Files
DocsGPT/application/api/user/workflows/routes.py
T
Alex 23e249fca1 fix(workflows): validate CEL at save time and document which fields use it
Workflows ship two expression languages in adjacent fields. Agent
`prompt_template` and end `output_template` are Jinja2, so `{{query}}` is
correct there. State and condition `expression` fields are bare CEL,
where the same string is a parse error.

Nothing told users this. docs/content/Agents/nodes.mdx documented the
pre-CEL Set State node with `{{variable_name}}` examples and Set /
Increment / Append operations that no longer exist — "CEL" appeared
nowhere in the docs. The builder's own placeholder was `input.foo + 1`,
referencing an `input` namespace that is not in workflow state, while the
panel beside it advertised `{{ agent.variable }}`.

There was also no validation anywhere: neither validateWorkflow nor
validate_workflow_structure looked at state nodes at all, and conditions
were only checked for a non-empty string. A workflow containing
`{{query}}` saved and published clean, then aborted on the first message
with a bare caret dump that sanitize_api_error collapsed into "An error
occurred … please try again later" — advice that sends the user round the
same loop, which is what the 2026-08-01 report shows.

Adds validate_cel_expression (compile-only, since state is built at run
time and unresolved names are not knowable when saving) and wires it into
the workflow save path for both node types, plus the half-configured
state operations the engine silently skips. `{{ }}` gets a targeted hint,
raised only after compilation has already failed so valid CEL that
contains braces — `x == "{{y}}"`, or a nested map literal — is not
rejected.

celpy errors are now summarized: undeclared-reference messages embed a
repr of the entire activation, thousands of characters including the
user's own query, and others interpolate the offending state value.
Quoted fragments that are not bare identifiers are redacted, since
config errors now bypass sanitize_api_error to reach the user, and a
shared agent's runner is not its owner.

Docs rewritten with a table of which field takes which syntax, CEL
examples for Set State, and the Condition node section that basics.mdx
has been linking to all along.
2026-08-05 11:26:23 +01:00

594 lines
23 KiB
Python

"""Workflow management routes."""
from typing import Any, Dict, List, Optional, Set
from flask import current_app, request
from flask_restx import Namespace, Resource
from application.agents.workflows.cel_evaluator import (
CelEvaluationError,
validate_cel_expression,
)
from application.storage.db.base_repository import looks_like_uuid
from application.storage.db.repositories.workflow_edges import WorkflowEdgesRepository
from application.storage.db.repositories.workflow_nodes import WorkflowNodesRepository
from application.storage.db.repositories.workflows import WorkflowsRepository
from application.storage.db.session import db_readonly, db_session
from application.core.json_schema_utils import (
JsonSchemaValidationError,
normalize_json_schema_payload,
)
from application.core.model_utils import get_model_capabilities
from application.api.user.utils import (
error_response,
get_user_id,
require_auth,
require_fields,
success_response,
)
workflows_ns = Namespace("workflows", path="/api")
def _workflow_error_response(message: str, err: Exception):
current_app.logger.error(f"{message}: {err}", exc_info=True)
return error_response(message)
def _resolve_workflow(repo: WorkflowsRepository, workflow_id: str, user_id: str):
"""Resolve a workflow by UUID or legacy Mongo id, scoped to user."""
if not workflow_id:
return None
if looks_like_uuid(workflow_id):
row = repo.get(workflow_id, user_id)
if row is not None:
return row
return repo.get_by_legacy_id(workflow_id, user_id)
def _write_graph(
conn,
pg_workflow_id: str,
graph_version: int,
nodes_data: List[Dict],
edges_data: List[Dict],
) -> List[Dict]:
"""Bulk-create nodes + edges for one graph version. Uses ON CONFLICT upsert.
Edges arrive with source/target as user-provided node-id strings. We
insert nodes first, capture their ``node_id → UUID`` map, then
translate edges before insertion. Edges referencing missing nodes are
dropped with a warning.
