Parser Tools

What is RAG Parser?

RAG Parser is a critical component in Retrieval-Augmented Generation (RAG) systems, responsible for parsing and breaking down raw data as a preprocessing step for embedding vectorization. It provides the foundation for subsequent vectorization and semantic retrieval, having a decisive impact on overall data quality and retrieval effectiveness.

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1. Document Parser Types

MaiAgent provides four document parsers, suitable for various document formats including PDF, Word, Excel, images, and more:

Feature	MaiAgent Parser (Default)	MaiAgent Parser (Online)	MaiAgent Parser (Offline)	Vision Parser
Cost	Low	High	Medium	High
Image Content Parsing	Cannot parse text in images	OCR only, can parse text in images	OCR + AI understands image semantics	AI visual understanding, best quality
Uses LLM	No	Yes	Yes	Yes
Text Parsing Quality	Standard	Good	Good (excellent structure preservation)	Good
Table Parsing	Native extraction	AI intelligently extracts text from images	Native structure preservation (best), includes static resources in images besides visual understanding	AI visual recognition generates text content from visual understanding of images
Parsing Speed	Fast	Medium	Slow	Slow
On-Premises (Offline)	Yes	No	Yes, but requires VLM deployment	No
Supported Formats	22 types	20 types	20 types (PDF only supports OCR)	7 types

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2. Speech-to-Text Parser Types

MaiAgent provides four speech-to-text parsers that can transcribe audio files into text for knowledge base integration:

Feature	Azure Speech	Whisper (Groq)	Whisper (OpenAI)	Whisper (Offline)
Cost	High	Low	Medium	Free
Transcription Accuracy	High	High (large-v3)	High (whisper-1)	High (depends on local model)
Uses LLM	No	No	No	No
Parsing Speed	Real-time	Fastest	Medium	Depends on hardware
On-Premises (Offline)	No	No	No	Yes
Multi-language Support	Yes	Yes (auto-detect)	Yes (auto-detect)	Yes (auto-detect)
Custom Prompts	No	Yes	Yes	Yes
VAD Voice Detection	—	Yes	Yes	Yes
Data Privacy	Cloud (Azure)	Cloud (Groq)	Cloud (OpenAI)	Fully local

After audio files are uploaded to the knowledge base, the system automatically performs speech-to-text parsing and provides transcript viewing and download functionality: