"""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