"""
nodes_repo = WorkflowNodesRepository(conn)
edges_repo = WorkflowEdgesRepository(conn)
if nodes_data:
created_nodes = nodes_repo.bulk_create(
pg_workflow_id, graph_version,
[
{
"node_id": n["id"],
"node_type": n["type"],
"title": n.get("title", ""),
"description": n.get("description", ""),
"position": n.get("position", {"x": 0, "y": 0}),
"config": n.get("data", {}),
}
for n in nodes_data
],
)
node_uuid_by_str = {n["node_id"]: n["id"] for n in created_nodes}
else:
created_nodes = []
node_uuid_by_str = {}
if edges_data:
translated_edges: List[Dict] = []
for e in edges_data:
src = e.get("source")
tgt = e.get("target")
from_uuid = node_uuid_by_str.get(src)
to_uuid = node_uuid_by_str.get(tgt)
if not from_uuid or not to_uuid:
current_app.logger.warning(
"Workflow graph write: dropping edge %s; node refs unresolved "
"(source=%s, target=%s)",
e.get("id"), src, tgt,
)
continue
translated_edges.append({
"edge_id": e["id"],
"from_node_id": from_uuid,
"to_node_id": to_uuid,
"source_handle": e.get("sourceHandle"),
"target_handle": e.get("targetHandle"),
})
if translated_edges:
edges_repo.bulk_create(
pg_workflow_id, graph_version, translated_edges,
)
return created_nodes
def serialize_workflow(w: Dict) -> Dict:
"""Serialize workflow row to API response format."""
created_at = w.get("created_at")
updated_at = w.get("updated_at")
return {
"id": str(w["id"]),
"name": w.get("name"),
"description": w.get("description"),
"created_at": created_at.isoformat() if hasattr(created_at, "isoformat") else created_at,
"updated_at": updated_at.isoformat() if hasattr(updated_at, "isoformat") else updated_at,
}
def serialize_node(n: Dict) -> Dict:
"""Serialize workflow node row to API response format."""
return {
"id": n["node_id"],
"type": n["node_type"],
"title": n.get("title"),
"description": n.get("description"),
"position": n.get("position"),
"data": n.get("config", {}) or {},
}
def serialize_edge(e: Dict) -> Dict:
"""Serialize workflow edge row to API response format."""
return {
"id": e["edge_id"],
"source": e.get("source_id"),
"target": e.get("target_id"),
"sourceHandle": e.get("source_handle"),
"targetHandle": e.get("target_handle"),
}
def get_workflow_graph_version(workflow: Dict) -> int:
"""Get current graph version with fallback."""
raw_version = workflow.get("current_graph_version", 1)
try:
version = int(raw_version)
return version if version > 0 else 1
except (ValueError, TypeError):
return 1
def validate_json_schema_payload(
json_schema: Any,
) -> tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Validate and normalize optional JSON schema payload for structured output."""
if json_schema is None:
return None, None
try:
return normalize_json_schema_payload(json_schema), None
except JsonSchemaValidationError as exc:
return None, str(exc)
def normalize_agent_node_json_schemas(nodes: List[Dict]) -> List[Dict]:
"""Normalize agent-node JSON schema payloads before persistence."""
normalized_nodes: List[Dict] = []
for node in nodes:
if not isinstance(node, dict):
normalized_nodes.append(node)
continue
normalized_node = dict(node)
if normalized_node.get("type") != "agent":
normalized_nodes.append(normalized_node)
continue
raw_config = normalized_node.get("data")
if not isinstance(raw_config, dict) or "json_schema" not in raw_config:
normalized_nodes.append(normalized_node)
continue
normalized_config = dict(raw_config)
try:
normalized_config["json_schema"] = normalize_json_schema_payload(
raw_config.get("json_schema")
)
except JsonSchemaValidationError:
# Validation runs before normalization; keep original on unexpected shape.
normalized_config["json_schema"] = raw_config.get("json_schema")
normalized_node["data"] = normalized_config
normalized_nodes.append(normalized_node)
return normalized_nodes
def validate_workflow_structure(
nodes: List[Dict], edges: List[Dict], user_id: str | None = None
) -> List[str]:
"""Validate workflow graph structure.
``user_id`` is required so per-user BYOM custom-model UUIDs resolve
when checking each agent node's structured-output capability.
