What this category of data looks like
Biologics investment research data primarily comes from public clinical trial databases, official regulatory agency approvals, R&D enterprise pipeline announcements, academic journal papers, and industry guideline documents. Update cadence varies with business milestones: clinical trial data updates with enrollment, interim analysis, and conclusion milestones. Regulatory approvals are released alongside approval progress. Enterprise announcements have no fixed publication schedule. Data structure includes structured tables such as subject enrollment data and potency test results, and unstructured text such as trial protocols and R&D progress descriptions. Professional fields and units include IU, mg/mL, number of subjects, trial phases, and more.
What constraints these characteristics impose on deployment and upgrade
The multi-source, heterogeneous nature of biologics investment research data requires the deployment phase to adapt to access protocols for different data sources, and support mixed parsing of structured tables and unstructured documents. Data sources with no fixed update cycle require the upgrade phase to allow flexible configuration of incremental sync scheduling rules, to accommodate sudden updates to approvals or announcements. The diversity of professional fields and units requires support for custom field mapping during deployment, to avoid loss of critical investment research information after parsing. The increasing proportion of long document content requires optimization of the vector storage index structure during upgrades, to accommodate storage of longer text segments.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Biologics investment research documents include multi-page clinical reports, pipeline ledgers, and similar materials. Single file size is typically larger than general use cases |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Parsing long clinical reports requires significant processing time. This setting prevents interruptions during parsing of large documents |
Segment Length | 800–1200 characters | Biologics documents contain professional terminology and long sentences. Excessively long segments reduce retrieval accuracy, while excessively short segments break contextual relevance |
Similarity Threshold | 0.75–0.85 | Precise matching of professional terminology and trial data is required. A threshold that is too low may introduce irrelevant results, while a threshold that is too high leads to insufficient retrieval |
Incremental Sync Interval | Every 6 hours | Updates for regulatory approvals, enterprise R&D announcements, and similar content have no fixed schedule. Adjust the sync frequency as needed to align with data update patterns |
Number of Retrieved Results | Top 8–12 results | Investment research decisions require coverage of multi-dimensional trial data and pipeline information. Too many results increase filtering costs, while too few results may miss critical information |
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 specific analysis. It is recommended to perform testing using samples relevant to the actual deployment before finalizing settings.
Three Common Mistakes
- Issue: Service fails to start after running
docker-compose up, and the frontend page remains in a loading state. Cause:UPLOAD_FILE_MAX_SIZEand local storage mount path are not configured correctly, causing blocking during the file upload phase. - Issue: The number of knowledge base retrieval results does not match the configured
Number of Retrieved Results. Cause: The vector database index has not been updated synchronously, or theSimilarity Thresholdis set outside a reasonable range, resulting in excessive filtering of results. - Issue: The locally deployed open-source knowledge base has a limit of 30 knowledge bases. Cause: The open-source
MAX_KNOWLEDGE_BASE_COUNTparameter has not been modified, and the default limit is 30 knowledge bases.
How to Confirm Configuration is Correct
- Upload a typical biologics clinical report PDF, verify that the parsed text retains professional fields and units, and confirm that parsing time does not exceed the configured
PARSE_FILE_TIMEOUT_SECONDS. - Run a test query related to investment research, confirm that the number of returned results matches the configured
Number of Retrieved Results, and that result similarity aligns with the presetSimilarity Threshold. - Configure an incremental sync task and trigger it manually, confirm that newly uploaded pipeline data or approval documents are automatically added to the knowledge base index.
- View service runtime logs, confirm there are no timeout or permission errors during file upload or parsing.
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.