Document Parsing and Chunking for Industrial Metals Financing Daily Reports

Data sources include daily public reports from domestic nonferrous metals industry associations, the Shanghai Futures Exchange, and the London Metal

What the Data for This Category Looks Like

Data sources include daily public reports from domestic nonferrous metals industry associations, the Shanghai Futures Exchange, and the London Metal Exchange, plus aggregated daily financing ledgers from traders. Updates run each midnight, pushing full data for the previous day. Common document formats include Excel spreadsheets, PDF structured reports, and plain text summaries. The overall structure splits sections by product segments such as copper, aluminum, zinc. Each section includes fields like product name, financing balance, daily change amount, corresponding spot benchmark price, and total warehouse inventory. Financing balance uses 100 million yuan as its unit, daily change amount uses 10,000 yuan, and total inventory uses tons.

Constraints for Document Parsing and Chunking

Cross-source document format differences require parsing workflows to support multiple file types. This avoids data loss from format incompatibility. Daily update timeliness requires parsing and chunking processes to match the T+1 update schedule. Single-file parsing time must stay within acceptable limits. The structured layout split by product segments requires chunking to use product as the core dimension. This prevents mixing data across different products. Multiple unit numeric fields require parsing processes to retain original unit identifiers. Unit information must not be lost during chunking. Anomaly description paragraphs usually follow the corresponding product’s table. These paragraphs must bind to their table and cannot be split into chunks for other products.

Configuration Settings

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS600 secondsMatches the maximum parsing time limit for a single industrial metals financing daily report, to avoid timeouts triggered by file size or format complexity
Segment Length800–1200 charactersMatches the total length of a single product segment’s financing data table plus its corresponding anomaly description, to avoid splitting cross-product data into the same chunk
chunk_overlap100–150 charactersRetains contextual association between adjacent chunks, ensuring the binding relationship between product fields and corresponding anomaly descriptions
UPLOAD_FILE_MAX_SIZE100 MBMatches the typical size of a single daily report original file or compressed package, to avoid upload failures
PARSE_ENABLE_STRUCTUREDEnabledAdapts to the structured table format in the daily report, retaining original field and unit information
Similarity Threshold0.75Filters repeated industry-general expressions, retaining financing data details specific to the industrial metals category

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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

  • After upgrading FastGPT, uploading an industrial metals financing daily report CSV file triggers a 413 Request Entity Too Large error. The cause is that the default UPLOAD_FILE_MAX_SIZE parameter in the new version is reset to a low default value, which does not adapt to the file size of industrial metals daily reports.
  • After parsing, chunks lose unit information, with only numeric values retained without unit identifiers. The cause is that the PARSE_ENABLE_STRUCTURED configuration is not enabled, resulting in the discarding of structured table metadata.
  • When calling a custom node, passing the original file results in the large model returning that it cannot recognize the file content. The cause is that the default parsing process is not turned off, and the original file is directly passed into the large model context.

How to Verify the Configuration Is Correct

  • Upload a test industrial metals financing daily report file, review the field integrity in the parsing result, and confirm whether the configured PARSE_ENABLE_STRUCTURED takes effect as expected.
  • Randomly select a chunk, verify that it contains the complete product name, numeric value, and corresponding unit, and confirm that the values of Segment Length and chunk_overlap adapt to the current data structure.
  • Upload a test file that exceeds the typical size, check the interface prompt or backend log, and verify that the UPLOAD_FILE_MAX_SIZE configuration is correct.
  • Pass the original file in a custom node, confirm that the large model can directly read the file content, and verify that the default parsing process is turned off.

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.