"""
errors = []
if not nodes:
errors.append("Workflow must have at least one node")
return errors
start_nodes = [n for n in nodes if n.get("type") == "start"]
if len(start_nodes) != 1:
errors.append("Workflow must have exactly one start node")
end_nodes = [n for n in nodes if n.get("type") == "end"]
if not end_nodes:
errors.append("Workflow must have at least one end node")
node_ids = {n.get("id") for n in nodes}
node_map = {n.get("id"): n for n in nodes}
end_ids = {n.get("id") for n in end_nodes}
for edge in edges:
source_id = edge.get("source")
target_id = edge.get("target")
if source_id not in node_ids:
errors.append(f"Edge references non-existent source: {source_id}")
if target_id not in node_ids:
errors.append(f"Edge references non-existent target: {target_id}")
if start_nodes:
start_id = start_nodes[0].get("id")
if not any(e.get("source") == start_id for e in edges):
errors.append("Start node must have at least one outgoing edge")
condition_nodes = [n for n in nodes if n.get("type") == "condition"]
for cnode in condition_nodes:
cnode_id = cnode.get("id")
cnode_title = cnode.get("title", cnode_id)
outgoing = [e for e in edges if e.get("source") == cnode_id]
if len(outgoing) < 2:
errors.append(
f"Condition node '{cnode_title}' must have at least 2 outgoing edges"
)
node_data = cnode.get("data", {}) or {}
cases = node_data.get("cases", [])
if not isinstance(cases, list):
cases = []
if not cases or not any(
isinstance(c, dict) and str(c.get("expression", "")).strip() for c in cases
):
errors.append(
f"Condition node '{cnode_title}' must have at least one case with an expression"
)
case_handles: Set[str] = set()
duplicate_case_handles: Set[str] = set()
for case in cases:
if not isinstance(case, dict):
continue
raw_handle = case.get("sourceHandle", "")
handle = raw_handle.strip() if isinstance(raw_handle, str) else ""
if not handle:
errors.append(
f"Condition node '{cnode_title}' has a case without a branch handle"
)
continue
if handle in case_handles:
duplicate_case_handles.add(handle)
case_handles.add(handle)
for handle in duplicate_case_handles:
errors.append(
f"Condition node '{cnode_title}' has duplicate case handle '{handle}'"
)
outgoing_by_handle: Dict[str, List[Dict]] = {}
for out_edge in outgoing:
raw_handle = out_edge.get("sourceHandle", "")
handle = raw_handle.strip() if isinstance(raw_handle, str) else ""
outgoing_by_handle.setdefault(handle, []).append(out_edge)
for handle, handle_edges in outgoing_by_handle.items():
if not handle:
errors.append(
f"Condition node '{cnode_title}' has an outgoing edge without sourceHandle"
)
continue
if handle != "else" and handle not in case_handles:
errors.append(
f"Condition node '{cnode_title}' has a connection from unknown branch '{handle}'"
)
if len(handle_edges) > 1:
errors.append(
f"Condition node '{cnode_title}' has multiple outgoing edges from branch '{handle}'"
)
if "else" not in outgoing_by_handle:
errors.append(f"Condition node '{cnode_title}' must have an 'else' branch")
for case in cases:
if not isinstance(case, dict):
continue
raw_handle = case.get("sourceHandle", "")
handle = raw_handle.strip() if isinstance(raw_handle, str) else ""
if not handle:
continue
raw_expression = case.get("expression", "")
has_expression = isinstance(raw_expression, str) and bool(
raw_expression.strip()
)
has_outgoing = bool(outgoing_by_handle.get(handle))
if has_expression and not has_outgoing:
errors.append(
f"Condition node '{cnode_title}' case '{handle}' has an expression but no outgoing edge"
)
if not has_expression and has_outgoing:
errors.append(
f"Condition node '{cnode_title}' case '{handle}' has an outgoing edge but no expression"
)
if has_expression:
try:
validate_cel_expression(raw_expression)
except CelEvaluationError as exc:
errors.append(
f"Condition node '{cnode_title}' case '{handle}' "
f"has an invalid expression: {exc}"
)
for handle, handle_edges in outgoing_by_handle.items():
if not handle:
continue
for out_edge in handle_edges:
target = out_edge.get("target")
if target and not _can_reach_end(target, edges, node_map, end_ids):
errors.append(
f"Branch '{handle}' of condition '{cnode_title}' "
f"must eventually reach an end node"
)
