What the data for this category looks like
Data sources for specialized equipment intelligent due diligence reports include manufacturer factory technical documentation, on-site operation and maintenance logs, and industry regulatory filing reports. There are three update cycles:
- Factory documentation updates with equipment model iterations
- Operation and maintenance logs sync with equipment operation cycles
- Regulatory files update quarterly
Document structures include core equipment parameter tables, troubleshooting manuals, compliance certification pages, and operation record logs. Most fields are physical quantity parameters with standard units such as N·m, IP codes. Some documents also include batch serial numbers and supplier qualification attachments.
What constraints do these characteristics impose on the "document parsing and chunking" link
Core equipment parameter tables contain a large number of structured fields with standard units. Parsing must retain the binding relationship between parameters and units to avoid losing physical meaning after splitting. Operation and maintenance logs are long texts linked by timelines. Chunking must retain the complete context of single operation records to prevent breaking the logic chain of troubleshooting. Industry regulatory filing pages have fixed-format compliance certification modules. Chunking must retain page-level structural associations to avoid splitting compliance certification modules across different paragraphs. Some documents embed supplier qualification attachments. Parsing must simultaneously extract parameter data from attachments to prevent missing core information.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Specialized equipment due diligence reports often include multi-page attachment collections; 300 seconds covers the complete parsing process |
maxContext | 800–1200 characters | Specialized equipment parameters often include units; 800–1200 characters retains complete information for a single parameter table or operation record |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some due diligence reports include multiple equipment document attachments; 1000 MB covers conventional batch upload requirements |
chunk_size | 700 characters | Adapts to the structured paragraph length of specialized equipment documents, avoiding splitting compliance certification modules |
similarity_threshold | 0.75 | Filters low-relevance equipment parameter fragments, retaining core due diligence information |
RECALL_TOP_K | Top 5 entries | Matches high-frequency query scenarios for specialized equipment due diligence reports, recalling core parameters and troubleshooting content |
The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Upload a specialized equipment due diligence PDF and receive a parsing failure, with the log showing
504 Gateway Timeout. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient to parse due diligence reports that include multi-page attachments. - Phenomenon: In parsed chunking results, equipment parameters and units are separated. For example, "rated power" only retains the numerical part. Cause: The structured parameter binding function of FastGPT was not enabled. The default chunking logic splits the association between parameters and units.
- Phenomenon: After connecting a custom PDF parsing service, uploading files has no response. Cause: The interface address of the custom parsing service was not configured in the FastGPT backend, or the corresponding port permissions were not opened.
How to confirm the configuration is correct
- Upload a standard-format factory technical document for specialized equipment, view the parsed chunk list, and confirm that parameters and units are not split.
- Enter the FastGPT file parsing configuration page, check that the value of
PARSE_FILE_TIMEOUT_SECONDSmatches the average parsing duration of the current due diligence report. - Trigger a test request for the custom parsing service, confirm that the chunk data format returned by the interface matches the field structure required by FastGPT.
- Adjust the
similarity_thresholdparameter, query the recall results of the test document, and confirm that low-relevance fragments have been filtered.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.