Learn how to interact with this route using the Ouro SDK or REST API.
API access requires an API key. Create one in Settings → API Keys, then set OURO_API_KEY in your environment.
Parameters and request body schema for this route.
Get route metadata including name, visibility, description, and endpoint details. You can retrieve by route ID or identifier.
Execute the route endpoint with request body, query parameters, path parameters, or asset IDs.
Get the request and response history for this route. Actions are especially useful for long-running routes where you can poll the status and retrieve the response when ready.
import os
from ouro import Ouro
# Set OURO_API_KEY in your environment or replace os.environ.get("OURO_API_KEY")
ouro = Ouro(api_key=os.environ.get("OURO_API_KEY"))
# Option 1: Retrieve by route ID
route_id = "c1708d4f-eeea-4de0-ba41-c185b878b804"
route = ouro.routes.retrieve(route_id)
# Option 2: Retrieve by route identifier (username/route-name)
route_identifier = "mmoderwell/crystal-likeness-score-synthesizability-from-cif"
route = ouro.routes.retrieve(route_identifier)
print(route.name, route.visibility)
print(route.metadata)# Retrieve the route
route = ouro.routes.retrieve("mmoderwell/crystal-likeness-score-synthesizability-from-cif")
# Execute the route
action = route.execute(
assets={
'CIF file': 'your-file-id'
},
)
print(action.final_data)# Retrieve the route
route = ouro.routes.retrieve("mmoderwell/crystal-likeness-score-synthesizability-from-cif")
# Read all actions (request/response history) for this route
actions = route.read_actions()
print(actions)
# Actions are especially useful for long-running routes
# You can poll the status and retrieve the response when ready
for action in actions:
print(f"Action ID: {action['id']}")
print(f"Status: {action['status']}")
print(f"Response: {action.get('response_data')}")Run the Jang et al. PU-CGCNN ensemble on a CIF and return the Crystal-Likeness Score (CLscore). Values near 1 look like known synthesizable crystals; near 0 look unlike them. Typical screening thresholds in the literature are around 0.5–0.7.
Execution
Usage
26 callsView historyPU-CGCNN validation: experimental crystals vs high-e_hull theoreticals
Spot-check of PU-CGCNN on 10 experimentally known vs 10 high-e_hull theoretical Materials Project structures. Directional separation, real overlap, and some surprising misses (LiFePO₄, AgC₂N₃).
Will it actually form? Predicting crystal synthesizability with PU-CGCNN
An explainer for the new Crystal-Likeness Score (PU-CGCNN) service: what the CLscore means, how positive–unlabeled learning works, and when to use it in a screening pipeline.