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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.
107 lines
2.7 KiB
Python
107 lines
2.7 KiB
Python
"""API-specific test fixtures."""
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import uuid
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import pytest
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@pytest.fixture
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def auth_headers():
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return {"Authorization": "Bearer test_token"}
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@pytest.fixture
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def mock_request_token(monkeypatch, decoded_token):
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def mock_decorator(f):
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def wrapper(*args, **kwargs):
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from flask import request
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request.decoded_token = decoded_token
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return f(*args, **kwargs)
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return wrapper
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monkeypatch.setattr("docsgpt.auth.api_key_required", lambda: mock_decorator)
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return decoded_token
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@pytest.fixture
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def sample_conversation():
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return {
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"_id": uuid.uuid4().hex[:24],
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"user": "test_user",
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"name": "Test Conversation",
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"queries": [
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{
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"prompt": "What is Python?",
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"response": "Python is a programming language",
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}
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],
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"date": "2025-01-01T00:00:00",
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}
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@pytest.fixture
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def sample_prompt():
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return {
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"_id": uuid.uuid4().hex[:24],
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"user": "test_user",
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"name": "Helpful Assistant",
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"content": "You are a helpful assistant that provides clear and concise answers.",
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"type": "custom",
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}
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@pytest.fixture
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def sample_agent():
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return {
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"_id": uuid.uuid4().hex[:24],
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"user": "test_user",
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"name": "Test Agent",
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"type": "classic",
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"endpoint": "openai",
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"model": "gpt-4",
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"prompt_id": "default",
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"status": "active",
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}
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@pytest.fixture
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def sample_answer_request():
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return {
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"question": "What is Python?",
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"history": [],
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"conversation_id": None,
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"prompt_id": "default",
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"chunks": 2,
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"retriever": "classic_rag",
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"active_docs": "local/test/",
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"isNoneDoc": False,
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"save_conversation": True,
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}
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@pytest.fixture
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def flask_app():
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from flask import Flask
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app = Flask(__name__)
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return app
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@pytest.fixture
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def mock_mongo_db():
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"""Compatibility shim for tests written against the old mongomock fixture.
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The canonical ``mock_mongo_db`` fixture was removed when the answer pipeline
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moved from Mongo to Postgres (see tests/conftest.py docstring). Most API
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tests that still request it only do so as a historical gate: they patch
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specific mongo collections (``agents_collection``, etc.) via
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``unittest.mock.patch`` inside the test body and never touch the fixture's
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return value. Yielding ``None`` keeps those tests runnable without
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reintroducing mongomock. Tests that actually need a working Mongo client
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(e.g. ones that call ``MongoDB.get_client()``) will still fail; skip or
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rewrite those per-case rather than reviving a global fake.
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"""
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yield None
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