mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-14 14:17:08 +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.
130 lines
3.6 KiB
Python
130 lines
3.6 KiB
Python
"""End-to-end smoke tests for AnthropicLLM against the Messages API.
|
|
|
|
Narrower than test_anthropic.py: these pin the request shape and the
|
|
streaming contract a caller sees, not the individual mapping rules.
|
|
"""
|
|
|
|
import sys
|
|
import types
|
|
|
|
import pytest
|
|
|
|
|
|
class _FakeUsage:
|
|
def __init__(self, input_tokens=0, output_tokens=0):
|
|
self.input_tokens = input_tokens
|
|
self.output_tokens = output_tokens
|
|
self.cache_creation_input_tokens = 0
|
|
self.cache_read_input_tokens = 0
|
|
|
|
|
|
class _FakeStream:
|
|
def __init__(self, events):
|
|
self._events = list(events)
|
|
self.closed = False
|
|
|
|
def __iter__(self):
|
|
return iter(self._events)
|
|
|
|
def close(self):
|
|
self.closed = True
|
|
|
|
|
|
def _text_delta(text):
|
|
return types.SimpleNamespace(
|
|
type="content_block_delta",
|
|
index=0,
|
|
delta=types.SimpleNamespace(type="text_delta", text=text),
|
|
)
|
|
|
|
|
|
class _FakeMessages:
|
|
def __init__(self):
|
|
self.last_kwargs = None
|
|
self._stream = [
|
|
_text_delta("s1"),
|
|
_text_delta("s2"),
|
|
types.SimpleNamespace(
|
|
type="message_delta",
|
|
delta=types.SimpleNamespace(stop_reason="end_turn"),
|
|
usage=_FakeUsage(output_tokens=2),
|
|
),
|
|
]
|
|
|
|
def create(self, **kwargs):
|
|
self.last_kwargs = kwargs
|
|
if kwargs.get("stream"):
|
|
return _FakeStream(self._stream)
|
|
return types.SimpleNamespace(
|
|
type="message",
|
|
role="assistant",
|
|
content=[types.SimpleNamespace(type="text", text="final")],
|
|
stop_reason="end_turn",
|
|
usage=_FakeUsage(7, 3),
|
|
)
|
|
|
|
|
|
class _FakeAnthropic:
|
|
def __init__(self, api_key=None, base_url=None):
|
|
self.api_key = api_key
|
|
self.base_url = base_url
|
|
self.messages = _FakeMessages()
|
|
|
|
|
|
@pytest.fixture(autouse=True)
|
|
def patch_anthropic():
|
|
fake = types.ModuleType("anthropic")
|
|
fake.Anthropic = _FakeAnthropic
|
|
|
|
modules_to_remove = [key for key in sys.modules if key.startswith("anthropic")]
|
|
for key in modules_to_remove:
|
|
sys.modules.pop(key, None)
|
|
sys.modules["anthropic"] = fake
|
|
|
|
if "docsgpt.llm.anthropic" in sys.modules:
|
|
del sys.modules["docsgpt.llm.anthropic"]
|
|
yield
|
|
|
|
sys.modules.pop("anthropic", None)
|
|
if "docsgpt.llm.anthropic" in sys.modules:
|
|
del sys.modules["docsgpt.llm.anthropic"]
|
|
|
|
|
|
def test_anthropic_raw_gen_uses_messages_api_and_returns_text():
|
|
from docsgpt.llm.anthropic import AnthropicLLM
|
|
|
|
llm = AnthropicLLM(api_key="k")
|
|
msgs = [
|
|
{"role": "system", "content": "sys"},
|
|
{"role": "user", "content": "q"},
|
|
]
|
|
out = llm._raw_gen(llm, model="claude-x", messages=msgs, stream=False, max_tokens=55)
|
|
|
|
assert out == "final"
|
|
last = llm.anthropic.messages.last_kwargs
|
|
assert last["model"] == "claude-x"
|
|
assert last["max_tokens"] == 55
|
|
assert last["system"] == "sys"
|
|
assert last["messages"] == [
|
|
{"role": "user", "content": [{"type": "text", "text": "q"}]}
|
|
]
|
|
# The retired Text Completions parameters are gone.
|
|
assert "prompt" not in last
|
|
assert "max_tokens_to_sample" not in last
|
|
|
|
|
|
def test_anthropic_raw_gen_stream_yields_text_chunks():
|
|
from docsgpt.llm.anthropic import AnthropicLLM
|
|
|
|
llm = AnthropicLLM(api_key="k")
|
|
msgs = [
|
|
{"role": "system", "content": "sys"},
|
|
{"role": "user", "content": "q"},
|
|
]
|
|
chunks = list(
|
|
llm._raw_gen_stream(llm, model="claude", messages=msgs, stream=True, max_tokens=10)
|
|
)
|
|
|
|
assert [c for c in chunks if isinstance(c, str)] == ["s1", "s2"]
|
|
assert llm.anthropic.messages.last_kwargs["stream"] is True
|