What data for this use case looks like
Data for this use case is sourced from the national unified construction project EIA declaration and approval system, ecological environment zoning control results, pollution discharge permit platform, and monitoring data. Update frequency is irregular. Core daily documents include environmental impact assessment statements, environmental impact assessment report forms, approval applications, public participation explanations, technical evaluation opinions, and EIA approval documents. Each document includes fields such as project category, EIA level, pollution prevention measures, and public participation status. There are no unified fixed units. Parameter values are adjusted based on the specific details of each project.
Constraints imposed by these characteristics on multi-turn dialogue and prompting
Data sources are scattered, and updates have no fixed cycle. Multi-turn dialogue processes must support dynamic calls to the latest declaration, control, and monitoring data. Prompts must clearly distinguish exclusive fields for different documents. The content volume of core documents varies significantly. Environmental impact assessment statements have longer length. Single-turn dialogue context input length must be limited to avoid exceeding the model's context processing limit. There are no unified fixed units for fields. Prompts must guide the model to match corresponding parameters based on the specific project scenario. Approval errors directly affect project construction startup. Multi-turn dialogue must add a content verification link to ensure outputs meet core EIA approval requirements.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk length | 800–1200 characters | Adapts to the chapter content length of environmental impact assessment statements, avoids information fragmentation within chunks |
| Single search limit | Top 6 entries | Covers core document types required for EIA approval, avoids interference from redundant data |
| Context window limit | 4000 characters | Matches the core information volume of EIA-related documents, prevents exceeding the model's processing limit |
variables | Pre-set by project category | Used to pass basic project information, simplifies repeated input during multi-turn dialogue |
chatId | Bound to user sessions | Retains context association for multi-turn dialogue, ensures consistency of approval consultation |
messages | Stored with session updates | Records complete history of multi-turn interactions, supports contextually consistent consultation responses |
Three Common Misconfigurations
- Phenomenon: After calling the text content extraction link in a dialogue, returned fields are empty, and the preset specified response prompt is not triggered. Cause: No fallback trigger rule is configured for the text extraction link, so normal jump to the prompt link fails after extraction failure.
- Phenomenon: After configuring an English prompt and explicitly requiring the model to output in English, the model still returns only Chinese content. Cause: The language output rule for the model is not clearly defined in the prompt, or the model's default language preference is not overridden.
- Phenomenon: After uploading EIA-related documents, the model cannot parse the document content and returns a parsing failure prompt. Cause: The chunk configuration is not adjusted for the long text structure of EIA documents, leading to chunks exceeding the model's processing capacity.
How to Verify Successful Configuration
- Launch a simulated EIA project consultation, verify the contextual consistency of multi-turn dialogue, confirm that session information bound to
chatIdis not lost. - Upload an environmental impact assessment statement, check the integrity of chunked content, confirm that the chunk length matches the preset configuration.
- Trigger a text extraction failure scenario, verify whether the preset specified response prompt is triggered, confirm that the configured fallback logic takes effect.
- Check whether the preset basic project information in
variablescan be correctly passed to the dialogue process, confirm that the variable configuration is correct.
The values provided 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.