What this use case’s data looks like
Data for policy and regulatory basis use cases in the basic telecommunications operations sector comes primarily from industry regulatory documents, communication service specifications, user rights protection regulations released by the Ministry of Industry and Information Technology and the State-owned Assets Supervision and Administration Commission, as well as internal compliance management manuals from telecommunications operators. Data update timing adjusts in real time with regulatory policy releases, and is synchronized immediately after new documents are issued. Document structures typically include fields such as policy document number, issuing authority, effective date, chapters and clauses, scope of application, and penalties. Individual document lengths vary widely, ranging from several hundred-word special notices to tens of thousands-word comprehensive management regulations.
Constraints imposed on model access and configuration
The wide range of policy document lengths requires context window configuration to support flexible adjustment. This avoids truncation of long documents and waste of computing resources on short documents. Structured field designs require model access to support precise identification of specified fields. This prevents confusion between different policy versions or effective dates. The high-frequency update feature requires knowledge base synchronization configuration to adapt to rapid update needs. It also ensures that model calls prioritize the latest version of policy data. In addition, compliance requirements for policy content require that the model call chain adheres to telecommunications industry data security standards.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the wide range of lengths of basic telecommunications operation policy documents, and fully carries the core content of a single policy document |
temperature | 0.1–0.3 | Ensures accuracy when quoting policy clauses, and reduces irrelevant statements and subjective speculation |
quoteMaxToken | 1500–2000 characters | Accurately extracts key fragments of policy clauses, and retains core identifying information such as document numbers and effective dates |
AIPROXY_API_ENDPOINT | Bind to the operator's exclusive compliance proxy address | Meets compliance requirements for data transmission in the telecommunications industry, and ensures secure calls to internal policy data |
AIPROXY_API_TOKEN | Use an encrypted and stored exclusive token | Prevents token leakage, and complies with the information security management specifications of the operator's internal systems |
toolChoice | none | Policy Q&A focuses on text understanding and clause quotation, and does not require triggering tool call workflows |
Three common configuration mistakes
- Phenomenon: The policy quotes returned by the model include irrelevant redundant characters or incorrect numbers. Cause: The
quoteMaxTokenparameter is not configured correctly, causing the extracted clause fragments to exceed the limited range and mix in non-target content. - Phenomenon: The knowledge base cannot retrieve newly released policy documents after synchronization. Cause: The
AIPROXY_API_ENDPOINTis not bound to the compliance proxy address, so synchronization requests are blocked and updated policy data cannot be obtained. - Phenomenon: The model's response includes meaningless numeric suffixes. Cause:
toolChoiceis not set tonone, triggering an unnecessary tool call workflow that generates redundant and unexpected content.
How to verify successful configuration
- Initiate a query targeting a known policy clause, and confirm that the policy document number and effective date cited in the returned results match the source document.
- Check the FastGPT v4.17.0 knowledge base synchronization logs to confirm that newly released policy documents have been successfully indexed.
- Test queries for long-text policy documents to confirm that the returned results are not truncated and no call errors occur.
- Verify the model call request logs to confirm that
AIPROXY_API_TOKENis correctly carried and there is no risk of plaintext leakage.
All provided configuration values are common starting points, and should be evaluated against local specific samples and use cases.
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.