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border-red-post-nalati/backend/app/schemas/rag.py
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Python

"""Provider-independent, non-streaming Chat Completions preparation contracts."""
from datetime import datetime
from typing import Literal
from uuid import UUID
from pydantic import BaseModel, Field
from app.schemas.catalog import Input
from app.schemas.indexing import ChunkProvenance
class CompletionOptions(Input):
model: str = Field(pattern=r"^[A-Za-z0-9][A-Za-z0-9._:/-]{0,127}$")
output_tokens: int = Field(512, ge=1, le=4096)
token_parameter: Literal["max_completion_tokens", "max_tokens"] = "max_completion_tokens"
instruction_role: Literal["system", "developer"] = "system"
temperature: float | None = Field(None, ge=0, le=2)
class PrepareContext(Input):
retrieval_run_id: UUID
completion: CompletionOptions
max_input_characters: int = Field(10000, ge=1024, le=24000)
max_evidence: int = Field(5, ge=1, le=10)
class Evidence(ChunkProvenance):
citation_id: str
chunk_id: UUID
chunk_ordinal: int
retrieval_rank: int
text: str
text_sha256: str
start_offset: int
end_offset: int
class ExcludedEvidence(BaseModel):
chunk_id: UUID
reason: Literal["overlap", "budget", "evidence_limit"]
class ContextRead(BaseModel):
id: UUID
kind: Literal["prepared_request"] = "prepared_request"
model_called: Literal[False] = False
status: Literal["prepared", "insufficient_evidence"]
reason: Literal["candidates_available", "no_candidates", "context_budget"]
retrieval_run_id: UUID
retrieval_mode: Literal["keyword_chunks", "vector", "hybrid"]
query: str
text_index_version_id: UUID
text_generation: int
catalog_revision: int
vector_version_id: UUID | None
vector_generation: int | None
corpus_fingerprint: str
prompt_version: Literal["nalati-evidence-v1"] = "nalati-evidence-v1"
completion: CompletionOptions
max_input_characters: int
input_characters: int
max_evidence: int
evidence: list[Evidence]
excluded: list[ExcludedEvidence]
request_body: dict | None
request_sha256: str | None
created_at: datetime
class CompletionUsage(BaseModel):
prompt_tokens: int = Field(ge=0, strict=True)
completion_tokens: int = Field(ge=0, strict=True)
total_tokens: int = Field(ge=0, strict=True)
class ParsedCompletion(BaseModel):
status: Literal["answer_candidate", "insufficient_evidence", "incomplete", "refused"]
completion_id: str
model: str
answer: str | None
citations: list[str]
usage: CompletionUsage | None