# Set State nodes were validated nowhere. A node whose CEL does not compile
# saves and publishes clean, then aborts the run on first execution — the
# user only finds out as a failed answer, with no pointer to the node.
state_nodes = [n for n in nodes if n.get("type") == "state"]
for snode in state_nodes:
snode_title = snode.get("title", snode.get("id"))
node_data = snode.get("data", {}) or {}
# The builder writes state config under ``data.config`` but other
# payloads keep it flat on ``data``; the engine reads
# ``node.config.get("config", node.config)`` for exactly this reason,
# so accept both rather than silently validating nothing.
nested = node_data.get("config")
source = nested if isinstance(nested, dict) else node_data
operations = source.get("operations", [])
if not isinstance(operations, list):
continue
for index, operation in enumerate(operations):
if not isinstance(operation, dict):
continue
raw_expression = operation.get("expression", "")
target_variable = operation.get("target_variable", "")
has_expression = isinstance(raw_expression, str) and bool(
raw_expression.strip()
)
has_target = isinstance(target_variable, str) and bool(
target_variable.strip()
)
# The engine silently skips an operation missing either half
# (workflow_engine._execute_state_node), so downstream nodes read a
# variable that never gets set. Surface it at save time instead.
if has_expression and not has_target:
errors.append(
f"Set State node '{snode_title}' operation {index + 1} "
f"has an expression but no target variable"
)
if has_target and not has_expression:
errors.append(
f"Set State node '{snode_title}' operation {index + 1} "
f"has a target variable but no expression"
)
if has_expression:
try:
validate_cel_expression(raw_expression)
except CelEvaluationError as exc:
errors.append(
f"Set State node '{snode_title}' operation {index + 1} "
f"has an invalid expression: {exc}"
)
agent_nodes = [n for n in nodes if n.get("type") == "agent"]
for agent_node in agent_nodes:
agent_title = agent_node.get("title", agent_node.get("id", "unknown"))
raw_config = agent_node.get("data", {}) or {}
if not isinstance(raw_config, dict):
errors.append(f"Agent node '{agent_title}' has invalid configuration")
continue
normalized_schema, schema_error = validate_json_schema_payload(
raw_config.get("json_schema")
)
has_json_schema = normalized_schema is not None
model_id = raw_config.get("model_id")
if has_json_schema and isinstance(model_id, str) and model_id.strip():
capabilities = get_model_capabilities(model_id.strip(), user_id=user_id)
if capabilities and not capabilities.get("supports_structured_output", False):
errors.append(
f"Agent node '{agent_title}' selected model does not support structured output"
)
if schema_error:
errors.append(f"Agent node '{agent_title}' JSON schema {schema_error}")
code_nodes = [n for n in nodes if n.get("type") == "code"]
for code_node in code_nodes:
code_title = code_node.get("title", code_node.get("id", "unknown"))
raw_config = code_node.get("data", {}) or {}
if not isinstance(raw_config, dict):
errors.append(f"Code node '{code_title}' has invalid configuration")
continue
if not str(raw_config.get("code", "")).strip():
errors.append(f"Code node '{code_title}' must have code to execute")
_, schema_error = validate_json_schema_payload(raw_config.get("json_schema"))
if schema_error:
errors.append(f"Code node '{code_title}' JSON schema {schema_error}")
for node in nodes:
if not node.get("id"):
errors.append("All nodes must have an id")
if not node.get("type"):
errors.append(f"Node {node.get('id', 'unknown')} must have a type")
return errors
def _can_reach_end(
node_id: str, edges: List[Dict], node_map: Dict, end_ids: set, visited: set = None
) -> bool:
if visited is None:
visited = set()
if node_id in end_ids:
return True
if node_id in visited or node_id not in node_map:
return False
visited.add(node_id)
outgoing = [e.get("target") for e in edges if e.get("source") == node_id]
return any(_can_reach_end(t, edges, node_map, end_ids, visited) for t in outgoing if t)
@workflows_ns.route("/workflows")
class WorkflowList(Resource):
@require_auth
@require_fields(["name"])
def post(self):
"""Create a new workflow with nodes and edges."""
