301 lines
9.3 KiB
Markdown
301 lines
9.3 KiB
Markdown
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# What's New: Multi-Agent Features
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General Bots has been enhanced with powerful multi-agent orchestration capabilities. This document summarizes the new features, keywords, and configuration options.
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## Overview
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The multi-agent update introduces:
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- **Agent-to-Agent (A2A) Protocol** - Bots communicate and delegate tasks
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- **Cross-Session User Memory** - User data persists across bots and sessions
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- **Dynamic Model Routing** - Switch LLM models based on task requirements
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- **Hybrid RAG Search** - Combined semantic + keyword search with RRF
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- **Code Sandbox** - Safe Python/JavaScript/Bash execution
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- **Agent Reflection** - Self-analysis for continuous improvement
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- **SSE Streaming** - Real-time response streaming
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## New BASIC Keywords
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### Multi-Agent Keywords
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| Keyword | Description |
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|---------|-------------|
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| `ADD BOT` | Add a bot with triggers, tools, or schedules |
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| `DELEGATE TO BOT` | Send task to another bot and get response |
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| `BROADCAST TO BOTS` | Send message to all session bots |
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| `TRANSFER CONVERSATION` | Hand off conversation to another bot |
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| `BOT REFLECTION` | Enable agent self-analysis |
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| `BOT REFLECTION INSIGHTS` | Get reflection analysis results |
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### Memory Keywords
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| Keyword | Description |
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|---------|-------------|
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| `SET USER MEMORY` | Store data at user level (cross-bot) |
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| `GET USER MEMORY` | Retrieve user-level data |
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| `SET USER FACT` | Store a fact about the user |
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| `USER FACTS` | Get all stored user facts |
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### Model Routing Keywords
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| Keyword | Description |
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|---------|-------------|
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| `USE MODEL` | Switch LLM model (fast/quality/code/auto) |
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### Code Execution Keywords
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| Keyword | Description |
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|---------|-------------|
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| `RUN PYTHON` | Execute Python in sandbox |
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| `RUN JAVASCRIPT` | Execute JavaScript in sandbox |
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| `RUN BASH` | Execute Bash script in sandbox |
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| `RUN ... WITH FILE` | Run script from file |
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## Quick Examples
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### Multi-Agent Routing
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```basic
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' Router bot directing queries to specialists
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HEAR userquery
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category = LLM "Classify into billing, technical, sales: " + userquery
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SWITCH category
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CASE "billing"
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result = DELEGATE userquery TO BOT "billing-bot"
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CASE "technical"
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result = DELEGATE userquery TO BOT "tech-bot"
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CASE "sales"
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result = DELEGATE userquery TO BOT "sales-bot"
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END SWITCH
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TALK result
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```
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### Cross-Bot User Memory
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```basic
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' Store user preference (accessible from any bot)
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SET USER MEMORY "language", "pt-BR"
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SET USER MEMORY "timezone", "America/Sao_Paulo"
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' In another bot - retrieve preference
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language = GET USER MEMORY("language")
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IF language = "pt-BR" THEN
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TALK "Olá! Como posso ajudar?"
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END IF
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```
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### Dynamic Model Selection
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```basic
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' Use fast model for simple queries
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USE MODEL "fast"
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greeting = LLM "Say hello"
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' Switch to quality model for complex analysis
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USE MODEL "quality"
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analysis = LLM "Analyze market trends and provide recommendations"
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' Let system decide automatically
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USE MODEL "auto"
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```
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### Code Sandbox
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```basic
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' Execute Python for data processing
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code = "
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import json
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data = [1, 2, 3, 4, 5]
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print(json.dumps({'sum': sum(data), 'avg': sum(data)/len(data)}))
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"
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result = RUN PYTHON code
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TALK "Statistics: " + result
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```
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### Agent Reflection
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```basic
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' Enable self-analysis
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BOT REFLECTION true
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BOT REFLECTION ON "conversation_quality"
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' Later, check insights
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insights = BOT REFLECTION INSIGHTS()
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IF insights.qualityScore < 0.7 THEN
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SEND MAIL admin, "Low Quality Alert", insights.summary
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END IF
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```
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## New Configuration Options
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Add these to your `config.csv`:
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### Multi-Agent (A2A)
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```csv
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name,value
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a2a-enabled,true
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a2a-timeout,30
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a2a-max-hops,5
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a2a-retry-count,3
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```
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### User Memory
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```csv
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name,value
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user-memory-enabled,true
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user-memory-max-keys,1000
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user-memory-default-ttl,0
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```
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### Model Routing
