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browser-local provider for @agentix-e/nl2spel","maintainers":[{"name":"lambertyan","email":"853901691@qq.com"}],"readme":"# @agentix-e/nl2spel-webllm\n\n> Browser-local LLM Provider for @agentix-e/nl2spel\n>\n> GBNF grammar-constrained decoding · 4 optimized models · Zero API cost · WebLLM handles GPU detection natively\n\n[![npm](https://img.shields.io/npm/v/@agentix-e/nl2spel-webllm?color=blue)](https://www.npmjs.com/package/@agentix-e/nl2spel-webllm)\n[![API Docs](https://img.shields.io/badge/docs-TypeDoc-blue)](https://agentix-e.github.io/nl2spel/api/modules/nl2spel_webllm.html)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](../../LICENSE)\n\n---\n\n## API Documentation\n\n→ [nl2spel-webllm API](https://agentix-e.github.io/nl2spel/api/modules/nl2spel_webllm.html)\n\n## Model Configurations (4)\n\n| Model | Context | VRAM | Quantization |\n|-------|---------|------|--------------|\n| Qwen 2.5 1.5B | 32K | 1.5 GB | q4f16_1 |\n| Gemma 2 2B | 8K | 2.0 GB | q4f16_1 |\n| Phi-3 Mini 4K | 4K | 2.8 GB | q4f16_1 |\n| Llama 3.2 3B | 8K | 3.5 GB | q4f16_1 |\n\n## Quick Start\n\n```typescript\nimport { NL2SpelEngine } from '@agentix-e/nl2spel';\nimport { WebLLMProvider, recommendModel } from '@agentix-e/nl2spel-webllm';\n\nconst engine = new NL2SpelEngine();\n\n// Auto-select the best model for the current device\nconst modelName = recommendModel(4);  // 4GB VRAM\n// → 'qwen2.5-1.5b' (fastest)\n\nconst provider = new WebLLMProvider({\n  model: modelName,\n  onProgress: (p) => console.log(`Loading: ${(p.progress * 100).toFixed(0)}%`),\n});\n\nawait provider.initialize();\nengine.registerProvider(provider);\n\n// Zero API cost, local browser inference\nconst result = await engine.generate('Amount greater than 1000');\n```\n\n## GBNF Grammar Constraints\n\nThe WebLLM Provider constrains LLM output via dynamically generated GBNF grammar, ensuring **100% valid SpEL expressions**:\n\n```typescript\nimport { GBNFGenerator } from 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