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chore: import upstream snapshot with attribution
2026-07-13 13:08:55 +08:00

237 lines
8.4 KiB
Python

"""Integration tests for text optimization with the research service."""
import pytest
from unittest.mock import patch
from local_deep_research.web.services.research_service import (
get_citation_formatter,
export_report_to_memory,
)
from local_deep_research.text_optimization import (
CitationFormatter,
CitationMode,
)
class TestResearchServiceIntegration:
"""Test integration of text optimization with research service."""
@patch("local_deep_research.config.search_config.get_setting_from_snapshot")
def test_get_citation_formatter_number_mode(self, mock_get_setting):
"""Test getting formatter with number hyperlinks mode."""
mock_get_setting.return_value = "number_hyperlinks"
formatter = get_citation_formatter()
assert isinstance(formatter, CitationFormatter)
assert formatter.mode == CitationMode.NUMBER_HYPERLINKS
@patch("local_deep_research.config.search_config.get_setting_from_snapshot")
def test_get_citation_formatter_domain_mode(self, mock_get_setting):
"""Test getting formatter with domain hyperlinks mode."""
mock_get_setting.return_value = "domain_hyperlinks"
formatter = get_citation_formatter()
assert isinstance(formatter, CitationFormatter)
assert formatter.mode == CitationMode.DOMAIN_HYPERLINKS
@patch("local_deep_research.config.search_config.get_setting_from_snapshot")
def test_get_citation_formatter_no_hyperlinks_mode(self, mock_get_setting):
"""Test getting formatter with no hyperlinks mode."""
mock_get_setting.return_value = "no_hyperlinks"
formatter = get_citation_formatter()
assert isinstance(formatter, CitationFormatter)
assert formatter.mode == CitationMode.NO_HYPERLINKS
@patch("local_deep_research.config.search_config.get_setting_from_snapshot")
def test_get_citation_formatter_invalid_mode(self, mock_get_setting):
"""Test getting formatter with invalid mode falls back to default."""
mock_get_setting.return_value = "invalid_mode"
formatter = get_citation_formatter()
assert isinstance(formatter, CitationFormatter)
assert formatter.mode == CitationMode.NUMBER_HYPERLINKS # Default
def test_export_report_to_latex(self):
"""Test LaTeX export functionality."""
markdown_content = """# Test Report
This is a test with citation [1].
## Sources
[1] Test Source
URL: https://example.com
"""
# Export to LaTeX
latex_bytes, filename, mimetype = export_report_to_memory(
markdown_content, "latex"
)
# Check export results
assert filename.endswith(".tex")
assert mimetype == "text/plain"
# Check LaTeX content
latex_content = latex_bytes.decode("utf-8")
assert r"\documentclass[12pt]{article}" in latex_content
assert r"\section{Test Report}" in latex_content
assert r"\cite{1}" in latex_content
assert r"\bibitem{1}" in latex_content
@patch("local_deep_research.config.search_config.get_setting_from_snapshot")
def test_real_world_citation_formatting(self, mock_get_setting):
"""Test citation formatting with real-world example."""
mock_get_setting.return_value = "number_hyperlinks"
# Simulate research report content
content = """# Deep Learning Research Summary
Query: What are the latest advances in transformer architectures?
## Executive Summary
Recent advances in transformer architectures have focused on efficiency improvements [1],
novel attention mechanisms [2], and scaling laws [3]. The field has seen rapid progress
with models like GPT-4 [4] and Claude [5] demonstrating impressive capabilities.
