What this category of data looks like
Data for this category typically comes from national public resource trading platforms, natural resource trading systems, property right exchange systems, and state-owned asset supervision systems, and is updated daily. Common documents include transfer announcements, trading guidelines, bid application materials, margin vouchers, transaction confirmation letters, listing result announcements, and property right transfer specifications. Core fields cover ownership information of transaction subjects, restriction conditions, bidding rules, margin standards, and transaction confirmation details. Data is generated across the full transaction process of resource and asset rights.
What constraints these characteristics impose on model access and configuration
Data for this category comes from multiple dispersed sources and is updated daily. This requires the model access link to support format adaptation and incremental synchronization for multiple data sources. This avoids inaccurate consulting replies caused by delayed data. The range of document types is wide, from short margin vouchers to multi-thousand-word transfer announcements. This requires adaptation to text chunking and retrieval logic for different lengths. Core fields focus on key transaction information such as ownership, restriction conditions, and bidding rules. Model configuration must prioritize the retrieval weight and matching accuracy of these fields. It must also strictly verify the compliance of returned content. This prevents disputes over invalid transactions or asset loss caused by incorrect replies.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the context requirements of long documents in this category (such as transfer announcements, property right transfer specifications) to avoid truncation of core transaction information |
maxTokens | 2000–3000 token | Matches the length requirements of transaction consulting replies, covering complete trading rule explanations while avoiding redundant output content |
quoteMaxToken | 1500–2000 token | Ensures that retrieved trading document fragments (such as ownership descriptions, bidding rules) can be fully included in the context without truncation |
temperature | 0.1–0.3 | Reduces random output probability, ensuring the accuracy of replies for key information such as ownership and bidding rules |
AIPROXY_API_ENDPOINT | Corresponding deployed FastGPT proxy address | Adapts to the proxy forwarding requirements of multiple data source access, unifying interface call paths |
AIPROXY_API_TOKEN | Exclusive key assigned by the system | Ensures identity verification for interface calls, preventing unauthorized access |
Three common mistakes
- After configuring
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKEN, API calls return a 401 Unauthorized error. This occurs due to an incorrectly configured key, or the proxy address not being bound to corresponding access permissions. - A Connection error prompt appears during model debugging. This occurs because the proxy address cannot be accessed normally, or network policies restrict communication links with the model service.
- The model returns only a single matching text block, without a comprehensive reply that references multiple documents. This occurs because the
quoteMaxTokenconfiguration value is too small to fit only a single document fragment, or the retrieval logic does not have multi-result retrieval rules enabled.
How to confirm the configuration is correct
- Initiate an API call test, and verify that the returned HTTP status code falls within the normal response range, with no identity verification errors.
- Input a consulting question covering transaction ownership and bidding rules, and verify that the returned content references multiple different business document fragments.
- Adjust the
temperatureparameter, then call the same consulting question multiple times, and verify that the core transaction information in the returned content has no obvious random deviations. - Check the system synchronization log, and confirm that the update frequency of business data meets the preset daily update requirement.
The values provided are common starting points, and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.