Tests/factcheck pipeline test #22
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Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Fix: remove unused variable 'claim_result'
committed suggestion by coderabbit Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Fix: removed an unused variable once again
WalkthroughThe changes introduce new and improved testing infrastructure for the VerifactManager pipeline, including mock agent classes, parameterized test fixtures, and comprehensive tests for both faithfulness metrics and the end-to-end fact-checking flow. The Changes
Sequence Diagram(s)sequenceDiagram
participant Test as Test Function
participant VM as VerifactManager
participant MockClaim as MockAgent (Claim)
participant MockEvidence as MockAgent (Evidence)
participant MockVerdict as MockAgent (Verdict)
Test->>VM: run(claim_text)
VM->>MockClaim: process(claim_text)
MockClaim-->>VM: mock_claim
VM->>MockEvidence: process(mock_claim)
MockEvidence-->>VM: mock_evidence
VM->>MockVerdict: process(mock_claim, mock_evidence)
MockVerdict-->>VM: mock_verdict
VM-->>Test: result (verdict, evidence)
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Actionable comments posted: 3
🧹 Nitpick comments (8)
src/tests/conftest.py (2)
1-12: Fix docstring formatting issues.The module docstring has several formatting issues that should be addressed for better readability and compliance with Python documentation standards.
Apply this diff to fix the docstring formatting:
-""" pytest fixtures: - pytest_generate_tests is a list of questions for testing with expect_success [True,False] and a min_score - - -Other potential queries - queries = [ - "The sky is green during a storm.", - "Grass is usually yellow.", - "Water normally boils at 90°C.", - "The Great Wall of China is visible from space with the naked eye." - ] -Can potentially add testing with "strict" in [False, True] -""" +"""Pytest fixtures for VerifactManager testing. + +This module provides parametrized test fixtures for testing faithfulness metrics +and pipeline functionality with various queries and expected outcomes. + +Other potential queries for future expansion: + - "The sky is green during a storm." + - "Grass is usually yellow." + - "Water normally boils at 90°C." + - "The Great Wall of China is visible from space with the naked eye." + +Can potentially add testing with "strict" parameter in [False, True]. +"""🧰 Tools
🪛 Ruff (0.11.9)
1-12: 1 blank line required between summary line and description
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1-12: No whitespaces allowed surrounding docstring text
Trim surrounding whitespace
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Add closing punctuation
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[convention] 2-2: Line too long (106/100)
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14-24: Add function docstring and approve the implementation.The parametrization logic is well-implemented and provides good test coverage with varied scenarios.
Add a docstring to the function:
def pytest_generate_tests(metafunc): + """Parametrize tests that require query, expect_success, and min_score fixtures. + + Args: + metafunc: The pytest metafunc object for test parametrization. + """ if {"query", "expect_success", "min_score"}.issubset(metafunc.fixturenames):🧰 Tools
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14-14: Missing docstring in public function
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[convention] 14-14: Missing function or method docstring
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src/tests/mocks/mock_agents.py (2)
4-9: Add docstring for MockResult class.The class lacks documentation explaining its purpose and usage in the testing framework.
class MockResult: + """Mock result class for testing that wraps a fixed output value.""" + def __init__(self, output: Any): + """Initialize with a fixed output value. + + Args: + output: The fixed output to return in tests. + """ self.output = output def final_output_as(self, _type): + """Return the output regardless of requested type. + + Args: + _type: Ignored type parameter for compatibility. + + Returns: + The fixed output value. + """ return self.output🧰 Tools
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__init__(D107)
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[refactor] 4-4: Too few public methods (1/2)
(R0903)
11-28: Add docstring and consider the unused parameter.The MockAgent implementation is solid for testing purposes, providing all necessary attributes to simulate real agents.