## Key Findings
### Efficiency Improvements
Multiple research groups have proposed methods to reduce computational complexity [1, 2, 3]:
- Flash Attention reduces memory usage significantly [1]
- Sparse transformers achieve O(n√n) complexity [2]
- Linear attention approximations show promise [3]
### Novel Architectures
Recent architectural innovations include:
- Mixture of Experts (MoE) models [4][5]
- Retrieval-augmented generation [6]
- Tool-use capabilities [7][8][9]
## Sources
[1] FlashAttention: Fast and Memory-Efficient Exact Attention
URL: https://arxiv.org/abs/2205.14135
[2] Efficient Transformers: A Survey
URL: https://arxiv.org/abs/2009.06732
[3] Linformer: Self-Attention with Linear Complexity
URL: https://arxiv.org/abs/2006.04768
[4] Mixtral of Experts
URL: https://arxiv.org/abs/2401.04088
[5] Switch Transformers
URL: https://arxiv.org/abs/2101.03961
[6] Retrieval-Augmented Generation
URL: https://arxiv.org/abs/2005.11401
[7] Toolformer: Language Models Can Teach Themselves
URL: https://arxiv.org/abs/2302.04761
[8] WebGPT: Browser-assisted question-answering
URL: https://arxiv.org/abs/2112.09332
[9] Constitutional AI: Harmlessness from AI Feedback
URL: https://arxiv.org/abs/2212.08073
"""
formatter = get_citation_formatter()
result = formatter.format_document(content)
# Verify all citation formats are handled correctly
assert "[[1]](https://arxiv.org/abs/2205.14135)" in result
assert (
"[[1]](https://arxiv.org/abs/2205.14135)[[2]](https://arxiv.org/abs/2009.06732)[[3]](https://arxiv.org/abs/2006.04768)"
in result
)
assert (
"[[4]](https://arxiv.org/abs/2401.04088)[[5]](https://arxiv.org/abs/2101.03961)"
in result
)
assert (
"[[7]](https://arxiv.org/abs/2302.04761)[[8]](https://arxiv.org/abs/2112.09332)[[9]](https://arxiv.org/abs/2212.08073)"
in result
)
# Ensure sources section is preserved
assert "## Sources" in result
assert "[1] FlashAttention" in result
def test_export_report_to_quarto(self):
"""Test Quarto export functionality."""
markdown_content = """# AI Research Report
This report discusses recent advances [1] and challenges [2].
## Sources
[1] Advances in AI
URL: https://arxiv.org/abs/2024.1234
[2] AI Challenges
URL: https://example.com/challenges
"""
# Export to Quarto
zip_bytes, filename, mimetype = export_report_to_memory(
markdown_content, "quarto", "AI Research"
)
# Check export results
assert filename.endswith(".zip")
assert mimetype == "application/zip"
# Extract and check content from zip
import zipfile
import io
zip_buffer = io.BytesIO(zip_bytes)
with zipfile.ZipFile(zip_buffer, "r") as zipf:
# Check files in zip
file_list = zipf.namelist()
qmd_files = [f for f in file_list if f.endswith(".qmd")]
bib_files = [f for f in file_list if f.endswith(".bib")]
assert len(qmd_files) == 1, "Should have one .qmd file"
assert len(bib_files) == 1, "Should have one .bib file"
# Check Quarto content
quarto_content = zipf.read(qmd_files[0]).decode("utf-8")
# Verify YAML header
assert 'title: "AI Research"' in quarto_content
assert "bibliography: references.bib" in quarto_content
# Verify citation conversion
assert "[@ref1]" in quarto_content
assert "[@ref2]" in quarto_content
# Check bibliography content
bib_content = zipf.read(bib_files[0]).decode("utf-8")
assert "@misc{ref1," in bib_content
assert 'title = "{Advances in AI}"' in bib_content
def test_export_with_invalid_format(self):
"""Test export with invalid format raises error."""
markdown_content = "# Test"
with pytest.raises(ValueError, match="Unsupported export format"):
export_report_to_memory(markdown_content, "invalid_format")
@patch("local_deep_research.config.search_config.get_setting_from_snapshot")
def test_automatic_export_formats(self, mock_get_setting):
"""Test automatic export to multiple formats based on settings."""
# This would be called in the actual research service when saving reports
mock_get_setting.return_value = ["markdown", "latex", "quarto"]
# Simulate the export logic
export_formats = mock_get_setting("report.export_formats", ["markdown"])
assert "markdown" in export_formats
assert "latex" in export_formats
assert "quarto" in export_formats