firefrost-gaming/skill-seekers-reference
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style: Format all Python files with ruff

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- Formatted 103 files to comply with ruff format requirements
- No code logic changes, only formatting/whitespace
- Fixes CI formatting check failures
This commit is contained in:
yusyus
2026-02-08 14:42:27 +03:00
parent 6e4f623b9d
commit 0265de5816
103 changed files with 2241 additions and 2627 deletions
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106
tests/test_chunking_integration.py
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@@ -60,7 +60,7 @@ class TestChunkingDisabledByDefault:
"""Test that LangChain doesn't chunk by default."""
skill_dir = create_test_skill(tmp_path, large_doc=True)
adaptor = get_adaptor('langchain')
adaptor = get_adaptor("langchain")
package_path = adaptor.package(skill_dir, tmp_path)
with open(package_path) as f:
@@ -71,8 +71,8 @@ class TestChunkingDisabledByDefault:
# No chunking metadata
for doc in data:
assert 'is_chunked' not in doc['metadata']
assert 'chunk_index' not in doc['metadata']
assert "is_chunked" not in doc["metadata"]
assert "chunk_index" not in doc["metadata"]
class TestChunkingEnabled:
@@ -82,12 +82,9 @@ class TestChunkingEnabled:
"""Test that LangChain chunks large documents when enabled."""
skill_dir = create_test_skill(tmp_path, large_doc=True)
adaptor = get_adaptor('langchain')
adaptor = get_adaptor("langchain")
package_path = adaptor.package(
skill_dir,
tmp_path,
enable_chunking=True,
chunk_max_tokens=512
skill_dir, tmp_path, enable_chunking=True, chunk_max_tokens=512
)
with open(package_path) as f:
@@ -97,25 +94,22 @@ class TestChunkingEnabled:
assert len(data) > 2, f"Large doc should be chunked, got {len(data)} docs"
# Check for chunking metadata
chunked_docs = [doc for doc in data if doc['metadata'].get('is_chunked')]
chunked_docs = [doc for doc in data if doc["metadata"].get("is_chunked")]
assert len(chunked_docs) > 0, "Should have chunked documents"
# Verify chunk metadata structure
for doc in chunked_docs:
assert 'chunk_index' in doc['metadata']
assert 'total_chunks' in doc['metadata']
assert 'chunk_id' in doc['metadata']
assert "chunk_index" in doc["metadata"]
assert "total_chunks" in doc["metadata"]
assert "chunk_id" in doc["metadata"]
def test_chunking_preserves_small_docs(self, tmp_path):
"""Test that small documents are not chunked."""
skill_dir = create_test_skill(tmp_path, large_doc=False)
adaptor = get_adaptor('langchain')
adaptor = get_adaptor("langchain")
package_path = adaptor.package(
skill_dir,
tmp_path,
enable_chunking=True,
chunk_max_tokens=512
skill_dir, tmp_path, enable_chunking=True, chunk_max_tokens=512
)
with open(package_path) as f:
@@ -125,7 +119,7 @@ class TestChunkingEnabled:
assert len(data) == 2, "Small docs should not be chunked"
for doc in data:
assert 'is_chunked' not in doc['metadata']
assert "is_chunked" not in doc["metadata"]
class TestCodeBlockPreservation:
@@ -158,43 +152,43 @@ More content after code block.
# Create references dir (required)
(skill_dir / "references").mkdir()
adaptor = get_adaptor('langchain')
adaptor = get_adaptor("langchain")
package_path = adaptor.package(
skill_dir,
tmp_path,
enable_chunking=True,
chunk_max_tokens=200, # Small chunks to force splitting
preserve_code_blocks=True
preserve_code_blocks=True,
)
with open(package_path) as f:
data = json.load(f)
# Find chunks with code block
code_chunks = [
doc for doc in data
if '```python' in doc['page_content']
]
code_chunks = [doc for doc in data if "```python" in doc["page_content"]]
# Code block should be in at least one chunk
assert len(code_chunks) >= 1, "Code block should be preserved"
# Code block should be complete (opening and closing backticks)
for chunk in code_chunks:
content = chunk['page_content']
if '```python' in content:
content = chunk["page_content"]
if "```python" in content:
# Should also have closing backticks
assert content.count('```') >= 2, "Code block should be complete"
assert content.count("```") >= 2, "Code block should be complete"
class TestAutoChunkingForRAGPlatforms:
"""Test that chunking is auto-enabled for RAG platforms."""
