mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-04 12:13:05 +00:00
Alex
574f96341e
The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
502 lines
20 KiB
Python
502 lines
20 KiB
Python
from unittest.mock import MagicMock, Mock, patch
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import pytest
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from docsgpt.retriever.base import BaseRetriever
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from docsgpt.retriever.retriever_creator import RetrieverCreator
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# ── BaseRetriever ──────────────────────────────────────────────────────────────
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@pytest.mark.unit
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class TestBaseRetriever:
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def test_cannot_instantiate_directly(self):
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with pytest.raises(TypeError):
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BaseRetriever()
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def test_subclass_must_implement_search(self):
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class Incomplete(BaseRetriever):
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pass
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with pytest.raises(TypeError):
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Incomplete()
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def test_concrete_subclass_works(self):
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class Concrete(BaseRetriever):
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def search(self, *args, **kwargs):
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return "ok"
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instance = Concrete()
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assert instance.search() == "ok"
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# ── RetrieverCreator ───────────────────────────────────────────────────────────
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@pytest.mark.unit
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class TestRetrieverCreator:
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def test_create_classic(self):
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mock_cls = Mock(return_value="rag_instance")
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original = RetrieverCreator.retrievers.copy()
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RetrieverCreator.retrievers["classic"] = mock_cls
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try:
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result = RetrieverCreator.create_retriever("classic", "arg1", key="val")
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mock_cls.assert_called_once_with("arg1", key="val")
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assert result == "rag_instance"
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finally:
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RetrieverCreator.retrievers.update(original)
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def test_create_default(self):
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mock_cls = Mock(return_value="rag_instance")
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original = RetrieverCreator.retrievers.copy()
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RetrieverCreator.retrievers["default"] = mock_cls
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try:
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result = RetrieverCreator.create_retriever("default")
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mock_cls.assert_called_once_with()
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assert result == "rag_instance"
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finally:
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RetrieverCreator.retrievers.update(original)
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def test_create_none_type_uses_default(self):
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mock_cls = Mock(return_value="rag_instance")
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original = RetrieverCreator.retrievers.copy()
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RetrieverCreator.retrievers["default"] = mock_cls
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try:
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result = RetrieverCreator.create_retriever(None)
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mock_cls.assert_called_once()
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assert result == "rag_instance"
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finally:
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RetrieverCreator.retrievers.update(original)
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def test_case_insensitive(self):
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mock_cls = Mock(return_value="rag_instance")
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original = RetrieverCreator.retrievers.copy()
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RetrieverCreator.retrievers["classic"] = mock_cls
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try:
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RetrieverCreator.create_retriever("CLASSIC")
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mock_cls.assert_called_once()
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finally:
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RetrieverCreator.retrievers.update(original)
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def test_invalid_type_raises(self):
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with pytest.raises(ValueError, match="No retievers class found"):
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RetrieverCreator.create_retriever("nonexistent")
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# ── ClassicRAG ─────────────────────────────────────────────────────────────────
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@pytest.fixture
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def _patch_llm_creator(mock_llm, monkeypatch):
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"""Patch LLMCreator.create_llm to return the shared mock_llm fixture."""
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monkeypatch.setattr(
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"docsgpt.retriever.classic_rag.LLMCreator.create_llm",
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Mock(return_value=mock_llm),
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)
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return mock_llm
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def _make_rag(source=None, _patch_llm_creator=None, **overrides):
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"""Helper – builds a ClassicRAG with sensible defaults."""
