What the data for this category looks like
This category draws data from health supervision information systems, medical institution electronic registration systems, complaint and reporting platforms, and law enforcement inspection records. Data updates occur monthly. Commonly processed documents include supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Data fields cover institution qualification numbers, law enforcement inspection times, rectification requirements, and penalty items. No additional custom units are used. Core content revolves around institutional practice compliance and on-site supervision matters.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Data sources for this category are scattered across multiple systems. Multi-turn dialogue gradually guides users to retrieve qualification certificates and inspection records from corresponding systems to avoid missing information. The monthly update frequency requires the knowledge base synchronization mechanism to adapt to fixed cycles. Prompts include data timeliness verification logic. The variety of document types requires dynamic adjustment of field extraction rules for different documents during multi-turn dialogue, with dedicated guiding scripts for supervision inspection forms, rectification notices, and other document types. Core time-consuming tasks require multi-turn dialogue to focus on institutional qualification verification and rectification tracking, and compress unnecessary interaction steps.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Knowledge base single recall limit | Top 5 entries | Core documents for this category are concentrated in quantity; excessive recall will interfere with accurate extraction of qualification and rectification information |
| Context window length | 1200–1500 characters | Adapts to the standard length of single documents such as supervision inspection forms and rectification notices, avoiding truncation of key content |
chatId management | Persistently store per session | Tracks qualification verification progress in multi-turn dialogue, ensures interaction continuity, and adapts to FastGPT v4.17.0 session logic |
messages context truncation threshold | Retain the most recent 8 interactions | Focuses on the current law enforcement or rectification tracking dialogue, avoiding interference from irrelevant historical information with core logic |
variables configuration | Bind corresponding business knowledge base | Associates health supervision-related document libraries, ensuring retrieved content matches the business scenario |
| Question optimization switch | Enabled | Optimizes questions for professional terms in law enforcement scenarios, improving knowledge base retrieval accuracy |
Three common misconfigurations
- Phenomenon: The returned result when calling the dialogue interface does not carry a knowledge base association identifier. Cause: The knowledge base binding parameter is not configured in
variables, causing the session to not be associated with the corresponding business document library. - Phenomenon: Image URL content in the knowledge base cannot be output during dialogue. Cause: The prompt does not explicitly require extraction and return of image URLs, and the static resource access path mapping is not configured during local deployment.
- Phenomenon: Repeated requests for the same institutional qualification information occur during multi-turn dialogue. Cause: Verified qualification fields are not marked in session context management, leading to repeated guidance for users to provide the same content.
How to confirm the configuration is complete
- Initiate a simulated dialogue for medical institution qualification verification, and verify that the returned result extracts core fields such as practice license numbers.
- View session operation logs, confirm that
chatIdis correctly carried in each round of dialogue requests. - Test different types of business queries, confirm that the system can adapt to extraction logic for different documents such as supervision inspection forms and rectification notices.
- After calling the dialogue interface, check whether the returned result includes the expected knowledge base association information.
The values provided here are common starting points and should be evaluated against samples relevant to the specific deployment scenario.
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.