Data Characteristics
Medical insurance claim research and development documents include policy regulations, settlement rules, drug catalogs (e.g., national and provincial supplementary lists), diagnostic and treatment project catalogs, service facility fee standards, cost calculation formulas, and related explanatory documents and FAQs. Government agencies (National Healthcare Security Administration, provincial medical insurance departments) typically publish these documents on official websites. Updates are frequent; for example, the national medical insurance catalog usually adjusts annually, and local policies may update irregularly based on actual conditions.
Document structures are often hierarchical legal provisions, lists, and tables. They contain extensive specialized terminology, generic drug names, disease diagnosis codes (e.g., ICD-10), medical service item codes, monetary units (Yuan), and percentages (%). Most documents are PDFs, with some in Word or Excel.
Constraints on Deployment and Upgrade from Data Characteristics
The update frequency and complex structure of medical insurance claim documents impose specific deployment and upgrade requirements. High-frequency policy updates necessitate efficient version management and incremental update capabilities for the knowledge base to ensure information timeliness.
The large volume of tabular data, coding information, and calculation formulas in documents requires the structured parser to accurately identify and extract these critical entities, preventing data loss or parsing errors. Complex layouts in PDF documents can lead to incomplete text extraction or garbled characters, affecting subsequent semantic understanding and retrieval.
During upgrades, focus on the parsing module's compatibility with new document formats and ensure effective migration of historical data to maintain knowledge base continuity and accuracy. The authoritative nature of data sources requires the deployment environment to have stable external data interface access and data integrity validation.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Medical insurance policy documents often contain many images and complex layouts, leading to large file sizes. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large files and recognizing complex tables takes longer, requiring an extended timeout. |
Segment Length | 800–1200 characters | Medical insurance policy clauses are logically rigorous; longer segments help maintain semantic integrity and prevent critical information truncation. |
Recall Count | Top 5 | Medical insurance claim queries demand high accuracy; increasing the recall count improves relevance. |
Similarity Threshold | 0.75 | Medical insurance terminology includes many proper nouns; a higher threshold helps filter irrelevant results. |
maxContext | 4000 tokens | Complex medical insurance claim questions require a larger context window for reasoning. |
Common Pitfalls
- After an upgrade, some medical insurance policy queries return inaccurate results, with critical numbers or conditions missing. This occurs because the new parser incompletely recognizes tables or multi-column text in specific PDF layouts, leading to structured data extraction failure.
- After a system upgrade, the medical drug code query function becomes slow or returns 504 Gateway Timeout errors. This happens when indexes are not properly rebuilt or optimized during database migration, significantly reducing query efficiency for large drug catalog tables.
- After deploying a new FastGPT version, the logs show an
invalid version stringerror. This indicates a mismatch between the installation package version and the actual runtime environment version, or an incorrect version string format when manually configuringconfig.json.
Verification Steps
- Upload a typical medical insurance policy PDF document containing complex tables and multi-level headings. Check if the segmented content in the knowledge base is complete and if critical fields (e.g., drug names, codes, reimbursement ratios) are correctly identified.
- Test common medical insurance claim questions, such as "What is the reimbursement ratio for a specific drug under certain conditions?", through multiple rounds of queries. Evaluate the accuracy, completeness, and response speed of the answers.
- Check system logs to ensure no data parsing or integrity-related error messages, such as
PARSE_FILE_TIMEOUTordata integrity check failed, appear. - Through the FastGPT administration interface, verify that the current deployment version number matches the expected upgrade version number (e.g.,
4.8.20) and that system health indicators are normal.
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 2026-09-21.