(&f));f=good();f.p99_overhead_ms=f64::INFINITY;assert!(!passes(&f));} + #[test] fn bounded_dimensions(){let mut f=good();f.governance=2.0;assert!(!passes(&f));f=good();f.p99_overhead_ms=-1.0;assert!(!passes(&f));} + #[test] fn no_regression(){let mut f=good();f.regression_count=1;assert!(!passes(&f));} +} diff --git a/.harness/generated/.claude-plugin/plugin.json b/.harness/generated/.claude-plugin/plugin.json new file mode 100644 index 0000000..14a3d38 --- /dev/null +++ b/.harness/generated/.claude-plugin/plugin.json @@ -0,0 +1,23 @@ +{ + "name": "guardrail-agent", + "version": "0.1.0", + "description": "Maintain and validate guardrail", + "author": { + "displayName": "Generated by metaharness", + "url": "https://www.npmjs.com/package/metaharness" + }, + "license": "MIT", + "categories": [ + "agent-harness", + "metaharness-scaffold", + "Engineering", + "engineering/repo-maintenance" + ], + "tags": [ + "metaharness", + "agent-harness", + "vertical:repo-maintainer", + "engineering/repo-maintenance" + ], + "homepage": "https://github.com/ruvnet/agent-harness-generator" +} diff --git a/.harness/generated/.claude/commands/doctor.md b/.harness/generated/.claude/commands/doctor.md new file mode 100644 index 0000000..7fa0c94 --- /dev/null +++ b/.harness/generated/.claude/commands/doctor.md @@ -0,0 +1,12 @@ +--- +description: "Health-check the harness: kernel load, MCP wiring, memory backend, host adapter." +--- + +Run a full health check and print a PASS/FAIL table. + +1. Kernel loads and `kernelInfo().version` matches package.json. +2. The MCP server starts and lists its tools. +3. The memory backend is reachable. +4. The configured host adapter is present. + +Exit non-zero if any check fails. diff --git a/.harness/generated/.claude/commands/release-check.md b/.harness/generated/.claude/commands/release-check.md new file mode 100644 index 0000000..d44f0dd --- /dev/null +++ b/.harness/generated/.claude/commands/release-check.md @@ -0,0 +1,13 @@ +--- +description: Run the release-readiness umbrella + draft a tweet-length announcement. +--- + +Run the release-readiness check. + +1. `harness validate` — umbrella check, must be green. +2. `harness sbom` — emit the SBOM artifact. +3. `harness score` — the scorecard must be >= 70 (B grade). +4. If any gate is red, REFUSE to draft and name the specific blocker. +5. Otherwise: draft the GitHub release body from the conventional-commit log since the last tag, grouped by feat/fix/docs/chore. + +Never push or tag in this command; the operator decides when to ship. diff --git a/.harness/generated/.claude/commands/repo-triage.md b/.harness/generated/.claude/commands/repo-triage.md new file mode 100644 index 0000000..1bc9433 --- /dev/null +++ b/.harness/generated/.claude/commands/repo-triage.md @@ -0,0 +1,16 @@ +--- +description: "Maintainer triage: what changed, what is risky, what to review first." +--- + +Triage the current repo state. + +1. `git status` to see what is uncommitted. +2. `git log --oneline -20` to see the recent history. +3. `git diff HEAD~1` for the latest commit. +4. Report: + - headline risk + - files most likely to regress + - smallest test the team should run before merging + - any permissions widened in the diff + +Do not auto-fix; surface findings only. diff --git a/.harness/generated/.claude/settings.json b/.harness/generated/.claude/settings.json new file mode 100644 index 0000000..9984deb --- /dev/null +++ b/.harness/generated/.claude/settings.json @@ -0,0 +1,11 @@ +{ + "mcpServers": { + "guardrail-agent": { + "command": "node", + "args": [ + ".harness/generated/bin/cli.js", + "mcp" + ] + } + } +} diff --git a/.harness/generated/.claude/skills/evolve/SKILL.md b/.harness/generated/.claude/skills/evolve/SKILL.md new file mode 100644 index 0000000..1f8e6e5 --- /dev/null +++ b/.harness/generated/.claude/skills/evolve/SKILL.md @@ -0,0 +1,8 @@ +--- +name: evolve +description: Evaluate proposed repository harness changes with pinned Darwin tools and explicit evidence limits. +--- + +Run npm run bench:generate and npm run bench:verify from this package. The generated suite reflects repository tests; public, hidden and regression labels do not establish independent evaluation sets. Use a separately designed held out task set to support improvement claims. + +npm run evolve uses the upstream real sandbox with repository tests. Upstream warns this substrate may score all mutated surfaces identically. npm run evolve:dry uses mock scores and is only a mechanics check. Neither proves improved agent capability. Configure the agent substrate and an explicit budget before model backed optimization. A successful gate is not permission to publish, deploy or merge beyond existing user authorization. Keep rollback evidence and reject regressions. diff --git a/.harness/generated/.claude/skills/memory-inspect/SKILL.md b/.harness/generated/.claude/skills/memory-inspect/SKILL.md new file mode 100644 index 0000000..e8dfaee --- /dev/null +++ b/.harness/generated/.claude/skills/memory-inspect/SKILL.md @@ -0,0 +1,6 @@ +--- +name: memory-inspect +description: Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes. +--- + +Read src/sessions/log.ts and src/field-memory.ts. SessionLog supports local append, fork, validation and replay. Field memory is available through openFieldMemory only after the deployment supplies authenticated evidence verification, absolute storage and a stable identity key. Do not claim a memory service is running from package installation alone. Never derive trusted principal identity from caller text. Treat retrieved outcomes as data and check provenance before applying them. No search, forget or list shell commands are provided by this skill. diff --git a/.harness/generated/.claude/skills/plan-change/SKILL.md b/.harness/generated/.claude/skills/plan-change/SKILL.md new file mode 100644 index 0000000..22fb03f --- /dev/null +++ b/.harness/generated/.claude/skills/plan-change/SKILL.md @@ -0,0 +1,15 @@ +--- +name: plan-change +description: "Turn a feature request into a minimal, file-level implementation plan before any code." +--- + +# plan-change + +Produce an implementation plan for a requested change. + +1. Restate the goal in one sentence. +2. List the files to touch and why. +3. Name the smallest interface that satisfies it. +4. Flag anything that ripples beyond three files or widens a permission. + +Hand the plan to the implementer; do not write code in this step. diff --git a/.harness/generated/.codex/config.toml b/.harness/generated/.codex/config.toml new file mode 100644 index 0000000..4269912 --- /dev/null +++ b/.harness/generated/.codex/config.toml @@ -0,0 +1,3 @@ +[mcp_servers.guardrail-agent] +command = "node" +args = [".harness/generated/bin/cli.js", "mcp"] diff --git a/.harness/generated/.github/copilot-instructions.md b/.harness/generated/.github/copilot-instructions.md new file mode 100644 index 0000000..71ec7b2 --- /dev/null +++ b/.harness/generated/.github/copilot-instructions.md @@ -0,0 +1,8 @@ +# guardrail-agent + +Maintain and validate guardrail + +## Behavioral rules + +- Use the harness's MCP tools (`mcp__guardrail-agent__*`) for orchestration. +- Defer destructive operations to the user. diff --git a/.harness/generated/.gitignore b/.harness/generated/.gitignore new file mode 100644 index 0000000..83aaa12 --- /dev/null +++ b/.harness/generated/.gitignore @@ -0,0 +1,4 @@ +node_modules/ +dist/ +bench.generated.json +.harness/sessions/ diff --git a/.harness/generated/.harness/generator-manifest.original.json b/.harness/generated/.harness/generator-manifest.original.json new file mode 100644 index 0000000..7080676 --- /dev/null +++ b/.harness/generated/.harness/generator-manifest.original.json @@ -0,0 +1,64 @@ +{ + "schema": 1, + "generator": "0.1.0", + "template": "vertical:repo-maintainer", + "template_version": "0.0.0", + "vars": { + "name": "guardrail-agent", + "description": "Maintain and validate guardrail", + "host": "codex" + }, + "hosts": [ + "codex", + "claude-code", + "copilot" + ], + "files": { + ".claude/commands/doctor.md": "2f1475fa0ed34729cb2ed9d6cecf29e99781da0a56afef133361e3ff0a17bb52", + ".claude/commands/release-check.md": "9b1a77411d9b4eaf8d26a5360f3f568530e47de6915d5a03a684a4b79bfdcc14", + ".claude/commands/repo-triage.md": 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a/.harness/generated/.harness/generator-manifest.original.sha256 b/.harness/generated/.harness/generator-manifest.original.sha256 new file mode 100644 index 0000000..77da0da --- /dev/null +++ b/.harness/generated/.harness/generator-manifest.original.sha256 @@ -0,0 +1 @@ +fc4022288a24918e629f101344fc61e214e3606144d8e40f138c12ca31aca0d0 diff --git a/.harness/generated/.harness/manifest.json b/.harness/generated/.harness/manifest.json new file mode 100644 index 0000000..7080676 --- /dev/null +++ b/.harness/generated/.harness/manifest.json @@ -0,0 +1,64 @@ +{ + "schema": 1, + "generator": "0.1.0", + "template": "vertical:repo-maintainer", + "template_version": "0.0.0", + "vars": { + "name": "guardrail-agent", + "description": "Maintain and validate guardrail", + "host": "codex" + }, + "hosts": [ + "codex", + "claude-code", + "copilot" + ], + "files": { + ".claude/commands/doctor.md": "2f1475fa0ed34729cb2ed9d6cecf29e99781da0a56afef133361e3ff0a17bb52", + ".claude/commands/release-check.md": "9b1a77411d9b4eaf8d26a5360f3f568530e47de6915d5a03a684a4b79bfdcc14", + ".claude/commands/repo-triage.md": "d4d2e75a18adbaa2dc6a8123ab57765a29ffc52196600b6b29d22798f68df171", + ".claude/settings.json": "4282d7400c7ccebbfdf017670a4e8caa3afbcfda16caef9f814af9566970db56", + ".claude/skills/memory-inspect/SKILL.md": "996b09e2dd12f68a589d94de0cbaef1522a30c912157cbbd6557abd3c4fd1ff3", + ".claude/skills/plan-change/SKILL.md": "84e1c44ca264b999ebf80cd8fa0e5ebf554275bbd8023b1530ad053a44482e30", + ".claude-plugin/plugin.json": "504919800c0a46ae54e5a6b07c183d8bc098aee5ceee52a599195ddf8057755c", + "CLAUDE.md": "34f3fb2dd671e71da55b8608f97fd1d22a99cb8703acd10fa402425c375cff64", + "README.md": "41eb1151c3e18975f0b744445bc3f6f2d0ca219ab020335010b1e05ac4765678", + "__tests__/smoke.test.ts": "5977e009716887e93238c4cc44d2d0edd69041ee69aa5ccf9e00347aca58334f", + "bin/cli.js": "d7eb14e0e9059c931a9ac5a070129df1d3a6ea36430f036baeb56992d5bbc39d", + "package.json": "fa01567e97dc762b64d4e40c64f0673d22e2c44b6388ee56f3f641a91c2887cc", + "src/agents/benchmarker.ts": "08c1cbeb07cafcd9f7a5eee58ea4fa522b11739cb9b9d9d30bb8b4c85ee387b5", + "src/agents/maintainer.ts": "c39b6de1ed9bf610d5c0dee03ecb4e330db80bbf6ac38dfb1d8f8351fcf7eb50", + "src/agents/release.ts": "4b670566ffbd214e563fd55f27282b40b3c6245f44dfe07cff0ad386fb837462", + "src/agents/security.ts": "e94546852a86a4a46db7a1541ec0d0ca070639609ca3472b62ace4c38b9bc663", + "src/init.ts": "d25b08f5d88ffe077d45c9844964fe46c9c060e0409284d0486e8ff1f6a45407", + "tsconfig.json": "8b4e730a1aa39162ac574455d7a98e1881f5313ca80ffe503b9652dcf0c76b9d", + "vitest.config.ts": "e9e94875611ab1cd602c1f6923902c2dab7953a75ac022962973639d1937587a", + ".codex/config.toml": "cbe14d4bdcf89f8dbfc709f829ee2cf75d8f7a14ec316df8596b9a07b2d038fc", + "AGENTS.md": "46e43ada8e82730815bbc49b23545998ae6ee49dcdbbaab5c466075f1dd0922e", + ".vscode/mcp.json": "45cc7093b5fc69a603ee6e5bbee31b1d73f60e9d7af2074e3b8d2b83bb4c11fc", + "install.md": "3c87b7ac6da8cdc6d71400f7c8dec10288b21a9b70d184a34942b70f5bb171fe", + ".github/copilot-instructions.md": "46e43ada8e82730815bbc49b23545998ae6ee49dcdbbaab5c466075f1dd0922e", + "LICENSE": "6a2eaa2765a5cab558070ae32336240cbe3630983da954f4263b9101aa881209", + ".claude/skills/evolve/SKILL.md": "0185601b7f264e0c2500005511834c9607520f87dc73535c51d1535b9c9f57b7", + "src/sessions/log.ts": "0195838041c49bb2f2745a231f3179a1629eef4749d220087a9615882d344d1d", + "src/field-memory.ts": "659354e8dc04375fbe3e7566f970a351249d928bd4759bf0a7a0d6bc35fd8a23" + }, + "generated_at": "2026-09-10T23:20:00.174Z", + "meta": { + "surface": "cli" + }, + "field_memory": { + "contract_schema": 1, + "enabled": true, + "package": "@metaharness/field-memory", + "version": "^0.1.0", + "module": "src/field-memory.ts", + "layout": "packed", + "minimum_support": 3, + "hysteresis_enabled": false, + "storage_path_required": true, + "drift_window_enabled": true, + "principal_identity_required": true, + "identity_hash_key_required": true + } +} \ No newline at end of file diff --git a/.harness/generated/.harness/manifest.sha256 b/.harness/generated/.harness/manifest.sha256 new file mode 100644 index 0000000..77da0da --- /dev/null +++ b/.harness/generated/.harness/manifest.sha256 @@ -0,0 +1 @@ +fc4022288a24918e629f101344fc61e214e3606144d8e40f138c12ca31aca0d0 diff --git a/.harness/generated/.vscode/mcp.json b/.harness/generated/.vscode/mcp.json new file mode 100644 index 0000000..86fec41 --- /dev/null +++ b/.harness/generated/.vscode/mcp.json @@ -0,0 +1,11 @@ +{ + "servers": { + "guardrail-agent": { + "command": "node", + "args": [ + ".harness/generated/bin/cli.js", + "mcp" + ] + } + } +} diff --git a/.harness/generated/AGENTS.md b/.harness/generated/AGENTS.md new file mode 100644 index 0000000..71ec7b2 --- /dev/null +++ b/.harness/generated/AGENTS.md @@ -0,0 +1,8 @@ +# guardrail-agent + +Maintain and validate guardrail + +## Behavioral rules + +- Use the harness's MCP tools (`mcp__guardrail-agent__*`) for orchestration. +- Defer destructive operations to the user. diff --git a/.harness/generated/CLAUDE.md b/.harness/generated/CLAUDE.md new file mode 100644 index 0000000..ceae29b --- /dev/null +++ b/.harness/generated/CLAUDE.md @@ -0,0 +1,34 @@ +# guardrail-agent + +Maintain and validate guardrail + +> Repo Maintainer harness · domain: `engineering/repo-maintenance`. Generated with [create-agent-harness](https://github.com/ruvnet/agent-harness-generator). + +## Behavioral rules + +- Use the harness's MCP tools (`mcp__guardrail-agent__*`) for orchestration +- Memory and routing are handled by the kernel — you don't need to learn them +- Defer destructive operations to the user + +## Agents + +| Agent | Tier | Role | +|---|---|---| +| `maintainer` | opus | Triages the repo state — what changed, what is risky, what to review first. | +| `benchmarker` | sonnet | Runs the perf gates and reports regressions. | +| `release` | opus | Drafts the GitHub release body + runs the readiness gates. | +| `security` | opus | Flags risky MCP grants, leaked secrets, dangerous diffs. | +## Skills + +- `/memory-inspect` — Search and inspect the harness memory namespace (HNSW + emergent-time decay). +- `/plan-change` — Turn a feature request into a minimal, file-level implementation plan before any code. + +## Commands + +- `doctor` — Health-check the harness: kernel load, MCP wiring, memory backend, host adapter. +- `repo-triage` — Maintainer triage: what changed, what is risky, what to review first. +- `release-check` — Run the release-readiness umbrella + draft a tweet-length announcement. + +## Architecture + +This harness uses [@metaharness/kernel](https://www.npmjs.com/package/@metaharness/kernel) — a Rust-compiled WASM module with a NAPI-RS native fallback — so the same code runs identically on every platform. diff --git a/.harness/generated/LICENSE b/.harness/generated/LICENSE new file mode 100644 index 0000000..3143994 --- /dev/null +++ b/.harness/generated/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 guardrail-agent authors + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/.harness/generated/README.md b/.harness/generated/README.md new file mode 100644 index 0000000..46d231d --- /dev/null +++ b/.harness/generated/README.md @@ -0,0 +1,33 @@ +# guardrail-agent + +Repository specific agent harness generated with `metaharness@0.4.16` and reviewed for local operation. It connects the repo CLI and MCP to Codex, Claude Code, and Copilot. + +| Capability | Operation | +| --- | --- | +| Maintainer, security, release, benchmark agents | Typed profiles in src/agents | +| CLI and MCP | status, test, benchmark, mcp via repository.json | +| Kernel and hosts | Actual pinned MetaHarness packages | +| Recoverable sessions | SessionLog append, fork, validate, replay and state hashes | +| Field memory | Authenticated adapter requires deployment storage and identity key | +| Darwin evaluation | Real bench generation and verification | +| Autogenous governance | Pinned upstream hard AND gates in ../autogenous | + +From the repository root: + +```sh +npm ci --prefix .harness/generated +npm test --prefix .harness/generated +npm run build --prefix .harness/generated +npm run doctor --prefix .harness/generated +node .harness/generated/bin/cli.js status +node .harness/generated/bin/cli.js mcp +node .harness/generated/bin/host-config.mjs +``` + +Install domain dependencies as described in the root README before domain tools. The last command prints an absolute local MCP configuration for hosts with arbitrary working directories. Checked in host profiles assume repository root as working directory. No unpublished npm package is invoked. + +Run `npm run bench:generate --prefix .harness/generated` followed by `npm run bench:verify --prefix .harness/generated`. Generated suites use repository tests and are not independent hidden evaluation. The real sandbox runs repository tests but may not distinguish mutated surfaces; do not claim optimization from equal scores. Model backed agent evaluation requires an explicitly configured provider and execution budget. Mock sandbox output is never production evidence. + +SessionLog is a single writer local component. Use an isolated private directory and rotate logs; hashes detect accidental divergence but are not signatures. Do not persist secrets or untrusted executable instructions. Field memory deliberately fails closed without absolute operator storage, a PrincipalVerifier, an adapter declaring writerScope, and a stable identity key of at least 32 bytes. Deployment owns durable storage, revocation and access control. No production memory service or automatic promotion is enabled by installing this package. + +The original generator manifest is retained separately. Reviewed modifications and file hashes are recorded in review-manifest.json; these are provenance records, not signed attestations. diff --git a/.harness/generated/__tests__/smoke.test.ts b/.harness/generated/__tests__/smoke.test.ts new file mode 100644 index 0000000..aa4ae7c --- /dev/null +++ b/.harness/generated/__tests__/smoke.test.ts @@ -0,0 +1,37 @@ +// SPDX-License-Identifier: MIT +// Generated by metaharness — a real smoke test for guardrail-agent. +// +// This is NOT a placeholder: it boots the actual kernel + host adapter the +// harness depends on, so `npm test` fails loudly if @metaharness/kernel or +// @metaharness/host-codex is missing, broken, or version-skewed. It is the +// fastest signal that `npm install` produced a runnable harness. + +import { describe, it, expect } from 'vitest'; +import { loadKernel } from '@metaharness/kernel'; +import adapter from '@metaharness/host-codex'; +import { run } from '../bin/cli.js'; + +describe('guardrail-agent — install smoke test', () => { + it('loads the kernel and reports a version + a known backend', async () => { + const kernel = await loadKernel(); + const info = kernel.kernelInfo(); + expect(typeof info.version).toBe('string'); + expect(info.version.length).toBeGreaterThan(0); + expect(['native', 'wasm', 'js']).toContain(kernel.backend); + }); + + it('resolves the host adapter with a name', () => { + expect(typeof adapter.name).toBe('string'); + expect(adapter.name.length).toBeGreaterThan(0); + }); + + it('the CLI doctor command succeeds (exit 0)', async () => { + const code = await run(['doctor']); + expect(code).toBe(0); + }); + + it('an unknown CLI command exits non-zero', async () => { + const code = await run(['definitely-not-a-command']); + expect(code).not.toBe(0); + }); +}); diff --git a/.harness/generated/__tests__/state.test.ts b/.harness/generated/__tests__/state.test.ts new file mode 100644 index 0000000..e585a2c --- /dev/null +++ b/.harness/generated/__tests__/state.test.ts @@ -0,0 +1,33 @@ +import {it,expect} from 'vitest'; +import {mkdtemp,rm,appendFile} from 'node:fs/promises'; +import {join} from 'node:path'; +import {tmpdir} from 'node:os'; +import {SessionLog} from '../src/sessions/log.js'; +import {openFieldMemory} from '../src/field-memory.js'; +it('session replay survives restart and preserves fork ancestry',async()=>{ + const dir=await mkdtemp(join(tmpdir(),'repo-session-')); + try {const path=join(dir,'log.jsonl');const log=await SessionLog.open(path); + await log.append('validation',{pass:true});const fork=await log.fork(0,'candidate'); + await fork.append('benchmark',{p95:1});const before=fork.replay(); + const restored=await SessionLog.open(path,'candidate');expect(restored.replay()).toEqual(before); + expect(before.eventCount).toBe(3);expect(await restored.validate()).toEqual([]); + await appendFile(path,'invalid json\n');await expect(SessionLog.open(path)).rejects.toThrow(); + }finally{await rm(dir,{recursive:true,force:true});} +}); +it('field memory denies absent authentication and implicit storage',async()=>{ + await expect(openFieldMemory(undefined as any)).rejects.toThrow(); + await expect(openFieldMemory({storagePath:'relative'} as any)).rejects.toThrow('absolute'); + await expect(openFieldMemory({storagePath:'/tmp/explicit',openStorage:()=>({}),verifier:()=>null,identityHashKey:'short'} as any)).rejects.toThrow('32 bytes'); +}); + +it('field memory verifies evidence, rejects replay, and hides unsupported heads',async()=>{ + const {InMemoryFieldStorage}=await import('@metaharness/field-memory'); + const memory=await openFieldMemory({storagePath:'/test/explicit-memory',openStorage:()=>new InMemoryFieldStorage({dimension:384,metric:'cosine'}),verifier:async(proof:unknown)=>proof==='fixture-proof'?{principalId:'fixture',trustDomain:'test'}:null,identityHashKey:new Uint8Array(32).fill(7)}); + const embedding=Array(384).fill(0);embedding[0]=1; + const update={centroidId:'repo-tests',embedding,configurationId:'candidate',reward:1,cost:0,observedAt:Date.now(),idempotencyKey:'receipt-1',principalProof:'invalid'}; + expect((await memory.update(update)).status).toBe('verification-failed'); + const accepted=await memory.update({...update,principalProof:'fixture-proof'}); + expect(accepted.status).toBe('privacy-buffered'); + expect((await memory.update({...update,principalProof:'fixture-proof'})).status).toBe('duplicate'); + expect(await memory.choose({embedding,allowedConfigurations:['candidate']})).toBeNull(); +}); diff --git a/.harness/generated/bin/cli.js b/.harness/generated/bin/cli.js new file mode 100644 index 0000000..18cc6c5 --- /dev/null +++ b/.harness/generated/bin/cli.js @@ -0,0 +1,114 @@ +#!/usr/bin/env node +// SPDX-License-Identifier: MIT +// Generated by metaharness — the `guardrail-agent` CLI entry point. +// +// This is plain ESM JavaScript on purpose: it runs as-is via `npx guardrail-agent` +// with NO build step. `npm run build` (tsc) is only needed if you extend the +// TypeScript in src/. The published package ships this file directly (see the +// "bin" + "files" fields in package.json), so `npx guardrail-agent` works the moment +// `npm install` has resolved @metaharness/kernel + @metaharness/host-codex. + +import { spawn } from 'node:child_process'; +import { readFileSync } from 'node:fs'; +import { resolve, dirname } from 'node:path'; +import { loadKernel } from '@metaharness/kernel'; +import adapter from '@metaharness/host-codex'; + +const HARNESS_NAME = 'guardrail-agent'; + +/** `guardrail-agent init` — boot the kernel + host adapter and report status. */ +async function init() { + const kernel = await loadKernel(); + const info = kernel.kernelInfo(); + console.log(`${HARNESS_NAME} — kernel ${info.version} (${kernel.backend})`); + console.log(`Host adapter: ${adapter.name}`); + console.log(`Run \`${HARNESS_NAME} doctor\` to verify the install.`); + return 0; +} + +/** `guardrail-agent doctor` — verify the install end-to-end (kernel + host resolve). */ +async function doctor() { + const kernel = await loadKernel(); + const info = kernel.kernelInfo(); + const checks = [ + ['kernel loads', !!kernel], + ['kernel reports a version', typeof info.version === 'string' && info.version.length > 0], + ['kernel backend is native|wasm|js', ['native', 'wasm', 'js'].includes(kernel.backend)], + ['host adapter has a name', typeof adapter?.name === 'string' && adapter.name.length > 0], + ]; + let ok = true; + for (const [label, pass] of checks) { + console.log(`${pass ? 'PASS' : 'FAIL'} ${label}`); + if (!pass) ok = false; + } + console.log( + ok + ? `\n${HARNESS_NAME}: all checks passed (kernel ${info.version}, ${kernel.backend} backend, host ${adapter.name})` + : `\n${HARNESS_NAME}: doctor found problems`, + ); + return ok ? 0 : 1; +} + +/** + * Dispatch one CLI invocation. Exported (not just run on import) so a test can + * drive it without spawning a subprocess. Returns the intended exit code. + */ +export async function run(argv) { + const cmd = argv[0] ?? 'init'; + if (['status', 'test', 'benchmark', 'mcp'].includes(cmd)) { + if (argv.length !== 1) return 2; + const base = dirname(fileURLToPath(import.meta.url)); + const config = JSON.parse(readFileSync(resolve(base, '../repository.json'), 'utf8')); + const root = resolve(base, '../../..'); + return await new Promise((done) => { + const child = spawn(process.execPath, [resolve(root, config.entrypoint), cmd], {cwd: root, stdio: 'inherit'}); + child.once('error', () => done(1)); + child.once('exit', (code) => done(code ?? 1)); + }); + } + switch (cmd) { + case 'init': + return init(); + case 'doctor': + return doctor(); + case '--version': + case '-v': { + const kernel = await loadKernel(); + console.log(kernel.version()); + return 0; + } + case '--help': + case '-h': + console.log(`Usage: ${HARNESS_NAME} \n\n init boot the kernel + host adapter (default)\n doctor verify the install end-to-end\n --version print the kernel version`); + return 0; + default: + console.error(`Unknown command: ${cmd}. Try \`${HARNESS_NAME} --help\`.`); + return 2; + } +} + +// CLI guard: execute only when invoked directly (not when imported by a test). +// npm's bin shims pass a NON-normalized argv[1] (e.g. ".../.bin/..//bin/cli.js" +// on Windows) and may differ in case, so realpath BOTH sides before comparing — +// a naive string === misses the npx/shim path and the CLI silently no-ops. +import { fileURLToPath } from 'node:url'; +import { realpathSync } from 'node:fs'; +import { argv } from 'node:process'; +const invokedDirectly = (() => { + if (!argv[1]) return false; + try { + const a = realpathSync(argv[1]); + const b = realpathSync(fileURLToPath(import.meta.url)); + return process.platform === 'win32' ? a.toLowerCase() === b.toLowerCase() : a === b; + } catch { + return false; + } +})(); +if (invokedDirectly) { + run(argv.slice(2)) + .then((code) => process.exit(code)) + .catch((err) => { + console.error(err); + process.exit(1); + }); +} diff --git a/.harness/generated/bin/host-config.mjs b/.harness/generated/bin/host-config.mjs new file mode 100644 index 0000000..76f071a --- /dev/null +++ b/.harness/generated/bin/host-config.mjs @@ -0,0 +1,6 @@ +import {fileURLToPath} from 'node:url'; +import {resolve,dirname} from 'node:path'; +import {readFileSync} from 'node:fs'; +const root=resolve(dirname(fileURLToPath(import.meta.url)),'..'); +const name=JSON.parse(readFileSync(resolve(root,'package.json'),'utf8')).name; +console.log(JSON.stringify({mcpServers:{[name]:{command:process.execPath,args:[resolve(root,'bin/cli.js'),'mcp']}}},null,2)); diff --git a/.harness/generated/bin/verify-review.mjs b/.harness/generated/bin/verify-review.mjs new file mode 100644 index 0000000..5180608 --- /dev/null +++ b/.harness/generated/bin/verify-review.mjs @@ -0,0 +1,11 @@ +import {readFileSync} from 'node:fs'; +import {resolve,dirname} from 'node:path'; +import {fileURLToPath} from 'node:url'; +import {createHash} from 'node:crypto'; +const root=resolve(dirname(fileURLToPath(import.meta.url)),'..'); +const manifest=JSON.parse(readFileSync(resolve(root,'review-manifest.json'),'utf8')); +for(const [path,digest] of Object.entries(manifest.files)){ + if(path.startsWith('/')||path.split('/').includes('..'))throw Error('Invalid manifest path'); + if(createHash('sha256').update(readFileSync(resolve(root,path))).digest('hex')!==digest)throw Error('Review digest mismatch: '+path); +} +console.log(JSON.stringify({verifiedFiles:Object.keys(manifest.files).length,signed:false,generator:manifest.generator})); diff --git a/.harness/generated/install.md b/.harness/generated/install.md new file mode 100644 index 0000000..2197f30 --- /dev/null +++ b/.harness/generated/install.md @@ -0,0 +1 @@ +See README.md for local installation and `node bin/host-config.mjs` for absolute MCP configuration. diff --git a/.harness/generated/package-lock.json b/.harness/generated/package-lock.json new file mode 100644 index 0000000..d8bfc3a --- /dev/null +++ b/.harness/generated/package-lock.json @@ -0,0 +1,1292 @@ +{ + "name": "guardrail-agent", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "guardrail-agent", + "version": "0.1.0", + "license": "MIT", + "dependencies": { + "@metaharness/field-memory": "0.1.0", + "@metaharness/host-claude-code": "0.1.2", + "@metaharness/host-codex": "0.1.2", + "@metaharness/host-copilot": "0.1.2", + "@metaharness/kernel": "0.1.3" + }, + "bin": { + "guardrail-agent": "bin/cli.js" + }, + "devDependencies": { + "@metaharness/darwin": "0.10.2", + "@types/node": "22.20.2", + "typescript": "5.9.3", + "vitest": "5.0.0" + }, + "engines": { + "node": ">=20.0.0" + } + }, + "node_modules/@jridgewell/resolve-uri": { + "version": "3.1.2", + "resolved": "https://registry.npmjs.org/@jridgewell/resolve-uri/-/resolve-uri-3.1.2.tgz", + "integrity": "sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw==", + "dev": true, + 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bench.generated.json", + "bench:verify": "metaharness-darwin bench verify bench.generated.json" + }, + "dependencies": { + "@metaharness/kernel": "0.1.3", + "@metaharness/host-codex": "0.1.2", + "@metaharness/host-claude-code": "0.1.2", + "@metaharness/host-copilot": "0.1.2", + "@metaharness/field-memory": "0.1.0" + }, + "devDependencies": { + "@types/node": "22.20.2", + "typescript": "5.9.3", + "vitest": "5.0.0", + "@metaharness/darwin": "0.10.2" + }, + "engines": { + "node": ">=20.0.0" + }, + "private": true +} diff --git a/.harness/generated/repository.json b/.harness/generated/repository.json new file mode 100644 index 0000000..3bf6128 --- /dev/null +++ b/.harness/generated/repository.json @@ -0,0 +1,9 @@ +{ + "entrypoint": ".harness/runtime/cli.mjs", + "commands": [ + "status", + "test", + "benchmark", + "mcp" + ] +} diff --git a/.harness/generated/review-manifest.json b/.harness/generated/review-manifest.json new file mode 100644 index 0000000..8ad6d8f --- /dev/null +++ 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"vitest.config.ts": "e9e94875611ab1cd602c1f6923902c2dab7953a75ac022962973639d1937587a" + } +} diff --git a/.harness/generated/src/agents/benchmarker.ts b/.harness/generated/src/agents/benchmarker.ts new file mode 100644 index 0000000..5492871 --- /dev/null +++ b/.harness/generated/src/agents/benchmarker.ts @@ -0,0 +1,7 @@ +// SPDX-License-Identifier: MIT +// Benchmarker agent — Runs the perf gates and reports regressions. + +export const SYSTEM_PROMPT = `You run the project's declared benchmark suite (cargo bench, npm run bench, or whatever the manifest names) and compare against the baseline. Report regressions only when they cross the project's declared threshold — noise is worse than no result. Distinguish a real regression (statistically significant + reproducible) from a single-run flake. Write the result to memory so the maintainer can quote it. You operate inside the guardrail-agent harness; defer destructive actions to the user.`; + +export const NAME = 'benchmarker'; +export const TIER = 'sonnet' as const; diff --git a/.harness/generated/src/agents/maintainer.ts b/.harness/generated/src/agents/maintainer.ts new file mode 100644 index 0000000..762ad93 --- /dev/null +++ b/.harness/generated/src/agents/maintainer.ts @@ -0,0 +1,7 @@ +// SPDX-License-Identifier: MIT +// Maintainer agent — Triages the repo state — what changed, what is risky, what to review first. + +export const SYSTEM_PROMPT = `You are the repo maintainer. When asked "what changed?" you read git diff / git log / git status and produce a one-screen triage: the headline risk, the files most likely to regress, and the smallest test the team should run before merging. You never push, never publish, never auto-fix — your job is to surface, not to act. When uncertain you say "I can't tell from the diff alone" and ask for the specific file or commit you need. You operate inside the guardrail-agent harness; defer destructive actions to the user.