No project description provided
Project description
Neurion Ganglion - Ion Framework
Overview
Neurion Ganglion provides a framework for defining, deploying, and managing Ions – decentralized computational units that operate within the Neurion ecosystem. This repository offers a streamlined way to create and register Ions, either as self-hosted services or pre-existing services ready for registration.
Features
- Define input and output schemas using Pydantic.
- Register Ions with Neurion automatically or manually.
- Health-check endpoints for ensuring service availability.
- Auto-recovery mechanism for self-hosted Ions.
- Easy-to-use decorators for defining execution logic.
- Integrated Ganglion Server for managing pathways and processing Ion calls.
- Support for both localnet and alpha testnet environments.
Installation
pip install neurion-ganglion
Network Configuration
Neurion supports multiple networks. Initialize a network configuration before using Ganglion or Ions:
from neurionpy.synapse.config import NetworkConfig
# Choose the appropriate network
config = NetworkConfig.neurion_localnet() # For local development
# config = NetworkConfig.neurion_alpha_testnet() # For testnet
Creating an Ion
You can create an Ion in two different ways:
1. Self-Hosting Ion (Auto-Registering)
This mode runs the Ion server locally and automatically registers it with Neurion.
from pydantic import BaseModel
from neurion_ganglion.ion.ion import Ion, ion_handler
from neurion_ganglion.custom_types.capacity import Capacity
from neurionpy.synapse.config import NetworkConfig
config = NetworkConfig.neurion_localnet() # Set network config
# Define Input Schema
class MyInputSchema(BaseModel):
task_id: str
parameters: int
# Define Output Schema
class MyOutputSchema(BaseModel):
message: str
result: float
# Use decorator to attach schemas
@ion_handler(MyInputSchema, MyOutputSchema)
def my_ion_handler(data: MyInputSchema) -> MyOutputSchema:
return MyOutputSchema(message="Success", result=12)
# Start Ion Server
if __name__ == "__main__":
description = "My custom Ion server"
stake = 20000000
fee_per_thousand_calls = 1
capacities = [Capacity.SCRAPER, Capacity.AI_AGENT]
Ion.create_self_hosting_ion(config, description, stake, fee_per_thousand_calls, capacities, my_ion_handler).start()
2. Starting a Pure Ion Server & Registering it
If you want to set up multiple backend Ion servers and manually register them, you can start a pure Ion server first, note its public IP, and then use the registration function.
Step 1: Start the Pure Ion Server
from neurion_ganglion.ion.ion import Ion
from pydantic import BaseModel
from neurionpy.synapse.config import NetworkConfig
config = NetworkConfig.neurion_localnet() # Set network config
# Define Input Schema
class MyInputSchema(BaseModel):
task_id: str
parameters: int
# Define Output Schema
class MyOutputSchema(BaseModel):
message: str
result: float
@ion_handler(MyInputSchema, MyOutputSchema)
def my_ion_handler(data: MyInputSchema) -> MyOutputSchema:
return MyOutputSchema(message="Success", result=12)
# Start a pure Ion server
if __name__ == "__main__":
Ion.start_pure_ion_server(config, my_ion_handler)
Step 2: Manually Register the Running Ion Server
Once the pure Ion server is running, note its IP address and use the following script to register it:
from neurion_ganglion.ion.ion import Ion
from neurion_ganglion.custom_types.capacity import Capacity
from neurionpy.synapse.config import NetworkConfig
config = NetworkConfig.neurion_localnet() # Set network config
description = "My external Ion server"
stake = 20000000
fee_per_thousand_calls = 1
capacities = [Capacity.SCRAPER, Capacity.AI_AGENT]
endpoints = ["http://<noted-public-ip>:8000"] # Replace <noted-public-ip> with actual IP
Ion.create_server_ready_ion(config, description, stake, fee_per_thousand_calls, capacities, MyInputSchema, MyOutputSchema, endpoints).register_ion()
Using Pathways
A Pathway defines a structured flow between multiple Ions.
from neurion_ganglion.ion.pathway import Pathway
from neurionpy.synapse.config import NetworkConfig
config = NetworkConfig.neurion_localnet() # Set network config
# Initialize Pathway by ID
pathway = Pathway.of_id(config, 1)
# Call Pathway
response = pathway.call({"task_id": "1234", "parameters": 100})
print(response)
Ganglion Server
The Ganglion Server handles requests, routing them to the appropriate Ion or Pathway.
from neurion_ganglion.ganglion.server import GanglionServer
from neurionpy.synapse.config import NetworkConfig
config = NetworkConfig.neurion_localnet() # Set network config
# Start Ganglion Server
GanglionServer.start(config)
Health Check
All Ions expose a /health endpoint that can be used to check their availability.
curl http://localhost:8000/health
License
This project is licensed under the MIT License.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file neurion_ganglion-0.4.0.tar.gz.
File metadata
- Download URL: neurion_ganglion-0.4.0.tar.gz
- Upload date:
- Size: 15.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.1 CPython/3.9.21 Linux/6.8.0-1021-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
133a436d2da28cd357530a2015350b37f02990aab96aee4d9fb72443c09a8814
|
|
| MD5 |
2620bca64b8dab7cb509e1c1c7b9e7d9
|
|
| BLAKE2b-256 |
ed7c41a9e6128ff0d04ac94a5eb87bd1f8c9fe381affbe96fbdde0e625d2511b
|
File details
Details for the file neurion_ganglion-0.4.0-py3-none-any.whl.
File metadata
- Download URL: neurion_ganglion-0.4.0-py3-none-any.whl
- Upload date:
- Size: 20.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.1 CPython/3.9.21 Linux/6.8.0-1021-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
74bac3077f9503cf838b4ae76df036ffb916a38a63e80f2165032d6009b34d5b
|
|
| MD5 |
610ae7da3def1de0a03360b95adb7c84
|
|
| BLAKE2b-256 |
ee5fa9f678d40cb346731e1cede920023832d9deec8c93b2f33e479e45d79ae6
|