brent.edwards
17fe46d925
CI / lint (pull_request) Successful in 18s
CI / typecheck (pull_request) Successful in 26s
CI / security (pull_request) Successful in 17s
CI / quality (pull_request) Successful in 14s
CI / build (pull_request) Successful in 12s
CI / behave (3.13) (pull_request) Failing after 3m50s
CI / docker (pull_request) Has been skipped
CI / helm (pull_request) Has been skipped
CI / coverage (pull_request) Failing after 4m20s
There had been over 100 behave tests failing. There should be none failing now.
166 lines
6.3 KiB
Gherkin
166 lines
6.3 KiB
Gherkin
Feature: Context Service Analysis Integration
|
|
As a developer using CleverAgents
|
|
I want to analyze context files using LangGraph workflows
|
|
So that I can understand the codebase better before making changes
|
|
|
|
# TODO: Uncomment when step definitions are implemented
|
|
# Background:
|
|
# Given I have initialized a CleverAgents project
|
|
# And I have a context service with LangGraph integration
|
|
#
|
|
# Scenario: Analyze context when no files are loaded
|
|
# Given the current plan has no context files
|
|
# When I analyze the context
|
|
# Then the analysis result should have empty documents
|
|
# And the analysis summary should indicate no files to analyze
|
|
# And there should be no error in the analysis
|
|
#
|
|
# Scenario: Analyze context with a single Python file
|
|
# Given I have a Python file "main.py" with content:
|
|
# """
|
|
# import os
|
|
# import sys
|
|
# from pathlib import Path
|
|
#
|
|
# def main():
|
|
# print("Hello, World!")
|
|
# """
|
|
# And I have added "main.py" to the LangGraph context
|
|
# When I analyze the context
|
|
# Then the analysis result should have 1 document
|
|
# And the dependencies for "main.py" should include "os"
|
|
# And the relevance score for "main.py" should be between 0.0 and 1.0
|
|
# And the summary should not be empty
|
|
#
|
|
# Scenario: Analyze context with multiple files
|
|
# Given I have a Python file "utils.py" with content:
|
|
# """
|
|
# def helper():
|
|
# return 42
|
|
# """
|
|
# And I have a Python file "app.py" with content:
|
|
# """
|
|
# from utils import helper
|
|
# print(helper())
|
|
# """
|
|
# And I have added "utils.py" to the LangGraph context
|
|
# And I have added "app.py" to the LangGraph context
|
|
# When I analyze the context
|
|
# Then the analysis result should have 2 documents
|
|
# And the dependencies should include entries for both files
|
|
# And the relevance scores should have entries for both files
|
|
#
|
|
# Scenario: Get context summary
|
|
# Given I have a Python file "sample.py" with content:
|
|
# """
|
|
# # Sample module
|
|
# class Sample:
|
|
# pass
|
|
# """
|
|
# And I have added "sample.py" to the LangGraph context
|
|
# When I get the context summary
|
|
# Then the summary should be a non-empty string
|
|
# And the summary should not indicate an error
|
|
#
|
|
# Scenario: Get context dependencies
|
|
# Given I have a Python file "deps.py" with content:
|
|
# """
|
|
# import json
|
|
# import requests
|
|
# from typing import Dict
|
|
# """
|
|
# And I have added "deps.py" to the LangGraph context
|
|
# When I get the context dependencies
|
|
# Then the dependencies dict should have an entry for "deps.py"
|
|
# And the dependencies should be a non-empty list
|
|
#
|
|
# Scenario: Get relevant files with threshold
|
|
# Given I have a Python file "important.py" with content:
|
|
# """
|
|
# # Core business logic
|
|
# def critical_function():
|
|
# return "important"
|
|
# """
|
|
# And I have a Python file "trivial.py" with content:
|
|
# """
|
|
# # Just comments
|
|
# pass
|
|
# """
|
|
# And I have added "important.py" to the LangGraph context
|
|
# And I have added "trivial.py" to the LangGraph context
|
|
# When I get relevant files with threshold 0.0
|
|
# Then the result should include both files with scores
|
|
# And all LangGraph scores should be between 0.0 and 1.0
|
|
#
|
|
# Scenario: Stream context analysis
|
|
# Given I have a Python file "streaming.py" with content:
|
|
# """
|
|
# print("test streaming")
|
|
# """
|
|
# And I have added "streaming.py" to the LangGraph context
|
|
# When I stream the context analysis
|
|
# Then I should receive multiple events
|
|
# And the events should include node execution results
|
|
#
|
|
# Scenario: Stream context analysis when no files are loaded
|
|
# Given the current plan has no context files
|
|
# When I stream the context analysis
|
|
# Then the streaming output should report no files to analyze
|
|
#
|
|
# Scenario: Analyze context asynchronously
|
|
#
|
|
# Given I have a Python file "async_test.py" with content:
|
|
# """
|
|
# async def async_func():
|
|
# return "async"
|
|
# """
|
|
# And I have added "async_test.py" to the LangGraph context
|
|
# When I analyze the context asynchronously
|
|
# Then the async result should have documents
|
|
# And the async result should have a summary
|
|
# And there should be no error in the async result
|
|
#
|
|
# Scenario: Analyze context asynchronously when no files are loaded
|
|
# Given the current plan has no context files
|
|
# When I analyze the context asynchronously
|
|
# Then the async analysis result should have empty documents
|
|
# And the async analysis summary should indicate no files to analyze
|
|
#
|
|
# Scenario: Stream context analysis asynchronously with loaded files
|
|
# Given I have a Python file "async_stream.py" with content:
|
|
# """
|
|
# print("async stream")
|
|
# """
|
|
# And I have added "async_stream.py" to the LangGraph context
|
|
# When I stream the context analysis asynchronously
|
|
# Then the async streaming events should include node execution results
|
|
#
|
|
# Scenario: Stream context analysis asynchronously with no files
|
|
# Given the current plan has no context files
|
|
# When I stream the context analysis asynchronously
|
|
# Then the async streaming output should report no files to analyze
|
|
#
|
|
# Scenario: Handle non-existent files gracefully
|
|
# Given I have added a non-existent file path to the analysis
|
|
#
|
|
#
|
|
# When I analyze the context with the non-existent path
|
|
# Then the analysis should complete without raising an exception
|
|
# And the error field should contain file not found information
|
|
#
|
|
# Scenario: Get context agent instance
|
|
# When I request a context analysis agent
|
|
# Then I should receive a ContextAnalysisAgent instance
|
|
# And the agent should have the standard workflow nodes
|
|
#
|
|
# Scenario: Prepare LangSmith metadata when tracing is enabled
|
|
# Given LangSmith tracing is enabled for context analysis metadata
|
|
# And I have a Python file "langsmith.py" with content:
|
|
# """
|
|
# print("langsmith tracing")
|
|
# """
|
|
# And I have added "langsmith.py" to the LangGraph context
|
|
# When I prepare the LangGraph analysis config for run "LangSmithRun" in "stream" mode
|
|
# Then the LangSmith config should include the current project metadata
|
|
# And the LangSmith config should record 1 context file path
|