CoreRasurae
8f986c1e31
Additional BDD scenarios covering registry resolver errors, cache TTL expiry, runtime dispatch normalization, template base edge cases, validation actor coverage gaps, and YAML Jinja loader deferred rendering.
218 lines
11 KiB
Gherkin
218 lines
11 KiB
Gherkin
Feature: Validation Actor Runtime Config Validation
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As a developer
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I want actor-level runtime configs to be validated correctly for graph, LLM, tool, and multi_actor types
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So that only well-formed individual actor configs are accepted by the validation layer
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Background:
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Given the validation actor test context is initialized (vac)
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# ── validate_actor_config dispatch ──
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Scenario: validate_actor_config dispatches to graph validator for type graph
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Given a config dict with type graph and route in legacy format (vac)
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When validate_actor_config is called (vac)
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Then no error should be raised for valid graph config (vac)
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Scenario: validate_actor_config dispatches to llm validator for type llm
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Given a config dict with type llm provider and model (vac)
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When validate_actor_config is called (vac)
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Then no error should be raised for valid llm config (vac)
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Scenario: validate_actor_config dispatches to tool validator for type tool
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Given a config dict with type tool and tools list (vac)
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When validate_actor_config is called (vac)
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Then no error should be raised for valid tool config (vac)
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Scenario: validate_actor_config dispatches to multi_actor validator for type multi_actor
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Given a config dict with type multi_actor and actors mapping (vac)
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When validate_actor_config is called (vac)
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Then no error should be raised for valid multi_actor config (vac)
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# ── _infer_actor_type implicit detection ──
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Scenario: _infer_actor_type detects graph from top-level routes key
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Given a config dict without type but with top-level routes key (vac)
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When _infer_actor_type is called (vac)
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Then the inferred type should be graph (vac)
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Scenario: _infer_actor_type detects multi_actor from top-level actors key
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Given a config dict without type but with top-level actors key (vac)
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When _infer_actor_type is called (vac)
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Then the inferred type should be multi_actor (vac)
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Scenario: _infer_actor_type raises when routes has spec-level route types
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Given a config dict without type but with routes containing spec-level stream entry (vac)
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When _infer_actor_type is called (vac)
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Then a ConfigurationError should be raised mentioning missing agents key (vac)
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Scenario: _infer_actor_type raises for non-string type field
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Given a config dict with integer type field (vac)
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When _infer_actor_type is called (vac)
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Then a ConfigurationError should be raised for non-string type (vac)
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Scenario: _infer_actor_type raises for unknown actor type
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Given a config dict with unknown actor type (vac)
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When _infer_actor_type is called (vac)
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Then a ConfigurationError should be raised for unknown type (vac)
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Scenario: _infer_actor_type raises when no type and no routes or actors
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Given a config dict without type routes or actors (vac)
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When _infer_actor_type is called (vac)
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Then a ConfigurationError should be raised for missing type (vac)
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# ── _validate_graph_actor legacy format ──
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Scenario: _validate_graph_actor validates legacy format successfully
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Given a config dict with type graph and legacy route with nodes edges entry_node (vac)
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When _validate_graph_actor is called (vac)
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Then no error should be raised for valid legacy graph config (vac)
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Scenario: _validate_graph_actor rejects legacy format without edges
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Given a config dict with type graph and legacy route without edges (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for missing edges (vac)
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Scenario: _validate_graph_actor rejects legacy format without entry_node
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Given a config dict with type graph and legacy route without entry_node (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for missing entry_node (vac)
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Scenario: _validate_graph_actor rejects legacy format exceeding max nodes
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Given a config dict with type graph and legacy route with 100 nodes (vac)
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And platform limits with max_total_nodes 10 (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for exceeding max nodes (vac)
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# ── _validate_graph_actor v2.0 format ──
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Scenario: _validate_graph_actor validates v2.0 format successfully
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Given a config dict with type graph and v2 routes with nodes edges entry_point (vac)
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When _validate_graph_actor is called (vac)
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Then no error should be raised for valid v2 graph config (vac)
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Scenario: _validate_graph_actor rejects v2 format without edges
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Given a config dict with type graph and v2 routes without edges (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for missing edges in routes main (vac)
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Scenario: _validate_graph_actor rejects v2 format without entry_point
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Given a config dict with type graph and v2 routes without entry_point (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for missing entry_point in routes main (vac)
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Scenario: _validate_graph_actor rejects v2 format exceeding max nodes
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Given a config dict with type graph and v2 routes with 200 nodes (vac)
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And platform limits with max_total_nodes 10 (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for exceeding max nodes (vac)
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Scenario: _validate_graph_actor rejects v2 format with non-dict routes main
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Given a config dict with type graph and v2 routes with non-dict main (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for non-mapping routes main (vac)
