What the data for this category looks like
Data for commercial real estate financing daily reports comes primarily from public regulatory filing documents, announcements released by commercial real estate project parties, and daily submitted data from industry-specific professional databases. The update schedule follows a daily cadence on workdays, with delays applied on holidays. Each document uses structured entries for individual financing projects, with fields including full project name, financing subject, financing amount, financing method, fund provider, disclosure date, and the business district and location of the project. Amounts are uniformly denominated in RMB 100 million yuan. Date fields use the ISO 8601 format. Location fields are accurate to the city core business district level.
What constraints these characteristics impose on the citation sources and traceability link
The multi-channel, scattered sources of commercial real estate financing daily reports require the traceability link to bind independent original source identifiers to each data entry, to avoid confusion between entries for the same project from different channels. The high-frequency daily update schedule on workdays requires recency filtering by the disclosure date field during recall, to prevent introducing expired or not officially disclosed projects. The precise unit requirements for structured fields require retaining the complete format of original amounts and locations during traceability, without unauthorized unit conversion or simplified location descriptions. The fixed number of fields per project but large volume of aggregated entries requires associating each entry with the publication batch of the daily report it belongs to, to ensure traceability to the specific publication cycle when citing.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
RECALL_TOP_N | Top 8-12 entries | Commercial real estate financing daily reports contain multiple projects per entry. Too many recalled entries increase context redundancy, too few will miss core financing cases |
VECTOR_SIMILARITY_THRESHOLD | 0.72-0.85 | Financing project descriptions have high semantic similarity. A threshold that is too low will introduce irrelevant entries, a threshold that is too high will miss similar projects |
CHUNK_SIZE | 600-800 characters | The structured description length of a single financing project is moderate. Too long a chunk will destroy field association logic, too short a chunk will split complete project information |
VECTOR_MODEL_NAME | bge-large-zh-v1.5 | Adapts to professional business district and financing terminology in the commercial real estate field, with Chinese embedding effects that better fit the business scenario |
SOURCE_TAG_ENABLE | Enabled | Must bind an original source identifier to each recalled entry to meet traceability display requirements |
FUNCTION_CALL_RETURN_RAW | Enabled | Retain complete fragments from the database or daily report original text, to achieve original citation effects similar to RAG knowledge bases |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: After calling Function CALL to obtain MySQL data, the answer does not display the original database text fragments, only returns generalized content generated by the large model. Cause: The
FUNCTION_CALL_RETURN_RAWconfiguration item is not enabled. Only the return result of the function call is received, and the original data fragments are not obtained. - Phenomenon: The reason field generated by the custom conversation component cannot be read and called by subsequent process nodes. Cause: The
FUNCTION_OUTPUT_PERSISTconfiguration item is not enabled, and intermediate variables are not persisted for storage. - Phenomenon: After switching the vector model, a large number of irrelevant entries appear in the recall results, and it is impossible to accurately match commercial real estate financing content. Cause: The vectorized index of the commercial real estate financing daily report original documents is not recreated, and the new model is not adapted to the semantic features of the original dataset.
How to confirm the configuration is complete
- Initiate a query targeting commercial real estate financing projects, check whether the answer includes the original source identifier of each recalled content, to confirm that the source binding function works normally.
- Call Function CALL to connect to the MySQL database, check whether the answer includes the original text fragments returned by the database, to confirm that the original data citation function works normally.
- After adjusting the vector model, re-execute document parsing and indexing, and initiate a query to verify that the semantic matching degree of the recall results meets business expectations.
- Trigger the custom conversation component to generate the reason field, view the intermediate variable list through the process debugging tool, and confirm that the field can be read and called by subsequent nodes.
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.