Add LLM question import functionality and enhance question model with new fields

sbas/forms.py

@@ -3,6 +3,7 @@ from django.forms import (
     ModelForm,
     ModelMultipleChoiceField,
     ModelChoiceField,
+    CheckboxSelectMultiple,
     ChoiceField,
     CharField,
 )
@@ -22,6 +23,8 @@ from django.forms.widgets import RadioSelect, TextInput, Textarea
 
 from tinymce.widgets import TinyMCE
 
+from dal import autocomplete
+
 
 class UserAnswerForm(ModelForm):
     class Meta:
@@ -140,6 +143,11 @@ class QuestionForm(ModelForm):
             "e_answer",
             "e_feedback",
             "best_answer",
+            "finding",
+            "structure",
+            "condition",
+            "presentation",
+            "subspecialty",
         ]
 
         widgets = {
@@ -158,6 +166,19 @@ class QuestionForm(ModelForm):
             "c_feedback" : TinyMCE(attrs={'cols': 80, 'rows': 4}, mce_attrs={'height': 140}),
             "d_feedback" : TinyMCE(attrs={'cols': 80, 'rows': 4}, mce_attrs={'height': 140}),
             "e_feedback" : TinyMCE(attrs={'cols': 80, 'rows': 4}, mce_attrs={'height': 140}),
+            "structure": autocomplete.ModelSelect2Multiple(
+                url="atlas:structure-autocomplete"
+            ),
+            "finding": autocomplete.ModelSelect2Multiple(
+                url="atlas:finding-autocomplete"
+            ),
+            "condition": autocomplete.ModelSelect2Multiple(
+                url="atlas:condition-autocomplete"
+            ),
+            "presentation": autocomplete.ModelSelect2Multiple(
+                url="atlas:presentation-autocomplete"
+            ),
+            "subspecialty": CheckboxSelectMultiple(),
         }
 
         #widgets = {

sbas/migrations/0018_question_condition_question_finding_and_more.py

@@ -0,0 +1,39 @@
+# Generated by Django 5.1.4 on 2025-10-20 08:47
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('atlas', '0079_casecollection_prerequisites'),
+        ('sbas', '0017_exam_results_supervisor_visible'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='question',
+            name='condition',
+            field=models.ManyToManyField(blank=True, related_name='sbas_questions', to='atlas.condition'),
+        ),
+        migrations.AddField(
+            model_name='question',
+            name='finding',
+            field=models.ManyToManyField(blank=True, related_name='sbas_questions', to='atlas.finding'),
+        ),
+        migrations.AddField(
+            model_name='question',
+            name='presentation',
+            field=models.ManyToManyField(blank=True, related_name='sbas_questions', to='atlas.presentation'),
+        ),
+        migrations.AddField(
+            model_name='question',
+            name='structure',
+            field=models.ManyToManyField(blank=True, related_name='sbas_questions', to='atlas.structure'),
+        ),
+        migrations.AddField(
+            model_name='question',
+            name='subspecialty',
+            field=models.ManyToManyField(blank=True, related_name='sbas_questions', to='atlas.subspecialty'),
+        ),
+    ]

sbas/migrations/0019_question_title.py

@@ -0,0 +1,18 @@
+# Generated by Django 5.1.4 on 2025-10-20 09:30
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('sbas', '0018_question_condition_question_finding_and_more'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='question',
+            name='title',
+            field=models.CharField(blank=True, help_text='Short title for question', max_length=200, null=True),
+        ),
+    ]

sbas/models.py

@@ -15,6 +15,8 @@ import reversion
 
 from django.contrib.contenttypes.fields import GenericRelation
 
+from atlas.models import Finding, Structure, Condition, Subspecialty, Presentation
+
 
 class Category(models.Model):
     category = models.CharField(max_length=200)
@@ -24,6 +26,7 @@ class Category(models.Model):
 
 
 class Question(QuestionBase):
+    title = models.CharField(max_length=200, help_text="Short title for question", blank=True, null=True)
     stem = models.TextField(
         blank=False,
         help_text="Stem of the question",
@@ -91,6 +94,12 @@ class Question(QuestionBase):
         Category, on_delete=models.SET_NULL, null=True, blank=True
     )
 
