Data Characteristics of This Category
Financial report data for biologics companies is primarily sourced from publicly disclosed regular reports: annual reports, semi-annual reports, and quarterly reports, released on official stock exchange platforms. Updates follow fixed disclosure cycles: annual reports are released within four months after the end of the fiscal year, and semi-annual reports are released within two months after the end of the first half of the fiscal year. Document structure mixes structured tables and unstructured text. Structured content includes revenue per individual product, production costs, batch issuance data, and similar items. Unstructured content includes R&D pipeline progress and clinical trial details. Professional fields include "per-unit product production cost", "batch issuance quantity", and "clinical trial enrollment count". Units include ten thousand yuan, doses, milliliters, and similar units.
Constraints on Retrieval and Recall
Publicly disclosed financial reports have inconsistent formats, with notable differences in document structure across companies. This requires retrieval logic to adapt to content extraction across multiple formats. Fixed disclosure cycles create demand for bulk data updates, requiring higher time limits for single import or incremental updates. A large number of professional fields and terms exist, such as "batch issuance quantity" and "mRNA vaccine pipeline". Retrieval models must adapt to professional semantics in the biologics field to avoid semantic bias from general-purpose models. Individual financial reports have long lengths; fixed-length splitting easily breaks the integrity of core business units such as R&D pipelines and revenue per product, reducing the accuracy of retrieval results.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunk_size | 1000–1500 characters | Adapts to the information density of professional paragraphs in biologics financial reports, avoiding splitting that disrupts the integrity of core units such as revenue per product and R&D pipelines |
chunk_overlap | 150–200 characters | Retains contextual information for cross-chunk professional terms, ensuring that associated context for terms such as "mRNA vaccine" and "batch issuance" is not lost |
recall_top_k | Top 8–12 results | Balances recall coverage and retrieval efficiency, adapting to multi-dimensional professional data query needs for financial reports |
similarity_threshold | 0.75–0.85 | Filters low-relevance general financial report statements, focusing on biologics-specific R&D, production, and revenue data |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to parsing time for long individual financial reports, avoiding timeout errors for large file parsing tasks |
vector_db_provider | Connect via custom vector database | Supports integration with existing vector database instances, reusing existing data storage resources |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and testing on local samples is recommended before finalizing values.
Three Common Configuration Mistakes
- Phenomenon: Retrieval results include unrelated content across business modules, such as mixing unassociated data from the "R&D pipeline" section and the "financial notes" section. Cause: Did not segment documents according to the directory structure of biologics financial reports, only used fixed-length splitting.
- Phenomenon: After connecting to a self-hosted Qdrant vector database instance, retrieval results are empty or return status code 404. Cause: Did not configure the mapping between the vector database collection name and the FastGPT knowledge base, or vector dimensions do not match.
- Phenomenon: Parsed financial report files have garbled text, with professional terms displayed as unreadable characters. Cause: Did not specify the encoding format for document parsing, and the default encoding does not match the actual encoding of biologics financial reports, such as GBK or UTF-8.
How to Verify Correct Configuration
- Upload a single biologics financial report file, review the parsed segmented results, confirm that core business modules are not split.
- Submit a retrieval query targeting biologics-specific business content, check the relevance of recall results, and adjust the similarity threshold to a range that meets business requirements.
- After connecting to a custom vector database, perform an index check on existing data, confirm that data synchronization status is normal.
- Test a parsing task for a single long financial report, confirm that the parsing task does not trigger a timeout error.
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.