What the data for this category looks like
Data for professional services investment research knowledge bases primarily comes from public industry research reports, regulatory policy documents, periodic financial reports of listed companies, and third-party survey data. Update rhythms are irregular: research reports are updated daily as institutions release them, financial reports receive concentrated updates quarterly or annually, and regulatory files are pushed irregularly when policies are issued. Single documents are long texts containing nested tables, charts, and technical terminology. Fixed fields include issuing institution, release date, rating, target price, and others. Target price uses currency units, and ratings use standardized terminology.
What constraints these characteristics impose on deployment and upgrade
Long texts and nested structures require the parsing pipeline to adapt to complex layouts without losing core information, so parsing timeout parameters must be adjusted during deployment. Frequent, irregular update requirements require configuring customizable scheduled sync tasks to adapt to the update rhythms of different data sources. Metadata needs for multiple fixed fields require enabling metadata extraction during deployment to ensure the knowledge base can be searched by dimensions such as issuing institution and rating. During version upgrades, existing long document parsing rules must be compatible to avoid formatting errors in previously imported research reports.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600-900 seconds | Professional services investment research documents are mostly long texts with nested charts, so parsing takes significantly longer than general documents |
UPLOAD_FILE_MAX_SIZE | 500-1000 MB | Single research report collections or financial report collections have large file sizes, so upload limits need to be expanded |
chunkSize | 800-1200 characters | Investment research documents have a high proportion of long sentences, so segment length needs to balance contextual completeness and retrieval accuracy |
recallTopK | Top 8-12 results | Investment research data is highly professional, so enough relevant fragments need to be returned to support professional conclusions |
similarityThreshold | 0.75-0.85 | Filter low-correlation industry data and retain high-match core content |
scheduleCron | 0 2 * * * | Adapt to the daily update rhythm of most research reports, run sync tasks in the early morning |
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 case-by-case analysis, and testing on local samples is recommended before finalizing settings.
Three common mistakes
- Symptom: After adding a model for local deployment, testing returns
403 status code (no body). Cause: API key permissions for model calls or system cross-domain whitelists are not configured correctly. - Symptom: Database connection fails for Docker deployment, with a prompt indicating account and password verification failure. Cause:
MONGO_INITDB_ROOT_USERNAMEandMONGO_INITDB_ROOT_PASSWORDare not correctly set in environment variables. - Symptom: Cannot find the system upgrade entry or confirm the current latest version. Cause: The official version update source is not bound, or the version auto-detection function is not enabled in system settings.
How to confirm the configuration is complete
- Upload a typical industry research report, check if the parsed text fully retains nested tables, issuing institution, target price and other metadata.
- Manually trigger a scheduled sync task, check if the knowledge base has added data sources from the corresponding update cycle.
- Call the retrieval test interface to verify that the number of returned recall results and similarity match the configured value range.
- View system operation logs to confirm there are no error messages in database connection, document parsing and model call links.
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.