Add Step 5 flat context and txtai file tools for agents

backend/services/intelligence/sif_agents.py

@@ -15,6 +15,7 @@ from loguru import logger
 from .txtai_service import TxtaiIntelligenceService, TXTAI_AVAILABLE
 from services.intelligence.agents.core_agent_framework import BaseALwrityAgent
 from services.llm_providers.main_text_generation import llm_text_gen
+from services.intelligence.agent_flat_context import AgentFlatContextStore
 
 # Optional txtai imports (align with core agent framework)
 try:
@@ -170,8 +171,8 @@ class SIFBaseAgent(BaseALwrityAgent):
 
     def _create_txtai_agent(self):
         """
-        SIF agents primarily use the intelligence service directly, but we can expose
-        capabilities via a standard agent interface if available.
+        Expose a txtai Agent interface with flat-file context tools.
+        Tools are scoped to the current user workspace via AgentFlatContextStore.
         """
         if not TXTAI_AVAILABLE or Agent is None:
             raise RuntimeError(f"[{self.__class__.__name__}] txtai Agent not available")
@@ -180,11 +181,103 @@ class SIFBaseAgent(BaseALwrityAgent):
             _llm_for_agent = self.llm
             for _ in range(3):
                 _llm_for_agent = getattr(_llm_for_agent, "llm", _llm_for_agent)
-            return Agent(llm=_llm_for_agent, tools=[])
+
+            return Agent(
+                llm=_llm_for_agent,
+                tools=[
+                    {
+                        "name": "flat_context_manifest",
+                        "description": "Returns manifest of available onboarding flat-context documents for this user",
+                        "target": self._tool_flat_context_manifest,
+                    },
+                    {
+                        "name": "flat_context_read",
+                        "description": "Read a flat-context document by logical name: step2|step3|step4|step5|manifest",
+                        "target": self._tool_flat_context_read,
+                    },
+                    {
+                        "name": "flat_context_write_note",
+                        "description": "Write lightweight agent notes/updates to a specific flat-context document",
+                        "target": self._tool_flat_context_write_note,
+                    },
+                ],
+            )
         except Exception as e:
             logger.error(f"[{self.__class__.__name__}] Failed to create txtai Agent: {e}")
             raise
 
+    def _tool_flat_context_manifest(self, context: Dict[str, Any]) -> Dict[str, Any]:
+        """Tool: list available flat-context docs and links."""
+        try:
+            store = AgentFlatContextStore(self.user_id)
+            manifest = store.load_context_manifest() or {"documents": []}
+            return {"ok": True, "manifest": manifest}
+        except Exception as e:
+            return {"ok": False, "error": str(e)}
+
+    def _tool_flat_context_read(self, context: Dict[str, Any]) -> Dict[str, Any]:
+        """Tool: read one user-scoped context doc."""
+        try:
+            key = str((context or {}).get("document") or "").strip().lower()
+            store = AgentFlatContextStore(self.user_id)
+            mapping = {
+                "step2": store.load_step2_context_document,
+                "step3": store.load_step3_context_document,
+                "step4": store.load_step4_context_document,
+                "step5": store.load_step5_context_document,
+                "manifest": store.load_context_manifest,
+            }
+            if key not in mapping:
+                return {"ok": False, "error": "Invalid document. Use step2|step3|step4|step5|manifest"}
+            data = mapping[key]()
+            return {"ok": True, "document": key, "data": data or {}}
+        except Exception as e:
+            return {"ok": False, "error": str(e)}
+
+    def _tool_flat_context_write_note(self, context: Dict[str, Any]) -> Dict[str, Any]:
+        """Tool: append agent note/update to step context by re-saving payload."""
+        try:
+            key = str((context or {}).get("document") or "").strip().lower()
+            note = str((context or {}).get("note") or "").strip()
+            if not note:
+                return {"ok": False, "error": "note is required"}
+
+            store = AgentFlatContextStore(self.user_id)
+            if key == "step2":
+                doc = store.load_step2_context_document() or {}
+                payload = doc.get("data") if isinstance(doc.get("data"), dict) else {}
+                notes = payload.get("agent_notes") if isinstance(payload.get("agent_notes"), list) else []
+                notes.append({"note": note, "agent": self.agent_type, "ts": datetime.utcnow().isoformat()})
+                payload["agent_notes"] = notes[-50:]
+                ok = store.save_step2_website_analysis(payload, source="agent_note")
+            elif key == "step3":
+                doc = store.load_step3_context_document() or {}
+                payload = doc.get("data") if isinstance(doc.get("data"), dict) else {}
+                notes = payload.get("agent_notes") if isinstance(payload.get("agent_notes"), list) else []
+                notes.append({"note": note, "agent": self.agent_type, "ts": datetime.utcnow().isoformat()})
+                payload["agent_notes"] = notes[-50:]
+                ok = store.save_step3_research_preferences(payload, source="agent_note")
+            elif key == "step4":
+                doc = store.load_step4_context_document() or {}
+                payload = doc.get("data") if isinstance(doc.get("data"), dict) else {}
+                notes = payload.get("agent_notes") if isinstance(payload.get("agent_notes"), list) else []
+                notes.append({"note": note, "agent": self.agent_type, "ts": datetime.utcnow().isoformat()})
+                payload["agent_notes"] = notes[-50:]
+                ok = store.save_step4_persona_data(payload, source="agent_note")
+            elif key == "step5":
+                doc = store.load_step5_context_document() or {}
+                payload = doc.get("data") if isinstance(doc.get("data"), dict) else {}
+                notes = payload.get("agent_notes") if isinstance(payload.get("agent_notes"), list) else []
+                notes.append({"note": note, "agent": self.agent_type, "ts": datetime.utcnow().isoformat()})
+                payload["agent_notes"] = notes[-50:]
+                ok = store.save_step5_integrations(payload, source="agent_note")
+            else:
+                return {"ok": False, "error": "Invalid document. Use step2|step3|step4|step5"}
+
+            return {"ok": bool(ok), "document": key}
+        except Exception as e:
+            return {"ok": False, "error": str(e)}
+
 class StrategyArchitectAgent(SIFBaseAgent):
     """Agent for discovering content pillars and identifying strategic gaps."""
     
