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AGENTIC_CONTEXT_STRATEGY.md
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AGENTIC_CONTEXT_STRATEGY.md
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# Agentic Context Management Strategy
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**Date:** January 25, 2026
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**Version:** 0.1.3+
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**Purpose:** AI-powered context management for multilingual, intelligent user experience
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---
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## 🎯 Core Philosophy: Let AI Handle AI Context
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### **The Problem with Hardcoded Solutions**
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**Previous Approach (FLAWED):**
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```javascript
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// ❌ English-only, brittle, not scalable
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if (content.includes('outline') || content.includes('structure')) {
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return 'create_outline';
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}
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```
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**Issues:**
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- ❌ Only works in English
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- ❌ Breaks in Indonesian, Arabic, Chinese, etc.
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- ❌ Misses nuanced intent
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- ❌ Requires constant maintenance
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- ❌ Goes against "agentic" philosophy
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### **Agentic Principle**
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> **"If AI is smart enough to write articles, it's smart enough to manage its own context."**
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**New Approach:**
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- ✅ Use AI to summarize chat history
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- ✅ Use AI to detect user intent
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- ✅ Language-agnostic (works in any language)
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- ✅ Adapts to context automatically
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- ✅ True "agentic" experience
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---
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## 💰 Cost Analysis: AI-Powered Context Management
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### **Your Cost Reference**
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```
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Action: meta_description
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Model: deepseek-chat-v3-032
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Tokens: 510
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Cost: $0.0001
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```
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**This is EXTREMELY cheap!** Let's use this model for context operations.
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### **Proposed Actions**
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#### **1. Action: `summarize_context`**
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**Purpose:** Condense long chat history into key points
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**Input:**
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```json
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{
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"action": "summarize_context",
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"chat_history": [
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{"role": "user", "content": "Saya ingin menulis tentang keamanan WordPress"},
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{"role": "assistant", "content": "[Long response in Indonesian...]"},
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{"role": "user", "content": "Fokus pada plugin vulnerabilities saja"},
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{"role": "assistant", "content": "[Detailed plugin security response...]"}
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]
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}
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```
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**Prompt:**
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```
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Summarize this conversation into key points that capture the user's intent and requirements.
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Focus on:
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- Main topic
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- Specific focus areas
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- Rejected/excluded topics
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- User preferences (tone, audience, etc.)
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Keep the summary concise (max 200 words) but preserve critical context.
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Write in the same language as the conversation.
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Output format:
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TOPIC: [main topic]
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FOCUS: [what to include]
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EXCLUDE: [what to avoid]
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PREFERENCES: [any specific requirements]
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```
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**Expected Output:**
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```
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TOPIC: WordPress security
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FOCUS: Plugin vulnerabilities only
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EXCLUDE: Performance optimization, backup strategies (user rejected these)
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PREFERENCES: Technical audience, detailed explanations
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```
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**Cost Estimate:**
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- Input: 4,000 tokens (long chat history)
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- Output: 100 tokens (summary)
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- Model: deepseek-chat-v3-032
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- **Cost: ~$0.0001 per summarization**
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**When to Use:**
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- Chat history > 6 messages
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- Before generating outline
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- Before executing article
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---
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#### **2. Action: `detect_intent`**
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**Purpose:** Understand what user wants to do next
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**Input:**
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```json
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{
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"action": "detect_intent",
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"last_message": "Baiklah, sekarang buatkan outline-nya",
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"has_plan": false,
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"current_mode": "chat"
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}
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```
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**Prompt:**
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```
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Based on the user's message, determine their intent. Choose ONE:
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1. "create_outline" - User wants to create an article outline/structure
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2. "start_writing" - User wants to write the full article
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3. "refine_content" - User wants to improve existing content
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4. "continue_chat" - User wants to continue discussing/exploring
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5. "clarify" - User is asking questions or needs clarification
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Consider:
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- The user's explicit request
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- Whether they have an outline already (has_plan: {has_plan})
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- Current mode (current_mode: {current_mode})
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Respond with ONLY the intent code (e.g., "create_outline").
