Refactor ResearchState into smaller artifacts (#229)

* Complete refactoring of ResearchState to artifact-based architecture

This commit implements the design document for splitting the monolithic ResearchState into separate, named artifacts with custom visualizations. Major changes include:

## New Artifact Classes
- **QueryContext**: Immutable context containing the research query and sub-questions
- **SearchData**: All search results and cost tracking information
- **SynthesisData**: Synthesized information from searches (including enhanced versions)
- **AnalysisData**: Cross-viewpoint analysis and reflection metadata
- **FinalReport**: The generated HTML report with metadata

## Custom Materializers
Each artifact now has its own materializer with beautiful HTML visualizations:
- Interactive charts using Chart.js for search costs
- Collapsible sections for better organization
- Consistent styling across all artifact views
- Metadata tables with key statistics

## Pipeline Updates
- All steps refactored to use the new artifact-based approach
- Proper dependencies established between parallel steps
- Fixed merge step to run after parallel sub-question processing
- Updated metadata logging and tagging throughout

## Bug Fixes
- Fixed log_metadata calls to include infer_artifact=True parameter
- Fixed template variable names in final report generation
- Corrected enhanced_info merging logic to preserve original synthesis data
- Added proper step dependencies in parallel pipeline

## Test Updates
- Updated all tests to use the new artifact-based interface
- Tests now create individual artifacts instead of ResearchState
- Maintained test coverage for all functionality

This refactoring improves modularity, enables better artifact visualization in the ZenML dashboard, and makes the pipeline more maintainable and extensible.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

* Delete legacy code

---------

Co-authored-by: Claude <[email protected]>

Author: strickvl

deep_research/materializers/__init__.py

@@ -2,20 +2,25 @@
 Materializers package for the ZenML Deep Research project.
 
 This package contains custom ZenML materializers that handle serialization and
-deserialization of complex data types used in the research pipeline, particularly
-the ResearchState object that tracks the state of the research process.
+deserialization of complex data types used in the research pipeline.
 """
 
+from .analysis_data_materializer import AnalysisDataMaterializer
 from .approval_decision_materializer import ApprovalDecisionMaterializer
+from .final_report_materializer import FinalReportMaterializer
 from .prompt_materializer import PromptMaterializer
-from .pydantic_materializer import ResearchStateMaterializer
-from .reflection_output_materializer import ReflectionOutputMaterializer
+from .query_context_materializer import QueryContextMaterializer
+from .search_data_materializer import SearchDataMaterializer
+from .synthesis_data_materializer import SynthesisDataMaterializer
 from .tracing_metadata_materializer import TracingMetadataMaterializer
 
 __all__ = [
     "ApprovalDecisionMaterializer",
     "PromptMaterializer",
-    "ReflectionOutputMaterializer",
-    "ResearchStateMaterializer",
     "TracingMetadataMaterializer",
+    "QueryContextMaterializer",
+    "SearchDataMaterializer",
+    "SynthesisDataMaterializer",
+    "AnalysisDataMaterializer",
+    "FinalReportMaterializer",
 ]