mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-04 16:13:23 +00:00
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.
148 lines
4.6 KiB
Python
148 lines
4.6 KiB
Python
"""Tests for AgenticAgent — LLM-controlled retrieval agent."""
|
|
|
|
from unittest.mock import Mock
|
|
|
|
import pytest
|
|
from docsgpt.agents.agentic_agent import AgenticAgent
|
|
|
|
|
|
@pytest.fixture
|
|
def _no_tools(monkeypatch):
|
|
monkeypatch.setattr(
|
|
"docsgpt.agents.tool_executor.ToolExecutor.get_tools",
|
|
lambda self: {},
|
|
)
|
|
|
|
|
|
@pytest.mark.unit
|
|
class TestAgenticAgentInit:
|
|
|
|
def test_initialization(
|
|
self, agent_base_params, mock_llm_creator, mock_llm_handler_creator
|
|
):
|
|
agent = AgenticAgent(**agent_base_params)
|
|
assert isinstance(agent, AgenticAgent)
|
|
assert agent.retriever_config == {}
|
|
|
|
def test_initialization_with_retriever_config(
|
|
self, agent_base_params, mock_llm_creator, mock_llm_handler_creator
|
|
):
|
|
rc = {"source": {"active_docs": ["abc"]}, "retriever_name": "classic"}
|
|
agent = AgenticAgent(retriever_config=rc, **agent_base_params)
|
|
assert agent.retriever_config == rc
|
|
|
|
def test_inherits_base_properties(
|
|
self, agent_base_params, mock_llm_creator, mock_llm_handler_creator
|
|
):
|
|
agent = AgenticAgent(**agent_base_params)
|
|
assert agent.endpoint == agent_base_params["endpoint"]
|
|
assert agent.llm_name == agent_base_params["llm_name"]
|
|
assert agent.model_id == agent_base_params["model_id"]
|
|
|
|
|
|
@pytest.mark.unit
|
|
class TestAgenticAgentGenInner:
|
|
|
|
def test_basic_flow_yields_sources_and_tool_calls(
|
|
self,
|
|
agent_base_params,
|
|
mock_llm,
|
|
mock_llm_handler,
|
|
mock_llm_creator,
|
|
mock_llm_handler_creator,
|
|
_no_tools,
|
|
log_context,
|
|
):
|
|
mock_llm.gen_stream = Mock(return_value=iter(["Answer"]))
|
|
|
|
def mock_handler(*args, **kwargs):
|
|
yield "Processed"
|
|
|
|
mock_llm_handler.process_message_flow = Mock(side_effect=mock_handler)
|
|
|
|
agent = AgenticAgent(**agent_base_params)
|
|
results = list(agent._gen_inner("Test query", log_context))
|
|
|
|
sources = [r for r in results if "sources" in r]
|
|
tool_calls = [r for r in results if "tool_calls" in r]
|
|
assert len(sources) == 1
|
|
assert len(tool_calls) == 1
|
|
|
|
def test_logs_agent_component(
|
|
self,
|
|
agent_base_params,
|
|
mock_llm,
|
|
mock_llm_handler,
|
|
mock_llm_creator,
|
|
mock_llm_handler_creator,
|
|
_no_tools,
|
|
log_context,
|
|
):
|
|
mock_llm.gen_stream = Mock(return_value=iter(["Answer"]))
|
|
|
|
def mock_handler(*args, **kwargs):
|
|
yield "Done"
|
|
|
|
mock_llm_handler.process_message_flow = Mock(side_effect=mock_handler)
|
|
|
|
agent = AgenticAgent(**agent_base_params)
|
|
list(agent._gen_inner("Query", log_context))
|
|
|
|
agent_logs = [s for s in log_context.stacks if s["component"] == "agent"]
|
|
assert len(agent_logs) == 1
|
|
assert "tool_calls" in agent_logs[0]["data"]
|
|
|
|
def test_no_pre_fetched_docs_in_messages(
|
|
self,
|
|
agent_base_params,
|
|
mock_llm,
|
|
mock_llm_handler,
|
|
mock_llm_creator,
|
|
mock_llm_handler_creator,
|
|
_no_tools,
|
|
log_context,
|
|
):
|
|
mock_llm.gen_stream = Mock(return_value=iter(["Answer"]))
|
|
|
|
def mock_handler(*args, **kwargs):
|
|
yield "Done"
|
|
|
|
mock_llm_handler.process_message_flow = Mock(side_effect=mock_handler)
|
|
|
|
agent = AgenticAgent(**agent_base_params)
|
|
list(agent._gen_inner("Query", log_context))
|
|
|
|
call_kwargs = mock_llm.gen_stream.call_args[1]
|
|
messages = call_kwargs["messages"]
|
|
# System prompt should not contain {summaries} replacement
|
|
assert messages[0]["role"] == "system"
|
|
assert messages[-1]["role"] == "user"
|
|
assert messages[-1]["content"] == "Query"
|
|
|
|
|
|
@pytest.mark.unit
|
|
class TestAgenticAgentCollectSources:
|
|
|
|
def test_collect_internal_sources_from_cache(
|
|
self, agent_base_params, mock_llm_creator, mock_llm_handler_creator
|
|
):
|
|
agent = AgenticAgent(**agent_base_params)
|
|
|
|
mock_tool = Mock()
|
|
mock_tool.retrieved_docs = [
|
|
{"text": "Found", "title": "Doc", "source": "test"},
|
|
]
|
|
cache_key = f"internal_search:internal:{agent.user or ''}"
|
|
agent.tool_executor._loaded_tools[cache_key] = mock_tool
|
|
|
|
agent._collect_internal_sources()
|
|
assert len(agent.retrieved_docs) == 1
|
|
assert agent.retrieved_docs[0]["title"] == "Doc"
|
|
|
|
def test_collect_internal_sources_no_cache(
|
|
self, agent_base_params, mock_llm_creator, mock_llm_handler_creator
|
|
):
|
|
agent = AgenticAgent(**agent_base_params)
|
|
agent._collect_internal_sources()
|
|
assert agent.retrieved_docs == []
|