Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
Mining and mineral processing data primarily comes from production ledgers, mineral processing process records, safety compliance documents, and business approval forms. Data is updated either per work shift or calendar day. Document types include PDF safety regulations, DOCX work instructions, and Excel production parameter ledgers. Some monthly summary reports can reach tens of megabytes in size. Documents contain fields such as ore grade, processing volume, and operation duration, with units including tons and hours. The structure mixes structured tables and long text passages.
What Constraints These Characteristics Impose on Document Parsing and Chunking
The mixed structure of mining and mineral processing documents requires the parsing step to support both structured table extraction and long text passage parsing. This prevents splitting that breaks the contextual logical connection of production parameters and approval nodes. Large monthly reports may exceed standard parsing thresholds and cause timeout errors. The professional nature of industrial field values requires retaining the connection between adjacent fields during chunking, preventing fragmentation of the operational process logic chain. Fixed approval formats in business documents require accurate identification of node text to avoid incorrect splitting of approval steps.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Mining and mineral processing documents mostly contain coherent operational process descriptions and industrial parameters. This range preserves the complete logic of single-step operations. |
chunkSplitter | Custom delimiter and semantic segmentation | Documents contain structured tables and long text. Custom delimiters can match chapter separators in work instructions, and semantic segmentation avoids breaking the connection of industrial parameters. |
customPdfParse | Enabled | Mining and mineral processing PDF documents mostly contain embedded tables and professional charts. Enabling custom parsing improves extraction accuracy for structured content. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large monthly reports takes a long time. This duration covers the parsing needs of most large documents. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some monthly summary reports can be tens of megabytes in size. This threshold meets conventional large file upload requirements. |
chunkSettingMode | Manual configuration | Mining and mineral processing documents have large format differences. Manual configuration allows flexible adjustment of chunking rules to adapt to different types of business documents. |
Three Common Misconfigurations
- Uploading a 10+ MB PDF document triggers a
timeout of 360000ms exceedederror. The cause is failure to adjust thePARSE_FILE_TIMEOUT_SECONDSparameter to a duration suitable for large documents. The default timeout threshold is insufficient to cover the parsing time of large reports. - Content is missing or fields are misaligned when parsing individual DOCX documents. The cause is failure to enable the
customPdfParseconfiguration. The default parsing engine cannot accurately identify embedded industrial tables and professional formats in mining and mineral processing documents. - After importing preset question-and-answer pair documents and initiating related business queries, the returned results do not use the knowledge base original text for responses. The cause is failure to match the chunking rules to the separation format of the question-and-answer pairs. The default chunking logic breaks the complete structure of the question-and-answer pairs.
How to Verify Proper Configuration
- Upload a single mining and mineral processing PDF document larger than 10 MB, check whether the parsing task completes within the preset
PARSE_FILE_TIMEOUT_SECONDSduration, with no timeout errors. - Upload a DOCX work instruction containing embedded tables, verify that the parsed table content is complete and fields are not misaligned or missing.
- Import preset question-and-answer pair documents, initiate related business question queries, confirm that the returned results match the original text content of the knowledge base.
- View the chunking preview interface, confirm that long text passages are split reasonably without breaking the contextual connection of industrial parameters.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.