@pytest.mark.parametrize("platform", [
'langchain',
# Add others after they're updated:
# 'llama-index', 'haystack', 'weaviate', 'chroma', 'faiss', 'qdrant'
])
@pytest.mark.parametrize(
"platform",
[
"langchain",
# Add others after they're updated:
# 'llama-index', 'haystack', 'weaviate', 'chroma', 'faiss', 'qdrant'
],
)
def test_rag_platforms_auto_chunk(self, platform, tmp_path):
"""Test that RAG platforms auto-enable chunking."""
skill_dir = create_test_skill(tmp_path, large_doc=True)
@@ -208,7 +202,7 @@ class TestAutoChunkingForRAGPlatforms:
open_folder_after=False,
skip_quality_check=True,
target=platform,
enable_chunking=False # Explicitly disabled, but should be auto-enabled
enable_chunking=False, # Explicitly disabled, but should be auto-enabled
)
assert success, f"Packaging failed for {platform}"
@@ -221,8 +215,8 @@ class TestAutoChunkingForRAGPlatforms:
# Should have multiple documents/chunks
if isinstance(data, list):
assert len(data) > 2, f"{platform}: Should auto-chunk large docs"
elif isinstance(data, dict) and 'documents' in data:
assert len(data['documents']) > 2, f"{platform}: Should auto-chunk large docs"
elif isinstance(data, dict) and "documents" in data:
assert len(data["documents"]) > 2, f"{platform}: Should auto-chunk large docs"
class TestBaseAdaptorChunkingHelper:
@@ -237,11 +231,7 @@ class TestBaseAdaptorChunkingHelper:
content = "Test content " * 1000 # Large content
metadata = {"source": "test"}
chunks = adaptor._maybe_chunk_content(
content,
metadata,
enable_chunking=False
)
chunks = adaptor._maybe_chunk_content(content, metadata, enable_chunking=False)
# Should return single chunk
assert len(chunks) == 1
@@ -258,10 +248,7 @@ class TestBaseAdaptorChunkingHelper:
metadata = {"source": "test"}
chunks = adaptor._maybe_chunk_content(
content,
metadata,
enable_chunking=True,
chunk_max_tokens=512
content, metadata, enable_chunking=True, chunk_max_tokens=512
)
# Should return single chunk
@@ -282,7 +269,7 @@ class TestBaseAdaptorChunkingHelper:
enable_chunking=True,
chunk_max_tokens=512,
preserve_code_blocks=True,
source_file="test.md"
source_file="test.md",
)
# Should return multiple chunks
@@ -292,12 +279,12 @@ class TestBaseAdaptorChunkingHelper:
for chunk_text, chunk_meta in chunks:
assert isinstance(chunk_text, str)
assert isinstance(chunk_meta, dict)
assert chunk_meta['is_chunked']
assert 'chunk_index' in chunk_meta
assert 'chunk_id' in chunk_meta
assert chunk_meta["is_chunked"]
assert "chunk_index" in chunk_meta
assert "chunk_id" in chunk_meta
# Original metadata preserved
assert chunk_meta['source'] == 'test'
assert chunk_meta['file'] == 'test.md'
assert chunk_meta["source"] == "test"
assert chunk_meta["file"] == "test.md"
class TestChunkingCLIIntegration:
@@ -313,10 +300,10 @@ class TestChunkingCLIIntegration:
skill_dir=skill_dir,
open_folder_after=False,
skip_quality_check=True,
target='langchain',
target="langchain",
enable_chunking=True, # --chunk flag
chunk_max_tokens=512,
preserve_code_blocks=True
preserve_code_blocks=True,
)
assert success
@@ -339,10 +326,10 @@ class TestChunkingCLIIntegration:
skill_dir=skill_dir,
open_folder_after=False,
skip_quality_check=True,
target='langchain',
target="langchain",
enable_chunking=True,
chunk_max_tokens=256, # Small chunks
preserve_code_blocks=True
preserve_code_blocks=True,
)
assert success
@@ -355,10 +342,10 @@ class TestChunkingCLIIntegration:
skill_dir=skill_dir,
open_folder_after=False,
skip_quality_check=True,
target='langchain',
target="langchain",
enable_chunking=True,
chunk_max_tokens=1024, # Large chunks
preserve_code_blocks=True
preserve_code_blocks=True,
)
assert success
@@ -367,9 +354,10 @@ class TestChunkingCLIIntegration:
data_large = json.load(f)
# Small chunk size should produce more chunks
assert len(data_small) > len(data_large), \
assert len(data_small) > len(data_large), (
f"Small chunks ({len(data_small)}) should be more than large chunks ({len(data_large)})"
)
if __name__ == '__main__':
pytest.main([__file__, '-v'])
if __name__ == "__main__":
pytest.main([__file__, "-v"])