What the data for this category looks like
The policy data for advanced chemical materials comes from industry guidance catalogs and new material industry development plans issued by the Ministry of Industry and Information Technology and the National Development and Reform Commission, as well as local supporting rules and special subsidy policies issued by provincial and municipal industry and information technology departments. National-level policies are revised every 1 to 2 years, while local supporting rules are adjusted dynamically every quarter in line with industry changes. Documents include policy document numbers, issuing entities, effective dates, applicable sub-sectors, core clauses, application requirements and other content. Fields include unified national economic industry classification codes, units involve industrial quantitative indicators such as ten thousand tons per year and ten thousand yuan. Data formats are mainly official PDF files and structured web page text, with individual document lengths ranging from hundreds to tens of thousands of characters.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" link
Policy documents are lengthy and contain multi-level compliance clauses. Multi-turn dialogue must retain core identifiers such as policy document numbers and effective dates, otherwise confusion between new and old policies will occur. Local supporting rules are updated frequently, so prompts need to dynamically bind filter conditions based on the latest effective dates to avoid calling expired policy content. The national economic industry classification codes for sub-sectors need to be gradually supplemented by the user across multiple turns, so dialogue context must retain each round of supplementary information to ensure accurate recall scope. Long-text policies cannot be fully loaded into the model context at one time, so chunked recall integration is required, and the number of single recall entries must be limited to avoid context overload.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | 8000–12000 token | Adapts to the long text length of advanced chemical material policy documents, avoids truncating core policy identifiers and effective dates |
| Single Recall Limit | Top 6 entries | Controls the number of recalled policy entries, avoids confusion between clauses with different document numbers during multi-turn dialogue |
| Dialogue Record Retention Period | 30 days | Meets conventional compliance requirements for government and state-owned enterprise administrative data retention |
messages Parameter | Retain the first 10 rounds of dialogue context | Covers restricted information such as region and sub-category supplemented by the user across multiple turns, ensures context coherence |
variables Parameter | Bind region, sub-category, effective date fields | Automatically filters expired policies and accurately matches user's specific sub-segment needs |
chatId Parameter | Bind unique dialogue identifier | Distinguishes dialogue contexts of different users, avoids information confusion across dialogues |
Three common mistakes
- Phenomenon: When executing a long-text policy parsing task, the interface shows the task completed normally but throws the error "The value of 'offset' is out of range". Cause: The length of policy document chunks loaded at one time is not restricted, causing long text to exceed the model's input token limit and triggering an offset exception.
- Phenomenon: Fails to accurately recall regional advanced chemical material subsidy policies during multi-turn dialogue. Cause: Restricted fields such as region and sub-category are not bound in
variables, causing the recall scope to cover all policies and fail to match the user's specific needs. - Phenomenon: Dialogue record automatic clearance period exceeds expectations. Cause: The dialogue retention period is not set in accordance with compliance requirements, or the retention time is incorrectly configured to a value less than 30 days, which does not meet the specifications for administrative data retention by government and state-owned enterprises.
How to confirm the configuration is effective
Reference only; verify against the target FastGPT release and deployment documentation.
- Initiate a multi-turn dialogue including region and sub-category, confirm whether the recalled policies match the restricted conditions supplemented by the user.
- Review the dialogue record list, confirm that dialogue entries older than 30 days have been automatically cleaned up.
- Test a long-text policy parsing task, confirm that no offset-related errors occur.
- Access the
messagesparameter configuration interface, confirm whether the number of retained context rounds meets the preset 10-round requirement. - Check whether the
chatIdparameter is bound to the unique dialogue identifier, ensure that dialogue contexts of different users do not interfere with each other.
The values provided here 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.