Modern Agent Management, Version Control & Orchestration Framework
Project description
🌠 AgentComet
Build once. Run anywhere. Resume anytime.
Stateful. Portable. Composable AI agents.
⚡ The Problem
Every AI team ends up rebuilding the same agents.
Same logic. Same tools. Different environment. New framework.
And the worst part? All the memory, context, and progress is lost. Agents today are stateless, fragile, and non-portable.
🚀 Introducing AgentComet
AgentComet is a modern agent framework designed to make agents:
- Stateful by default
- Portable across environments
- Resumable at any point in time
Instead of treating agents like scripts, AgentComet treats them like artifacts.
🎯 What makes AgentComet different?
AgentComet introduces a new primitive: Portable, Stateful Agent Artifacts (.uaf)
You don't just write agents. You package, move, version, and resume them.
🚀 Quick Start
Installation
pip install agentcomet
Build an Agent
Create an agent, assign it custom tools, and let it handle the heavy lifting.
from agentcomet import Agent, tool
from agentcomet.models import Ollama
@tool
def greet(name: str) -> str:
return f"Hello, {name}!"
class GreeterAgent(Agent):
def setup(self):
self.name = "greeter"
self.add_tools(greet)
# Instantiate and chat
agent = GreeterAgent(llm=Ollama(model="llama3"))
print(agent.run("Say hello to Alice!"))
✨ Core Capabilities
🧠 Persistent Memory
Every agent comes with a highly flexible key-value memory store (self.memory). Conversational history is auto-saved without any manual boilerplate.
agent.memory.save("user_preferences", {"theme": "dark"})
print(agent.memory.get("messages"))
💾 State Checkpoints
Save and restore exact agent timelines. Need to rollback a prompt mistake? Just load the state.
agent.save_state("checkpoint-1")
agent.load_state("checkpoint-1")
📦 Portable Agents with .uaf
Stop writing boilerplate to serialize agent code. Export your entire agent—along with its memory, history, LLM config, and tools—into a portable .uaf archive.
agent.export("assistant.uaf")
from agentcomet import load_agent
agent = load_agent("assistant.uaf")
☁️ Local Registry (Push & Pull)
Sync your agents with a locally hosted AgentComet Studio registry. Version, share, and pull agents across your team — like git, but for agents.
1. Start AgentComet Studio
docker pull vaibhavhaswani/agentcomet-studio:latest
docker run -p 3451:3451 \
-v $(pwd)/data:/app/data \
vaibhavhaswani/agentcomet-studio:latest
Windows (PowerShell):
docker run -p 3451:3451 -v ${PWD}/data:/app/data vaibhavhaswani/agentcomet-studio:latest
2. Configure the SDK
from agentcomet import Settings
Settings.init(
AGENTCOMET_LOCAL_URL="http://localhost:3451",
AGENTCOMET_LOCAL_KEY="your-secret-key"
)
Or set environment variables:
export AGENTCOMET_LOCAL_URL=http://localhost:3451
export AGENTCOMET_LOCAL_KEY=your-secret-key
3. Push & Pull
# Push — auto-increments version
agent.push_local()
# Pull — latest or specific version
agent = Agent.pull_local("greeter")
agent = Agent.pull_local("greeter", version="0.1.2")
🔌 Multi-Provider LLM Support
Switching your backend is as simple as defining a new class.
from agentcomet.models import OpenAIChat, Gemini, Anthropic, Ollama
agent.use_llm(OpenAIChat(model="gpt-4o"))
🧠 Why this matters
We believe the future of AI is not just models. It's agents that evolve over time.
Agents that:
- Learn
- Persist
- Move
- Continue
AgentComet is a step toward that future.
🛣️ Vision
This is just the beginning.
AgentComet is part of a larger vision to build:
- A universal agent format
- A global agent registry
- A composable ecosystem of agents
Where agents are not rewritten, but shared, reused, and extended.
📚 Documentation
For a detailed look at all features, API methods, schemas, and configurations, check out the comprehensive Usage Documentation.
🤝 Contributing
- ⭐ Star the repo
- 🛠️ Break things
- 🚀 Open PRs
All contributions are welcome.
📄 License & Legal
- License: Apache License 2.0
- Patent: Indian Provisional Patent Application No. 202611013684
- Branding: "AgentComet" is a trademark. See BRANDING.md.
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