What Data for This Category Looks Like
Data sources for this category include the national government procurement website, local government procurement websites, fiscal integration systems, procurer budget systems, and supplier credit records. Data is updated daily. Daily processed documents cover procurement requirements, procurement plans, bidding documents, tender documents, bid evaluation reports, winning bid announcements, procurement contracts, and objection responses. These correspond to different business workflows across entities including procurer organizations, fiscal department government procurement supervision offices, procurement agencies, and professional evaluation experts. Data fields are configured around the full procurement workflow, and include core information such as project identification numbers, supplier qualifications, and bid evaluation results.
Constraints for Multi-turn Dialogue and Prompt Engineering
Daily updated data sources require dialogue contexts to sync with latest dynamic information such as winning bid announcements and objection responses, to avoid using outdated data. Differentiated structures across multiple document types require prompt engineering to adapt to different business scenarios. For example, relevant budget data must be called when drafting procurement requirements, and credit records must be retrieved when verifying supplier qualifications. High error risk in business workflows requires multi-turn dialogue to accurately carry over historical queries, ensuring context continuity during qualification verification, objection handling and other links. Additionally, the decentralized nature of data sources requires dialogue to support precise recall of corresponding documents by project tags, to avoid mixing data across projects.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the procurement project as a fixed value | Ensure multi-turn dialogue context only belongs to the corresponding procurement project, avoid cross-project session confusion, and comply with FastGPT v4.17.0 session management specifications |
messages | Retain 10–15 rounds of context by conversation turn, with single round content not exceeding 2000 characters | Government procurement-related documents have relatively long lengths; overly long context increases inference latency. Retaining core historical conversations ensures continuity of business queries |
variables | Bind procurement project-specific tag variables, such as [procurement project ID], [supplier credit rating] | Accurately match procurement requirements, tender documents and other data for the corresponding project, avoid calling irrelevant documents across projects, and improve recall accuracy |
| Maximum context length | 8000–12000 token | Cover complete core document content such as procurement plans and bid evaluation reports, while controlling inference overhead, and adapt to document lengths in government procurement scenarios |
| Single search limit | Top 6 entries | Government procurement-related data entries are numerous; too many results cause distraction. The top 6 entries cover core business required content such as winning bid announcements and qualification review records |
| Question optimization | Calibrate based on actual testing | Questions in government procurement scenarios mostly involve professional terminology. Adjust optimization rules based on actual business scenarios to ensure returned content complies with industry norms |
Three Common Misconfigurations
- A 400 status code is returned when calling the
chat/completionsinterface. Cause: The role and content format of themessagesparameter are not correctly configured, or the knowledge base tag variable corresponding to the government procurement project is not bound. - The dialogue fails to recall specified categories of government procurement documents. Cause: The correct knowledge base tag parameter is not specified in the request, or the project-specific tag is not configured in
variables, resulting in recall scope covering irrelevant project data. - Dialogue context is lost, and the previous round of procurement requirement queries cannot be carried over. Cause:
chatIdis not correctly set as a fixed procurement project identifier, resulting in a new session context being generated for each request and loss of historical business information.
How to Verify Proper Configuration
- Initiate a query that includes the procurement project identification number, and verify that returned results only include documents such as bidding documents and winning bid announcements for the corresponding project, with no cross-project irrelevant content.
- Initiate 3 consecutive related queries, and verify that the
messagesparameter retains key content of historical conversations, with no context loss or jump errors. - Submit a prompt that includes government procurement professional terminology, and verify that returned results comply with format and content requirements of relevant documents, with no logical deviations.
- Call the interface and check that the returned status code is 200, with no parameter format error prompts, and ensure that parameters such as
chatId,messages, andvariablesare configured correctly.
The values listed here are common starting points, and should be evaluated against the user’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.