What the data for this category looks like
Data for this category comes from the China Government Procurement Network, local government procurement networks, fiscal integration systems, procurer budget systems, and supplier credit records. The update frequency is daily. Daily processed documents include procurement requirements, procurement plans, bidding documents, tender documents, bid evaluation reports, winning bid announcements, procurement contracts, and responses to inquiries. Each document has fixed structural fields. For example, procurement requirements must specify procurement content and budget, bidding documents must include bid evaluation method clauses, and supplier credit records must be linked to unified social credit codes and credit status.
What constraints do these characteristics impose on the "model access and configuration" link
The data characteristics of this category impose clear constraints on model access and configuration: Datasets from multiple sources with daily updates require configurations that support batch synchronization of documents from different systems, to avoid delays and errors from manual imports. Diverse document structures and fields require configurations that adapt to format parsing of different documents, to ensure key fields are accurately extracted. High-risk consequences of errors require configurations to strictly control the compliance of generated content, to avoid drafting documents that do not comply with government procurement rules. Additionally, scenario differences across different users require configurations that flexibly adjust the focus of generated documents.
How to set the configurations
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 4000–6000 token | The total length of single associated documents for government procurement projects mostly falls between 2000–4000 characters. Sufficient context must be reserved to accommodate multiple reference documents and generated results |
maxTokens | 8000–12000 token | Single government procurement documents need to cover complete clauses, so sufficient tokens are required to support long-text generation and detail filling |
temperature | 0.3–0.5 | Government procurement documents must strictly comply with fixed rules, so low randomness is needed to ensure content compliance and uniform format |
AIPROXY_API_ENDPOINT | Consistent with the locally deployed large model service address | Requests must be directed to self-built or compliant large model services, to avoid sensitive data leaks from using public interfaces |
AIPROXY_API_TOKEN | Fill in according to the actual deployed proxy service key | Used for identity authentication, to ensure that only authorized requests are received by the accessed large model service |
toolChoice | auto | Corresponding tools must be automatically called based on document type, for example, automatically associating bid evaluation method reference data when generating bidding documents |
Three common errors
- Symptom: After deployment, calling the large model returns a 500 status code, and logs show proxy connection failure. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not configured correctly, causing requests to fail to reach the target large model service. - Symptom: Generated procurement requirement documents lack budget fields, with key information incomplete. Cause: The
maxContextparameter is not adjusted, causing imported budget system data to be truncated by the context window, so the model cannot extract complete fields. - Symptom: Generated response to inquiries has messy formatting, and does not meet the fixed typesetting requirements of government procurement documents. Cause: Generation rules are not configured for the structure of government procurement documents, causing the model to generate content that does not comply with industry-standard formats.
How to confirm the configuration is complete
- Check the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfiguration items, and initiate a test request to confirm that the large model connection is normal, with no authentication or address errors. - Import a standard government procurement bidding document and corresponding procurement requirement document, test generating a tender document template, and verify that key fields are complete.
- Adjust the
temperatureparameter, compare the content of two generated bid evaluation reports, and confirm that randomness meets compliance requirements. - Import multiple daily updated supplier credit records, test batch generation of qualification review documents, and confirm that synchronization and parsing have no delays.
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.