[Feature] Basic logging of Jobs, Model Evaluation (#169)

Co-authored-by: Tim Lorsbach <tim@lorsba.ch>
Reviewed-on: enviPath/enviPy#169

epdb/management/commands/create_ml_models.py

@@ -114,6 +114,6 @@ class Command(BaseCommand):
             print(f"Training {model_name}")
             model.build_model()
             print(f"Evaluating {model_name}")
-            model.evaluate_model()
+            model.evaluate_model(False, eval_packages=eval_packages)
             print(f"Saving {model_name}")
             model.save()

epdb/management/commands/update_job_logs.py

@@ -0,0 +1,38 @@
+from datetime import date, timedelta
+
+from django.core.management.base import BaseCommand
+from django.db import transaction
+
+from epdb.models import JobLog
+
+
+class Command(BaseCommand):
+    def add_arguments(self, parser):
+        parser.add_argument(
+            "--cleanup",
+            type=int,
+            default=None,
+            help="Remove all logs older than this number of days. Default is None, which does not remove any logs.",
+        )
+
+    @transaction.atomic
+    def handle(self, *args, **options):
+        if options["cleanup"] is not None:
+            cleanup_dt = date.today() - timedelta(days=options["cleanup"])
+            print(JobLog.objects.filter(created__lt=cleanup_dt).delete())
+
+        logs = JobLog.objects.filter(status="INITIAL")
+        print(f"Found {logs.count()} logs to update")
+        updated = 0
+        for log in logs:
+            res = log.check_for_update()
+            if res:
+                updated += 1
+
+        print(f"Updated {updated} logs")
+
+        from django.db.models import Count
+
+        qs = JobLog.objects.values("status").annotate(total=Count("status"))
+        for r in qs:
+            print(r["status"], r["total"])

epdb/models.py

@@ -2225,10 +2225,18 @@ class PackageBasedModel(EPModel):
         self.model_status = self.BUILT_NOT_EVALUATED
         self.save()
 
-    def evaluate_model(self):
+    def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None):
         if self.model_status != self.BUILT_NOT_EVALUATED:
             raise ValueError(f"Can't evaluate a model in state {self.model_status}!")
 
+        if multigen:
+            self.multigen_eval = multigen
+            self.save()
+
+        if eval_packages is not None:
+            for p in eval_packages:
+                self.eval_packages.add(p)
+
         self.model_status = self.EVALUATING
         self.save()
 
@@ -2525,7 +2533,6 @@ class RuleBasedRelativeReasoning(PackageBasedModel):
         package: "Package",
         rule_packages: List["Package"],
         data_packages: List["Package"],
-        eval_packages: List["Package"],
         threshold: float = 0.5,
         min_count: int = 10,
         max_count: int = 0,
@@ -2574,10 +2581,6 @@ class RuleBasedRelativeReasoning(PackageBasedModel):
             for p in rule_packages:
                 rbrr.data_packages.add(p)
 
-        if eval_packages:
-            for p in eval_packages:
-                rbrr.eval_packages.add(p)
-
         rbrr.save()
 
         return rbrr
@@ -2632,7 +2635,6 @@ class MLRelativeReasoning(PackageBasedModel):
         package: "Package",
         rule_packages: List["Package"],
         data_packages: List["Package"],
-        eval_packages: List["Package"],
         threshold: float = 0.5,
         name: "str" = None,
         description: str = None,
@@ -2672,10 +2674,6 @@ class MLRelativeReasoning(PackageBasedModel):
             for p in rule_packages:
                 mlrr.data_packages.add(p)
 
-        if eval_packages:
-            for p in eval_packages:
-                mlrr.eval_packages.add(p)
-
         if build_app_domain:
             ad = ApplicabilityDomain.create(
                 mlrr,
@@ -2995,7 +2993,6 @@ class EnviFormer(PackageBasedModel):
     def create(
         package: "Package",
         data_packages: List["Package"],
-        eval_packages: List["Package"],
         threshold: float = 0.5,
         name: "str" = None,
         description: str = None,
@@ -3028,10 +3025,6 @@ class EnviFormer(PackageBasedModel):
         for p in data_packages:
             mod.data_packages.add(p)
 
-        if eval_packages:
-            for p in eval_packages:
-                mod.eval_packages.add(p)
-
         # if build_app_domain:
         #     ad = ApplicabilityDomain.create(mod, app_domain_num_neighbours, app_domain_reliability_threshold,
         #                                     app_domain_local_compatibility_threshold)
@@ -3144,10 +3137,18 @@ class EnviFormer(PackageBasedModel):
         args = {"clz": "EnviFormer"}
         return args
 
-    def evaluate_model(self):
+    def evaluate_model(self, multigen: bool, eval_packages: List["Package"] = None):
         if self.model_status != self.BUILT_NOT_EVALUATED:
             raise ValueError(f"Can't evaluate a model in state {self.model_status}!")
 
