Deployment and Upgrade for Residential Development Research Report Retrieval

Residential development research report data primarily comes from housing authority project filing databases, public annual reports of real estate

What the data for this category looks like

Residential development research report data primarily comes from housing authority project filing databases, public annual reports of real estate enterprises, monthly survey materials from industry associations, and third-party land transaction platform data.

Update rhythms fall into three categories:

  • Project filing data is synced daily
  • Monthly industry research reports are updated on a fixed cycle
  • Real estate enterprise annual reports are updated annually

Document structures include modules such as project location parameters, plot-compliant gross floor area, floor land price, sales rate, and competitive product comparison tables. Most fields are quantitative data with units. For example, plot-compliant gross floor area uses square meters as its unit, and floor land price uses yuan per square meter.

What constraints do these characteristics impose on deployment and upgrade

The characteristics of residential development research report data impose three constraints on the deployment and upgrade process:

  1. Documents contain multi-page long content and professional quantitative fields with units, leading to longer parsing time. File upload and parsing timeout configurations must be adjusted.
  2. Multiple data sources with varying update rhythms require configuring incremental sync rules during deployment, and compatibility with different data source update frequencies during upgrade.
  3. Highly specialized fields require custom parsing templates to match exclusive parameters. Field mapping configuration must be completed before deployment to avoid retrieving irrelevant generic content.

How to set configurations

Configuration ItemRecommended ValueBasis for This Value
PARSE_FILE_TIMEOUT_SECONDS600 secondsResidential development research reports often include multi-page tables and project-specific parameters, requiring sufficient parsing time
UPLOAD_FILE_MAX_SIZE800 MBSome research reports include attachments such as project floor plans and competitive product comparison tables, requiring relaxed upload limits due to large single-file size
maxContext8000–12000 charactersResearch reports contain multi-dimensional associated data, requiring sufficient context space to match project parameters and competitive product analysis content
Recall CountTop 10 entriesData related to residential development is scattered across multiple documents, requiring sufficient retrieved content to cover complete information
Similarity Threshold0.75–0.85Precise matching of core fields such as project location and cost parameters is required to avoid retrieving irrelevant generic industry research reports
Reranked Return CountTop 5 entriesRetain the most relevant project data and competitive product analysis content after filtering to avoid overly redundant results

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three common misconfigurations

  • Phenomenon: A white screen appears when accessing the deployed interface via the public network, the chat window fails to load on mobile devices, and the console returns a 413 status code. Cause: The UPLOAD_FILE_MAX_SIZE parameter is not adjusted, triggering a request size limit when uploading large research report attachments, or cross-origin allowance parameters are not configured, leading to resource loading failure.
  • Phenomenon: GPU utilization is below 30% during large model inference, and single CPU core occupancy reaches 100%. Cause: The batch_size and model_parallel_size parameters are not configured, and GPU acceleration scheduling is not enabled, leading to unbalanced compute resource allocation and inability to fully utilize GPU computing power.
  • Phenomenon: After upgrading to V4.9 version, the online DeepSeek model fails to load, and an interface error is returned during calls. Cause: The OPENAI_API_BASE and MODEL_LIST parameters are not configured in the system settings, and the third-party model interface address and model name are not correctly bound.

How to confirm proper configuration

  • Upload a research report file that includes project floor plans and cost parameters, check if the parsing status shows success with no timeout error prompts.
  • Check GPU resource usage, confirm that GPU cores are active, and single CPU core occupancy does not remain at 100%.
  • Search for content related to a specified residential development project, check if the returned results include the project's exclusive fields, with no large volumes of irrelevant generic industry documents.
  • Fill in the online model interface parameters in the system settings of the V4.9 version, initiate a test call, and confirm that the model can normally return research report question and answer results.

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.