ai-output-guard 0.1.1

AI Output Safety Middleware — the seatbelt between LLMs and your systems

AI Output Guard

AI Output Safety Engine — The seatbelt between LLMs and your systems

---

Why AI Output Guard?

LLM outputs are unreliable. Missing JSON fields, hallucinated APIs, permission bypasses — any of these can cause production incidents.

AI Output Guard provides a three-layer progressive validation pipeline (Schema → Semantic → Policy) to catch problems before AI output reaches your systems.

LLM Output  ──→  [Schema Guard]  ──→  [Semantic Guard]  ──→  [Policy Guard]  ──→  Safe Output
                  Structure check        Intent detection         Policy rules
                  auto-fix               keyword+regex            YAML DSL engine

Quick Start

Install

# Core (Python SDK + CLI)
pip install ai-output-guard

# With semantic enhancement (sentence-transformers)
pip install ai-output-guard[semantic]

# All extras (proxy, API, semantic)
pip install ai-output-guard[all]

Use

from agentguard import Guard
from pydantic import BaseModel

class APIResponse(BaseModel):
    action: str
    target: str

# One-line initialization, all three layers active
guard = Guard(
    schema=APIResponse,          # Schema validation + auto-fix
    semantic=True,               # Dangerous intent detection
    policy="policies/prod.yaml", # Policy rule matching
)

# Validate LLM output
result = guard.validate('{"action": "DROP TABLE users", "target": "*"}')

if result.passed:
    use(result.output)    # Safe to use
elif result.blocked:
    log_and_alert(result) # Blocked — check blocked_by
elif result.was_fixed:
    use(result.output)    # Auto-fixed — review fixes

Three Guard Layers

1. Schema Guard — Structure Validation

• Supports Pydantic v2 models and raw JSON Schema
• Auto-fix: enum fuzzy matching (Levenshtein), type coercion, missing field defaults, extra field stripping
• Nested object recursive fixing and array item type coercion
• <1ms latency

2. Semantic Guard — Intent Detection

• 25 built-in dangerous intents (drop_table, ssh_connect, expose_api_key, etc.)
• Three-level matching: keyword (fastest) → regex → heuristic
• critical/high → DENY, medium/low → WARN
• Zero external dependencies

3. Policy Guard — Rule Engine

• YAML DSL with 14 operators
• Logical combinators: all (AND) / any (OR)
• Dot-notation nested field access
• 5 actions: allow / deny / warn / ask_human / modify

Policy DSL Example

version: "1.0"
defaults:
  on_no_match: allow
  on_error: deny

rules:
  - name: block-db-writes
    priority: 100
    condition:
      all:
        - field: action
          operator: in
          value: [DROP, DELETE, TRUNCATE, ALTER]
        - field: target
          operator: matches
          value: "*users*"
    action: deny
    message: "Database write operations blocked for user tables"

  - name: warn-large-response
    priority: 50
    condition:
      field: response_size
      operator: gt
      value: 1000000
    action: warn
    message: "Large response detected"

  - name: flag-external-ssh
    priority: 80
    condition:
      any:
        - field: target_host
          operator: not_in
          value: [10.0.0.0/8, 172.16.0.0/12]
        - field: protocol
          operator: equals
          value: ssh
    action: ask_human
    message: "SSH to external host requires approval"

CLI Usage

# Quick validation
agentguard check '{"action": "read", "target": "users"}'

# File validation with policy
agentguard validate response.json --policy prod.yaml -v

# Policy file validation
agentguard policy validate policies/prod.yaml

Distribution

AI Output Guard can be used in 5 ways, covering every scenario:

Form	Use Case	Integration
Python SDK	Agent frameworks (LangChain, AutoGen, etc.)	2 lines of code
CLI	CI/CD pipelines, shell scripts	Zero intrusion
MCP Server	Cursor, Copilot, Claude Code, Windsurf	IDE plugin config
API Proxy	Any LLM API call (zero code changes)	Set HTTP_PROXY
VS Code Extension	Editor-native diagnostics	Install from marketplace

API Proxy — One-Click Deploy

# Docker deployment
docker run -d -p 8080:8080 \
  -v $(pwd)/policy.yaml:/policies/policy.yaml \
  -e AGENTGUARD_POLICY=/policies/policy.yaml \
  ai-output-guard/proxy:latest

# Client config (zero code)
export HTTP_PROXY=http://localhost:8080
export HTTPS_PROXY=http://localhost:8080
# All LLM API calls are now validated by AI Output Guard

Project Structure

agentguard/
├── src/agentguard/
│   ├── guard.py           # Main orchestrator (three-layer pipeline)
│   ├── schema_guard.py    # Schema validation + auto-fix
│   ├── semantic_guard.py  # Intent detection (rules)
│   ├── policy_guard.py    # YAML DSL policy engine
│   ├── result.py          # GuardLevel / CheckResult / GuardResult
│   ├── config.py          # Configuration management
│   ├── errors.py          # Exception hierarchy
│   ├── fix/               # Auto-fix (enum/type/schema recursive)
│   ├── semantic/          # Intent registry + rule matcher
│   ├── policy/            # Policy engine (actions/operators/parser/validator)
│   ├── audit/             # Audit logging
│   ├── cli/               # Typer CLI (Rich formatting)
│   ├── api/               # FastAPI REST API (validate/policy/audit/billing)
│   ├── proxy/             # API Proxy (zero-intrusion LLM safety layer)
│   ├── mcp/               # MCP Server (JSON-RPC 2.0 protocol)
│   └── billing/           # Subscription management (Lemon Squeezy)
├── lsp/                   # VS Code extension (TypeScript)
├── dashboard/             # Web Dashboard (Vue 3 + FastAPI)
├── docs/                  # Architecture, API reference, policy templates
├── examples/              # Demo + policy examples
├── tests/                 # 479+ test cases
├── Dockerfile             # API Proxy Docker image
├── docker-compose.yml     # One-command team deployment
└── pyproject.toml

Roadmap

Phase	Content	Status
Phase 1	Python SDK + CLI + Tests	✅ Complete
Phase 2	MCP Server (IDE integration)	✅ Complete
Phase 2.5	Schema Guard Enhancement (nested fix, advanced coercion, matching)	✅ Complete
Phase 3	API Proxy (zero-intrusion)	✅ Complete
Phase 3b	VS Code Extension (editor diagnostics)	✅ Complete
Phase 4	Dashboard + PyPI Release + Billing	✅ Complete

Pricing

Tier	Price	Features
Community	Free	SDK + CLI + MCP + LSP + Basic policies
Team	$29/month	API Proxy + Dashboard + Team policies + Audit export
Enterprise	Contact us	SSO/SAML + Custom deployment + SLA + Priority support

Support Us

If AI Output Guard is useful to you, please give us a ⭐!

License

MIT