What data for this category looks like
Data for this category originates from the state-owned assets supervision investment supervision system, enterprise ERP and project management systems, industry market data, audit and financial statements. Update frequency is quarterly. Commonly processed documents include annual investment plans, project proposals, feasibility study reports, due diligence reports, asset appraisal reports, and post-investment evaluation reports. Most documents contain fields such as project core parameters, financial calculations, risk assessment, and post-investment performance. These documents must comply with state-owned assets supervision reporting specifications. They have no unified fixed format, but cover all investment process nodes.
Constraints on the Model Access and Configuration Link
Dispersed data sources requiring integration with multiple channels including state-owned assets supervision and internal enterprise systems mean the model access link must support context integration across multiple data sources to avoid data silos. The quarterly update frequency means the vector database synchronization cycle must match the business rhythm, and should not be too frequent or too delayed. Unstandardized document structures covering all investment process fields require context window configuration to adapt to long text processing needs, while also accommodating field differences across different documents. Additionally, severe consequences accompany business errors, so model-generated content must comply with state-owned assets supervision specifications, and targeted constraints must be applied to the generation logic.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to long text documents such as feasibility study reports and post-evaluation reports, covering core business fields and historical data |
maxTokens | 2000–3000 token | Meets the output length requirement for drafting a single document, and aligns with the standard length of state-owned assets reports |
temperature | 0.2–0.4 | Reduces generation randomness to ensure content complies with the rigor requirements of state-owned assets supervision |
AIPROXY_API_ENDPOINT | Fill in the corresponding node according to the deployment environment | Adapts to proxy configuration for multi-data source integration, ensuring secure access to internal systems |
AIPROXY_API_TOKEN | Fill in the proxy key generated during deployment | Ensures valid identity verification for model calls, avoiding permission denied errors |
toolChoice | auto | Automatically calls tools to integrate data from multiple systems, improving the accuracy of document drafting |
Three Common Configuration Errors
- Symptom: After adding a third-party model API key, the interface prompts that no available channels are available, and models cannot be loaded under the default group. Cause: The channel whitelist for the corresponding model has not been added in the proxy configuration, or the group permission for third-party model calls has not been enabled.
- Symptom: Inconsistent model lists appear in the chat and workspace, with some configured models not displayed synchronously. Cause: Model synchronization cache refresh has not been enabled in the system configuration, or the workspace model permission configuration does not match the global configuration.
- Symptom: Document generation takes too long, hard disk IO usage is high, and single-processing speed is suboptimal. Cause:
maxContextis set too large, and long texts have not been properly chunked, causing the model to load excessive context data and increasing storage and computing pressure.
How to Confirm Correct Configuration
- Check that the configuration values for
AIPROXY_API_TOKENandAIPROXY_API_ENDPOINTmatch the deployment documentation, and verify that a normal response is returned by calling the test interface. - Verify that the values for
maxContextandmaxTokensare suitable for the longest document currently being processed, by uploading a single complete feasibility study report to test that the generation process is not interrupted. - Cross-check the value of
temperature, by generating two post-evaluation reports on the same topic and confirming that content consistency meets business rigor requirements. - Review system logs to confirm that proxy requests for multi-data source integration have no timeout errors, and that the model call return format complies with the field specifications of state-owned assets reports.
The values provided 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.