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6b8bb0d 1239f44 6b8bb0d 1239f44 6b8bb0d 1239f44 6b8bb0d | 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 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 | """Typer command-line entrypoint for DocuLearn-RAG."""
from __future__ import annotations
import json
from pathlib import Path
from typing import cast
import typer
from pydantic import BaseModel, ValidationError
from src.export import ExportFormat, export
from src.filters import MetadataFilter, filters_to_dict
from src.indexing import ingest as ingest_data
from src.learning import generate_flashcards, generate_quiz
from src.learning import summarize as summarize_learning
from src.rag import answer, retrieve
from src.retrieval_telemetry import load_retrieval_summary
from src.schemas import RetrievedChunk
app = typer.Typer(help="Index PDFs and use grounded DocuLearn-RAG learning features.")
def _parse_filters(value: str | None) -> MetadataFilter | None:
if value is None or not value.strip():
return None
parsed: dict[str, object] = {}
allowed = set(MetadataFilter.model_fields)
for expression in value.split(","):
key, separator, raw_value = expression.partition("=")
key = key.strip()
raw_value = raw_value.strip()
if not separator or not key or not raw_value:
raise typer.BadParameter("Filters must use key=value pairs separated by commas.")
if key not in allowed:
raise typer.BadParameter(
f"Unknown filter '{key}'. Expected one of: {', '.join(sorted(allowed))}."
)
if key == "page":
try:
parsed[key] = int(raw_value)
except ValueError as error:
raise typer.BadParameter("The page filter must be an integer.") from error
elif key == "filenames":
parsed[key] = [item.strip() for item in raw_value.split("|") if item.strip()]
else:
parsed[key] = raw_value
try:
return MetadataFilter.model_validate(parsed)
except ValidationError as error:
raise typer.BadParameter(str(error)) from error
def _write_result(
result: BaseModel,
output: Path | None,
fmt: ExportFormat,
) -> None:
rendered = export(result, fmt=fmt, output=output)
if output is None:
typer.echo(rendered, nl=False)
else:
typer.echo(f"Exported to {rendered}")
def _print_sources(chunks: list[RetrievedChunk]) -> None:
if not chunks:
return
typer.echo("\nSources:")
for index, chunk in enumerate(chunks, start=1):
metadata = chunk.metadata
typer.echo(f"S{index}: {metadata.filename}, page {metadata.page}")
@app.command()
def ingest(recreate: bool = False) -> None:
"""Index all PDFs in the configured data directory."""
count = ingest_data(recreate=recreate)
typer.echo(f"Done. {count} chunks indexed.")
@app.command()
def ask(
question: str,
k: int | None = None,
filters: str | None = None,
) -> None:
"""Ask a grounded question and show its retrieved sources."""
result = answer(question, k=k, filters=filters_to_dict(_parse_filters(filters)))
typer.echo(result.answer)
_print_sources(result.chunks)
@app.command("debug-retrieval")
def debug_retrieval(
question: str,
k: int | None = None,
filters: str | None = None,
as_json: bool = False,
) -> None:
"""Inspect the chunks retrieved for a question."""
chunks = retrieve(question, k=k, filters=filters_to_dict(_parse_filters(filters)))
if as_json:
typer.echo(
json.dumps(
[chunk.model_dump(mode="json") for chunk in chunks],
ensure_ascii=False,
indent=2,
)
)
return
for index, chunk in enumerate(chunks, start=1):
metadata = chunk.metadata
typer.echo(
f"S{index} {metadata.filename} p.{metadata.page} "
f"score={chunk.score:.4f}\n{chunk.text}\n"
)
@app.command(
"retrieval-telemetry",
help="Summarize privacy-safe retrieval pilot telemetry and promotion gates.",
)
def retrieval_telemetry(
path: Path | None = None,
max_fallback_rate: float = 0.01,
max_error_rate: float = 0.01,
max_insufficient_rate: float = 0.01,
max_primary_p95_ms: float | None = None,
min_events: int = 100,
min_shadow_events: int = 30,
output: Path | None = None,
fail_on_gate: bool = False,
) -> None:
summary = load_retrieval_summary(
path,
max_fallback_rate=max_fallback_rate,
max_error_rate=max_error_rate,
max_insufficient_rate=max_insufficient_rate,
max_primary_p95_ms=max_primary_p95_ms,
min_events=min_events,
min_shadow_events=min_shadow_events,
)
rendered = json.dumps(summary, ensure_ascii=False, indent=2) + "\n"
if output is None:
typer.echo(rendered, nl=False)
else:
output.parent.mkdir(parents=True, exist_ok=True)
_ = output.write_text(rendered, encoding="utf-8")
typer.echo(f"Exported to {output}")
gate = cast(dict[str, object], summary["promotion_gate"])
status = str(gate["status"])
if fail_on_gate and status != "pass":
raise typer.Exit(code=1)
@app.command()
def summarize(
document: str | None = None,
query: str | None = None,
filters: str | None = None,
k: int | None = None,
output: Path | None = None,
fmt: ExportFormat = "text",
) -> None:
"""Create a grounded summary."""
result = summarize_learning(
document=document,
query=query,
filters=filters_to_dict(_parse_filters(filters)),
k=k,
)
_write_result(result, output, fmt)
@app.command()
def quiz(
document: str | None = None,
query: str | None = None,
filters: str | None = None,
count: int | None = None,
k: int | None = None,
output: Path | None = None,
fmt: ExportFormat = "text",
) -> None:
"""Generate a grounded multiple-choice quiz."""
result = generate_quiz(
document=document,
query=query,
filters=filters_to_dict(_parse_filters(filters)),
count=count,
k=k,
)
_write_result(result, output, fmt)
@app.command()
def flashcards(
document: str | None = None,
query: str | None = None,
filters: str | None = None,
count: int | None = None,
k: int | None = None,
output: Path | None = None,
fmt: ExportFormat = "text",
) -> None:
"""Generate grounded flashcards."""
result = generate_flashcards(
document=document,
query=query,
filters=filters_to_dict(_parse_filters(filters)),
count=count,
k=k,
)
_write_result(result, output, fmt)
if __name__ == "__main__":
app()
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