Overview
An Excel agent combines Chunkr’s parsing power with an interactive viewer and LLM capabilities. Users can view native Excel cells, search for tables, and let the LLM read/write to specific cell ranges while keeping everything synchronized.Architecture
How It Works
1. Chunkr Output as Foundation
- Chunkr parses the Excel file once into structured data
- The viewer renders native cells directly from this parsed output
- All components work with the same underlying data structure
2. LLM Integration
- Read Operations: LLM analyzes specific cell ranges for patterns and insights
- Write Operations: LLM requests data changes through the sync code
- No Re-parsing: Changes are made to existing parsed data, Chunkr doesn’t re-parse
3. Sync Code Coordination
- Sync code is the central coordinator for all data modifications
- LLM sends change requests to sync code rather than modifying data directly
- Sync code updates parsed data, viewer, and vector DB embeddings simultaneously
- Ensures all components stay synchronized with a single source of truth
4. Search & Discovery
- Chunkr parsed output gets converted into embeddings for semantic understanding
- Vector DB stores these embeddings for efficient similarity search
- Enables semantic search for more intelligent data discovery
- LLM can quickly locate specific data ranges through natural language queries
Example Workflow
- Upload Excel file → Chunkr parses structure
- Create embeddings → Convert parsed data to vectors for search
- View native cells → Viewer displays from parsed output
- Search for tables → Find specific tables through natural language in vector DB
- LLM operations → Read/write to cell ranges
- Auto-update → Viewer reflects changes immediately