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```
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**Expected Output:**
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```
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create_outline
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```
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**Cost Estimate:**
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- Input: 100 tokens (last message + context)
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- Output: 5 tokens (intent code)
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- Model: deepseek-chat-v3-032
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- **Cost: ~$0.00002 per detection**
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**When to Use:**
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- After every user message in Chat mode
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- To show contextual action buttons
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- To auto-suggest next steps
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---
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## 📊 Cost Comparison: Full History vs AI-Powered
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### **Scenario: 5 Agent + 4 Human Messages**
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| Approach | Input Tokens | Output Tokens | Cost per Request | Quality | Language Support |
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|----------|--------------|---------------|------------------|---------|------------------|
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| **Full History** | 4,365 | 0 | $0.013 (Claude) | ✅ Best | ✅ All |
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| **AI Summarization** | 100 (summary) | 0 | $0.003 (Claude) + $0.0001 (summary) | ✅ Good | ✅ All |
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| **Hardcoded Pruning** | 1,800 | 0 | $0.005 (Claude) | ⚠️ Fair | ❌ English only |
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| **No Context** | 0 | 0 | $0.000 | ❌ Poor | ✅ All |
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### **Cost Breakdown for 100 Articles/Month**
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**Full History:**
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- Planning: 100 × $0.00033 = $0.033
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- Execution: 100 × $0.013 = $1.30
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- **Total: $1.33/month**
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**AI Summarization:**
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- Summarization: 100 × $0.0001 = $0.01
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- Planning: 100 × $0.00008 = $0.008
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- Execution: 100 × $0.003 = $0.30
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- **Total: $0.32/month**
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- **Savings: $1.01/month (76% reduction)**
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**Intent Detection:**
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- Per message: $0.00002
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- Average 10 messages per article: 100 × 10 × $0.00002 = $0.02
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- **Total: $0.02/month (negligible)**
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---
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## 🎯 The Big Picture: Agentic Experience
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### **User Journey Analysis**
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**Current Flow (Fragmented):**
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```
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1. User opens editor
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2. User manually switches to Chat mode
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3. User types message
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4. Agent responds
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5. User types more
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6. Agent responds
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7. User manually switches to Planning mode
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8. User types "create outline"
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9. Outline generated
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10. User manually clicks "Start Writing"
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11. Article generated
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```
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**Problems:**
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- Too many manual mode switches
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- User must know when to switch
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- No guidance on next steps
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- Friction in workflow
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---
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### **Proposed Agentic Flow (Seamless):**
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```
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1. User opens editor (any mode)
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2. User types: "Saya ingin menulis tentang keamanan WordPress"
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3. Agent responds with suggestions
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4. User types: "Fokus pada plugin vulnerabilities"
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5. Agent responds with refined ideas
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6. 💡 UI shows: [📝 Ready to create outline?] (AI-detected intent)
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7. User clicks button (or types "yes" or "buatkan outline")
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8. ✨ AI summarizes chat history (0.1 seconds)
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9. Outline generated with clean context
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10. 💡 UI shows: [✍️ Start Writing] (auto-suggested)
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11. User clicks
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12. Article generated
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```
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**Improvements:**
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- ✅ No manual mode switching needed
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- ✅ AI suggests next steps proactively
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- ✅ Context automatically optimized
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- ✅ Smooth, guided experience
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- ✅ Works in any language
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---
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## 🔧 Implementation Design
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### **Backend: New Actions**
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```php
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/**
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* Handle context summarization request.
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*
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* @param WP_REST_Request $request REST request.
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* @return WP_REST_Response|WP_Error Response.
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*/
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public function handle_summarize_context( $request ) {
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$params = $request->get_json_params();
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$chat_history = $params['chatHistory'] ?? array();
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if ( empty( $chat_history ) || count( $chat_history ) < 4 ) {
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// No need to summarize short history
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return new WP_REST_Response(
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array(
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'summary' => '',
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'use_full_history' => true,
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),
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200
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);
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}
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// Build summarization prompt
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$history_text = '';
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foreach ( $chat_history as $msg ) {
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$role = ucfirst( $msg['role'] ?? 'Unknown' );
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$content = $msg['content'] ?? '';
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$history_text .= "{$role}: {$content}\n\n";
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}
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$prompt = "Summarize this conversation into key points that capture the user's intent and requirements.
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Focus on:
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- Main topic
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- Specific focus areas
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- Rejected/excluded topics
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- User preferences (tone, audience, etc.)
|
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|
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Keep the summary concise (max 200 words) but preserve critical context.
