Data Characteristics
Lead optimization regulation data in biopharmaceutical fields primarily comes from internal research and development project documents, laboratory records, computational simulation reports, and external regulatory databases. This data updates infrequently, typically with project phase progression or regulatory revisions, such as quarterly or semi-annually. Document structures are mostly semi-structured, including PDF regulation files, Word-format SOP (Standard Operating Procedure) documents, and some structured parameter tables stored in JSON or XML. Fields and units are highly specialized. Examples include compound IC50 values (unit nM), ADME/Tox parameters (e.g., LogP, TPSA), and synthesis route step descriptions. This involves extensive chemical structures, biological activity data, and pharmacokinetic indicators.
Constraints from HTTP Interface and External Systems
The low update frequency of lead optimization regulation data means FastGPT does not require high polling frequency when pulling data via HTTP interfaces. Implement event-driven or scheduled tasks (e.g., daily) for incremental synchronization. Semi-structured document formats, especially PDF and Word files, require the interface to support file uploads. The interface must integrate well with FastGPT's internal document parsing module to extract text content and key metadata. Specialized fields and units, such as IC50 values and pharmacokinetic parameters, require external systems to ensure standardized field naming and clear units when sending data to FastGPT. This prevents ambiguity and facilitates subsequent vectorization and retrieval. Additionally, due to sensitive research and development information, the interface needs to support authentication mechanisms like OAuth 2.0 or API Key to ensure data transmission security.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 200 MB | Lead optimization documents often include images and charts, leading to larger file sizes. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Complex PDF and Word document parsing can be time-consuming. |
maxContext | 8000 tokens | Regulation clauses and SOP process descriptions are often lengthy, requiring a large context. |
Chunk size | 800 characters | Ensures semantic completeness of individual paragraphs for better model understanding. |
Similarity threshold | 0.75 | Ensures accuracy in regulation Q&A, recalling the most relevant clauses. |
Rerank result count | Top 5 entries | Provides sufficient but not overwhelming reference information for user judgment. |
Common Pitfalls
- Calling the interface returns a
403 Forbiddenerror. This happens when the API Key or Token is incorrectly configured or has expired. - After uploading a large PDF document, the content is not fully parsed. This manifests as some regulation clauses being unretrievable. This is usually due to
PARSE_FILE_TIMEOUT_SECONDSbeing set too low, causing parsing to abort. - After calling the multimodal image recognition interface, image content is not recognized or recognition results are inaccurate. This may be because image data is not correctly encoded as a Base64 string or parameter field names do not match expectations.
Verification Steps
- Upload a lead optimization SOP document containing complex charts and long text. Confirm the document status shows "parsing completed" and check if the number of segments meets expectations.
- Use FastGPT's test interface to query with specific technical terms or regulation clauses from the document. Verify the system accurately recalls relevant passages.
- When an external system calls the HTTP interface to upload files or query, check if FastGPT returns an HTTP status code of
200 OK. Verify the data structure and content in the response body are correct.
The values given are common starting points and should be measured against your 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.