class MockAgent(Agent): + """Mock agent implementation for testing purposes. + + Provides a fixed output and all necessary attributes to simulate + real agent behavior in tests. + """ + def __init__(self, output, name="MockAgent"): + """Initialize mock agent with fixed output. + + Args: + output: The fixed output to return from process method. + name: Optional agent name, defaults to "MockAgent". + """ self._output = outputFor the unused
input_dataparameter in theprocessmethod, consider using an underscore prefix to indicate it's intentionally unused:- async def process(self, input_data): + async def process(self, _input_data): + """Process method that returns fixed output regardless of input. + + Args: + _input_data: Ignored input data for compatibility. + + Returns: + MockResult containing the fixed output. + """ return MockResult(self._output)🧰 Tools
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11-11: Missing docstring in public class
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__init__(D107)
23-23: Missing docstring in public method
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[convention] 11-11: Missing class docstring
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[refactor] 11-11: Too many instance attributes (9/7)
(R0902)
[convention] 23-23: Missing function or method docstring
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[warning] 23-23: Unused argument 'input_data'
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[convention] 27-27: Missing function or method docstring
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src/tests/test_faithfulness.py (1)
1-10: Add module docstring for better documentation.The module lacks a docstring explaining its purpose in the testing framework.
+"""Faithfulness metric tests for VerifactManager pipeline. + +This module contains tests that evaluate the faithfulness of outputs +generated by the VerifactManager using the DeepEval framework. +""" + import pytest🧰 Tools
🪛 Pylint (3.3.7)
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[error] 2-2: Unable to import 'deepeval.evaluate'
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[error] 4-4: Unable to import 'deepeval.test_case'
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[error] 5-5: Unable to import 'dotenv'
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[error] 7-7: Unable to import 'src.verifact_manager'
(E0401)
src/tests/test_verifact_manager.py (3)
1-13: Fix docstring formatting issues.The module docstring has formatting issues that violate PEP 257 conventions.
Apply this diff to fix the docstring formatting:
-""" -Basic pipeline execution: +"""Basic pipeline execution. + uses monkeypatched agents (claim_detector_agent, evidence_hunter_agent, verdict_writer_agent) and Runner.run() instead of real agents. 1. Testing if the full VerifactManager.run() pipeline executes successfully with mocked agents. 2. Testing if a claim goes through detection, evidence gathering, and verdict generation using mocked data with a range of verdict cases: "false", "partially true", "unverifiable", and "true". a. The verdict text returned matches the expected result. b. The sources in the verdict match the mock evidence source. c. The evidence content and source returned from the mock agent match what was injected - """🧰 Tools
🪛 Ruff (0.11.9)
1-13: 1 blank line required between summary line and description
(D205)
1-13: Multi-line docstring summary should start at the first line
Remove whitespace after opening quotes
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🪛 Pylint (3.3.7)
[convention] 3-3: Line too long (110/100)
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[convention] 7-7: Line too long (106/100)
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20-46: Consider breaking long lines for better readability.Some parameter lines exceed the 100-character limit, which can impact readability.
Consider formatting the parameterization for better readability:
@pytest.mark.parametrize("claim_text, verdict_text, evidence_content, evidence_source", [ ( "The moon is made of cheese", "false", "Scientific consensus disproves this", - "https://nasa.gov" + "https://nasa.gov", ), ( "The Great Wall of China is visible from space", "partially true", - "Astronauts report visibility depends on conditions", - "https://esa.int" + "Astronauts report visibility depends on conditions", + "https://esa.int", ), ( "Aliens built the pyramids", "unverifiable", - "There is no direct evidence confirming or denying alien involvement", - "https://historychannel.com" + "There is no direct evidence confirming or denying alien involvement", + "https://historychannel.com", ), ( "Water boils at 100 degrees Celsius at sea level", "true", "This is a well-documented scientific fact", - "https://science.org" + "https://science.org", ), ])
47-47: Add a docstring to the test function.The test function is missing a docstring that would help explain its purpose and behavior.
