Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
The data for coal-electric integration party building learning Q&A comes from internal materials archived by the enterprise’s party and mass work department. These materials include original superior party building policy documents, branch study courseware, party lesson meeting minutes, and special study compilations. Update frequency is adjusted based on needs. Updates happen immediately when superior authorities deploy new study tasks. Daily supplements add new study materials once per month. Supported document formats include PDF, Word, TXT, and PPT. Some materials are scanned documents with embedded images. Most content follows a chapter and paragraph structure. It includes fixed document numbers, issuing units, and main text. There is no unified standardized field format.
What constraints do these characteristics impose on the "document parsing and chunking" link
Mixed multi-format documents require the parsing engine to support multiple file types. Scanned documents and embedded images require additional OCR support. On-demand update requirements mean parsing tools must support batch uploads and scheduled synchronization tasks. This prevents backlogs of temporary tasks. Long text and chapter-based structures require retaining semantic boundaries during chunking. This avoids retrieval errors caused by cross-chapter splicing. Non-standardized field formats require the parsing engine to automatically identify main text content. It also filters redundant format markers and issuing metadata.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Coal-electric integration party building documents are mostly long-text policies and study materials. This range preserves semantic completeness for single chunk content |
chunkSplitter | Split by paragraph + title | Party building documents are organized by chapters and paragraphs. Following this splitting rule ensures chunked content has independent semantics, enabling accurate retrieval |
customPdfParse | Enable OCR mode | Some party building documents are scanned documents or PDFs with embedded images. Enabling this mode extracts text content from images |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large party building study compilation files takes a long time. This duration prevents mid-parsing interruptions for large files |
chunkSettingMode | Manual configuration | Adjusting chunk parameters for the long-text characteristics of coal-electric party building documents requires manual configuration to adapt to specific scenarios |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts to batch uploads of large party building study compilation files, preventing parsing failures due to oversized files |
Three common mistakes
- Uploading non-standard format documents with modified file extensions, such as renaming code documents to TXT to mix into party building materials, results in no valid content after parsing. Reason: FastGPT document parsing relies on native file format recognition. Modifying the file extension does not change the actual encoding and structure of the file. This causes the parsing engine to fail to match the correct parsing rules.
- After batch uploading large party building study compilation files, the interface displays "indexing" for a long time. Reason: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient to complete large file parsing and chunking. This causes the task to hang. - After uploading a PDF party building courseware with embedded images, the text within the images is not included in the chunked content. Reason: The OCR mode of
customPdfParsewas not enabled. Only text extraction logic is used, which cannot recognize text embedded in images.
How to confirm the configuration is correct
- Upload a typical coal-electric party building document. Check the parsed chunked results to confirm that chunk boundaries align with the document’s chapters and paragraphs.
- Check the parsing task logs. Confirm that no timeout errors occur, and that parsing duration meets expectations.
- Upload a PDF document with embedded images. Confirm that text within the images is correctly extracted and included in the chunked content.
- Use chunk mode to call the pushdata API to upload a test document. Confirm that the task completes indexing within a reasonable time frame, with no long-term hanging status.
The values provided are common starting points and should be measured against the relevant 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.