Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
Documents in this category include pollution discharge permit application forms, implementation reports, self-monitoring plans, ledger records, change applications, permit copies, and similar materials. They are generated and reviewed daily by ecological environment department pollution discharge permit management staff, environmental protection departments of polluting enterprises, and third-party environmental protection service institutions. Data sources include the national pollution discharge permit management information platform, enterprise environmental protection ledgers, online monitoring systems, and environmental statistics systems. The update frequency is quarterly. Documents cover multiple types: structured forms, semi-structured reports, and sequential ledgers. Fields include emission control requirements, monitoring indicators, ledger cycles, and more. They use standard units related to pollutant concentration and emission volume.
What constraints do these characteristics impose on document parsing and chunking
Quarterly batch updates create large document volumes, with multiple different types of pollution discharge permit documents per batch. This creates clear requirements for batch parsing stability. Document types vary significantly. Structured forms require complete field retention. Semi-structured reports need paragraph-level splitting. Sequential ledgers need entry-level chunking. A single chunking logic cannot adapt to all document types in this category. Data from multiple sources may have inconsistent formats. Parsing rules must be adjusted specifically to ensure accurate field extraction. The review process has high requirements for document content integrity. Chunking operations must avoid splitting key information. Otherwise, subsequent review efficiency and accuracy will be affected.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Pollution discharge permit documents contain long sections of implementation requirements and ledger records. This range preserves semantic completeness |
chunkSplitter | Switch based on document type | Adapts to structured chunking for application forms and paragraph chunking for implementation reports |
customPdfParse | Enabled | Adapts to the fixed layout and fixed field positions of pollution discharge permit PDFs, improving parsing accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Single batch PDF parsing takes a long time. This avoids task interruption due to timeout |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports large-volume ledgers and monitoring reports uploaded in single batches |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types to adapt to the diversity of pollution discharge permit documents |
Three Common Mistakes
- Symptom: After uploading batch pollution discharge permit PDFs, FastGPT reports a timeout. The PDF parsing service log shows parsing succeeded. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient to cover the batch document parsing cycle. - Symptom: The workflow cannot read Excel ledger content from pollution discharge permit declarations. Cause: Corresponding file parsing rules were not configured, or the custom parsing switch for non-PDF formats was not enabled.
- Symptom: Parsed pollution discharge permit document content cannot be called by the model to answer questions. Cause: Chunking parameters were set incorrectly, leading to loss of key fields due to splitting, or insufficient chunk overlap ratio leading to semantic breakage.
How to confirm the configuration is correct
- Upload a single pollution discharge permit application form PDF, and check if the parsed text contains complete application unit and permit term fields.
- Batch upload quarterly implementation reports from the same batch, and confirm that the parsing task does not interrupt midway and the parsing progress updates normally.
- Test calling the model, input a question containing emission limits, and confirm that the model returns content from the uploaded documents.
- View the file parsing log, and confirm that the
customPdfParsefunction triggers normally, with no format parsing error reports.
The values provided are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.