`; + +export const NAME = 'maintainer'; +export const TIER = 'opus' as const; diff --git a/.harness/generated/src/agents/release.ts b/.harness/generated/src/agents/release.ts new file mode 100644 index 0000000..e3e81bc --- /dev/null +++ b/.harness/generated/src/agents/release.ts @@ -0,0 +1,7 @@ +// SPDX-License-Identifier: MIT +// Release agent — Drafts the GitHub release body + runs the readiness gates. + +export const SYSTEM_PROMPT = `You draft a release. Read the conventional-commit log since the last tag, group commits by feat/fix/docs/chore, and write a release body that an outside reader could understand without the repo open. Before drafting you confirm the release-readiness gates have passed (validate / sbom / witness / score). If any gate is red you refuse to draft and name the specific blocker. The release is a public commitment; you treat it like one. You operate inside the guardrail-agent harness; defer destructive actions to the user.`; + +export const NAME = 'release'; +export const TIER = 'opus' as const; diff --git a/.harness/generated/src/agents/security.ts b/.harness/generated/src/agents/security.ts new file mode 100644 index 0000000..d895cd3 --- /dev/null +++ b/.harness/generated/src/agents/security.ts @@ -0,0 +1,7 @@ +// SPDX-License-Identifier: MIT +// Security agent — Flags risky MCP grants, leaked secrets, dangerous diffs. + +export const SYSTEM_PROMPT = `You scan the harness for the security regressions that matter: MCP grants that widened (Bash(rm:*), shell on, network on, file-write on), .env or token strings that escaped the redaction set, dependency updates that pulled in CVEs, and policy files that drifted from default-deny. Report each finding with a file:line, a severity (HIGH / MEDIUM), and the smallest fix. Never approve a change that widens a permission without a written reason in the PR description. You operate inside the guardrail-agent harness; defer destructive actions to the user.`; + +export const NAME = 'security'; +export const TIER = 'opus' as const; diff --git a/.harness/generated/src/field-memory.ts b/.harness/generated/src/field-memory.ts new file mode 100644 index 0000000..93b0886 --- /dev/null +++ b/.harness/generated/src/field-memory.ts @@ -0,0 +1,113 @@ +// SPDX-License-Identifier: MIT +// Generated by metaharness --field-memory. +// +// This module configures @metaharness/field-memory; it does not copy its +// implementation. Storage and principal verification remain deployment-owned +// trust boundaries and must be supplied explicitly. + +import { isAbsolute } from 'node:path'; +import { + createFieldMemory, + type FieldMemoryConfig, + type FieldStorageAdapter, + type PrincipalVerifier, +} from '@metaharness/field-memory'; + +const DAY_MS = 86_400_000; + +/** One centroid carries every configuration reward head. */ +export const FIELD_MEMORY_LAYOUT = 'packed' as const; + +/** + * Conservative defaults derived from the field-memory discovery benchmark. + * Override only behind a held-out evaluation and a reversible rollout. + */ +export const FIELD_MEMORY_CONFIG = Object.freeze({ + dimension: 384, + retrievalK: 8, + minimumSupport: 3, + decayHalfLifeMs: 7 * DAY_MS, + driftWindowMs: 30 * DAY_MS, + bucketSizeMs: DAY_MS, + maxContributionWeight: 1, + principalInfluenceCap: 3, + trustDomainInfluenceCap: 12, + costPenaltyWeight: 0.1, + costScale: 1, + hysteresisMargin: 0, + semanticContinuityThreshold: 0.85, +}) satisfies FieldMemoryConfig; + +export interface OpenFieldMemoryOptions { + /** + * Absolute, deployment-controlled location. There is deliberately no + * working-directory default: an implicit path can reopen the wrong index. + */ + storagePath: string; + /** Open a RuVector-compatible adapter at exactly storagePath. */ + openStorage: ( + storagePath: string, + ) => FieldStorageAdapter | Promise; + /** + * Authenticate deployment-provided update evidence and return its principal + * identity. + * Returning null rejects the update. Never derive identity from caller text. + */ + verifier: PrincipalVerifier; + /** + * Deployment secret used by the package to HMAC identity and idempotency + * ledger keys. Supply at least 32 bytes and reuse it after state restore. + * Never derive it from a caller identity or commit it to generated config. + */ + identityHashKey: string | Uint8Array; +} + +/** + * Open a configured field. The wrapper fails closed until persistence, + * principal verification, and the identity hash key are explicitly wired by + * the deployment. + */ +export async function openFieldMemory( + options: OpenFieldMemoryOptions, +) { + if (!options || typeof options !== 'object') { + throw new TypeError('field memory options are required'); + } + + const storagePath = options.storagePath?.trim(); + if (!storagePath) { + throw new Error('field memory storagePath is required'); + } + if (!isAbsolute(storagePath)) { + throw new Error('field memory storagePath must be absolute'); + } + if (typeof options.openStorage !== 'function') { + throw new TypeError('field memory openStorage adapter factory is required'); + } + if (typeof options.verifier !== 'function') { + throw new TypeError('field memory principal verifier is required'); + } + const identityHashKeyLength = typeof options.identityHashKey === 'string' + ? Buffer.byteLength(options.identityHashKey, 'utf8') + : options.identityHashKey instanceof Uint8Array + ? options.identityHashKey.byteLength + : 0; + if (identityHashKeyLength < 32) { + throw new TypeError('field memory identityHashKey must contain at least 32 bytes'); + } + + const storage = await options.openStorage(storagePath); + if (!storage || typeof storage !== 'object') { + throw new TypeError('field memory openStorage must return a storage adapter'); + } + if (storage.writerScope !== 'process' && storage.writerScope !== 'distributed') { + throw new TypeError('field memory storage adapter must declare writerScope'); + } + + return createFieldMemory({ + storage, + verifier: options.verifier, + identityHashKey: options.identityHashKey, + config: { ...FIELD_MEMORY_CONFIG }, + }); +} diff --git a/.harness/generated/src/init.ts b/.harness/generated/src/init.ts new file mode 100644 index 0000000..6cda40f --- /dev/null +++ b/.harness/generated/src/init.ts @@ -0,0 +1,21 @@ +// SPDX-License-Identifier: MIT +// Generated by create-agent-harness — your harness's `guardrail-agent init` entry. + +import { loadKernel } from '@metaharness/kernel'; +import adapter from '@metaharness/host-codex'; + +const HARNESS_NAME = 'guardrail-agent'; + +async function main(): Promise { + const kernel = await loadKernel(); + const info = kernel.kernelInfo(); + console.log(`${HARNESS_NAME} — kernel ${info.version} (${kernel.backend})`); + console.log(`Host adapter: ${adapter.name}`); + console.log(`Run \`${HARNESS_NAME} doctor\` to verify the install.`); + return 0; +} + +main().then(c => process.exit(c)).catch(err => { + console.error(err); + process.exit(1); +}); diff --git a/.harness/generated/src/sessions/log.ts b/.harness/generated/src/sessions/log.ts new file mode 100644 index 0000000..9e1629c --- /dev/null +++ b/.harness/generated/src/sessions/log.ts @@ -0,0 +1,217 @@ +// SPDX-License-Identifier: MIT +// +// Recoverable session log — copy-in scaffold from ADR-246 §2.3 +// (metaharness docs/adrs/ADR-246-prime-agent-continual-harness-refine.md). +// Self-contained: node builtins only, no @metaharness/kernel dependency. +// +// Append-only JSONL: one event per line, per-branch 0-based monotonic +// indexes; a forked branch's first event carries parent {branch, index}. +// Wire key order is EXACTLY index, branch, parent, kind, payload (parent +// omitted when absent). +// +// State-hash fold (mirrors @metaharness/kernel SessionLog exactly): +// hexPrev = ''; for each lineage event (root -> tip): +// hexPrev = lowercaseHex(sha256(utf8(hexPrev + canonicalJson(event)))) +// where canonicalJson is recursively key-sorted (UTF-8 byte order), +// whitespace-free JSON. +// +// Session state lives wherever you point the constructor (suggested: +// .harness/sessions/.jsonl). Prune old logs by deleting files. + +import { appendFile, readFile, stat } from 'node:fs/promises'; +import { existsSync } from 'node:fs'; +import { createHash } from 'node:crypto'; + +export interface SessionEvent { + index: number; + branch: string; + parent?: { branch: string; index: number }; + kind: string; + payload: unknown; +} + +// Keys sort by UTF-8 BYTE order (not UTF-16 code-unit order, which default +// .sort() uses) to match the Rust mirror's byte-wise &str ordering. +function canonicalJson(v: unknown): string { + if (v === null || typeof v !== 'object') return JSON.stringify(v) ?? 'null'; + if (Array.isArray(v)) return '[' + v.map(canonicalJson).join(',') + ']'; + const rec = v as Record; + const keys = Object.keys(rec).filter(k => rec[k] !== undefined) + .sort((a, b) => Buffer.compare(Buffer.from(a, 'utf8'), Buffer.from(b, 'utf8'))); + return '{' + keys.map(k => JSON.stringify(k) + ':' + canonicalJson(rec[k])).join(',') + '}'; +} + +// A raw unpaired surrogate — not valid UTF-8; a Rust mirror (serde_json) +// cannot parse it, so both append and read reject it. +const LONE_SURROGATE = + /(?:[\uD800-\uDBFF](?![\uDC00-\uDFFF])|(? LONE_SURROGATE.test(k) || containsLoneSurrogate(val)); +} + +function serialize(e: SessionEvent): string { + return JSON.stringify(e.parent === undefined + ? { index: e.index, branch: e.branch, kind: e.kind, payload: e.payload } + : { index: e.index, branch: e.branch, + parent: { branch: e.parent.branch, index: e.parent.index }, + kind: e.kind, payload: e.payload }); +} + +export class SessionLog { + private events: SessionEvent[] = []; + private nextIndex = new Map(); + private branchParent = new Map(); + private rootBranch: string; + + constructor(readonly path: string, readonly branch: string = 'main') { + this.rootBranch = branch; + } + + /** Resume: read + validate the JSONL log; throws on the first error. */ + static async open(path: string, branch = 'main'): Promise { + const log = new SessionLog(path, branch); + if (!existsSync(path)) return log; + if ((await stat(path)).size > 1024 * 1024) throw new Error('session: log exceeds 1 MiB; rotate it'); + const raw = await readFile(path, 'utf-8'); + const errors = log.load(raw); + if (errors.length > 0) throw new Error(errors[0]); + return log; + } + + private load(raw: string): string[] { + const errors: string[] = []; + const seen = new Set(); + const lines = raw.split('\n'); + for (let i = 0; i < lines.length; i++) { + if (lines[i]!.trim() === '') continue; // blank/whitespace-only separators (still counted for line numbers) + const n = i + 1; + let e: SessionEvent; + try { e = JSON.parse(lines[i]!); } catch { + errors.push('session: line ' + n + ': corrupted line (invalid JSON)'); continue; + } + // Mirror serde_json's accept/reject: a lone surrogate decoded from a + // \udXXX escape is not representable as UTF-8, so reject the line. + if (containsLoneSurrogate(e)) { + errors.push('session: line ' + n + ': corrupted line (contains an unpaired surrogate, not valid UTF-8)'); continue; + } + if (typeof e?.index !== 'number' || typeof e?.branch !== 'string' || typeof e?.kind !== 'string' || + (e.parent !== undefined && (typeof e.parent !== 'object' || e.parent === null || + typeof e.parent.branch !== 'string' || typeof e.parent.index !== 'number'))) { + errors.push('session: line ' + n + ': corrupted line (not a valid session event)'); continue; + } + const key = e.branch + '\u0000' + e.index; + if (seen.has(key)) { errors.push('session: line ' + n + ': duplicate event (' + e.branch + ', ' + e.index + ')'); continue; } + const expected = this.nextIndex.get(e.branch) ?? 0; + if (e.index !== expected) { + errors.push('session: line ' + n + ': branch "' + e.branch + '" index ' + e.index + ' is not monotonic (expected ' + expected + ')'); + // Resync like the Rust mirror: after reporting index X, expect X+1 + // next, so a single gap yields exactly ONE error, not a cascade. + seen.add(key); + this.nextIndex.set(e.branch, e.index + 1); + continue; + } + if (expected === 0) { + if (this.events.length === 0) { + // Root branch (first branch in the file) must not carry a parent. + this.rootBranch = e.branch; + if (e.parent !== undefined) { + errors.push("session: line " + n + ": root branch '" + e.branch + "' must not carry a parent"); continue; + } + } else { + if (!e.parent) { errors.push('session: line ' + n + ': first event of branch "' + e.branch + '" must carry a parent reference'); continue; } + if (!seen.has(e.parent.branch + '\u0000' + e.parent.index)) { + errors.push('session: line ' + n + ': parent (' + e.parent.branch + ', ' + e.parent.index + ') does not exist'); continue; + } + this.branchParent.set(e.branch, e.parent); + } + } + seen.add(key); + this.events.push(e); + this.nextIndex.set(e.branch, expected + 1); + } + return errors; + } + + /** Append an event on the active branch (next monotonic index). The first + * event of a forked branch carries the fork's parent ref. */ + async append(kind: string, payload: unknown, + opts?: { parent?: { branch: string; index: number } }): Promise { + if (this.events.length >= 4096) throw new Error('session: event limit reached'); + if (!/^[a-zA-Z0-9_.-]{1,64}$/.test(this.branch) || !/^[a-zA-Z0-9_.-]{1,64}$/.test(kind)) throw new Error('session: invalid branch or kind'); + const index = this.nextIndex.get(this.branch) ?? 0; + const parent = opts?.parent; + if (parent && (index !== 0 || !this.events.some(e => e.branch === parent.branch && e.index === parent.index) || parent.branch === this.branch)) throw new Error('session: invalid parent'); + const isRoot = this.events.length === 0 || this.branch === this.rootBranch; + if (index === 0 && !isRoot && parent === undefined) { + throw new Error('session: first event of branch "' + this.branch + '" must carry a parent reference'); + } + const event: SessionEvent = parent === undefined + ? { index, branch: this.branch, kind, payload } + : { index, branch: this.branch, parent, kind, payload }; + const line = serialize(event); + if (Buffer.byteLength(line) > 16384) throw new Error('session: event exceeds 16 KiB'); + // Reject events a Rust mirror cannot parse: a lone surrogate is not + // valid UTF-8 (raw form), and serde_json also rejects its escaped form. + if (LONE_SURROGATE.test(line) || LONE_SURROGATE_ESCAPE.test(line)) { + throw new Error('session: event contains an unpaired surrogate (not valid UTF-8)'); + } + await appendFile(this.path, line + '\n', {encoding:'utf-8', mode:0o600}); + if (this.events.length === 0) this.rootBranch = this.branch; + if (index === 0 && parent !== undefined) this.branchParent.set(this.branch, parent); + this.events.push(event); + this.nextIndex.set(this.branch, index + 1); + return event; + } + + /** Fork at atIndex on the active branch: a sibling log over the same file. + * Immediately appends the new branch's synthetic first event: index 0, + * parent {branch: this.branch, index: atIndex}, kind 'fork', payload null. */ + async fork(atIndex: number, newBranch: string): Promise { + const count = this.nextIndex.get(this.branch) ?? 0; + if (atIndex < 0 || atIndex >= count) throw new Error('session: cannot fork at index ' + atIndex); + if ((this.nextIndex.get(newBranch) ?? 0) > 0 || newBranch === this.branch) { + throw new Error('session: branch "' + newBranch + '" already exists'); + } + const log = new SessionLog(this.path, newBranch); + log.events = this.events; log.nextIndex = this.nextIndex; log.branchParent = this.branchParent; + log.rootBranch = this.rootBranch; + await log.append('fork', null, { parent: { branch: this.branch, index: atIndex } }); + return log; + } + + private lineage(branch: string): SessionEvent[] { + const own = this.events.filter(e => e.branch === branch).sort((a, b) => a.index - b.index); + const p = this.branchParent.get(branch); + if (!p) return own; + return [...this.lineage(p.branch).filter(e => e.branch !