What the data for this category looks like
Financial report data for decoration enterprises comes from publicly disclosed annual and quarterly reports, internal project ledgers, and supply chain procurement data. There are three update cycles: monthly operating data is updated in real time; quarterly financial reports are updated within 15 days after the end of each quarter; annual financial reports are officially released by April of the following year. Each financial report document includes project details, cost categories, revenue composition, cash flow data and other content. The fields cover project number, project address, contract amount, actual expenditure, and completion progress. Their units are no unit, square meters, ten thousand yuan, ten thousand yuan, and days respectively.
What constraints do these characteristics impose on deployment and upgrade
Decoration industry financial reports have many detailed entries, wide variation in single-document length, and frequently updated monthly operating data. These create multiple constraints for the deployment and upgrade process. First, frequently written detailed data increases disk IO pressure. Storage and concurrency configurations must be planned in advance. Second, there are many custom fields. Field mapping configurations must be completed during deployment, and old version mapping rules must be compatible during upgrades. Third, some enterprises use arm64 architecture servers. Images adapted for this architecture must be used to avoid deployment failures.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single decoration industry financial report documents (including project details) usually do not exceed 800 MB. This value covers most scenarios and avoids parsing timeouts |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Financial report documents for large decoration projects include multi-page details. The parsing process takes a long time. The default value is often insufficient to complete full parsing |
VECTOR_INSERT_BATCH_SIZE | 50–100 | Decoration industry financial reports have many detailed entries. This batch size balances write efficiency and disk IO pressure, avoiding read/write overload caused by high concurrency |
maxContext | 8000–12000 characters | The context length of financial report documents is long. This value covers complete project cost and revenue information, ensuring accurate analysis results |
RECALL_TOP_K | Top 10 entries | Decoration industry financial reports have many associated projects. This number of recalled entries provides sufficient associated information for financial report analysis |
MILVUS_INDEX_DIM | 1536 | The output dimension of general text embedding models is 1536, which meets the embedding requirements of text fields in decoration industry financial reports |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: High and sustained disk IO load after Docker deployment. Read/write volume exceeds reasonable limits within a single day, eventually leading to hard drive failure. Cause:
VECTOR_INSERT_BATCH_SIZEandUPLOAD_FILE_MAX_SIZEwere not adjusted, and batch write concurrency was not limited. This leads to frequent disk write operations triggered by detailed data from decoration industry financial reports. - Symptom: Error "pgvector connection failed" when starting the Milvus container, interrupting the deployment process. Cause: pgvector configuration parameters were incorrectly written to the Milvus compose file. Connection parameters between the vector database and metadata database were not properly configured, mixing deployment configurations for different databases.
- Symptom: Container startup failure on arm64 architecture servers, with the error "exec format error". Cause: The official arm64 architecture image was not used. The amd64 architecture image was pulled directly, leading to architecture incompatibility.
How to confirm that configurations are correctly set
- Upload a typical decoration industry project financial report document. Check that the parsed text fields fully include custom fields such as project number and contract amount, confirming that the field mapping configuration is effective.
- Run a batch import test task. Check disk IO monitoring metrics, confirming that the write rate meets business requirements and no overload occurs.
- Start the Milvus container and check logs. Confirm that the connection parameters between the vector database and metadata database are correct, with no database connection errors.
- Pull the corresponding image and start the container on an arm64 architecture server. Confirm that there are no architecture incompatibility startup errors.
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.