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pridanie_testov

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Ján Pták 2026-08-16 16:14:32 +02:00
parent 67b51683cb
commit 07134b7681
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test/test_rag.py
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@ -1,6 +1,8 @@
from __future__ import annotations from __future__ import annotations
import json
import os import os
import sqlite3
from pathlib import Path from pathlib import Path
from typing import Any from typing import Any
@ -1835,3 +1837,829 @@ def test_rag_endpoint_live_context_has_source_boundaries(
"context" "context"
] ]
) )
def create_section_lead_test_db(
tmp_path: Path,
) -> Path:
db_path = (
tmp_path
/ "section_lead.sqlite"
)
with sqlite3.connect(
db_path
) as conn:
conn.execute(
"""
CREATE TABLE chunks (
id INTEGER PRIMARY KEY,
chunk_id TEXT NOT NULL,
document_path TEXT NOT NULL,
chunk_index INTEGER NOT NULL,
heading_paths_json TEXT NOT NULL,
text TEXT NOT NULL,
published INTEGER NOT NULL
)
"""
)
return db_path
def insert_section_lead_chunk(
db_path: Path,
*,
chunk_id: str,
document_path: str,
chunk_index: int,
heading_paths: list[Any],
text: str,
published: bool = True,
) -> None:
with sqlite3.connect(
db_path
) as conn:
conn.execute(
"""
INSERT INTO chunks (
chunk_id,
document_path,
chunk_index,
heading_paths_json,
text,
published
)
VALUES (?, ?, ?, ?, ?, ?)
""",
(
chunk_id,
document_path,
chunk_index,
json.dumps(
heading_paths,
ensure_ascii=False,
),
text,
(
1
if published
else 0
),
),
)
def section_lead_primary_result() -> dict[str, Any]:
return {
"chunk_id": (
"pages/students/2016/"
"jan_holp/README.md::chunk-3"
),
"chunk_index": 3,
"document_path": (
"pages/students/2016/"
"jan_holp/README.md"
),
"title": "Ján Holp",
"author": "Daniel Hladek",
"published": True,
"heading_paths": [
[
"Ján Holp",
"Diplomová práca 2021",
],
],
"text": (
"Najrelevantnejší úsek "
"z neskoršej časti sekcie."
),
"source_url": (
"https://zp.kemt.fei.tuke.sk/"
"students/2016/jan_holp"
),
"match_strategy": "vector",
"fts_rank": None,
"vector_rank": 1,
"vector_score": 0.91,
"hybrid_score": 0.03,
}
def test_load_section_lead_chunk_uses_earliest_chunk_in_same_section(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
heading_paths = result[
"heading_paths"
]
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
),
document_path=result[
"document_path"
],
chunk_index=0,
heading_paths=heading_paths,
text=(
"Názov diplomovej práce: "
"Systém získavania informácií."
),
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-1"
),
document_path=result[
"document_path"
],
chunk_index=1,
heading_paths=heading_paths,
text=(
"Druhý chunk rovnakej sekcie."
),
)
with sqlite3.connect(
db_path
) as conn:
conn.row_factory = (
sqlite3.Row
)
lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=False,
)
)
assert lead is not None
assert (
lead["chunk_index"]
== 0
)
assert (
lead["chunk_id"]
== (
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
)
)
assert (
lead["text"]
== (
"Názov diplomovej práce: "
"Systém získavania informácií."
)
)
def test_load_section_lead_chunk_ignores_other_sections(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
),
document_path=result[
"document_path"
],
chunk_index=0,
heading_paths=[
[
"Ján Holp",
"Bakalárska práca 2019",
],
],
text=(
"Toto je iná sekcia."
),
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-2"
),
document_path=result[
"document_path"
],
chunk_index=2,
heading_paths=result[
"heading_paths"
],
text=(
"Správny začiatok "
"diplomovej sekcie."
),
)
with sqlite3.connect(
db_path
) as conn:
conn.row_factory = (
sqlite3.Row
)
lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=False,
)
)
assert lead is not None
assert (
lead["chunk_index"]
== 2
)
assert (
lead["text"]
== (
"Správny začiatok "
"diplomovej sekcie."
)
)
def test_load_section_lead_chunk_ignores_other_documents(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2017/"
"other/README.md::chunk-0"
),
document_path=(
"pages/students/2017/"
"other/README.md"
),
chunk_index=0,
heading_paths=result[
"heading_paths"
],
text=(
"Rovnaká sekcia, "
"ale iný dokument."
