What’s RAG (Retrieval-Augmented Technology)?
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The Current RAG Panorama
Challenges with Conventional RAG Architectures
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Three Main Agentic Methods
Agentic Layers for RAG Pipelines
Agentic RAG and LLMaIndex
Can the software handle diverse formats? The design should accommodate various file types, allowing users to easily integrate their data. Implementing a robust parser will ensure seamless integration, and support for popular formats such as CSV, JSON, and XML can be included. This versatility will attract a broader user base, increasing its market appeal.
1. Instrument Use and Routing
2. Lengthy-Time period Context Retention
3. Subquestion Engines for Planning
4. Reflection and Error Correction
5. Advanced agentic reasoning:
LlamaCloud and LlamaParse
Conclusion