better-qdrant-mcp-server/build/services/embeddings/ollama.js

MCP server for enhanced Qdrant vector database functionality

import axios from 'axios';
import { BaseEmbeddingService } from './base.js';
export class OllamaEmbeddingService extends BaseEmbeddingService {
    constructor(endpoint, model) {
        super(undefined, endpoint || 'http://localhost:11434', model || 'nomic-embed-text');
        // Vector size depends on the model
        // nomic-embed-text produces 768-dimensional embeddings
        this.vectorSize = 768;
        this.defaultModel = 'nomic-embed-text';
        this.defaultEndpoint = 'http://localhost:11434';
        this.validateConfig();
    }
    async generateEmbeddings(texts) {
        const embeddings = [];
        // Ollama API requires sequential processing of texts
        for (const text of texts) {
            const response = await axios.post(`${this.endpoint}/api/embeddings`, {
                model: this.model || this.defaultModel,
                prompt: text,
            }, {
                headers: {
                    'Content-Type': 'application/json',
                },
            });
            if (!response.data.embedding || !Array.isArray(response.data.embedding)) {
                throw new Error('Invalid response from Ollama API');
            }
            embeddings.push(response.data.embedding);
        }
        return embeddings;
    }
    requiresApiKey() {
        return false;
    }
    validateConfig() {
        if (!this.endpoint) {
            throw new Error('Ollama endpoint is required');
        }
    }
}
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