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from docsgpt.retriever.classic_rag import ClassicRAG
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defaults = dict(
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source=source or {"question": "hello"},
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chat_history=None,
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prompt="",
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chunks=2,
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doc_token_limit=50000,
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model_id="test-model",
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user_api_key=None,
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agent_id=None,
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llm_name="openai",
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api_key="fake",
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decoded_token={"sub": "user1"},
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)
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defaults.update(overrides)
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return ClassicRAG(**defaults)
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@pytest.mark.unit
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class TestClassicRAGInit:
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def test_basic_init(self, _patch_llm_creator):
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rag = _make_rag()
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assert rag.original_question == "hello"
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assert rag.chunks == 2
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assert rag.vectorstores == []
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def test_request_id_and_source_stamped_on_rephrase_llm(
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self, _patch_llm_creator
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):
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_make_rag(request_id="req-123")
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assert _patch_llm_creator._request_id == "req-123"
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assert _patch_llm_creator._token_usage_source == "rag_condense"
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def test_active_docs_as_list(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q", "active_docs": ["a", "b"]})
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assert rag.vectorstores == ["a", "b"]
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def test_active_docs_as_string(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q", "active_docs": "single"})
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assert rag.vectorstores == ["single"]
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def test_active_docs_none(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q", "active_docs": None})
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assert rag.vectorstores == []
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def test_chunks_string_converted(self, _patch_llm_creator):
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rag = _make_rag(chunks="5")
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assert rag.chunks == 5
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def test_chunks_invalid_string_defaults(self, _patch_llm_creator):
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rag = _make_rag(chunks="abc")
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assert rag.chunks == 2
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def test_decoded_token_none(self, _patch_llm_creator):
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rag = _make_rag(decoded_token=None)
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assert rag.decoded_token is None
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@pytest.mark.unit
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class TestClassicRAGValidateVectorstore:
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def test_removes_empty_ids(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q", "active_docs": ["ok", "", " ", "good"]})
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assert rag.vectorstores == ["ok", "good"]
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def test_empty_vectorstores_no_error(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q"})
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assert rag.vectorstores == []
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@pytest.mark.unit
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class TestClassicRAGRephraseQuery:
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def test_no_history_returns_original(self, _patch_llm_creator):
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rag = _make_rag(
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source={"question": "original", "active_docs": ["vs1"]},
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chat_history=[],
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)
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assert rag.question == "original"
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def test_no_vectorstores_returns_original(self, _patch_llm_creator):
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rag = _make_rag(
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source={"question": "original"},
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chat_history=[{"prompt": "hi", "response": "hello"}],
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)
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assert rag.question == "original"
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def test_chunks_zero_returns_original(self, _patch_llm_creator):
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rag = _make_rag(
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source={"question": "original", "active_docs": ["vs1"]},
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chat_history=[{"prompt": "hi", "response": "hello"}],
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chunks=0,
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)
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assert rag.question == "original"
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def test_rephrase_called_with_history(self, _patch_llm_creator, mock_llm):
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mock_llm.gen = Mock(return_value="rephrased question")
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rag = _make_rag(
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source={"question": "original", "active_docs": ["vs1"]},
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chat_history=[{"prompt": "hi", "response": "hello"}],
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)
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assert rag.question == "rephrased question"
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mock_llm.gen.assert_called_once()
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def test_rephrase_llm_returns_empty_falls_back(self, _patch_llm_creator, mock_llm):
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mock_llm.gen = Mock(return_value="")
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rag = _make_rag(
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source={"question": "original", "active_docs": ["vs1"]},
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chat_history=[{"prompt": "hi", "response": "hello"}],
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)
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assert rag.question == "original"
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def test_rephrase_llm_exception_falls_back(self, _patch_llm_creator, mock_llm):
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mock_llm.gen = Mock(side_effect=RuntimeError("boom"))
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rag = _make_rag(
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source={"question": "original", "active_docs": ["vs1"]},
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chat_history=[{"prompt": "hi", "response": "hello"}],
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)
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assert rag.question == "original"
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@pytest.mark.unit
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class TestClassicRAGLLMCreatorWiring:
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"""ClassicRAG must forward model_id + model_user_id to LLMCreator so
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the registry-resolution path runs (BYOM api_key/base_url overrides
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and upstream_model_id translation). Without these the rephrase
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client dispatches the registry UUID to the plugin's default endpoint
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with the instance API key."""
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def test_passes_model_id_and_user_id_to_llmcreator(self, mock_llm, monkeypatch):
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captured = Mock(return_value=mock_llm)
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monkeypatch.setattr(
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"docsgpt.retriever.classic_rag.LLMCreator.create_llm", captured
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)
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_make_rag(
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model_id="byom-uuid",
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model_user_id="owner",
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decoded_token={"sub": "caller"},
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)
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assert captured.call_count == 1
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kwargs = captured.call_args.kwargs
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assert kwargs["model_id"] == "byom-uuid"
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assert kwargs["model_user_id"] == "owner"
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# Caller identity still flows so non-BYOM paths keep working.
