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109 lines
3.3 KiB
Python
109 lines
3.3 KiB
Python
from types import SimpleNamespace
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import pytest
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from mirage.cache.index import RAMIndexCacheStore
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from mirage.io.types import materialize
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from mirage.types import PathSpec
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from mirage.utils.key_prefix import mount_key
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def document(document_id: str, name: str, slug: str | None = None) -> dict:
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metadata = []
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if slug is not None:
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metadata = [{"name": "slug", "value": slug}]
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return {
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"id": document_id,
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"name": name,
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"doc_metadata": metadata,
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"enabled": True,
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"indexing_status": "completed",
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"archived": False,
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"tokens": 4,
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"data_source_type": "upload_file",
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"data_source_detail_dict": {
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"upload_file": {
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"size": 12
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}
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},
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"created_at": 1716282000,
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}
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def accessor() -> SimpleNamespace:
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return SimpleNamespace(config=SimpleNamespace(slug_metadata_name="slug"))
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@pytest.mark.asyncio
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async def test_search_command_resolves_globs_and_passes_multiple_documents(
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monkeypatch):
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from mirage.commands.builtin.dify import search as command_search
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from mirage.core.dify import search, tree
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calls: list[tuple[list[PathSpec], dict]] = []
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async def list_documents(config):
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return [
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document("doc-1", "API", "guides/api.md"),
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document("doc-2", "Auth", "guides/auth.md"),
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]
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async def search_segments(accessor, query, paths, index, **kwargs):
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calls.append((paths, kwargs))
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return b"api\nauth"
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monkeypatch.setattr(tree, "list_all_documents", list_documents)
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monkeypatch.setattr(search, "search_segments", search_segments)
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stdout, io = await command_search(
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accessor(),
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[
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PathSpec(resource_path=mount_key("/knowledge/guides/*.md",
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"/knowledge"),
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virtual="/knowledge/guides/*.md",
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directory="/knowledge/guides",
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pattern="*.md",
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resolved=False)
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],
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"login",
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index=RAMIndexCacheStore(),
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)
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assert await materialize(stdout) == b"api\nauth"
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assert io.reads == {}
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assert io.cache == []
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assert [path.virtual for path in calls[0][0]] == [
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"/knowledge/guides/api.md",
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"/knowledge/guides/auth.md",
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]
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assert calls[0][1]["mount_prefix"] == "/knowledge"
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@pytest.mark.asyncio
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async def test_search_command_root_searches_whole_dataset(monkeypatch):
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from mirage.commands.builtin.dify import search as command_search
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from mirage.core.dify import search
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calls: list[tuple[list[PathSpec], dict]] = []
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async def search_segments(accessor, query, paths, index, **kwargs):
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calls.append((paths, kwargs))
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return b"dataset"
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monkeypatch.setattr(search, "search_segments", search_segments)
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root = PathSpec(resource_path=mount_key("/knowledge", "/knowledge"),
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virtual="/knowledge",
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directory="/knowledge")
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stdout, _ = await command_search(accessor(), [root],
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"anything",
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index=RAMIndexCacheStore())
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assert await materialize(stdout) == b"dataset"
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assert calls == [([], {
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"method": "semantic",
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"top_k": 10,
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"threshold": 0.0,
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"mount_prefix": "/knowledge"
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})]
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