from dataclasses import dataclass, field
from datetime import datetime
import hashlib
@dataclass
class CodeBlock:
id: str
doc_id: str
chunk_id: str
content: str
language: str
@dataclass
class Chunk:
chunk_id: str
doc_id: str
content: str
metadata: dict
chunk_index: int
header_path: str
start_pos: int
end_pos: int
file_path: str
modified_time: datetime
parent_chunk_id: str | None = None
content_hash: str = field(default="", init=False)
def __post_init__(self):
"""Compute content hash after initialization."""
if not self.content_hash:
self.content_hash = self.compute_content_hash()
def compute_content_hash(self) -> str:
"""Compute SHA256 hash of chunk content for change detection."""
return hashlib.sha256(self.content.encode("utf-8")).hexdigest()
@dataclass
class ChunkResult:
chunk_id: str
doc_id: str
score: float
header_path: str
file_path: str
content: str = ""
parent_chunk_id: str | None = None
parent_content: str | None = None
def to_dict(self):
result = {
"chunk_id": self.chunk_id,
"doc_id": self.doc_id,
"score": self.score,
"header_path": self.header_path,
"file_path": self.file_path,
"content": self.content,
}
if self.parent_chunk_id is not None:
result["parent_chunk_id"] = self.parent_chunk_id
if self.parent_content is not None:
result["parent_content"] = self.parent_content
return result
@dataclass
class CompressionStats:
original_count: int
after_threshold: int
after_content_dedup: int
after_ngram_dedup: int
after_dedup: int
after_doc_limit: int
clusters_merged: int
def to_dict(self):
return {
"original_count": self.original_count,
"after_threshold": self.after_threshold,
"after_content_dedup": self.after_content_dedup,
"after_ngram_dedup": self.after_ngram_dedup,
"after_dedup": self.after_dedup,
"after_doc_limit": self.after_doc_limit,
"clusters_merged": self.clusters_merged,
}
@dataclass
class SearchStrategyStats:
vector_count: int | None = None
keyword_count: int | None = None
graph_count: int | None = None
code_count: int | None = None
tag_expansion_count: int | None = None
def to_dict(self):
result = {}
if self.vector_count is not None:
result["vector_count"] = self.vector_count
if self.keyword_count is not None:
result["keyword_count"] = self.keyword_count
if self.graph_count is not None:
result["graph_count"] = self.graph_count
if self.code_count is not None:
result["code_count"] = self.code_count
if self.tag_expansion_count is not None:
result["tag_expansion_count"] = self.tag_expansion_count
return result
@dataclass
class Document:
id: str
content: str
metadata: dict[str, str | list[str] | int | float | bool]
links: list[str]
tags: list[str]
file_path: str
modified_time: datetime
chunks: list[Chunk] | None = None
@dataclass
class CommitResult:
"""Git commit search result."""
hash: str
title: str
author: str
committer: str
timestamp: int
message: str
files_changed: list[str]
delta_truncated: str
score: float
repo_path: str
@dataclass
class GitSearchResponse:
"""Response from git history search."""
results: list[CommitResult]
query: str
total_commits_indexed: int
@dataclass
class ReconciliationResult:
"""Result of index reconciliation operation."""
added_count: int = 0
removed_count: int = 0
moved_count: int = 0
failed_count: int = 0
