What the data for this category looks like
Daily documents for this category include department budget drafts, project application forms, performance target forms, personnel expense calculation forms, budget approvals, and similar materials. Data mainly comes from the unified budget management system, department personnel establishment system, prior-year final accounts, project repository, and Ministry of Finance budget preparation notices. Data is updated annually, only during the new year’s budget preparation cycle. Document fields include personnel establishment count, project expense details, performance target scores, budget approval document numbers, and similar items. Corresponding units are usually ten thousand yuan, person, and point.
What constraints these characteristics impose on the "model access and configuration" link
The annual update data feature requires model access configuration to adapt to single-year cycle datasets, to avoid mixing cross-year data. Multi-source system data has format differences, so configuration needs to support parsing logic for mixed structured and unstructured documents. Single-year budget preparation involves a large number of detailed calculation and summary tasks, so the model needs to handle long text content. Context and token limits must therefore match the document length. At the same time, errors in budget preparation may lead to returns or failure to arrange funds. Configuration must ensure the rigor of model output, avoiding content that does not comply with business rules.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Department budget preparation related documents include multiple years of historical data, current calculation forms, and subordinate unit submission materials. Sufficient context is needed to associate business information from different sources |
maxTokens | 4000–6000 token | Single core documents such as personnel expense calculation forms and project application forms have relatively large content lengths. Complete parsing and output must be ensured |
temperature | 0.1–0.3 | Budget preparation requires accurate and rigorous output. A lower temperature value can reduce the probability of randomly generated content |
toolChoice | auto | The model needs to automatically determine whether to call tools to complete business operations such as subordinate unit budget data summary and expense calculation |
AIPROXY_API_ENDPOINT | Fill in according to the third-party model forwarding address | Adapt to third-party models accessed via OneAPI and other methods. Must match the model deployment address |
AIPROXY_API_TOKEN | Fill in according to the key generated by the third-party model | Used to verify the identity legitimacy of model access. Must match the key configured on the third-party platform |
Three common mistakes
- Phenomenon: The interface displays "No available channel for model XXX under current group default". Reason: The configured model channel has not been added to the default group, or
AIPROXY_API_TOKENdoes not match the key generated by the third-party platform. - Phenomenon: The budget calculation result returned by the model deviates from the actual data in the document. Reason: The
maxContextsetting is too small, resulting in loss of key historical budget data or detailed information submitted by subordinate units. - Phenomenon: The model returns parsing failure when processing large budget summary documents. Reason: The
maxTokenssetting is insufficient, which prevents the model from loading the complete document content and causes parsing interruption.
How to confirm the configuration is complete
- In the FastGPT v4.17.0 model management interface, select the configured model channel to initiate a test, and confirm that the prompt of successful test is returned.
- Upload a department budget draft document, initiate a service consultation question, and confirm that the model can accurately extract core fields such as personnel establishment count and project expense details from the document.
- Check the system logs to confirm that there are no error records such as "channel unavailable" or "token verification failure".
- After configuring the
maxContextandmaxTokensparameters, upload a test file with a length similar to the business document, and confirm that the model can load and parse the content completely.
The values provided 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.