What the data for this category looks like
Data sources include financial ledgers, investment signing archives, property fee modules from the park operation management system, and rent filing data from industrial buildings. Updates occur monthly. Some core business format data is synchronized weekly. Each document contains a unique park identifier, list of settled enterprises, benchmark rent prices for each business format, monthly actual received amount, operating cost details, and yield rate calculation fields. Field units are: rent unit price is yuan per square meter per month, actual received amount is ten thousand yuan, operating cost is ten thousand yuan, and yield rate is a calculated value. Documents usually include detailed entries for multiple business formats, have a high total character count, and associate data source identifiers from multiple systems.
Constraints for Conversation Logging and Auditing
The multi-source nature of industrial park yield rate data requires conversation logs to fully record data source traceability information for each call. This ensures the original source of data can be traced during audits. The monthly update frequency requires conversation logs to link to the correct version of the dataset for each cycle. This avoids audit risks caused by mixing data across cycles. The high character count of documents triggers length limit issues during dataset indexing. Conversation log storage must support recording long text fragments. The multi-field, multi-unit structure requires the audit process to verify field unit consistency in each log entry. This prevents deviations in calculation logic.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_CHARS | 800–1200 characters | Industrial park yield rate documents include multi-format details, with high per-document character count. This value balances indexing efficiency and content completeness |
maxContext | 4000–6000 characters | Conversation logs must retain context for multi-turn interactions. This value supports long-text retrieval needs for park data, while avoiding exceeding model input limits |
LOG_STORAGE_ENABLED | Enabled | Audit processes require complete retention of internal details from conversation interactions. This configuration enables storage of full logs |
MONGO_DB_BATCH_INSERT_SIZE | 50–100 entries per batch | Industrial park data documents have large volume. Batch insertion reduces the probability of indexing timeouts and improves dataset building efficiency |
UPLOAD_FILE_MAX_SIZE | 200 MB | Single park operation documents include multi-year detailed data. This value supports batch uploads of multiple associated documents |
QUERY_RECALL_THRESHOLD | 0.75–0.85 | Park data fields have strong correlation. This threshold filters low-relevance retrieval results and improves the accuracy of log records |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Issue: Dataset import remains in the indexing state for an extended period. Console logs display
text length exceeds limiterrors. Cause: ThePARSE_FILE_MAX_CHARSparameter is not adjusted. The multi-format details of industrial park documents cause per-document character count to exceed default limits, triggering indexing failure. - Issue: The conversation details page only displays user questions and final replies. It cannot display dataset retrieval fragments, calculation steps, or other internal details. Cause: The
LOG_STORAGE_ENABLEDconfiguration is not enabled, or the "Record full interaction logs" option in the interface is not checked. This results in internal call links not being retained. - Issue: After logging into the MongoDB database, no conversation history records for the corresponding application can be found. Cause: The
MONGO_DB_CONNECTION_STRINGparameter is not configured, or the parameter is filled incorrectly. This causes conversation logs to not be correctly written to the specified database collection.
How to Confirm Configuration is Correct
- Upload a typical industrial park operation document. Check if indexing completes within a reasonable time frame. If not, adjust the values of the
PARSE_FILE_MAX_CHARSandUPLOAD_FILE_MAX_SIZEparameters. - Initiate a conversation that includes yield rate calculation. Enter the conversation details page. Check if specific fragments of dataset retrieval and calculation logic are displayed. If not, confirm the enabled status of
LOG_STORAGE_ENABLED. - Log into the MongoDB database. Query the conversation log collection for the corresponding application. Check if records for this interaction exist. If not, verify the correctness of the
MONGO_DB_CONNECTION_STRINGparameter. - Initiate multi-turn conversations. Check if logs fully retain context call records for each turn. If records are missing, adjust the value range of the
maxContextparameter.
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.