101 lines
3.2 KiB
Go
101 lines
3.2 KiB
Go
package main
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import (
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"kreuzberg"
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)
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func main() {
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// Example 1: Preset model (recommended)
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// Fast, balanced, or quality preset configurations optimized for common use cases.
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embeddingConfig := kreuzberg.EmbeddingConfig{
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Model: kreuzberg.EmbeddingModelType{
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Type: "preset",
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Name: "balanced",
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},
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BatchSize: 32,
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Normalize: true,
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ShowDownloadProgress: true,
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CacheDir: "~/.cache/kreuzberg/embeddings",
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}
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// Available presets:
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// - "fast" (384 dims): Quick prototyping, development, resource-constrained
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// - "balanced" (768 dims): Production, general-purpose RAG, English documents
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// - "quality" (1024 dims): Complex documents, maximum accuracy
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// - "multilingual" (768 dims): International documents, 100+ languages
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// Example 2: Custom ONNX model (requires embeddings feature)
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// Direct access to specific ONNX embedding models from HuggingFace with custom dimensions.
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embeddingConfig = kreuzberg.EmbeddingConfig{
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Model: kreuzberg.EmbeddingModelType{
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Type: "custom",
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ModelID: "BAAI/bge-small-en-v1.5",
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Dimensions: 384,
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},
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BatchSize: 32,
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Normalize: true,
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ShowDownloadProgress: true,
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CacheDir: "", // Uses default: .kreuzberg/embeddings/
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}
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// Popular ONNX-compatible models:
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// - "BAAI/bge-small-en-v1.5" (384 dims): Fast, efficient
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// - "BAAI/bge-base-en-v1.5" (768 dims): Balanced quality/speed
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// - "BAAI/bge-large-en-v1.5" (1024 dims): High quality, slower
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// - "sentence-transformers/paraphrase-multilingual-mpnet-base-v2" (768 dims): Multilingual support
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// Example 3: Alternative Custom ONNX Model
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// For advanced users wanting different ONNX embedding models.
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embeddingConfig = kreuzberg.EmbeddingConfig{
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Model: kreuzberg.EmbeddingModelType{
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Type: "custom",
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ModelID: "sentence-transformers/all-mpnet-base-v2",
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Dimensions: 768,
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},
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BatchSize: 16, // Larger model requires smaller batch size
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Normalize: true,
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ShowDownloadProgress: true,
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CacheDir: "/var/cache/embeddings",
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}
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// Integration with ChunkingConfig
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// Add embeddings to your chunking configuration:
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chunkingConfig := kreuzberg.ChunkingConfig{
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MaxChars: 1024,
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MaxOverlap: 100,
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Preset: "balanced",
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Embedding: &kreuzberg.EmbeddingConfig{
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Model: kreuzberg.EmbeddingModelType{
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Type: "preset",
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Name: "balanced",
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},
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BatchSize: 32,
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Normalize: true,
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},
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}
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extractionConfig := kreuzberg.ExtractionConfig{
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Chunking: &chunkingConfig,
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}
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_ = embeddingConfig
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_ = extractionConfig
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}
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// Key parameter explanations:
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//
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// BatchSize: Number of texts to embed at once (32-128 typical)
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// - Larger batches are faster but use more memory
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// - Smaller batches for resource-constrained environments
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//
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// Normalize: Whether to normalize vectors (L2 norm)
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// - true (recommended): Enables cosine similarity in vector DBs
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// - false: Raw embedding values
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//
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// CacheDir: Where to store downloaded models
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// - Empty string: Uses .kreuzberg/embeddings/ in current directory
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// - Non-empty: Custom directory for model storage
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//
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// ShowDownloadProgress: Display download progress bar
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// - Useful for monitoring large model downloads
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