brent.edwards
e801eb1ee8
- Rewrite .forgejo/workflows/ci.yml to route all jobs through nox sessions - Fix coverage_report nox session: serial behave mode replaces broken parallel mode (22% -> 97% accuracy), raise fail-under from 85% to 97% - Pass posargs through format nox session for CI --check support - Add 11 CI workflow validation scenarios (Behave) + Robot smoke test + ASV bench - Add 108 new Behave scenarios covering 6 largest coverage gaps to reach 97%: yaml_template_engine, actor/config, actor/registry, message_router, context_analysis, context_service - Update docs/development/ci-cd.md with nox-based CI docs and 97% threshold - Restore implementation_plan.md verbose style, check off completed CI tasks Verified: 1673 scenarios pass, 97% coverage, lint clean, typecheck clean
107 lines
4.4 KiB
Gherkin
107 lines
4.4 KiB
Gherkin
Feature: Context analysis agent new coverage
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As a developer
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I want the ContextAnalysisAgent workflow thoroughly tested
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So that file loading, dependency analysis, chunking, scoring, and summarization stay stable
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Scenario: Agent initializes with default FakeListLLM
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When I create a ContextAnalysisAgent without an LLM
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Then the agent should use FakeListLLM
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And the agent should have a compiled graph
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Scenario: Agent initializes with custom LLM
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When I create a ContextAnalysisAgent with a mock LLM
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Then the agent should use the provided LLM
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Scenario: _load_files returns preloaded documents when present
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Given a ContextAnalysisAgent instance
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When I invoke _load_files with preloaded documents
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Then the result should return those preloaded documents
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Scenario: _load_files loads real files from disk
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Given a ContextAnalysisAgent instance
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And a temporary Python file on disk
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When I invoke _load_files with the temp file path
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Then the result should contain loaded documents
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Scenario: _load_files reports missing files as errors
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Given a ContextAnalysisAgent instance
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When I invoke _load_files with a nonexistent file path
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Then the result error should mention file not found
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Scenario: _load_files reports non-files as errors
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Given a ContextAnalysisAgent instance
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When I invoke _load_files with a directory path
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Then the result error should mention not a file
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Scenario: _analyze_dependencies extracts deps from documents
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Given a ContextAnalysisAgent instance
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And a state with one loaded document
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When I invoke _analyze_dependencies
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Then the dependencies dict should have entries
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Scenario: _parse_dependencies extracts items from LLM output
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Given a ContextAnalysisAgent instance
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When I parse dependencies from "Dependencies: ['os', 'sys', 'pathlib']"
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Then the parsed list should contain os sys pathlib
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Scenario: _chunk_documents passes small docs through unchanged
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Given a ContextAnalysisAgent instance
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And a state with a small document
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When I invoke _chunk_documents
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Then the chunks should contain the original document
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Scenario: _chunk_documents splits large docs into overlapping chunks
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Given a ContextAnalysisAgent instance with chunk_size 100
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And a state with a large document of 500 characters
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When I invoke _chunk_documents
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Then the chunks should contain more than one document
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Scenario: _score_relevance scores each unique file
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Given a ContextAnalysisAgent instance
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And a state with chunks from two files
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When I invoke _score_relevance
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Then relevance scores should exist for both files
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Scenario: _parse_relevance_score extracts numeric score
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Given a ContextAnalysisAgent instance
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When I parse relevance score from "Score: 0.85 - very relevant"
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Then the parsed score should be approximately 0.85
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Scenario: _parse_relevance_score returns 0.8 for high keyword
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Given a ContextAnalysisAgent instance
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When I parse relevance score from "This is High relevance"
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Then the parsed score should be approximately 0.8
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Scenario: _parse_relevance_score returns 0.3 for low keyword
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Given a ContextAnalysisAgent instance
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When I parse relevance score from "This has low relevance"
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Then the parsed score should be approximately 0.3
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Scenario: _parse_relevance_score returns 0.5 as default
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Given a ContextAnalysisAgent instance
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When I parse relevance score from "No numeric or keyword info"
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Then the parsed score should be approximately 0.5
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Scenario: _summarize_context generates summary
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Given a ContextAnalysisAgent instance
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And a full analysis state with documents and scores
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When I invoke _summarize_context
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Then the direct summary should be a non-empty string
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Scenario: invoke runs the full workflow synchronously
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Given a ContextAnalysisAgent instance
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And a temporary Python file on disk
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When I invoke the full workflow with the temp file
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Then the result should contain summary and scores
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Scenario: stream yields events from the workflow
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Given a ContextAnalysisAgent instance
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And a temporary Python file on disk
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When I stream the workflow with the temp file
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Then at least one analysis event should be yielded
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Scenario: _with_retry wraps a chain that supports retry
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Given a ContextAnalysisAgent instance
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When I wrap a chain with retry support
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Then the wrapped chain should be returned
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