Complete implementation of the DCOS package including: - 40+ Python source files across agents, communication, core, learning, memory, protocols, utils - pyproject.toml build configuration - 102 unit tests across all subsystems - Fixed flake.nix (Python 3.12, proper dependencies, pyproject build) - Fixed .woodpecker.yml (correct paths, removed silent-fail flags) - Added .gitignore - Cleared stale pytest cache
25 lines
635 B
Python
25 lines
635 B
Python
"""
|
|
Tests for ResearchAgent.
|
|
"""
|
|
|
|
import pytest
|
|
from dcos.agents.research import ResearchAgent
|
|
|
|
|
|
class TestResearchAgent:
|
|
def test_initialization(self):
|
|
agent = ResearchAgent()
|
|
assert agent.identity.name == "researcher"
|
|
|
|
def test_research(self):
|
|
agent = ResearchAgent()
|
|
result = agent.research("AI safety", depth=3)
|
|
assert result["topic"] == "AI safety"
|
|
assert len(result["key_findings"]) == 3
|
|
|
|
def test_act(self):
|
|
agent = ResearchAgent()
|
|
result = agent.act({"query": "test query"})
|
|
assert "findings" in result
|
|
assert result["confidence"] > 0
|