What this category of data looks like
Data sources for this category include the State-owned Assets Supervision and Administration Commission (SASAC) investment supervision system, enterprise ERP and project management systems, industry market data, audit and financial statements, with a quarterly update frequency. Commonly processed documents include annual investment plans, project proposals, feasibility study reports, due diligence reports, asset appraisal reports, and post-investment evaluation reports. Structured fields such as project number, investment amount, and project initiation approval nodes are included, alongside unstructured text such as technical demonstrations, financial calculations, and investment decision meeting minutes. Fields and units align with general specifications for the corresponding business scenarios.
What constraints do these characteristics impose on the workflow orchestration stage
Quarterly data updates require workflows to support periodic batch data synchronization and verification, to avoid using expired industry market data or financial statements. Mixed processing of multiple document types requires workflow nodes to support automatic recognition and chunking of different document formats, while addressing differentiated needs for structured field extraction and unstructured text parsing. Cross-system data sources require configuration of cross-system pull rules to ensure data consistency across project initiation and post-evaluation links. Full-cycle document chains require workflows to connect links such as project initiation declaration, material review, investment decision meetings, and post-evaluation data collection. Each link retains traceable review nodes to meet state-owned asset supervision compliance requirements.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Config Item | Recommended Setting | Rationale |
|---|---|---|
| Question Optimization | Place before the agent node | First handle formatting and keyword redundancy issues in declaration materials to reduce the agent's parsing load |
| Single Search Limit | Top 8 entries | Match retrieval needs for multi-source documents, balancing recall accuracy and processing efficiency |
| Maximum Context | 12000 token | Adapt to context loading for long documents such as multiple feasibility study reports and due diligence reports |
variables | Bind fields such as project number and investment amount | Ensure that fields called by the workflow remain consistent with business data |
nodeId | Configure unique IDs in link order | Enable traceable workflow node jumps and audit status tracking |
| Reranking | Enable | Sort retrieved review materials by relevance to improve matching accuracy |
Three Common Mistakes
- Phenomenon: Workflow runs show failures, but response logs exist in the model backend. Cause: Port configuration restrictions in the deployment environment block data transfer between workflow nodes.
- Phenomenon: The prompt for the agent node does not process declaration materials as expected. Cause: The prompt configuration is not associated with the business fields bound to
variables, leading to missing key business information in the context. - Phenomenon: Configuring the question optimization component does not change the relevance ranking of review results. Cause: The question optimization component is not placed before the agent node, so no preprocessing is done on original declaration materials, and keyword precision for subsequent retrieval cannot be optimized.
How to Confirm Proper Configuration
- Run a single workflow test, check if node logs include the business fields bound to
variables, to confirm normal data transfer. - Review the workflow node order, confirm that the question optimization component is placed before the agent node and covers the current document type being processed.
- Check the
nodeIdconfiguration, confirm that each link's node ID is unique and arranged in execution order, verify jump logic via node status tracking. - Trigger a quarterly data synchronization test, check if pulled documents match updated content from business systems.
The values provided are common starting points and should be measured 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.