What data for this category looks like
General equipment investment research data comes from manufacturer product manuals, industry association operation data bulletins, listed company periodic reports, patent application documents, and tender announcements. Update rhythms vary significantly: product manuals are updated irregularly with model iterations, industry bulletins are released quarterly, listed company reports are updated annually or semi-annually, and tender announcements are released in real time.
Document structures include structured technical parameter tables, long market analysis texts, scanned equipment disassembled drawings, and performance indicator pages with clear units. Fields and units include rated power (kW), daily production capacity (units/day), operating noise (dB(A)), service life (hours), and more. Some documents mix multiple sets of parameters for the same model of equipment and corresponding technical descriptions.
What constraints do these characteristics impose on document parsing and chunking
General equipment investment research data contains a large number of structured parameter tables with units. The parsing link must accurately match fields and units to avoid parameter misalignment or unit loss. A notable share of scanned equipment drawings and announcement documents requires adaptation to OCR recognition processes, and handling of typesetting offset issues after recognition.
Update rhythms of different data sources differ greatly. The text length and structural complexity of real-time tender announcements and quarterly industry reports vary, so flexible chunking rules must be supported. Mixed technical parameters and analysis texts require chunking to retain content relevance for the same equipment model, and avoid cross-model or cross-parameter group content mixing, which would reduce the accuracy of subsequent investment research retrieval.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_OCR_ENABLE | Set to true when scanned documents account for ≥20% | General equipment documents often include scanned drawings and announcements, so OCR must be enabled to recognize non-text content |
PARSE_TABLE_EXTRACT_MODE | Merge cells + retain original units | General equipment parameter tables often have nested cells and units, so the corresponding relationship between fields and units must be fully retained |
CHUNK_SIZE | 800–1200 characters | Balance the completeness of technical parameters and the semantic coherence of analysis texts, and adapt to the chunking needs of mixed content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Single general equipment documents (such as large product manuals) have large file sizes, so the timeout threshold must be extended to avoid parsing interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapt to the upload needs of large equipment manuals and drawing documents, and avoid triggering file size limit errors |
RECALL_CHUNK_TOP_N | Top 6–8 entries | Investment research scenarios need to balance parameter accuracy and analysis breadth, and avoid recalling too much redundant content |
The parameter values provided on this page are all conventional recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: A
413 Request Entity Too Largeerror is returned when uploading large equipment manuals or drawings. Cause: TheUPLOAD_FILE_MAX_SIZEconfiguration is not adjusted, and the large file size characteristic of single general equipment documents is not adapted. - Phenomenon: Technical parameters are missing or units are lost after parsing some PDF documents. Cause: The unit retention mode of
PARSE_TABLE_EXTRACT_MODEis not enabled, so structured parameters with units in general equipment documents cannot be recognized. - Phenomenon: Performance parameters and corresponding market analysis of the same equipment model are split into different chunks in the chunking result. Cause:
CHUNK_SIZEis set too short, which destroys the semantic relevance of the same type of content.
How to confirm correct configuration
- Upload 1 to 2 typical general equipment documents, such as product manuals and industry reports, and check whether parsed structured parameters fully retain fields and units.
- Test documents in different formats, including scanned PDFs, Word documents with tables, and parameter Excel tables, and confirm that OCR and table extraction functions take effect according to the configured settings.
- Review chunking results, verify that parameters and analysis texts of the same equipment model are not split across chunks, and ensure complete content relevance.
- Upload large-volume documents, and confirm that the parsing process does not trigger timeout or file size limit errors.
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.