Add a descriptive docstring:
async def test_factcheck_pipeline(monkeypatch, claim_text, verdict_text, evidence_content, evidence_source): + """Test the end-to-end fact-checking pipeline with mocked agents. + + Verifies that the VerifactManager.run() pipeline correctly processes claims + through detection, evidence gathering, and verdict generation stages using + mocked components. Tests multiple verdict scenarios and validates both + verdict and evidence results. + """🧰 Tools
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📒 Files selected for processing (5)
.gitignore(2 hunks)src/tests/conftest.py(1 hunks)src/tests/mocks/mock_agents.py(1 hunks)src/tests/test_faithfulness.py(1 hunks)src/tests/test_verifact_manager.py(1 hunks)
🧰 Additional context used
🧬 Code Graph Analysis (1)
src/tests/mocks/mock_agents.py (1)
src/verifact_agents/base.py (1)
Agent(12-16)
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src/tests/conftest.py
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src/tests/mocks/mock_agents.py
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src/tests/test_verifact_manager.py
1-13: 1 blank line required between summary line and description
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Remove whitespace after opening quotes
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src/tests/conftest.py
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src/tests/mocks/mock_agents.py
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src/tests/test_verifact_manager.py
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🪛 GitHub Check: Codacy Static Code Analysis
src/tests/test_faithfulness.py
[warning] 12-12: src/tests/test_faithfulness.py#L12
Method test_faithfulness_real_output has a cyclomatic complexity of 11 (limit is 8)
⏰ Context from checks skipped due to timeout of 90000ms (1)
- GitHub Check: Codacy Static Code Analysis
🔇 Additional comments (4)
.gitignore (1)
164-164: LGTM! Appropriate gitignore patterns added.The changes correctly ignore IDE-specific files (.idea/) and evaluation framework directories (.deepeval/), which aligns with the new testing infrastructure being introduced.
Also applies to: 188-190
src/tests/test_faithfulness.py (1)
11-44: Comprehensive test implementation with good coverage.The test effectively validates faithfulness metrics using real VerifactManager output and covers all essential aspects of the evaluation process.
🧰 Tools
🪛 GitHub Check: Codacy Static Code Analysis
[warning] 12-12: src/tests/test_faithfulness.py#L12
Method test_faithfulness_real_output has a cyclomatic complexity of 11 (limit is 8)src/tests/test_verifact_manager.py (2)
64-65: LGTM! Strategic import placement after monkeypatching.The import of
src.verifact_managerafter monkeypatching is intentional and correct. This ensures that the patched agent instances are used when the module is imported, which is essential for the test to work properly.🧰 Tools
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[convention] 65-65: Import outside toplevel (src.verifact_manager)
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[error] 65-65: Unable to import 'src.verifact_manager'
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68-71: LGTM! Clean mock runner implementation.The mock runner function correctly simulates the Runner.run behavior by calling the agent's process method asynchronously, which aligns with the expected interface.
| _, evidence_result, verdict_result = result[0] | ||
|
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||
| # Verdict checks | ||
| assert verdict_result.verdict == verdict_text | ||
| assert evidence_source in verdict_result.sources | ||
|
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||
| # Evidence checks | ||
| assert evidence_result is not None | ||
| assert len(evidence_result) > 0 | ||
| assert evidence_result[0].content == evidence_content | ||
| assert evidence_result[0].source == evidence_source |
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💡 Verification agent
🧩 Analysis chain
Verify the return structure assumption.
The test assumes a specific return structure from manager.run() where result[0] contains a tuple with at least 3 elements. Consider adding defensive checks or documentation about the expected return format.
Run this script to verify the return structure of VerifactManager.run():
🏁 Script executed:
#!/bin/bash
# Description: Check the return structure of VerifactManager.run method
# Expected: Find the method definition and understand its return format
ast-grep --pattern $'class VerifactManager {
$$$
async def run($$$) {
$$$
return $$$
}
$$$
}'
# Also search for any documentation about the return format
rg -A 10 -B 5 "def run.*:" --type py | grep -A 15 -B 5 "VerifactManager"Length of output: 1144
🏁 Script executed:
#!/bin/bash
# Inspect the implementation and return statements of VerifactManager.run
rg -n "async def run" -A 50 src/verifact_manager.py
# Locate the Verdict class definition to understand its structure
rg -n "class Verdict" -A 30 src
# Preview the test file to see how run() is used and unpacked
sed -n '1,200p' src/tests/test_verifact_manager.pyLength of output: 9172
🏁 Script executed:
#!/bin/bash
# Extract the full run method to examine its return structure
sed -n '41,200p' src/verifact_manager.py
# Locate all return statements within VerifactManager.run
rg -n "return" -B 5 -A 5 src/verifact_manager.pyLength of output: 11671
Update VerifactManager.run return signature and docstring
The test’s unpacking of result[0] as (claim, evidence_list, verdict) is correct—the method returns a List[tuple[Claim, List[Evidence], Verdict]], not just List[Verdict] (and it’s currently annotated as returning None). Please update the code to make this explicit:
• In src/verifact_manager.py (Line 41):
- async def run(self, query: str, progress_callback=None, progress_msg=None) -> None:
+ async def run(self, query: str, progress_callback=None, progress_msg=None)
+ -> list[tuple[Claim, list[Evidence], Verdict]]:• In the same docstring’s Returns: section:
- Returns:
- List[Verdict]: A list of verdicts for claims in the text
+ Returns:
+ List[tuple[Claim, List[Evidence], Verdict]]:
+ A list of (claim, evidence_list, verdict) tuples for each detected claimThis will align the signature and documentation with the actual return structure and remove any confusion for future maintainers.
📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| _, evidence_result, verdict_result = result[0] | |
| # Verdict checks | |
| assert verdict_result.verdict == verdict_text | |
| assert evidence_source in verdict_result.sources | |
| # Evidence checks | |
| assert evidence_result is not None | |
| assert len(evidence_result) > 0 | |
| assert evidence_result[0].content == evidence_content | |
| assert evidence_result[0].source == evidence_source | |
| async def run(self, query: str, progress_callback=None, progress_msg=None) -> list[tuple[Claim, list[Evidence], Verdict]]: | |
| """ | |
| Execute the verifact process on the given query. | |
| Args: | |
| query: The input text to analyze for claims. | |
| progress_callback: Optional callback for progress updates. | |
| progress_msg: Optional base message for progress updates. | |
| Returns: | |
| List[tuple[Claim, List[Evidence], Verdict]]: | |
| A list of (claim, evidence_list, verdict) tuples for each detected claim | |
| """ | |
| # … rest of implementation … |
🤖 Prompt for AI Agents
In src/verifact_manager.py around line 41, update the async def run method's
return type annotation to reflect that it returns a List of tuples containing
Claim, List of Evidence, and Verdict, instead of None. Also, revise the method's
docstring Returns section to explicitly describe this return structure,
clarifying that it returns List[tuple[Claim, List[Evidence], Verdict]]. This
will align the code and documentation with the actual return format used in the
tests and improve maintainability.
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Actionable comments posted: 1
♻️ Duplicate comments (1)
src/tests/test_faithfulness.py (1)
21-67: Consider further refactoring to reduce cyclomatic complexity.While the
validate_metrichelper function was a good start, the function still has high cyclomatic complexity (11 vs limit of 8) due to nested loops and conditionals. Consider extracting the evaluation logic into separate helper functions.The previous review comment about refactoring for complexity reduction is still applicable. Consider extracting the evaluation results processing into a separate helper function to further reduce complexity.
