Document Parsing and Chunking for Minor Metal Marketing Content

Sources of minor metal documents include public data from domestic minor metal industry associations, spot trading platform quotes, production

What the data for this category looks like

Sources of minor metal documents include public data from domestic minor metal industry associations, spot trading platform quotes, production enterprise technical manuals, industry research reports, and marketing materials. Update rhythms fall into three categories:

  • Spot quote data updates daily
  • Industry supply and demand research reports update monthly or quarterly
  • Marketing campaign plans and product manuals update irregularly

Document structures include three types: structured quote detail tables, semi-structured analysis reports, and plain-text marketing copy. Fields include product grades, production locations, transaction prices, inventory levels, and similar. Units are mostly tons, yuan per kilogram, yuan per ton, and similar. There is no unified fixed format template.

What constraints do these characteristics impose on the document parsing and chunking stage

The multi-format nature of minor metal documents requires the parsing process to adapt to structured tables, semi-structured reports, and plain-text materials. It must avoid splitting cross-row and cross-column table content.

Frequently updated spot quote documents require chunking logic to support fast processing of short single-page documents, while retaining associations between fields.

The frequent appearance of proprietary grades, standard numbers, and specific units requires chunking to preserve contextual coherence, preventing professional terms from being truncated.

The existence of long-text research reports requires chunk length to adapt to the information density of professional content, avoiding disruption to the complete logic of supply and demand analysis.

How to set the configurations

Configuration ItemRecommended SettingRationale
PARSE_TABLE_ENABLEEnabledMinor metal documents contain a large number of structured quote tables. Enabling this setting fully extracts table row and column content, avoiding splitting cross-row and cross-column data
chunk_size800–1200 charactersProfessional content density of minor metal research reports and marketing materials is high. This range balances contextual coherence and chunk granularity
chunk_overlap10–15%Professional terms and contextual associations must be retained, preventing fragmentation of proprietary information across chunks
PARSE_FILE_TIMEOUT_SECONDS120 secondsParsing long-text research reports requires additional time, preventing parsing failures due to timeout
split_by_separatorCombine title and paragraph separators with custom keywordsMinor metal documents contain fixed-format section titles. Combining default separators with keywords such as "grade" and "quote" improves chunking accuracy
UPLOAD_FILE_MAX_SIZE500 MBCovers upload requirements for standard marketing materials and industry research reports, adapting to parsing of some large-volume documents

The parameter values provided on this page are common recommended starting points for defining configurations. 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

  • Symptom: After uploading a minor metal spot quote Excel file, the parsing status shows failure, and the console returns 400 Bad Request. Cause: The PARSE_TABLE_ENABLE configuration is not enabled, preventing structured tables from being recognized and parsed.
  • Symptom: After uploading a long-text industry research report, the parsing status shows timeout, and the console returns 504 Gateway Timeout. Cause: The PARSE_FILE_TIMEOUT_SECONDS value is set too short, failing to adapt to the parsing time required for long-text research reports.
  • Symptom: A custom JS parsing script does not filter redundant information in marketing materials. Cause: The corresponding script is not bound in the knowledge base's post-parsing processing module, or the script does not correctly reference parsed text fields.

How to confirm configurations are correctly set

  • Upload a standard minor metal spot quote Excel file, and check if the table content in the parsing result fully retains the row and column structure without splitting or misalignment.
  • Upload a long-text industry research report, and verify that the length of chunk results falls within the preset range, with no obvious truncation of professional terms.
  • After binding a custom JS parsing script, upload a marketing material document, and check if the parsing result has completed content filtering according to the script rules.
  • View the knowledge base's parsing logs, confirm there are no 400 or 504 error codes, and that parsing time falls within the range set by PARSE_FILE_TIMEOUT_SECONDS.

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.