ALwrity AI Blog Writer - Added Google Grounding UI Implementation

backend/services/blog_writer/outline/parallel_processor.py

@@ -0,0 +1,107 @@
+"""
+Parallel Processor - Handles parallel processing of outline generation tasks.
+
+Manages concurrent execution of source mapping and grounding insights extraction.
+"""
+
+import asyncio
+from typing import Tuple, Any
+from loguru import logger
+
+
+class ParallelProcessor:
+    """Handles parallel processing of outline generation tasks for speed optimization."""
+    
+    def __init__(self, source_mapper, grounding_engine):
+        """Initialize the parallel processor with required dependencies."""
+        self.source_mapper = source_mapper
+        self.grounding_engine = grounding_engine
+    
+    async def run_parallel_processing(self, outline_sections, research, task_id: str = None) -> Tuple[Any, Any]:
+        """
+        Run source mapping and grounding insights extraction in parallel.
+        
+        Args:
+            outline_sections: List of outline sections to process
+            research: Research data object
+            task_id: Optional task ID for progress updates
+            
+        Returns:
+            Tuple of (mapped_sections, grounding_insights)
+        """
+        if task_id:
+            from api.blog_writer.task_manager import task_manager
+            await task_manager.update_progress(task_id, "⚡ Running parallel processing for maximum speed...")
+        
+        logger.info("Running parallel processing for maximum speed...")
+        
+        # Run these tasks in parallel to save time
+        source_mapping_task = asyncio.create_task(
+            self._run_source_mapping(outline_sections, research, task_id)
+        )
+        
+        grounding_insights_task = asyncio.create_task(
+            self._run_grounding_insights_extraction(research, task_id)
+        )
+        
+        # Wait for both parallel tasks to complete
+        mapped_sections, grounding_insights = await asyncio.gather(
+            source_mapping_task,
+            grounding_insights_task
+        )
+        
+        return mapped_sections, grounding_insights
+    
+    async def run_parallel_processing_async(self, outline_sections, research) -> Tuple[Any, Any]:
+        """
+        Run parallel processing without progress updates (for non-progress methods).
+        
+        Args:
+            outline_sections: List of outline sections to process
+            research: Research data object
+            
+        Returns:
+            Tuple of (mapped_sections, grounding_insights)
+        """
+        logger.info("Running parallel processing for maximum speed...")
+        
+        # Run these tasks in parallel to save time
+        source_mapping_task = asyncio.create_task(
+            self._run_source_mapping_async(outline_sections, research)
+        )
+        
+        grounding_insights_task = asyncio.create_task(
+            self._run_grounding_insights_extraction_async(research)
+        )
+        
+        # Wait for both parallel tasks to complete
+        mapped_sections, grounding_insights = await asyncio.gather(
+            source_mapping_task,
+            grounding_insights_task
+        )
+        
+        return mapped_sections, grounding_insights
+    
+    async def _run_source_mapping(self, outline_sections, research, task_id):
+        """Run source mapping in parallel."""
+        if task_id:
+            from api.blog_writer.task_manager import task_manager
+            await task_manager.update_progress(task_id, "🔗 Applying intelligent source-to-section mapping...")
+        return self.source_mapper.map_sources_to_sections(outline_sections, research)
+    
+    async def _run_grounding_insights_extraction(self, research, task_id):
+        """Run grounding insights extraction in parallel."""
+        if task_id:
+            from api.blog_writer.task_manager import task_manager
+            await task_manager.update_progress(task_id, "🧠 Extracting grounding metadata insights...")
+        return self.grounding_engine.extract_contextual_insights(research.grounding_metadata)
+    
+    async def _run_source_mapping_async(self, outline_sections, research):
+        """Run source mapping in parallel (async version without progress updates)."""
+        logger.info("Applying intelligent source-to-section mapping...")
+        return self.source_mapper.map_sources_to_sections(outline_sections, research)
+    
+    async def _run_grounding_insights_extraction_async(self, research):
+        """Run grounding insights extraction in parallel (async version without progress updates)."""
+        logger.info("Extracting grounding metadata insights...")
+        return self.grounding_engine.extract_contextual_insights(research.grounding_metadata)