Data Characteristics for This Category
Autoimmune disease regulations and SOP documents originate primarily from pharmaceutical R&D departments, clinical trial organizations, regulatory bodies' guidelines, and medical professional associations. Data update frequency is relatively low, typically aligning with new drug development, clinical guideline revisions, or regulatory policy adjustments, usually quarterly or semi-annually. Document structures are predominantly PDF, Word, or HTML, containing extensive specialized terminology, abbreviations, and cross-document references. Common fields include disease name, target, mechanism of action, clinical indications, contraindications, adverse reactions, dosage regimens, administration routes, and compliance requirements. Units involve medical-specific measurements like mg/kg, IU/mL, mmol/L, often accompanied by complex critical values and range descriptions.
Constraints Imposed by These Characteristics on "HTTP Interface and External Systems"
The low update frequency of autoimmune regulation documents means real-time data synchronization with external systems is not critical. Periodic polling or event-triggered updates can be used, avoiding resource waste from frequent requests. Diverse document formats require the HTTP interface to have robust file parsing capabilities, especially for extracting text from tables and images within PDFs and Word documents. Extensive specialized terminology and abbreviations necessitate preprocessing or integration with external medical dictionary services to ensure RAG recall accuracy. The complexity of fields and units requires the HTTP interface to effectively link structured information with unstructured text and validate numerical data. Cross-document references pose challenges for index construction and retrieval logic, requiring external systems to support graph construction or semantic linking to integrate knowledge across multiple documents and overcome the limitations of single-document retrieval.
Configuration Recommendations
| Configuration Item | Suggested Value | Rationale for This Value |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 200 MB | Autoimmune SOP documents often contain numerous charts and appendices, leading to large file sizes. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Complex PDF/Word document parsing is time-consuming; sufficient processing time must be allocated. |
maxContext | 1500 characters | Ensures complete pharmacological mechanisms or clinical pathway descriptions are captured within a single segment. |
Chunk size | 800–1200 characters | Balances context completeness with recall precision, reducing semantic fragmentation across segments. |
Similarity threshold | 0.75 | The autoimmune field demands high precision for terminology, avoiding erroneous recall from low similarity. |
Rerank result count | Top 5 entries | Guarantees the most relevant regulatory provisions are prioritized for display, aiding engineers in quick identification. |
Three Common Pitfalls
- Symptom: Workflow template imports successfully, but the actual workflow nodes are empty. Reason: The workflow definition JSON returned by the external system does not conform to FastGPT's expected format, leading to parsing failure.
- Symptom: HTTP interface calls to an external medical dictionary service return status code
403 Forbidden. Reason: API key expired or IP whitelist not configured, causing authentication failure. - Symptom: Dosage units or critical values are incorrect in knowledge base retrieval results. Reason: The file parser failed to correctly identify and extract numbers and unit combinations from the document, or unit standardization was not performed.
How to Verify Correct Configuration
- Upload an autoimmune SOP document containing complex tables and charts. Check if the document content is correctly parsed and usable knowledge blocks are generated.
- Use the HTTP interface to call external systems. Verify successful retrieval and synchronization of the latest regulatory updates, and check if the returned data structure matches expectations.
- Test knowledge base recall results for queries involving specific disease names, drug dosages, or contraindications. Cross-reference the returned regulatory provisions for accuracy and validate the correctness of numerical fields.
The values provided 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 2026-09-21.