Backend features: - Tree sharing via secure tokens with expiration (Issue #16) - Draft tree status with conditional validation (Issue #25) - Save session as custom tree with fork tracking (Issue #17) - Tree validation system for publish requirements - Session-to-tree conversion preserving custom steps Database migrations: - 024: Tree sharing (tree_shares table, visibility field) - 025: Tree status field (draft/published) - 25b: Merge migration for indexes New endpoints: - POST /api/v1/trees/{id}/share - Generate share token - GET /api/v1/shared/{token} - Public tree access - POST /api/v1/trees/{id}/can-publish - Validate tree - POST /api/v1/sessions/{id}/save-as-tree - Convert session Test coverage: - 20 tests for draft trees functionality - 14 tests for session-to-tree conversion - 15 tests for tree sharing Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
207 lines
6.1 KiB
Python
207 lines
6.1 KiB
Python
"""Helper module to convert sessions into tree structures."""
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import uuid
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from typing import Any
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def convert_session_to_tree(
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session_path: list[str],
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tree_snapshot: dict[str, Any],
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custom_steps: list[dict[str, Any]],
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decisions: list[dict[str, Any]]
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) -> dict[str, Any]:
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"""Convert a session's path and custom steps into a linear tree structure.
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Creates a linear decision tree that represents the path taken through the
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original tree, including any custom steps inserted during the session.
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Args:
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session_path: List of node IDs representing the path taken
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tree_snapshot: Original tree structure (for node details)
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custom_steps: Custom steps inserted during session
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decisions: Decision records with answers and notes
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Returns:
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Tree structure dict representing the linear path
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"""
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if not session_path:
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# Return minimal valid tree if no path taken
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return {
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"id": str(uuid.uuid4()),
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"type": "solution",
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"solution": "Session had no recorded path",
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"children": []
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}
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# Build a map of custom steps by their ID
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custom_steps_map = {}
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for step in custom_steps:
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if "id" in step:
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custom_steps_map[step["id"]] = step
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# Build a map of decisions by node_id for quick lookup
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decisions_map = {}
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for decision in decisions:
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if "node_id" in decision:
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decisions_map[decision["node_id"]] = decision
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# Build the linear tree structure
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root_node = None
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current_node = None
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for i, node_id in enumerate(session_path):
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# Check if this is a custom step
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if node_id in custom_steps_map:
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step = custom_steps_map[node_id]
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new_node = _create_node_from_custom_step(step, node_id)
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else:
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# Find node in original tree
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original_node = _find_node_in_tree(tree_snapshot, node_id)
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if original_node:
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new_node = _create_node_from_original(original_node, decisions_map.get(node_id))
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else:
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# Node not found, create a placeholder
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new_node = {
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"id": node_id,
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"type": "action",
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"action": f"Step from original tree (node {node_id})",
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"children": []
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}
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# Add notes from decision if available
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decision = decisions_map.get(node_id)
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if decision and decision.get("notes"):
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new_node["notes"] = decision["notes"]
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# Build the chain
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if root_node is None:
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root_node = new_node
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current_node = root_node
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else:
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current_node["children"] = [new_node]
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current_node = new_node
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return root_node
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def _find_node_in_tree(tree: dict[str, Any], node_id: str) -> dict[str, Any] | None:
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"""Recursively find a node in the tree structure by ID.
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Args:
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tree: Tree structure dict
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node_id: Node ID to find
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Returns:
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Node dict if found, None otherwise
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"""
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if tree.get("id") == node_id:
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return tree
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for child in tree.get("children", []):
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result = _find_node_in_tree(child, node_id)
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if result:
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return result
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return None
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def _create_node_from_original(
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original_node: dict[str, Any],
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decision: dict[str, Any] | None = None
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) -> dict[str, Any]:
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"""Create a new node based on an original tree node.
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Args:
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original_node: Original node from tree
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decision: Decision record for this node (optional)
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Returns:
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New node dict for the linear tree
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"""
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node_type = original_node.get("type", "action")
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new_node = {
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"id": str(uuid.uuid4()), # Generate new ID for the saved tree
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"type": node_type,
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"children": []
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}
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# Copy relevant content based on node type
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if node_type == "decision":
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new_node["question"] = original_node.get("question", "")
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if decision and decision.get("answer"):
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new_node["question"] += f"\n\nAnswer: {decision['answer']}"
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elif node_type == "action":
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new_node["action"] = original_node.get("action", "")
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if decision and decision.get("action_performed"):
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new_node["action"] = decision["action_performed"]
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elif node_type == "solution":
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new_node["solution"] = original_node.get("solution", "")
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return new_node
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def _create_node_from_custom_step(
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custom_step: dict[str, Any],
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step_id: str
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) -> dict[str, Any]:
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"""Create a node from a custom step.
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Args:
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custom_step: Custom step dict
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step_id: ID of the custom step
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Returns:
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Node dict for the linear tree
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"""
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step_type = custom_step.get("type", "action")
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content = custom_step.get("content", "")
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new_node = {
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"id": str(uuid.uuid4()),
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"type": step_type,
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"children": []
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}
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# Map content to appropriate field based on type
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if step_type == "decision":
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new_node["question"] = content
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elif step_type == "action":
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new_node["action"] = content
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elif step_type == "solution":
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new_node["solution"] = content
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# Add notes if present
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if custom_step.get("notes"):
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if step_type == "decision":
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new_node["question"] += f"\n\nNotes: {custom_step['notes']}"
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elif step_type == "action":
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new_node["action"] += f"\n\nNotes: {custom_step['notes']}"
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elif step_type == "solution":
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new_node["solution"] += f"\n\nNotes: {custom_step['notes']}"
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return new_node
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def generate_tree_name_from_session(
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original_tree_name: str,
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ticket_number: str | None = None,
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client_name: str | None = None
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) -> str:
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"""Generate a descriptive name for the saved tree.
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Args:
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original_tree_name: Name of the original tree
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ticket_number: Optional ticket number
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client_name: Optional client name
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Returns:
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Generated tree name
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"""
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parts = [original_tree_name, "Session"]
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if ticket_number:
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parts.append(f"(Ticket {ticket_number})")
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if client_name:
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parts.append(f"- {client_name}")
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return " ".join(parts)
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