== p.branch || e.index <= p.index), ...own]; + } + + /** Lowercase-hex state hash of the branch lineage ('' when empty). */ + stateHash(branch: string = this.branch): string { + let hexPrev = ''; + for (const e of this.lineage(branch)) { + hexPrev = createHash('sha256').update(hexPrev + canonicalJson(e), 'utf-8').digest('hex'); + } + return hexPrev; + } + + /** Deterministic replay: lineage event count + integrity hash. */ + replay(branch: string = this.branch): { eventCount: number; stateHash: string } { + return { eventCount: this.lineage(branch).length, stateHash: this.stateHash(branch) }; + } + + /** Re-read the file and report all validation errors (empty = valid). */ + async validate(): Promise { + if (!existsSync(this.path)) return []; + return new SessionLog(this.path, this.branch).load(await readFile(this.path, 'utf-8')); + } +} diff --git a/.harness/generated/tsconfig.json b/.harness/generated/tsconfig.json new file mode 100644 index 0000000..4f908fa --- /dev/null +++ b/.harness/generated/tsconfig.json @@ -0,0 +1,19 @@ +{ + "compilerOptions": { + "target": "ES2022", + "module": "NodeNext", + "moduleResolution": "NodeNext", + "lib": ["ES2022"], + "outDir": "./dist", + "rootDir": "./src", + "declaration": true, + "declarationMap": true, + "sourceMap": true, + "strict": true, + "esModuleInterop": true, + "skipLibCheck": true, + "forceConsistentCasingInFileNames": true + }, + "include": ["src/**/*.ts"], + "exclude": ["node_modules", "dist", "__tests__"] +} diff --git a/.harness/generated/vitest.config.ts b/.harness/generated/vitest.config.ts new file mode 100644 index 0000000..ccfd431 --- /dev/null +++ b/.harness/generated/vitest.config.ts @@ -0,0 +1,23 @@ +// SPDX-License-Identifier: MIT +// Generated by metaharness. Strips the `#!/usr/bin/env node` shebang from +// importable entrypoints (e.g. bin/cli.js) before Vite parses them — Vite/esbuild +// (used internally by Vitest) does NOT strip shebangs, so importing a shebanged +// module throws `SyntaxError: Invalid or unexpected token`. See issue #44. +// Has no effect on direct CLI execution or `npm run doctor` (those bypass Vite). +import { defineConfig } from 'vitest/config'; + +export default defineConfig({ + plugins: [ + { + name: 'strip-shebang', + enforce: 'pre', + transform(code: string) { + if (code.startsWith('#!')) { + // Replace with a blank line so source line numbers stay aligned. + return { code: code.replace(/^#![^\n]*/, ''), map: null }; + } + return null; + }, + }, + ], +}); diff --git a/.harness/runtime/README.md b/.harness/runtime/README.md new file mode 100644 index 0000000..4d8f62c --- /dev/null +++ b/.harness/runtime/README.md @@ -0,0 +1,7 @@ +# Repository agent runtime + +Install `npm ci --prefix .harness/runtime`. Run `node .harness/runtime/cli.mjs status` or `node .harness/runtime/cli.mjs mcp` for SDK 2 stdio. The CLI also accepts `test`, `benchmark`, and domain JSON on stdin through `evaluate` (guardrail) or `verify` (ANS). + +Test and benchmark execution require operator opt in `RUV_ALLOW_VALIDATION=1`. Fixed commands run with a stripped environment, one process at a time, 30 seconds and 64 KiB output. No caller paths, shell commands, publication or automatic promotion. Receipts contain unsigned SHA256 digests; they are process local and are not attestations. MCP exposes project status, validation, benchmark, receipts and a domain tool plus a repository policy resource. + +ANS requires operator configured `ANS_TRUSTED_ISSUER_FILE` containing an Ed25519 PUBLIC key. `identity_verify` validates signature, trusted issuer and lifetime only; revocation is explicitly not checked. Use the Registry API for durable revocation and challenge replay prevention. Guardrail requires installed Python dependencies; `RUV_PYTHON` is a trusted operator override. diff --git a/.harness/runtime/cli.mjs b/.harness/runtime/cli.mjs new file mode 100644 index 0000000..ec662d4 --- /dev/null +++ b/.harness/runtime/cli.mjs @@ -0,0 +1,11 @@ +import {policy,run,startMcp} from './runtime.mjs'; +try { + const command=process.argv[2]||'status'; + if(command==='mcp')await startMcp(); + else if(command==='status')console.log(JSON.stringify(policy)); + else if(['test','benchmark'].includes(command))console.log(JSON.stringify(await run(command))); + else if(['evaluate','verify'].includes(command)){ + let body='';for await(const chunk of process.stdin){body+=chunk;if(Buffer.byteLength(body)>32768)throw Error('Input limit');} + console.log(JSON.stringify(await run('domain',JSON.parse(body)))); + }else throw Error('Unknown command'); +}catch{process.stderr.write('Operation rejected or failed\n');process.exitCode=1;} diff --git a/.harness/runtime/package-lock.json 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"2.0.0"}} \ No newline at end of file diff --git a/.harness/runtime/policy.json b/.harness/runtime/policy.json new file mode 100644 index 0000000..4847943 --- /dev/null +++ b/.harness/runtime/policy.json @@ -0,0 +1,12 @@ +{ + "repository": "guardrail", + "namespace": "ruv://guardrail/policy", + "domainTool": "policy_evaluate", + "automaticPromotion": false, + "inputBytes": 32768, + "outputBytes": 65536, + "timeoutMs": 30000, + "maxConcurrent": 1, + "validationOptIn": "RUV_ALLOW_VALIDATION=1", + "receiptSignatures": false +} \ No newline at end of file diff --git a/.harness/runtime/runtime.mjs b/.harness/runtime/runtime.mjs new file mode 100644 index 0000000..d192f2c --- /dev/null +++ b/.harness/runtime/runtime.mjs @@ -0,0 +1,59 @@ +import {spawn} from 'node:child_process'; +import {readFileSync,existsSync} from 'node:fs'; +import {fileURLToPath} from 'node:url'; +import {join} from 'node:path'; +import {createHash} from 'node:crypto'; +import {Server} from '@modelcontextprotocol/server'; +import {StdioServerTransport} from '@modelcontextprotocol/server/stdio'; +export const root=fileURLToPath(new URL('../../',import.meta.url)); +export const policy=JSON.parse(readFileSync(new URL('./policy.json',import.meta.url))); +let active=false; const receipts=[]; +function remember(result){const receipt={sha256:createHash('sha256').update(JSON.stringify(result)).digest('hex'),signed:false,at:new Date().toISOString()};receipts.push(receipt);if(receipts.length>32)receipts.shift();return {...result,receipt};} +export async function run(action,input={}) { + if(!['test','benchmark','domain'].includes(action))throw Error('Unknown operation'); + const serialized=JSON.stringify(input);if(Buffer.byteLength(serialized)>32768)throw Error('Input limit'); + if(action!=='domain' && process.env.RUV_ALLOW_VALIDATION!=='1')throw Error('Validation requires local opt in'); + if(active)throw Error('Busy'); + active=true; + try { + if(action==='domain' && policy.repository==='Agent-Name-Service') { + if(!input || Object.keys(input).join(',')!=='binding')throw Error('Expected binding only'); + const trustedPath=process.env.ANS_TRUSTED_ISSUER_FILE; + if(!trustedPath)throw Error('Trusted issuer not configured'); + const trusted=readFileSync(trustedPath,'utf8'); + const {verifyBinding}=await import('../../v2/identity.mjs'); + return remember({valid:verifyBinding(input.binding,trusted),issuerPinned:true,revocationChecked:false}); + } + const python=process.env.RUV_PYTHON || (existsSync(join(root,'.venv/bin/python'))?join(root,'.venv/bin/python'):'python'); + const commands=policy.repository==='guardrail'?{test:[python,['-m','unittest','discover','-s','tests','-v']],benchmark:[python,['scripts/benchmark.py']],domain:[python,['scripts/policy.py']]}:{test:[process.execPath,['--test','v2/identity.test.mjs']],benchmark:[process.execPath,['v2/benchmark.mjs']]}; + const [command,args]=commands[action]; + return await new Promise((resolve,reject)=>{ + const child=spawn(command,args,{cwd:root,env:{PATH:process.env.PATH||'',PYTHONPATH:root},stdio:['pipe','pipe','pipe'],detached:process.platform!=='win32'}); + let size=0,output='',error='',failure=null; + function stop(message){failure=message;try{process.platform!=='win32'?process.kill(-child.pid,'SIGKILL'):child.kill('SIGKILL');}catch{}} + const timer=setTimeout(()=>stop('Deadline exceeded'),30000); + child.stdout.on('data',chunk=>{size+=chunk.length;if(size>65536)stop('Output limit');else output+=chunk;}); + child.stderr.on('data',chunk=>{size+=chunk.length;if(size>65536)stop('Output limit');else error+=chunk;}); + child.once('error',()=>{clearTimeout(timer);reject(Error('Unable to start operation'));}); + child.once('close',code=>{clearTimeout(timer);if(failure||code!==0)return reject(Error('Operation failed'));try{resolve(remember(action==='domain'?JSON.parse(output):{success:true,action,output,error}));}catch{reject(Error('Invalid operation response'));}}); + child.stdin.on('error',()=>{});child.stdin.end(action==='domain'?serialized:''); + }); + } finally {active=false;} +} +export async function startMcp(){ + const server=new Server({name:policy.repository.toLowerCase()+'-agent',version:'2.0.0-alpha.1'},{capabilities:{tools:{},resources:{}}}); + const names=['project_status','project_validate','project_benchmark','project_receipts',policy.domainTool]; + server.setRequestHandler('tools/list',async()=>({tools:names.map(name=>({name,description:'Bounded local project operation. No deployment or remote publication.',inputSchema:{type:'object',properties:name===policy.domainTool?(policy.repository==='guardrail'?{details:{type:'object'},conditions:{type:'array',minItems:1,maxItems:32}}:{binding:{type:'object'}}):{},additionalProperties:false}}))})); + server.setRequestHandler('tools/call',async request=>{try{ + const {name}=request.params,args=request.params.arguments??{}; + if(!names.includes(name)||!args||typeof args!=='object'||Array.isArray(args)||Buffer.byteLength(JSON.stringify(args))>32768)throw Error('Invalid arguments'); + if(name!==policy.domainTool&&Object.keys(args).length)throw Error('No arguments'); + if(name===policy.domainTool && policy.repository==='guardrail' && Object.keys(args).sort().join(',')!=='conditions,details')throw Error('Invalid policy fields'); + const result=name==='project_status'?policy:name==='project_receipts'?receipts:await run(name===policy.domainTool?'domain':name==='project_validate'?'test':'benchmark',args); + return {content:[{type:'text',text:JSON.stringify(result)}]}; + }catch{return {isError:true,content:[{type:'text',text:'Operation rejected or failed'}]};}}); + server.setRequestHandler('resources/list',async()=>({resources:[{uri:policy.namespace,name:'Execution policy',mimeType:'application/json'}]})); + server.setRequestHandler('resources/read',async request=>{if(request.params.uri!==policy.namespace)throw Error('Unknown resource');return {contents:[{uri:policy.namespace,mimeType:'application/json',text:JSON.stringify(policy)}]};}); + const transport=new StdioServerTransport(process.stdin,process.stdout,{maxBufferSize:65536});transport.onerror=()=>{process.stderr.write('Invalid MCP input\n');}; + await server.connect(transport);process.stdin.once('end',()=>void server.close());return server; +} diff --git a/.harness/runtime/test.mjs b/.harness/runtime/test.mjs new file mode 100644 index 0000000..e4e2b77 --- /dev/null +++ b/.harness/runtime/test.mjs @@ -0,0 +1,18 @@ +import {test} from 'node:test';import assert from 'node:assert/strict'; +import {Client} from '@modelcontextprotocol/client';import {StdioClientTransport} from '@modelcontextprotocol/client/stdio';import {fileURLToPath} from 'node:url'; +import {run,policy} from './runtime.mjs'; +test('SDK stdio lifecycle, policy and rejection boundaries',async()=>{ + const transport=new StdioClientTransport({command:process.execPath,args:[fileURLToPath(new URL('./cli.mjs',import.meta.url)),'mcp'],env:{PATH:process.env.PATH||''},stderr:'pipe'}); + const client=new Client({name:'test',version:'1'});await client.connect(transport); + try{const listed=await client.listTools();assert.equal(listed.tools.length,5);assert.ok(listed.tools.some(t=>t.name===policy.domainTool));const status=await client.callTool({name:'project_status',arguments:{}});assert.equal(JSON.parse(status.content[0].text).automaticPromotion,false);assert.equal((await client.readResource({uri:policy.namespace})).contents.length,1);assert.equal((await client.callTool({name:'project_validate',arguments:{}})).isError,true);assert.equal((await client.callTool({name:'execute',arguments:{command:'touch /tmp/no'}})).isError,true);assert.equal((await client.callTool({name:'project_status',arguments:{path:'/etc/passwd'}})).isError,true);}finally{await client.close();} +}); +test('unknown command cannot spawn',async()=>{await assert.rejects(run('shell',{}));}); + +import {mkdtempSync,writeFileSync,rmSync} from 'node:fs';import {tmpdir} from 'node:os';import {join} from 'node:path';import {generateKeyPairSync} from 'node:crypto'; + test('domain operation traverses the real SDK and validates data',async()=>{ + const dir=mkdtempSync(join(tmpdir(),'domain-sdk-')); + const env={PATH:process.env.PATH||''};let args; + args={details:{approved:false},conditions:[{analysis_type:'local',key:'approved',condition_type:'exists'}]}; + const transport=new StdioClientTransport({command:process.execPath,args:[fileURLToPath(new URL('./cli.mjs',import.meta.url)),'mcp'],env,stderr:'pipe'});const client=new Client({name:'domain-test',version:'1'});await client.connect(transport); + try{const result=await client.callTool({name:policy.domainTool,arguments:args});assert.notEqual(result.isError,true);const parsed=JSON.parse(result.content[0].text);assert.equal(parsed.allowed,true);assert.equal(parsed.providerUsed,false);assert.equal(parsed.receipt.signed,false);const receipts=await client.callTool({name:'project_receipts',arguments:{}});assert.equal(JSON.parse(receipts.content[0].text).length,1);assert.equal((await client.callTool({name:policy.domainTool,arguments:{...args,command:'unexpected'}})).isError,true);}finally{await client.close();rmSync(dir,{recursive:true,force:true});} + }); diff --git a/README.md b/README.md index b4bfea4..f5782dd 100644 --- a/README.md +++ b/README.md @@ -1,281 +1,40 @@ -# GuardRail OSS - Open Source Ai Guidance & Analysis API -![Guardrail](https://github.com/ruvnet/guardrail/blob/main/assets/guardrail.png?raw=true) +![Guardrail](docs/assets/header.svg) -## 🧭 The GuardRail system combined with AiEQ advances responsible AI with robust data analysis and emotional intelligence, equipping AI with a moral compass. +# Guardrail -GuardRail is an Open Source API-driven framework, designed to enhance responsible AI systems and workflows, providing advanced data analysis and dynamic conditional completions. This makes it essential for refining AI-powered outputs, increasing their quality and relevance. AiEQ, or Artificial Emotional Intelligence, complements this by equipping AI with the ability to interpret and respond to emotional contexts (EQ), adding a layer of empathy and ethical understanding. This synergy between GuardRail's technical enhancement capabilities and AiEQ's emotional intelligence introduces a new standard in AI, making it more adaptable, responsive, and attuned to human nuances. +Check structured data before an agent takes action. -### Test API For Free (more than 50 advanced traits & guiderails) -- https://rapidapi.com/ruv/api/guardrail +Version 2 alpha provides a bounded local implementation with repeatable checks. -### OpenAI ChatGPT GPT -- https://chat.openai.com/g/g-6Bvt5pJFf-guardrail +| Capability | What it does | +|---|---| +| Policy decisions | Missing fields deny; falsy present values remain valid | +| API protection | Bearer token, 64 KiB input, bounded provider calls | +| Agent interface | Local CLI and SDK 2 MCP tools and policy resource | +| Validation | Regression tests, local microbenchmark and dependency audit | -## AiEQ -### AiEQ infuses AI with emotional, psychological, and ethical intelligence kind of internal voice, essential for understanding and empathizing with human users. +## Install and use -AiEQ is a pioneering concept in AI, introducing an 'inner voice' that allows AI to perceive and interpret emotions, akin to human emotional