+        if multigen:
+            self.multigen_eval = multigen
+            self.save()
+
+        if eval_packages is not None:
+            for p in eval_packages:
+                self.eval_packages.add(p)
+
         self.model_status = self.EVALUATING
         self.save()
 
@@ -3671,3 +3672,53 @@ class Setting(EnviPathModel):
             self.public = True
         self.global_default = True
         self.save()
+
+
+class JobLogStatus(models.TextChoices):
+    INITIAL = "INITIAL", "Initial"
+    SUCCESS = "SUCCESS", "Success"
+    FAILURE = "FAILURE", "Failure"
+    REVOKED = "REVOKED", "Revoked"
+    IGNORED = "IGNORED", "Ignored"
+
+
+class JobLog(TimeStampedModel):
+    user = models.ForeignKey("epdb.User", models.CASCADE)
+    task_id = models.UUIDField(unique=True)
+    job_name = models.TextField(null=False, blank=False)
+    status = models.CharField(
+        max_length=20,
+        choices=JobLogStatus.choices,
+        default=JobLogStatus.INITIAL,
+    )
+
+    done_at = models.DateTimeField(null=True, blank=True, default=None)
+    task_result = models.TextField(null=True, blank=True, default=None)
+
+    def check_for_update(self):
+        async_res = self.get_result()
+        new_status = async_res.state
+
+        TERMINAL_STATES = [
+            "SUCCESS",
+            "FAILURE",
+            "REVOKED",
+            "IGNORED",
+        ]
+
+        if new_status != self.status and new_status in TERMINAL_STATES:
+            self.status = new_status
+            self.done_at = async_res.date_done
+
+            if new_status == "SUCCESS":
+                self.task_result = async_res.result
+
+            self.save()
+
+            return True
+        return False
+
+    def get_result(self):
+        from celery.result import AsyncResult
+
+        return AsyncResult(str(self.task_id))

epdb/tasks.py

@@ -1,10 +1,13 @@
 import logging
-from typing import Optional
+from datetime import datetime
-from celery.utils.functional import LRUCache
+from typing import Callable, Optional
-from celery import shared_task
+from uuid import uuid4
-from epdb.models import Pathway, Node, EPModel, Setting
-from epdb.logic import SPathway
 
+from celery import shared_task
+from celery.utils.functional import LRUCache
+
+from epdb.logic import SPathway
+from epdb.models import EPModel, JobLog, Node, Package, Pathway, Setting, User
 
 logger = logging.getLogger(__name__)
 ML_CACHE = LRUCache(3)  # Cache the three most recent ML models to reduce load times.
@@ -16,6 +19,40 @@ def get_ml_model(model_pk: int):
     return ML_CACHE[model_pk]
 
 
+def dispatch_eager(user: "User", job: Callable, *args, **kwargs):
+    try:
+        x = job(*args, **kwargs)
+        log = JobLog()
+        log.user = user
+        log.task_id = uuid4()
+        log.job_name = job.__name__
+        log.status = "SUCCESS"
+        log.done_at = datetime.now()
+        log.task_result = str(x) if x else None
+        log.save()
+
+        return x
+    except Exception as e:
+        logger.exception(e)
+        raise e
+
+
+def dispatch(user: "User", job: Callable, *args, **kwargs):
+    try:
+        x = job.delay(*args, **kwargs)
+        log = JobLog()
+        log.user = user
+        log.task_id = x.task_id
+        log.job_name = job.__name__
+        log.status = "INITIAL"
+        log.save()
+
+        return x.result
+    except Exception as e:
+        logger.exception(e)
+        raise e
+
+
 @shared_task(queue="background")
 def mul(a, b):
     return a * b
@@ -33,17 +70,55 @@ def send_registration_mail(user_pk: int):
     pass
 
 
-@shared_task(queue="model")
+@shared_task(bind=True, queue="model")
-def build_model(model_pk: int):
+def build_model(self, model_pk: int):
     mod = EPModel.objects.get(id=model_pk)
+
+    if JobLog.objects.filter(task_id=self.request.id).exists():
+        JobLog.objects.filter(task_id=self.request.id).update(status="RUNNING", task_result=mod.url)
+
+    try:
         mod.build_dataset()
         mod.build_model()
+    except Exception as e:
+        if JobLog.objects.filter(task_id=self.request.id).exists():
+            JobLog.objects.filter(task_id=self.request.id).update(
+                status="FAILED", task_result=mod.url
+            )
+
+        raise e
+
+    if JobLog.objects.filter(task_id=self.request.id).exists():
+        JobLog.objects.filter(task_id=self.request.id).update(status="SUCCESS", task_result=mod.url)
+
+    return mod.url
 
