What the data for this category looks like
Data sources for this category include China Government Procurement Network, local government procurement networks, fiscal integration systems, purchaser budget systems, and supplier credit records. The update frequency is daily. Daily processed documents include procurement requirements, procurement plans, bidding documents, bid documents, bid evaluation reports, winning bid announcements, procurement contracts, and responses to inquiries. All documents follow standardized formats under the government procurement law framework, and include fixed fields. For example, procurement requirements contain project budget and procurement content; winning bid announcements contain winning bidder name and winning bid amount, among others. The data structure is unified with clear fields. FastGPT v4.17.0 supports synchronization configuration for data sources of this category.
What constraints these characteristics impose on the model access and configuration link
Daily updated data sources require configuring incremental synchronization mechanisms when accessing models, to avoid excessive computing resource usage from full data pulls. Government procurement documents have standardized formats and fixed fields, so extraction logic adapted to structured fields must be configured to ensure accurate extraction of key information from bid evaluation reports, winning bid announcements, and other documents. When processing frequently updated documents such as responses to inquiries and change announcements, limit the number of documents processed per single run to prevent timeouts. Permission differences across different entities require configuring role-level model call permissions, to comply with government procurement regulatory requirements. Since errors have serious consequences, configure failure retry and log retention mechanisms, to avoid invalid bids, established complaints, or regulatory penalties caused by configuration errors.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Government procurement documents have long content per batch, need to accommodate complete context of multiple bidding documents and bid evaluation reports |
temperature | 0.1–0.3 | Ensure consistency in processing procurement-related text, avoid generating content that does not comply with regulatory standards |
toolChoice | auto | Automatically select between calling tools or generating results directly based on tasks, adapts to multiple scenarios such as drafting procurement requirements and verifying qualifications |
AIPROXY_API_ENDPOINT | Exclusive interface address for government procurement data sources | Used to connect to official data sources such as China Government Procurement Network, ensure compliance of data acquisition |
quoteMaxToken | 2000 token | Limit the length of a single referenced document, avoid context overflow, ensure readability of retrieval results |
Three common configuration errors
- Phenomenon: After enabling the re-ranking model, the order of knowledge base retrieval results does not change. Cause: The call threshold of the re-ranking model is not set to a reasonable range adapted to government procurement documents, or the re-ranking trigger condition is not enabled in the configuration.
- Phenomenon: The locally deployed content extraction module cannot extract government procurement documents normally, but the official online version runs normally. Cause: The local deployment does not synchronize the exclusive field mapping rules for government procurement documents, or lacks permission configuration for official data sources.
- Phenomenon: Workflow execution only returns single model call results, and cannot achieve integrated output after step-by-step processing. Cause: The node dependency relationship of the workflow is not configured correctly, or related settings for multi-model calls are not enabled.
How to confirm the configuration is complete
- In FastGPT v4.17.0, run a batch retrieval containing multiple government procurement documents, check whether the context length of the returned results matches the configured
maxContextrange. - Call the re-ranking model to process retrieval results related to procurement requirements, confirm whether the result order is rearranged by matching degree.
- Check the call logic of workflow nodes, confirm that multiple model steps can be connected in series as needed, and intermediate results can be hidden.
- Verify the access permission of the data source interface, confirm that the latest announcement data from China Government Procurement Network can be synchronized daily.
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.