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assert kwargs["decoded_token"] == {"sub": "caller"}
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def test_default_model_user_id_is_none(self, mock_llm, monkeypatch):
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captured = Mock(return_value=mock_llm)
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monkeypatch.setattr(
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"docsgpt.retriever.classic_rag.LLMCreator.create_llm", captured
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)
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_make_rag() # no model_user_id override
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assert captured.call_args.kwargs["model_user_id"] is None
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@pytest.mark.unit
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class TestClassicRAGGetData:
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def test_chunks_zero_returns_empty(self, _patch_llm_creator):
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rag = _make_rag(chunks=0)
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assert rag._get_data() == []
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def test_no_vectorstores_returns_empty(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q"})
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assert rag._get_data() == []
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_returns_docs_with_metadata(self, mock_tokens, mock_vc, _patch_llm_creator):
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mock_docsearch = MagicMock()
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mock_doc = MagicMock()
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mock_doc.page_content = "content here"
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mock_doc.metadata = {
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"title": "path/to/Title",
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"filename": "/docs/file.txt",
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"source": "http://example.com",
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}
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mock_docsearch.search.return_value = [mock_doc]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
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docs = rag._get_data()
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assert len(docs) == 1
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assert docs[0]["text"] == "content here"
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assert docs[0]["title"] == "Title"
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assert docs[0]["filename"] == "file.txt"
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assert docs[0]["source"] == "http://example.com"
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_dict_style_docs(self, mock_tokens, mock_vc, _patch_llm_creator):
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mock_docsearch = MagicMock()
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mock_docsearch.search.return_value = [
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{"text": "dict content", "metadata": {"title": "Dict Title"}}
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]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
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docs = rag._get_data()
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assert len(docs) == 1
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assert docs[0]["text"] == "dict content"
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=100000)
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def test_token_budget_respected(self, mock_tokens, mock_vc, _patch_llm_creator):
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mock_docsearch = MagicMock()
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mock_doc = MagicMock()
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mock_doc.page_content = "big content"
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mock_doc.metadata = {"title": "t"}
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mock_docsearch.search.return_value = [mock_doc, mock_doc, mock_doc]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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rag = _make_rag(
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source={"question": "q", "active_docs": ["vs1"]},
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doc_token_limit=100,
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)
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docs = rag._get_data()
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# tokens (100000) exceed budget (90), so no docs should be added
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assert len(docs) == 0
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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def test_vectorstore_error_continues(self, mock_vc, _patch_llm_creator):
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mock_vc.create_vectorstore.side_effect = RuntimeError("connection failed")
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
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docs = rag._get_data()
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assert docs == []
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_multiple_vectorstores(self, mock_tokens, mock_vc, _patch_llm_creator):
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mock_docsearch = MagicMock()
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mock_doc = MagicMock()
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mock_doc.page_content = "content"
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mock_doc.metadata = {"title": "t", "source": "s"}
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mock_docsearch.search.return_value = [mock_doc]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1", "vs2"]})
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docs = rag._get_data()
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assert len(docs) == 2
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_doc_missing_filename_uses_title(self, mock_tokens, mock_vc, _patch_llm_creator):
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mock_docsearch = MagicMock()
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mock_doc = MagicMock()
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mock_doc.page_content = "content"
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mock_doc.metadata = {"title": "MyTitle"}
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mock_docsearch.search.return_value = [mock_doc]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
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docs = rag._get_data()
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assert docs[0]["filename"] == "MyTitle"
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_non_string_title_converted(self, mock_tokens, mock_vc, _patch_llm_creator):
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mock_docsearch = MagicMock()
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mock_doc = MagicMock()
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mock_doc.page_content = "content"
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mock_doc.metadata = {"title": 42}
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mock_docsearch.search.return_value = [mock_doc]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
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docs = rag._get_data()
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assert docs[0]["title"] == "42"
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@pytest.mark.unit
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class TestClassicRAGSearch:
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_search_with_query_override(self, mock_tokens, mock_vc, _patch_llm_creator, mock_llm):
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mock_docsearch = MagicMock()
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mock_doc = MagicMock()
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mock_doc.page_content = "result"
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mock_doc.metadata = {"title": "t"}
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mock_docsearch.search.return_value = [mock_doc]
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mock_vc.create_vectorstore.return_value = mock_docsearch
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mock_llm.gen = Mock(return_value="")
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rag = _make_rag(source={"question": "original", "active_docs": ["vs1"]})
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docs = rag.search(query="override query")
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assert rag.original_question == "override query"
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assert len(docs) == 1
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def test_search_without_query_uses_default(self, _patch_llm_creator):
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rag = _make_rag(source={"question": "q"})
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docs = rag.search()
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assert docs == []
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# ── ClassicRAG per-source overrides (C1) ────────────────────────────────────────
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@pytest.mark.unit
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class TestClassicRAGPerSource:
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"""Per-source chunks / score_threshold / rephrase_query in the loop."""