 
-@shared_task(queue="model")
+@shared_task(bind=True, queue="model")
-def evaluate_model(model_pk: int):
+def evaluate_model(self, model_pk: int, multigen: bool, package_pks: Optional[list] = None):
+    packages = None
+
+    if package_pks:
+        packages = Package.objects.filter(pk__in=package_pks)
+
     mod = EPModel.objects.get(id=model_pk)
-    mod.evaluate_model()
+    if JobLog.objects.filter(task_id=self.request.id).exists():
+        JobLog.objects.filter(task_id=self.request.id).update(status="RUNNING", task_result=mod.url)
+
+    try:
+        mod.evaluate_model(multigen, eval_packages=packages)
+    except Exception as e:
+        if JobLog.objects.filter(task_id=self.request.id).exists():
+            JobLog.objects.filter(task_id=self.request.id).update(
+                status="FAILED", task_result=mod.url
+            )
+
+        raise e
+
+    if JobLog.objects.filter(task_id=self.request.id).exists():
+        JobLog.objects.filter(task_id=self.request.id).update(status="SUCCESS", task_result=mod.url)
+
+    return mod.url
 
 
 @shared_task(queue="model")
@@ -52,9 +127,13 @@ def retrain(model_pk: int):
     mod.retrain()
 
 
-@shared_task(queue="predict")
+@shared_task(bind=True, queue="predict")
 def predict(
-    pw_pk: int, pred_setting_pk: int, limit: Optional[int] = None, node_pk: Optional[int] = None
+    self,
+    pw_pk: int,
+    pred_setting_pk: int,
+    limit: Optional[int] = None,
+    node_pk: Optional[int] = None,
 ) -> Pathway:
     pw = Pathway.objects.get(id=pw_pk)
     setting = Setting.objects.get(id=pred_setting_pk)
@@ -65,6 +144,9 @@ def predict(
     pw.kv.update(**{"status": "running"})
     pw.save()
 
+    if JobLog.objects.filter(task_id=self.request.id).exists():
+        JobLog.objects.filter(task_id=self.request.id).update(status="RUNNING", task_result=pw.url)
+
     try:
         # regular prediction
         if limit is not None:
@@ -89,7 +171,18 @@ def predict(
     except Exception as e:
         pw.kv.update({"status": "failed"})
         pw.save()
+
+        if JobLog.objects.filter(task_id=self.request.id).exists():
+            JobLog.objects.filter(task_id=self.request.id).update(
+                status="FAILED", task_result=pw.url
+            )
+
         raise e
 
     pw.kv.update(**{"status": "completed"})
     pw.save()
+
+    if JobLog.objects.filter(task_id=self.request.id).exists():
+        JobLog.objects.filter(task_id=self.request.id).update(status="SUCCESS", task_result=pw.url)
+
+    return pw.url

epdb/templatetags/envipytags.py

@@ -1,8 +1,21 @@
 from django import template
+from pydantic import AnyHttpUrl, ValidationError
+from pydantic.type_adapter import TypeAdapter
 
 register = template.Library()
 
+url_adapter = TypeAdapter(AnyHttpUrl)
+
 
 @register.filter
 def classname(obj):
     return obj.__class__.__name__
+
+
+@register.filter
+def is_url(value):
+    try:
+        url_adapter.validate_python(value)
+        return True
+    except ValidationError:
+        return False

epdb/urls.py

@@ -190,6 +190,7 @@ urlpatterns = [
     re_path(r"^indigo/dearomatize$", v.dearomatize, name="indigo_dearomatize"),
     re_path(r"^indigo/layout$", v.layout, name="indigo_layout"),
     re_path(r"^depict$", v.depict, name="depict"),
+    re_path(r"^jobs", v.jobs, name="jobs"),
     # OAuth Stuff
     path("o/userinfo/", v.userinfo, name="oauth_userinfo"),
 ]

epdb/views.py

@@ -47,6 +47,7 @@ from .models import (
     ExternalDatabase,
     ExternalIdentifier,
     EnzymeLink,
+    JobLog,
 )
 
 logger = logging.getLogger(__name__)
@@ -754,8 +755,8 @@ def package_models(request, package_uuid):
         context["unreviewed_objects"] = unreviewed_model_qs
 
         context["model_types"] = {
-            "ML Relative Reasoning": "ml-relative-reasoning",
+            "ML Relative Reasoning": "mlrr",
-            "Rule Based Relative Reasoning": "rule-based-relative-reasoning",
+            "Rule Based Relative Reasoning": "rbrr",
         }
 
         if s.FLAGS.get("ENVIFORMER", False):
@@ -775,48 +776,40 @@ def package_models(request, package_uuid):
 
         model_type = request.POST.get("model-type")
 
