153 lines
4.4 KiB
Python
153 lines
4.4 KiB
Python
import json
|
|
|
|
import pytest
|
|
|
|
from haiku.rag.app import HaikuRAGApp
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_app_info_outputs(temp_db_path, capsys):
|
|
# Build a minimal LanceDB with settings, documents, and chunks without using Store
|
|
import lancedb
|
|
from lancedb.pydantic import LanceModel, Vector
|
|
from pydantic import Field
|
|
|
|
db = lancedb.connect(temp_db_path)
|
|
|
|
class SettingsRecord(LanceModel):
|
|
id: str = Field(default="settings")
|
|
settings: str = Field(default="{}")
|
|
|
|
class DocumentRecord(LanceModel):
|
|
id: str
|
|
content: str
|
|
|
|
class ChunkRecord(LanceModel):
|
|
id: str
|
|
document_id: str
|
|
content: str
|
|
vector: Vector(3) # type: ignore
|
|
|
|
settings_tbl = db.create_table("settings", schema=SettingsRecord)
|
|
docs_tbl = db.create_table("documents", schema=DocumentRecord)
|
|
chunks_tbl = db.create_table("chunks", schema=ChunkRecord)
|
|
|
|
# Insert one of each - using the new config format
|
|
settings_tbl.add(
|
|
[
|
|
SettingsRecord(
|
|
id="settings",
|
|
settings=json.dumps(
|
|
{
|
|
"version": "1.2.3",
|
|
"embeddings": {
|
|
"model": {
|
|
"provider": "openai",
|
|
"name": "text-embedding-3-small",
|
|
"vector_dim": 3,
|
|
}
|
|
},
|
|
}
|
|
),
|
|
)
|
|
]
|
|
)
|
|
docs_tbl.add([DocumentRecord(id="doc-1", content="hello")])
|
|
chunks_tbl.add(
|
|
[ChunkRecord(id="c1", document_id="doc-1", content="c", vector=[0.1, 0.2, 0.3])]
|
|
)
|
|
|
|
app = HaikuRAGApp(db_path=temp_db_path)
|
|
await app.info()
|
|
|
|
out = capsys.readouterr().out
|
|
# Validate expected content substrings
|
|
# Note: Rich console may wrap long paths to new lines, so check separately
|
|
assert "path:" in out
|
|
assert str(temp_db_path) in out
|
|
assert "haiku.rag version (db):" in out
|
|
assert "embeddings: openai/text-embedding-3-small (dim: 3)" in out
|
|
assert "documents: 1" in out
|
|
assert "chunks: 1" in out
|
|
|
|
# Vector index should not exist (only 1 chunk, need 256)
|
|
assert "vector index: ✗ not created" in out
|
|
assert "need 255 more chunks" in out
|
|
|
|
# Table versions should be shown
|
|
assert "versions (documents):" in out
|
|
assert "versions (chunks):" in out
|
|
|
|
# Package versions section
|
|
assert "lancedb:" in out
|
|
assert "haiku.rag:" in out
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_app_info_with_vector_index(temp_db_path, capsys):
|
|
# Build a database with enough chunks to create a vector index
|
|
import lancedb
|
|
from lancedb.pydantic import LanceModel, Vector
|
|
from pydantic import Field
|
|
|
|
db = lancedb.connect(temp_db_path)
|
|
|
|
class SettingsRecord(LanceModel):
|
|
id: str = Field(default="settings")
|
|
settings: str = Field(default="{}")
|
|
|
|
class DocumentRecord(LanceModel):
|
|
id: str
|
|
content: str
|
|
|
|
class ChunkRecord(LanceModel):
|
|
id: str
|
|
document_id: str
|
|
content: str
|
|
vector: Vector(3) # type: ignore
|
|
|
|
settings_tbl = db.create_table("settings", schema=SettingsRecord)
|
|
docs_tbl = db.create_table("documents", schema=DocumentRecord)
|
|
chunks_tbl = db.create_table("chunks", schema=ChunkRecord)
|
|
|
|
# Insert settings
|
|
settings_tbl.add(
|
|
[
|
|
SettingsRecord(
|
|
id="settings",
|
|
settings='{"version": "1.0.0", "embeddings": {"model": {"provider": "ollama", "name": "test", "vector_dim": 3}}}',
|
|
)
|
|
]
|
|
)
|
|
|
|
# Insert document
|
|
docs_tbl.add([DocumentRecord(id="doc-1", content="test")])
|
|
|
|
# Insert 512 chunks to allow index creation (PQ needs more than 256 for training)
|
|
chunks = [
|
|
ChunkRecord(
|
|
id=f"chunk-{i}",
|
|
document_id="doc-1",
|
|
content=f"content {i}",
|
|
vector=[0.1 * i, 0.2 * i, 0.3 * i],
|
|
)
|
|
for i in range(512)
|
|
]
|
|
chunks_tbl.add(chunks)
|
|
|
|
# Create vector index
|
|
chunks_tbl.create_index(metric="cosine", index_type="IVF_PQ")
|
|
|
|
app = HaikuRAGApp(db_path=temp_db_path)
|
|
await app.info()
|
|
|
|
out = capsys.readouterr().out
|
|
|
|
# Check vector index exists
|
|
assert "vector index: ✓ exists" in out
|
|
assert "indexed chunks: 512" in out
|
|
assert "unindexed chunks: 0" in out
|
|
|
|
# Check basic info still present
|
|
assert "documents: 1" in out
|
|
assert "chunks: 512" in out
|