AI Tools

Evaluador de calidad de chunks RAG

Evalúa esquemas candidatos de división en chunks RAG para un documento en cuatro métricas — coherencia (límites limpios de frase/párrafo), cobertura (foco temático / concentración de términos clave), salud del solape de contexto y consistencia de tamaño — compara hasta tres esquemas y recomienda el mejor. Heurísticas offline, sin llamadas a modelo.

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Llama a esta herramienta desde tu código en tres lenguajes.

cURL

curl -X POST 'https://api.elysiatools.com/es/api/tools/ai-rag-chunk-quality-scorer' \
  -H 'Content-Type: application/json' \
  -d '{"document":"Retrieval-augmented generation combines a retriever and a language model. The retriever finds relevant passages in a knowledge base. Chunking strategy strongly affects retrieval quality. Smaller chunks are precise but lose context. Larger chunks carry context but dilute relevance. Overlap between chunks preserves context across boundaries. Evaluate several schemes before indexing.","unit":"tokens","method":"sentence","sizeA":256,"overlapA":32,"sizeB":512,"overlapB":64,"sizeC":1024,"overlapC":128,"renderMode":"comparison","precision":1}'

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Evaluador de calidad de chunks RAG

html· Resultado HTMLAbrir herramienta

Inicio rápido

Llama a esta herramienta desde tu código en tres lenguajes.

cURL

curl -X POST 'https://api.elysiatools.com/es/api/tools/ai-rag-chunk-quality-scorer' \
  -H 'Content-Type: application/json' \
  -d '{"document":"Retrieval-augmented generation combines a retriever and a language model. The retriever finds relevant passages in a knowledge base. Chunking strategy strongly affects retrieval quality. Smaller chunks are precise but lose context. Larger chunks carry context but dilute relevance. Overlap between chunks preserves context across boundaries. Evaluate several schemes before indexing.","unit":"tokens","method":"sentence","sizeA":256,"overlapA":32,"sizeB":512,"overlapB":64,"sizeC":1024,"overlapC":128,"renderMode":"comparison","precision":1}'

Nombre	Tipo	Obligatorio	Descripción
document	textarea	Sí	—
unit	select	No	—
method	select	No	—
sizeA	number	Sí	—
overlapA	number	No	—
sizeB	number	Sí	—
overlapB	number	No	—
sizeC	number	Sí	—
overlapC	number	No	—
renderMode	select	No	—
precision	number	Sí	—

{ "mcpServers": { "elysiatools-ai-rag-chunk-quality-scorer": { "name": "ai-rag-chunk-quality-scorer", "description": "Evalúa esquemas candidatos de división en chunks RAG para un documento en cuatro métricas — coherencia (límites limpios de frase/párrafo), cobertura (foco temático / concentración de términos clave), salud del solape de contexto y consistencia de tamaño — compara hasta tres esquemas y recomienda el mejor. Heurísticas offline, sin llamadas a modelo.", "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=ai-rag-chunk-quality-scorer", "command": "", "args": [], "env": {}, "isActive": true, "type": "sse" } } }

{ "jsonrpc": "2.0", "id": 2, "method": "tools/call", "params": { "name": "ai-rag-chunk-quality-scorer", "arguments": { "document": "Retrieval-augmented generation combines a retriever and a language model. The retriever finds relevant passages in a knowledge base. Chunking strategy strongly affects retrieval quality. Smaller chunks are precise but lose context. Larger chunks carry context but dilute relevance. Overlap between chunks preserves context across boundaries. Evaluate several schemes before indexing.", "unit": "tokens", "method": "sentence", "sizeA": 256, "overlapA": 32, "sizeB": 512, "overlapB": 64, "sizeC": 1024, "overlapC": 128, "renderMode": "comparison", "precision": 1 } } }

Evaluador de calidad de chunks RAG

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Evaluador de calidad de chunks RAG

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