Deployment and Upgrade for Biopharmaceutical Equipment

Biopharmaceutical Equipment Data Characteristics

Biopharmaceutical equipment registration data typically includes technical requirements, inspection reports, clinical evaluations, risk management reports, and instruction manuals. Data originates from equipment manufacturers, third-party testing agencies, and clinical trial units. Data update frequency is relatively low, primarily occurring during equipment design changes, regulatory updates, or performance optimizations, usually once a year or as needed. Document structures combine structured and semi-structured data. For example, technical requirement documents contain detailed parameter lists and performance indicators, while risk management reports may be primarily narrative text. Fields and units are highly specialized. For instance, "sterilization temperature" is expressed in Celsius (℃) or Fahrenheit (℉), and "flow accuracy" is expressed as a percentage (%) or specific units (mL/min), often accompanied by specific testing methods and standard numbers.

Constraints on Deployment and Upgrade from Data Characteristics

The low update frequency of biopharmaceutical equipment registration data means that model training and index rebuilding do not need to be overly frequent. However, each update may involve a large volume of data, requiring the system to have efficient batch processing capabilities. The specialized and diverse data sources require FastGPT to support multiple file formats (e.g., PDF, Word, Excel) during data ingestion and to handle complex document structures. Specifically, the specialized fields and units in technical requirements and inspection reports demand high accuracy in text segmentation and entity recognition to prevent loss or misinterpretation of critical information during processing. The presence of semi-structured text necessitates optimizing segmentation strategies during deployment to balance context completeness with retrieval efficiency. Additionally, the prevalence of specialized terminology and abbreviations requires incorporating a domain-specific dictionary for enhancement and updating this dictionary synchronously during upgrades to improve question-answering quality.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`200 MB`	Technical documents and reports in biopharmaceutical equipment registration data can contain numerous charts, graphs, and detailed descriptions, leading to large individual file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Complex PDF document parsing, especially scanned documents with many images and tables, can be time-consuming. Extending the timeout prevents parsing interruptions.
`maxContext`	`8000`	Biopharmaceutical equipment technical parameters and regulatory clauses have strong contextual relevance. A longer context window aids in understanding specialized terminology and complex logic.
`Chunk size`	`800–1200 characters`	Paragraphs in registration data are often long and contain multiple related facts. Shorter segments can break context, while excessively long ones may introduce unnecessary noise and increase retrieval costs.
`Recall count`	`Top 8 entries`	This ensures retrieval results cover relevant information from multiple dimensions, such as technical requirements, inspection standards, and risk assessments, enhancing the comprehensiveness of answers.
`Similarity threshold`	`0.75`	The biopharmaceutical field demands extremely high information accuracy. A higher similarity threshold ensures retrieved results are highly relevant to the user's query, reducing interference from inaccurate information.

Three Common Mistakes

The system log displays Failed to parse document: "File too large". This usually indicates that the UPLOAD_FILE_MAX_SIZE configuration is too low to handle large registration documents.
Query results for equipment performance parameters show missing units or incorrect values. This may be due to professional fields being incorrectly truncated during text segmentation or incomplete parsing because PARSE_FILE_TIMEOUT_SECONDS is too short.
After local deployment, attempts to use online search features result in Network connection error: 111 Connection refused. This is often caused by firewall policies not opening the necessary ports for FastGPT services, or incorrect network proxy configuration in older FastGPT versions.

How to Verify Configuration

Upload a technical requirements document in PDF format containing complex tables and charts. Observe if the file parses correctly and generates retrievable content.
For an inspection report containing a specific sterilization temperature (e.g., 121℃) and flow accuracy (e.g., ±5%), ask questions about these parameters. Verify that the answer includes accurate values and units.
Query a specific fault code (e.g., E-001) from equipment operating procedures. Check if the system accurately retrieves the corresponding troubleshooting steps and if the number of retrieved items meets expectations.

Note: The values provided are common starting points. Measure against your own samples for optimal performance.

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.