Reference only; verify against the target FastGPT release and deployment documentation.
What data for this category looks like
Business data for this category primarily comes from the national public resource trading platform, natural resource trading systems, property right exchange systems, and state-owned asset supervision systems. The update frequency is daily.
Commonly generated document types include transfer announcements, trading guidelines, bid application documents, margin vouchers, transaction confirmation documents, listing result announcements, property right transfer specifications, and more. Different documents have varying structures and field focuses. For example, ownership-related documents include fields such as subject location and right type, while trading-related documents include content such as bidding rules and margin requirements.
What constraints do these characteristics impose on model access and configuration
Multi-source system data requires configuring access paths adapted to different data sources to ensure complete data synchronization. The daily update frequency requires configuring scheduled synchronization tasks to ensure the policy and transaction data retrieved by the model remains up to date. Diverse document structures and fields require adjusting context window configurations to accommodate different document lengths and avoid truncation of critical information. The attribute association between transaction subject ownership and policy requires improving retrieval accuracy to prevent ownership matching errors or policy basis deviations.
How to set configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Typical single documents for this category (such as property right transfer specifications) are lengthy, requiring sufficient context to associate policy basis |
maxTokens | 4000–6000 token | Policy Q&A requires complete output of basis clauses to avoid truncation of responses |
quoteMaxToken | 2000–3000 token | Sufficient original text fragments must be retained for tracing policy documents to ensure response credibility |
temperature | 0.1–0.3 | Policy Q&A requires rigor, reducing randomness in generated content to avoid deviation from business basis |
toolChoice | auto | Automatically call retrieval tools to obtain the latest transaction and policy data, adapting to real-time updated business scenarios |
vision | enabled | Supports parsing image-based ownership materials such as parcel maps and property right certificates, covering visual input needs for this category |
AIPROXY_API_ENDPOINT | Fill in the official access address of the corresponding large model | Ensures connectivity and correctness of model calls |
AIPROXY_API_TOKEN | Fill in the identity verification key assigned by the platform | Completes identity verification for interface calls and ensures data transmission security |
Three common mistakes
- Symptom: A 404 no body prompt appears during model testing. Cause: Incorrect configuration of
AIPROXY_API_ENDPOINTorAIPROXY_API_TOKEN, leading to authentication or address parameter errors in interface calls. - Symptom: An unmarshal_resp error occurs during speech-to-text. Cause: The
maxTokenssetting range is too small, and the model-generated response exceeds the limit and is truncated, preventing successful response serialization. - Symptom: The image analysis process cannot run normally. Cause: The
visionconfiguration item is not enabled, and images are not converted to the required base64 format, preventing the model from parsing visual ownership materials.
How to confirm configuration is complete
- Manually upload a typical document of this category, trigger policy Q&A, and check if the returned result associates the corresponding policy basis fragment.
- View the data source synchronization log to confirm that the daily automatic synchronization task executes normally without error messages.
- Call the model interface to check that the returned response format complies with preset rules, with no truncation or serialization errors.
- Test the visual input function, upload a parcel map or property right certificate scan, and check if the model can correctly parse the ownership information in the image and associate it with policy basis.
The configuration values provided are common starting points. Adjust them based on your own specific samples and use cases.
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.