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Write in the same language as the conversation.
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|
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Output format:
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TOPIC: [main topic]
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FOCUS: [what to include]
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EXCLUDE: [what to avoid]
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PREFERENCES: [any specific requirements]
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Conversation:
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{$history_text}";
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$provider = WP_Agentic_Writer_OpenRouter_Provider::get_instance();
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$messages = array(
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array(
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'role' => 'user',
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'content' => $prompt,
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),
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);
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// Use cheap model for summarization
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$response = $provider->chat( $messages, array(), 'summarize' );
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if ( is_wp_error( $response ) ) {
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return $response;
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}
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// Track cost
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do_action(
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'wp_aw_after_api_request',
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$params['postId'] ?? 0,
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$response['model'] ?? '',
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'summarize_context',
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$response['input_tokens'] ?? 0,
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$response['output_tokens'] ?? 0,
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$response['cost'] ?? 0
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);
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return new WP_REST_Response(
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array(
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'summary' => $response['content'] ?? '',
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'use_full_history' => false,
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'cost' => $response['cost'] ?? 0,
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),
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200
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);
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}
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/**
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* Handle intent detection request.
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*
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* @param WP_REST_Request $request REST request.
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* @return WP_REST_Response|WP_Error Response.
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*/
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public function handle_detect_intent( $request ) {
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$params = $request->get_json_params();
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$last_message = $params['lastMessage'] ?? '';
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$has_plan = $params['hasPlan'] ?? false;
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$current_mode = $params['currentMode'] ?? 'chat';
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if ( empty( $last_message ) ) {
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return new WP_REST_Response(
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array( 'intent' => 'continue_chat' ),
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200
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);
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}
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$prompt = "Based on the user's message, determine their intent. Choose ONE:
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1. \"create_outline\" - User wants to create an article outline/structure
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2. \"start_writing\" - User wants to write the full article
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3. \"refine_content\" - User wants to improve existing content
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4. \"continue_chat\" - User wants to continue discussing/exploring
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5. \"clarify\" - User is asking questions or needs clarification
|
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|
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Consider:
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- The user's explicit request
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- Whether they have an outline already (has_plan: " . ( $has_plan ? 'true' : 'false' ) . ")
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- Current mode (current_mode: {$current_mode})
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User's message: \"{$last_message}\"
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Respond with ONLY the intent code (e.g., \"create_outline\").";
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$provider = WP_Agentic_Writer_OpenRouter_Provider::get_instance();
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$messages = array(
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array(
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'role' => 'user',
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'content' => $prompt,
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),
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);
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$response = $provider->chat( $messages, array(), 'intent_detection' );
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|
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if ( is_wp_error( $response ) ) {
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return $response;
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}
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|
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// Track cost
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do_action(
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'wp_aw_after_api_request',
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$params['postId'] ?? 0,
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$response['model'] ?? '',
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'detect_intent',
|
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$response['input_tokens'] ?? 0,
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$response['output_tokens'] ?? 0,
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$response['cost'] ?? 0
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);
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$intent = trim( strtolower( $response['content'] ?? 'continue_chat' ) );
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return new WP_REST_Response(
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array(
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'intent' => $intent,
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'cost' => $response['cost'] ?? 0,
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),
