Data Characteristics for This Category
Phase I clinical research data originates from early trials involving a small number of healthy volunteers or specific patient populations. Data update frequency is relatively low. Updates typically occur at key milestones such as study design, ethical approval, subject recruitment, drug administration, sample collection, and preliminary data analysis. Document structures are complex, including study protocols, informed consent forms, subject screening records, case report forms (CRFs), laboratory test reports, pharmacokinetic (PK)/pharmacodynamic (PD) data, and adverse event (AE) records. Fields and units are highly specialized. For example, dosage units are often mg/kg or mg, time points are precise to hours or days, and biomarker concentrations may involve ng/mL or μg/L. These often accompany complex medical terminology and abbreviations.
Constraints on "Deployment and Upgrade" from These Characteristics
The specialized and complex nature of Phase I clinical data imposes specific requirements on FastGPT deployment and upgrades. Low data update frequency, coupled with large single update volumes, means that knowledge base synchronization strategies require efficient merging and version management capabilities for incremental updates. This avoids resource waste from full re-indexing. Complex document structures, with mixed formats like PDF and Word, demand powerful structured information extraction capabilities from file parsers, especially for text embedded in tables and figures. Recognizing and normalizing specialized fields and units requires the model to accurately understand context during vectorization. This prevents recall bias caused by unit mismatches or terminology confusion. Furthermore, due to high data sensitivity, on-premise deployment is the mainstream choice. This requires higher standards for deployment package completeness, ease of use, and seamless upgrade continuity, to prevent service unavailability due to deployment failures or upgrade interruptions.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Phase I clinical study protocols and reports often contain numerous charts and detailed descriptions, leading to large individual file sizes. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large PDF or Word documents can be time-consuming, requiring a longer timeout to prevent parsing failures. |
Chunk size | 800 characters | Ensures the integrity of medical terms and context, preventing truncation of critical information. |
Recall count | Top 10 entries | Increases coverage during the initial retrieval phase, ensuring more relevant segments enter the re-ranking stage. |
Similarity threshold | 0.75 | Phase I clinical questions demand high precision; raising the threshold appropriately filters irrelevant results. |
Rerank result count | Top 5 entries | After re-ranking, the quality of the top few results is usually sufficient to support an answer. |
Common Pitfalls
- After uploading to the knowledge base, some PDF files appear empty. This occurs because the file parser fails to correctly process the text layer in encrypted or scanned PDFs.
- After Docker deployment, accessing the address shows
502 Bad Gateway. This usually indicates that the internal container service failed to start correctly or that port mapping configuration is incorrect. - After a new version upgrade, knowledge base retrieval quality significantly degrades. This may be due to incompatible vector model or tokenizer versions, leading to invalidation of old data indexes.
How to Verify Configuration
- Upload a Phase I clinical trial report PDF containing complex tables and medical terminology. Check if the knowledge base content is fully indexed.
- Attempt to retrieve information using questions with specialized terminology. Verify that the recall results include the expected key information and data.
- In the FastGPT interface, check
System Settings->Version Informationto confirm that the current deployed version matches the expected version number.
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.