),
)
with sqlite3.connect(
db_path
) as conn:
conn.row_factory = (
sqlite3.Row
)
lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=False,
)
)
assert lead is None
def test_load_section_lead_chunk_returns_none_when_primary_is_section_start(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
result[
"chunk_id"
] = (
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
)
result[
"chunk_index"
] = 0
insert_section_lead_chunk(
db_path,
chunk_id=result[
"chunk_id"
],
document_path=result[
"document_path"
],
chunk_index=0,
heading_paths=result[
"heading_paths"
],
text=result[
"text"
],
)
with sqlite3.connect(
db_path
) as conn:
conn.row_factory = (
sqlite3.Row
)
lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=False,
)
)
assert lead is None
def test_load_section_lead_chunk_returns_none_without_heading_paths(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
result[
"heading_paths"
] = []
with sqlite3.connect(
db_path
) as conn:
conn.row_factory = (
sqlite3.Row
)
lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=False,
)
)
assert lead is None
def test_load_section_lead_chunk_respects_published_only(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
),
document_path=result[
"document_path"
],
chunk_index=0,
heading_paths=result[
"heading_paths"
],
text=(
"Nepublikovaný začiatok "
"sekcie."
),
published=False,
)
with sqlite3.connect(
db_path
) as conn:
conn.row_factory = (
sqlite3.Row
)
published_lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=True,
)
)
unrestricted_lead = (
rag_utils.load_section_lead_chunk(
conn,
result,
published_only=False,
)
)
assert (
published_lead
is None
)
assert (
unrestricted_lead
is not None
)
def test_expand_results_with_section_leads_preserves_primary_retrieval_data(
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
),
document_path=result[
"document_path"
],
chunk_index=0,
heading_paths=result[
"heading_paths"
],
text=(
"Začiatok relevantnej sekcie."
),
)
expanded = (
rag_utils.expand_results_with_section_leads(
db_path,
[
result
],
published_only=False,
)
)
assert (
len(
expanded
)
== 1
)
item = expanded[
0
]
assert (
item[
"chunk_id"
]
== result[
"chunk_id"
]
)
assert (
item[
"hybrid_score"
]
== result[
"hybrid_score"
]
)
assert (
item[
"vector_rank"
]
== result[
"vector_rank"
]
)
assert (
item[
"section_lead_text"
]
== (
"Začiatok relevantnej sekcie."
)
)
assert (
item[
"context_expansion"
][
"applied"
]
is True
)
assert (
item[
"context_expansion"
][
"primary_chunk_id"
]
== result[
"chunk_id"
]
)
assert (
item[
"context_expansion"
][
"lead_chunk_index"
]
== 0
)
def test_build_source_text_combines_section_lead_and_primary_text() -> None:
result = (
section_lead_primary_result()
)
result[
"section_lead_text"
] = (
"Názov diplomovej práce: "
"Systém získavania informácií."
)
text = (
rag_utils.build_source_text(
result
)
)
assert (
"ZAČIATOK RELEVANTNEJ SEKCIE"
in text
)
assert (
"Názov diplomovej práce: "
"Systém získavania informácií."
in text
)
assert (
"NAJRELEVANTNEJŠÍ NÁJDENÝ ÚSEK"
in text
)
assert (
result[
"text"
]
in text
)
def test_build_source_text_does_not_duplicate_identical_text() -> None:
result = (
section_lead_primary_result()
)
result[
"section_lead_text"
] = result[
"text"
]
text = (
rag_utils.build_source_text(
result
)
)
assert (
text
== result[
"text"
]
)
def test_build_rag_context_expands_section_lead_end_to_end(
monkeypatch: pytest.MonkeyPatch,
tmp_path: Path,
) -> None:
db_path = (
create_section_lead_test_db(
tmp_path
)
)
result = (
section_lead_primary_result()
)
insert_section_lead_chunk(
db_path,
chunk_id=(
"pages/students/2016/"
"jan_holp/README.md::chunk-0"
),
document_path=result[
"document_path"
],
chunk_index=0,
heading_paths=result[
"heading_paths"
],
text=(
"Názov diplomovej práce: "
"Systém získavania informácií "
"v slovenskom jazyku."
),
)
def fake_search_database(
db_path_arg: Path,
query: str,
limit: int,
*,
published_only: bool,
max_per_document: int,
) -> dict[str, Any]:
assert (
db_path_arg
== db_path
)
assert (
max_per_document
== 1
)
return {
"engine": (
"hybrid_fts5_embeddings"
),
"strategies": [
"vector"
],
"results": [
result
],
}
monkeypatch.setattr(
rag_utils,
"search_database",
fake_search_database,
)
response = (
build_rag_context(
db_path,
(
"Aká je téma diplomovej "
"práce Jána Holpa?"
),
limit=5,
max_per_document=1,
)
)
assert (
response[
"source_count"
]
== 1
)
assert (
len(
response[
"sources"
]
)
== 1
)
source = response[
"sources"
][0]
assert (
source[
"retrieval"
][
"hybrid_score"
]
== result[
"hybrid_score"
]
)
assert (
"Názov diplomovej práce: "
"Systém získavania informácií "
"v slovenskom jazyku."
in source[
"text"
]
)
assert (
result[
"text"
]
in source[
"text"
]
)
assert (
"Názov diplomovej práce: "
"Systém získavania informácií "
"v slovenskom jazyku."
in response[
"context"
]
)
assert (
result[
"text"
]
in response[
"context"
]
)