-        if model_type == "enviformer":
-            threshold = float(request.POST.get(f"{model_type}-threshold", 0.5))
-
-            mod = EnviFormer.create(current_package, name, description, threshold)
-
-        elif model_type == "ml-relative-reasoning" or model_type == "rule-based-relative-reasoning":
         # Generic fields for ML and Rule Based
-            rule_packages = request.POST.getlist("package-based-relative-reasoning-rule-packages")
+        rule_packages = request.POST.getlist("model-rule-packages")
-            data_packages = request.POST.getlist("package-based-relative-reasoning-data-packages")
+        data_packages = request.POST.getlist("model-data-packages")
-            eval_packages = request.POST.getlist(
-                "package-based-relative-reasoning-evaluation-packages", []
-            )
 
         # Generic params
         params = {
             "package": current_package,
             "name": name,
             "description": description,
-                "rule_packages": [
-                    PackageManager.get_package_by_url(current_user, p) for p in rule_packages
-                ],
             "data_packages": [
                 PackageManager.get_package_by_url(current_user, p) for p in data_packages
             ],
-                "eval_packages": [
-                    PackageManager.get_package_by_url(current_user, p) for p in eval_packages
-                ],
         }
 
-            if model_type == "ml-relative-reasoning":
+        if model_type == "enviformer":
+            threshold = float(request.POST.get("model-threshold", 0.5))
+            params["threshold"] = threshold
+
+            mod = EnviFormer.create(**params)
+        elif model_type == "mlrr":
             # ML Specific
-                threshold = float(request.POST.get(f"{model_type}-threshold", 0.5))
+            threshold = float(request.POST.get("model-threshold", 0.5))
             # TODO handle additional fingerprinter
-                # fingerprinter = request.POST.get(f"{model_type}-fingerprinter")
+            # fingerprinter = request.POST.get("model-fingerprinter")
+
+            params["rule_packages"] = [
+                PackageManager.get_package_by_url(current_user, p) for p in rule_packages
+            ]
 
             # App Domain related parameters
             build_ad = request.POST.get("build-app-domain", False) == "on"
             num_neighbors = request.POST.get("num-neighbors", 5)
             reliability_threshold = request.POST.get("reliability-threshold", 0.5)
-                local_compatibility_threshold = request.POST.get(
+            local_compatibility_threshold = request.POST.get("local-compatibility-threshold", 0.5)
-                    "local-compatibility-threshold", 0.5
-                )
 
             params["threshold"] = threshold
             # params['fingerprinter'] = fingerprinter
@@ -826,18 +819,24 @@ def package_models(request, package_uuid):
             params["app_domain_local_compatibility_threshold"] = local_compatibility_threshold
 
             mod = MLRelativeReasoning.create(**params)
-            else:
+        elif model_type == "rbrr":
+            params["rule_packages"] = [
+                PackageManager.get_package_by_url(current_user, p) for p in rule_packages
+            ]
+
             mod = RuleBasedRelativeReasoning.create(**params)
-
+        elif s.FLAGS.get("PLUGINS", False) and model_type in s.CLASSIFIER_PLUGINS.values():
-            from .tasks import build_model
+            pass
-
-            build_model.delay(mod.pk)
         else:
             return error(
                 request, "Invalid model type.", f'Model type "{model_type}" is not supported."'
             )
-        return redirect(mod.url)
 
+        from .tasks import dispatch, build_model
+
+        dispatch(current_user, build_model, mod.pk)
+
+        return redirect(mod.url)
     else:
         return HttpResponseNotAllowed(["GET", "POST"])
 
@@ -865,6 +864,10 @@ def package_model(request, package_uuid, model_uuid):
                 return JsonResponse({"error": f'"{smiles}" is not a valid SMILES'}, status=400)
 
             if classify:
+                from epdb.tasks import dispatch_eager, predict_simple
+
+                res = dispatch_eager(current_user, predict_simple, current_model.pk, stand_smiles)
+
                 pred_res = current_model.predict(stand_smiles)
                 res = []
 
@@ -909,9 +912,25 @@ def package_model(request, package_uuid, model_uuid):
                 current_model.delete()
                 return redirect(current_package.url + "/model")
             elif hidden == "evaluate":
-                from .tasks import evaluate_model
+                from .tasks import dispatch, evaluate_model
+
+                eval_type = request.POST.get("model-evaluation-type")
+
+                if eval_type not in ["sg", "mg"]:
+                    return error(
+                        request,
+                        "Invalid evaluation type",
+                        f'Evaluation type "{eval_type}" is not supported. Only "sg" and "mg" are supported.',
+                    )
+
+                multigen = eval_type == "mg"
+
+                eval_packages = request.POST.getlist("model-evaluation-packages")
+                eval_package_ids = [
+                    PackageManager.get_package_by_url(current_user, p).id for p in eval_packages
+                ]
+                dispatch(current_user, evaluate_model, current_model.pk, multigen, eval_package_ids)
 