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# ── _validate_graph_actor neither format ──
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Scenario: _validate_graph_actor rejects config without route or routes
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Given a config dict with type graph but no route or routes key (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for missing route or routes (vac)
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# ── _validate_llm_actor ──
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Scenario: _validate_llm_actor rejects config without name
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Given a config dict with type llm but no name field (vac)
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When _validate_llm_actor is called (vac)
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Then a ConfigurationError should be raised for missing name in llm (vac)
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Scenario: _validate_llm_actor rejects config without provider
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Given a config dict with type llm name but no provider (vac)
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When _validate_llm_actor is called (vac)
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Then a ConfigurationError should be raised for missing provider (vac)
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Scenario: _validate_llm_actor rejects config without model
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Given a config dict with type llm name provider but no model (vac)
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When _validate_llm_actor is called (vac)
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Then a ConfigurationError should be raised for missing model (vac)
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Scenario: _validate_llm_actor accepts config with provider and model in config block
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Given a config dict with type llm name and provider model in config block (vac)
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When _validate_llm_actor is called (vac)
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Then no error should be raised for valid llm config (vac)
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# ── _validate_tool_actor ──
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Scenario: _validate_tool_actor rejects config without name
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Given a config dict with type tool but no name field (vac)
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When _validate_tool_actor is called (vac)
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Then a ConfigurationError should be raised for missing name in tool (vac)
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Scenario: _validate_tool_actor rejects config without tools
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Given a config dict with type tool name but no tools (vac)
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When _validate_tool_actor is called (vac)
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Then a ConfigurationError should be raised for missing tools (vac)
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Scenario: _validate_tool_actor accepts config with tools in config block
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Given a config dict with type tool name and tools in config block (vac)
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When _validate_tool_actor is called (vac)
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Then no error should be raised for valid tool config (vac)
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# ── _validate_multi_actor ──
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Scenario: _validate_multi_actor rejects config with empty actors
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Given a config dict with type multi_actor and empty actors (vac)
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When _validate_multi_actor is called (vac)
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Then a ConfigurationError should be raised for empty actors mapping (vac)
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Scenario: _validate_multi_actor rejects config with non-dict actors
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Given a config dict with type multi_actor and non-dict actors (vac)
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When _validate_multi_actor is called (vac)
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Then a ConfigurationError should be raised for empty actors mapping (vac)
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Scenario: _validate_multi_actor rejects config exceeding total nodes limit
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Given a config dict with type multi_actor containing many graph actors (vac)
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And platform limits with max_total_nodes 3 (vac)
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When _validate_multi_actor is called (vac)
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Then a ConfigurationError should be raised for exceeding total nodes (vac)
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Scenario: _validate_multi_actor accepts config within node limits
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Given a config dict with type multi_actor containing few graph actors (vac)
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And platform limits with max_total_nodes 100 (vac)
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When _validate_multi_actor is called (vac)
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Then no error should be raised for valid multi_actor config (vac)
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# ── Additional edge cases ──
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Scenario: _validate_graph_actor handles non-int max_total_nodes fallback
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Given a config dict with type graph and legacy route with nodes edges entry_node (vac)
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And platform limits with string max_total_nodes value (vac)
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When _validate_graph_actor is called (vac)
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Then no error should be raised for valid legacy graph config (vac)
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Scenario: _validate_graph_actor v2 format with non-dict routes main raises error
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Given a config dict with type graph and v2 routes having non-dict main value (vac)
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When _validate_graph_actor is called (vac)
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Then a ConfigurationError should be raised for non-mapping routes main (vac)
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Scenario: _validate_llm_actor non-dict config block falls back to empty dict
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Given a config dict with type llm name without provider and string config block (vac)
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When _validate_llm_actor is called (vac)
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Then a ConfigurationError should be raised for missing provider (vac)
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Scenario: _validate_tool_actor non-dict config block falls back to empty dict
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Given a config dict with type tool name and string config block (vac)
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When _validate_tool_actor is called (vac)
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Then a ConfigurationError should be raised for missing tools (vac)
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Scenario: _validate_top_level_keys raises ConfigurationError when agents key is missing
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When I call _validate_top_level_keys on a dict missing the agents key
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Then a ConfigurationError about missing agents key should be raised
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Scenario: _count_total_nodes raises ConfigurationError for non-dict nodes value
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When I call _count_total_nodes with a non-dict nodes value in a graph route
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Then a ConfigurationError should be raised about nodes being invalid
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Scenario: _compute_subgraph_depth returns cached value on cache hit
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When I call _compute_subgraph_depth twice for the same subgraph route
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Then the second call should return the cached depth value
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