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Typer_Body
2026-05-18 01:47:13 +08:00
parent 27c0d344bf
commit bb7db53447
89 changed files with 1202 additions and 6883 deletions
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40
src/langbot/pkg/api/http/service/workflow.py
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@@ -567,58 +567,30 @@ class WorkflowService:
return result
def _enrich_node_type_configs(self, node_types: list[dict]) -> list[dict]:
"""Enrich node schemas with node YAML config metadata if available"""
# Get workflow node configs loaded from YAML files
workflow_node_configs = getattr(self.ap, 'workflow_node_configs', {})
"""Enrich node schemas with pipeline config metadata if available.
Dedicated workflow node YAML metadata is already applied by
NodeTypeRegistry before this method runs. This method only keeps the
older pipeline metadata reuse path for nodes that explicitly request it.
"""
for node_schema in node_types:
node_type = node_schema.get('type', '')
node_schema.setdefault('config_schema', [])
# First, try to load config from dedicated node YAML file
if node_type in workflow_node_configs:
node_config = workflow_node_configs[node_type]
# Enrich inputs from YAML if Python class has empty inputs
yaml_inputs = node_config.get('inputs', [])
if yaml_inputs and not node_schema.get('inputs'):
node_schema['inputs'] = [self._normalize_port_item(inp) for inp in yaml_inputs]
# Enrich outputs from YAML if Python class has empty outputs
yaml_outputs = node_config.get('outputs', [])
if yaml_outputs and not node_schema.get('outputs'):
node_schema['outputs'] = [self._normalize_port_item(out) for out in yaml_outputs]
# Enrich config_schema from YAML
yaml_configs = node_config.get('config', [])
# Normalize and add YAML configs to config_schema
existing_names = {cfg.get('name') for cfg in node_schema.get('config_schema', [])}
for cfg in yaml_configs:
if cfg.get('name') not in existing_names:
normalized_cfg = self._normalize_config_item(cfg)
node_schema['config_schema'].append(normalized_cfg)
existing_names.add(cfg.get('name'))
# Second, try to load from pipeline config metadata (for backward compatibility)
config_schema_source = node_schema.get('config_schema_source')
config_stages = node_schema.get('config_stages', [])
if config_schema_source and config_stages:
# Get pipeline config metadata
pipeline_meta = self._get_pipeline_config_meta(config_schema_source)
if pipeline_meta:
# Extract config items from specified stages
enriched_configs = []
for stage_name in config_stages:
stage_data = self._find_stage_in_pipeline(pipeline_meta, stage_name)
if stage_data and 'config' in stage_data:
enriched_configs.extend(stage_data['config'])
# Merge with existing config_schema (avoid duplicates by name)
existing_names = {cfg.get('name') for cfg in node_schema.get('config_schema', [])}
for cfg in enriched_configs:
if cfg.get('name') not in existing_names:
# Normalize config item format for frontend compatibility
normalized_cfg = self._normalize_config_item(cfg)
node_schema['config_schema'].append(normalized_cfg)
existing_names.add(cfg.get('name'))