What this category of data looks like
The data for query result reports originates from internal system compilations of public-sector and state-owned enterprises, as well as structured business reports generated by individual business modules. Updates follow business cycles, including monthly, quarterly, or on-demand generation. Documents use structured tables as their core content, paired with brief explanatory text, and include fields such as unique report identifier, generation time, designated management department, statistical dimensions, corresponding values, and units of measurement. Units of measurement include clear values such as ten thousand yuan, person-times, and calendar days.
What constraints these characteristics impose on the "model access and configuration" link
Structured report data requires the model to accurately identify fields and units of measurement, to avoid errors where values and units do not match. Regularly updated data sources require configuration to support incremental retrieval logic, reducing full-volume repeated calls. Requirements for associating multi-source systems and reports require configuring trigger conditions for associated retrieval during model access, ensuring that Q&A can match both system clauses and corresponding report data. Rigorous internal usage requirements limit the scope of model-generated content, requiring outputs to be based solely on pre-configured data sources.
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 | Adapts to the total length of report and system text, avoiding truncation of core content |
temperature | 0.1–0.3 | Maintains answer rigor, aligning with compliance requirements for internal Q&A |
maxContext | 6000–10000 characters | Carries associated system text and report data, ensuring complete context |
| Question Optimization | Enabled | Resolves ambiguous references and supports question expansion, adapting to multi-source data Q&A scenarios |
AIPROXY_API_TOKEN | Exclusive key assigned by the platform | Ensures secure identity verification for model access, complying with permission specifications for internal usage |
toolChoice | auto | Allows the model to independently decide whether to call retrieval tools, adapting to associated Q&A for multi-source data |
Three common configuration errors
- Symptom: The model returns report values that do not match their units, such as displaying ten thousand yuan as yuan. Cause: No validation logic for fields and units of measurement is configured, or the
temperaturevalue is set too high, leading the model to generate incorrect units. - Symptom: The model call returns a 401 unauthorized error, or the target model cannot be accessed normally. Cause: The
AIPROXY_API_TOKENconfiguration is incorrect, or the correctAIPROXY_API_ENDPOINTfor the target model is not used. - Symptom: Model request parameter logs cannot be viewed, making configuration issues impossible to troubleshoot. Cause: The log recording switch for model calls is not enabled, or the output path for parameter logs is not configured.
How to confirm configuration is complete
A test question containing report fields and system clauses can be submitted, with returned results checked to confirm coverage of content from both data sources. Model call logs may be reviewed to confirm that actual values for configuration parameters such as maxTokens and temperature match preset values. A test question with ambiguous references may be entered, with verification that the model automatically resolves reference ambiguity and expands the question. A model call may be triggered, with checks performed to confirm that report values and units of measurement in generated results match correctly.
The values listed here are common starting points, and should be evaluated against the samples of the relevant deployment context.
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.