What this category of data looks like
Coal transportation and sales policy and regulatory basis data is sourced from public policy documents released by the National Energy Administration and local coal industry regulatory departments, as well as internal compliance systems of coal transportation and sales enterprises. Documents follow a structured clause format, and include policy document numbers, effective cycles, applicable transportation and sales links, quantitative indicator requirements, and other content. Fields cover transportation and sales subject qualifications, transportation capacity matching standards, tax payment rules, cross-regional transportation and sales approval requirements, and more. Data update frequency adjusts according to the pace of policy releases, with no fixed cycle. The length of a single document typically ranges from several thousand characters.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The structured clauses and multi-field characteristics of coal transportation and sales policy documents require precise matching of user-specified scenario parameters during multi-turn dialogue, to avoid confusion between policies across regions and categories. Long policy document lengths necessitate limiting the dialogue context window size, to prevent the model from confusing different clauses due to context overload. Users often obtain specific clauses, quantitative indicators or approval processes through multi-round follow-up questions, so recent rounds of interaction information must be retained to ensure the model can associate key conditions from historical questions. Additionally, policy effective cycles and applicable scopes vary. It is necessary to guide users to supplement key variables such as region and transportation and sales category during the initial dialogue stage, to narrow the Q&A scope.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Matches the typical length of single coal transportation and sales policy documents, and adapts to the context processing limit of FastGPT v4.17.0 |
messages parameter configuration | Retain the most recent 8–12 rounds of dialogue content | Adapts to the multi-round follow-up question scenario of coal transportation and sales policy Q&A, no need to retain redundant early interactions |
variables configuration | Bind region, transportation and sales category, effective time variables | Used to accurately limit the applicable scope of Q&A policies, filter irrelevant policy clauses |
| Dialogue history auto-cleanup threshold | Triggered after 720 seconds of no interaction | Avoids system resource occupation by session context that has not been interacted with for a long time |
chatId configuration | Generate unique identifier per user session | Distinguishes consultation sessions of different users, prevents context interference |
| Prompt template variable filling | Automatically replace example value, example value | Ensures Q&A is always based on the specific scenario specified by the user, improves matching accuracy |
Three Common Misconfigurations
- Unexpected rule display symbols appear at the end of dialogue response results: The phenomenon is that the policy Q&A content output by the model is attached with unconfigured trace display markers at the end. The cause is that the default rule output configuration of the model is not turned off in the prompt, or default rule prompt content remains in the template.
- Request failure or empty return result during concurrent calls: The phenomenon is that the session return result is empty or the status code is abnormal. The cause is that a reasonable number of retained dialogue history is not configured, resulting in excessive context length that exceeds the resource limit of concurrent processing.
- Incorrect matching of policy clauses during multi-turn dialogue: The phenomenon is that the policy clauses returned by the model do not match the region and transportation and sales category specified by the user. The cause is that the scenario variables specified by the user are not bound in
variables, resulting in the model calling irrelevant policy documents.
How to Verify Proper Configuration
- Initiate a test session, input a specific question that includes region and transportation and sales category, check whether the returned results only include policy clauses matching the scenario, with no irrelevant content.
- Initiate two consecutive follow-up questions, check whether the model can associate key conditions from historical questions and correctly continue the Q&A scope.
- Wait for the configured no-interaction threshold duration, then initiate a session again, check whether the initial prompt is reloaded with no historical context residue.
- Initiate multiple independent sessions, check whether the return results of different sessions do not interfere with each other, with no context interference.
The values listed above are common starting points, and should be evaluated 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.