What Data Looks Like for This Industry
Panel furniture, solid wood furniture, custom home and door enterprises generate daily data from order design systems, sheet and wood batch ledgers, CNC cutting and drilling equipment logs, ERP/MES systems, and moisture content test records. Daily documents include order breakdown drawings, cutting lists, edge banding and drilling programs, coating process documents, hardware material lists, assembly and packaging records. Data updates occur per order, daily, or per material batch. Document fields include panel size, batch number, hardware model, sheet thickness, processing time, and some documents include CAD vector drawings.
Constraints on Document Parsing and Chunking
Custom order-driven production creates high panel counts per order and wide variation in document structure. Some order breakdown drawings use mixed text and vector graphics exported from CAD. Differing update frequencies across multi-source data require adaptable parsing workflows. These workflows prevent traceability failures caused by delayed updates. Panel parameters are strongly linked to batches and hardware models. Chunking must retain contextual connections between parameters. This avoids loss of complete panel information after splitting. Compared to other product categories, custom furniture panel sizes tie directly to on-site installation spaces. Parsed chunks must accurately link to order information. This provides precise foundations for subsequent traceability.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Furniture documents contain multiple fields such as panel size and batch number. This range retains parameter associations within a single chunk and avoids splitting core information |
chunkSplitter | Split by paragraph + heading | Furniture documents have structured sections such as cutting lists and process descriptions. Splitting by headings preserves the logical hierarchy of documents |
customPdfParse | Enable vector graphic extraction mode | Furniture order breakdown drawings include CAD vector drawings. Extracted content can be linked to panel metadata and resolves issues where images cannot be viewed |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Large cutting list PDFs contain multi-page panel data. This range covers full parsing duration |
UPLOAD_FILE_MAX_SIZE | 500 MB | Collections of order breakdown drawings for custom orders may occupy significant storage space. This value supports batch uploads of multiple documents |
Three Common Configuration Errors
- A blank image area appears in the post-upload PDF preview. This occurs when vector graphic extraction for
customPdfParseis not enabled. Only text is parsed, and CAD drawing images are not extracted. - Search results return only text fragments without accompanying metadata. This happens when binding rules between chunks and document metadata are not configured. Search results cannot link to key information such as panel batch numbers and sheet thickness.
- Parsing times out after uploading an Excel cutting list. This is caused by not adjusting
PARSE_FILE_TIMEOUT_SECONDSto a value suitable for large tables. The default duration is insufficient to complete parsing.
How to Verify Proper Configuration
- Upload a test PDF containing a CAD order breakdown drawing. Check the knowledge base preview page to confirm images display correctly. This verifies that the
customPdfParseconfiguration is active. - Search for keywords for panel sizes in a cutting list. Review returned results to confirm they include accompanying metadata such as batch numbers and sheet thickness. This verifies the chunk and metadata binding configuration.
- Upload a cutting list PDF with more than 100 pages. Check the parsing status to confirm completion within 300 seconds. This verifies that the
PARSE_FILE_TIMEOUT_SECONDSvalue is appropriate. - Upload a document collection with a single file size of 400 MB. Confirm successful upload and completed parsing. This verifies that the
UPLOAD_FILE_MAX_SIZEconfiguration meets requirements.
The values provided are common starting points and should be measured against the reader's own samples. This page was written for FastGPT v4.17.0.