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An overview of rules based ingestion in DataBridge
- DataBridge leverages Language Models (LLMs) guided by user-defined rules for consistent document processing, eliminating the need for custom pipelines.
- The rules system allows metadata extraction and content transformation, wherein rules are applied sequentially to document content.
- MetadataExtractionRule extracts structured data from documents into searchable metadata based on defined schemas.
- NaturalLanguageRule transforms document content as per natural language instructions like redaction or summarization.
- DataBridge supports multiple LLM providers like OpenAI and Ollama, configured through the databridge.toml file.
- Rules processing logic involves document parsing, validation, applying prompts, LLM interaction, and storing results based on rule types.
- DataBridge chunks large documents for efficient processing and provides the option to adjust batch_size for performance optimization.
- Effective rule creation involves specific prompts, rule sequencing, LLM selection based on task complexity, and engineering high-quality schemas.
- DataBridge's rules-based ingestion system is versatile for various use cases such as resume processing, medical record management, and legal document analysis.
- With a balance of simplicity on the client-side and power on the server-side, DataBridge offers flexibility, performance, and easy adaptation for diverse document processing needs.
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