🧰 Tools
🪛 Pylint (3.3.7)
[warning] 65-66: Else clause on loop without a break statement, remove the else and de-indent all the code inside it
(W0120)
🪛 GitHub Check: Codacy Static Code Analysis
[warning] 21-21: src/tests/test_faithfulness.py#L21
Method test_faithfulness_real_output has a cyclomatic complexity of 11 (limit is 8)
[warning] 65-65: src/tests/test_faithfulness.py#L65
Else clause on loop without a break statement, remove the else and de-indent all the code inside it
🧹 Nitpick comments (1)
src/tests/test_faithfulness.py (1)
11-19: Add missing docstring for the helper function.The
validate_metricfunction is missing a docstring explaining its purpose and parameters.def validate_metric(metric_data, expect_success, min_score): + """Validate metric data against expected criteria. + + Args: + metric_data: The metric data to validate + expect_success: Expected success flag (True/False) + min_score: Minimum score threshold + """ assert metric_data.score > min_score, "Score should be greater than specified in the test data"🧰 Tools
🪛 Ruff (0.11.9)
11-11: Missing docstring in public function
(D103)
🪛 Pylint (3.3.7)
[convention] 11-11: Missing function or method docstring
(C0116)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (1)
src/tests/test_faithfulness.py(1 hunks)
🧰 Additional context used
🪛 Ruff (0.11.9)
src/tests/test_faithfulness.py
11-11: Missing docstring in public function
(D103)
🪛 Pylint (3.3.7)
src/tests/test_faithfulness.py
[convention] 1-1: Missing module docstring
(C0114)
[error] 2-2: Unable to import 'deepeval.evaluate'
(E0401)
[error] 3-3: Unable to import 'deepeval.metrics'
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[error] 4-4: Unable to import 'deepeval.test_case'
(E0401)
[error] 5-5: Unable to import 'dotenv'
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[error] 7-7: Unable to import 'src.verifact_manager'
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[convention] 11-11: Missing function or method docstring
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[warning] 65-66: Else clause on loop without a break statement, remove the else and de-indent all the code inside it
(W0120)
🪛 GitHub Check: Codacy Static Code Analysis
src/tests/test_faithfulness.py
[warning] 21-21: src/tests/test_faithfulness.py#L21
Method test_faithfulness_real_output has a cyclomatic complexity of 11 (limit is 8)
[warning] 65-65: src/tests/test_faithfulness.py#L65
Else clause on loop without a break statement, remove the else and de-indent all the code inside it
⏰ Context from checks skipped due to timeout of 90000ms (1)
- GitHub Check: Codacy Static Code Analysis
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Actionable comments posted: 1
🧹 Nitpick comments (3)
src/tests/test_faithfulness.py (3)
1-1: Add module docstring for better documentation.The module is missing a docstring that would help other developers understand the purpose and scope of these faithfulness tests.
+""" +Faithfulness testing module for VerifactManager. + +This module contains tests that evaluate the faithfulness of outputs generated by +the VerifactManager using DeepEval metrics. Tests validate that generated verdicts +are faithful to the evidence retrieved during the fact-checking process. +""" import pytest🧰 Tools
🪛 Pylint (3.3.7)
[convention] 1-1: Missing module docstring
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12-21: Add docstring to improve function documentation.The
validate_metricsfunction would benefit from a docstring explaining its parameters and purpose.def validate_metrics(metric_data, expect_success, min_score): + """ + Validate metric data against expected criteria. + + Args: + metric_data: The metric data object to validate + expect_success: Expected success boolean value + min_score: Minimum score threshold + """ assert metric_data.score > min_score, "Score should be greater than specified in the test data"🧰 Tools
🪛 Ruff (0.11.9)
12-12: Missing docstring in public function
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[convention] 12-12: Missing function or method docstring
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23-32: Add docstring and improve error handling.The function needs documentation and could handle edge cases better.
def handle_evaluation_results(evaluation_results, expect_success, min_score): + """ + Process evaluation results and validate each metric. + + Args: + evaluation_results: List of evaluation result tuples + expect_success: Expected success boolean value + min_score: Minimum score threshold + """ for result in evaluation_results: _, test_result_list = result if test_result_list: for test_result in test_result_list: for metric_data in test_result.metrics_data: validate_metrics(metric_data, expect_success, min_score) else: print("Test result list is None or empty")🧰 Tools
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23-23: Missing docstring in public function
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[convention] 23-23: Missing function or method docstring
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📒 Files selected for processing (1)
src/tests/test_faithfulness.py(1 hunks)
🧰 Additional context used
🪛 Ruff (0.11.9)
src/tests/test_faithfulness.py
12-12: Missing docstring in public function
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🪛 Pylint (3.3.7)
src/tests/test_faithfulness.py
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[convention] 1-1: Missing module docstring
(C0114)
[error] 2-2: Unable to import 'deepeval.evaluate'
(E0401)
[error] 3-3: Unable to import 'deepeval.metrics'
(E0401)
[error] 4-4: Unable to import 'deepeval.test_case'
(E0401)
[error] 5-5: Unable to import 'dotenv'
(E0401)
[error] 7-7: Unable to import 'src.verifact_manager'
(E0401)
[convention] 12-12: Missing function or method docstring
(C0116)
[convention] 23-23: Missing function or method docstring
(C0116)
[convention] 34-34: Missing function or method docstring
(C0116)
⏰ Context from checks skipped due to timeout of 90000ms (1)
- GitHub Check: Codacy Static Code Analysis
🔇 Additional comments (1)
src/tests/test_faithfulness.py (1)
50-61: LGTM! Well-structured async test function.The test function is well-documented and follows good pytest patterns. The async structure is correct, and the delegation to helper functions keeps the main test clean and focused.
