What is a RAG application?

The RAG application template integrates information retrieval with text generation, allowing it to generate more accurate and contextually relevant responses.

Key features of a RAG workflow

• Allows more accurate response generation.
• Enables personalized, domain-specific content generation.
• Allows quick access to vast amounts of knowledge.

Who can benefit from the RAG template?

• Improve automated responses in customer service.
• Can assist legal professionals by retrieving relevant precedents, case law, and documents.
• Enrich company chats with access to internal knowledge.
• Quickly gather insights from previous campaigns, blogs, or market data for marketers.

How does the RAG application operate?

• Converts the query into vector representations (embeddings).
• Uses the generated embeddings to search a knowledge base.
• Generates a response using gathered information.

Customizing the RAG template for your needs

• Switch to alternative models for embedding or response generation. Use different storage solutions (such as PgVector, Pinecone, Qdrant, Chroma, Milvus).
• Add extra pre-processing steps for query refinement or file pre-processing.
• Any additional infrastructure can be easily built on top, such as integration with APIs and tools.
• Update prompts to ensure the tone and style remain accurate and aligned with your needs.
• Set-up custom document rankers.

Performance metrics and monitoring

• Monitor the latency and accuracy of retrieved documents, as well as the tone and correctness of the final responses, using both custom and prebuilt metrics.
• Monitor number of tokens and cost of inference.

How to use theRAG template

1. Press the “Use Template” button.
2. Press the “Test” button.
3. Type your query into the “query” field.
4. Press “Run”.