What this category of data looks like
Data for this category originates from enterprise procurement platforms, public resource trading platforms, supplier databases, contract management systems, and audit issue repositories. It is updated daily. Commonly processed documents include procurement plans, requirement specifications, bidding documents, bid evaluation records, contracts, acceptance documents, and supplier complaint materials. Data fields include procurement entities, budget amounts, procurement methods, bid evaluation rules, performance acceptance status, and other relevant items. No unified fixed format exists, so adaptation to each organization’s internal procurement system is required.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Data is scattered across multiple internal and external systems. Multi-turn dialogue must retrieve different types of documents such as procurement plans and bid evaluation records step-by-step according to procurement process nodes, to avoid loading excessive unrelated data at once. Since documents have no unified fixed format, prompts must adapt to multiple document structures including procurement plans, bidding documents, and complaint materials, to extract fields required for compliance verification separately. Data is updated daily. Multi-turn dialogue must ensure that each call retrieves the latest versions of supplier databases and contract information. Errors in compliance verification have serious consequences. Multi-turn dialogue must clearly state the verification basis in each interaction, to avoid missing check items required by audit and discipline inspection requirements.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Context Window Size | 8000–12000 characters | Aligns with the total length of full bidding and procurement process documents, to avoid truncating key compliance verification content |
| Maximum Dialogue Turns | First 8 turns | Matches typical interaction nodes for procurement inquiries, covering the full process of requirement confirmation, compliance verification, and result feedback |
| Context Bound Variables | Bind procurement entity ID via variables | Accurately retrieves supplier database and procurement regulation data for the corresponding organization, to avoid cross-entity data confusion |
| Dialogue History Transmission | Truncate messages in reverse chronological order | Prioritizes retaining the latest compliance verification requests and historical replies, to ensure consistent interaction logic |
| Session Identifier Binding | Bind procurement project number via chatId | Distinguishes dialogue contexts for different procurement projects, to avoid cross-project data mixing |
| Verification Trigger Threshold | Calibrated based on actual testing | Adapts to each organization’s compliance verification strictness level, to avoid false positives or missed detections |
Three Common Misconfigurations
- Phenomenon: Intermediate AI replies inserted during the multi-turn dialogue process are appended to the final output result. Cause: The
messagesfor intermediate links are not explicitly filtered in the dialogue configuration, causing all interaction content to be included in the final context. - Phenomenon: Unconfigured title content appears in the dialogue log when calling the dialogue API interface. Cause: The default title generation parameter is not disabled in
variables, or the title field in the interface request is not cleared. - Phenomenon: Multi-turn dialogue fails to accurately match compliance documents for the corresponding procurement project. Cause: The
chatIdis not bound to the procurement project number, leading to cross-project context confusion and inability to retrieve correct bidding documents and bid evaluation records.
How to Verify Successful Configuration
- Initiate a simulated procurement inquiry dialogue using the FastGPT v4.17.0 platform, and check that the final output only includes user requirements and final replies, with no intermediate AI interaction content.
- Submit a test request via the API interface, view the dialogue log, and confirm that no unconfigured title content appears.
- Switch test data for different procurement projects, verify that the retrieved documents match the corresponding project, and no cross-project data mixing occurs.
- Adjust the context window size configuration, test performance when loading long documents, and confirm that the configured value meets the current business’s document length requirements.
The configuration values listed above are common starting points. They should be evaluated against the reader’s own specific samples and business requirements.
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.