+    finding = models.ManyToManyField(Finding, blank=True, related_name="sbas_questions")
+    structure = models.ManyToManyField(Structure, blank=True, related_name="sbas_questions")
+    condition = models.ManyToManyField(Condition, blank=True, related_name="sbas_questions")
+    presentation = models.ManyToManyField(Presentation, blank=True, related_name="sbas_questions")
+    subspecialty = models.ManyToManyField(Subspecialty, blank=True, related_name="sbas_questions")
+
     #notes = GenericRelation(QuestionNote)
 
     def __str__(self):

sbas/templates/sbas/base.html

@@ -27,6 +27,13 @@
                           <li><a class="dropdown-item" href="{% url 'sbas:question_create' %}" title="Create a new question"><i class="bi bi-question-circle"></i> Question</a></li>
                         </ul>
                       </li>
+                    <li class="nav-item-dropdown">
+                        <a class="nav-link dropdown-toggle" data-bs-toggle="dropdown" href="#" role="button" aria-expanded="false"><i class="bi bi-gear"></i> LLM</a>
+                        <ul class="dropdown-menu">
+                            <li><a class="dropdown-item" href="{% url 'sbas:llm_prompt_view' %}" title="Generate questions using LLM"><i class="bi bi-robot"></i> LLM prompt</a></li>
+                            <li><a class="dropdown-item" href="{% url 'sbas:import_llm_questions' %}" title="Import questions using LLM"><i class="bi bi-upload"></i> Import Questions</a></li>
+                        </ul>
+                    </li>
                         
                     {% if request.user.is_superuser %}
                         <li class="nav-item">

sbas/templates/sbas/import_llm_questions.html

@@ -0,0 +1,11 @@
+{% extends 'sbas/base.html' %}
+
+{% block content %}
+  <h1>Import LLM Questions</h1>
+  <form method="post" enctype="multipart/form-data">
+    {% csrf_token %}
+    {{ form.as_p }}
+    <button class="btn btn-primary" type="submit">Upload and Import</button>
+  </form>
+  <p>Upload a single JSON array, a single object, or JSONL (one JSON object per line) matching the agreed schema.</p>
+{% endblock %}

