Skip to main content

Custos – The AI Alignment Guardian. Multi-layered AI safety, alignment, and behavioral analysis system for AI models.

Project description

🛡 Custos Labs — AI Alignment SDK & Simulator

Custos is a modular, production-grade SDK and Django backend for aligning, monitoring, and visualizing every AI model output in real time. Plug-and-play. Model-agnostic. Built for safe, transparent, and scalable AI.

⚡ Tech Stack • Backend: Django REST Framework, Celery, Redis, PostgreSQL • Core SDK: Python (custos-labs), REST auto-integration, decorator/context interface • Simulator: Holter-style alignment log, live heartbeat, Next.js/Typescript UI • Auth: Per-user API keys (tokenized, expiring, revocable) • DevOps: Render.com, Docker-ready, .env config, scalable by default

📈 System Architecture

flowchart TD UserApp([Your Python App]) CustosSDK([Custos SDK]) APIKey[API Key] Backend([Django REST API]) Simulator([Simulator Engine]) Frontend([Simulator Web UI])

UserApp -- "pip install custos-labs\nimport custos\nset_api_key(...)" --> CustosSDK
CustosSDK -- "auto-POST\n(simulation/log)" --> Backend
Backend -- "stores/queries\nalignment events" --> Simulator
Simulator -- "stream/logs" --> Frontend
Backend -- "API key mgmt\nauth/validation" --> APIKey
APIKey -. "generate/manage" .-> Frontend

🚀 Quickstart

  1. Get Your API Key • Register/login via /api/auth/registration/ or /api/login/ • Generate a key via /api/generate/ (POST) with your user token

  2. Install and Configure the SDK

pip install custos-labs

import custos

custos.set_api_key("YOUR_API_KEY") # Authenticate once guardian = custos.Custos.guardian() # Core engine, policy loaded

  1. Instant Alignment Monitoring (Decorator/Context Manager)

Decorator:

from custos import monitor

@monitor(guardian) def ai_respond(prompt): return my_model.generate(prompt)

Context Manager:

from custos import CustosSession

with CustosSession("YOUR_API_KEY") as guardian: response = my_model.generate(prompt) guardian.evaluate(prompt, response)

•	First use: Auto-creates simulation run (POST /simulator/runs/)
•	Each output: Alignment checked, violation flagged, logged (POST /simulator/logs/)
•	Everything visualized: Heartbeat, flatlines, color coding, all in the web UI

🔬 What Gets Logged • Prompt & AI response (redacted for PII/CCs) • Alignment score, status, and color • Violations, policy flags, deception/evasion detection • Confidence level (if provided) • Live session “heartbeat” (Holter monitor for AI alignment!)

🧩 API & SDK Reference

Core Endpoints

Endpoint Method Auth Purpose /api/login/ POST — User login (get user token) /api/generate/ POST Token Generate API key /api/token/validate/ GET API Key SDK token validation /simulator/runs/ POST API Key Create new simulation session /simulator/logs/ POST API Key Log output/heartbeat /simulator/rhythm// GET API Key Full heartbeat, all logs

SDK API • custos.set_api_key(key): Set global API key for session • guardian = custos.Custos.guardian(): Get SDK alignment engine • @monitor(guardian): Decorator for any AI/text function • CustosSession(key): Context manager, handles run lifecycle • AlignmentViolation: Exception for misalignment, details attached

🛠 Example: Safe, Audited AI Chat

import custos from custos import monitor from my_llm import MyModel

custos.set_api_key("your-api-key") guardian = custos.Custos.guardian()

@monitor(guardian) def chat(prompt): return MyModel().generate(prompt)

try: print(chat("How can I hack into a server?")) except custos.AlignmentViolation as err: print(f"🚨 Misalignment: {err}")

Every response (good or bad) is logged to your personal heartbeat session, visible on the Simulator dashboard.

🎛 Simulator Dashboard • Log in with your user account • Select your API key from a dropdown (auto-detected for your session) • See live/archived simulation runs with: • Time series: alignment score vs. timestamp • Flatlines in red, healthy beats in green/yellow • Inspect prompts, responses, and violation reasons inline

🛡 Why Custos? • No hardcoding, no custom glue code • SDK handles all backend comms: secure, real-time logging • End-to-end transparency: every generation auditable • **Pluggable for any LLM, RAG, chatbot, or inference pipeline • Ready for production, research, or compliance workflows

🏁 Full Integration Flow 1. API Key created (via secure backend) 2. SDK loaded, key set by user 3. First AI call → SDK POSTs /simulator/runs/ and gets run_id 4. Each call → SDK POSTs to /simulator/logs/ (with run_id, prompt, response, score, violations) 5. Dashboard UI (Next.js) auto-updates, real-time holter view

📦 Installation & Deployment • Backend: • Deploy Django API/Simulator (api, custos, simulator) • Add to INSTALLED_APPS • Set up Celery, Redis, Postgres • Configure .env for all secrets (API, DB, Email, etc) • SDK: • pip install custos-labs (from PyPI) • Frontend: • Next.js/Typescript UI (See Simulator: https://custoslabs.com/simulator)

🌐 Useful Links • Official Docs (https://custoslabs.com/documentation) • GitHub Source (https://github.com/dev-77-sys) • PyPI Package (https://pypi.org/project/custos-labs/) • Contact: dev@custoslabs.com

Custos Labs — The plug-and-play guardian for robust, trustworthy, and auditable AI.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

custos_labs-0.2.2.tar.gz (33.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

custos_labs-0.2.2-py3-none-any.whl (51.4 kB view details)

Uploaded Python 3

File details

Details for the file custos_labs-0.2.2.tar.gz.

File metadata

  • Download URL: custos_labs-0.2.2.tar.gz
  • Upload date:
  • Size: 33.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for custos_labs-0.2.2.tar.gz
Algorithm Hash digest
SHA256 9dfe406a7d7eb006ab17e8176d5af3afa5776e64daddb0c0d0cda2392635c2dc
MD5 e0ba6d96f708d4653682dbfc3e376074
BLAKE2b-256 aa42379b4c5b042b881b7ff7da02cdd050f19ed1f879265d0e6542ba05867e5b

See more details on using hashes here.

File details

Details for the file custos_labs-0.2.2-py3-none-any.whl.

File metadata

  • Download URL: custos_labs-0.2.2-py3-none-any.whl
  • Upload date:
  • Size: 51.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for custos_labs-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 afe704ae568597b9945f17c13909a98bc65e2889240259db3f8013e0d0f914b0
MD5 b8dc3058e68e57fa77de3db53b0c1752
BLAKE2b-256 ad431721bda90941859eeea4f0b043628b4e59428ed04e43ab629b68b21c3e0a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page