"""API response models for MCP tool return types."""
from __future__ import annotations
from typing import TYPE_CHECKING
from pydantic import BaseModel
from semantic_code_mcp.models.domain import SearchResult
if TYPE_CHECKING:
from semantic_code_mcp.services.search_service import SearchOutcome
class SearchTimings(BaseModel):
"""Timing breakdown for search operation."""
embedding_ms: float
search_ms: float
total_ms: float
indexing_ms: float | None = None
class SearchStats(BaseModel):
"""Statistics about search results."""
results_count: int
filtered_out: int
unique_files: int
tokens_estimate: int
@classmethod
def from_outcome(cls, outcome: SearchOutcome) -> SearchStats:
total_content = "\n".join(r.content for r in outcome.results)
tokens_estimate = len(total_content) // 4
return cls(
results_count=len(outcome.results),
filtered_out=outcome.filtered_count,
unique_files=len({r.file_path for r in outcome.results}),
tokens_estimate=tokens_estimate,
)
class IndexStatusSummary(BaseModel):
"""Summary of index status for search debug info."""
files_count: int
chunks_count: int
was_stale: bool | None = None
class IndexResultSummary(BaseModel):
"""Summary of indexing result for search debug info."""
files_indexed: int
chunks_indexed: int
class SearchDebugInfo(BaseModel):
"""Debug information included in search response."""
timings: SearchTimings
stats: SearchStats
index_status: IndexStatusSummary
index_result: IndexResultSummary
class FormattedSearchResult(BaseModel):
"""A search result formatted for response."""
file_path: str
line_start: int
line_end: int
name: str
chunk_type: str
content: str
score: float
truncated: bool = False
@classmethod
def from_domain(
cls,
result: SearchResult,
max_lines: int = 50,
) -> FormattedSearchResult:
content = result.content
lines = content.split("\n")
truncated = len(lines) > max_lines
if truncated:
content = "\n".join(lines[:max_lines]) + "\n... (truncated)"
return cls(
file_path=result.file_path,
line_start=result.line_start,
line_end=result.line_end,
name=result.name,
chunk_type=result.chunk_type.value,
content=content,
score=round(result.score, 3),
truncated=truncated,
)
class SearchResponse(BaseModel):
"""Complete search response with results and debug info."""
results: list[FormattedSearchResult]
debug: SearchDebugInfo
class IndexCodebaseResponse(BaseModel):
"""Response from index_codebase tool."""
files_indexed: int
chunks_indexed: int
files_deleted: int
duration_seconds: float
class IndexStatusResponse(BaseModel):
"""Response from index_status tool."""
is_indexed: bool
last_updated: str | None
files_count: int
chunks_count: int
class ErrorResponse(BaseModel):
"""Error response for tool failures."""
error: str
