Merge pull request #393 from lskun/fix/embed-context-overflow
fix: truncate oversized text before embedding to prevent GGML crash
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commit
f35b4e19e0
43
src/llm.ts
43
src/llm.ts
@ -832,13 +832,42 @@ export class LlamaCpp implements LLM {
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// Core API methods
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// ==========================================================================
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/**
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* Truncate text to fit within the embedding model's context window.
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* Uses the model's own tokenizer for accurate token counting, then
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* detokenizes back to text if truncation is needed.
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* Returns the (possibly truncated) text and whether truncation occurred.
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*/
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private async truncateToContextSize(text: string): Promise<{ text: string; truncated: boolean }> {
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if (!this.embedModel) return { text, truncated: false };
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const maxTokens = this.embedModel.trainContextSize;
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if (maxTokens <= 0) return { text, truncated: false };
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const tokens = this.embedModel.tokenize(text);
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if (tokens.length <= maxTokens) return { text, truncated: false };
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// Leave a small margin (4 tokens) for BOS/EOS overhead
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const safeLimit = Math.max(1, maxTokens - 4);
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const truncatedTokens = tokens.slice(0, safeLimit);
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const truncatedText = this.embedModel.detokenize(truncatedTokens);
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return { text: truncatedText, truncated: true };
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}
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async embed(text: string, options: EmbedOptions = {}): Promise<EmbeddingResult | null> {
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// Ping activity at start to keep models alive during this operation
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this.touchActivity();
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try {
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const context = await this.ensureEmbedContext();
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const embedding = await context.getEmbeddingFor(text);
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// Guard: truncate text that exceeds model context window to prevent GGML crash
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const { text: safeText, truncated } = await this.truncateToContextSize(text);
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if (truncated) {
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console.warn(`⚠ Text truncated to fit embedding context (${this.embedModel?.trainContextSize} tokens)`);
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}
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const embedding = await context.getEmbeddingFor(safeText);
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return {
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embedding: Array.from(embedding.vector),
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@ -871,7 +900,11 @@ export class LlamaCpp implements LLM {
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const embeddings: ({ embedding: number[]; model: string } | null)[] = [];
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for (const text of texts) {
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try {
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const embedding = await context.getEmbeddingFor(text);
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const { text: safeText, truncated } = await this.truncateToContextSize(text);
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if (truncated) {
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console.warn(`⚠ Batch text truncated to fit embedding context (${this.embedModel?.trainContextSize} tokens)`);
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}
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const embedding = await context.getEmbeddingFor(safeText);
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this.touchActivity();
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embeddings.push({ embedding: Array.from(embedding.vector), model: this.embedModelUri });
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} catch (err) {
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@ -894,7 +927,11 @@ export class LlamaCpp implements LLM {
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const results: (EmbeddingResult | null)[] = [];
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for (const text of chunk) {
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try {
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const embedding = await ctx.getEmbeddingFor(text);
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const { text: safeText, truncated } = await this.truncateToContextSize(text);
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if (truncated) {
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console.warn(`⚠ Batch text truncated to fit embedding context (${this.embedModel?.trainContextSize} tokens)`);
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}
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const embedding = await ctx.getEmbeddingFor(safeText);
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this.touchActivity();
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results.push({ embedding: Array.from(embedding.vector), model: this.embedModelUri });
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} catch (err) {
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