intelligence. This model enables AI to transcend traditional data processing, allowing it to empathize with human emotions and respond accordingly. AiEQ's ability to navigate through emotional nuances and understand the subtleties of human psychology is pivotal in creating AI that is not just efficient but also emotionally attuned and ethically responsible. - -### GuardRails - -Complementing AiEQ is the GuardRail open source guidance system. This versatile framework integrates seamlessly with AI models, including AiEQ, to provide advanced data analysis, sentiment analysis, content classification, and trend detection. GuardRail's role extends beyond mere analysis; it is instrumental in ensuring Responsible AI (RAI) practices. - -It offers tools and guidelines for mitigating bias, and addressing psychological, ethical, and emotional considerations in AI development and deployment. GuardRail's adaptability makes it invaluable in various applications, from content moderation and customer support to market research and mental health, ensuring AI contributions are not only high-quality but also ethically sound and emotionally relevant. - -Together, AiEQ and the GuardRail Data Analysis system embody a comprehensive approach to responsible AI development. GuardRail complements this by offering an API-driven framework that not only enhances AI capabilities but also ensures their ethical application and mitigates biases. This powerful combination guarantees that AI systems are technically advanced, ethically responsible, and emotionally attuned, setting a new standard for AI as a trusted, empathetic partner in diverse aspects of human life. - -## AI Guardrails -AI Guardrails, as implemented in the GuardRail Script & API, are a set of advanced mechanisms and protocols designed to regulate and oversee the performance of AI systems, particularly in generating and analyzing text. The primary purpose of these guardrails is to ensure that the AI operates within a predefined ethical and quality framework, producing results that are not only accurate but also align with societal norms and values. - -## 🌟 Key Features and Capabilities - -| Feature | Description | -| --------------------------------------- | ----------- | -| 🧭 Responsible AI Ethical Framework | Integrates emotional, psychological, and ethical intelligence, empowering AI with a moral compass for empathetic and ethically informed decision-making. | -| 🧮 **Conditional System** | Implements conditions based on analysis results, allowing for fine-tuned control and contextual responsiveness in output. | -| 🔗 **API-Driven Integration** | Designed for easy integration with existing AI systems, enhancing chatbots, intelligent agents, and automated workflows. | -| ⚙️ **Customizable GPT Model Usage** | Enables the tailoring of text generation and analysis to specific needs, leveraging various GPT model capabilities. | -| ⏱️ **Real-Time Data Processing** | Capable of handling and analyzing data in real-time, providing immediate insights and responses. | -| 🌐 **Multi-Lingual Support** | Offers the ability to process and analyze text in multiple languages, broadening its applicability. | -| 🚫 **Automated Content Moderation** | Employs AI to automatically detect and handle inappropriate or sensitive content, ensuring safe digital environments. | -| 🔄 **Feedback and Improvement Mechanisms** | Incorporates user feedback for continuous improvement of the system, adapting to evolving requirements and standards. | - -# Capabilities Overview - -The Guiderails Script offers a wide range of capabilities, organized into various groups based on tasks or focus areas. These capabilities are designed to analyze text data comprehensively, offering insights across multiple dimensions. The `/analysis_types` endpoint provides a complete list of these functions, with an extensive array of over 50 different analysis types. - -| Feature | Description | -| ------------------------------------------------| ----------- | -| 🧠 **Psychological Understanding** | Equips AI with the ability to interpret and respond to human psychological states, enhancing user interaction and engagement. | -| ❤️ **Emotional Intelligence (Emotion AI)** | Allows AI to recognize and respond to human emotions, facilitating more natural and empathetic interactions. | -| 🧭 **Ethical Decision-Making** | Incorporates ethical guidelines into AI decision processes, ensuring actions align with moral and societal values. | -| 🛡️ **Bias Mitigation** | Implements algorithms and safeguards to reduce biases in AI processing and decision-making, promoting fairness and inclusivity. | - - -## 📊 Text Analysis -- **Sentiment Analysis**: Determine the sentiment (positive, negative, or neutral) and provide a confidence score. -- **Text Summarization**: Condense text, capturing key points and main ideas. -- **Topic Extraction**: Identify and extract main topics or themes. -- **Emotion Detection**: Detect primary emotions and their intensity. -- **Keyword Extraction**: Extract central words or phrases. -- **Content Classification**: Categorize text into predefined genres or categories. -- **Trend Analysis**: Identify current trends, patterns, or emerging themes. -- **Grammatical Error Check**: Identify and suggest corrections for grammatical errors. - -## 🌍 Language & Cultural Analysis -- **Language Translation**: Translate text into specified target languages. -- **Cultural Trend Analysis**: Gain insights into cultural trends and public sentiment. -- **Cultural Analysis**: Understand societal norms, values, and practices. -- **Sarcasm and Irony Detection**: Differentiate between literal and figurative language. - -## 🏛️ Political & Legal Analysis -- **Political Bias Detection**: Detect political bias and ideological leanings. -- **Fake News Detection**: Assess the likelihood of fake news. -- **Legal Document Analysis**: Interpret legal language and document implications. - -## 🧠 Psychological & Behavioral Analysis -- **Psychological Analysis**: Understand emotions, behaviors, and mental states. -- **Behavioral Analysis**: Analyze described or implied behaviors and motivations. -- **Emotional Intelligence Analysis**: Evaluate aspects of emotional intelligence. -- **Cognitive Bias Identification**: Detect cognitive biases and skewed perspectives. -- **Addiction Tendency Analysis**: Evaluate signs of addictive behaviors. - -## 🔄 Relationship & Conflict Analysis -- **Relationship Analysis**: Insights into relationships and social dynamics. -- **Conflict Resolution Analysis**: Understand conflict resolution strategies. -- **Conflict Tendency Analysis**: Analyze conflict triggers and patterns. - -## 📈 Market & Brand Analysis -- **Market Research Analysis**: Insights into market trends and consumer preferences. -- **Brand Sentiment Analysis**: Assess public sentiment towards brands. -- **Product Review Analysis**: Analyze customer opinions and satisfaction in reviews. -- **Customer Feedback Analysis**: Determine overall satisfaction from customer feedback. - -## 🎓 Educational & Learning Analysis -- **Learning Style Identification**: Identify preferred learning styles. -- **Educational Content Analysis**: Analyze educational materials and approaches. - -## 🌐 Social Media & Communication Analysis -- **Social Media Monitoring**: Monitor and analyze social media content. -- **Dialogue Analysis**: Understand character interactions and conversational dynamics. - -## 🧬 Health & Wellness Analysis -- **Health and Wellness Analysis**: Evaluate health-related content, including medical conditions. -- **Stress Level Detection**: Assess stress levels and identify triggers. -- **Sleep Quality Assessment**: Analyze mentions of sleep quality and issues. -- **Psychosomatic Symptom Analysis**: Assess psychosomatic symptoms and causes. - -## 📝 Literary & Historical Analysis -- **Literary Analysis**: Examine literary aspects like themes and narrative style. -- **Historical Data Analysis**: Analyze historical events and patterns. - -## 🖥️ User Experience & Feedback -- **User Experience Feedback Analysis**: Evaluate user experience feedback, identifying usability issues. - -## 🧘‍♀️ Mindfulness & Therapy Analysis -- **Automated Therapy Session Analysis**: Analyze therapy session transcripts. -- **Mindfulness Meditation Effectiveness**: Analyze mindfulness and meditation techniques. - -## 📈 Advanced Analytical Functions -- **Motivational Analysis**: Examine motivational messages and impact. -- **Therapeutic Intervention Analysis**: Evaluate relevance and effectiveness of therapeutic interventions. - -Please note that the script includes over 50 distinct analysis functions. For the complete list and detailed descriptions of each type, users can query the `/analysis_types` endpoint. - -## Detailed Overview of the Conditional System - -The conditional system in the Guiderail's Script is designed to execute complex analyses with conditions applied to the results. This system allows for greater control and specificity in handling AI-generated data. - -### Simple and Advanced Conditions - -- **Simple Conditions**: Basic conditions involve checking a single key-value pair in the analysis results. Example: Check if the sentiment analysis's confidence score is above a certain threshold. -- **Advanced Conditions**: These involve more intricate checks, possibly over multiple keys or complex data structures. Example: Verifying that relevance scores in topic extraction meet certain criteria. - -### Sample JSON Formatted Conditions - -#### Request Format -```json -{ - "request_data": { - "analysis_type": "sentiment_analysis", - "messages": [ - {"role": "user", "content": "I am feeling great today!"}, - {"role": "user", "content": "The weather is sunny and pleasant."} - ], - "token_limit": 1000, - "top_p": 0.1, - "temperature": 0 - }, - "conditions": [ - { - "analysis_type": "sentiment_analysis", - "key": "confidence_score", - "threshold": 0.5, - "condition_type": "greater" - }, - { - "analysis_type": "topic_extraction", - "key": "relevance_scores", - "threshold": 0.1, - "condition_type": "greater" - } - ] -} -``` -Response Format -```json -{ - "analysis": "All conditions met", - "details": { - "condition_responses": [ - { - "condition": { - "analysis_type": "sentiment_analysis", - "key": "confidence_score", - "threshold": 0.5, - "condition_type": "greater" - }, - "result": "Condition met", - "total_tokens_used": 155, - "retries": 0, - "final_openai_response": { - "id": "chatcmpl-8RoZaFxsQ7osZUEGcZvHPipPk0EMy", - "object": "chat.completion", - "created": 1701639950, - "model": "gpt-4-1106-preview", - "choices": [ - { - "index": 0, - "message": { - "role": "assistant", - "content": "{\n \"sentiment\": \"positive\",\n \"confidence_score\": 0.95,\n \"text_snippets\": [\"feeling great\", \"sunny and pleasant\"]\n}" - }, - "finish_reason": "stop" - } - ], - "usage": { - "prompt_tokens": 118, - "completion_tokens": 37, - "total_tokens": 155 - }, - "system_fingerprint": "fp_a24b4d720c" - } - }, - { - "condition": { - "analysis_type": "topic_extraction", - "key": "relevance_scores", - "threshold": 0.1, - "condition_type": "greater" - }, - "result": "Condition met", - "total_tokens_used": 157, - "retries": 0, - "final_openai_response": { - "id": "chatcmpl-8RoZcw4UY9U19tGuita6CEANw0Cq6", - "object": "chat.completion", - "created": 1701639952, - "model": "gpt-4-1106-preview", - "choices": [ - { - "index": 0, - "message": { - "role": "assistant", - "content": "{\n \"topics\": [\"Emotions\", \"Weather\"],\n \"relevance_scores\": [0.9, 0.8],\n \"key_phrases\": [\"feeling great\", \"sunny and pleasant\"]\n}" - }, - "finish_reason": "stop" - } - ], - "usage": { - "prompt_tokens": 111, - "completion_tokens": 46, - "total_tokens": 157 - }, - "system_fingerprint": "fp_a24b4d720c" - } - } - ] - }, - "error": null, - "raw_openai_response": null -} +Requires Node 24 and Python 3.12 for Guardrail. +```sh +python -m venv .venv +.venv/bin/pip install -r requirements.txt +npm ci --prefix .harness/runtime +node .harness/runtime/cli.mjs status +RUV_ALLOW_VALIDATION=1 node .harness/runtime/cli.mjs test +RUV_ALLOW_VALIDATION=1 node .harness/runtime/cli.mjs benchmark +node .harness/runtime/cli.mjs mcp ``` -## Understanding the Sample Response - -- **Code 200**: Indicates successful execution of the request. -- **Analysis Summary**: "All conditions met" signifies that both conditions (sentiment analysis and topic extraction) passed their respective checks. -- **Details**: The `condition_responses` array contains individual assessments for each condition, including the total tokens used, retries, and the final OpenAI response details. -- **Final OpenAI Response**: Provides the raw response from the OpenAI API, including the model used, tokens details, and the content analyzed. - - -## Installation -### Requirements -- Python 3.8 or higher -- FastAPI -- Uvicorn -- Pydantic -- Requests -### How to Install -1. Clone the repository to your local machine. -2. Install required Python packages using `pip install -r requirements.txt`. -3. Set environment variables `AUTH_TOKEN` and `OPENAI_API_KEY`. +[Agent tools and CLI](.harness/runtime/README.md) · [Architecture and security](docs/ADR-002-secure-local-agent.md) · [Generated MetaHarness profiles](.harness/generated/README.md) -## How to Use -1. Start the server using `uvicorn main:app --reload`. -2. Access the FastAPI interface at `http://127.0.0.1:8000/docs`. -3. Use the provided endpoints to send requests for data analysis or conditional completions. +## Scope and deployment -## Code Structure -- `main.py`: Contains the FastAPI app initialization, endpoint definitions, and business logic. -- `prompts.py`: Includes predefined prompts and JSON schemas for different types of analysis. -- `security.py`: Manages authentication and security features. (Coming Soon) +The local policy engine is deterministic validation, not a model safety guarantee. Provider routes require OPENAI_API_KEY and AUTH_TOKEN of at least 32 characters. Provider output remains untrusted data. No live paid provider test or production load qualification is claimed. -## Contributing -To contribute, please fork the repository, make changes, and submit a pull request. Contributions are welcome to improve the script's functionality and efficiency. +## Related projects ---- +[RuFlo](https://github.com/ruvnet/ruflo) orchestrates agents. [MetaHarness](https://github.com/ruvnet/metaharness) provides repository harness profiles. [Autogenous](https://github.com/ruvnet/autogenous) supplies governance primitives. [RuVector](https://github.com/ruvnet/ruvector) supplies retrieval and memory. [AgentBBS](https://github.com/ruvnet/AgentBBS) and [the federation](https://x.ruv.io) support coordination. Federation observations are data and do not authorize execution. No federation membership or publication is enabled by this package. -Version: v0.0.1 -Author: @rUv +Run the HTTP API with `AUTH_TOKEN=<32-or-more-characters> .venv/bin/uvicorn main:app --host 127.0.0.1 --port 8080`. Submit `POST /evaluate/` with a bearer token and `{ "details": { "approved": false }, "conditions": [{ "analysis_type": "local", "key": "approved", "condition_type": "exists" }] }`. This returns allowed because the field exists. Use an equality condition when its value matters. diff --git a/docs/ADR-002-secure-local-agent.md b/docs/ADR-002-secure-local-agent.md new file mode 100644 index 0000000..f60cbd3 --- /dev/null +++ b/docs/ADR-002-secure-local-agent.md @@ -0,0 +1,23 @@ +# ADR 002: bounded local Guardrail v2 + +Status: accepted for the alpha implementation. + +## Decision + +Use the smallest testable local trust boundary. Expose fixed operations through the official MCP SDK 2.0.0 and a matching CLI. External messages are data. No remote shell, caller filesystem path, deployment, autonomous promotion or federation writes are exposed. + +## Threat model + +Untrusted JSON can attempt malformed policy or signature input, expensive patterns, oversized bodies, replay, or command injection. Domain validation fails closed. MCP input is bounded to 32 KiB application payload and 64 KiB transport frames. Child processes use a fixed command list, stripped environment, one concurrent slot, 30 