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d9d1e9b63a
Fixes discovered during end-to-end testing of Agent workflow execution: 1. ModelManager instantiation: use ModelManager.for_tenant() instead of ModelManager() which requires a ProviderManager argument 2. Variable template resolution: use VariableTemplateParser(template).format() instead of non-existent resolve_template() static method 3. invoke_llm() signature: remove unsupported 'user' keyword argument 4. Event dispatch: remove ModelInvokeCompletedEvent from _run() yield (graphon base Node._dispatch doesn't support it via singledispatch) 5. NodeRunResult metadata: use WorkflowNodeExecutionMetadataKey enum keys (TOTAL_TOKENS, TOTAL_PRICE, CURRENCY) instead of arbitrary string keys 6. SSE topic mismatch: use AppMode.AGENT (not ADVANCED_CHAT) in retrieve_events() so publisher and subscriber share the same channel 7. Celery task routing: add AppMode.AGENT to workflow_execute_task._run_app() alongside ADVANCED_CHAT All issues verified fixed: Agent V2 node successfully invokes LLM and returns "Hello there!" through the full SSE streaming pipeline. Made-with: Cursor |
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| .. | ||
| nodes | ||
| __init__.py | ||
| file_reference.py | ||
| human_input_compat.py | ||
| human_input_forms.py | ||
| node_factory.py | ||
| node_runtime.py | ||
| system_variables.py | ||
| template_rendering.py | ||
| variable_pool_initializer.py | ||
| variable_prefixes.py | ||
| workflow_entry.py | ||
| workflow_run_outputs.py | ||