What this category of data looks like
Daily documents for this category include request registration forms, dispatch records, handling responses, follow-up visit records, extension applications, return explanations, and knowledge base entries. Data sources include the 12345 citizen hotline platform, business systems of handling units, knowledge bases, follow-up evaluation data, and local hotline management measures. Data updates occur daily. Most documents contain fixed business fields and free-form text content. Some documents come from cross-system heterogeneous formats, covering both structured forms and unstructured text. The content length of individual documents varies widely.
What constraints these characteristics impose on the document parsing and chunking link
Since data sources include cross-system heterogeneous formats, the document parsing link must adapt to different file types and field extraction rules. This avoids losing key business information. Daily updated batch ticket data requires the parsing and chunking process to have high processing efficiency. This prevents delays in ticket closed-loop handling. The mixed structure of fixed fields and free text in documents requires chunking rules to retain the logical association between fields and their corresponding content. Otherwise, this will affect the accuracy of subsequent request type judgment and response generation links. At the same time, time limit requirements for ticket handling mean the parsing and chunking process cannot have excessively long timeouts. This may otherwise cause issues such as overdue tickets.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the typical length of request content and response text in 12345 hotline ticket documents. It retains contextual association while avoiding overly long single chunks that harm retrieval efficiency. |
chunkSplitter | Paragraph + semantic splitting | Matches the structure of ticket documents divided by processing stages. It retains the logical association between requests and corresponding responses, extension applications, and other content. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing needs of batch ticket documents with multiple attachments. It reserves sufficient time for format conversion and field extraction, avoiding ticket processing interruptions caused by timeouts. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports handling units uploading large-volume historical ticket batch files. It meets business requirements for batch import and parsing. |
chunkSettingMode | Custom mode | Adapts to differences in document structures across different types of tickets, such as inquiry and complaint. It allows flexible adjustment of chunking rules and field extraction logic. |
customPdfParse | Enabled | Accurately extracts fixed form fields from ticket PDF documents, avoiding loss of structured information. |
Three common mistakes
- Phenomenon: A
net::ERR_INCOMPLETE_CHUNKED_ENCODINGerror occurs when uploading ticket attachments, and page loading is interrupted. Cause: TheUPLOAD_FILE_MAX_SIZEconfiguration was not adjusted. The current configuration cannot support large-volume ticket attachment files. - Phenomenon: When retrieving ticket-related documents, key request content is split across multiple chunks. Cause: The
chunkSplitterconfiguration only uses fixed character splitting, without combining semantic and paragraph division. This destroys the logical association between requests and responses. - Phenomenon: Calling the API fails to retrieve chunk index content, and the returned result is empty. Cause: The index generation configuration was not enabled in
chunkSettingMode, or the FastGPT version in use does not support the corresponding parameter settings.
How to confirm the configuration is correct
- Upload a standard request registration form document, check the parsed chunk list, confirm that the chunk length falls within the preset
chunkSizerange. - Upload batch ticket files within 1000 MB, test the upload and parsing process, confirm there are no timeout or upload failure errors.
- Call the FastGPT document parsing API, verify that the returned result includes chunk index fields and corresponding chunk content.
- Adjust the
chunkSplitterconfiguration to only use character splitting, compare the parsing results, confirm that semantic splitting better retains the logical association of ticket documents.
The values given are common starting points and should be measured 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.