Local RAG System

# Auto-run: Plan and execute automatically
$ rago agent auto-run "analyze project structure and create documentation"

# Step-by-step approach
$ rago agent plan "monitor system performance daily"
$ rago agent run-plan plan_id_12345

# Create reusable agents
$ rago agent create research-agent "Weekly market research automation"
$ rago agent execute research-agent

# Workflow templates
$ rago agent templates
$ rago agent generate-template monitoring --type system-monitoring

# Plan management
$ rago agent list-plans
$ rago agent plan-status plan_id_12345

# Direct LLM chat
$ rago chat "Explain the concept of RAG systems"

# MCP-enhanced chat with tool access
$ rago mcp chat --interactive

# MCP server management
$ rago mcp status
$ rago mcp start filesystem
$ rago mcp list

# Direct tool calls
$ rago mcp call filesystem read_file '{"path": "README.md"}'
$ rago mcp call sqlite query '{"database": "data.db", "query": "SELECT * FROM users"}'

# Data management
$ rago rag export --format json --output backup.json
$ rago rag import --file backup.json
$ rago rag list --detailed
$ rago rag reset --confirm

# Start API server with UI
$ rago serve --port 7127 --ui

# RAG Operations
curl -X POST http://localhost:7127/api/ingest \
  -H "Content-Type: application/json" \
  -d '{"file_path": "document.pdf"}'

curl -X POST http://localhost:7127/api/query \
  -H "Content-Type: application/json" \
  -d '{"query": "summarize", "top_k": 5, "show_sources": true}'

# Agent Operations  
curl -X POST http://localhost:7127/api/agents \
  -H "Content-Type: application/json" \
  -d '{"name": "research-agent", "description": "Market research automation"}'

curl -X POST http://localhost:7127/api/agents/research-agent/execute \
  -H "Content-Type: application/json" \
  -d '{"goal": "analyze competitor pricing"}'

# MCP Tool Calls
curl -X POST http://localhost:7127/api/mcp/tools/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "filesystem", "action": "read_file", "params": {"path": "data.txt"}}'

# Health and Status
curl http://localhost:7127/api/health
curl http://localhost:7127/api/status

package main

import (
    "context"
    "fmt"
    "log"
    
    "github.com/liliang-cn/rago/v2/client"
)

func main() {
    ctx := context.Background()
    
    // Simplified client API - only 2 entry points!
    c, err := client.New("rago.toml") // Or empty string for defaults
    if err != nil {
        log.Fatal(err)
    }
    defer c.Close()
    
    // LLM operations with wrapper
    if c.LLM != nil {
        response, _ := c.LLM.Generate("Write a haiku about coding")
        fmt.Println(response)
        
        // Streaming
        c.LLM.Stream(ctx, "Tell a story", func(chunk string) {
            fmt.Print(chunk)
        })
    }
    
    // RAG operations with wrapper
    if c.RAG != nil {
        // Ingest documents
        c.RAG.Ingest("Your document content here")
        
        // Query with sources
        resp, _ := c.RAG.QueryWithOptions(ctx, "What are the key findings?",
            &client.QueryOptions{TopK: 5, ShowSources: true})
        fmt.Printf("Answer: %s\n", resp.Answer)
        
        for _, source := range resp.Sources {
            fmt.Printf("Source: %s (score: %.2f)\n", source.Source, source.Score)
        }
    }
    
    // MCP tools with wrapper
    if c.Tools != nil {
        tools, _ := c.Tools.List()
        fmt.Printf("Available tools: %d\n", len(tools))
        
        result, _ := c.Tools.Call(ctx, "filesystem_read",
            map[string]interface{}{"path": "README.md"})
        fmt.Printf("Tool result: %v\n", result)
    }
    
    // Agent automation with wrapper
    if c.Agent != nil {
        result, _ := c.Agent.Run("Summarize recent changes")
        fmt.Printf("Agent result: %v\n", result)
    }
    
    // Direct BaseClient methods also available
    resp, _ := c.Query(ctx, client.QueryRequest{
        Query: "test query",
        TopK:  3,
    })
    fmt.Printf("Direct query: %s\n", resp.Answer)
}