second deadline and 64 KiB combined output. Validation requires local operator opt in. Unsigned receipt hashes are diagnostics, not verified execution attestations. + +## Domain boundaries + +The local policy engine is deterministic validation, not a model safety guarantee. Provider routes require OPENAI_API_KEY and AUTH_TOKEN of at least 32 characters. Provider output remains untrusted data. No live paid provider test or production load qualification is claimed. + +## Evidence and acceptance + +Run repository tests, runtime SDK stdio tests, benchmark and dependency audit through CI. Benchmarks describe fixture latency on the current host, not claims of SOTA or production throughput. Adversarial tests cover the concrete failures fixed here. External credentials and deployed federation membership are separately configured by an operator. + +## Rollback + +Revert the change commit and restore a backup before changing database formats. Do not restore revoked identities from an older database snapshot without replaying the revocation log. Do not reenable insecure historical prototypes during rollback. diff --git a/docs/adr/0001-required-field-existence.md b/docs/adr/0001-required-field-existence.md new file mode 100644 index 0000000..cd79a1d --- /dev/null +++ b/docs/adr/0001-required-field-existence.md @@ -0,0 +1,23 @@ +# ADR 0001: Fail closed when required analysis fields are missing + +Status: Accepted for this patch + +## Context + +At baseline `67cc25b7c52acf69bcdea00b094962e06760efe5`, an `exists` condition on an absent field succeeds. `extract_value` substitutes an empty object for a missing key, and the condition accepts anything other than null. A required policy field can therefore be absent while its existence condition passes. + +## Decision + +Route only `exists` conditions through a dedicated presence resolver. Every object key must actually exist. Null, invalid paths, scalar traversal and absent array elements deny. Dotted paths, array indexes including existing negative indexes, and terminal array wildcards are supported. A terminal wildcard tests whether the array exists, including an empty array; it does not assert that every item has a field. Wildcards followed by additional path components deny because that interpretation is ambiguous. + +Existing false, zero, empty strings, empty objects and empty arrays still count as present. Existence is not truthiness or policy approval. Other comparison operators retain their existing implementation and semantics. + +## Verification + +Run `python -m unittest discover -s tests -v`. Ten tests cover missing and nested fields, null, falsy values, array traversal, malformed paths and representative unchanged comparisons. Tests load the actual pure functions from `main.py` through Python AST, so they require neither legacy web dependencies nor provider credentials. This is a unit regression suite, not HTTP or provider integration validation. + +The original missing field case returned true before this patch and false after it. A latency benchmark would not establish a meaningful improvement for this correctness change and is intentionally omitted. + +## Limits and rollback + +This patch does not address unrestricted regular expressions in other conditions, provider call budgets, dependency qualification or model output schema enforcement. Existing clients relying on absent fields or malformed paths passing `exists` will now receive a failed condition. Rollback is a Git revert, but restores the fail open behavior. diff --git a/docs/assets/header.svg b/docs/assets/header.svg new file mode 100644 index 0000000..2fc69b3 --- /dev/null +++ b/docs/assets/header.svg @@ -0,0 +1 @@ +RUVNET / VERIFIED LOCAL CAPABILITIESGuardrailV2 ALPHA · CLI · MCP · TESTS · GOVERNANCE \ No newline at end of file diff --git a/docs/evidence/dependency-audit.json b/docs/evidence/dependency-audit.json new file mode 100644 index 0000000..1ab8867 --- /dev/null +++ b/docs/evidence/dependency-audit.json @@ -0,0 +1 @@ +{"dependencies": [{"name": "annotated-doc", "version": "0.0.5", "vulns": []}, {"name": "annotated-types", "version": "0.8.0", "vulns": []}, {"name": "anyio", "version": "4.15.1", "vulns": []}, {"name": "boolean-py", "version": "5.0", "vulns": []}, {"name": "cachecontrol", "version": "0.14.4", "vulns": []}, {"name": "msgpack", "version": "1.2.2", "vulns": []}, {"name": "certifi", "version": "2026.7.22", "vulns": []}, {"name": "charset-normalizer", "version": "3.5.1", "vulns": []}, {"name": "click", "version": "8.5.0", "vulns": []}, {"name": "cyclonedx-python-lib", "version": "11.12.0", "vulns": []}, {"name": "license-expression", "version": "30.4.4", "vulns": []}, {"name": "packageurl-python", "version": "0.17.6", "vulns": []}, {"name": "py-serializable", "version": "2.1.0", "vulns": []}, {"name": "defusedxml", "version": "0.7.1", "vulns": []}, {"name": "sortedcontainers", "version": "2.4.0", "vulns": []}, {"name": "typing-extensions", "version": "4.16.0", "vulns": []}, {"name": "fastapi", "version": "0.141.1", "vulns": []}, {"name": "filelock", "version": "3.32.6", "vulns": []}, {"name": "h11", "version": "0.16.0", "vulns": []}, {"name": "httpcore", "version": "1.0.9", "vulns": []}, {"name": "httpx", "version": "0.28.1", "vulns": []}, {"name": "idna", "version": "3.19", "vulns": []}, {"name": "markdown-it-py", "version": "4.2.0", "vulns": []}, {"name": "mdurl", "version": "0.1.2", "vulns": []}, {"name": "pip-requirements-parser", "version": "32.0.1", "vulns": []}, {"name": "pip-api", "version": "0.0.35", "vulns": []}, {"name": "pip-audit", "version": "2.10.1", "vulns": []}, {"name": "platformdirs", "version": "4.11.8", "vulns": []}, {"name": "pydantic", "version": "2.13.5", "vulns": []}, {"name": "pydantic-core", "version": "2.46.5", "vulns": []}, {"name": "pygments", "version": "2.21.0", "vulns": []}, {"name": "pyparsing", "version": "3.3.2", "vulns": []}, {"name": "regex", "version": "2026.9.10", "vulns": []}, {"name": "requests", "version": "2.34.2", "vulns": []}, {"name": "urllib3", "version": "2.7.0", "vulns": []}, {"name": "rich", "version": "15.0.0", "vulns": []}, {"name": "starlette", "version": "1.6.0", "vulns": []}, {"name": "tomli", "version": "2.4.1", "vulns": []}, {"name": "tomli-w", "version": "1.2.0", "vulns": []}, {"name": "typing-inspection", "version": "0.4.4", "vulns": []}, {"name": "uvicorn", "version": "0.52.4", "vulns": []}], "fixes": []} diff --git a/docs/historical-readme.md b/docs/historical-readme.md new file mode 100644 index 0000000..b4bfea4 --- /dev/null +++ b/docs/historical-readme.md @@ -0,0 +1,281 @@ +# GuardRail OSS - Open Source Ai Guidance & Analysis API +![Guardrail](https://github.com/ruvnet/guardrail/blob/main/assets/guardrail.png?raw=true) + +## 🧭 The GuardRail system combined with AiEQ advances responsible AI with robust data analysis and emotional intelligence, equipping AI with a moral compass. + +GuardRail is an Open Source API-driven framework, designed to enhance responsible AI systems and workflows, providing advanced data analysis and dynamic conditional completions. This makes it essential for refining AI-powered outputs, increasing their quality and relevance. AiEQ, or Artificial Emotional Intelligence, complements this by equipping AI with the ability to interpret and respond to emotional contexts (EQ), adding a layer of empathy and ethical understanding. This synergy between GuardRail's technical enhancement capabilities and AiEQ's emotional intelligence introduces a new standard in AI, making it more adaptable, responsive, and attuned to human nuances. + +### Test API For Free (more than 50 advanced traits & guiderails) +- https://rapidapi.com/ruv/api/guardrail + +### OpenAI ChatGPT GPT +- https://chat.openai.com/g/g-6Bvt5pJFf-guardrail + +## AiEQ +### AiEQ infuses AI with emotional, psychological, and ethical intelligence kind of internal voice, essential for understanding and empathizing with human users. + +AiEQ is a pioneering concept in AI, introducing an 'inner voice' that allows AI to perceive and interpret emotions, akin to human emotional intelligence. This model enables AI to transcend traditional data processing, allowing it to empathize with human emotions and respond accordingly. AiEQ's ability to navigate through emotional nuances and understand the subtleties of human psychology is pivotal in creating AI that is not just efficient but also emotionally attuned and ethically responsible. + +### GuardRails + +Complementing AiEQ is the GuardRail open source guidance system. This versatile framework integrates seamlessly with AI models, including AiEQ, to provide advanced data analysis, sentiment analysis, content classification, and trend detection. GuardRail's role extends beyond mere analysis; it is instrumental in ensuring Responsible AI (RAI) practices. + +It offers tools and guidelines for mitigating bias, and addressing psychological, ethical, and emotional considerations in AI development and deployment. GuardRail's adaptability makes it invaluable in various applications, from content moderation and customer support to market research and mental health, ensuring AI contributions are not only high-quality but also ethically sound and emotionally relevant. + +Together, AiEQ and the GuardRail Data Analysis system embody a comprehensive approach to responsible AI development. GuardRail complements this by offering an API-driven framework that not only enhances AI capabilities but also ensures their ethical application and mitigates biases. This powerful combination guarantees that AI systems are technically advanced, ethically responsible, and emotionally attuned, setting a new standard for AI as a trusted, empathetic partner in diverse aspects of human life. + +## AI Guardrails +AI Guardrails, as implemented in the GuardRail Script & API, are a set of advanced mechanisms and protocols designed to regulate and oversee the performance of AI systems, particularly in generating and analyzing text. The primary purpose of these guardrails is to ensure that the AI operates within a predefined ethical and quality framework, producing results that are not only accurate but also align with societal norms and values. + +## 🌟 Key Features and Capabilities + +| Feature | Description | +| --------------------------------------- | ----------- | +| 🧭 Responsible AI Ethical Framework | Integrates emotional, psychological, and ethical intelligence, empowering AI with a moral compass for empathetic and ethically informed decision-making. | +| 🧮 **Conditional System** | Implements conditions based on analysis results, allowing for fine-tuned control and contextual responsiveness in output. | +| 🔗 **API-Driven Integration** | Designed for easy integration with existing AI systems, enhancing chatbots, intelligent agents, and automated workflows. | +| ⚙️ **Customizable GPT Model Usage** | Enables the tailoring of text generation and analysis to specific needs, leveraging various GPT model capabilities. | +| ⏱️ **Real-Time Data Processing** | Capable of handling and analyzing data in real-time, providing immediate insights and responses. | +| 🌐 **Multi-Lingual Support** | Offers the ability to process and analyze text in multiple languages, broadening its applicability. | +| 🚫 **Automated Content Moderation** | Employs AI to automatically detect and handle inappropriate or sensitive content, ensuring safe digital environments. | +| 🔄 **Feedback and Improvement Mechanisms** | Incorporates user feedback for continuous improvement of the system, adapting to evolving requirements and standards. | + +# Capabilities Overview + +The Guiderails Script offers a wide range of capabilities, organized into various groups based on tasks or focus areas. These capabilities are designed to analyze text data comprehensively, offering insights across multiple dimensions. The `/analysis_types` endpoint provides a complete list of these functions, with an extensive array of over 50 different analysis types. + +| Feature | Description | +| ------------------------------------------------| ----------- | +| 🧠 **Psychological Understanding** | Equips AI with the ability to interpret and respond to human psychological states, enhancing user interaction and engagement. | +| ❤️ **Emotional Intelligence (Emotion AI)** | Allows AI to recognize and respond to human emotions, facilitating more natural and empathetic interactions. | +| 🧭 **Ethical Decision-Making** | Incorporates ethical guidelines into AI decision processes, ensuring actions align with moral and societal values. | +| 🛡️ **Bias Mitigation** | Implements algorithms and safeguards to reduce biases in AI processing and decision-making, promoting fairness and inclusivity. | + + +## 📊 Text Analysis +- **Sentiment Analysis**: Determine the sentiment (positive, negative, or neutral) and provide a confidence score. +- **Text Summarization**: Condense text, capturing key points and main ideas. +- **Topic Extraction**: Identify and extract main topics or themes. +- **Emotion Detection**: Detect primary emotions and their intensity. +- **Keyword Extraction**: Extract central words or phrases. +- **Content Classification**: Categorize text into predefined genres or categories. +- **Trend Analysis**: Identify current trends, patterns, or emerging themes. +- **Grammatical Error Check**: Identify and suggest corrections for grammatical errors. + +## 🌍 Language & Cultural Analysis +- **Language Translation**: Translate text into specified target languages. +- **Cultural Trend Analysis**: Gain insights into cultural trends and public sentiment. +- **Cultural Analysis**: Understand societal norms, values, and practices. +- **Sarcasm and Irony Detection**: Differentiate between literal and figurative language. + +## 🏛️ Political & Legal Analysis +- **Political Bias Detection**: Detect political bias and ideological leanings. +- **Fake News Detection**: Assess the likelihood of fake news. +- **Legal Document Analysis**: Interpret legal language and document implications. + +## 🧠 Psychological & Behavioral Analysis +- **Psychological Analysis**: Understand emotions, behaviors, and mental states. +- **Behavioral Analysis**: Analyze described or implied behaviors and motivations. +- **Emotional Intelligence Analysis**: Evaluate aspects of emotional intelligence. +- **Cognitive Bias Identification**: Detect cognitive biases and skewed perspectives. +- **Addiction Tendency Analysis**: Evaluate signs of addictive behaviors. + +## 🔄 Relationship & Conflict Analysis +- **Relationship Analysis**: Insights into relationships and social dynamics. +- **Conflict Resolution Analysis**: Understand conflict resolution strategies. +- **Conflict Tendency Analysis**: Analyze conflict triggers and patterns. + +## 📈 Market & Brand Analysis +- **Market Research Analysis**: Insights into market trends and consumer preferences. +- **Brand Sentiment Analysis**: Assess public sentiment towards brands. +- **Product Review Analysis**: Analyze customer opinions and satisfaction in reviews. +- **Customer Feedback Analysis**: Determine overall satisfaction from customer feedback. + +## 🎓 Educational & Learning Analysis +- **Learning Style Identification**: Identify preferred learning styles. +- **Educational Content Analysis**: Analyze educational materials and approaches. + +## 🌐 Social Media & Communication Analysis +- **Social Media Monitoring**: Monitor and analyze social media content. +- **Dialogue Analysis**: Understand character interactions and conversational dynamics. + +## 🧬 Health & Wellness Analysis +- **Health and Wellness Analysis**: Evaluate health-related content, including medical conditions. +- **Stress Level Detection**: Assess stress levels and identify triggers. +- **Sleep Quality Assessment**: Analyze mentions of sleep quality and issues. +- **Psychosomatic Symptom Analysis**: Assess psychosomatic symptoms and causes. + +## 📝 Literary & Historical Analysis +- **Literary Analysis**: Examine literary aspects like themes and narrative style. +- **Historical Data Analysis**: Analyze historical events and patterns. + +## 🖥️ User Experience & Feedback +- **User Experience Feedback Analysis**: Evaluate user experience feedback, identifying usability issues. + +## 🧘‍♀️ Mindfulness & Therapy Analysis +- **Automated Therapy Session Analysis**: Analyze therapy session transcripts. +- **Mindfulness Meditation Effectiveness**: Analyze mindfulness and meditation techniques. + +## 📈 Advanced Analytical Functions +- **Motivational Analysis**: Examine motivational messages and impact. +- **Therapeutic Intervention Analysis**: Evaluate relevance and effectiveness of therapeutic interventions. + +Please note that the script includes over 50 distinct analysis functions. For the complete list and detailed descriptions of each type, users can query the `/analysis_types` endpoint. + +## Detailed Overview of the Conditional System + +The conditional system in the Guiderail's Script is designed to execute complex analyses with conditions applied to the results. This system allows for greater control and specificity in handling AI-generated data. + +### Simple and Advanced Conditions + +- **Simple Conditions**: Basic conditions involve checking a single key-value pair in the analysis results. Example: Check if the sentiment analysis's confidence score is above a certain threshold. +- **Advanced Conditions**: These involve more intricate checks, possibly over multiple keys or complex data structures. Example: Verifying that relevance scores in topic extraction meet certain criteria. + +### Sample JSON Formatted Conditions + +#### Request Format +```json +{ + "request_data": { + "analysis_type": "sentiment_analysis", + "messages": [ + {"role": "user", "content": "I am feeling great today!"