What the data for this category looks like
Agrochemical product data comes from multiple sources, including agricultural regulatory agency pesticide registration announcements, industry association monthly supply and demand reports, listed companies’ annual reports, raw pesticide price weekly reports, field test datasets, and more. Document types include official PDFs with digital signatures, encrypted or unencrypted DOCX/XLSX spreadsheet files, and plain text industry briefings. Update frequencies vary widely: registration announcements are released irregularly, price weekly reports are updated weekly, industry reports are mostly released monthly or quarterly, and annual reports are updated annually. Document structures include standardized fields, such as active ingredient content (units: g/L, %), production capacity (units: 10,000 tons/year), application rate per hectare (units: g/ha), product price (units: yuan/ton). These documents often contain complex multi-row and multi-column data tables.
What constraints do these characteristics impose on document parsing and chunking
The characteristics of agrochemical data sources impose multiple constraints on document parsing and chunking. Irregularly released official registration announcements and frequently updated price weekly reports require parsing tools to support both short text rapid processing and long document batch parsing. A high proportion of official documents with digital signatures require parsing configurations to support reading content from signed files. Otherwise, core fields such as registration certificate numbers and active ingredients cannot be extracted. Documents contain a large number of multi-row and multi-column tables for production capacity, price, and supply and demand balance, along with specialized units. Parsing processes must retain structured table information and the binding relationship between fields and units to avoid breaking data logic after chunking. Mixed format upload requirements require parsing configurations to support multiple file types including PDF, DOCX, XLSX, while filtering unsupported file formats.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxChunkSize | 800–1200 characters | Agrochemical industry documents contain a large number of technical terms and long tables. This range preserves contextual connections while avoiding overloading single chunks |
chunkOverlap | 150–200 characters | Technical terms and cross-paragraph industry logic require contextual continuity to prevent logic breaks caused by chunking |
enableTableParse | Enabled | Agrochemical documents contain a large number of production capacity, price, supply and demand balance tables. Retaining structured formats prevents loss of specialized data |
PARSE_DOCX_SUPPORT_SIGNED | Enabled | Official industry registration announcements in the agrochemical sector are mostly DOCX/PDF files with digital signatures. Parsing of signed file content must be supported |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large industry reports (over 100 pages) take a long time to parse. 300 seconds covers conventional batch parsing needs |
UPLOAD_FILE_MAX_SIZE | 500 MB | Batch collections of industry reports in the agrochemical sector have large file sizes. Large file upload parsing must be supported |
The parameter values provided on this page are common starting points for configuration. Actual values depend on material form, data volume, and business rules. Each case requires individual analysis. It is recommended to test on in-house samples before finalizing settings.
Three common mistakes
- When using the Doc2x tool in FastGPT V4.9.1 or later, an error like
Only support .txt, .md, .pdfmay be returned. The cause is that the uploaded file format is not in the allowed list, or the file extension does not match the actual content. - Parsing results for uploaded PDF files with digital signatures are empty. The cause is that signed file parsing configuration is not enabled. The tool cannot bypass signature verification to read document content.
- Fields and units separate after parsing complex business tables, or table structures split into chaotic text. The cause is that table structured parsing configuration is not enabled. Using plain text chunking alone leads to loss of specialized data.
How to confirm correct configuration
- Upload one official pesticide registration announcement PDF with a digital signature. Check if the parsing result contains complete core fields such as registration certificate number and active ingredients.
- Upload one industry report DOCX containing a supply and demand balance table. Check if the parsing result retains the table's row and column structure and unit information.
- Upload one industry report with more than 50 pages. Check if the parsing task completes within the preset timeout period without timeout errors.
- Call the knowledge base interface to test chunking results. Check if the overlapping character count of long text chunks matches the preset configuration.
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.