What the data for this category looks like
Data sources for specialized chain industry research reports include financial retail industry segment research reports, chain retail format analysis documents released by industry associations, quarterly operating announcements publicly released by chain brands, and store sales performance research reports from third-party research institutions. Core format research reports are updated quarterly. Individual store operating segment data is updated monthly. Document structures typically include four modules: store distribution, per-store efficiency analysis, supply chain costs, and competitor benchmarking. Fields include store ID, monthly store revenue (unit: ten thousand yuan), supply chain turnover days (unit: days), and competitor store density (unit: stores per square kilometer). Data formats mix structured tables and semi-structured analytical text.
What constraints these characteristics impose on HTTP interfaces and external systems
Mixed multi-source data formats require HTTP interfaces to support multiple document parsing configurations such as CSV and PDF. This prevents incorrect extraction of some store operating data. Monthly and quarterly update schedules require interfaces to support scheduled synchronization parameters. This adapts to the data update cycles of chain brands. Precise field dimensions require interfaces to support filtering by conditions such as store ID and time range. This ensures returned data matches business requirements. Long length of individual research reports requires interfaces to support pagination recall mechanisms. This avoids excessive single return data impacting external system performance. When connecting to financial investment research systems, interfaces must support tenant authentication parameters. This ensures compliance of data access permissions.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single specialized chain research report often contains quarterly data for multiple stores. Parsing takes a long time, so extend the timeout to avoid parsing interruptions |
maxContext | 8000–12000 characters | Research reports contain multi-dimensional business fields. Sufficient context length is needed to retain complete store operating and analytical data |
recall_count | Top 8 entries | Core business dimensions of specialized chain research reports are concentrated. No excessive recall results are needed to cover daily retrieval needs |
similarity_threshold | 0.75–0.85 | Distinguish between precise store operating data and general retail generic research reports. Avoid recalling irrelevant industry-wide content |
UPLOAD_FILE_MAX_SIZE | 500 MB | Single chain research report may contain quarterly summary data for multiple stores. Support for large file uploads is required |
sync_interval | 3600 seconds | Monthly updated store segment data requires scheduled synchronization. Pull data at hourly intervals to ensure data timeliness |
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 specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: The HTTP interface returns a 413 Request Entity Too Large error. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration is not adjusted, and the large file size requirements of specialized chain research reports are not accommodated. - Phenomenon: When calling the question-and-answer interface consecutively, the second question cannot associate the previously specified store filtering conditions. Cause: Context passing configuration is not enabled, or the
maxContextsetting is too small, causing store filtering parameters to be truncated. - Phenomenon: The unit of per-store efficiency data returned by the interface is inconsistent. Cause: Unified field mapping rules are not configured, resulting in misaligned units of research report data pulled from different sources, which affects data analysis of external systems.
How to Confirm Correct Configuration
- Send a parsing request for a single research report. Check that the parsing status returned by the interface is successful, and the returned fields include preset business dimensions such as store ID and per-store efficiency.
- Send two consecutive question-and-answer requests with store filtering parameters. Check that the return result of the second request includes store-related data specified in the first request.
- Upload a single research report file that meets the configuration limit. Check that the upload status returned by the interface is successful, and the file parsing progress updates normally.
- Call the interface to trigger an abnormal request. Check that the corresponding error message and complete request parameters can be captured in the external log system.
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.