Data Profile for This Category
Data sources for this category include China Government Procurement Network, local government procurement networks, fiscal integration systems, procurer budget systems, and supplier credit records. Update frequency is daily. Daily processed documents cover procurement requirements, procurement plans, bidding documents, tender documents, bid evaluation reports, winning bid announcements, procurement contracts, and responses to inquiries. Most document fields include project numbers, supplier qualification information, evaluation scoring items and other business-specific fields. Single document length varies widely, ranging from hundreds of characters for announcements to thousands of characters for complete bidding documents.
Constraints Imposed by These Characteristics on Model Access and Configuration
Daily updated and decentralized data sources require model access configuration to support multi-data source incremental synchronization, avoiding resource consumption from full repeated pulls. Wide range of document lengths, from short announcements to complete bidding documents, requires configuring processing logic adapted to different text lengths. Sensitive business content such as supplier qualifications and evaluation rules requires compliance verification links in the configuration, ensuring outputs meet relevant regulatory requirements for government procurement. Business processes require verifying qualifications and handling inquiries, so the model must accurately match document fields and business rules to avoid process errors caused by field identification deviations.
How to Configure Settings
The following are recommended configuration items for FastGPT v4.17.0:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the length range of government procurement documents, ensuring long texts such as procurement requirements and tender documents are fully included |
maxTokens | 4000 token | Controls the length of a single model output, avoiding timeouts or excessive resource usage caused by long outputs |
quoteMaxToken | 2000 token | Limits the total length of recalled and referenced text, ensuring the context does not exceed the model's window limit |
temperature | 0.1–0.3 | Reduces output randomness, ensuring result consistency in scenarios such as qualification review and rule matching |
AIPROXY_API_ENDPOINT | Corresponding internal compliance proxy service address | Meets sensitive data call requirements in government procurement scenarios, ensuring interface access complies with internal security specifications |
AIPROXY_API_TOKEN | Access key configured according to internal permissions | Ensures interface call security, preventing unauthorized access to sensitive business data |
Three Common Configuration Mistakes
- Phenomenon: The Rerank model does not activate during online recall testing, and the number of recall results does not match the configured value. Reason: The Rerank switch is not enabled in the knowledge base recall flow, or the Rerank model is not bound to the current application configuration.
- Phenomenon: When
quoteMaxTokenis set to a value above 3000, the large model does not receive context content. Reason: The sum ofmaxContextandquoteMaxTokenexceeds the maximum window limit supported by the model. The system automatically truncates the context, making it impossible to deliver. - Phenomenon: Request Time errors occur frequently during conversations. Reason: Reasonable interface timeout parameters are not configured, or the locally running large model response speed is too slow, exceeding the interface timeout threshold.
How to Confirm Proper Configuration
- Enter the application configuration page, check whether the values of parameters such as
maxContextandquoteMaxTokenmeet the length requirements of current business documents. - Initiate an online recall test, verify whether the recall results include expected document content, and check whether the number of results matches the recall configuration.
- Trigger a test conversation containing long documents, confirm that the large model can normally receive and process context content without truncation or timeout errors.
- Check the interface key and endpoint configuration, initiate a simple test request, and confirm that the interface call is normal without permission errors.
The configuration values listed above are common starting points. Adjust them based on your own specific samples and use cases.
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.