Update app.py

app.py

@@ -23,6 +23,83 @@ class ReqGroupingCategory(BaseModel):
 class ReqGroupingResponse(BaseModel):
     categories: List[ReqGroupingCategory]
 
+    model_config = {
+  "categories": [
+    {
+      "id": 1,
+      "title": "Robustness & Resilience",
+      "requirements": [
+        {
+          "context": "Subject to the operator’s policy and regulatory requirements, an AI service provided by the 6G network or UE shall be able to provide information regarding robustness scores.",
+          "requirement": "Expose an overall robustness score to service consumers."
+        },
+        {
+          "context": "The network can respond with a missings-resilience score for the used AI application.",
+          "requirement": "Report a missings-resilience score that quantifies tolerance to missing or corrupted input data."
+        }
+      ]
+    },
+    {
+      "id": 2,
+      "title": "Environmental Sustainability",
+      "requirements": [
+        {
+          "context": "What is the level of energy consumption per information request (per inference run of the AI).",
+          "requirement": "Report energy consumption per 1 000 inference requests."
+        },
+        {
+          "context": "What is the portion of renewable energy of the energy consumed by the AI service.",
+          "requirement": "Report the share of renewable energy in the AI service’s power mix."
+        },
+        {
+          "context": "The application sets a requirement for the energy consumption needed for inference.",
+          "requirement": "Allow the consumer to specify a maximum energy-per-inference threshold that must be met."
+        }
+      ]
+    },
+    {
+      "id": 3,
+      "title": "Explainability & Transparency",
+      "requirements": [
+        {
+          "context": "Local explanation: The aim is to explain individual outputs provided by an ML model.",
+          "requirement": "Support local explanations for single predictions."
+        },
+        {
+          "context": "Global explanation: The aim is to explain the whole ML model behaviour.",
+          "requirement": "Support global explanations that describe overall model logic."
+        },
+        {
+          "context": "Third-party applications have explanations of AI agent reasoning.",
+          "requirement": "Provide on-demand reasoning for predictions to authorised consumers."
+        }
+      ]
+    },
+    {
+      "id": 4,
+      "title": "Service Discovery & Criteria Negotiation",
+      "requirements": [
+        {
+          "context": "A subscriber density prediction service is offered via an exposure interface.",
+          "requirement": "Ensure AI services are discoverable through the exposure interface."
+        },
+        {
+          "context": "The application requests further profile information regarding robustness, sustainability and explainability aspects.",
+          "requirement": "Expose a profile that includes robustness, sustainability and explainability metrics."
+        },
+        {
+          "context": "A service consumer shall be able to provide service criteria regarding robustness, environmental sustainability, and explainability when requesting an AI service to the 6G system.",
+          "requirement": "Accept consumer-supplied criteria for robustness, sustainability and explainability."
+        },
+        {
+          "context": "In some cases the AI service could not be fulfilled, or could fall back to a non-AI mechanism if the criteria cannot be met.",
+          "requirement": "Support rejection or graceful fallback when agreed criteria are not satisfied."
+        }
+      ]
+    }
+  ]
+}
+
 
 # ---- Solution Models ----