What the data for this category looks like
The data primarily comes from regulatory documents issued by state-owned assets supervision authorities, group internal charters, investment and financing due diligence reports, property right transaction filing documents, and annual operation summaries. Update frequency is adjusted according to business milestones. State-owned assets policy documents are updated in quarterly batches. Internal business documents are generated in real time as projects progress. Most documents follow formal official document formats, including uniform document numbers, supervision level markings, core clause items, and attachment lists. Fields include capital contribution amount, shareholding ratio, compliance requirement descriptions, and more. Units mostly use standard metrics common to state-owned assets systems, such as ten thousand yuan and percentage.
What constraints these characteristics impose on model access and configuration
The formal nature of state-owned assets supervision documents requires model outputs to match official standardized wording, so the model must be adapted to handle long document context capacity. Internal business documents are updated in real time as projects progress, which requires the model to quickly access the latest business data, so the context cache refresh cycle must be limited. Structured documents include clear fields such as capital contribution amount and shareholding ratio, which requires the model to accurately match field correspondences, so the tool call field recognition logic must be adjusted. The existence of long documents requires configuring reasonable context parameter thresholds to avoid content truncation that affects document integrity.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range/Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Documents for state-owned capital operation companies often include long policy citations and business data, requiring adaptation to long context needs |
maxTokens | 2000–3000 token | Document drafting requires generating complete paragraphs to avoid output truncation that affects document integrity |
toolChoice | auto | Structured field matching requires the model to independently select tool calls to adapt to field recognition needs |
temperature | 0.1–0.3 | Formal documents require precise wording, avoiding non-standard content that does not comply with state-owned assets regulations |
AIPROXY_API_ENDPOINT | http://your-proxy-address:port | Private model access requires specifying the correct API endpoint address to ensure normal request routing |
AIPROXY_API_TOKEN | Custom verification key | Ensures the security of model access and prevents unauthorized access |
Three Common Configuration Mistakes
- Symptom: After configuring
toolChoiceas auto, the model fails to trigger tool calls, and logs show no tool call request was generated. Cause: Tool call support was not enabled in the model access configuration, or the private model did not correctly implement the tool call protocol. - Symptom: A 400 error is returned when accessing the model via a third-party proxy, with a prompt indicating invalid parameters. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENwere not configured as required, or the request parameter format does not meet the model's requirements. - Symptom: After modifying the configuration file and restarting the container, the model list is not updated, and checking the
/app/data/configdirectory inside the container shows no effect. Cause: The modified configuration file was not mounted to the corresponding container directory, or the configuration file has syntax errors.
How to Confirm the Configuration Is Successful
- Upload a long document from a state-owned capital operation company, and check whether the model can fully load and recognize the structured fields within it.
- Initiate a document drafting request, and check whether the model can automatically trigger tool calls to match preset fields such as capital contribution amount and shareholding ratio.
- Check whether the wording of the document returned by the model complies with the formal standards of the state-owned assets system, with no obvious non-compliant content.
- Check the system logs to confirm that parameters such as
maxContextandtemperaturein API requests match the configured values.
The values provided are common starting points and should be evaluated against the deploying organization’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.