sbas/templates/sbas/llm_prompt_view.html

@@ -0,0 +1,133 @@
+{% extends 'sbas/base.html' %}
+
+{% block content %}
+<h2>LLM Prompts</h2>
+<p>
+    Below are the prompts used for interacting with large language models (LLMs) within the SBA system.
+</p>
+
+<h3>Question Generation Prompt</h3>
+    <pre>
+You are an expert radiologist tasked with generating high-quality multiple-choice questions for medical imaging education. Each question should consist of a clinical vignette, an image description, and five answer choices (A through E), with one correct answer and four plausible distractors.
+
+Please adhere to the following guidelines when creating each question:
+1. Clinical Vignette: Provide a brief clinical scenario that sets the context for the question including relevant patient history and clinical findings.
+2. Make sure the question focuses on key radiological concepts, findings, or diagnoses.
+3. Answer Choices: Create five answer options. Ensure that one is the correct answer and the others are plausible distractors.
+4. Explanation: Provide a concise explanation for why the correct answer is right and why the distractors are incorrect.
+5. Difficulty Level: Aim for a moderate difficulty level suitable for training radiologists.
+6. Clarity and Precision: Use clear and precise language, avoiding ambiguity.
+7. Relevance: Ensure that the question is relevant to current radiological practices and guidelines.
+8. Questions should feature metadata tags for finding, structure, condition, presentation, and subspecialty.
+9. Each question output should be a json object with the following schema:
+10. For article sources pleese reference the article doi within the explanation field in the format [doi:10.xxxx/xxxxx].
+11. For statdx sources please reference the article in the format [statdx:article_id].
+12. References should be included inline within the explanation field.
+13. Questions need to have a radiology focus, please avoid questions that are purely clinical or biochemical without imaging relevance.
+
+JSON Schema (draft-07 compatible)
+{
+"$schema": "http://json-schema.org/draft-07/schema#",
+"title": "SBA Question",
+"description": "Schema for importing LLM-generated questions into the sbas.Question model.",
+"type": "object",
+"additionalProperties": false,
+"required": [
+"title",
+"stem",
+"a_answer",
+"b_answer",
+"c_answer",
+"d_answer",
+"e_answer",
+"best_answer",
+"category"
+],
+"properties": {
+"title": {
+"type": "string",
+"description": "Short title for the question."
+},
+"stem": {
+"type": "string",
+"description": "HTML or plain text question stem. Trim leading/trailing whitespace before saving."
+},
+"a_answer": { "type": "string" },
+"a_feedback": { "type": "string", "default": "" },
+"b_answer": { "type": "string" },
+"b_feedback": { "type": "string", "default": "" },
+"c_answer": { "type": "string" },
+"c_feedback": { "type": "string", "default": "" },
+"d_answer": { "type": "string" },
+"d_feedback": { "type": "string", "default": "" },
+"e_answer": { "type": "string" },
+"e_feedback": { "type": "string", "default": "" },
+"feedback": {
+"type": "string",
+"description": "General question feedback (may include HTML)."
+},
+"best_answer": {
+"type": "string",
+"enum": ["a", "b", "c", "d", "e"],
+"description": "One of 'a','b','c','d','e'."
+},
+"category": {
+"oneOf": [
+{ "type": "string", "description": "Category name ('Central Nervous and Head & Neck', 'Paediatric', 'Genito-urinary, Adrenal, Obstetrics & Gynaecology and Breast', 'Gastro-intestinal', 'Musculoskeletal and Trauma', 'Cardiothoracic and Vascular')" }
+]
+},
+"finding": {
+"type": "array",
+"description": "References to Finding objects. Prefer numeric IDs; names allowed if importer resolves them.",
+"items": {
+"oneOf": [
+{ "type": "integer" },
+{ "type": "string" }
+]
+},
+"uniqueItems": true
+},
+"structure": {
+"type": "array",
+"items": {
+"oneOf": [
+{ "type": "integer" },
+{ "type": "string" }
+]
+},
+"uniqueItems": true
+},
+"condition": {
+"type": "array",
+"items": {
+"oneOf": [
+{ "type": "integer" },
+{ "type": "string" }
+]
+},
+"uniqueItems": true
+},
+"presentation": {
+"type": "array",
+"items": {
+"oneOf": [
+{ "type": "integer" },
+{ "type": "string" }
+]
+},
+"uniqueItems": true
+},
+"subspecialty": {
+"type": "array",
+"items": {
+"oneOf": [
+{ "type": "integer" },
+{ "type": "string", "description": "Subspecialty name (e.g. 'Haematology & Oncology', 'Vascular', 'Uroradiology', 'Thoracic', 'Paediatric', 'Obstetric and Gynaecological', 'Neuroradiology', 'Musculoskeletal', 'Head and Neck', 'Gastrointestinal and hepatobiliary', 'Cardiac', 'Breast')" }
+]
+},
+"uniqueItems": true
+},
+}
+}
+
+</pre>

sbas/templates/sbas/question_detail.html

@@ -29,14 +29,78 @@
                 <a href="{% url 'sbas:exam_overview' pk=exam.pk %}">{{ exam }}</a>
             {% endfor %}
         </div>
+        <div>
+            Findings: {% if question.finding.exists %}
+                <ul>
+                    {% for f in question.finding.all %}
+                        <li>{{ f.get_link|safe }}</li>
+                    {% endfor %}
+                </ul>
+            {% else %}
+                None
+            {% endif %}
+        </div>
+        <div>
+            Structures: {% if question.structure.exists %}
+                <ul>
+                    {% for s in question.structure.all %}
+                        <li>{{ s.get_link|safe }}</li>
+                    {% endfor %}
+                </ul>
+            {% else %}
+                None
+            {% endif %}
+        </div>
+        <div>
+            Conditions: {% if question.condition.exists %}
+                <ul>
+                    {% for c in question.condition.all %}
+                        <li>{{ c.get_link|safe }}</li>
+                    {% endfor %}
+                </ul>
+            {% else %}
+                None
+            {% endif %}
+        </div>
+        <div>
+            Presentations: {% if question.presentation.exists %}
+                <ul>
+                    {% for p in question.presentation.all %}
+                        <li>{{ p.get_link|safe }}</li>
+                    {% endfor %}
+                </ul>
+            {% else %}
+                None
+            {% endif %}
+        </div>
+        <div>
+            Subspecialties: {% if question.subspecialty.exists %}
+                <ul>
+                    {% for ss in question.subspecialty.all %}
+                        <li>{{ ss.get_link|safe }}</li>
+                    {% endfor %}
+                </ul>
+            {% else %}
+                None
+            {% endif %}
+        </div>
         <div>
             Category: {{ question.category }}
         </div>
 
