What the Data for This Category Looks Like
Data for this category originates from central state-owned enterprise and public sector procurement platforms, public resource trading platforms, supplier databases, contract management systems, and audit issue repositories, with daily updates. Commonly processed documents include procurement plans, requirement specifications, bidding documents, bid evaluation records, contracts, acceptance documents, and supplier complaint materials. Fields cover procurement methods, budget basis, supplier qualification criteria, scoring rules, performance acceptance information, and units related to amount, quantity, and time cycle.
Constraints on Multi-turn Dialogue and Prompt Engineering
The multi-source daily updated data, diverse document types, and differentiated fields of this category impose clear constraints on the multi-turn dialogue and prompt engineering link. Multi-source data requires gradual integration of ledger entries from different platforms via multi-turn dialogue to avoid data lag or inconsistency. Diverse documents require prompt engineering to preset adaptive rules for different documents such as procurement plans, bid evaluation records, and contracts to accurately extract corresponding fields. Full-chain compliance review requirements also require multi-turn dialogue to proceed step-by-step through links such as procurement method verification, supplier qualification review, and performance acceptance comparison, ensuring each verification step is supported by corresponding documents.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Unique identifier bound to a single procurement project | Isolate conversation context for different projects to avoid data confusion |
messages | Conversation turns split by compliance link | Advance through links such as procurement method verification and supplier qualification review step-by-step to ensure clear context |
variables | Field variables bound to procurement ledgers, bid evaluation records, etc. | Directly link to real-time data from business systems to reduce manual entry errors |
| Temperature parameter | 0.1–0.3 | Ensure rigorous and consistent output for compliance reviews, in line with fixed rule requirements for central state-owned enterprise and public sector tendering and procurement |
| Maximum context window | First 10–15 turns of conversation content | Adapt to daily updated multi-source data, avoid context overflow leading to missing compliance fields |
| Conversation log storage | Enable full storage | Facilitate review of audit trails, meeting compliance traceability requirements for disciplinary and audit work |
Common Misconfiguration Issues
Reference only; verify against the target FastGPT release and deployment documentation.
- Phenomenon: After binding business fields via variable references, the temperature parameter setting button disappears, making it impossible to adjust the model's generation rigor. Cause: The variable reference configuration is not correctly associated with the scope of the
variablesparameter, causing the interface control to be hidden. - Phenomenon: After calling the workflow via an interface to generate a compliance report, the running data fields in the conversation log are empty, making it impossible to troubleshoot exceptions in the review link. Cause: Full storage configuration for conversation logs is not enabled in the workflow, or the
chatIdparameter is not correctly bound to the session identifier.
How to Verify Proper Configuration
- Initiate a test dialogue targeting a procurement plan, check that the conversation context correctly associates the project identifier bound to
chatId, with no cross-project context confusion. - Enter the variable reference configuration interface, confirm that the temperature parameter setting button displays normally, and allows adjustment of parameter values.
- Trigger an interface call to the workflow to generate a test report, check that the conversation log generates complete running data, including input and output content for each turn of dialogue.
- Copy the generated Markdown format report, confirm that the content has normal line breaks, with no manual text selection pop-up prompt.
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.