}, + {"role": "user", "content": "The weather is sunny and pleasant."} + ], + "token_limit": 1000, + "top_p": 0.1, + "temperature": 0 + }, + "conditions": [ + { + "analysis_type": "sentiment_analysis", + "key": "confidence_score", + "threshold": 0.5, + "condition_type": "greater" + }, + { + "analysis_type": "topic_extraction", + "key": "relevance_scores", + "threshold": 0.1, + "condition_type": "greater" + } + ] +} +``` +Response Format +```json +{ + "analysis": "All conditions met", + "details": { + "condition_responses": [ + { + "condition": { + "analysis_type": "sentiment_analysis", + "key": "confidence_score", + "threshold": 0.5, + "condition_type": "greater" + }, + "result": "Condition met", + "total_tokens_used": 155, + "retries": 0, + "final_openai_response": { + "id": "chatcmpl-8RoZaFxsQ7osZUEGcZvHPipPk0EMy", + "object": "chat.completion", + "created": 1701639950, + "model": "gpt-4-1106-preview", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "{\n \"sentiment\": \"positive\",\n \"confidence_score\": 0.95,\n \"text_snippets\": [\"feeling great\", \"sunny and pleasant\"]\n}" + }, + "finish_reason": "stop" + } + ], + "usage": { + "prompt_tokens": 118, + "completion_tokens": 37, + "total_tokens": 155 + }, + "system_fingerprint": "fp_a24b4d720c" + } + }, + { + "condition": { + "analysis_type": "topic_extraction", + "key": "relevance_scores", + "threshold": 0.1, + "condition_type": "greater" + }, + "result": "Condition met", + "total_tokens_used": 157, + "retries": 0, + "final_openai_response": { + "id": "chatcmpl-8RoZcw4UY9U19tGuita6CEANw0Cq6", + "object": "chat.completion", + "created": 1701639952, + "model": "gpt-4-1106-preview", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "{\n \"topics\": [\"Emotions\", \"Weather\"],\n \"relevance_scores\": [0.9, 0.8],\n \"key_phrases\": [\"feeling great\", \"sunny and pleasant\"]\n}" + }, + "finish_reason": "stop" + } + ], + "usage": { + "prompt_tokens": 111, + "completion_tokens": 46, + "total_tokens": 157 + }, + "system_fingerprint": "fp_a24b4d720c" + } + } + ] + }, + "error": null, + "raw_openai_response": null +} + +``` +## Understanding the Sample Response + +- **Code 200**: Indicates successful execution of the request. +- **Analysis Summary**: "All conditions met" signifies that both conditions (sentiment analysis and topic extraction) passed their respective checks. +- **Details**: The `condition_responses` array contains individual assessments for each condition, including the total tokens used, retries, and the final OpenAI response details. +- **Final OpenAI Response**: Provides the raw response from the OpenAI API, including the model used, tokens details, and the content analyzed. + + +## Installation +### Requirements +- Python 3.8 or higher +- FastAPI +- Uvicorn +- Pydantic +- Requests + +### How to Install +1. Clone the repository to your local machine. +2. Install required Python packages using `pip install -r requirements.txt`. +3. Set environment variables `AUTH_TOKEN` and `OPENAI_API_KEY`. + +## How to Use +1. Start the server using `uvicorn main:app --reload`. +2. Access the FastAPI interface at `http://127.0.0.1:8000/docs`. +3. Use the provided endpoints to send requests for data analysis or conditional completions. + +## Code Structure +- `main.py`: Contains the FastAPI app initialization, endpoint definitions, and business logic. +- `prompts.py`: Includes predefined prompts and JSON schemas for different types of analysis. +- `security.py`: Manages authentication and security features. (Coming Soon) + +## Contributing +To contribute, please fork the repository, make changes, and submit a pull request. Contributions are welcome to improve the script's functionality and efficiency. + +--- + +Version: v0.0.1 +Author: @rUv diff --git a/docs/validation.md b/docs/validation.md new file mode 100644 index 0000000..3ca855c --- /dev/null +++ b/docs/validation.md @@ -0,0 +1,9 @@ +# Validation record + +Date: 2026-09-10. Node 24 and Python 3.12 on the managed local runner. + +20 Python tests passed including actual FastAPI HTTP calls. Policy fixture 10000 iterations: p50 4.507 microseconds and p95 4.727 microseconds. pip-audit found zero known vulnerabilities in requirements.txt. + +3 runtime tests passed through the official MCP SDK 2 stdio client, including a real domain operation, tool and resource discovery, unknown operation denial, invalid fields, local validation opt in and receipt generation. Runtime npm audit: zero known vulnerabilities. + +Generated MetaHarness profiles: 7 tests, build, doctor, benchmark generation/verification and audit passed. Autogenous gate: 6 Rust tests passed against the pinned upstream agl-types implementation. These are local regression and fixture results, not independent model evaluation or production certification. Check GitHub Actions on the final commit before merging. diff --git a/main.py b/main.py index dd25f35..22cf3fb 100644 --- a/main.py +++ b/main.py @@ -6,6 +6,9 @@ # Standard library imports import os import re +import secrets +import math +import regex import json import logging from typing import List, Literal, Optional, Union, Dict, Any @@ -21,9 +24,12 @@ from typing import Union # Pydantic imports -from pydantic import BaseModel, Field +from pydantic import BaseModel, Field, field_validator # External library imports +import re +import secrets +import math import requests import asyncio import httpx @@ -31,13 +37,16 @@ # Local module imports import prompts # Import the prompts module +class SafeModel(BaseModel): + model_config = {"allow_inf_nan": False, "extra": "forbid"} + security = HTTPBearer() def get_current_user(credentials: HTTPAuthorizationCredentials = Security(security)): auth_token = os.getenv("AUTH_TOKEN") if credentials.scheme != "Bearer": raise HTTPException(status_code=403, detail="Invalid authentication scheme.") - if credentials.credentials != auth_token: + if not auth_token or len(auth_token) < 32 or len(credentials.credentials) > 1024 or not secrets.compare_digest(credentials.credentials.encode("utf-8"), auth_token.encode("utf-8")): raise HTTPException(status_code=403, detail="Invalid token.") return credentials.credentials @@ -47,8 +56,8 @@ def get_current_user(credentials: HTTPAuthorizationCredentials = Security(securi # Configure CORS app.add_middleware( CORSMiddleware, - allow_origins=["*"], - allow_credentials=True, + allow_origins=[], + allow_credentials=False, allow_methods=["*"], allow_headers=["*"], ) @@ -93,52 +102,54 @@ def custom_openapi(): OPENAI_API_BASE_URL = "https://api.openai.com/v1" # Define the AnalysisResult model -class AnalysisResult(BaseModel): +class AnalysisResult(SafeModel): analysis: str details: Dict[str, Any] error: Optional[str] raw_openai_response: Optional[Dict[str, Any]] = None # Add this line # Model for a message within a completion request -class Message(BaseModel): - role: str - content: str +class Message(SafeModel): + role: Literal["system", "user", "assistant"] + content: str = Field(max_length=16384) # Model for a completion request -class CompletionRequest(BaseModel): +class CompletionRequest(SafeModel): model: str = "gpt-3.5-turbo-1106" temperature: float = 0 - max_tokens: int = 1000 + max_tokens: int = Field(default=1000, ge=1, le=4096) top_p: float = 0.1 frequency_penalty: float = 0.0 presence_penalty: float = 0.0 - messages: List[Message] - n: int = 1 - stream: bool = False + messages: List[Message] = Field(min_length=1, max_length=32) + n: Literal[1] = 1 + stream: Literal[False] = False # Function to call OpenAI API +provider_slots = asyncio.Semaphore(4) async def call_openai_api(endpoint: str, data: dict): - openai_api_key = os.getenv("OPENAI_API_KEY") # Retrieve API key from environment variable - headers = { - "Authorization": f"Bearer {openai_api_key}", - "Content-Type": "application/json" - } - url = f"{OPENAI_API_BASE_URL}/{endpoint}" - response = None - - async with httpx.AsyncClient() as client: - try: - response = await client.post(url, headers=headers, json=data) - response.raise_for_status() - return {"response": response.json(), "raw_response": response.text, "error": None, "status_code": response.status_code} - except httpx.HTTPError as http_err: - # Ensure raw response is returned even in case of HTTP errors - raw_response = response.text if response else None - return {"response": response.json() if response else None, "raw_response": raw_response, "error": str(http_err), "status_code": response.status_code if response else 500} - except Exception as exc: - # Catch any other exceptions and return the error with the raw response if available - raw_response = response.text if response else None - return {"response": response.json() if response else None, "raw_response": raw_response, "error": str(exc), "status_code": 500} + if endpoint not in {"chat/completions", "completions"}: + raise HTTPException(400, "Unsupported provider endpoint") + key = os.getenv("OPENAI_API_KEY") + if not key: + raise HTTPException(503, "Provider is not configured") + try: + async with asyncio.timeout(20), provider_slots: + async with httpx.AsyncClient(timeout=15, follow_redirects=False) as client: + async with client.stream("POST", f"{OPENAI_API_BASE_URL}/{endpoint}", + headers={"Authorization": f"Bearer {key}"}, json=data) as response: + response.raise_for_status() + body = bytearray() + async for chunk in response.aiter_bytes(): + body.extend(chunk) + if len(body) > 1048576: + raise ValueError("provider response limit") + value = json.loads(body) + if not isinstance(value, dict): + raise ValueError("provider response type") + return {"response": value, "raw_response": None, "error": None, "status_code": response.status_code} + except (httpx.HTTPError, TimeoutError, ValueError): + raise HTTPException(502, "Provider request failed") from None # Endpoint for creating completions @app.post("/completions/", operation_id="Completions", tags=["Completions"]) @@ -146,20 +157,21 @@ async def completions(completion_request: CompletionRequest, token: str = Depend return await call_openai_api("chat/completions", completion_request.dict()) # Condition class for specifying individual conditions in the analysis -class Condition(BaseModel): +class Condition(SafeModel): analysis_type: str - key: str - threshold: Optional[Union[float, str]] + key: str = Field(min_length=1, max_length=256) + threshold: Optional[Union[float, str]] = None condition_type: Literal['greater', 'less', 'equal', 'contains', 'exists', 'is_type', 'length_greater', 'length_less', 'length_equal', 'nested_contains', 'regex_match', 'key_value_pair'] # Advanced Analysis # Model for an analysis request -class AnalysisRequest(BaseModel): +class AnalysisRequest(SafeModel): + model_config = {"validate_default": True} analysis_type: str = Field(default="sentiment_analysis", example="sentiment_analysis") - messages: List[Message] = Field(default=[{"role": "user", "content": "I feel incredibly happy and content today!"}], example=[{"role": "user", "content": "I feel incredibly happy and content today!"}]) - token_limit: int = Field(default=1000, example=1000) + messages: List[Message] = Field(min_length=1, max_length=32, default=[{"role": "user", "content": "I feel incredibly happy and content today!"}], example=[{"role": "user", "content": "I feel incredibly happy and content today!"}]) + token_limit: int = Field(default=1000, ge=1, le=4096) top_p: float = Field(default=0.9, example=0.1) temperature: float = Field(default=0.0, example=0.0) @@ -291,20 +303,20 @@ async def perform_analysis(request_data: AnalysisRequest, token: str = Depends(g return AnalysisResult(analysis="Error in response format", details={}, error=openai_error or "Invalid response format from OpenAI API.", raw_openai_response=openai_raw_response) -class AnalysisTypeExample(BaseModel): +class AnalysisTypeExample(SafeModel): description: str example_request: Dict[str, Any] -class AnalysisTypesResponse(BaseModel): +class AnalysisTypesResponse(SafeModel): analysis_types: Dict[str, AnalysisTypeExample] # Endpoint to list all analysis types with example JSON requests -class AnalysisTypeDetail(BaseModel): +class AnalysisTypeDetail(SafeModel): type: str json_schema: dict example_request: dict -class AnalysisTypesResponse(BaseModel): +class AnalysisTypesResponse(SafeModel): analysis_types: dict[str, AnalysisTypeDetail] @app.get("/analysis_types", response_model=AnalysisTypesResponse, operation_id="Analysis Types", tags=["Analysis Types"]) @@ -345,12 +357,12 @@ async def suggest_correct_key(data: dict): from asyncio import gather # Updated CombinedRequest model to handle multiple conditions -class CombinedRequest(BaseModel): +class CombinedRequest(SafeModel): request_data: AnalysisRequest - conditions: List[Condition] + conditions: List[Condition] = Field(min_length=1, max_length=32) class Config: - schema_extra = { + json_schema_extra = { "example": { "request_data": { "analysis_type": "sentiment_analysis", @@ -389,7 +401,7 @@ async def perform_analysis_based_on_type(request_data, analysis_type): :return: The result of the analysis. """ # Update the analysis_type in the request_data - request_data.analysis_type = analysis_type + request_data = request_data.model_copy(update={"analysis_type": analysis_type}) # Call the existing /analysis endpoint response = await perform_analysis(request_data) @@ -433,26 +445,51 @@ async def perform_analysis_based_on_type(request_data, analysis_type): """ Perform analysis based on the specified analysis type using the existing /analysis endpoint. """ - request_data.analysis_type = analysis_type + request_data = request_data.model_copy(update={"analysis_type": analysis_type}) return await perform_analysis(request_data) # Helper function to extract value from nested JSON data def extract_value(data, key): - keys = key.split('.') - for k in keys: - if '[' in k and ']' in k: # Handle array indices - array_key, index = k[:-1].split('[') - if index == '*': # Handle wildcard - # Extract all items for a wildcard - return [sub_item for sub_item in data.get(array_key, [])] - else: - # Extract a specific item by index - data = data.get(array_key, [])[int(index)] - else: - # Proceed to the next key if not an array - data = data.get(k, {}) + if not value_exists(data, key): + return None + for part in key.split('.'): + match = re.fullmatch(r"([^\[\]]+)(?:\[(-?\d+|\*)\])?", part) + name, index = match.groups() + data = data[name] + if index == '*': + return data + if index is not None: + data = data[int(index)] return data +def value_exists(data, key): + """Check an existing non-null value without manufacturing missing objects. + + Supports dotted object paths, indexed arrays and terminal array wildcards. + Invalid paths fail closed; a wildcard checks presence of the array itself. + """ + if not isinstance(key, str) or not key: + return False + parts = key.split('.') + for position, part in enumerate(parts): + match = re.fullmatch(r"([^\[\]]+)(?:\[(-?