         <div>
-            Author: {% for user in question.author.all %}
+            Author(s):
-                {{ author }},
+            {% if question.author.exists %}
+                {% for u in question.author.all %}
+                    {{ u.get_full_name|default:u.username }}{% if not forloop.last %}, {% endif %}
                 {% endfor %}
+            {% else %}
+                Unknown
+            {% endif %}
+        </div>
+
+        <div>
+            Feedback: {{ question.feedback|linebreaks }}
         </div>
 
         {% include 'question_notes.html' %}

sbas/urls.py

@@ -82,6 +82,18 @@ urlpatterns = [
         views.UserAnswerDelete.as_view(),
         name="user_answer_delete",
     ),
+    path(
+        "llm_prompts/",
+        views.llm_prompt_view,
+        name="llm_prompt_view",
+
+    )
+    ,
+    path(
+        "import_llm_questions/",
+        views.import_llm_questions,
+        name="import_llm_questions",
+    ),
     #path(
     #    "exam/<int:pk>/scores/<int:cid>/<str:passcode>/",
     #    views.exam_scores_cid_user,

sbas/views.py

@@ -29,6 +29,250 @@ from django.http import Http404, HttpResponseBadRequest, JsonResponse
 from django.http import HttpResponseRedirect, HttpResponse
 
