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style: ruff format remaining 14 files

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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
yusyus
2026-03-01 10:54:45 +03:00
parent 6c31990941
commit 68bdbe8307
14 changed files with 88 additions and 43 deletions
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9
src/skill_seekers/cli/adaptors/base.py
View File

@@ -371,7 +371,10 @@ class SkillAdaptor(ABC):
# If overlap is at the default value but chunk size was customized,
# scale overlap proportionally (10% of chunk size, min DEFAULT_CHUNK_OVERLAP_TOKENS)
effective_overlap = chunk_overlap_tokens
if chunk_overlap_tokens == DEFAULT_CHUNK_OVERLAP_TOKENS and chunk_max_tokens != DEFAULT_CHUNK_TOKENS:
if (
chunk_overlap_tokens == DEFAULT_CHUNK_OVERLAP_TOKENS
and chunk_max_tokens != DEFAULT_CHUNK_TOKENS
):
effective_overlap = max(DEFAULT_CHUNK_OVERLAP_TOKENS, chunk_max_tokens // 10)
chunker = RAGChunker(
@@ -518,9 +521,7 @@ class SkillAdaptor(ABC):
for i in range(0, len(documents), batch_size):
batch = documents[i : i + batch_size]
try:
response = client.embeddings.create(
input=batch, model="text-embedding-3-small"
)
response = client.embeddings.create(input=batch, model="text-embedding-3-small")
embeddings.extend([item.embedding for item in response.data])
print(f" ✓ Embedded {min(i + batch_size, len(documents))}/{len(documents)}")
except Exception as e:

8
src/skill_seekers/cli/adaptors/chroma.py
View File

@@ -91,7 +91,9 @@ class ChromaAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks to parallel arrays
@@ -123,7 +125,9 @@ class ChromaAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks to parallel arrays

8
src/skill_seekers/cli/adaptors/faiss_helpers.py
View File

@@ -93,7 +93,9 @@ class FAISSHelpers(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks to parallel arrays
@@ -124,7 +126,9 @@ class FAISSHelpers(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks to parallel arrays

8
src/skill_seekers/cli/adaptors/haystack.py
View File

@@ -74,7 +74,9 @@ class HaystackAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as documents
@@ -109,7 +111,9 @@ class HaystackAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as documents

8
src/skill_seekers/cli/adaptors/langchain.py
View File

@@ -74,7 +74,9 @@ class LangChainAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks to documents
@@ -104,7 +106,9 @@ class LangChainAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks to documents

8
src/skill_seekers/cli/adaptors/llama_index.py
View File

@@ -89,7 +89,9 @@ class LlamaIndexAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as nodes
@@ -126,7 +128,9 @@ class LlamaIndexAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as nodes

21
src/skill_seekers/cli/adaptors/pinecone_adaptor.py
View File

@@ -38,7 +38,9 @@ class PineconeAdaptor(SkillAdaptor):
"""Generate deterministic ID from content and metadata."""
return self._generate_deterministic_id(content, metadata, format="hex")
def _truncate_text_for_metadata(self, text: str, max_bytes: int = PINECONE_METADATA_BYTES_LIMIT) -> str:
def _truncate_text_for_metadata(
self, text: str, max_bytes: int = PINECONE_METADATA_BYTES_LIMIT
) -> str:
"""Truncate text to fit within Pinecone's metadata byte limit.
Pinecone limits metadata to 40KB per vector. This truncates
@@ -120,7 +122,9 @@ class PineconeAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
for chunk_text, chunk_meta in chunks:
@@ -155,7 +159,9 @@ class PineconeAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
for chunk_text, chunk_meta in chunks:
@@ -281,10 +287,7 @@ class PineconeAdaptor(SkillAdaptor):
if not api_key:
return {
"success": False,
"message": (
"PINECONE_API_KEY not set. "
"Set via env var or pass api_key parameter."
),
"message": ("PINECONE_API_KEY not set. Set via env var or pass api_key parameter."),
}
# Load package
@@ -332,7 +335,9 @@ class PineconeAdaptor(SkillAdaptor):
# Create index if it doesn't exist
existing_indexes = [idx.name for idx in pc.list_indexes()]
if index_name not in existing_indexes:
print(f"🔧 Creating Pinecone index: {index_name} (dimension={dimension}, metric={metric})")
print(
f"🔧 Creating Pinecone index: {index_name} (dimension={dimension}, metric={metric})"
)
pc.create_index(
name=index_name,
dimension=dimension,

8
src/skill_seekers/cli/adaptors/qdrant.py
View File

@@ -88,7 +88,9 @@ class QdrantAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as points
@@ -139,7 +141,9 @@ class QdrantAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as points

8
src/skill_seekers/cli/adaptors/weaviate.py
View File

@@ -156,7 +156,9 @@ class WeaviateAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file="SKILL.md",
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as objects
@@ -199,7 +201,9 @@ class WeaviateAdaptor(SkillAdaptor):
chunk_max_tokens=kwargs.get("chunk_max_tokens", DEFAULT_CHUNK_TOKENS),
preserve_code_blocks=kwargs.get("preserve_code_blocks", True),
source_file=ref_file.name,
chunk_overlap_tokens=kwargs.get("chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS),
chunk_overlap_tokens=kwargs.get(
"chunk_overlap_tokens", DEFAULT_CHUNK_OVERLAP_TOKENS
),
)
# Add all chunks as objects