mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-04 22:13:08 +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.
52 lines
2.7 KiB
Python
52 lines
2.7 KiB
Python
"""Offline verification: every check must pass, docling only when installed."""
|
|
|
|
import sys
|
|
import types
|
|
from unittest.mock import patch
|
|
|
|
from docsgpt.scripts import verify_offline
|
|
|
|
|
|
def _fake_tiktoken(monkeypatch):
|
|
module = types.ModuleType("tiktoken")
|
|
module.get_encoding = lambda name: types.SimpleNamespace(encode=lambda text: [1, 2])
|
|
monkeypatch.setitem(sys.modules, "tiktoken", module)
|
|
|
|
|
|
class TestVerify:
|
|
def test_passes_when_every_check_passes(self, monkeypatch, capsys):
|
|
_fake_tiktoken(monkeypatch)
|
|
counter = types.SimpleNamespace(name="org/model", count=lambda text: 4)
|
|
with patch("docsgpt.parser.tokenization.get_token_counter", return_value=counter), \
|
|
patch("docsgpt.vectorstore.embeddings_local.EmbeddingsWrapper") as wrapper, \
|
|
patch.object(verify_offline, "is_available", return_value=False):
|
|
wrapper.return_value.embed_query.return_value = [0.0] * 768
|
|
assert verify_offline.verify(["ibm-granite/granite-embedding-311m-multilingual-r2"]) is True
|
|
out = capsys.readouterr().out
|
|
assert "ok tiktoken cl100k_base" in out
|
|
assert "skip docling" in out
|
|
|
|
def test_fails_when_the_tokenizer_fell_back_to_cl100k(self, monkeypatch, capsys):
|
|
"""A cache miss makes chunking silently use cl100k; that is a failed check."""
|
|
_fake_tiktoken(monkeypatch)
|
|
counter = types.SimpleNamespace(name="cl100k_base", count=lambda text: 4)
|
|
with patch("docsgpt.parser.tokenization.get_token_counter", return_value=counter), \
|
|
patch("docsgpt.vectorstore.embeddings_local.EmbeddingsWrapper") as wrapper, \
|
|
patch.object(verify_offline, "is_available", return_value=False):
|
|
wrapper.return_value.embed_query.return_value = [0.0] * 768
|
|
assert verify_offline.verify(["ibm-granite/granite-embedding-311m-multilingual-r2"]) is False
|
|
assert "FAIL tokenizer" in capsys.readouterr().out
|
|
|
|
def test_runs_the_docling_check_when_installed(self, monkeypatch):
|
|
_fake_tiktoken(monkeypatch)
|
|
with patch.object(verify_offline, "is_available", return_value=True), \
|
|
patch.object(verify_offline, "_docling_check", return_value="models from /app/models/docling") as check:
|
|
assert verify_offline.verify([]) is True
|
|
check.assert_called_once()
|
|
|
|
def test_remote_models_are_skipped(self, monkeypatch, capsys):
|
|
_fake_tiktoken(monkeypatch)
|
|
with patch.object(verify_offline, "is_available", return_value=False):
|
|
assert verify_offline.verify(["openai_text-embedding-ada-002"]) is True
|
|
assert "skip openai_text-embedding-ada-002" in capsys.readouterr().out
|