Document Parsing and Chunking for Integrated Services

What the data for this category looks like

Data sources for integrated services investment research cover multiple channels including public brokerage research reports, industry databases, listed company periodic announcements, regulatory policy documents, and more. Data update rhythm adjusts dynamically with source document releases: brokerage research reports go live in real time, while announcements and regulatory files update per disclosure timelines. Document structures include long-form text analyses, structured statistical tables, embedded charts and formulas. Fields cover issuing institutions, release dates, ratings, target prices, revenue data, and more. Units include RMB yuan, percentage, 100 million yuan market capitalization, and others. Some documents integrate multi-source data fragments, with relatively high structural complexity.

What constraints do these characteristics impose on the document parsing and chunking link

Multi-source heterogeneous document structures require the parsing step to adapt to plain text, tables, charts and other formats simultaneously, to avoid losing structured information. High-frequency updated data sources require the chunking process to support incremental parsing, reducing repeated processing overhead. The diversity of fields and units requires retaining original association relationships during chunking, and statistical content spanning multiple fields cannot be split arbitrarily. In scenarios where long documents account for a large proportion, chunk length needs to balance information integrity and retrieval efficiency, avoiding overloaded or overly fragmented single chunks.

Configuration settings

Configuration Item	Recommended Value	Rationale
`chunk_size`	800–1200 characters	Adapts to the single-paragraph information density of integrated services investment research documents, balancing content integrity and retrieval accuracy
`chunk_overlap`	50–80 characters	Retains contextual association between chunks, avoiding breaks in cross-chunk logical analysis
`enable_table_parse`	Enabled	Integrated services investment research documents contain large numbers of structured revenue and position tables, requiring retention of original field and unit information
`max_table_chunk_chars`	1500–2000 characters	Adapts to the field count and unit complexity of table data, avoiding reduced retrieval accuracy caused by overly long single-table chunks
`parse_timeout`	120 seconds	Addresses parsing time for multi-source integrated long documents, avoiding task interruption due to mid-task timeout
`enable_chart_text_extract`	Enabled	Some investment research documents include chart annotation text, requiring extraction to supplement chunk information dimensions

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.

Three common mistakes

When calling the document parsing API of FastGPT 4.8.10, the returned chunk data does not include the chunk_index field. The cause is that the chunk index generation configuration is not enabled, so the parsing process does not generate the associated identifier.
When clicking the copy button for knowledge base chunk content, a prompt pops up saying "Unable to use browser automatic copy, please manually copy the following content". The cause is that there are cross-domain restrictions in the deployment environment, and the source site allowed for copy operations is not configured.
When parsing investment research documents containing embedded charts, the annotation text of the charts is not extracted into the chunk content. The cause is that the enable_chart_text_extract configuration is not enabled, so the parsing process ignores non-text embedded elements.

How to confirm the configuration is correctly set

Upload a comprehensive service investment research document containing structured tables, enter the knowledge base management interface to view the parsed chunk list, and confirm that the table content is completely split and the original field associations are retained.
Call the FastGPT document parsing API, check whether the returned chunk data includes the chunk_index field, and confirm that the index configuration has taken effect.
Adjust the parse_timeout configuration, upload a single investment research document with more than 100 pages, and confirm that the parsing task does not time out and fail.
Test the function of copying chunk content, and confirm that the pop-up prompt matches the cross-domain configuration of the deployment environment.

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.