forked from enviPath/enviPy
Initial bayer app Show Pack Classification Adjusted docker compose to bayer specifics Adjusted Dockerfile for Bayer Adding secret flags to group, add secret pools to packages Adjusted View for Package creation Prep configs, added Package Create Modal wip More on PES wip wip Wip minor PW interactions API PES wip Make Select Widget reflect required make required generallay available Update UI if pathway mode is set to build Added ais circle adjustments Initial Zoom, fix AD Creation wip auth log, bb4g fix missing import Added viz hint if PES is part of reaction Add Edge check for pes flip boolean ... pes Added extra ... In / Out Edges Viz, Submitting Button Text ...
199 lines
5.4 KiB
Python
199 lines
5.4 KiB
Python
import enum
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import json
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import logging
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import math
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from datetime import datetime
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from typing import List
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import requests
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from django.conf import settings as s
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from envipy_additional_information import register, EnviPyModel, UIConfig, WidgetType
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from bridge.contracts import Classifier # noqa: I001
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from bridge.dto import (
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BuildResult,
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EnviPyDTO,
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EvaluationResult,
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RunResult,
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TransformationProductPrediction,
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) # noqa: I001
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logger = logging.getLogger("epdb")
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class SamplingAlgorithm(enum.Enum):
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EXACT = "exact"
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@register("bb4gconfig")
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class BB4GConfig(EnviPyModel):
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sampling_algorithm: SamplingAlgorithm = SamplingAlgorithm.EXACT
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cutoff: int = -5
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class UI:
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title = "BB4G Configuration"
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sampling_algorithm = UIConfig(
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widget=WidgetType.SELECT,
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label="BB4G Sampling Algorithm",
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order=1,
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placeholder="If unset defaults to 'exact'"
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)
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cutoff = UIConfig(
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widget=WidgetType.NUMBER,
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label="BB4G Cutoff",
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order=2,
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placeholder="If unset defaults to -5"
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)
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# Once stable these will be exposed by enviPy-plugins lib
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class BB4G(Classifier):
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Config = BB4GConfig
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def __init__(self, config: BB4GConfig | None = None):
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super().__init__(config)
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self.url = f"{s.BB4G_URL}"
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self.token = self.acquire_token()
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self.header = {
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"Authorization": f"Bearer {self.token}",
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"Content-Type": "application/json",
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}
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def acquire_token(self):
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BB4G_TENANT_ID = s.BB4G_TENANT_ID
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BB4G_CLIENT_ID = s.BB4G_CLIENT_ID
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BB4G_CLIENT_SECRET = s.BB4G_CLIENT_SECRET
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BB4G_SCOPE = s.BB4G_SCOPE
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BB4G_TOKEN_URL = f"https://login.microsoftonline.com/{BB4G_TENANT_ID}/oauth2/v2.0/token"
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payload = {
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"client_id": BB4G_CLIENT_ID,
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"client_secret": BB4G_CLIENT_SECRET,
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"scope": BB4G_SCOPE,
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"grant_type": "client_credentials"
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}
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# No Proxy required, URL is whitelisted
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res = requests.post(BB4G_TOKEN_URL, data=payload)
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res.raise_for_status()
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return res.json()["access_token"]
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def start(self):
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header = {
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"Authorization": f"Bearer {self.token}",
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"Content-Type": "application/json",
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}
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started = False
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while not started:
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res = requests.post(f"{self.url}/start", headers=header, data={}, proxies=s.PROXIES or None)
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logger.info(f"Starting BB4G: {res.status_code}")
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if res.status_code == 200:
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started = True
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elif res.status_code in [500, 502]:
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import time
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time.sleep(5)
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else:
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raise ValueError(f"Unexpected status code: {res.status_code}")
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@classmethod
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def requires_rule_packages(cls) -> bool:
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return False
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@classmethod
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def requires_data_packages(cls) -> bool:
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return False
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@classmethod
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def identifier(cls) -> str:
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return "bb4g"
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@classmethod
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def name(cls) -> str:
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return "BB4G Template Free Model"
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@classmethod
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def display(cls) -> str:
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return "BB4G Template Free Model"
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def build(self, eP: EnviPyDTO, *args, **kwargs) -> BuildResult | None:
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return
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def run(self, eP: EnviPyDTO, *args, **kwargs) -> RunResult:
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# Ensure Service is running
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self.start()
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smiles = [c.smiles for c in eP.get_compounds()]
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preds = self._post(smiles)
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results = []
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for substrate in preds.keys():
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results.append(
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TransformationProductPrediction(
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substrate=substrate,
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products=preds[substrate],
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)
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)
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return RunResult(
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producer=eP.get_context().url,
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description=f"Generated at {datetime.now()}",
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result=results,
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)
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def evaluate(self, eP: EnviPyDTO, *args, **kwargs) -> EvaluationResult:
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pass
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def build_and_evaluate(self, eP: EnviPyDTO, *args, **kwargs) -> EvaluationResult:
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pass
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def _post(self, smiles: List[str]) -> dict[str, dict[str, float]]:
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header = {
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"Authorization": f"Bearer {self.token}",
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"Content-Type": "application/json",
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}
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result = {}
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for smi in smiles:
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data = {
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"smiles": smi,
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"sampling_alg": self.config.sampling_algorithm.value,
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"cutoff": self.config.cutoff,
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}
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retries = 0
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while retries < 100:
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resp = requests.post(f"{self.url}/compute", headers=header, data=json.dumps(data),
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proxies=s.PROXIES or None)
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if resp.status_code == 418:
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retries += 1
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logger.info(f"BB4G predict hit a 418, retrying in 60 seconds")
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import time
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time.sleep(3)
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continue
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resp.raise_for_status()
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for substrate, predictions in resp.json().items():
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preds = {}
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for pred in predictions:
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prod = pred["prediction"]
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prob = math.exp(pred["log_likelihood"])
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preds[prod] = prob
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result[substrate] = preds
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break
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return result
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