 from .models import Question, Category, Exam, UserAnswer
+from django.views.decorators.http import require_http_methods
+from django.db import transaction
+import re
+import logging
+
+logger = logging.getLogger(__name__)
+
+from loguru import logger
+
+try:
+    import jsonschema
+except Exception:
+    jsonschema = None
+
+
+class LLMImportForm(forms.Form):
+    file = forms.FileField(required=False, help_text="Upload a JSON or JSONL file matching the SBA import schema")
+    raw = forms.CharField(
+        required=False,
+        widget=forms.Textarea(attrs={"rows": 10, "cols": 80}),
+        help_text="Or paste JSON, JSONL (newline-delimited), or multiple JSON documents separated by blank lines",
+    )
+
+
+def _resolve_m2m(model_class, value):
+    """Resolve an item which may be an int (pk) or a string (name/slug).
+    Returns a queryset or empty list of matching objects.
+    """
+    if value is None:
+        return []
+    if isinstance(value, int):
+        try:
+            return [model_class.objects.get(pk=value)]
+        except model_class.DoesNotExist:
+            return []
+    if isinstance(value, str):
+        # try exact name field, then case-insensitive contains
+        qs = model_class.objects.filter(name__iexact=value)
+        if not qs.exists():
+            qs = model_class.objects.filter(name__icontains=value)
+        return list(qs[:5])
+    return []
+
+
+@login_required
+@user_passes_test(lambda u: u.is_superuser)
+@require_http_methods(["GET", "POST"])
+def import_llm_questions(request):
+    """Upload a JSON/JSONL file of LLM-produced questions and import them.
+
+    Only superusers may use this view. The view validates each object against
+    the agreed JSON schema (draft-07) and attempts to resolve M2M references
+    by numeric id or by name. Returns a JSON report of created items and errors.
+    """
+    schema = {
+        "$schema": "http://json-schema.org/draft-07/schema#",
+        "title": "SBA Question",
+        "type": "object",
+        "additionalProperties": False,
+        "required": [
+            "title",
+            "stem",
+            "a_answer",
+            "b_answer",
+            "c_answer",
+            "d_answer",
+            "e_answer",
+            "best_answer",
+            "category",
+        ],
+        "properties": {
+            "title": {"type": "string"},
+            "stem": {"type": "string"},
+            "a_answer": {"type": "string"},
+            "a_feedback": {"type": "string"},
+            "b_answer": {"type": "string"},
+            "b_feedback": {"type": "string"},
+            "c_answer": {"type": "string"},
+            "c_feedback": {"type": "string"},
+            "d_answer": {"type": "string"},
+            "d_feedback": {"type": "string"},
+            "e_answer": {"type": "string"},
+            "e_feedback": {"type": "string"},
+            "feedback": {"type": "string"},
+            "best_answer": {"type": "string", "enum": ["a", "b", "c", "d", "e"]},
+            "category": {"oneOf": [{"type": "string"}]},
+            "finding": {"type": "array", "items": {"oneOf": [{"type": "integer"}, {"type": "string"}]}, "uniqueItems": True},
+            "structure": {"type": "array", "items": {"oneOf": [{"type": "integer"}, {"type": "string"}]}, "uniqueItems": True},
+            "condition": {"type": "array", "items": {"oneOf": [{"type": "integer"}, {"type": "string"}]}, "uniqueItems": True},
+            "presentation": {"type": "array", "items": {"oneOf": [{"type": "integer"}, {"type": "string"}]}, "uniqueItems": True},
+            "subspecialty": {"type": "array", "items": {"oneOf": [{"type": "integer"}, {"type": "string"}]}, "uniqueItems": True},
+        },
+    }
+
+    if request.method == "GET":
+        form = LLMImportForm()
+        return render(request, "sbas/import_llm_questions.html", {"form": form})
+
+    # POST
+    form = LLMImportForm(request.POST, request.FILES)
+    if not form.is_valid():
+        return JsonResponse({"ok": False, "errors": ["No file uploaded or invalid form"]}, status=400)
+
+    raw_text = None
+    if form.cleaned_data.get("raw"):
+        raw_text = form.cleaned_data.get("raw")
+    elif form.cleaned_data.get("file"):
+        f = form.cleaned_data["file"]
+        raw_text = f.read().decode("utf-8")
+    else:
+        return JsonResponse({"ok": False, "errors": ["No file uploaded or text provided"]}, status=400)
+
+    # support: single JSON object, JSON array, JSONL (one JSON object per line),
+    # or multiple JSON documents separated by one or more blank lines.
+    candidates = []
+    # sanitize raw_text by escaping backslashes that are not part of a valid
+    # JSON escape sequence. This handles inputs containing LaTeX-style
+    # sequences such as "\ge" which are invalid JSON (Invalid \escape).
+    def _sanitize_backslashes(s: str):
+        # valid escapes after backslash in JSON: \" \\ \/ \b \f \n \r \t and \uXXXX
+        # This regex finds backslashes not followed by ", \\ , /, b, f, n, r, t, or u
+        pattern = re.compile(r"\\(?!(?:[\"\\/bfnrtu]))")
+        new_s, n = pattern.subn(r"\\\\", s)
+        return new_s, n
+
+    raw_text_stripped = raw_text.strip()
+    raw_text, sanitized_count = _sanitize_backslashes(raw_text_stripped)
+    logger.debug("import_llm_questions: sanitized input length %d (escaped %d backslashes)", len(raw_text), sanitized_count)
+    # Try whole-text JSON first (object or array)
+    parse_error = None
+    try:
+        parsed = json.loads(raw_text)