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200
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);
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}
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```
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---
|
||||
|
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### **Frontend: Agentic UX**
|
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|
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```javascript
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// Auto-detect intent after each message
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const handleMessageSent = async (userMessage) => {
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// Send message to chat
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const chatResponse = await sendChatMessage(userMessage);
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|
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// Detect intent in background
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const intentResponse = await fetch('/wp-json/wp-agentic-writer/v1/detect-intent', {
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method: 'POST',
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body: JSON.stringify({
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lastMessage: userMessage,
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hasPlan: !!currentPlan,
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currentMode: agentMode,
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postId: postId
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})
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});
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const { intent } = await intentResponse.json();
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// Show contextual action based on intent
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setDetectedIntent(intent);
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showContextualAction(intent);
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};
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// Render contextual action buttons
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const renderContextualAction = () => {
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if (!detectedIntent) return null;
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switch (detectedIntent) {
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case 'create_outline':
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return (
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<div className="contextual-action">
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<p>💡 Ready to create an outline?</p>
|
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<button onClick={handleCreateOutlineWithSummary} className="primary">
|
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📝 Create Outline
|
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</button>
|
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</div>
|
||||
);
|
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|
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case 'start_writing':
|
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if (!currentPlan) {
|
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return (
|
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<div className="contextual-action">
|
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<p>⚠️ You need an outline first</p>
|
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<button onClick={handleCreateOutlineWithSummary}>
|
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📝 Create Outline First
|
||||
</button>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
return (
|
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<div className="contextual-action">
|
||||
<p>💡 Ready to write the article?</p>
|
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<button onClick={handleStartWriting} className="primary">
|
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✍️ Start Writing
|
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</button>
|
||||
</div>
|
||||
);
|
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|
||||
case 'refine_content':
|
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return (
|
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<div className="contextual-action">
|
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<p>💡 Use @block to refine specific sections</p>
|
||||
</div>
|
||||
);
|
||||
|
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default:
|
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return null;
|
||||
}
|
||||
};
|
||||
|
||||
// Create outline with AI summarization
|
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const handleCreateOutlineWithSummary = async () => {
|
||||
setIsLoading(true);
|
||||
|
||||
// Step 1: Summarize chat history if needed
|
||||
let contextToSend = messages;
|
||||
|
||||
if (messages.length > 6) {
|
||||
showStatus('Optimizing context...');
|
||||
|
||||
const summaryResponse = await fetch('/wp-json/wp-agentic-writer/v1/summarize-context', {
|
||||
method: 'POST',
|
||||
body: JSON.stringify({
|
||||
chatHistory: messages,
|
||||
postId: postId
|
||||
})
|
||||
});
|
||||
|
||||
const { summary, use_full_history, cost } = await summaryResponse.json();
|
||||
|
||||
if (!use_full_history && summary) {
|
||||
// Use summarized context
|
||||
contextToSend = [
|
||||
{
|
||||
role: 'system',
|
||||
content: `Context Summary:\n${summary}`
|
||||
},
|
||||
...messages.slice(-2) // Keep last exchange
|
||||
];
|
||||
|
||||
console.log('Context optimized. Cost:', cost);
|
||||
}
|
||||
}
|
||||
|
||||
// Step 2: Generate outline with optimized context
|
||||
showStatus('Creating outline...');
|
||||
|
||||
const outlineResponse = await fetch('/wp-json/wp-agentic-writer/v1/generate-plan', {
|
||||
method: 'POST',
|
||||
body: JSON.stringify({
|
||||
topic: extractTopic(messages),
|
||||
chatHistory: contextToSend,
|
||||
postId: postId,
|
||||
postConfig: postConfig,
|
||||
stream: true
|
||||
})
|
||||
});
|
||||
|
||||
// Handle streaming response...
|
||||
};
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🎨 UX Enhancements
|
||||
|
||||
### **1. Contextual Action Cards**
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ Agent: "I can help you create a comprehensive │
|
||||
│ outline for WordPress plugin security..." │
|
||||
├─────────────────────────────────────────────────────┤
|
||||
│ 💡 Detected Intent: Create Outline │
|
||||
│ │
|
||||
│ [📝 Create Outline] [💬 Continue Discussing] │
|
||||
│ │
|
||||
│ 💰 Context will be optimized (~$0.0001) │
|
||||
└─────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### **2. Context Optimization Indicator**
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ ⚡ Optimizing context... │
|
||||
│ • 9 messages → Summary (200 words) │
|
||||
│ • Token reduction: 4,365 → 450 (90%) │
|
||||
│ • Cost: $0.0001 │
|
||||
│ ✓ Done in 0.2s │
|
||||
└─────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### **3. Smart Mode Transitions**
|
||||
|
||||
```
|
||||
User in Chat mode types: "buatkan outline-nya"
|
||||
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ 💡 Switching to Planning mode... │
|
||||
│ • Detected intent: Create outline │
|
||||
│ • Optimizing 7 messages of context │
|
||||
│ • Generating outline... │
|
||||
└─────────────────────────────────────────────────────┘
|
||||
|
||||
[Outline appears]
|
||||
|
||||
┌─────────────────────────────────────────────────────┐
|
||||
│ ✨ Outline ready! │
|
||||
│ │
|
||||
│ Next step: │
|
||||
│ [✍️ Start Writing Article] │
|
||||
└─────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 📊 Decision Matrix: When to Use What?
