What Data for This Category Looks Like
Data for this category originates from publicly disclosed announcements from the Shanghai, Shenzhen, and Beijing Stock Exchanges, official financing tracking interfaces from licensed financial institutions, and information disclosure platforms for New Third Board listed enterprises. The update schedule synchronizes all incremental financing events from the prior natural day each early morning. Each entry is a structured item containing fields including 融资Event ID, 融资方名称, 融资轮次, 融资金额, 计价单位, 投资方列表, 融资公告发布日期, and 所属一级行业. Financing amounts must be differentiated by valuation units such as ten thousand yuan and hundred million yuan. Some entries also include detailed proportion breakdowns for lead and follow-up investors.
Constraints Imposed by These Characteristics on Deployment and Upgrade
The daily incremental synchronization update schedule requires precise scheduled pull trigger configuration during deployment, and built-in deduplication logic for duplicate financing events to avoid data redundancy. Differences across multiple structured fields and valuation units require configuration of cross-data source field mapping rules before deployment, to adapt to varying field naming conventions returned by different interfaces. The data volume fluctuates with market activity, requiring adjustments to vector database sharding and indexing strategies during upgrades to avoid excessive load on single nodes. Some data sources have call frequency limits, so rate limiting parameters must be configured during deployment to prevent triggering interface risk control rules. Additionally, financing daily reports for investment platforms must be displayed to users in real time, so upgrades must support gray release to ensure service continuity.
How to Configure Settings
| Configuration Key | Recommended Value | Rationale |
|---|---|---|
SYNC_FREQUENCY | Once per hour | Financing daily reports update with the previous day's data each day. Pulling every hour keeps data latency under 1 hour, balancing real-time performance and interface load |
DUPLICATE_REMOVE_MODE | Deduplicate by financing event ID | Financing events may be reported repeatedly across data sources. Deduplicating using the unique ID ensures no data redundancy |
FIELD_MAPPING_TEMPLATE | Map using official standard fields | Field naming varies across different data sources. Using official standard templates reduces configuration complexity |
VECTOR_INDEX_CHUNK_SIZE | 800–1200 characters | The text content of a single financing daily report is typically around 1000 characters. This range ensures retrieval accuracy |
MAX_SYNC_RETRY_TIMES | 3 retries | Some data source interfaces have temporary fluctuations. 3 retries ensure successful data pulling without impacting service |
RATE_LIMIT_THRESHOLD | 15 QPS | Most public financing data source interface rate limits range from 15–20 QPS. Configuring this parameter avoids triggering risk control rules |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, 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
- Symptom: All configuration items for
oneapiandfastgptare lost after Docker container restart. Cause: The database mount directory was not mapped to host persistent storage. Data inside the container is cleared after restart. - Symptom: Scheduled financing daily report pull tasks time out, returning a
504 Gateway Timeouterror. Cause: Reasonable retry counts and timeout periods were not configured. Retries were not triggered when data source interfaces experienced temporary fluctuations, leading to task failure. - Symptom: The
融资金额field in financing daily reports displays as empty. Cause: Field mapping rules were not configured. Theamountfield returned by the data source was not mapped to the system-standard融资金额field, resulting in failed data parsing.
How to Verify Correct Configuration
- Run the
docker logs fastgptcommand to view execution logs for synchronization tasks. Adjust theSYNC_FREQUENCYvalue based on latency duration shown in the logs. - Connect to the pgvector database, query the number of entries in the financing daily report table, and compare with the number of daily events from public data sources. Adjust configurations for field mapping and synchronization frequency.
- Access the financing daily report display page for the investment platform, verify that all fields for individual entries are complete. Adjust the
FIELD_MAPPING_TEMPLATEconfiguration based on display results. - Restart the deployment container, check that the database and configuration items are not lost. Adjust host mount directory configurations based on retention status.
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.