feat: add delta response parsing and action-type prompt dispatch

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/core/ai_chat_service.py

@@ -284,6 +284,92 @@ def _strip_markdown_fences(text: str) -> str:
     return text
 
 
+def _parse_delta(response: str) -> dict | None:
+    """Extract [DELTA]...[/DELTA] JSON from AI response."""
+    match = re.search(r'\[DELTA\](.*?)\[/DELTA\]', response, re.DOTALL)
+    if not match:
+        return None
+    raw = _strip_markdown_fences(match.group(1).strip())
+    try:
+        return json.loads(raw)
+    except json.JSONDecodeError:
+        return None
+
+
+def _find_node_by_id(tree: dict, node_id: str) -> dict | None:
+    """Find a node by ID in a tree structure (recursive)."""
+    if tree.get("id") == node_id:
+        return tree
+    for child in tree.get("children", []):
+        found = _find_node_by_id(child, node_id)
+        if found:
+            return found
+    for step in tree.get("steps", []):
+        if step.get("id") == node_id:
+            return step
+    return None
+
+
+def _build_action_prompt(
+    action_type: str,
+    focal_node_id: str | None,
+    tree_structure: dict,
+    flow_type: str,
+) -> str:
+    """Build action-specific system prompt supplement."""
+    tree_json = json.dumps(tree_structure, indent=2)
+
+    focal_context = ""
+    if focal_node_id:
+        focal_node = _find_node_by_id(tree_structure, focal_node_id)
+        if focal_node:
+            focal_context = f"\n\nFOCAL NODE (the node being acted on):\n{json.dumps(focal_node, indent=2)}"
+
+    prompts = {
+        "generate_branch": (
+            f"Generate a complete branch of child nodes for the focal node. "
+            f"Return the new nodes wrapped in [DELTA]...[/DELTA] markers as JSON with "
+            f"action='add', target_node_id='{focal_node_id}', and nodes array."
+            f"{focal_context}"
+        ),
+        "modify_node": (
+            f"Modify the focal node based on the user's instruction. "
+            f"Return the updated node in [DELTA]...[/DELTA] markers with action='modify'."
+            f"{focal_context}"
+        ),
+        "add_steps": (
+            f"Generate new procedural steps to insert after the focal step. "
+            f"Return them in [DELTA]...[/DELTA] markers with action='add'."
+            f"{focal_context}"
+        ),
+        "quick_action": (
+            f"Respond to the user's quick action request about the focal node. "
+            f"If the action modifies the node, return changes in [DELTA]...[/DELTA] markers. "
+            f"If it's informational (e.g. explain), just respond in text."
+            f"{focal_context}"
+        ),
+        "open_chat": (
+            "Have a helpful conversation about the flow. If the user asks for changes, "
+            "return them in [DELTA]...[/DELTA] markers. Otherwise respond in text."
+        ),
+        "generate_full": (
+            "Generate a complete flow structure based on the user's description."
+        ),
+        "variable_inference": (
+            "Analyze the procedural steps for implicit variables. Look for references to "
+            "specific servers, clients, credentials, or other values that should be captured "
+            "in an intake form. Return suggestions as JSON."
+        ),
+    }
+
+    action_prompt = prompts.get(action_type, prompts["open_chat"])
+
+    return (
+        f"CURRENT FLOW STRUCTURE ({flow_type}):\n{tree_json}\n\n"
+        f"ACTION: {action_type}\n{action_prompt}"
+    )
+
+
 def _parse_ai_response(raw_response: str) -> dict[str, Any]:
     """Parse structured markers from AI response.