from __future__ import annotations
from dataclasses import dataclass
from datetime import datetime, timezone
import json
import pytest
import aura.agents.iris.tools as iris
from aura.core.config import AppConfig, FeatureFlags, ModelSettings, PathsSettings
import aura.memory.mneme.tools as mneme_tools
@dataclass
class FakeResponse:
content: str
class FakeRouter:
def generate(self, prompt: str) -> FakeResponse:
return FakeResponse(content="Synthesized answer")
@pytest.fixture()
def iris_config(tmp_path):
config = AppConfig(
name="AURA",
offline_mode=True,
log_level="INFO",
primary_model=ModelSettings(provider="ollama", name="llama3", host="http://127.0.0.1:11434"),
fallback_models=[],
paths=PathsSettings(
allowed_roots=[tmp_path],
data_dir=tmp_path,
log_dir=tmp_path / "logs",
memory_dir=tmp_path / "memory",
ipc_socket=tmp_path / "aura.sock",
),
features=FeatureFlags(hotkey=True, tray=True, ipc=True, api=True),
source_path=tmp_path / "config.yaml",
)
mneme_tools.set_config(config)
iris.set_config(config)
iris.set_router(FakeRouter())
return config
def test_web_search_caches_and_summarizes(monkeypatch, iris_config, tmp_path):
calls = {"count": 0}
def fake_search(query, num_results, date_filter):
calls["count"] += 1
return [iris.SearchResult(title="Doc", url=str(tmp_path / "page.html"), snippet="Snippet", source_domain="example.com", relevance_score=1.0)]
page = tmp_path / "page.html"
page.write_text("DocAlpha
Beta.
", encoding="utf-8")
monkeypatch.setattr(iris, "_search_backend", fake_search)
first = iris.web_search("alpha", num_results=1)
second = iris.web_search("alpha", num_results=1)
summary = iris.summarize_content(str(page))
assert calls["count"] == 1
assert first[0].title == "Doc"
assert second[0].title == "Doc"
assert summary.summary_text
def test_deep_research_and_fact_check(monkeypatch, iris_config, tmp_path):
page = tmp_path / "source.html"
page.write_text("Python is a language.
", encoding="utf-8")
monkeypatch.setattr(iris, "web_search", lambda query, num_results=10, date_filter=None, safe_search=True: [iris.SearchResult(title="S", url=str(page), snippet="Python is a language", source_domain="example.com", relevance_score=1.0)])
monkeypatch.setattr(iris, "fetch_url", lambda url, extract_main_content=True: iris.PageContent(url=url, title="S", main_text="Python is a language.", word_count=4, fetched_at=datetime.now(timezone.utc), links=[]))
deep = iris.deep_research("python")
fact = iris.fact_check("Python is a language")
papers = iris.search_academic("neural nets", source="arxiv", max_results=1)
assert deep.synthesized_answer
assert fact.verdict in {"supported", "contradicted", "unverified"}
assert isinstance(papers, list)
def test_compare_and_citations(monkeypatch, iris_config, tmp_path):
page = tmp_path / "compare.html"
page.write_text("Reference 2024. Doe, J.
", encoding="utf-8")
monkeypatch.setattr(iris, "fetch_url", lambda url, extract_main_content=True: iris.PageContent(url=url, title="T", main_text="Reference 2024. Doe, J.", word_count=4, fetched_at=datetime.now(timezone.utc), links=[]))
compare = iris.compare_sources([str(page)], "question")
citations = iris.extract_citations("Reference 2024. Doe, J.")
assert compare.sources == [str(page)]
assert citations
class FakeHTTPResponse:
def __init__(self, payload: bytes, status: int = 200):
self._payload = payload
self.status = status
def read(self):
return self._payload
def __enter__(self):
return self
def __exit__(self, exc_type, exc, tb):
return False
def test_fetch_and_academic_search(monkeypatch, iris_config, tmp_path):
page = tmp_path / "raw.html"
page.write_text("RawBody text", encoding="utf-8")
raw = iris.fetch_url(page.as_uri(), extract_main_content=False)
assert raw.title == "Raw"
assert "Body text" in raw.main_text
arxiv_xml = b"""
Paper One
Abstract one
http://arxiv.org/abs/1234.5678
Alice
"""
sem_json = json.dumps({"data": [{"title": "Paper Two", "abstract": "Abstract two", "authors": [{"name": "Bob"}], "url": "https://example.com", "year": 2024, "citationCount": 5}]}).encode("utf-8")
def fake_urlopen(url, timeout=20):
if "arxiv" in url:
return FakeHTTPResponse(arxiv_xml)
return FakeHTTPResponse(sem_json)
monkeypatch.setattr(iris.urllib.request, "urlopen", fake_urlopen)
papers = iris.search_academic("neural nets", source="both", max_results=2)
assert len(papers) == 2
assert {paper.source for paper in papers} == {"arxiv", "semantic_scholar"}