|
||||
|
||||
| Situation | Recommended Approach | Reason |
|
||||
|-----------|---------------------|--------|
|
||||
| **Chat history ≤ 4 messages** | Send full history | Short enough, no optimization needed |
|
||||
| **Chat history 5-8 messages** | AI summarization | Balance cost and quality |
|
||||
| **Chat history > 8 messages** | AI summarization + last 2 | Keep recent context verbatim |
|
||||
| **User switches modes** | Detect intent | Guide user to next action |
|
||||
| **Before outline generation** | Summarize context | Clean, focused input |
|
||||
| **Before article execution** | Use plan (no chat history) | Plan already has all context |
|
||||
| **Block refinement** | No chat history | Block content is sufficient |
|
||||
| **User types "/reset"** | Clear all context | Fresh start |
|
||||
|
||||
---
|
||||
|
||||
## 🎯 Recommendation: Hybrid Intelligent Approach
|
||||
|
||||
### **The Winning Strategy**
|
||||
|
||||
**Combine AI-powered + Smart Defaults:**
|
||||
|
||||
1. **Default Behavior (No User Action)**
|
||||
- Chat history ≤ 4 messages → Send full history
|
||||
- Chat history > 4 messages → Auto-summarize with AI
|
||||
- Cost: ~$0.0001 per summarization (negligible)
|
||||
|
||||
2. **Intent Detection (Automatic)**
|
||||
- After every user message → Detect intent
|
||||
- Show contextual action buttons
|
||||
- Cost: ~$0.00002 per detection (negligible)
|
||||
|
||||
3. **User Control (Optional)**
|
||||
- Settings: "Context Mode" → Auto/Full/Minimal
|
||||
- "/reset" command → Clear context
|
||||
- Manual selection UI (advanced users)
|
||||
|
||||
### **Why This Works**
|
||||
|
||||
✅ **Language-Agnostic**
|
||||
- Works in English, Indonesian, Arabic, Chinese, etc.
|
||||
- No hardcoded keywords
|
||||
|
||||
✅ **Cost-Effective**
|
||||
- 76% cost reduction vs full history
|
||||
- Total added cost: ~$0.34/month for 100 articles
|
||||
- ROI: Better quality + Lower cost
|
||||
|
||||
✅ **True Agentic Experience**
|
||||
- AI manages its own context
|
||||
- Proactive suggestions
|
||||
- Seamless workflow
|
||||
- No manual mode switching
|
||||
|
||||
✅ **User-Friendly**
|
||||
- Automatic by default
|
||||
- Optional manual control
|
||||
- Transparent (shows what's happening)
|
||||
- Fast (summarization takes 0.1-0.3s)
|
||||
|
||||
---
|
||||
|
||||
## 🔧 Implementation Plan
|
||||
|
||||
### **Phase 1: Core Infrastructure** (Week 1)
|
||||
|
||||
**Backend:**
|
||||
- [ ] Add `/summarize-context` endpoint
|
||||
- [ ] Add `/detect-intent` endpoint
|
||||
- [ ] Add `summarize` and `intent_detection` operation types to cost tracking
|
||||
- [ ] Update OpenRouter provider to support these actions
|
||||
|
||||
**Frontend:**
|
||||
- [ ] Add `handleSummarizeContext()` function
|
||||
- [ ] Add `handleDetectIntent()` function
|
||||
- [ ] Add context optimization indicator component
|
||||
|
||||
**Testing:**
|
||||
- [ ] Test summarization in English, Indonesian, Arabic
|
||||
- [ ] Test intent detection in multiple languages
|
||||
- [ ] Verify cost tracking
|
||||
|
||||
### **Phase 2: UX Integration** (Week 2)
|
||||
|
||||
**Frontend:**
|
||||
- [ ] Add contextual action cards
|
||||
- [ ] Auto-detect intent after each message
|
||||
- [ ] Show "Optimizing context..." status
|
||||
- [ ] Add smart mode transitions
|
||||
|
||||
**Settings:**
|
||||
- [ ] Add "Context Mode" setting (Auto/Full/Minimal)
|
||||
- [ ] Add context optimization toggle
|
||||
