What data looks like for this category
Residential development scenario data includes two categories: structured and unstructured. Structured data originates from sales systems, CRM ledgers, and land transfer announcements. It includes fields such as salable area (㎡), number of visiting customers (people), total subscription price (ten thousand yuan), and building number. A single sales data table can reach 2MB in size and contain over 100,000 records. Unstructured data refers to marketing materials, including floor plans, location brochures, project promo scripts, launch event plans, and more. A single long document can reach tens of thousands of characters. The data update rhythm follows project milestones: sales data updates daily, and marketing materials are updated in batches during launch, re-launch, and other key milestones.
What constraints these characteristics impose on model access and configuration
The volume and field complexity of structured data require the access link to support batch data mapping and format validation, to avoid field misalignment or unit errors. The presence of long unstructured documents requires the configuration link to adapt parameters for long text parsing and segmented storage. Differences in update rhythms across data types require configuring scheduled sync task trigger frequencies, to ensure marketing content uses the latest sales and material data. Additionally, residential development marketing content needs to accurately match customer groups and project parameters. When calling the model, field and unit constraints must be explicitly specified, to prevent generated content from deviating from actual business rules.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Adapts to the batch upload requirements of high-definition marketing materials and 100,000-row sales data tables in residential development scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Meets the parsing time requirements for long documents such as project feasibility study reports and complete floor plan manuals |
maxContext | 8000–12000 characters | Supports context association across multiple segments of sales data and marketing materials, enabling accurate generation of marketing content |
Recall Count | Top 8 | Matches the precise marketing needs of residential development customer groups, filtering redundant historical data |
Similarity Threshold | 0.75 | Balances content relevance and data coverage, preventing low-relevance data from interfering with output |
Model Channel Configuration | Enable custom proxy, configure aiproxy address and secret key | Adapts to the unofficial model API call requirements of FastGPT 4.9.1, resolving error issues caused by unavailable channels |
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 it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: The interface prompts "No available channel for model qwq:latest under current group default". Cause: The custom proxy channel for the corresponding model is not configured, or the proxy address and call secret key are filled incorrectly.
- Phenomenon: A timeout error is triggered when the workflow processes sales data. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis too short to complete full parsing of a 100,000-row data table. - Phenomenon: Unit errors appear in generated marketing copy, such as incorrect units labeled for "salable area". Cause: Unit requirements for fields are not explicitly specified in the model call prompt, or correct mapping between sales data fields and model input fields is not completed.
How to confirm configuration is complete
- Upload the largest single marketing material or sales data table, check if the upload and parsing process proceeds smoothly. Adjust
UPLOAD_FILE_MAX_SIZEto a value that meets current business requirements. - Run a test workflow containing 100,000 rows of sales data, monitor task duration, and adjust the value of
PARSE_FILE_TIMEOUT_SECONDSto adapt to parsing needs. - Call the model to generate marketing copy for a specific floor plan, verify that the output contains correct field units and business parameters, and adjust the values of
maxContextand recall-related configurations. - Switch to an unofficial model for testing, check if calls can be completed normally and valid results returned, to verify the correctness of the model channel configuration.
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.