embeddings fix for ollama
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@ -119,16 +119,22 @@ class EmbeddingsService {
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const apiKey = process.env.AI_EMBEDDINGS_API_KEY;
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const apiKey = process.env.AI_EMBEDDINGS_API_KEY;
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const model = process.env.AI_EMBEDDINGS_MODEL;
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const model = process.env.AI_EMBEDDINGS_MODEL;
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if (!endpoint || !apiKey || !model) {
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if (!endpoint || !model) {
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throw new Error('Missing embeddings API configuration');
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throw new Error('Missing embeddings API configuration');
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}
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}
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const headers: Record<string, string> = {
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'Content-Type': 'application/json'
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};
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// API key is optional for Ollama but required for Mistral/OpenAI
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if (apiKey) {
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headers['Authorization'] = `Bearer ${apiKey}`;
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}
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const response = await fetch(endpoint, {
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const response = await fetch(endpoint, {
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method: 'POST',
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method: 'POST',
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headers: {
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headers,
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${apiKey}`
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},
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body: JSON.stringify({
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body: JSON.stringify({
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model,
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model,
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input: contents
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input: contents
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@ -141,7 +147,18 @@ class EmbeddingsService {
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}
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}
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const data = await response.json();
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const data = await response.json();
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return data.data.map((item: any) => item.embedding);
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// Detect Ollama format
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if (Array.isArray(data.embeddings)) {
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return data.embeddings;
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}
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// Detect OpenAI/Mistral format
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if (Array.isArray(data.data)) {
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return data.data.map((item: any) => item.embedding);
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}
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throw new Error('Unknown embeddings API response format');
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}
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}
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private async generateEmbeddings(toolsData: any, version: string): Promise<void> {
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private async generateEmbeddings(toolsData: any, version: string): Promise<void> {
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