- [ ] Add cost estimates in settings
|
||||
|
||||
**Testing:**
|
||||
- [ ] Test full user journey (chat → outline → write)
|
||||
- [ ] Test in multiple languages
|
||||
- [ ] Verify smooth transitions
|
||||
|
||||
### **Phase 3: Advanced Features** (Week 3)
|
||||
|
||||
**Features:**
|
||||
- [ ] Add `/reset` command
|
||||
- [ ] Add manual context selection UI (optional)
|
||||
- [ ] Add context analytics (token usage, cost breakdown)
|
||||
- [ ] Add context caching (reuse summaries)
|
||||
|
||||
**Optimization:**
|
||||
- [ ] Implement smart caching for summaries
|
||||
- [ ] Add context relevance scoring
|
||||
- [ ] Optimize prompt templates
|
||||
|
||||
**Documentation:**
|
||||
- [ ] Update user guide
|
||||
- [ ] Add context management section
|
||||
- [ ] Document cost implications
|
||||
|
||||
---
|
||||
|
||||
## 💰 Final Cost Analysis
|
||||
|
||||
### **Per Article (Average)**
|
||||
|
||||
| Component | Cost | Frequency |
|
||||
|-----------|------|-----------|
|
||||
| Intent detection | $0.00002 × 10 messages | = $0.0002 |
|
||||
| Context summarization | $0.0001 × 1 time | = $0.0001 |
|
||||
| Planning (with summary) | $0.003 | = $0.003 |
|
||||
| Execution (no history) | $0.50-$2.00 | = $1.00 avg |
|
||||
| **Total per article** | | **≈ $1.0033** |
|
||||
|
||||
**Compared to Full History:**
|
||||
- Full history approach: $1.013 per article
|
||||
- AI-powered approach: $1.0033 per article
|
||||
- **Savings: $0.01 per article** (negligible)
|
||||
|
||||
**But wait - the real benefit:**
|
||||
- ✅ Better quality (clean, focused context)
|
||||
- ✅ Language-agnostic (works everywhere)
|
||||
- ✅ Better UX (proactive suggestions)
|
||||
- ✅ Scalable (no hardcoded rules)
|
||||
|
||||
---
|
||||
|
||||
## 🎯 Answer to Your Question
|
||||
|
||||
### **"Send all chat history vs AI summarization?"**
|
||||
|
||||
**Answer: AI Summarization is Better**
|
||||
|
||||
**Reasons:**
|
||||
|
||||
1. **Cost is Nearly Identical**
|
||||
- Full history: $1.013/article
|
||||
- AI summary: $1.0033/article
|
||||
- Difference: $0.01 (1% savings)
|
||||
|
||||
2. **Quality is Better**
|
||||
- Summary removes contradicted ideas
|
||||
- Summary focuses on final intent
|
||||
- Summary prevents pollution
|
||||
- AI explicitly told what to focus on
|
||||
|
||||
3. **Language Support**
|
||||
- Full history: Works in all languages ✅
|
||||
- AI summary: Works in all languages ✅
|
||||
- Hardcoded: Only English ❌
|
||||
|
||||
4. **Agentic Experience**
|
||||
- AI managing AI context = true agentic
|
||||
- Proactive intent detection
|
||||
- Seamless workflow
|
||||
- No user friction
|
||||
|
||||
5. **Scalability**
|
||||
- No hardcoded rules to maintain
|
||||
- Adapts to new languages automatically
|
||||
- Handles edge cases gracefully
|
||||
|
||||
### **The Plan:**
|
||||
|
||||
1. ✅ **Implement AI summarization** (not hardcoded)
|
||||
2. ✅ **Implement AI intent detection** (not hardcoded)
|
||||
3. ✅ **Make it automatic** (no user action needed)
|
||||
4. ✅ **Add user controls** (optional override)
|
||||
5. ✅ **Track costs transparently** (show user what's happening)
|
||||
|
||||
---
|
||||
|
||||
**Status:** 🚀 READY TO IMPLEMENT
|
||||
**Approach:** AI-Powered (Agentic)
|
||||
**Cost Impact:** Negligible (+$0.34/month for 100 articles)
|
||||
**Quality Impact:** Significant improvement
|
||||
**UX Impact:** Seamless, guided experience
|
||||
Reference in New Issue
Block a user