What the data for this category looks like
Data sources for this category include the China Government Procurement Network, local government procurement websites, fiscal integration systems, purchaser budget systems, and supplier credit records. The update frequency is daily. Service targets include purchaser units, government procurement supervision departments of finance departments, procurement agencies, and evaluation experts. Daily documents cover procurement requirements, procurement plans, bidding documents, bid documents, bid evaluation reports, winning bid announcements, procurement contracts, response to inquiries, and more. They include standardized fields such as procurement project number, budget amount, supplier qualification requirements, and bid evaluation rules. Document structure changes with business stages. Fields and formats of documents vary significantly across different stages.
What Constraints These Characteristics Impose on the Model Access and Configuration Link
Daily updated data sources require model access configuration to support incremental synchronization and scheduled pulling. This avoids resource waste caused by full repeated processing. Multiple document types with obvious field differences require configuration to adapt to parsing logic for different documents. This prevents Q&A deviations caused by field mismatches. The rigor of government procurement business requires that model outputs strictly rely on official document content. No unfounded statements may be generated. It also requires compatibility with relevant regulatory compliance requirements, and no deviation from general government procurement rules. In addition, Q&A needs vary greatly across different business subjects. Configuration must support flexible adjustment of Q&A focus.
How to Set the Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the long-text context of government procurement documents, avoids truncation of key content such as procurement requirements and bid evaluation rules |
toolChoice | auto | Supports the model to independently determine whether to read uploaded government procurement-related documents, matching the scenario of answering questions by combining document content in party building learning Q&A |
temperature | 0.1–0.3 | Ensures Q&A content is rigorous and compliant, conforms to the official expression style of government procurement, and avoids generating content that does not meet regulatory requirements |
vision | Disabled | Most government procurement-related documents are in plain text format, no visual parsing capability is required, which can save model call costs |
AIPROXY_API_TOKEN | Exclusive key assigned by the platform | Ensures the identity legitimacy of model calls, adapts to security requirements in government procurement scenarios |
maxTokens | 1500–2000 token | Controls the output length of a single round of Q&A, ensures replies are concise and rigorous, and complies with the specifications of procurement-related instructions |
Three Common Configuration Mistakes
- Phenomenon: After enabling simple mode to upload a government procurement-related PDF, the interface shows empty tool call logs. The model does not read file content or calls tools incorrectly. Cause:
toolChoiceis not configured as auto, or the requirement to answer by combining uploaded documents is not clearly stated in the Q&A prompt. - Phenomenon: An error is reported when uploading a government procurement PDF of approximately 3MB, and the knowledge base indexing progress stalls. Cause:
maxContextis not adjusted to adapt to long-text parsing, or the used model does not support complex field parsing of government procurement documents. - Phenomenon: When calling a VL model, the reply content contains expressions that do not comply with government procurement specifications. Cause: The configuration logic of ordinary LLMs and VL models is confused, and parameters such as
temperatureare not adjusted according to the text characteristics of government procurement documents.
How to Confirm the Configuration Is Complete
- Upload a typical government procurement bidding document, initiate a Q&A asking to interpret the procurement process combined with party building requirements, and verify whether the model calls the file tool to read the document content and answers by combining the content.
- Upload a government procurement-related PDF document of approximately 3MB, check whether the indexing progress is completed within a reasonable time without error prompts.
- View the model call logs, confirm that
AIPROXY_API_TOKENandAIPROXY_API_ENDPOINTare configured correctly, with no authentication failure or timeout records. - Adjust the
temperatureparameter to approximately 0.2, initiate a test, and confirm that the rigor of the reply content conforms to the official expression style of government procurement documents.
The values provided are common starting points and should be validated against samples tailored to the intended use case.
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.