-                evaluate_model.delay(current_model.pk)
                 return redirect(current_model.url)
             else:
                 return HttpResponseBadRequest()
@@ -1809,9 +1828,9 @@ def package_pathways(request, package_uuid):
             pw.setting = prediction_setting
             pw.save()
 
-            from .tasks import predict
+            from .tasks import dispatch, predict
 
-            predict.delay(pw.pk, prediction_setting.pk, limit=limit)
+            dispatch(current_user, predict, pw.pk, prediction_setting.pk, limit=limit)
 
         return redirect(pw.url)
 
@@ -1930,10 +1949,16 @@ def package_pathway(request, package_uuid, pathway_uuid):
         if node_url:
             n = current_pathway.get_node(node_url)
 
-            from .tasks import predict
+            from .tasks import dispatch, predict
+
+            dispatch(
+                current_user,
+                predict,
+                current_pathway.pk,
+                current_pathway.prediction_setting.pk,
+                node_pk=n.pk,
+            )
 
-            # Dont delay?
-            predict(current_pathway.pk, current_pathway.setting.pk, node_pk=n.pk)
             return JsonResponse({"success": current_pathway.url})
 
         return HttpResponseBadRequest()
@@ -2705,6 +2730,24 @@ def setting(request, setting_uuid):
     pass
 
 
+def jobs(request):
+    current_user = _anonymous_or_real(request)
+    context = get_base_context(request)
+
+    if request.method == "GET":
+        context["object_type"] = "joblog"
+        context["breadcrumbs"] = [
+            {"Home": s.SERVER_URL},
+            {"Jobs": s.SERVER_URL + "/jobs"},
+        ]
+        if current_user.is_superuser:
+            context["jobs"] = JobLog.objects.all().order_by("-created")
+        else:
+            context["jobs"] = JobLog.objects.filter(user=current_user).order_by("-created")
+
+        return render(request, "collections/joblog.html", context)
+
+
 ###########
 # KETCHER #
 ###########

templates/collections/joblog.html

@@ -0,0 +1,71 @@
+{% extends "framework.html" %}
+{% load static %}
+{% load envipytags %}
+{% block content %}
+
+    <div class="panel-group" id="reviewListAccordion">
+        <div class="panel panel-default">
+            <div class="panel-heading" id="headingPanel" style="font-size:2rem;height: 46px">
+                Jobs
+            </div>
+            <div class="panel-body">
+                <p>
+                    Job Logs Desc
+                </p>
+
+            </div>
+
+            <div class="panel panel-default panel-heading list-group-item" style="background-color:silver">
+                <h4 class="panel-title">
+                    <a id="job-accordion-link" data-toggle="collapse" data-parent="#job-accordion" href="#jobs">
+                        Jobs
+                    </a>
+                </h4>
+            </div>
+            <div id="jobs"
+                 class="panel-collapse collapse in">
+                <div class="panel-body list-group-item" id="job-content">
+                    <table class="table table-bordered table-hover">
+                        <tr style="background-color: rgba(0, 0, 0, 0.08);">
+                            <th scope="col">ID</th>
+                            <th scope="col">Name</th>
+                            <th scope="col">Status</th>
+                            <th scope="col">Queued</th>
+                            <th scope="col">Done</th>
+                            <th scope="col">Result</th>
+                        </tr>
+                        <tbody>
+                        {% for job in jobs %}
+                            <tr>
+                                <td>{{ job.task_id }}</td>
+                                <td>{{ job.job_name }}</td>
+                                <td>{{ job.status }}</td>
+                                <td>{{ job.created }}</td>
+                                <td>{{ job.done_at }}</td>
+                                {% if job.task_result and job.task_result|is_url == True %}
+                                    <td><a href="{{ job.task_result }}">Result</a></td>
+                                {% elif job.task_result %}
+                                    <td>{{ job.task_result|slice:"40" }}...</td>
+                                {% else %}
+                                    <td>Empty</td>
+                                {% endif %}
+                            </tr>
+                        {% endfor %}
+                        </tbody>
+                    </table>
+                </div>
+            </div>
+
+            <!-- Unreviewable objects such as User / Group / Setting -->
+            <ul class='list-group'>
+                {% for obj in objects %}
+                    {% if object_type == 'user' %}
+                        <a class="list-group-item" href="{{ obj.url }}">{{ obj.username }}</a>
+                    {% else %}
+                        <a class="list-group-item" href="{{ obj.url }}">{{ obj.name }}</a>
+                    {% endif %}
+                {% endfor %}
+            </ul>
+        </div>
+    </div>
+{% endblock content %}

