Base code

docs/ALwrity Researcher/PHASE1_IMPLEMENTATION_SUMMARY.md

@@ -0,0 +1,136 @@
+# Phase 1 Implementation Summary: Research Persona Enhancements
+
+## Date: 2025-12-31
+
+---
+
+## ✅ **Phase 1 Implementation Complete**
+
+### **What Was Implemented:**
+
+#### **1. Content Type → Preset Generation** ✅
+
+**Enhancement**: Generate presets based on actual content types from website analysis
+
+**Changes Made**:
+- Extract `content_type` from website analysis (primary_type, secondary_types, purpose)
+- Added instructions to generate content-type-specific presets:
+  - Blog → "Blog Topic Research" preset
+  - Article → "Article Research" preset
+  - Case Study → "Case Study Research" preset
+  - Tutorial → "Tutorial Research" preset
+  - Thought Leadership → "Thought Leadership Research" preset
+  - Education → "Educational Content Research" preset
+- Preset names now include content type when relevant
+- Research mode selection considers content_type.purpose
+
+**Impact**: Presets now match user's actual content creation needs
+
+---
+
+#### **2. Writing Style Complexity → Research Depth** ✅
+
+**Enhancement**: Map writing style complexity to research depth preferences
+
+**Changes Made**:
+- Extract `writing_style.complexity` from website analysis
+- Added mapping logic:
+  - `complexity == "high"` → `default_research_mode = "comprehensive"`
+  - `complexity == "medium"` → `default_research_mode = "targeted"`
+  - `complexity == "low"` → `default_research_mode = "basic"`
+- Fallback to `research_preferences.research_depth` if complexity not available
+
+**Impact**: Research depth now matches user's writing sophistication level
+
+---
+
+#### **3. Crawl Result Topics → Suggested Keywords** ✅
+
+**Enhancement**: Extract topics and keywords from actual website content
+
+**Changes Made**:
+- Added `_extract_topics_from_crawl()` method:
+  - Extracts from topics, headings, titles, sections, metadata
+  - Returns top 15 unique topics
+- Added `_extract_keywords_from_crawl()` method:
+  - Extracts from keywords, metadata, tags, content frequency
+  - Returns top 20 unique keywords
+- Updated prompt to prioritize extracted keywords:
+  - First use extracted_keywords (top 8-10)
+  - Then supplement with industry/interests keywords
+  - Total: 8-12 keywords, with 50%+ from extracted_keywords
+
+**Impact**: Keywords now reflect user's actual website content topics
+
+---
+
+## 📋 **Code Changes**
+
+### **File Modified**: `backend/services/research/research_persona_prompt_builder.py`
+
+**Added**:
+1. Extraction of `writing_style`, `content_type`, `crawl_result` from website analysis
+2. `_extract_topics_from_crawl()` method
+3. `_extract_keywords_from_crawl()` method
+4. Enhanced prompt instructions for:
+   - Content-type-based preset generation
+   - Complexity-based research depth mapping
+   - Extracted keywords prioritization
+
+**Prompt Enhancements**:
+- Added "PHASE 1: WEBSITE ANALYSIS INTELLIGENCE" section
+- Enhanced "DEFAULT VALUES" section with complexity mapping
+- Enhanced "KEYWORD INTELLIGENCE" section with extracted keywords priority
+- Enhanced "RECOMMENDED PRESETS" section with content-type-specific generation
+
+---
+
+## 🎯 **Expected Benefits**
+
+1. **More Accurate Presets**: Based on actual content types (blog, tutorial, case study, etc.)
+2. **Aligned Research Depth**: Matches writing complexity (high complexity → comprehensive research)
+3. **Relevant Keywords**: Uses actual website topics instead of generic industry keywords
+4. **Better Personalization**: Research persona reflects user's actual content strategy
+
+---
+
+## 🧪 **Testing Recommendations**
+
+1. **Test with Different Content Types**:
+   - User with blog content → Should see "Blog Topic Research" preset
+   - User with tutorial content → Should see "Tutorial Research" preset
+   - User with case study content → Should see "Case Study Research" preset
+
+2. **Test Complexity Mapping**:
+   - High complexity writing → Should get "comprehensive" research mode
+   - Low complexity writing → Should get "basic" research mode
+
+3. **Test Keyword Extraction**:
+   - User with crawl_result → Should see extracted keywords in suggested_keywords
+   - User without crawl_result → Should fall back to industry keywords
+
+---
+
+## 📝 **Next Steps (Phase 2 & 3)**
+
+### **Phase 2: Medium Impact, Medium Effort**
+- Extract `style_patterns` → Generate pattern-based research angles
+- Extract `content_characteristics.vocabulary` → Sophisticated keyword expansion
+- Extract `style_guidelines` → Query enhancement rules
+
+### **Phase 3: High Impact, High Effort**
+- Full crawl_result analysis → Topic extraction, theme identification
+- Complete writing style mapping → All research preferences
+- Content strategy intelligence → Comprehensive preset generation
+
+---
+
+## ✅ **Implementation Status**
+
+- ✅ Content type extraction and preset generation
+- ✅ Writing style complexity mapping to research depth
+- ✅ Crawl result topic/keyword extraction
+- ✅ Enhanced prompt instructions
+- ✅ Helper methods for data extraction
+
+**Status**: Phase 1 Complete - Ready for Testing