user_id = get_user_id()
data = request.get_json()
name = data.get("name", "").strip()
description = data.get("description", "")
nodes_data = data.get("nodes", [])
edges_data = data.get("edges", [])
validation_errors = validate_workflow_structure(
nodes_data, edges_data, user_id=user_id
)
if validation_errors:
return error_response(
"Workflow validation failed", errors=validation_errors
)
nodes_data = normalize_agent_node_json_schemas(nodes_data)
try:
with db_session() as conn:
repo = WorkflowsRepository(conn)
workflow = repo.create(user_id, name, description=description)
pg_workflow_id = str(workflow["id"])
_write_graph(conn, pg_workflow_id, 1, nodes_data, edges_data)
except Exception as err:
return _workflow_error_response("Failed to create workflow", err)
return success_response({"id": pg_workflow_id}, 201)
@workflows_ns.route("/workflows/<string:workflow_id>")
class WorkflowDetail(Resource):
@require_auth
def get(self, workflow_id: str):
"""Get workflow details with nodes and edges."""
user_id = get_user_id()
try:
with db_readonly() as conn:
repo = WorkflowsRepository(conn)
workflow = _resolve_workflow(repo, workflow_id, user_id)
if workflow is None:
return error_response("Workflow not found", 404)
pg_workflow_id = str(workflow["id"])
graph_version = get_workflow_graph_version(workflow)
nodes = WorkflowNodesRepository(conn).find_by_version(
pg_workflow_id, graph_version,
)
edges = WorkflowEdgesRepository(conn).find_by_version(
pg_workflow_id, graph_version,
)
except Exception as err:
return _workflow_error_response("Failed to fetch workflow", err)
return success_response(
{
"workflow": serialize_workflow(workflow),
"nodes": [serialize_node(n) for n in nodes],
"edges": [serialize_edge(e) for e in edges],
}
)
@require_auth
@require_fields(["name"])
def put(self, workflow_id: str):
"""Update workflow and replace nodes/edges."""
user_id = get_user_id()
data = request.get_json()
name = data.get("name", "").strip()
description = data.get("description", "")
nodes_data = data.get("nodes", [])
edges_data = data.get("edges", [])
validation_errors = validate_workflow_structure(
nodes_data, edges_data, user_id=user_id
)
if validation_errors:
return error_response(
"Workflow validation failed", errors=validation_errors
)
nodes_data = normalize_agent_node_json_schemas(nodes_data)
try:
with db_session() as conn:
repo = WorkflowsRepository(conn)
workflow = _resolve_workflow(repo, workflow_id, user_id)
if workflow is None:
return error_response("Workflow not found", 404)
pg_workflow_id = str(workflow["id"])
current_graph_version = get_workflow_graph_version(workflow)
next_graph_version = current_graph_version + 1
_write_graph(
conn, pg_workflow_id, next_graph_version,
nodes_data, edges_data,
)
repo.update(
pg_workflow_id, user_id,
{
"name": name,
"description": description,
"current_graph_version": next_graph_version,
},
)
WorkflowNodesRepository(conn).delete_other_versions(
pg_workflow_id, next_graph_version,
)
WorkflowEdgesRepository(conn).delete_other_versions(
pg_workflow_id, next_graph_version,
)
except Exception as err:
return _workflow_error_response("Failed to update workflow", err)
return success_response()
@require_auth
def delete(self, workflow_id: str):
"""Delete workflow and its graph."""
user_id = get_user_id()
try:
with db_session() as conn:
repo = WorkflowsRepository(conn)
workflow = _resolve_workflow(repo, workflow_id, user_id)
if workflow is None:
return error_response("Workflow not found", 404)
# ON DELETE CASCADE on workflow_nodes/edges cleans children.
repo.delete(str(workflow["id"]), user_id)
except Exception as err:
return _workflow_error_response("Failed to delete workflow", err)
return success_response()