What Data for This Category Looks Like
Biologics investment research data primarily comes from public announcements by national drug regulatory authorities, clinical trial registration databases, prospectuses of listed pharmaceutical companies, professional medical research reports, and patent disclosure documents. Data is updated at varying frequencies: regulatory approval announcements are updated in real time, clinical trial data is synchronized quarterly, and industry research reports are released weekly or monthly. Document structures include both structured fields and unstructured text. Structured fields include generic drug names, clinical trial phases, sample sizes, adverse reaction rates, and other fields with clear units. Unstructured content mostly consists of long texts such as clinical trial protocols and safety evaluation reports, with individual documents reaching tens of thousands of characters.
What Constraints These Characteristics Impose on Model Access and Configuration
The large number of structured biologics data fields and strict unit specifications require preset field alignment rules during model access, to prevent returned results from mismatching business fields. The high proportion of long text requires configuring context windows to adapt to long document parsing, to avoid truncation of key information. Varying update frequencies across different data sources require that incremental sync trigger logic differentiates between real-time and periodic update tasks. Additionally, biologics have high professional terminology barriers. Prompt engineering and reranking modules for general-purpose models must be adapted to professional corpora, otherwise relevant data cannot be accurately identified and associated.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Adapts to the parsing length of single long documents such as clinical trial reports, to avoid truncation of core data |
RECALL_TOP_N | Top 8–12 results | Covers multi-dimensional investment research information including clinical trials, approval progress, patents and others, to avoid missing key basis due to too few results |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the parsing time of large clinical trial datasets; default timeout settings cannot cover long document parsing |
RERANK_MODEL | Medical professional adaptation version | General reranking models have poor compatibility with biologics terminology; professional adaptation versions can improve association accuracy |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports uploading large files such as listed company prospectuses and large clinical trial datasets |
PROMPT_TEMPLATE | Prioritize matching structured fields + professional term calibration | Forces the model to align with fixed biologics field specifications, reducing professional term recognition errors |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volumes and business rules. Specific issues require targeted analysis. It is recommended to test on one’s own samples before finalizing settings.
Three Common Mistakes
- Scenario: Local large language model interface is connected, but no content is returned. Cause: Context alignment prompts for biologics professional terms are not configured. The model cannot recognize specialized fields, leading to empty output.
- Scenario: AI conversation node returns empty content or reports an error. Cause: Exception capture logic is not configured. When the model returns a format that does not meet preset structured field requirements, fallback processing is not triggered.
- Scenario: Response times out after enabling question optimization and result reranking, exceeding 30 seconds. Cause: The reranking model is not adapted to biologics professional corpora, leading to excessively long inference time. Additionally, the upper limit of recalled entries is not restricted.
How to Confirm Configurations Are Correctly Set
- Upload a single large clinical trial report, check if the parsed text fully retains core fields such as clinical trial phases and sample sizes, with no obvious truncation.
- Launch a simulated investment research query, verify that returned results prioritize matching preset structured fields, and professional term expressions conform to industry specifications.
- Enable the exception capture switch, simulate scenarios where the model returns empty values or reports errors, check if preset fallback prompts are triggered.
- Adjust recalled entry quantity and reranking model configurations, test query response duration, confirm compliance with business expected thresholds.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.