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FAQ

Can I use this with my own vector database?​

Yes! You can implement the Retriever interface and register it:

registry.register('retriever', 'mydb', new MyRetriever());

Then use it via CLI or .ragrc.json.

Is streaming LLM response supported?​

Yes. LLM runners can yield async output tokens. This is handled internally via AsyncIterable in compatible models.

How do I evaluate performance?​

Use rag-pipeline evaluate dataset.json or open the dashboard at http://localhost:3000 to visualize BLEU/ROUGE and pass rates.

What file types can I ingest?​

Currently supported:

  • .pdf (mocked)
  • .md
  • .html
  • .csv
  • Full directory ingestion

Can I rerank results using a local model?​

Yes, as long as your local LLM implements:

llm.generate(prompt, context): Promise<string>

Use it to power LLMReranker.

How do I contribute?​

Fork the repo → add your plugin or CLI feature → test → submit PR.

Still stuck? Open an issue at GitHub.

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