chore: import upstream snapshot with attribution
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wehub-resource-sync
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# Basic Usage Example
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This example demonstrates the basic usage of Claude Context.
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## Prerequisites
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1. **OpenAI API Key**: Set your OpenAI API key for embeddings:
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```bash
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export OPENAI_API_KEY="your-openai-api-key"
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```
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2. **Milvus Server**: Make sure Milvus server is running:
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- You can also use fully managed Milvus on [Zilliz Cloud](https://zilliz.com/cloud).
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In this case, set the `MILVUS_ADDRESS` as the Public Endpoint and `MILVUS_TOKEN` as the Token like this:
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```bash
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export MILVUS_ADDRESS="https://your-cluster.zillizcloud.com"
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export MILVUS_TOKEN="your-zilliz-token"
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```
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- You can also set up a Milvus server on [Docker or Kubernetes](https://milvus.io/docs/install-overview.md). In this setup, please use the server address and port as your `uri`, e.g.`http://localhost:19530`. If you enable the authentication feature on Milvus, set the `token` as `"<your_username>:<your_password>"`, otherwise there is no need to set the token.
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```bash
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export MILVUS_ADDRESS="http://localhost:19530"
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export MILVUS_TOKEN="<your_username>:<your_password>"
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```
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## Running the Example
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1. Install dependencies:
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```bash
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pnpm install
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```
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2. Set environment variables (see examples above)
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3. Run the example:
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```bash
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pnpm run start
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```
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## What This Example Does
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1. **Indexes Codebase**: Indexes the entire Claude Context project
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2. **Performs Searches**: Executes semantic searches for different code patterns
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3. **Shows Results**: Displays search results with similarity scores and file locations
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## Expected Output
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```
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🚀 Claude Context Real Usage Example
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===============================
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...
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🔌 Connecting to vector database at: ...
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📖 Starting to index codebase...
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🗑️ Existing index found, clearing it first...
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📊 Indexing stats: 45 files, 234 code chunks
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🔍 Performing semantic search...
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🔎 Search: "vector database operations"
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1. Similarity: 89.23%
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File: /path/to/packages/core/src/vectordb/milvus-vectordb.ts
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Language: typescript
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Lines: 147-177
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Preview: async search(collectionName: string, queryVector: number[], options?: SearchOptions)...
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🎉 Example completed successfully!
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```
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import { Context, MilvusVectorDatabase, MilvusRestfulVectorDatabase, AstCodeSplitter, LangChainCodeSplitter } from '@zilliz/claude-context-core';
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import { envManager } from '@zilliz/claude-context-core';
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import * as path from 'path';
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// Try to load .env file
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try {
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require('dotenv').config();
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} catch (error) {
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// dotenv is not required, skip if not installed
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}
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async function main() {
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console.log('🚀 Context Real Usage Example');
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console.log('===============================');
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try {
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// 1. Choose Vector Database implementation
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// Set to true to use RESTful API (for environments without gRPC support)
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// Set to false to use gRPC (default, more efficient)
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const useRestfulApi = false;
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const milvusAddress = envManager.get('MILVUS_ADDRESS') || 'localhost:19530';
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const milvusToken = envManager.get('MILVUS_TOKEN');
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const splitterType = envManager.get('SPLITTER_TYPE')?.toLowerCase() || 'ast';
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console.log(`🔧 Using ${useRestfulApi ? 'RESTful API' : 'gRPC'} implementation`);
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console.log(`🔌 Connecting to Milvus at: ${milvusAddress}`);
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let vectorDatabase;
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if (useRestfulApi) {
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// Use RESTful implementation (for environments without gRPC support)
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vectorDatabase = new MilvusRestfulVectorDatabase({
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address: milvusAddress,
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...(milvusToken && { token: milvusToken })
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});
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} else {
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// Use gRPC implementation (default, more efficient)
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vectorDatabase = new MilvusVectorDatabase({
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address: milvusAddress,
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...(milvusToken && { token: milvusToken })
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});
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}
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// 2. Create Context instance
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let codeSplitter;
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if (splitterType === 'langchain') {
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codeSplitter = new LangChainCodeSplitter(1000, 200);
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} else {
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codeSplitter = new AstCodeSplitter(2500, 300);
