What the Data for This Category Looks Like
The party building learning Q&A data for mining and mineral processing enterprises comes from internal party building system learning materials, policy documents issued by superior party committees, branch study records, and party member assessment ledgers. Updates occur in real time alongside the release of superior documents, with monthly centralized updates for monthly study plans and supporting assessment materials. Most documents are long texts with hierarchical headings, containing modules such as topic, issuing body, release date, main content, and supporting study requirements. Fields include document unique identifier, topic classification, release time, content word count, associated production branch identifier. Standard Gregorian dates, Chinese character counts, and branch numbers are used as units.
Constraints Imposed on Model Access and Configuration
Long text documents with hierarchical headings can cause single-document token counts to exceed standard limits. Adjust context processing parameters to avoid truncating critical content. Real-time updated party building documents require the knowledge base synchronization cycle to not exceed 24 hours. This ensures Q&A content aligns with the latest policies. Fields associated with production branches require adding classification filter conditions during the retrieval stage. This ensures Q&A content matches the corresponding branch’s study scope. The policy-oriented and standardized nature of party building content requires limiting the model’s random generation tendency. This avoids outputting content that does not conform to official expressions.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Most party building documents for mining and mineral processing are long texts with hierarchical structures, requiring sufficient context-related content to support accurate Q&A |
maxTokens | 2000–3000 token | Party building learning Q&A requires complete policy explanations or study key points to be output, avoiding truncation of critical expressions |
quoteMaxToken | 4000 token | Sufficient original reference fragments must be retained to ensure Q&A content conforms to the original specifications of party building documents |
temperature | 0.1–0.3 | Party building learning Q&A requires strict and standardized content, reducing the possibility of random generation |
AIPROXY_API_ENDPOINT | Intranet-deployed FastGPT proxy address for the enterprise | Data from mining and mineral processing enterprises must be transferred within the intranet to comply with state-owned enterprise data security management requirements |
AIPROXY_API_TOKEN | Exclusive token generated in accordance with enterprise identity authentication rules | Restrict unauthorized access to ensure the security of data and model calls |
Three Common Misconfigurations
- Phenomenon: The AI model option in the workflow is empty, and no available models can be selected. Cause: The corresponding model has not been configured in the model management page, or the configured model permissions have not been synchronized to the workflow module.
- Phenomenon: When using the doubao 1.6 model, no main text is displayed after the thinking content is output. Cause: The
maxTokensparameter has not been adjusted to a sufficient length to cover the total length of thinking and main text, resulting in truncation of the main text. - Phenomenon: There is a significant difference between the results returned by online conversation and API calls. Deviations still occur when
streamis set tofalseanddetailis set totruein API calls. Cause: Knowledge base association parameters and retrieval filter conditions have not been configured synchronously in the API request, resulting in inconsistent retrieval ranges between online and offline calls.
How to Verify Successful Configuration
- Submit an API test request with the correct knowledge base ID and retrieval filter parameters, and check that the returned results are consistent with the content of the online conversation.
- Enter the system settings page, check that the configuration formats of
AIPROXY_API_TOKENandAIPROXY_API_ENDPOINTmeet the requirements, with no empty values or invalid characters. - Enter the workflow editing page, check that the AI model drop-down list displays the connected models, and confirm that permission synchronization has been completed.
- Launch a long document Q&A test, and check that the context reference range of the returned content matches the configuration parameters of
maxContextandquoteMaxToken.
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.