What this type of data looks like
Expense list data is sourced from the medical settlement systems of designated medical institutions, reimbursement ledgers of medical insurance handling agencies, or scanned paper documents uploaded by claim applicants. Each document maps to one claim application. Updates trigger when a claim is submitted, and complete after OCR or structured extraction finishes. Most documents are structured tables, with fields including treatment item name, unit price, quantity, total price, medical insurance reimbursement ratio, out-of-pocket amount, treatment date, treatment department, hospital name, and medical insurance project code. Unit price and total price use Chinese Yuan (CNY) as the unit. Quantity units include times, days, or pieces.
Constraints on Deployment and Upgrade from These Characteristics
The multi-source input, structured field requirements, and regional coding differences of expense lists create three core constraints for deployment and upgrade. First, support for multiple input formats such as spreadsheets and scanned documents is required. A general parsing template and custom configuration entry must be pre-configured during deployment. Second, concentrated submission of claim applications generates parsing concurrency. Queue current-limiting parameters must be configured to prevent service overload. Third, medical insurance coding rules vary across regions. The regional field mapping library must be updated synchronously during upgrades to ensure field matching accuracy. Additionally, document formats are updated as medical institutions iterate, so a pluggable interface for template upgrades must be reserved.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Expense lists include dozens of treatment items. OCR and structured parsing take a long time. 300 seconds covers the parsing process for most standard documents. |
UPLOAD_FILE_MAX_SIZE | 20 MB | The size of a single expense list scan or spreadsheet typically does not exceed 20 MB. Exceeding the threshold causes upload failures. |
RERANK_TOP_N | Top 8 entries | The medical insurance codes and project names that expense lists need to match are relatively fixed. Recalling the top 8 entries covers core matching items and avoids redundant calculations. |
PARSE_STRUCTURED_FIELDS | ["Treatment Item Name","Unit Price","Total Price","Medical Insurance Code"] | Claim initial review relies heavily on the above fields. Prioritizing structured extraction improves parsing efficiency and matching accuracy. |
QUEUE_CONCURRENT_LIMIT | 15 concurrent requests | The concurrency volume of a single batch of claim submissions is usually controllable. 15 concurrent requests balances service resource usage and parsing speed. |
RERANK_MODEL_AUTH_TOKEN | Custom secure credential string | Authenticating access to a locally deployed rerank model requires configuring identity verification via this parameter to prevent unauthorized access. |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: After local deployment of a rerank model, the platform displays authentication failure or model not loaded notification. Cause: The
RERANK_MODEL_AUTH_TOKENparameter is not configured correctly, or the credential lacks the required prefix per model specifications. - Phenomenon: A docker-compose-deployed rerank model does not appear in the platform configuration page options. Cause: The rerank service port is not exposed to the same internal network segment as the FastGPT service, or the correct model access address is not provided.
- Phenomenon: A specific version of parsing rules is configured, but actual parsing results use legacy logic. Cause: The platform’s parsing template cache has not been cleared, or the configuration item does not override the global parsing rule priority setting.
How to Verify Successful Configuration
- Upload a locally saved expense list scan or spreadsheet, review parsing results for extracted core fields, and verify accuracy of fields including Treatment Item Name, Unit Price, and Total Price.
- Access the model configuration page, confirm the rerank model appears in the optional list, click test connection, and validate return of normal matching results.
- Submit a simulated claim application, review parsing queue running logs, confirm parsing tasks do not time out and concurrency aligns with configured requirements.
- Access the offline deployed shared service link, confirm no redirection to the FastGPT login page occurs, verifying port isolation configuration is active.
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.