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}
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const context = new Context({
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vectorDatabase,
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codeSplitter,
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supportedExtensions: ['.ts', '.js', '.py', '.java', '.cpp', '.go', '.rs']
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});
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// 3. Check if index already exists and clear if needed
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console.log('\n📖 Starting to index codebase...');
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const codebasePath = path.join(__dirname, '../..'); // Index entire project
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// Check if index already exists
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const hasExistingIndex = await context.hasIndex(codebasePath);
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if (hasExistingIndex) {
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console.log('🗑️ Existing index found, clearing it first...');
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await context.clearIndex(codebasePath);
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}
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// Index with progress tracking
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const indexStats = await context.indexCodebase(codebasePath);
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// 4. Show indexing statistics
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console.log(`\n📊 Indexing stats: ${indexStats.indexedFiles} files, ${indexStats.totalChunks} code chunks`);
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// 5. Perform semantic search
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console.log('\n🔍 Performing semantic search...');
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const queries = [
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'vector database operations',
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'code splitting functions',
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'embedding generation',
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'typescript interface definitions'
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];
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for (const query of queries) {
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console.log(`\n🔎 Search: "${query}"`);
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const results = await context.semanticSearch(codebasePath, query, 3, 0.3);
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if (results.length > 0) {
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results.forEach((result, index) => {
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console.log(` ${index + 1}. Similarity: ${(result.score * 100).toFixed(2)}%`);
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console.log(` File: ${path.join(codebasePath, result.relativePath)}`);
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console.log(` Language: ${result.language}`);
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console.log(` Lines: ${result.startLine}-${result.endLine}`);
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console.log(` Preview: ${result.content.substring(0, 100)}...`);
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});
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} else {
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console.log(' No relevant results found');
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}
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}
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console.log('\n🎉 Example completed successfully!');
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} catch (error) {
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console.error('❌ Error occurred:', error);
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// Provide detailed error diagnostics
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if (error instanceof Error) {
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if (error.message.includes('API key')) {
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console.log('\n💡 Please make sure to set the correct OPENAI_API_KEY environment variable');
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console.log(' Example: export OPENAI_API_KEY="your-actual-api-key"');
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} else if (error.message.includes('Milvus') || error.message.includes('connect')) {
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console.log('\n💡 Please make sure Milvus service is running');
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console.log(' - Default address: localhost:19530');
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console.log(' - Can be modified via MILVUS_ADDRESS environment variable');
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console.log(' - For RESTful API: set MILVUS_USE_RESTFUL=true');
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console.log(' - For gRPC (default): set MILVUS_USE_RESTFUL=false or leave unset');
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console.log(' - Start Milvus: docker run -p 19530:19530 milvusdb/milvus:latest');
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}
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console.log('\n💡 Environment Variables:');
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console.log(' - OPENAI_API_KEY: Your OpenAI API key (required)');
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console.log(' - OPENAI_BASE_URL: Custom OpenAI API endpoint (optional)');
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console.log(' - MILVUS_ADDRESS: Milvus server address (default: localhost:19530)');
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console.log(' - MILVUS_TOKEN: Milvus authentication token (optional)');
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console.log(' - SPLITTER_TYPE: Code splitter type - "ast" or "langchain" (default: ast)');
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}
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process.exit(1);
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}
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}
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// Run main program
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if (require.main === module) {
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main().catch(console.error);
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}
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export { main };
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@@ -0,0 +1,21 @@
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{
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"name": "claude-context-basic-example",
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"version": "0.1.3",
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"description": "Basic usage example for Claude Context",
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"main": "index.ts",
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"scripts": {
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"start": "tsx index.ts",
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"build": "tsc index.ts --outDir dist --target es2020 --module commonjs --moduleResolution node --esModuleInterop true",
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"dev": "tsx --watch index.ts"
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},
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"dependencies": {
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"@zilliz/claude-context-core": "workspace:*"
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},
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"devDependencies": {
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"tsx": "^4.0.0",
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"typescript": "^5.0.0",
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"@types/node": "^20.0.0",
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"dotenv": "^16.0.0"
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},
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"private": true
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}
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