@@ -686,7 +779,25 @@ class ContentGuardianAgent(SIFBaseAgent):
             if not text:
                 return {"compliance_score": 0.0, "issues": ["No text provided"]}
 
-            # 1. Fetch Style Guidelines from SIF if not provided
+            guidelines_source = "provided" if style_guidelines else "none"
+
+            # 1. Fetch Style Guidelines from flat-file context first, then SIF fallback
+            if not style_guidelines:
+                try:
+                    flat_doc = AgentFlatContextStore(self.user_id).load_step2_context_document()
+                    flat_data = (flat_doc or {}).get("data") if isinstance(flat_doc, dict) else None
+                    if isinstance(flat_data, dict):
+                        style_guidelines = {
+                            "tone": (flat_data.get("brand_analysis") or {}).get("brand_voice", "neutral"),
+                            "style_patterns": flat_data.get("style_patterns", {}),
+                            "writing_style": flat_data.get("writing_style", {}),
+                            "style_guidelines": flat_data.get("style_guidelines", {}),
+                        }
+                        guidelines_source = "flat_file"
+                        logger.info(f"[{self.__class__.__name__}] Retrieved style guidelines from flat context")
+                except Exception as e:
+                    logger.warning(f"[{self.__class__.__name__}] Failed to retrieve style guidelines from flat context: {e}")
+
             if not style_guidelines and self.sif_service:
                 try:
                     # Search for website analysis to get brand voice/style
@@ -697,7 +808,7 @@ class ContentGuardianAgent(SIFBaseAgent):
                         res = results[0]
                         metadata_str = res.get('object')
                         metadata = json.loads(metadata_str) if isinstance(metadata_str, str) else (metadata_str or res)
-                        
+
                         if metadata.get('type') == 'website_analysis':
                             report = metadata.get('full_report', {})
                             style_guidelines = {
@@ -705,6 +816,7 @@ class ContentGuardianAgent(SIFBaseAgent):
                                 "style_patterns": report.get('style_patterns', {}),
                                 "writing_style": report.get('writing_style', {})
                             }
+                            guidelines_source = "sif_index"
                             logger.info(f"[{self.__class__.__name__}] Retrieved style guidelines from SIF: {style_guidelines.get('tone')}")
                 except Exception as e:
                     logger.warning(f"[{self.__class__.__name__}] Failed to retrieve style guidelines from SIF: {e}")
@@ -735,7 +847,7 @@ class ContentGuardianAgent(SIFBaseAgent):
                 "compliance_score": max(0.0, score),
                 "issues": issues,
                 "is_compliant": score > 0.8,
-                "guidelines_source": "sif_index" if not style_guidelines and self.sif_service else "provided"
+                "guidelines_source": guidelines_source
             }
             
         except Exception as e: