Implements a complete dynamic tool loading system that allows the playground to discover and load tools from the TPMJS registry at runtime. **Architecture:** - Search tool package (@tpmjs/search-registry) - Searches registry for tools - Search API endpoint (/api/tools/search) - Text-based search with scoring - Pre-flight tool loading - Automatically searches and loads tools on every message - Railway executor service (Deno) - Loads tools from esm.sh via HTTP imports - Dynamic tool loader - Calls Railway to load and execute tools remotely **Key Components:** 1. Railway Executor (apps/railway-executor/) - Deno-based service that natively supports HTTP imports - Endpoints: /load-and-describe, /execute-tool, /cache/stats, /cache/clear - Deploys to Railway with deno run --allow-net --allow-env server.ts 2. Search Tool Package (packages/tools/search-registry/) - AI SDK v6 tool for searching TPMJS registry - Uses jsonSchema + inputSchema pattern - Searches /api/tools/search endpoint 3. Search API (apps/web/src/app/api/tools/search/) - Text-based search with composite scoring - Scores: text relevance + quality boost + download boost - Returns tool metadata with importUrl for dynamic loading 4. Dynamic Tool Loader (apps/playground/src/lib/dynamic-tool-loader.ts) - Calls Railway service to load tools from esm.sh - Creates tool wrappers that execute remotely - Process-level module cache + per-conversation tracking 5. Pre-flight Loading (apps/playground/src/app/api/chat/route.ts) - Automatically searches for tools on every user message - Loads top 5 matching tools before agent processes request - Merges with static tools for seamless experience **Technical Decisions:** - Deno over Node.js: Native HTTP import support without flags - Remote execution: Tools run in Railway sandbox, not Vercel - Pre-flight loading: Better UX than two-turn search pattern - Text search: BM25 had dependency issues, simple scoring works well **Environment Variables:** - RAILWAY_SERVICE_URL: https://endearing-commitment-production.up.railway.app 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
9.1 KiB
Railway Service - Dynamic Tool Loader Implementation
Overview
This document describes the Railway service implementation needed to support dynamic tool loading from esm.sh in the TPMJS playground.
Why Railway Service?
Next.js/Turbopack intercepts all import() calls and tries to resolve them through its module graph. HTTP URLs like https://esm.sh/... are not supported.
Solution: Use a plain Node.js service on Railway that:
- Runs with
--experimental-network-importsflag - Can dynamically import from HTTP URLs (esm.sh)
- Executes tool functions and returns results
- Is already set up for existing ToolPlayground
New Endpoint Required
POST /load-and-describe
Purpose: Dynamically import a tool package and return its AI SDK tool definition (description, schema) without executing it.
Request:
{
"packageName": "firecrawl-aisdk",
"exportName": "webSearchTool",
"version": "0.7.2",
"importUrl": "https://esm.sh/firecrawl-aisdk@0.7.2"
}
Response:
{
"success": true,
"tool": {
"exportName": "webSearchTool",
"description": "Search the web using Firecrawl",
"inputSchema": {
"type": "object",
"properties": {
"query": { "type": "string", "description": "Search query" }
},
"required": ["query"]
}
}
}
Implementation (pseudo-code for Railway service):
// server.js (Railway service)
import express from 'express';
const app = express();
app.use(express.json());
// Cache for imported modules
const moduleCache = new Map();
app.post('/load-and-describe', async (req, res) => {
const { packageName, exportName, version, importUrl } = req.body;
const cacheKey = `${packageName}::${exportName}`;
try {
let toolModule;
// Check cache first
if (moduleCache.has(cacheKey)) {
console.log(`✅ Cache hit: ${cacheKey}`);
toolModule = moduleCache.get(cacheKey);
} else {
// Dynamic import from esm.sh
const url = importUrl || `https://esm.sh/${packageName}@${version}`;
console.log(`📦 Importing: ${url}`);
const module = await import(url);
toolModule = module[exportName];
if (!toolModule) {
return res.status(404).json({
success: false,
error: `Export "${exportName}" not found in module`
});
}
// Validate it's an AI SDK tool
if (!toolModule.description || !toolModule.execute) {
return res.status(400).json({
success: false,
error: `Invalid AI SDK tool structure`
});
}
// Cache it
moduleCache.set(cacheKey, toolModule);
}
// Extract tool definition (description + schema)
// AI SDK v6 tools have: description, inputSchema, execute
res.json({
success: true,
tool: {
exportName,
description: toolModule.description,
inputSchema: toolModule.inputSchema || toolModule.parameters?.shape || {},
}
});
} catch (error) {
console.error('Failed to load tool:', error);
res.status(500).json({
success: false,
error: error.message
});
}
});
// Start server
const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
console.log(`Railway tool loader running on port ${PORT}`);
});
Railway Deployment:
# Start command in Railway settings:
node --experimental-network-imports server.js
# Or in package.json:
{
"scripts": {
"start": "node --experimental-network-imports server.js"
}
}
Modified Endpoint: POST /execute-tool
Purpose: Execute a dynamically loaded tool with parameters.
Request:
{
"packageName": "firecrawl-aisdk",
"exportName": "webSearchTool",
"version": "0.7.2",
"importUrl": "https://esm.sh/firecrawl-aisdk@0.7.2",
"params": {
"query": "latest AI news"
}
}
Response:
{
"success": true,
"output": {
"results": [...]
},
"executionTimeMs": 1234
}
Implementation (pseudo-code):
app.post('/execute-tool', async (req, res) => {
const { packageName, exportName, version, importUrl, params } = req.body;
const cacheKey = `${packageName}::${exportName}`;
const startTime = Date.now();
try {
let toolModule;
// Check cache or import
if (moduleCache.has(cacheKey)) {
toolModule = moduleCache.get(cacheKey);
} else {
const url = importUrl || `https://esm.sh/${packageName}@${version}`;
const module = await import(url);
toolModule = module[exportName];
if (!toolModule || !toolModule.execute) {
return res.status(404).json({
success: false,
error: 'Tool not found or invalid'
});
}
moduleCache.set(cacheKey, toolModule);
}
// Execute the tool
const result = await toolModule.execute(params);
res.json({
success: true,
output: result,
executionTimeMs: Date.now() - startTime
});
} catch (error) {
res.status(500).json({
success: false,
error: error.message,
executionTimeMs: Date.now() - startTime
});
}
});
Integration with Playground
1. Update dynamic-tool-loader.ts
Replace local dynamic imports with Railway service calls:
// apps/playground/src/lib/dynamic-tool-loader.ts
const RAILWAY_SERVICE_URL = process.env.RAILWAY_SERVICE_URL || 'http://localhost:3001';
export async function loadToolDynamically(
packageName: string,
exportName: string,
version: string,
importUrl?: string
): Promise<any | null> {
const cacheKey = getCacheKey(packageName, exportName);
// Check local cache first
if (moduleCache.has(cacheKey)) {
console.log(`✅ Cache hit: ${cacheKey}`);
return moduleCache.get(cacheKey);
}
try {
console.log(`📦 Loading from Railway: ${packageName}/${exportName}`);
// Call Railway service to load and describe tool
const response = await fetch(`${RAILWAY_SERVICE_URL}/load-and-describe`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
packageName,
exportName,
version,
importUrl,
}),
});
if (!response.ok) {
console.error(`❌ Railway service error: ${response.status}`);
return null;
}
const data = await response.json();
if (!data.success) {
console.error(`❌ Failed to load tool: ${data.error}`);
return null;
}
// Create a tool wrapper that executes remotely
const tool = {
description: data.tool.description,
inputSchema: data.tool.inputSchema,
execute: async (params: any) => {
console.log(`🚀 Executing ${packageName}/${exportName} remotely`);
const execResponse = await fetch(`${RAILWAY_SERVICE_URL}/execute-tool`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
packageName,
exportName,
version,
importUrl,
params,
}),
});
const result = await execResponse.json();
if (!result.success) {
throw new Error(result.error || 'Tool execution failed');
}
return result.output;
},
};
// Cache the wrapper
moduleCache.set(cacheKey, tool);
console.log(`✅ Loaded and cached: ${cacheKey}`);
return tool;
} catch (error) {
console.error(`❌ Failed to load ${packageName}#${exportName}:`, error);
return null;
}
}
2. Environment Variables
Add to .env.local:
RAILWAY_SERVICE_URL=https://your-railway-service.up.railway.app
Or for local testing with Railway running locally:
RAILWAY_SERVICE_URL=http://localhost:3001
Testing Locally
Terminal 1: Run Railway service locally
cd railway-service
node --experimental-network-imports server.js
Terminal 2: Run playground
cd tpmjs
pnpm dev --filter=@tpmjs/playground
Test the flow:
# Test Railway service directly
curl -X POST http://localhost:3001/load-and-describe \
-H "Content-Type: application/json" \
-d '{
"packageName": "firecrawl-aisdk",
"exportName": "webSearchTool",
"version": "0.7.2"
}'
# Then test via playground UI
# Navigate to http://localhost:3000/playground
# Ask: "search the web for latest AI news"
Deployment Checklist
- Create Railway service with Node.js
- Add
--experimental-network-importsflag to start command - Deploy
/load-and-describeendpoint - Deploy
/execute-toolendpoint (or modify existing/execute) - Set
RAILWAY_SERVICE_URLin Vercel environment variables - Test with real tools from TPMJS registry
- Monitor Railway logs for import errors
Benefits
- ✅ Works around Next.js limitations - Imports happen in plain Node
- ✅ Reuses existing Railway infrastructure - No new service needed
- ✅ Caching on both sides - Local cache + Railway cache
- ✅ Security - Tools execute in Railway sandbox, not Next.js
- ✅ Scalability - Railway handles the heavy lifting
Next Steps
- Implement Railway service endpoints
- Update
dynamic-tool-loader.tsto use Railway - Test locally
- Deploy to Railway + Vercel
- Celebrate dynamic tool loading! 🎉