File size: 2,883 Bytes
30e6218 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | """Request and response models for the HTTP API."""
from __future__ import annotations
from typing import Any, Dict, List, Literal, Optional
from pydantic import BaseModel, ConfigDict, Field
RetrievalModeName = Literal["lexical", "vector", "hybrid"]
class SearchRequest(BaseModel):
"""Retrieval without generation. Unknown fields are rejected."""
model_config = ConfigDict(extra="forbid")
text: str = Field(..., min_length=1, max_length=4000, description="Query text")
top_k: Optional[int] = Field(default=None, ge=1, description="Results to return")
mode: RetrievalModeName = Field(
default="hybrid",
description="lexical (BM25), vector (dense), or hybrid (RRF of both). "
"hybrid degrades to lexical, and says so, when no embedding provider is configured.",
)
doc_ids: Optional[List[str]] = Field(
default=None,
max_length=50,
description="Restrict retrieval to these documents. An empty list matches nothing.",
)
alpha: float = Field(default=0.5, ge=0.0, le=1.0, description="Dense weight in hybrid fusion")
use_reranker: bool = Field(
default=False, description="Rerank the candidate pool with the configured reranker"
)
class QueryRequest(SearchRequest):
"""Retrieval plus grounded answer generation."""
generate: bool = Field(
default=True,
description="When false, or when no generation provider is configured, "
"return supporting excerpts instead of a generated answer.",
)
class JudgeRequest(BaseModel):
model_config = ConfigDict(extra="forbid")
question: str = Field(..., min_length=1, max_length=4000)
answer: str = Field(..., min_length=1, max_length=20000)
context: str = Field(..., min_length=1, max_length=40000)
class DocumentResponse(BaseModel):
doc_id: str
version: int
filename: str
extension: str
content_hash: str
size_bytes: int
status: str
chunk_count: int
page_count: Optional[int] = None
created_at: str
updated_at: str
chunking_config: str
embedding_identity: Optional[str] = None
metadata: Dict[str, Any] = Field(default_factory=dict)
error: Optional[str] = None
class UploadResponse(BaseModel):
document: DocumentResponse
created: bool
duplicate_of: Optional[str] = None
warnings: List[str] = Field(default_factory=list)
timings_ms: Dict[str, float] = Field(default_factory=dict)
evicted: List[str] = Field(
default_factory=list,
description="Documents removed (oldest first) to stay within MAX_DOCUMENTS",
)
class DeleteResponse(BaseModel):
doc_id: str
status: Literal["deleted"]
removed_chunks: int
removed_vectors: int
file_removed: bool
class ErrorResponse(BaseModel):
error: str
code: Optional[str] = None
request_id: Optional[str] = None
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