feat: Complete code integration of modules (#18)

The complete code integration is done.

Co-authored-by: Sagnik <sagnik7896@gmail.com>
Reviewed-on: #18

backend/oracle/prompt_orchestrator.py

@@ -16,6 +16,8 @@ from typing import Any
 from .policy_service import PolicyContext, PolicyService
 from .canvas_service import canvas_service
 from .data_access_gateway import data_access_gateway
+from .persona_service import persona_service
+from backend.services.nemoclaw_runtime import nemoclaw_runtime
 
 try:
     import asyncpg  # type: ignore
@@ -177,6 +179,19 @@ class PromptOrchestrator:
 
         execution["retrievalPlan"] = retrieval_plan
 
+        persona_plan = await persona_service.plan_for_prompt(
+            prompt=prompt,
+            tenant_id=tenant_id,
+            actor_role=actor_role,
+        )
+        execution["personaPlan"] = persona_plan
+        execution["workflowDispatch"] = nemoclaw_runtime.build_workflow_dispatch(
+            prompt=prompt,
+            tenant_id=tenant_id,
+            actor_role=actor_role,
+            component_templates=persona_plan["recommendedTemplates"],
+        )
+
         # ── Step 2: Policy validation ─────────────────────────────────────────
         policy_errors = []
         for component_plan in retrieval_plan.get("components", []):
@@ -209,6 +224,7 @@ class PromptOrchestrator:
             branch_id=branch_id,
             placement_mode=placement_mode,
             ctx=ctx,
+            persona_plan=persona_plan,
         )
         execution["visualizationPlan"] = viz_plan
 
@@ -255,9 +271,18 @@ class PromptOrchestrator:
         branch_id: str,
         placement_mode: str,
         ctx: PolicyContext,
+        persona_plan: dict[str, Any],
     ) -> dict[str, Any]:
         """Converts a retrieval plan into a list of CanvasComponent descriptors."""
-        components = []
+        components = [
+            self._persona_text_canvas(
+                execution_id=execution_id,
+                actor_id=actor_id,
+                branch_id=branch_id,
+                prompt=prompt,
+                persona_plan=persona_plan,
+            )
+        ]
         base_order = 900  # Append after existing components
 
         component_plans = retrieval_plan.get("components", [])
@@ -343,6 +368,85 @@ class PromptOrchestrator:
 
         return {"components": components}
 
+    @staticmethod
+    def _persona_text_canvas(
+        *,
+        execution_id: str,
+        actor_id: str,
+        branch_id: str,
+        prompt: str,
+        persona_plan: dict[str, Any],
+    ) -> dict[str, Any]:
+        recommended = ", ".join(persona_plan.get("recommendedTemplates", [])) or "no direct template matches"
+        content = (
+            f"Oracle received: {prompt}\n\n"
+            f"Reusable templates: {recommended}\n\n"
+            "Execution policy: query live CRM data first, reuse matching templates, "
+            "synthesize missing UI blocks, then dispatch the required ComfyUI-backed workflow."
+        )
+        return {
+            "componentId": str(uuid.uuid4()),
+            "type": "textCanvas",
+            "title": "Oracle Planning Notes",
+            "description": "Persona-driven guidance generated before data-bound components.",
+            "dataSourceDescriptor": {
+                "descriptorId": str(uuid.uuid4()),
+                "sourceType": "inline",
+                "connectorId": "oracle-persona",
+                "dataset": "oracle_persona_plan",
+                "authContextRef": f"authctx_{actor_id}_scope",
+                "queryTemplate": "",
+                "queryParameters": {},
+                "rowLimit": 1,
+                "privacyTier": "standard",
+            },
+            "visualizationParameters": {
+                "content": content,
+                "widthMode": "full",
+                "adjustableHeight": True,
+            },
+            "dataBindings": {"dimensions": [], "measures": [], "series": [], "filters": []},
+            "version": 1,
+            "lifecycleState": "active",
+            "provenance": {
+                "originType": "prompt_generated",
+                "promptExecutionId": execution_id,
+                "sourceBranchId": branch_id,
+                "createdBy": actor_id,
+                "createdAt": _now(),
+            },
+            "renderingHints": {"estimatedHeightPx": 180, "skeletonVariant": "text", "virtualizationPriority": 4},
+            "layout": {
+                "orderIndex": 910,
+                "sectionId": "sec_prompt_generated",
+                "widthMode": "full",
+                "minHeightPx": 180,
+                "stickyHeader": False,
+            },
+            "accessControls": {
+                "visibilityScope": "private",
+                "allowedRoles": ["senior_broker", "sales_director", "marketing_operator", "data_steward", "compliance_reviewer", "platform_admin"],
+                "redactionPolicy": "none",
+            },
+            "styleSignature": {
+                "theme": "velocity_glass",
+                "paletteToken": "ocean_signal",
+                "motionProfile": "calm_reveal",
+                "density": "comfortable",
+                "radiusScale": "lg",
+                "typographyScale": "balanced",
+            },
+            "validationState": {
+                "schema": "pass",
+                "policy": "pass",
+                "a11y": "pass",
+                "performance": "pass",
+                "status": "validated",
+            },
+            "auditLog": [f"aud_{execution_id}_persona"],
+            "dataRows": [],
+        }
+
     @staticmethod
     def _map_type(plan_type: str) -> str:
         mapping = {