templates/modals/collections/new_model_modal.html

@@ -18,13 +18,19 @@
                         prediction. You just need to set a name and the packages
                         you want the object to be based on. There are multiple types of models available.
                         For additional information have a look at our
-                        <a target="_blank" href="https://wiki.envipath.org/index.php/relative-reasoning" role="button">wiki &gt;&gt;</a>
+                        <a target="_blank" href="https://wiki.envipath.org/index.php/relative-reasoning" role="button">wiki
+                            &gt;&gt;</a>
                     </div>
+                    <!-- Name -->
                     <label for="model-name">Name</label>
                     <input id="model-name" name="model-name" class="form-control" placeholder="Name"/>
+
+                    <!-- Description -->
                     <label for="model-description">Description</label>
                     <input id="model-description" name="model-description" class="form-control"
                            placeholder="Description"/>
+
+                    <!-- Model Type -->
                     <label for="model-type">Model Type</label>
                     <select id="model-type" name="model-type" class="form-control" data-width='100%'>
                         <option disabled selected>Select Model Type</option>
@@ -32,12 +38,12 @@
                             <option value="{{ v }}">{{ k }}</option>
                         {% endfor %}
                     </select>
-                    <!-- ML and Rule Based Based Form-->
+
-                    <div id="package-based-relative-reasoning-specific-form">
                     <!-- Rule Packages -->
-                        <label for="package-based-relative-reasoning-rule-packages">Rule Packages</label>
+                    <div id="rule-packages" class="ep-model-param mlrr rbrr">
-                        <select id="package-based-relative-reasoning-rule-packages" name="package-based-relative-reasoning-rule-packages"
+                        <label for="model-rule-packages">Rule Packages</label>
-                                data-actions-box='true' class="form-control" multiple data-width='100%'>
+                        <select id="model-rule-packages" name="model-rule-packages" data-actions-box='true'
+                                class="form-control" multiple data-width='100%'>
                             <option disabled>Reviewed Packages</option>
                             {% for obj in meta.readable_packages %}
                                 {% if obj.reviewed %}
@@ -52,10 +58,13 @@
                                 {% endif %}
                             {% endfor %}
                         </select>
+                    </div>
+
                     <!-- Data Packages -->
-                        <label for="package-based-relative-reasoning-data-packages" >Data Packages</label>
+                    <div id="data-packages" class="ep-model-param mlrr rbrr enviformer">
-                        <select id="package-based-relative-reasoning-data-packages" name="package-based-relative-reasoning-data-packages"
+                        <label for="model-data-packages">Data Packages</label>
-                                data-actions-box='true' class="form-control" multiple data-width='100%'>
+                        <select id="model-data-packages" name="model-data-packages" data-actions-box='true'
+                                class="form-control" multiple data-width='100%'>
                             <option disabled>Reviewed Packages</option>
                             {% for obj in meta.readable_packages %}
                                 {% if obj.reviewed %}
@@ -70,32 +79,31 @@
                                 {% endif %}
                             {% endfor %}
                         </select>
+                    </div>
 
