What data for this category includes
Data for this category is sourced from the national public resource trading platform, local public resource trading platforms, project approval systems, and bidding supervision systems. The update frequency is daily. Documents processed daily include bid invitation announcements, qualification pre-qualification documents, bidding documents, bid submission files, bid evaluation reports, successful bid candidate notices, and successful bid result announcements. Documents contain fields such as bid section division, qualification requirements, bid evaluation expert records, objection and complaint content, and bill of quantities. All data is generated based on project construction and bidding-related rules.
Constraints on model access and configuration
The multi-platform source of this category’s data requires support for connecting to different format data source interfaces during configuration, to adapt to the output specifications of all types of public resource trading platforms. The daily update rhythm requires configuring incremental synchronization mechanisms to avoid excessive computing resource usage from full-volume data pulls. The diverse document structures require the model to support field parsing logic tailored to different bidding documents. Specific business fields such as bid sections, qualification requirements, and bid evaluation records require targeted context constraints to be configured during model access. Additionally, since errors can lead to severe consequences, strict control of model output accuracy is necessary to avoid compliance risks caused by incorrect replies.
Configuration parameters
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the long-text context of bidding documents, covering associated content across multiple announcements and documents |
maxTokens | 2000–3000 token | Controls the output length of single-round replies, aligning with the reasonable scope of business consultation |
quoteMaxToken | 1500–2000 token | Limits the length of referenced bidding document fragments, ensuring referenced content is precise and non-redundant |
temperature | 0.1–0.3 | Reduces randomness in model output, ensuring accuracy and compliance of replies related to bidding activities |
AIPROXY_API_ENDPOINT | Fill in the actual deployed proxy address | Connects to privately deployed model channels, adapting to local or cloud-based model services |
AIPROXY_API_TOKEN | Fill in the generated access key | Completes identity verification for model channels, ensuring the security of interface calls |
Three common configuration errors
- Entering an incorrect key when configuring
AIPROXY_API_TOKEN. The interface returns an insufficient permissions error. This occurs when the access key for the model channel is not correctly matched, or the key has expired and become invalid. - When connecting to a locally deployed model,
AIPROXY_API_ENDPOINTdoes not point to the correct proxy port. A 404 status code is returned during API calls. This occurs when the proxy address configuration does not match the actual deployment address of the model service. - Failing to adjust the
temperatureparameter for the bidding scenario, and setting it to an excessively high value. This causes the model’s generated replies to deviate from business compliance requirements, resulting in vague or inaccurate content. This occurs when the strictness requirements of bidding business are not considered, and the randomness of model output is not controlled.
How to verify successful configuration
- Log in to the model channel configuration page in the FastGPT v4.17.0 backend, and confirm that the configured model channel status shows normal connection.
- Upload a local bid invitation announcement fragment, initiate targeted consultation, and verify that the model can correctly extract relevant business field content.
- Check the interface call logs to confirm there are no permission errors, 404 status codes, or timeout exceptions.
- After adjusting the
maxContextparameter, verify that the model can fully associate related information across multiple bidding documents.
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.