+        if isinstance(parsed, list):
+            candidates = parsed
+        elif isinstance(parsed, dict):
+            candidates = [parsed]
+    except Exception as e_outer:
+        parse_error = e_outer
+        # Try JSONL: each non-empty line is a JSON object
+        for i, line in enumerate(raw_text.splitlines()):
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                candidates.append(json.loads(line))
+            except Exception:
+                # not JSONL or some lines are multi-line JSON; fallthrough
+                candidates = []
+                break
+
+        # If JSONL didn't produce candidates, try splitting by blank lines
+        if not candidates:
+            blocks = [b.strip() for b in re.split(r"\n\s*\n", raw_text) if b.strip()]
+            if len(blocks) > 1:
+                for i, block in enumerate(blocks):
+                    try:
+                        candidates.append(json.loads(block))
+                    except Exception as e_block:
+                        return JsonResponse({"ok": False, "errors": [f"Invalid JSON in block {i+1}: {e_block}"]}, status=400)
+
+    if not candidates:
+        # If still empty, return the original parse error if present
+        msg = str(parse_error) if parse_error is not None else "No JSON objects found"
+        logger.debug(f"Failed to parse input: {msg}")
+        return JsonResponse({"ok": False, "errors": [f"Failed to parse input: {msg}"]}, status=400)
+
+    report = {"total": len(candidates), "created": 0, "errors": [], "sanitized_backslashes": sanitized_count}
+
+    if jsonschema is None:
+        return JsonResponse({"ok": False, "errors": ["jsonschema library not available in environment"]}, status=500)
+
+    validator = jsonschema.Draft7Validator(schema)
+
+    from atlas.models import Finding, Structure, Condition, Presentation, Subspecialty
+
+    for idx, payload in enumerate(candidates):
+        errors = []
+        for err in validator.iter_errors(payload):
+            errors.append(err.message)
+        if errors:
+            logger.debug(f"Validation errors for item {idx}: {errors}")
+            report["errors"].append({"index": idx, "errors": errors})
+            continue
+
+        # create the Question inside a transaction; partial failures should not leave half-written objects
+        try:
+            with transaction.atomic():
+                q = Question()
+                q.stem = payload.get("stem", "").strip()
+                # map title -> not present in model; use as stem prefix or store in feedback
+                title = payload.get("title")
+                if title:
+                    q.stem = f"<strong>{title}</strong>\n" + q.stem
+
+                q.a_answer = payload.get("a_answer", "").strip()
+                q.a_feedback = payload.get("a_feedback", "")
+                q.b_answer = payload.get("b_answer", "").strip()
+                q.b_feedback = payload.get("b_feedback", "")
+                q.c_answer = payload.get("c_answer", "").strip()
+                q.c_feedback = payload.get("c_feedback", "")
+                q.d_answer = payload.get("d_answer", "").strip()
+                q.d_feedback = payload.get("d_feedback", "")
+                q.e_answer = payload.get("e_answer", "").strip()
+                q.e_feedback = payload.get("e_feedback", "")
+                q.feedback = payload.get("feedback", "")
+                q.best_answer = payload.get("best_answer")
+                # category resolve by name
+                cat_val = payload.get("category")
+                if isinstance(cat_val, str):
+                    cat_obj, created = Category.objects.get_or_create(category=cat_val)
+                    q.category = cat_obj
+                q.save()
+
+                # Resolve M2Ms
+                for key, model_cls in (
+                    ("finding", Finding),
+                    ("structure", Structure),
+                    ("condition", Condition),
+                    ("presentation", Presentation),
+                    ("subspecialty", Subspecialty),
+                ):
+                    vals = payload.get(key) or []
+                    resolved = []
+                    for v in vals:
+                        if isinstance(v, int):
+                            try:
+                                resolved.append(model_cls.objects.get(pk=v))
+                            except model_cls.DoesNotExist:
+                                # skip unknown
+                                continue
+                        elif isinstance(v, str):
+                            qs = model_cls.objects.filter(name__iexact=v)
+                            if not qs.exists():
+                                qs = model_cls.objects.filter(name__icontains=v)
+                            if qs.exists():
+                                resolved.extend(list(qs[:5]))
+                    if resolved:
+                        getattr(q, key).add(*[o.pk for o in resolved])
+
+                report["created"] += 1
+        except Exception as e:
+            report["errors"].append({"index": idx, "errors": [str(e)]})
+
+    return JsonResponse({"ok": True, "report": report})
 
 from django_tables2 import SingleTableView, SingleTableMixin
 from django_filters.views import FilterView
@@ -436,3 +680,7 @@ def exam_clone2(request, exam_id):
     new_exam = exam.clone_model()
     return redirect("sbas:exam_update", pk=new_exam.id)
 
+
+
+def llm_prompt_view(request):
+    return render(request, "sbas/llm_prompt_view.html", {})