feat: support manual add and edit for memory facts (#1538)

* feat: support manual add and edit for memory facts

* fix: restore memory updater save helper

* fix: address memory fact review feedback

* fix: remove duplicate memory fact edit action

* docs: simplify memory fact review setup

* docs: relax memory review startup instructions

* fix: clear rebase marker in memory settings page

* fix: address memory fact review and format issues

* fix: address memory fact review feedback

* refactor: make memory fact updates explicit patch semantics

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>

backend/packages/harness/deerflow/agents/memory/updater.py

@@ -2,6 +2,7 @@
 
 import json
 import logging
+import math
 import re
 import uuid
 from datetime import datetime
@@ -40,12 +41,54 @@ def reload_memory_data(agent_name: str | None = None) -> dict[str, Any]:
 
 def clear_memory_data(agent_name: str | None = None) -> dict[str, Any]:
     """Clear all stored memory data and persist an empty structure."""
-    cleared_memory = _create_empty_memory()
+    cleared_memory = create_empty_memory()
     if not _save_memory_to_file(cleared_memory, agent_name):
         raise OSError("Failed to save cleared memory data")
     return cleared_memory
 
 
+def _validate_confidence(confidence: float) -> float:
+    """Validate persisted fact confidence so stored JSON stays standards-compliant."""
+    if not math.isfinite(confidence) or confidence < 0 or confidence > 1:
+        raise ValueError("confidence")
+    return confidence
+
+
+def create_memory_fact(
+    content: str,
+    category: str = "context",
+    confidence: float = 0.5,
+    agent_name: str | None = None,
+) -> dict[str, Any]:
+    """Create a new fact and persist the updated memory data."""
+    normalized_content = content.strip()
+    if not normalized_content:
+        raise ValueError("content")
+
+    normalized_category = category.strip() or "context"
+    validated_confidence = _validate_confidence(confidence)
+    now = datetime.utcnow().isoformat() + "Z"
+    memory_data = get_memory_data(agent_name)
+    updated_memory = dict(memory_data)
+    facts = list(memory_data.get("facts", []))
+    facts.append(
+        {
+            "id": f"fact_{uuid.uuid4().hex[:8]}",
+            "content": normalized_content,
+            "category": normalized_category,
+            "confidence": validated_confidence,
+            "createdAt": now,
+            "source": "manual",
+        }
+    )
+    updated_memory["facts"] = facts
+
+    if not _save_memory_to_file(updated_memory, agent_name):
+        raise OSError("Failed to save memory data after creating fact")
+
+    return updated_memory
+
+
 def delete_memory_fact(fact_id: str, agent_name: str | None = None) -> dict[str, Any]:
     """Delete a fact by its id and persist the updated memory data."""
     memory_data = get_memory_data(agent_name)
@@ -63,6 +106,47 @@ def delete_memory_fact(fact_id: str, agent_name: str | None = None) -> dict[str,
     return updated_memory
 
 
+def update_memory_fact(
+    fact_id: str,
+    content: str | None = None,
+    category: str | None = None,
+    confidence: float | None = None,
+    agent_name: str | None = None,
+) -> dict[str, Any]:
+    """Update an existing fact and persist the updated memory data."""
+    memory_data = get_memory_data(agent_name)
+    updated_memory = dict(memory_data)
+    updated_facts: list[dict[str, Any]] = []
+    found = False
+
+    for fact in memory_data.get("facts", []):
+        if fact.get("id") == fact_id:
+            found = True
+            updated_fact = dict(fact)
+            if content is not None:
+                normalized_content = content.strip()
+                if not normalized_content:
+                    raise ValueError("content")
+                updated_fact["content"] = normalized_content
+            if category is not None:
+                updated_fact["category"] = category.strip() or "context"
+            if confidence is not None:
+                updated_fact["confidence"] = _validate_confidence(confidence)
+            updated_facts.append(updated_fact)
+        else:
+            updated_facts.append(fact)
+
+    if not found:
+        raise KeyError(fact_id)
+
+    updated_memory["facts"] = updated_facts
+
+    if not _save_memory_to_file(updated_memory, agent_name):
+        raise OSError(f"Failed to save memory data after updating fact '{fact_id}'")
+
+    return updated_memory
+
+
 def _extract_text(content: Any) -> str:
     """Extract plain text from LLM response content (str or list of content blocks).
 

backend/packages/harness/deerflow/client.py

@@ -688,12 +688,35 @@ class DeerFlowClient:
 
         return clear_memory_data()
 
+    def create_memory_fact(self, content: str, category: str = "context", confidence: float = 0.5) -> dict:
+        """Create a single fact manually."""
+        from deerflow.agents.memory.updater import create_memory_fact
+
+        return create_memory_fact(content=content, category=category, confidence=confidence)
+
     def delete_memory_fact(self, fact_id: str) -> dict:
         """Delete a single fact from memory by fact id."""
         from deerflow.agents.memory.updater import delete_memory_fact
 
         return delete_memory_fact(fact_id)
 
+    def update_memory_fact(
+        self,
+        fact_id: str,
+        content: str | None = None,
+        category: str | None = None,
+        confidence: float | None = None,
+    ) -> dict:
+        """Update a single fact manually, preserving omitted fields."""
+        from deerflow.agents.memory.updater import update_memory_fact
+
+        return update_memory_fact(
+            fact_id=fact_id,
+            content=content,
+            category=category,
+            confidence=confidence,
+        )
+
     def get_memory_config(self) -> dict:
         """Get memory system configuration.