OpenForgeAI
Open-source agentic architecture for production systems.
Built by one person. Running in production. Now open-source.
What Is This?
OpenForgeAI is the architecture framework extracted from Saarathi — a production AI-native platform built by a solo founder that competes with funded teams.
It provides the patterns you need to build systems where AI agents work as a real team: communicating via events, orchestrating multi-step workflows, and self-registering their capabilities.
This isn't a toy. These patterns run in production handling real users, real payments, and real-time messaging.
Core Components
EventBus — Agent Communication
A pub/sub event system where agents subscribe to events, emit new ones, and react autonomously. No direct function calls between agents.
from openforgeai.events import EventBus, Event
bus = EventBus()
bus.register_agent(my_agent) # Agent subscribes to events it handles
await bus.publish(OrderCreated(order_id="123")) # All subscribers react
Skill Registry — Agent Discovery
Auto-discovery and registration of agent skills. Drop a new skill file, it registers itself.
from openforgeai.agents import SkillRegistry
registry = SkillRegistry()
registry.discover("./skills/") # Auto-finds all skills
registry.initialize(tenant_id="abc") # Creates instances, wires EventBus
Saga Coordinators — Multi-Step Orchestration
Event-driven state machines for complex workflows. Each step completes on event arrival, not await calls.
from openforgeai.sagas import SagaCoordinator
class OnboardingSaga(SagaCoordinator):
steps = ["send_welcome", "create_profile", "notify_team"]
# Each step emits an event → next step triggers on completion event
Workflow Engine — Visual Process Automation
Define workflows as node graphs. Delay nodes, condition nodes, action nodes — all executing via the EventBus.
Deploy Validator — Pre-Deploy Safety
Catches broken imports, missing agent registrations, and compliance violations before you deploy.
python -m openforgeai.validators.deploy_check
# ✓ All skills imported
# ✓ All events have subscribers
# ✓ No orphan handlers
The 17 Laws of Agentic Engineering
The methodology behind the architecture. Read the full guide →
| # | Law | One-liner |
|---|---|---|
| 1 | Contracts have handlers | Every event type must have a subscriber |
| 2 | Coordinators emit, never call | No direct skill.execute() from coordinators |
| 3 | Sagas track via events | Steps complete on event arrival |
| 4 | No orphan events | Every emitted event must have a subscriber |
| 5 | Search before create | Check existing code before building new |
| 6 | PRD before code | Spec first, understand why, then build |
| 7 | Verify before done | Run checks, show output |
| 14 | Imports are code | Every symbol used must be imported |
| 15 | Match the API | Read method signature before calling |
| 16 | Definition of done | Imports ✓ Signatures ✓ Required fields ✓ Actually runs ✓ |
| 17 | Verify interfaces before use | Read model definition → validate locally → smoke test |
Quick Start
pip install openforgeai
from openforgeai import EventBus, BaseAgent, Event
# Define an event
class TaskCreated(Event):
task_id: str
title: str
# Define an agent
class NotificationAgent(BaseAgent):
consumes_events = [TaskCreated]
async def on_task_created(self, event: TaskCreated):
print(f"New task: {event.title}")
# Wire it up
bus = EventBus()
agent = NotificationAgent()
bus.register_agent(agent)
await bus.publish(TaskCreated(task_id="1", title="Ship it"))
# Output: New task: Ship it
Who Is This For?
- Solo founders building production SaaS without a team
- Startup CTOs who want 10X team output with agentic patterns
- Senior engineers transitioning to AI-native architecture
- Anyone tired of AI demos that break in production
Learn More
- The 17 Laws of Agentic Engineering
- Architecture Guide
- CLAUDE.md Template — Drop this into any project
- Session Protocol — How to manage AI collaboration
The Story
I built Saarathi — an AI-native platform with real-time WhatsApp nurturing, automated webinar funnels, payment processing, CRM, and 14 AI agent skills working as a team. One person. Zero employees. Production-deployed. Real revenue.
The secret isn't "AI writes my code." The secret is architecture.
When your codebase is spaghetti, AI is a liability. When your codebase has clean contracts — EventBus, saga coordinators, skill registries — AI becomes a genuine team member.
Software engineering isn't dead. It's reinvented.
License
MIT — Use it, fork it, build with it.
Links
- Website: openforgeai.com
- GitHub: github.com/openforgeai
- Author: Goutam Biswas
Metadata
Release files for openforgeai 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| openforgeai-0.1.0.tar.gz | 17.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| openforgeai-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 35.7 kB
Release files / openforgeai-0.1.0.tar.gz
| Download URL | openforgeai-0.1.0.tar.gz |
|---|---|
| Size | 17.7 kB |
| Tags | Source |
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Release files / openforgeai-0.1.0-py3-none-any.whl
| Download URL | openforgeai-0.1.0-py3-none-any.whl |
|---|---|
| Size | 17.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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