codevault/dist/providers/ollama.js

AI-powered semantic code search via Model Context Protocol

import { createRateLimiter } from '../utils/rate-limiter.js';
import { EmbeddingProvider, getModelProfile } from './base.js';
export class OllamaProvider extends EmbeddingProvider {
    ollama = null;
    model;
    rateLimiter;
    constructor(model = process.env.CODEVAULT_OLLAMA_EMBEDDING_MODEL || process.env.CODEVAULT_OLLAMA_MODEL || 'nomic-embed-text') {
        super();
        this.model = model;
        this.rateLimiter = createRateLimiter('Ollama');
    }
    async init() {
        if (!this.ollama) {
            try {
                const ollama = await import('ollama');
                this.ollama = ollama.default;
            }
            catch (error) {
                throw new Error('Ollama is not installed. Run: npm install ollama');
            }
        }
    }
    async generateEmbedding(text) {
        await this.init();
        const profile = await getModelProfile('Ollama', this.model);
        const maxChars = profile.maxChunkChars || 8000;
        return await this.rateLimiter.execute(async () => {
            const response = await this.ollama.embeddings({
                model: this.model,
                prompt: text.slice(0, maxChars)
            });
            return response.embedding;
        });
    }
    getDimensions() {
        if (process.env.CODEVAULT_EMBEDDING_DIMENSIONS || process.env.CODEVAULT_DIMENSIONS) {
            const dims = parseInt(process.env.CODEVAULT_EMBEDDING_DIMENSIONS || process.env.CODEVAULT_DIMENSIONS || '0', 10);
            if (!isNaN(dims) && dims > 0)
                return dims;
        }
        return 768;
    }
    getName() {
        return 'Ollama';
    }
    getModelName() {
        return this.model;
    }
}
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