What this category of data looks like
Cement market and yield rate data is primarily sourced from commodity market aggregation APIs and public APIs of the national building materials industry monitoring platform. Data updates on a natural day basis, with full daily data released after market close each workday. Each complete data entry includes fields such as statistical date, region name, cement grade, ex-factory unit price. The unit for the price field is yuan per ton. Data is structured by region, with each region containing market information for multiple common cement grades. A full daily report typically spans several thousand characters.
Constraints imposed by these characteristics on model access and configuration
The multi-region, multi-grade grouping feature of cement market data requires that model access supports filtering parameters by region, grade and other dimensions to avoid returning redundant information. The daily update rhythm requires that scheduled task intervals match the data release cycle to ensure access to the latest market data. The long-text document structure requires configuring text splitting parameters to split long documents into segments compatible with model context windows, preventing context overflow. The unit of yuan per ton for price fields requires configuring data validation rules to ensure parsed units align with business requirements and avoid unit confusion. Additionally, the need to extract multiple fields requires enabling function calling capabilities to accurately extract specified fields.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
HTTP_REQUEST_TIMEOUT | 600 seconds | The aggregated multi-region, multi-grade cement market API response has a large data volume. 600 seconds covers most normal response durations and avoids timeout interruptions |
segment_length | 800–1200 characters | This single-segment length is compatible with most model context windows, while ensuring complete presentation of cement market information including region, grade, unit price and other details |
toolChoice | auto | Automatic triggering of function calls is required to extract specified cement market fields. The auto mode automatically selects tool calls based on input content |
PARSE_FIELD_WHITELIST | Statistical Date, Region Name, Cement Grade, Factory Unit Price | Only retain fields required for business purposes, filter redundant information, and reduce model processing and transmission costs |
LOCAL_MODEL_ALLOW_LIST | ["chatglm2-6b", "cosyvoice2-0.5b"] | Add locally deployed models accessed via OneAPI to the allow list to ensure they can be properly selected when creating a knowledge base |
TEXT_SPLITTER_TYPE | character | The field boundaries of cement market data are clear. Splitting by characters ensures that single-segment information is not truncated |
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 targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: After calling the cement market API via an HTTP node, a long text is returned, but the model only processes the first segment, with subsequent information excluded from the broadcast. Cause: No text segmentation parameters are configured, and the long text is not split into independent segments compatible with the model context window.
- Phenomenon: After configuring the
functionCallparameter, the content extraction node fails to call the self-built model interface, returning an error stating "model does not support function calls". Cause: The self-built model does not have function calling enabled, or relevant parameters are not correctly configured inconfig.json. - Phenomenon: The voice broadcast node fails to call CosyVoice2-0.5B, returning an error stating "model not found". Whisper-large-v3-turbo runs normally. The current FastGPT version is 4.8.16, and the model is deployed via Xinference V1. Cause: The deployment address of CosyVoice2-0.5B is not added to the FastGPT voice model configuration, or there is a compatibility issue between the Xinference model version and the current FastGPT version.
How to Confirm the Configuration is Complete
- Initiate a test call, check whether the content returned by the HTTP node is correctly split into multiple segments, with segment lengths matching the preset requirements.
- Call the content extraction node, confirm that the returned results only include the fields configured in
PARSE_FIELD_WHITELIST, with no redundant information. - Enter the knowledge base management page, confirm that the locally deployed chatglm2 model and CosyVoice2-0.5B appear in the optional model list.
- Check the system operation logs, confirm that no timeout errors occur for HTTP requests, and that model calls return normal function calling results.
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.