-                        <div id="ml-relative-reasoning-specific-form">
                     <!-- Fingerprinter -->
-                            <label for="ml-relative-reasoning-fingerprinter">Fingerprinter</label>
+                    <div id="fingerprinter" class="ep-model-param mlrr">
-                            <select id="ml-relative-reasoning-fingerprinter" name="ml-relative-reasoning-fingerprinter"
+                        <label for="model-fingerprinter">Fingerprinter</label>
-                                    class="form-control">
+                        <select id="model-fingerprinter" name="model-fingerprinter" data-actions-box='true'
+                                class="form-control" multiple data-width='100%'>
                             <option value="MACCS" selected>MACCS Fingerprinter</option>
-                            </select>
                             {% if meta.enabled_features.PLUGINS and additional_descriptors %}
-                                <!-- Property Plugins go here -->
-                                <label for="ml-relative-reasoning-additional-fingerprinter">Additional Fingerprinter /
-                                    Descriptors</label>
-                                <select id="ml-relative-reasoning-additional-fingerprinter"
-                                        name="ml-relative-reasoning-additional-fingerprinter" class="form-control">
                                 <option disabled selected>Select Additional Fingerprinter / Descriptor</option>
                                 {% for k, v in additional_descriptors.items %}
                                     <option value="{{ v }}">{{ k }}</option>
                                 {% endfor %}
-                                </select>
                             {% endif %}
-
+                        </select>
-                            <label for="ml-relative-reasoning-threshold">Threshold</label>
-                            <input type="number" min="0" max="1" step="0.05" value="0.5"
-                                   id="ml-relative-reasoning-threshold"
-                                   name="ml-relative-reasoning-threshold" class="form-control">
                     </div>
+
+                    <!-- Threshold -->
+                    <div id="threshold" class="ep-model-param mlrr enviformer">
+                        <label for="model-threshold">Threshold</label>
+                        <input type="number" min="0" max="1" step="0.05" value="0.5" id="model-threshold"
+                               name="model-threshold" class="form-control">
+                    </div>
+
+                    <div id="appdomain" class="ep-model-param mlrr">
                         {% if meta.enabled_features.APPLICABILITY_DOMAIN %}
                             <!-- Build AD? -->
                             <div class="checkbox">
@@ -107,11 +115,13 @@
                             <div id="ad-params" style="display:none">
                                 <!-- Num Neighbors -->
                                 <label for="num-neighbors">Number of Neighbors</label>
-                            <input id="num-neighbors" name="num-neighbors" type="number" class="form-control" value="5"
+                                <input id="num-neighbors" name="num-neighbors" type="number" class="form-control"
+                                       value="5"
                                        step="1" min="0" max="10">
                                 <!-- Local Compatibility -->
                                 <label for="local-compatibility-threshold">Local Compatibility Threshold</label>
-                            <input id="local-compatibility-threshold" name="local-compatibility-threshold" type="number"
+                                <input id="local-compatibility-threshold" name="local-compatibility-threshold"
+                                       type="number"
                                        class="form-control" value="0.5" step="0.01" min="0" max="1">
                                 <!-- Reliability -->
                                 <label for="reliability-threshold">Reliability Threshold</label>
@@ -120,12 +130,6 @@
                             </div>
                         {% endif %}
                     </div>
-                    <!-- EnviFormer-->
-                    <div id="enviformer-specific-form">
-                        <label for="enviformer-threshold">Threshold</label>
-                        <input type="number" min="0" max="1" step="0.05" value="0.5" id="enviformer-threshold"
-                               name="enviformer-threshold" class="form-control">
-                    </div>
                 </form>
             </div>
             <div class="modal-footer">
@@ -138,19 +142,22 @@
 
 <script>
     $(function () {
+        // Built in Model Types
+        var nativeModelTypes = [
+            "mlrr",
+            "rbrr",
+            "enviformer",
+        ]
+
         // Initially hide all "specific" forms
-    $("div[id$='-specific-form']").each( function() {
+        $(".ep-model-param").each(function () {
             $(this).hide();
         });
 
         $('#model-type').selectpicker();
-    $("#ml-relative-reasoning-fingerprinter").selectpicker();
+        $("#model-fingerprinter").selectpicker();
-    $("#package-based-relative-reasoning-rule-packages").selectpicker();
+        $("#model-rule-packages").selectpicker();
-    $("#package-based-relative-reasoning-data-packages").selectpicker();
+        $("#model-data-packages").selectpicker();
-    $("#package-based-relative-reasoning-evaluation-packages").selectpicker();
-    if ($('#ml-relative-reasoning-additional-fingerprinter').length > 0) {
-        $("#ml-relative-reasoning-additional-fingerprinter").selectpicker();
-    }
 
         $("#build-app-domain").change(function () {
             if ($(this).is(":checked")) {
@@ -162,18 +169,12 @@ $(function() {
 
         // On change hide all and show only selected
         $("#model-type").change(function () {
-        $("div[id$='-specific-form']").each( function() {
+            $('.ep-model-param').hide();
-            $(this).hide();
+            var modelType = $('#model-type').val();
-        });
+            if (nativeModelTypes.indexOf(modelType) !== -1) {
-        val = $('option:selected', this).val();
+                $('.' + modelType).show();
-
-        if (val === 'ml-relative-reasoning' || val === 'rule-based-relative-reasoning') {
-            $("#package-based-relative-reasoning-specific-form").show();
-            if (val === 'ml-relative-reasoning') {
-                 $("#ml-relative-reasoning-specific-form").show();
-            }
             } else {
-            $("#" + val + "-specific-form").show();
+                // do nothing
             }
         });
 
@@ -183,7 +184,4 @@ $(function() {
         });
 
