What this category's data looks like
Typically, core documents and data for mobile development include end-version release notes, adaptation checklists, crash analysis reports, app store materials, and similar items. Data sources cover code repositories, app store backends, crash monitoring platforms, and device coverage data platforms. Update cycles follow daily synchronization or per-version iteration. Most document structures include structured fields: for example, device models and system versions in adaptation checklists, permission configuration items, version numbers, update nodes, and review status in version release notes. Some documents embed code snippets and rich text content.
What constraints these characteristics impose on document parsing and chunking
Mobile development documents have diverse types and significant structural differences. Code documents follow syntax rules different from plain text. They require targeted identification of units such as API declarations and code blocks. Without this, parsed content will be invalid. Data update frequency is high. A single document may contain associated information for multiple devices and versions. Chunking must retain contextual connections to ensure retrieval accuracy. Some documents embed images or non-standard format files. Failure to adapt parsing rules will lead to loss of key content. Some teams have large device data files. Parsing must adapt to time and capacity limits for large file uploads and processing.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Mobile development documents often contain code snippets and multi-dimensional parameters. Oversized chunks will lose contextual connections, while undersized chunks will increase retrieval overhead. This range balances semantic completeness and retrieval efficiency, and adapts to the default embedding model processing capability of FastGPT v4.17.0 |
chunkSplitter | Split by code blocks and headings | Mobile development documents take API declarations and adaptation rules as core semantic units. Splitting by code blocks and headings retains complete business logic and configuration associations, and avoids splitting that separates key information |
customPdfParse | Enable | Mobile app store materials and crash reports are often submitted in PDF format. Enabling custom parsing retains text hierarchy and code block structure, and resolves issues where default parsing ignores embedded code and structured content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | A single version release note or adaptation checklist may include configuration information for dozens of devices. Parsing takes a long time. This duration covers processing requirements for most large-volume documents, and prevents parsing interruptions due to timeout |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Device coverage data files for cross-platform development teams may include multiple batches of device parameters. This upper limit adapts to most teams' file upload requirements, and meets basic conditions for batch data parsing |
chunkSettingMode | Manual configuration | Mobile development documents have significant structural differences. Manual configuration allows flexible adjustment of chunking rules, and adapts to parsing requirements for different types of documents such as API files and adaptation checklists |
Three common mistakes
- Upload a Java interface file with a renamed .txt file extension, and the parsed result contains no valid interface information. Cause: Default text parsing fails to recognize Java interface syntax structures, and cannot extract core content such as interface methods and parameter lists.
- Use chunk mode to call the pushdata API to upload documents, and the index in progress status displays for a long time. Cause: The
chunkSizesetting is too large, causing chunk processing to time out, or thePARSE_FILE_TIMEOUT_SECONDSconfiguration value is lower than actual parsing time. - Upload a PDF document containing code screenshots or app store promotional images, and the parsed result does not include structured text related to the images. Cause: The
customPdfParseconfiguration is not enabled. Default PDF parsing ignores embedded text content from non-standard format images.
How to confirm configurations are set correctly
- Upload a single simplified Java interface file, check if the parsed result includes core content such as interface declarations and parameter lists, and confirm that chunks do not separate semantic connections.
- Upload a device coverage data test file of around 500 MB, check if upload and parsing progress completes within the
PARSE_FILE_TIMEOUT_SECONDSconfigured duration. - Enable
customPdfParse, then upload a PDF document containing code blocks, confirm that the parsed result retains code block indentation and syntax-related text structures. - Call the pushdata API in chunk mode to upload a test document, wait for indexing to complete, then search for keywords, and confirm that returned results match expected chunked content.
The values listed above are common starting points. Adjustments should be made based on local sample data and testing.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.