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@patch("docsgpt.retriever.classic_rag.VectorCreator")
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@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
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def test_per_source_chunks_changes_k(self, _tok, mock_vc, _patch_llm_creator):
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from docsgpt.storage.db.source_config import RetrievalConfig
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docsearch = MagicMock()
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doc = MagicMock()
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doc.page_content = "c"
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doc.metadata = {"title": "t"}
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docsearch.search.return_value = [doc]
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mock_vc.create_vectorstore.return_value = docsearch
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rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]}, chunks=2)
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rag.per_source_retrieval = {"vs1": RetrievalConfig(chunks=6)}
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rag._get_data()
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# src_k=6 → k = max(6*2, 20) = 20 (vs default chunks_per_source=2 → 20).
|
||
assert docsearch.search.call_args.kwargs["k"] == 20
|
||
|
||
docsearch.search.reset_mock()
|
||
rag.per_source_retrieval = {"vs1": RetrievalConfig(chunks=15)}
|
||
rag._get_data()
|
||
# src_k=15 → k = max(30, 20) = 30.
|
||
assert docsearch.search.call_args.kwargs["k"] == 30
|
||
|
||
@patch("docsgpt.retriever.classic_rag.VectorCreator")
|
||
@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
|
||
def test_per_source_score_threshold_passed(self, _tok, mock_vc, _patch_llm_creator):
|
||
from docsgpt.storage.db.source_config import RetrievalConfig
|
||
|
||
docsearch = MagicMock()
|
||
docsearch.search.return_value = []
|
||
mock_vc.create_vectorstore.return_value = docsearch
|
||
|
||
rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
|
||
rag.per_source_retrieval = {"vs1": RetrievalConfig(score_threshold=0.7)}
|
||
rag._get_data()
|
||
assert docsearch.search.call_args.kwargs["score_threshold"] == 0.7
|
||
|
||
@patch("docsgpt.retriever.classic_rag.VectorCreator")
|
||
@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
|
||
def test_default_path_omits_score_threshold(self, _tok, mock_vc, _patch_llm_creator):
|
||
docsearch = MagicMock()
|
||
docsearch.search.return_value = []
|
||
mock_vc.create_vectorstore.return_value = docsearch
|
||
|
||
rag = _make_rag(source={"question": "q", "active_docs": ["vs1"]})
|
||
rag._get_data()
|
||
assert "score_threshold" not in docsearch.search.call_args.kwargs
|
||
|
||
@patch("docsgpt.retriever.classic_rag.VectorCreator")
|
||
@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
|
||
def test_rephrase_false_skips_llm_and_uses_original(
|
||
self, _tok, mock_vc, _patch_llm_creator, mock_llm
|
||
):
|
||
from docsgpt.storage.db.source_config import RetrievalConfig
|
||
|
||
docsearch = MagicMock()
|
||
docsearch.search.return_value = []
|
||
mock_vc.create_vectorstore.return_value = docsearch
|
||
mock_llm.gen = Mock(return_value="REPHRASED")
|
||
|
||
# defer_rephrase mirrors what the Dispatcher does for per-source configs.
|
||
rag = _make_rag(
|
||
source={"question": "original", "active_docs": ["vs1"]},
|
||
chat_history=[{"prompt": "hi", "response": "yo"}],
|
||
defer_rephrase=True,
|
||
)
|
||
rag.per_source_retrieval = {"vs1": RetrievalConfig(rephrase_query=False)}
|
||
rag._get_data()
|
||
|
||
# No rephrase LLM call, and the raw original question is searched.
|
||
mock_llm.gen.assert_not_called()
|
||
assert docsearch.search.call_args.args[0] == "original"
|
||
|
||
@patch("docsgpt.retriever.classic_rag.VectorCreator")
|
||
@patch("docsgpt.retriever.classic_rag.num_tokens_from_string", return_value=10)
|
||
def test_rephrase_true_uses_rephrased(
|
||
self, _tok, mock_vc, _patch_llm_creator, mock_llm
|
||
):
|
||
from docsgpt.storage.db.source_config import RetrievalConfig
|
||
|
||
docsearch = MagicMock()
|
||
docsearch.search.return_value = []
|
||
mock_vc.create_vectorstore.return_value = docsearch
|
||
mock_llm.gen = Mock(return_value="REPHRASED")
|
||
|
||
rag = _make_rag(
|
||
source={"question": "original", "active_docs": ["vs1"]},
|
||
chat_history=[{"prompt": "hi", "response": "yo"}],
|
||
defer_rephrase=True,
|
||
)
|
||
rag.per_source_retrieval = {"vs1": RetrievalConfig(rephrase_query=True)}
|
||
rag._get_data()
|
||
assert docsearch.search.call_args.args[0] == "REPHRASED"
|