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- 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.
17 lines
777 B
Python
17 lines
777 B
Python
from autometabuilder.web.workflow_graph import build_workflow_graph
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def test_build_workflow_graph_structure():
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graph = build_workflow_graph()
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assert isinstance(graph.get("nodes"), list), "nodes list should be present"
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assert isinstance(graph.get("edges"), list), "edges list should be present"
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counts = graph.get("count", {})
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assert counts.get("nodes", 0) >= 5, "Expect at least the top-level nodes to exist"
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assert counts.get("edges", 0) > 0, "Edges should exist between workflow nodes"
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node_ids = {node["id"] for node in graph["nodes"]}
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for edge in graph["edges"]:
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assert edge["from"] in node_ids
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assert edge["to"] in node_ids
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assert isinstance(edge["var"], str) and edge["var"], "edges should reference a variable"
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