What This Category of Data Entails
Daily documents under this category include bidding announcements, qualification pre-qualification documents, bidding documents, tender documents, bid evaluation reports, successful bid candidate announcements, and successful bid result announcements. Data sources include the national public resource trading platform, local trading platforms, engineering approval systems, and bidding supervision systems, with daily updates. Associated entities include development and reform departments, industry competent departments such as housing and urban-rural development, transportation, water conservancy, public resource trading centers, and bidding agencies. Content revolves around engineering project construction and the bidding law system, involving fields such as qualifications, performance, bill of quantities, construction period, and other fields, and has clear differences from government procurement scenarios.
What Constraints These Characteristics Impose on Model Access and Configuration
Daily updated data sources require model access configuration to support scheduled incremental synchronization, to ensure the timeliness of party building learning materials. Mixed input of multiple types of documents requires configuration to adapt to the structural characteristics of different documents, and accurately extract core content such as bid sections, qualification conditions, and bid evaluation records. Error consequences in the bidding scenario are directly linked to project progress and compliance, requiring model output to maintain rigor and avoid generating interpretations that deviate from official policies. At the same time, the scenario revolves around the bidding law system, requiring configuration of model parameters adapted to industry terminology to ensure that Q&A content complies with relevant specifications.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
maxContext | 8000–12000 token | Engineering bidding-related documents have relatively long lengths, and need to accommodate multiple announcements, bid evaluation reports and other party building learning materials |
temperature | 0.1–0.3 | Party building learning Q&A needs to maintain rigor in policy interpretation, and avoid generating content that deviates from official statements |
AIPROXY_API_ENDPOINT | Fill in according to the internally deployed proxy address | Adapt to internal data access permissions of public resource trading platforms |
maxTokens | 2000–3000 token | Ensure that single-round responses cover core party building learning points such as qualification requirements and bid evaluation rules |
quoteMaxToken | 1500 characters | Accurately quote the original text of bidding announcements and qualification pre-qualification documents, to ensure the authority of learning materials |
AIPROXY_API_TOKEN | Exclusive token allocated by the administrator | Control internal data access permissions and comply with the security specifications of public resource trading |
Three Common Misconfigurations
- An "API request timed out" error is returned in the interface, with a duration exceeding 60 seconds. The cause is that
maxContextis not adjusted to adapt to long documents, causing the model to time out when processing full bidding documents. - In versions of FastGPT below v4.17.0, the configuration entry for local models cannot be found. The cause is that the model access module of older versions was not optimized for data sources in public resource trading scenarios.
- The generated party building Q&A content contains incorrect bidding qualification requirements. The cause is that the value of
temperatureexceeds the range of 0.3, causing the model to generate content that does not comply with official policies.
How to Confirm Configuration Is Complete
- Submit test questions that include bidding qualifications and party building learning points, and check whether the returned content accurately quotes the original text of the bidding announcement.
- View the data source synchronization log to confirm that the latest documents from the public resource trading platform can be automatically pulled daily.
- Call the configured
AIPROXY_API_ENDPOINTto confirm that model responses can be returned normally. - Adjust
temperatureto 0.2 and verify that the rigor of the generated content meets the requirements of party building learning.
The values provided here are common starting points and should be measured against the user'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.