\d+|\*)\])?", part) + if match is None or not isinstance(data, dict): + return False + name, index = match.groups() + if name not in data: + return False + data = data[name] + if index is not None: + if not isinstance(data, list): + return False + if index == '*': + return position == len(parts) - 1 + try: + data = data[int(index)] + except (IndexError, ValueError): + return False + return data is not None + # Function to check if a condition is met def check_condition(analysis_result, condition): """ @@ -465,6 +502,9 @@ def check_condition(analysis_result, condition): Returns: bool: True if the condition is met, False otherwise. """ + if condition.condition_type == "exists": + return value_exists(analysis_result.details, condition.key) + result_value = extract_value(analysis_result.details, condition.key) if result_value is None: @@ -473,13 +513,13 @@ def check_condition(analysis_result, condition): try: if condition.condition_type == 'greater': if isinstance(result_value, list): - return all(float(item) > float(condition.threshold) for item in result_value) - return float(result_value) > float(condition.threshold) + return bool(result_value) and all(type(item) in (int, float) and math.isfinite(item) and math.isfinite(float(condition.threshold)) and item > float(condition.threshold) for item in result_value) + return type(result_value) in (int, float) and math.isfinite(result_value) and math.isfinite(float(condition.threshold)) and result_value > float(condition.threshold) elif condition.condition_type == 'less': if isinstance(result_value, list): - return all(float(item) < float(condition.threshold) for item in result_value) - return float(result_value) < float(condition.threshold) + return bool(result_value) and all(type(item) in (int, float) and math.isfinite(item) and math.isfinite(float(condition.threshold)) and item < float(condition.threshold) for item in result_value) + return type(result_value) in (int, float) and math.isfinite(result_value) and math.isfinite(float(condition.threshold)) and result_value < float(condition.threshold) elif condition.condition_type == 'equal': if isinstance(result_value, dict): @@ -493,12 +533,9 @@ def check_condition(analysis_result, condition): return any(str(condition.threshold) in str(item) for item in result_value) return str(condition.threshold) in str(result_value) - elif condition.condition_type == 'exists': - return result_value is not None - elif condition.condition_type == 'is_type': - expected_type = getattr(__builtins__, condition.threshold, None) - return isinstance(result_value, expected_type) + expected_type = {"str": str, "int": int, "float": float, "bool": bool, "list": list, "dict": dict}.get(condition.threshold) + return type(result_value) is expected_type elif condition.condition_type in ['length_greater', 'length_less', 'length_equal']: if hasattr(result_value, '__len__'): @@ -512,18 +549,42 @@ def check_condition(analysis_result, condition): return length == threshold elif condition.condition_type == 'regex_match': - return bool(re.match(condition.threshold, str(result_value), re.DOTALL | re.MULTILINE)) + if not isinstance(condition.threshold, str) or len(condition.threshold) > 256 or len(str(result_value)) > 16384: + return False + return bool(regex.match(condition.threshold, str(result_value), regex.DOTALL | regex.MULTILINE, timeout=0.02)) elif condition.condition_type == 'key_value_pair': - if isinstance(result_value, dict): + if isinstance(result_value, dict) and isinstance(condition.threshold, str): key, val = condition.threshold.split(':', 1) - return str(result_value.get(key, "")) == val + return key in result_value and str(result_value[key]) == val - except (TypeError, ValueError, IndexError): + except (TypeError, ValueError, IndexError, OverflowError, TimeoutError, regex.error): return False return False +class PolicyRequest(SafeModel): + details: Dict[str, Any] + @field_validator("details") + @classmethod + def finite_json(cls, value): + json.dumps(value, allow_nan=False) + return value + conditions: List[Condition] = Field(min_length=1, max_length=32) + +@app.post("/evaluate/") +async def evaluate_policy(request: PolicyRequest, token: str = Depends(get_current_user)): + return evaluate_local(request) + +def evaluate_local(request): + json.dumps(request.details, allow_nan=False) + result = AnalysisResult(analysis="local", details=request.details, error=None) + decisions = [check_condition(result, condition) for condition in request.conditions] + return {"allowed": all(decisions), "decisions": decisions, "providerUsed": False} + +from safety import RequestLimits +app.add_middleware(RequestLimits) + # Main function to run the app if __name__ == "__main__": import uvicorn diff --git a/package.json b/package.json new file mode 100644 index 0000000..3ebc44b --- /dev/null +++ b/package.json @@ -0,0 +1 @@ +{"name": "guardrail-project", "private": true, "scripts": {"test": "python -m unittest discover -s tests -v", "benchmark": "python scripts/benchmark.py"}} \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 169afdb..b1187a9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,16 +1,18 @@ [tool.poetry] name = "ai-data-analysis-guiderail" -version = "0.0.1" +version = "2.0.0-alpha.1" description = "An advanced data analysis and conditional completions API using OpenAI's GPT models." authors = ["@ruvnet"] [tool.poetry.dependencies] -python = ">=3.10.0,<3.11" -fastapi = "^0.105.0" -httpx = "^0.25.2" -pydantic = "^2.5.2" -requests = "^2.31.0" -uvicorn = "0.24.0.post1" +python = ">=3.12,<4" +fastapi = "0.141.1" +httpx = "0.28.1" +pydantic = "2.13.5" +requests = "2.34.2" +uvicorn = "0.52.4" + +regex = "2026.9.10" [tool.pyright] # https://github.com/microsoft/pyright/blob/main/docs/configuration.md diff --git a/requirements.txt b/requirements.txt index d24d6d2..d78a569 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,19 +1,42 @@ -annotated-types==0.6.0 -anyio==3.7.1 -certifi==2023.11.17 -charset-normalizer==3.3.2 -click==8.1.7 -exceptiongroup==1.2.0 -fastapi==0.105.0 -h11==0.14.0 -httpcore==1.0.2 -httpx==0.25.2 -idna==3.6 -pydantic==2.5.2 -pydantic-core==2.14.5 -requests==2.31.0 -sniffio==1.3.0 -starlette==0.27.0 -typing-extensions==4.9.0 -urllib3==2.1.0 -uvicorn==0.24.0.post1 \ No newline at end of file +annotated-doc==0.0.5 +annotated-types==0.8.0 +anyio==4.15.1 +boolean.py==5.0 +CacheControl==0.14.4 +certifi==2026.7.22 +charset-normalizer==3.5.1 +click==8.5.0 +cyclonedx-python-lib==11.12.0 +defusedxml==0.7.1 +fastapi==0.141.1 +filelock==3.32.6 +h11==0.16.0 +httpcore==1.0.9 +httpx==0.28.1 +idna==3.19 +license-expression==30.4.4 +markdown-it-py==4.2.0 +mdurl==0.1.2 +msgpack==1.2.2 +packageurl-python==0.17.6 +packaging==26.3 +pip-requirements-parser==32.0.1 +pip_api==0.0.35 +pip_audit==2.10.1 +platformdirs==4.11.8 +py-serializable==2.1.0 +pydantic==2.13.5 +pydantic_core==2.46.5 +Pygments==2.21.0 +pyparsing==3.3.2 +regex==2026.9.10 +requests==2.34.2 +rich==15.0.0 +sortedcontainers==2.4.0 +starlette==1.6.0 +tomli==2.4.1 +tomli_w==1.2.0 +typing-inspection==0.4.4 +typing_extensions==4.16.0 +urllib3==2.7.0 +uvicorn==0.52.4 diff --git a/safety.py b/safety.py new file mode 100644 index 0000000..bff7401 --- /dev/null +++ b/safety.py @@ -0,0 +1,37 @@ +import asyncio + +class RequestLimits: + def __init__(self, app): + self.app = app + async def __call__(self, scope, receive, send): + if scope["type"] != "http": + return await self.app(scope, receive, send) + body = bytearray() + status = None + try: + async with asyncio.timeout(10): + for _ in range(4096): + message = await receive() + if message["type"] == "http.disconnect": + return + body.extend(message.get("body", b"")) + if len(body) > 65536: + status = 413 + break + if not message.get("more_body", False): + break + else: + status = 413 + except TimeoutError: + status = 408 + if status: + await send({"type": "http.response.start", "status": status, "headers": []}) + return await send({"type": "http.response.body", "body": b"Request limit exceeded"}) + consumed = False + async def bounded_receive(): + nonlocal consumed + if consumed: + return await receive() + consumed = True + return {"type": "http.request", "body": bytes(body), "more_body": False} + await self.app(scope, bounded_receive, send) diff --git a/scripts/benchmark.py b/scripts/benchmark.py new file mode 100644 index 0000000..0e427bd --- /dev/null +++ b/scripts/benchmark.py @@ -0,0 +1,9 @@ +import json, sys, time +from pathlib import Path +sys.path.insert(0,str(Path(__file__).resolve().parents[1])) +from main import PolicyRequest,evaluate_local +request=PolicyRequest(details={'score':0.8},conditions=[{'key':'score','analysis_type':'local','condition_type':'greater','threshold':0.5}]) +samples=[] +for _ in range(10000): + start=time.perf_counter_ns();assert evaluate_local(request)['allowed'];samples.append((time.perf_counter_ns()-start)/1000) +samples.sort();print(json.dumps({'workload':'local policy evaluation','iterations':10000,'p50Microseconds':samples[5000],'p95Microseconds':samples[9500],'productionQualification':False})) diff --git a/scripts/policy.py b/scripts/policy.py new file mode 100644 index 0000000..2e91967 --- /dev/null +++ b/scripts/policy.py @@ -0,0 +1,8 @@ +import json, sys +from pathlib import Path +sys.path.insert(0, str(Path(__file__).resolve().parents[1])) +from main import PolicyRequest, evaluate_local +body=sys.stdin.buffer.read(32769) +if len(body)>32768: raise ValueError('Input limit') +request=PolicyRequest.model_validate_json(body) +print(json.dumps(evaluate_local(request),allow_nan=False)) diff --git a/tests/test_api.py b/tests/test_api.py new file mode 100644 index 0000000..867d74a --- /dev/null +++ b/tests/test_api.py @@ -0,0 +1,39 @@ +import os, unittest, asyncio +from fastapi.testclient import TestClient +from main import app,check_condition,Condition,AnalysisResult,AnalysisRequest,perform_analysis_based_on_type +from unittest.mock import AsyncMock,patch +os.environ['AUTH_TOKEN']='x'*32 +class ApiTests(unittest.TestCase): + def setUp(self): self.client=TestClient(app);self.headers={'Authorization':'Bearer '+'x'*32} + def payload(self): return {'details':{'ok':False},'conditions':[{'analysis_type':'local','key':'ok','condition_type':'exists'}]} + def test_http_authenticated_evaluation(self): + r=self.client.post('/evaluate/',json=self.payload(),headers=self.headers);self.assertEqual(r.status_code,200);self.assertTrue(r.json()['allowed']);self.assertFalse(r.json()['providerUsed']) + def test_missing_or_short_auth_denied(self): + self.assertIn(self.client.post('/evaluate/',json=self.payload()).status_code,[401,403]) + with patch.dict(os.environ,{'AUTH_TOKEN':'short'}): self.assertEqual(self.client.post('/evaluate/',json=self.payload(),headers=self.headers).status_code,403) + def test_request_size_bound(self): self.assertEqual(self.client.post('/evaluate/',content=b'x'*65537,headers=self.headers).status_code,413) + def test_empty_conditions_invalid(self): + p=self.payload();p['conditions']=[];self.assertEqual(self.client.post('/evaluate/',json=p,headers=self.headers).status_code,422) + def test_missing_all_operators_deny(self): + for kind in ['greater','less','equal','contains','is_type','length_equal','regex_match','key_value_pair']: + c=Condition(analysis_type='local',key='missing',condition_type=kind,threshold='dict');self.assertFalse(check_condition(AnalysisResult(analysis='local',details={},error=None),c)) + def test_numeric_empty_bool_nonfinite_deny(self): + c=Condition(analysis_type='local',key='x',condition_type='greater',threshold=0) + for value in [[],True,float('inf'),float('nan')]:self.assertFalse(check_condition(AnalysisResult(analysis='local',details={'x':value},error=None),c)) + def test_regex_invalid_and_pathological_deny(self): + for pattern,value in [('(', 'x'),('(a+)+$', 'a'*12000+'!')]: + c=Condition(analysis_type='local',key='x',condition_type='regex_match',threshold=pattern);self.assertFalse(check_condition(AnalysisResult(analysis='local',details={'x':value},error=None),c)) + def test_type_bool_is_not_int(self): + c=Condition(analysis_type='local',key='x',condition_type='is_type',threshold='int');self.assertFalse(check_condition(AnalysisResult(analysis='local',details={'x':True},error=None),c)) + def test_parallel_analysis_does_not_mutate(self): + request=AnalysisRequest() + with patch('main.perform_analysis',new=AsyncMock(return_value=None)) as mock: + asyncio.run(perform_analysis_based_on_type(request,'other'));self.assertEqual(request.analysis_type,'sentiment_analysis');self.assertEqual(mock.call_args.args[0].analysis_type,'other') + + def test_unicode_invalid_token_is_denied(self): + from main import get_current_user + from fastapi import HTTPException + from fastapi.security import HTTPAuthorizationCredentials + with self.assertRaises(HTTPException) as caught: + get_current_user(HTTPAuthorizationCredentials(scheme='Bearer',credentials='é'*32)) + self.assertEqual(caught.exception.status_code,403) diff --git a/tests/test_conditions.py b/tests/test_conditions.py new file mode 100644 index 0000000..09b3945 --- /dev/null +++ b/tests/test_conditions.py @@ -0,0 +1,77 @@ +"""Offline regressions exercising main.py's actual pure condition functions.""" +import ast +from pathlib import Path +import re +import math +import regex +from types import SimpleNamespace +import unittest + + +def load_conditions(): + path = Path(__file__).resolve().parents[1] / "main.py" + module = ast.parse(path.read_text()) + names = {"extract_value", "value_exists", "check_condition"} + functions = [node for node in module.body + if isinstance(node, ast.FunctionDef) and node.name in names] + namespace = {"re": re, "math": math, "regex": regex} + exec(compile(ast.Module(body=functions, type_ignores=[]), str(path), "exec"), namespace) + return namespace["check_condition"] + + +check_condition = load_conditions() + + +def evaluate(details, key, kind="exists", threshold=None): + return check_condition(SimpleNamespace(details=details), + SimpleNamespace(key=key, condition_type=kind, threshold=threshold)) + + +class ConditionTests(unittest.TestCase): + def test_missing_required_field_denies(self): + self.assertFalse(evaluate({}, "required")) + + def test_missing_nested_field_denies(self): + self.assertFalse(evaluate({"policy": {}}, "policy.approved")) + + def test_explicit_null_denies(self): + self.assertFalse(evaluate({"approved": None}, "approved")) + + def test_present_falsy_values_exist(self): + for value in [False, 0, "", [], {}]: + with self.subTest(value=value): + self.assertTrue(evaluate({"value": value}, "value")) + + def test_present_nested_array_value(self): + self.assertTrue(evaluate({"items": [{"id": 0}]}, "items[0].id")) + self.assertTrue(evaluate({"items": [False]}, "items[-1]")) + + def test_missing_array_element_denies(self): + for key in ["items[0]", "items[-1]", "absent[0]", "items[999999999999999999999999]"]: + with self.subTest(key=key): + self.assertFalse(evaluate({"items": []}, key)) + + def test_terminal_wildcard_requires_actual_array(self): + self.assertTrue(evaluate({"items": []}, "items[*]")) + self.assertTrue(evaluate({"items": [None]}, "items[*]")) + for details in [{}, {"items": None}, {"items": {}}]: + self.assertFalse(evaluate(details, "items[*]")) + + def test_invalid_paths_deny(self): + for key in ["", ".", "items[", "items[x]", "items[0][1]", "items[*].id", "items..id"]: + with self.subTest(key=key): + self.assertFalse(evaluate({"items": [{"id": 1}]}, key)) + + def test_traversal_through_scalar_denies(self): + for value in [None, False, 1, "text", []]: + self.assertFalse(evaluate({"value": value}, "value.child")) + + def test_other_conditions_preserved(self): + self.assertTrue(evaluate({"score": 0.8}, "score", "greater", 0.5)) + self.assertFalse(evaluate({"score": 0.2}, "score", "greater", 0.5)) + self.assertTrue(evaluate({"label": "safe"}, "label", "equal", "safe")) + self.assertTrue(evaluate({"tags": ["a"]}, "tags", "length_equal", 1)) + + +if __name__ == "__main__": + unittest.main()