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```csv
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name,value
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model-routing-strategy,auto
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model-default,fast
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model-fast,DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_M.gguf
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model-quality,gpt-4
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model-code,codellama-7b.gguf
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```
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### Hybrid RAG Search
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```csv
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name,value
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rag-hybrid-enabled,true
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rag-dense-weight,0.7
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rag-sparse-weight,0.3
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rag-reranker-enabled,true
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```
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### Code Sandbox
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```csv
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name,value
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sandbox-runtime,lxc
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sandbox-timeout,30
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sandbox-memory-mb,512
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sandbox-cpu-percent,50
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sandbox-network,false
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sandbox-python-packages,numpy,pandas,pillow
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```
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### Bot Reflection
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```csv
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name,value
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reflection-enabled,true
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reflection-interval,10
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reflection-min-messages,3
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reflection-model,quality
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```
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### SSE Streaming
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```csv
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name,value
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sse-enabled,true
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sse-heartbeat,30
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sse-max-connections,1000
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```
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## Database Migrations
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Run migrations to create the new tables:
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```bash
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cd botserver
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cargo run -- migrate
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```
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### New Tables
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| Table | Purpose |
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|-------|---------|
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| `user_memory` | Cross-session user preferences and facts |
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| `user_preferences` | Per-session user settings |
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| `a2a_messages` | Agent-to-Agent protocol messages |
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| `user_memory_extended` | Enhanced memory with TTL |
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| `kg_relationships` | Knowledge graph relationships |
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| `conversation_summaries` | Episodic memory summaries |
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| `conversation_costs` | LLM cost tracking |
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| `openapi_tools` | OpenAPI tool tracking |
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| `agent_reflections` | Agent self-analysis results |
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| `chat_history` | Conversation history |
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| `session_bots` | Multi-agent session tracking |
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## Architecture
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```
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┌─────────────────────────────────────────────────────────────┐
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│ Multi-Agent System │
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├─────────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────┐ A2A Protocol ┌──────────┐ │
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│ │ Router │◄──────────────────►│ Billing │ │
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│ │ Bot │ │ Bot │ │
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│ └────┬─────┘ ┌──────────┐ └──────────┘ │
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│ │ │ Support │ │
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│ └─────────►│ Bot │◄──────────────────┐ │
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│ └──────────┘ │ │
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│ │ │
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│ ┌──────────────────────────────────────────────┼──────┐ │
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│ │ Shared Resources │ │ │
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│ │ ┌────────────┐ ┌────────────┐ ┌──────────┴─┐ │ │
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│ │ │ User │ │ Hybrid │ │ Model │ │ │
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│ │ │ Memory │ │ RAG Search │ │ Router │ │ │
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│ │ └────────────┘ └────────────┘ └────────────┘ │ │
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│ └───────────────────────────────────────────────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────┘
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```
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## Design Principles
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These features follow General Bots' core principles:
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1. **BASIC-First** - All features accessible via simple BASIC keywords
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2. **KISS** - Simple syntax, predictable behavior
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3. **Pragmatismo** - Real-world utility over theoretical purity
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4. **No Lock-in** - Local deployment, own your data
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## Performance Considerations
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| Feature | Impact | Mitigation |
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| A2A Protocol | Adds network latency | Use timeouts, local bots |
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| User Memory | Database queries | Caching, indexing |
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| Hybrid Search | Dual search paths | Results cached |
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| Code Sandbox | Container startup | Warm containers |
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| Reflection | LLM calls | Run periodically, not per-message |
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| SSE Streaming | Connection overhead | Connection pooling |
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## Migration Guide
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### From Single-Bot to Multi-Agent
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1. **Identify Specializations** - What tasks need dedicated bots?
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2. **Create Specialist Bots** - Each with focused config
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3. **Build Router** - Central bot to direct traffic
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4. **Share Memory** - Move shared data to User Memory
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5. **Test Delegation** - Verify communication paths
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### Upgrading Existing Bots
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1. Run database migrations
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2. Add new config options as needed
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3. Existing keywords continue to work unchanged
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4. Gradually adopt new features
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## See Also
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- [Multi-Agent Orchestration](./multi-agent-orchestration.md) - Complete guide
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- [Memory Management](./memory-management.md) - Memory deep dive
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- [Hybrid RAG Search](./hybrid-search.md) - Search configuration
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- [Keywords Reference](../chapter-06-gbdialog/keywords.md) - All keywords
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- [Configuration Parameters](../chapter-08-config/parameters.md) - All config options
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