What the data for this category looks like
Data sources for commercial real estate research reports include public industry research results, regional commercial monitoring datasets, and operational archives of existing commercial properties. Updates follow two schedules: quarterly full-industry research reports, and monthly key business district monitoring briefings. Individual documents vary widely in length, ranging from thousands of words for business district dynamic briefings to tens of thousands of words for project feasibility studies. Core fields include business district name, rental price per unit area, customer profile, and investment return calculation values. Units include yuan per square meter per day, square meters, number of visitors, and others. Some documents include structured business format proportion tables and location coordinate data.
What constraints these characteristics impose on deployment and upgrade
Since data sources cover multiple formats including public reports and operational archives, the deployment phase must support parsing for PDF, Word, Excel, and other document types. Research reports update on both quarterly and monthly cycles. The upgrade phase requires configuring incremental update trigger rules to align with release schedules. Individual document lengths vary greatly. Segmentation processing must balance semantic completeness and retrieval efficiency. Many structured fields require custom parsing templates to preserve technical terms and critical business information, and avoid parsing misalignment. Additionally, there are many commercial real estate projects and business districts. The vector database must reserve sufficient sharding and storage space to support full data indexing.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Commercial real estate research reports are mostly long documents. The parsing process includes format breakdown and field extraction, so sufficient processing time must be reserved |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Individual large feasibility study reports may exceed 1000 MB, so support for large file uploads is required |
chunkSize | 1200–1500 characters | Commercial real estate research reports contain large amounts of structured data and long paragraph descriptions. Segments that are too long will lose context association, while segments that are too short will damage semantic completeness |
similarityThreshold | 0.72–0.80 | Low-correlation business district or project data must be filtered to avoid recalling irrelevant non-commercial real estate research reports |
retrievalTopK | Top 8–10 results | Core information of commercial real estate research reports is concentrated in key business districts and projects. Too many recalled results will increase context load |
EMBEDDING_MODEL | m3e-large | Commercial real estate data contains large amounts of technical terms and structured fields. This model has stronger adaptability to industry-specific semantics |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Docker image pull times out or fails. Logs show connection timeout to the image source. Cause: Container image pull proxy is not configured correctly, or the image source does not adapt to local network conditions.
- Phenomenon: Vector database query returns empty results. The interface shows no matching research reports. Cause: Incremental update configuration is not enabled, or the update cycle setting does not match the research report release schedule, resulting in newly released business district data not being indexed.
- Phenomenon: Parsed document segments have field misalignment. Search results include irrelevant non-commercial real estate content. Cause: No custom document parsing template is configured. The default parsing rules cannot adapt to the structured field format of commercial real estate research reports.
How to confirm the configuration is properly set
- Upload a local commercial real estate business district research report. Check if parsed fields fully extract key information such as rental prices and location, to confirm the parsing process is operating normally.
- Trigger a vector database incremental update. Check if container logs show successful index generation, with no timeout or error messages.
- Enter a test query such as "rental trends for a certain business district". Check if the number and relevance of recalled results meet expected standards, and adjust relevant parameters to match business needs.
- Check the container connection status for MongoDB and the vector database. Confirm port mapping and network configuration are correct, with no connection failure or authentication error logs.
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.