What this category of data looks like
Sources include process specifications for the entire smelting workflow, daily production logs, batch quality inspection reports, and compliance documents. Update frequency: production logs are updated daily, quality inspection reports are updated when batches are completed, and annual compliance documents are finalized on a periodic basis. Most documents use fixed chapter or itemized structures, and include fields such as raw material ratios, equipment operating parameters, batch identifiers, and metal grade values. Units include tons, grams, hours, and others.
Constraints imposed by these characteristics on the document parsing and chunking process
Fixed-chapter process specifications must be split along chapter boundaries to avoid splitting combined process parameters. Itemized production logs must be split by batch or date to prevent mixing data across batches. Long-period compliance documents have large file sizes, so single chunk length must be limited to stay within model context thresholds. Documents with numeric fields such as metal grades and equipment parameters must retain context binding between fields and their associated descriptions to prevent parameters from being separated from their explanations. Frequently updated production data requires lightweight parsing workflows to avoid parsing timeouts that disrupt business handoffs.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Non-ferrous metal smelting documents contain multiple sets of associated parameters. This length retains parameter context while fitting standard model input limits |
chunkSplitter | By chapter + semantic boundaries | Process specifications and quality inspection reports mostly use fixed chapter structures. Combining chapter boundaries with semantic boundaries prevents splitting critical parameter groups |
customPdfParse | Enabled | Adapts to tabular quality inspection data in smelting documents, preserving complete table structure |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Long-period compliance documents have large file sizes, requiring sufficient parsing time to avoid timeouts |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Annual compliance documents may include multi-batch attachments, supporting large file upload requirements |
chunkSettingMode | Manual configuration | Smelting documents have significant structural differences; manual configuration allows flexible adaptation to different document types |
Three Common Misconfigurations
- Phenomenon: No response for an extended period after calling the file parsing API, with timeout errors in logs. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient for parsing large annual compliance documents. - Phenomenon: File parsing results lose tabular quality inspection data in version 4.9.0. Resolution: Switch to version 4.8.20 or enable
customPdfParseto restore functionality. Cause: The default setting for this configuration was disabled in the new version, preventing adaptation to the tabular structure of smelting documents. - Phenomenon: The file parsing tool cannot be invoked when calling the large model. Cause: File parsing permissions are not bound in the application configuration, or model tool calling configuration is not enabled.
How to Verify Proper Configuration
- Upload a typical smelting document, and check that the parsed chunk boundaries correspond to the document’s chapters, production batches, or itemized sections.
- Review parsing configuration logs to confirm that the
customPdfParseparameter is enabled, matching the tabular data requirements of smelting documents. - Test parsing for documents of different sizes, confirming that parsing duration aligns with business time requirements and no timeout exceptions are triggered.
- Validate individual chunk content, confirming that numeric fields and their associated descriptions are bound within the same chunk, with no parameter splitting or data loss.
The values provided are common starting points and should be evaluated against the user’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.