adjusted migration

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

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More on PES

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wip

Wip

minor

PW interactions

API PES

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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

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bb4g/__init__.py

@@ -0,0 +1,183 @@
+import json
+import math
+from datetime import datetime
+from typing import List
+import enum
+import requests
+from django.conf import settings as s
+from envipy_additional_information import EnviPyModel, UIConfig, WidgetType
+from envipy_additional_information import register
+
+from bridge.contracts import Classifier  # noqa: I001
+from bridge.dto import (
+    BuildResult,
+    EnviPyDTO,
+    EvaluationResult,
+    RunResult,
+    TransformationProductPrediction,
+)  # noqa: I001
+
+class SamplingAlgorithm(enum.Enum):
+    EXACT = "exact"
+
+
+@register("bb4gconfig")
+class BB4GConfig(EnviPyModel):
+    sampling_algorithm: SamplingAlgorithm = SamplingAlgorithm.EXACT
+    cutoff: int = -5
+
+    class UI:
+        title = "BB4G Configuration"
+        sampling_algorithm = UIConfig(
+            widget=WidgetType.SELECT,
+            label="BB4G Sampling Algorithm",
+            order=1,
+            placeholder="If unset defaults to 'exact'"
+        )
+        cutoff = UIConfig(
+            widget=WidgetType.NUMBER,
+            label="BB4G Cutoff",
+            order=2,
+            placeholder="If unset defaults to -5"
+        )
+
+
+# Once stable these will be exposed by enviPy-plugins lib
+class BB4G(Classifier):
+    Config = BB4GConfig
+
+    def __init__(self, config: BB4GConfig | None = None):
+        super().__init__(config)
+        self.url = f"{s.BB4G_URL}"
+
+        self.token = self.acquire_token()
+        self.header = {
+            "Authorization": f"Bearer {self.token}",
+            "Content-Type": "application/json",
+        }
+
+    def acquire_token(self):
+        BB4G_TENANT_ID = s.BB4G_TENANT_ID
+        BB4G_CLIENT_ID = s.BB4G_CLIENT_ID
+        BB4G_CLIENT_SECRET = s.BB4G_CLIENT_SECRET
+        BB4G_SCOPE = s.BB4G_SCOPE
+
+        BB4G_TOKEN_URL = f"https://login.microsoftonline.com/{BB4G_TENANT_ID}/oauth2/v2.0/token"
+
+        payload = {
+            "client_id": BB4G_CLIENT_ID,
+            "client_secret": BB4G_CLIENT_SECRET,
+            "scope": BB4G_SCOPE,
+            "grant_type": "client_credentials"
+        }
+
+        # No Proxy required, URL is whitelisted
+        res = requests.post(BB4G_TOKEN_URL, data=payload)
+
+        res.raise_for_status()
+
+        return res.json()["access_token"]
+
+    def start(self):
+        header = {
+            "Authorization": f"Bearer {self.token}",
+            "Content-Type": "application/json",
+        }
+
+        started = False
+        retries = 0
+        while not started and retries < 5:
+            res = requests.post(f"{self.url}/start", headers=header, data={}, proxies=s.PROXIES or None)
+
+            if res.status_code == 200:
+                started = True
+            elif res.status_code in [500, 502]:
+                retries += 1
+                import time
+                time.sleep(5)
+            else:
+                raise ValueError(f"Unexpected status code: {res.status_code}")
+
+    @classmethod
+    def requires_rule_packages(cls) -> bool:
+        return False
+
+    @classmethod
+    def requires_data_packages(cls) -> bool:
+        return False
+
+    @classmethod
+    def identifier(cls) -> str:
+        return "bb4g"
+
+    @classmethod
+    def name(cls) -> str:
+        return "BB4G Template Free Model"
+
+    @classmethod
+    def display(cls) -> str:
+        return "BB4G Template Free Model"
+
+    def build(self, eP: EnviPyDTO, *args, **kwargs) -> BuildResult | None:
+        return
+
+    def run(self, eP: EnviPyDTO, *args, **kwargs) -> RunResult:
+
+        # Ensure Service is running
+        self.start()
+
+        smiles = [c.smiles for c in eP.get_compounds()]
+        preds = self._post(smiles)
+
+        results = []
+
+        for substrate in preds.keys():
+            results.append(
+                TransformationProductPrediction(
+                    substrate=substrate,
+                    products=preds[substrate],
+                )
+            )
+
+        return RunResult(
+            producer=eP.get_context().url,
+            description=f"Generated at {datetime.now()}",
+            result=results,
+        )
+
+    def evaluate(self, eP: EnviPyDTO, *args, **kwargs) -> EvaluationResult:
+        pass
+
+    def build_and_evaluate(self, eP: EnviPyDTO, *args, **kwargs) -> EvaluationResult:
+        pass
+
+    def _post(self, smiles: List[str]) -> dict[str, dict[str, float]]:
+        header = {
+            "Authorization": f"Bearer {self.token}",
+            "Content-Type": "application/json",
+        }
+
+        result = {}
+
+        for smi in smiles:
+            data = {
+                "smiles": smi,
+                "sampling_alg": self.config.sampling_algorithm.value,
+                "cutoff": self.config.cutoff,
+            }
+
+            resp = requests.post(f"{self.url}/compute", headers=header, data=json.dumps(data), proxies=s.PROXIES or None)
+
+            resp.raise_for_status()
+
+            for substrate, predictions in resp.json().items():
+                preds = {}
+
+                for pred in predictions:
+                    prod = pred["prediction"]
+                    prob = math.exp(pred["log_likelihood"])
+                    preds[prod] = prob
+
+                result[substrate] = preds
+
+        return result