What this category of data looks like
This category of data primarily comes from the 12345 citizen hotline platform, contractor business systems, official knowledge bases, follow-up evaluation data, and local hotline management regulations, and is updated daily. Documents processed daily include request registration forms, dispatch records, handling responses, follow-up records, extension applications, return explanations, and knowledge base entries. Fields cover request number, request content, dispatching unit, response wording, follow-up evaluation results, and more. The structure is built around the closed-loop circulation of public requests.
What constraints these characteristics impose during model integration and configuration
Multi-source data updated daily requires model integration to support incremental data synchronization, to avoid reprocessing expired tickets. Diverse document types and scattered fields demand targeted field extraction rules, to accurately extract key information from forms and records in different formats. Multi-system integration needs access configurations that support multiple API endpoints and token management, plus strict control of model response latency, to prevent ticket overdue. Spoken request content needs semantic understanding logic adapted to daily language, to ensure accurate judgment of request type and responsible unit.
How to set up the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxTokens | 8000–12000 token | Adapt to the combined context length of ticket content and historical records, avoid truncating critical information |
temperature | 0.1–0.3 | Maintain consistent response wording, avoid generating content that deviates from business specifications |
AIPROXY_API_ENDPOINT | Fill in the locally deployed model proxy address | Adapt to the local deployment requirements of the 12345 hotline scenario, ensure data stays within the domain |
AIPROXY_API_TOKEN | Configure a dedicated access token | Isolate API access permissions for different business scenarios, prevent unauthorized calls |
quoteMaxToken | First 3–5 referenced documents | Prioritize matching core documents such as latest dispatch records and handling responses, improve response accuracy |
toolChoice | auto | Support automatic calling of knowledge bases or business data interfaces, adapt to multi-source information retrieval needs |
Three common configuration mistakes
- A 401 unauthorized error occurs when calling the model to process tickets. This is caused by incorrect
AIPROXY_API_TOKENconfiguration, insufficient token permissions, or failure to match access rules for the corresponding scenario. - The AI model dropdown list is empty in workflows. This is caused by incorrect
AIPROXY_API_ENDPOINTconfiguration, or the proxy service not starting normally, making it impossible to pull available model lists. - Content truncation appears when the model processes long tickets. This is caused by a too low
maxTokensvalue, which does not cover the total length of ticket history and current request, leading to loss of critical information.
How to confirm the configuration is complete
- Test the processing flow of a single request ticket, confirm the model can correctly extract request type and responsible unit fields, and check consistency between extraction results and manual annotations.
- Call the model interface to view return logs, confirm
AIPROXY_API_TOKENverification passes, and no 401-level errors occur. - Review the response content generated by the model, confirm the wording complies with 12345 hotline business specifications, and no non-compliant content appears.
- Test the incremental data synchronization flow, confirm daily updated ticket data can be normally read and processed by the model.
The values listed here 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.