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https://github.com/johndoe6345789/AutoMetabuilder.git
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johndoe6345789
877ba64de8
- Implement core components: CLI argument parsing, environment loading, GitHub service creation, and logging configuration. - Add support for OpenAI client setup and model resolution. - Develop SDLC context loader from GitHub and repository files. - Implement workflow context and engine builders. - Introduce major workflow packages: `game_tick_loop` and `contextual_iterative_loop`. - Update localization files with new package descriptions and labels. - Streamline web navigation by loading items from a dedicated JSON file.
54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
"""Execute workflow nodes."""
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class NodeExecutor:
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"""Execute workflow nodes with plugins."""
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def __init__(self, runtime, plugin_registry, input_resolver, loop_executor):
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self.runtime = runtime
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self.plugin_registry = plugin_registry
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self.input_resolver = input_resolver
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self.loop_executor = loop_executor
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def execute_nodes(self, nodes):
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"""Execute a list of nodes."""
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for node in nodes:
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self.execute_node(node)
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def execute_node(self, node):
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"""Execute a single node."""
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node_type = node.get("type")
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if not node_type:
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self.runtime.logger.error("Workflow node missing type.")
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return None
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when_value = node.get("when")
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if when_value is not None:
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if not self.input_resolver.coerce_bool(self.input_resolver.resolve_binding(when_value)):
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self.runtime.logger.trace("Node %s skipped by condition", node.get("id"))
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return None
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if node_type == "control.loop":
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return self.loop_executor.execute(node)
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plugin = self.plugin_registry.get(node_type)
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if not plugin:
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self.runtime.logger.error("Unknown node type: %s", node_type)
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return None
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inputs = self.input_resolver.resolve_inputs(node.get("inputs", {}))
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self.runtime.logger.debug("Executing node %s", node_type)
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result = plugin(self.runtime, inputs)
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if not isinstance(result, dict):
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result = {"result": result}
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outputs = node.get("outputs", {})
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if outputs:
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for output_name, store_key in outputs.items():
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if output_name in result:
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self.runtime.store[store_key] = result[output_name]
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else:
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for output_name, value in result.items():
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self.runtime.store[output_name] = value
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return result
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