Update to the graph view

app.py

@@ -142,7 +142,7 @@ class UI:
                 outputs=[self.assessed_risk_definition, self.relatedrisks, self.mitigations, self.benchmarks, self.mitigations_text, self.networks]
             ).then(
                 fn=mitigations,
-                inputs=[self.assessed_risks, self.taxonomy], 
+                inputs=[self.usecase, self.assessed_risks, self.taxonomy], 
                 # NOTETOSELF: Intent based risk is stored in self.risk (if needed)
                 outputs=[self.assessed_risk_definition, self.relatedrisks, self.mitigations, self.benchmarks, self.mitigations_text, self.networks]
             )

executor.py

@@ -26,39 +26,41 @@ def clear_previous_risks():
 def clear_previous_mitigations():
      return "", gr.Dataset(samples=[], sample_labels=[], visible=False), gr.DataFrame([], wrap=True, show_copy_button=True, show_search="search", visible=False), gr.DataFrame([], wrap=True, show_copy_button=True, show_search="search", visible=False), gr.Markdown(" "), gr.Markdown(" ")
 
-def generate_subgraph(risk):
+def generate_subgraph(usecase, risk):
     lines =[f'```mermaid\n', '---\n'
 'config:\n'
-'  layout: "tidy-tree"\n'
-'---\n',
-'mindmap\n']
+'  theme: mc\n'
+'  layout: dagre\n'
+'  look: classic\n'
+'---\n'
+'flowchart TB\n']
+    
+    lines.append(f'uc_173@{{ label: "{usecase}" }} -- subClassOf --> AISystem["AISystem"]\n')
+    lines.append(f'uc_173 -- hasRisk --> Risk2["{risk.name}"]\n')
+    lines.append(f'Risk2 -- isPartOf --> {risk.isPartOf}\n')
+    lines.append(f'Risk2 -- isDefinedByTaxonomy --> {risk.isDefinedByTaxonomy}\n')
     
-    lines.append(f'  root(("{risk.name}"))\n')
-    # origin info
-    lines.append(f'    Origins\n')
-    lines.append(f'      Riskgroup: {risk.isPartOf}\n')
-    lines.append(f'      Taxonomy: {risk.isDefinedByTaxonomy}\n')
-
     # add related risks
     rrs = ran.get_related_risks(id=risk.id)
     if len(rrs) > 0:
-        lines.append(f'    Related Risks\n')
+        r_risks = ''
         for rr in rrs:
-            lines.append(f'      {rr.name}\n')
-    
+            r_risks = r_risks + f'{rr.name}, '
+        lines.append(f'Risk2 -- hasRelatedRisks --> Risk3["{r_risks}"]\n')
+
     # add related evals
     revals = ran.get_related_evaluations(risk_id=risk.id)
     if len(revals) > 0:
-        lines.append(f'    Related AI evaluations\n')
+        r_evals =''
         for reval in revals:
-            lines.append(f'      {reval.name}\n')
+            r_evals = r_evals + f'{reval.name}, '
+        lines.append(f'Risk2 -- hasAiEvaluations --> Risk4["{r_evals[:100]}"] \n')
     
     # add related mitigations
     rmits = get_controls_and_actions(risk.id, risk.isDefinedByTaxonomy)
     if len(rmits) > 0:
-        lines.append(f'    Related mitigations\n')
-        for rmit in rmits:
-            lines.append(f'      {rmit}\n')
+        r_mits = ', '.join(rmits)
+        lines.append(f'Risk2 -- hasMitigations --> Risk5["{r_mits[:100]}"] \n')
 
     lines.append(f"```")
     diagram_string = "".join(lines)
@@ -172,7 +174,7 @@ def get_controls_and_actions(riskid, taxonomy):
 
 
 @lru_cache
-def mitigations(riskid: str, taxonomy: str) -> tuple[gr.Markdown, gr.Dataset, gr.DataFrame, gr.DataFrame, gr.Markdown, gr.Markdown]:
+def mitigations(usecase: str, riskid: str, taxonomy: str) -> tuple[gr.Markdown, gr.Dataset, gr.DataFrame, gr.DataFrame, gr.Markdown, gr.Markdown]:
     """
     For a specific risk (riskid), returns
     (a) a risk description
@@ -264,7 +266,7 @@ def mitigations(riskid: str, taxonomy: str) -> tuple[gr.Markdown, gr.Dataset, gr
     
     status = gr.Markdown(" ") if len(mitdf) > 0 else gr.Markdown("No mitigations found.")
 
-    fig = gr.Markdown(" ") if not selected_risk else generate_subgraph(selected_risk)
+    fig = gr.Markdown(" ") if not selected_risk else generate_subgraph(usecase, selected_risk)
 
     return (gr.Markdown(risk_sec), 
             gr.Dataset(samples=samples, label=label, sample_labels=sample_labels, visible=True),