What the data for this category looks like
Financial leasing investment research data primarily originates from leasing project ledgers, rent payment transaction records, lessee credit reports, industry regulatory policy documents, and leased asset vendor quotation sheets. Update frequency is adjusted based on project progress. Single project contracts are logged in real time after signing. Rent calculation sheets are updated on a monthly basis. Most documents combine structured tables and long-form text. Core fields include project number, lessee unified social credit code, original value of leased assets (unit: ten thousand yuan), annualized leasing interest rate, number of rent payment periods, and guarantor qualification level. Some documents include leased asset residual value assessment reports.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
There are numerous highly correlated structured fields. Multi-turn dialogue must continuously track entities such as project numbers and lessee information to avoid cross-project confusion. Data update frequencies vary significantly. Prompts must explicitly prioritize real-time project data entered after contract signing. Monthly updated calculation sheets may only be used for current period rent accounting. Documents mix long-form text and structured tables. Retrieval operations must retain full correlation of table fields. During multi-turn dialogue, the current rent payment period under discussion must be explicitly specified to eliminate contextual ambiguity. Internal credit and public regulatory documents require separate citation scopes. Prompts must limit calls to authorized project-related data stored in the knowledge base.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Covers multi-turn dialogue history and field content from 1 to 2 complete leasing project documents, preventing context truncation and loss of associated information |
recallTopK | Top 6–8 entries | Financial leasing project data has many fields. This range covers core modules including basic project information, rent plans, and guarantee clauses. A larger range increases context load |
similarityThreshold | 0.75–0.82 | Structured field matching requires high precision. A threshold that is too low introduces irrelevant project data. A threshold that is too high may miss valid information for different periods of the same project |
streamResponse | Enabled | Financial leasing investment research conversations often require gradual output of rent calculation details. Streamed responses improve interactive response speed |
PARSE_TABLE_STRUCTURE | Enabled | Financial leasing documents contain large numbers of structured rent payment tables. Retaining field structure improves the accuracy of data references during multi-turn dialogue |
maxTokenPerChunk | 1500–2000 characters | Matches the length of single-segment core information in leasing project documents, preventing segmentation from damaging table or clause integrity |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: Knowledge base reference fields returned by API calls are empty. Cause: The
sourceIdandprojectNofields are not passed in the context parameter of the dialogue request. This prevents the AI from binding to the currently discussed leasing project. - Phenomenon: The second round of dialogue cannot continue discussion of the leasing project from the first round. Cause:
maxContextwas not configured to retain historical entity information, leading to loss of key identifiers such as project numbers after context window truncation. - Phenomenon: Streamed API responses show segmented breaks or garbled text. Cause: The
streamResponseconfiguration was not enabled, ormaxTokenPerChunkwas set too small, leading to incorrect splitting of long-form leasing project content.
How to Verify Correct Configuration
- Initiate a single-turn dialogue test. Enter a specified project number. Confirm that returned results only associate structured data for the matching project, with no irrelevant project content.
- Initiate three consecutive dialogue rounds. Submit queries for different rent periods. Confirm that each round’s reply correctly inherits the project identifier and context information from the prior round.
- Call the streamed API interface. Observe that returned content is output gradually in natural segments, with no obvious breaks or garbled text.
- Upload a leased asset photo to the knowledge base. Initiate a multimodal query. Confirm that the system associates parameter and valuation information for the corresponding leased asset.
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.