What the data for this category looks like
Data sources for commercial real estate intelligent due diligence reports include real estate registration systems, property operation ledgers, commercial district passenger flow statistics platforms, lease contract archives, and surrounding competitor survey data. Update cycles vary across sources: real estate property right information is updated quarterly, lease contract terms are synchronized monthly, commercial district passenger flow data is updated weekly, and energy consumption and rent data are updated daily.
Document structures include a basic information module (property location, property right number, gross floor area), a lease module (tenant information, lease term, rent standard), an operation module (monthly average passenger flow, energy cost, per-square-meter efficiency), and a surrounding module (competitor rent, commercial district planning). Fields include standard units and identifier fields such as unified social credit code, square meters, yuan per square meter per month, and daily passenger trips.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The multi-source heterogeneous nature and varying update cycles of commercial real estate due diligence data require multi-turn dialogue to guide users to supplement missing information module by module. This prevents overloading the context with too many requests at once.
The long document structure requires limiting the context window size to avoid redundant information interfering with core judgments. Data sources with different update frequencies must have their timeliness clearly noted in prompts to ensure the accuracy of due diligence reports.
The diversity of fields and units requires prompts to enforce a unified output format, preventing mixed units or missing fields. Cross-module data associations, such as joint analysis of rent and passenger flow, require multi-turn dialogue to guide step-by-step, gradually integrating information from different modules.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Commercial real estate due diligence reports contain multiple long texts of lease and operation data. Sufficient context must be retained to avoid loss of key information |
temperature | 0.1–0.3 | Due diligence reports require rigor and accuracy. Lower randomness to avoid errors in field units or data deviations |
systemPrompt | Uniformly use square meters and yuan per square meter per month as units. Output according to the "Basic Info - Lease - Operation - Surrounding" structure | Match industry standard formats for commercial real estate, ensuring standardized and consistent output content |
recallTopK | Top 6 entries | Cover three core data categories: lease, operation, and surrounding. Avoid recalling excessive redundant irrelevant information |
similarityThreshold | 0.75–0.85 | Filter low-match non-property related data to ensure recalled content is highly relevant to the due diligence topic |
fileParseChunkSize | 1500 characters | When splitting long lease contracts and operation ledgers, retain the integrity of individual data segments to facilitate subsequent precise recall |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: Custom prompts do not take effect when calling the
/api/v1/chat/completionsAPI. Cause: Therole: systemcontent was not correctly added to themessagesarray in the request body, or the global default prompt overrode the custom configuration. - Phenomenon: It is not possible to switch between Chinese and English conversation opening lines in the same workflow. Cause: Independent
systemPromptbranches were not configured for different language scenarios, and context variables were not used to trigger language switching logic. - Phenomenon: When importing Markdown-format property documents, embedded image links are not automatically completed with the domain name. Cause: The image domain name completion function was only enabled during Word file import, and no corresponding domain name replacement rules were configured for Markdown parsing.
How to confirm the configuration is complete
- Initiate a test conversation, input "Please provide the lease information for XX Commercial Plaza", check whether the reply contains complete required fields such as property right number, tenant name, and lease term.
- Call the
/api/v1/chat/completionsAPI, pass a customsystemprompt, and confirm that the units of the returned results conform to industry standards. - Upload a Markdown-format property operation document, check whether the parsed image links carry the preset domain name.
- Configure two opening lines for Chinese and English in the same workflow, switch languages for input testing, and confirm that the conversation logic matches the prompt rules for the corresponding language.
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.