Deployment and Upgrade for Stem Cell Therapy Regulations

Data Characteristics

Regulatory and standard documents in the stem cell therapy field originate from national drug administration agencies, health commissions, provincial drug administrations, and medical institutions. These include regulations, guidelines, ethical review documents, and clinical Standard Operating Procedures (SOPs). Documents are typically in PDF, Word, or web page formats. Update frequencies vary: national regulations might update annually or every few years, while internal SOPs could be revised quarterly or semi-annually based on clinical practice or new research. Document structures are complex, containing specialized terminology, abbreviations, charts, and cross-references. Fields and units involve quality control metrics for cell preparations (e.g., cell viability percentage, cell purity, bacterial endotoxin units EU/mL), clinical trial protocols (dosage units, treatment cycles), ethical approval processes, and adverse event reporting mechanisms. Accuracy requirements are extremely high.

Constraints Imposed by These Characteristics on Deployment and Upgrade

The complexity and update frequency of stem cell therapy regulatory documents impose specific requirements on FastGPT's deployment and upgrade. First, the complex specialized terminology and abbreviations in documents require strong semantic understanding from the model. This may necessitate customized dictionary injection to prevent recall bias. Second, the multi-source, multi-format nature of documents demands efficient file parsing capabilities for the knowledge base, especially for extracting text from tables and images within PDFs. The uncertain update rhythm means the system must support incremental updates and version management, ensuring answers are always based on the latest regulations while allowing historical version traceability. High accuracy requirements make parameter tuning crucial, particularly for recall strategies and similarity thresholds. Any minor error could lead to answers deviating from official regulations, posing potential compliance risks.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Policy documents and guidelines in the stem cell field often include numerous attachments or detailed descriptions, resulting in large file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Parsing complex PDF documents can be time-consuming; this avoids parsing failures due to timeouts.
`Chunk size`	`800–1200 characters`	Retains sufficient context to understand complex regulatory clauses while avoiding redundancy from excessive length.
`Recall count`	`Top 8 entries`	Ensures coverage of multiple relevant regulatory provisions, improving the comprehensiveness and accuracy of answers.
`Similarity threshold`	`0.78–0.85`	The domain is highly specialized; a high threshold filters irrelevant information, but too high might miss slightly less relevant yet valid information.
`maxContext`	`3000 Tokens`	Addresses the need to comprehensively analyze multiple regulatory provisions in Q&A.

Three Common Mistakes

Symptom: After a user query, the AI responds with "I cannot find relevant information" or provides irrelevant answers. Reason: The Similarity threshold (similarity threshold) is set too high, causing the system to abandon recall even when relevant documents exist because the threshold is not met; or Chunk size (segment length) is too small, leading to key information being cut and semantics lost.
Symptom: After uploading a large PDF file, the file status remains "processing" for an extended period or directly shows "parsing failed." Reason: PARSE_FILE_TIMEOUT_SECONDS is set too short, preventing large, complex documents from completing parsing within the allotted time; or the parser has insufficient capability to handle special charts or scanned documents within the PDF.
Symptom: The system returns stem cell therapy protocols or ethical review processes that do not align with the latest regulations. Reason: The knowledge base failed to perform incremental updates in a timely manner, or during the update process, old documents were not correctly marked as expired, leading to the recall of historical version information.

How to Confirm Correct Configuration

Select at least 5 representative stem cell therapy regulations or SOPs. Upload them to the knowledge base and verify that all file statuses show "completed," confirming successful file parsing.
Prepare a set of test questions targeting core regulatory clauses and common clinical issues. Query FastGPT with these questions. Check if the answers accurately cite original text from the knowledge base and verify that the number of cited original entries matches the expectation for the Recall count (recall count) parameter.
Simulate an incremental update: Upload a revised version of an old regulation. Then, re-ask questions related to that regulation. Verify that the system prioritizes recalling and citing the latest version of the regulation, and ensure the old version is no longer preferentially recommended.

Note: The values provided are common starting points and should be measured against specific 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.