     });
-
-
-
 </script>

templates/modals/objects/evaluate_model_modal.html

@@ -17,10 +17,10 @@
                         For evaluation, you need to select the packages you want to use.
                         While the model is evaluating, you can use the model for predictions.
                     </div>
-                    <!-- Evaluation -->
+                    <!-- Evaluation Packages -->
-                    <label for="relative-reasoning-evaluation-packages">Evaluation Packages</label>
+                    <label for="model-evaluation-packages">Evaluation Packages</label>
-                    <select id="relative-reasoning-evaluation-packages" name=relative-reasoning-evaluation-packages"
+                    <select id="model-evaluation-packages" name="model-evaluation-packages" data-actions-box='true'
-                            data-actions-box='true' class="form-control" multiple data-width='100%'>
+                            class="form-control" multiple data-width='100%'>
                         <option disabled>Reviewed Packages</option>
                         {% for obj in meta.readable_packages %}
                             {% if obj.reviewed %}
@@ -35,6 +35,15 @@
                             {% endif %}
                         {% endfor %}
                     </select>
+
+                    <!-- Eval Type -->
+                    <label for="model-evaluation-type">Evaluation Type</label>
+                    <select id="model-evaluation-type" name="model-evaluation-type" class="form-control">
+                        <option disabled selected>Select evaluation type</option>
+                        <option value="sg">Single Generation</option>
+                        <option value="mg">Multiple Generations</option>
+                    </select>
+
                     <input type="hidden" name="hidden" value="evaluate">
                 </form>
             </div>
@@ -50,7 +59,7 @@
 
     $(function () {
 
-        $("#relative-reasoning-evaluation-packages").selectpicker();
+        $("#model-evaluation-packages").selectpicker();
 
         $('#evaluate_model_form_submit').on('click', function (e) {
             e.preventDefault();

templates/objects/model.html

@@ -117,7 +117,7 @@
                 <!-- End Predict Panel       -->
             {% endif %}
 
-            {% if model.app_domain %}
+            {% if model.ready_for_prediction and model.app_domain %}
                 <!-- App Domain -->
                 <div class="panel panel-default panel-heading list-group-item" style="background-color:silver">
                     <h4 class="panel-title">

tests/test_enviformer.py

@@ -3,7 +3,7 @@ from datetime import datetime
 from tempfile import TemporaryDirectory
 from django.test import TestCase, tag
 from epdb.logic import PackageManager
-from epdb.models import User, EnviFormer, Package, Setting, Pathway
+from epdb.models import User, EnviFormer, Package, Setting
 from epdb.tasks import predict_simple, predict
 
 
@@ -48,9 +48,7 @@ class EnviFormerTest(TestCase):
 
                 mod.build_dataset()
                 mod.build_model()
-                mod.multigen_eval = True
+                mod.evaluate_model(True, eval_packages_objs)
-                mod.save()
-                mod.evaluate_model()
 
                 mod.predict("CCN(CC)C(=O)C1=CC(=CC=C1)C")
 
@@ -75,11 +73,15 @@ class EnviFormerTest(TestCase):
 
                 # Test pathway prediction
                 times = [measure_predict(mods[1], self.BBD_SUBSET.pathways[0].pk) for _ in range(5)]
-                print(f"First pathway prediction took {times[0]} seconds, subsequent ones took {times[1:]}")
+                print(
+                    f"First pathway prediction took {times[0]} seconds, subsequent ones took {times[1:]}"
+                )
 
                 # Test eviction by performing three prediction with every model, twice.
                 times = defaultdict(list)
-                for _ in range(2):  # Eviction should cause the second iteration here to have to reload the models
+                for _ in range(
+                    2
+                ):  # Eviction should cause the second iteration here to have to reload the models
                     for mod in mods:
                         for _ in range(3):
                             times[mod.pk].append(measure_predict(mod))

tests/test_model.py

@@ -30,7 +30,6 @@ class ModelTest(TestCase):
                     self.package,
                     rule_package_objs,
                     data_package_objs,
-                    eval_packages_objs,
                     threshold=threshold,
                     name="ECC - BBD - 0.5",
                     description="Created MLRelativeReasoning in Testcase",
@@ -50,9 +49,7 @@ class ModelTest(TestCase):
 
                 mod.build_dataset()
                 mod.build_model()
-                mod.multigen_eval = True
+                mod.evaluate_model(True, eval_packages_objs)
-                mod.save()
-                mod.evaluate_model()
 
                 results = mod.predict("CCN(CC)C(=O)C1=CC(=CC=C1)C")
 

tests/views/test_model_views.py

@@ -6,7 +6,7 @@ from epdb.logic import UserManager
 from epdb.models import Package, User
 
 
-@override_settings(MODEL_DIR=s.FIXTURE_DIRS[0] / "models")
+@override_settings(MODEL_DIR=s.FIXTURE_DIRS[0] / "models", CELERY_TASK_ALWAYS_EAGER=True)
 class PathwayViewTest(TestCase):
     fixtures = ["test_fixtures_incl_model.jsonl.gz"]
 

tests/views/test_pathway_views.py

@@ -6,7 +6,7 @@ from epdb.logic import UserManager, PackageManager
 from epdb.models import Pathway, Edge
 
 
-@override_settings(MODEL_DIR=s.FIXTURE_DIRS[0] / "models")
+@override_settings(MODEL_DIR=s.FIXTURE_DIRS[0] / "models", CELERY_TASK_ALWAYS_EAGER=True)
 class PathwayViewTest(TestCase):
     fixtures = ["test_fixtures_incl_model.jsonl.gz"]