What this category of data looks like
Data sources 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 business documents cover procurement requirements, procurement plans, bidding documents, tender documents, bid evaluation reports, winning bid announcements, procurement contracts, response to inquiries, and more. Documents contain fields such as procurement project number, supplier qualification information, bid evaluation scores, and inquiry matters. Some documents also include unstructured content like scanned files and attachments. The overall data has both structured fields and semi-structured text characteristics.
What constraints these characteristics impose on the model access and configuration link
Daily updated data sources require scheduled synchronization tasks. This ensures the latest procurement announcements, response to inquiries, and other content are used during consultation calls, preventing expired information from being output. Multiple types of business documents have differentiated fields. Dedicated recall and indexing rules must be set for different documents such as procurement requirements and bid evaluation reports to improve matching accuracy. Supplier credit record compliance verification needs require associating corresponding data source interfaces when accessing the model. This ensures reply content complies with government procurement regulatory requirements. Government procurement documents have strong regulatory attributes. Consultation replies output by the model must strictly match the expression standards of official texts, and content conflicting with the regulatory system must not appear.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Government procurement-related documents have relatively long lengths, requiring sufficient context to associate procurement requirements with consultation questions |
maxTokens | 2000–3000 token | Service consultation replies need to be clear and accurate, controlling output length to avoid redundancy |
quoteMaxToken | 1500–2000 token | Official document content such as procurement announcements and winning bid results must be cited, reserving sufficient space for quoted text |
temperature | 0.1–0.3 | Government procurement replies need to be rigorous and compliant, reducing randomness to ensure accurate expression |
AIPROXY_API_ENDPOINT | Fill in according to the official access address provided by the platform | Ensure the model call link is compliant and adapts to the stable access requirements of government procurement scenarios |
AIPROXY_API_TOKEN | Fill in according to the exclusive key assigned by the platform | Ensure identity verification security for interface calls and prevent unauthorized access |
Three common misconfigurations
- Symptom: A red number error is returned when calling the model. Cause:
AIPROXY_API_TOKENorAIPROXY_API_ENDPOINTis not configured correctly, resulting in failed interface identity verification or invalid address. - Symptom: Uploaded procurement-related images (such as scanned bidding documents) cannot be recognized when calling a multimodal model. Cause: The
visionconfiguration item is not enabled, and visual recognition capability is not activated. - Symptom: Retrieval results do not include the latest government procurement announcements. Cause: No scheduled synchronization task for data sources is configured, resulting in recalled documents being out of date.
How to confirm the configuration is complete
- Access the model configuration page of FastGPT v4.17.0, and verify that the content filled in
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENmatches the officially provided information. - Initiate a test consultation, enter common questions about government procurement projects, and check whether the model output cites accurate content from official documents and that the
quoteMaxTokenconfiguration takes effect. - Upload procurement-related image files, initiate a multimodal consultation, and confirm that the model can correctly recognize text and key information in the images.
- Adjust the
temperatureparameter to 0.2, initiate multiple test consultations, check the expression consistency of the output content, and confirm that the randomness meets expectations.
The values provided are common starting points and should be evaluated using samples from the target deployment scenario.
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.