| def process_results(results, query, expect_success, min_score): | ||
| for _claim, evidence_list, verdict in results: | ||
| if not verdict or not evidence_list: | ||
| continue | ||
|
|
||
| test_case = LLMTestCase( | ||
| input=query, | ||
| actual_output=verdict.explanation, | ||
| retrieval_context=[str(ev.content) for ev in evidence_list if ev.content], | ||
| ) | ||
|
|
||
| metric = FaithfulnessMetric(include_reason=True, strict_mode=True) | ||
| evaluation_results = evaluate(test_cases=[test_case], metrics=[metric]) | ||
| handle_evaluation_results(evaluation_results, expect_success, min_score) | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add docstring and improve robustness.
The function needs documentation and should handle potential None values more defensively.
def process_results(results, query, expect_success, min_score):
+ """
+ Process VerifactManager results and evaluate faithfulness.
+
+ Args:
+ results: List of (claim, evidence_list, verdict) tuples
+ query: Original query string
+ expect_success: Expected success boolean value
+ min_score: Minimum score threshold
+ """
for _claim, evidence_list, verdict in results:
- if not verdict or not evidence_list:
+ if not verdict or not evidence_list or not verdict.explanation:
continue
test_case = LLMTestCase(
input=query,
actual_output=verdict.explanation,
retrieval_context=[str(ev.content) for ev in evidence_list if ev.content],
)
metric = FaithfulnessMetric(include_reason=True, strict_mode=True)
evaluation_results = evaluate(test_cases=[test_case], metrics=[metric])
handle_evaluation_results(evaluation_results, expect_success, min_score)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def process_results(results, query, expect_success, min_score): | |
| for _claim, evidence_list, verdict in results: | |
| if not verdict or not evidence_list: | |
| continue | |
| test_case = LLMTestCase( | |
| input=query, | |
| actual_output=verdict.explanation, | |
| retrieval_context=[str(ev.content) for ev in evidence_list if ev.content], | |
| ) | |
| metric = FaithfulnessMetric(include_reason=True, strict_mode=True) | |
| evaluation_results = evaluate(test_cases=[test_case], metrics=[metric]) | |
| handle_evaluation_results(evaluation_results, expect_success, min_score) | |
| def process_results(results, query, expect_success, min_score): | |
| """ | |
| Process VerifactManager results and evaluate faithfulness. | |
| Args: | |
| results: List of (claim, evidence_list, verdict) tuples | |
| query: Original query string | |
| expect_success: Expected success boolean value | |
| min_score: Minimum score threshold | |
| """ | |
| for _claim, evidence_list, verdict in results: | |
| if not verdict or not evidence_list or not verdict.explanation: | |
| continue | |
| test_case = LLMTestCase( | |
| input=query, | |
| actual_output=verdict.explanation, | |
| retrieval_context=[str(ev.content) for ev in evidence_list if ev.content], | |
| ) | |
| metric = FaithfulnessMetric(include_reason=True, strict_mode=True) | |
| evaluation_results = evaluate(test_cases=[test_case], metrics=[metric]) | |
| handle_evaluation_results(evaluation_results, expect_success, min_score) |
🧰 Tools
🪛 Ruff (0.11.9)
34-34: Missing docstring in public function
(D103)
🪛 Pylint (3.3.7)
[convention] 34-34: Missing function or method docstring
(C0116)
🤖 Prompt for AI Agents
In src/tests/test_faithfulness.py around lines 34 to 48, add a clear docstring
to the process_results function explaining its purpose, parameters, and
behavior. Improve robustness by adding checks to handle potential None values
for results, query, and verdict.explanation before processing. Also, ensure
evidence_list and its contents are validated to avoid errors during list
comprehension.
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