What the data for this category looks like
This category's data originates from compliant multi-source financial market and yield reporting application programming interfaces (APIs), covering non-standard assets across fixed income, equities, alternative investments and other categories. Full data synchronization is completed at a fixed time each day, with the day's reporting content released on the same day. Documents use a structured table format, including fields such as asset unique identifier, asset category name, statistical cycle, yield benchmark value, market fluctuation range, release time, and more. The units for yield benchmark value and fluctuation range are annualized basis points, and the statistical cycle is measured in natural days.
What constraints these characteristics impose on the model access and configuration workflow
Multi-source data access requires configuring cross-source data consistency check rules to avoid deviations in identical asset yield data returned by different APIs. The fixed update rhythm requires configuring scheduled trigger pull tasks to ensure data synchronization is completed within the specified time window. The structured document format requires configuring field mapping parameters to create a one-to-one correspondence between original API fields and model input fields. The coverage scope of non-standard assets requires configuring category filtering rules to limit the asset types processed by the model. At the same time, the timeliness requirement of daily reports requires configuring a reasonable API call timeout threshold to avoid task timeouts impacting that day's broadcast generation.
How to set the configurations
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
data_source_list | Add 2-3 compliant financial data APIs | This category requires coverage of multiple asset types, and multi-source APIs can improve data completeness |
sync_schedule | Trigger daily at 22:00 | Matches industry standard daily report reporting rhythm, ensuring data synchronization is completed after that day's trading session ends |
field_mapping | Map directly to model input fields using original field names | The field format of structured documents is fixed, direct mapping reduces data conversion errors |
api_timeout | 600 seconds | Pulling multi-source APIs requires waiting for full data returns, a longer timeout prevents task interruptions mid-execution |
batch_size | 16–32 | Limits the volume of data processed per batch, balancing model inference speed and video memory usage |
rerank_top_k | Top 5 entries | Sort pulled market data by priority, ensuring broadcast content aligns with user concern dimensions |
The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules, and specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- The symptom is an
invalid_tokenerror when calling domestic AI models or APIs. The oneAPI test passes but direct connection configuration fails. The cause is that the correct regional node and signature verification rules are not configured during direct connection; some domestic models require binding a dedicated gateway address. - The symptom is that after starting the
bge-rerankermodel, GPU video memory quickly grows to 6-7GB during calls, and all GPUs are occupied. The cause is that thebatch_sizeparameter is not configured, and the default batch processing logic does not limit the volume of data per batch, leading to video memory overflow. - The symptom is that the broadcast content generated by the model includes irrelevant system prompt text. The cause is that non-essential debug output configurations are not disabled, and background verification prompts are mixed into the model input context.
How to confirm the configuration is complete
- Run a manually triggered data pull task, and verify that the pulled fields match the configured mapping rules.
- View model call logs, confirm that all API return status codes are business success codes, and there are no
invalid_tokentype errors. - Test single-batch data calls, verify that GPU video memory usage matches the configured expectations, with no abnormal growth.
- Generate simulated daily report content, verify that the output does not include irrelevant system prompts or debug information.
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.