Data Characteristics for This Category
R&D documents for bidding and tendering originate primarily from public procurement platforms of government or medical institutions. Data updates typically occur daily or weekly. Newly published, modified, or withdrawn tender information updates in real-time. Document types are predominantly PDF, with some Word or image files. Content includes project names, tender numbers, purchasing entities, product specifications, technical parameters, qualification requirements, and bid submission deadlines. Fields often use unstructured or semi-structured expressions. Units may involve drug dosages (e.g., mg/tablet), equipment performance parameters (e.g., rpm, W), or service periods (e.g., month, year). Synonyms, abbreviations, and non-standard expressions are common.
Constraints Imposed by These Characteristics on "Deployment and Upgrade"
The dispersed sources and high update frequency of bidding and tendering documents require the deployed system to have efficient file fetching and processing capabilities. The system must adapt to multi-source heterogeneous data ingestion. The presence of significant unstructured content and non-standard field expressions challenges model parsing robustness. This necessitates more refined pre-processing and post-processing logic. For PDF and image documents, text extraction accuracy directly impacts subsequent structuring effectiveness. OCR engine selection and configuration are critical. Additionally, R&D documents contain dense technical details and specialized terminology. This demands high model generalization capabilities. Deployment must consider mechanisms for synchronized updates of model versions and proprietary glossaries.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 100 MB | Tender documents often include attachments; file sizes can be large. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large file parsing takes longer; prevents parsing interruptions. |
Chunk size (Segment Length) | 800 characters | Ensures individual segments contain sufficient context while balancing recall efficiency. |
Similarity threshold (Similarity Threshold) | 0.78 | Balances recall rate and accuracy; reduces interference from irrelevant information. |
Rerank result count (Rerank Return Count) | Top 5 entries | Ensures returned results focus on key information; improves engineer reading efficiency. |
Three Common Mistakes
- An
Exception: 'usage' Keyeerror in the logs typically indicates incorrect API key configuration or insufficient quota. - A "file parsing failed" message after creating a new knowledge base may result from
PARSE_FILE_TIMEOUT_SECONDSbeing set too short, causing large file parsing to time out. - Retrieval results containing significant irrelevant information might be due to a
Similarity threshold(Similarity Threshold) set too low, leading to the recall of semantically distant content.
How to Verify Configuration
- Upload a typical tender document containing multiple tables and images. Check if FastGPT's knowledge base correctly identifies and extracts all text content.
- Conduct question-answering tests on key technical parameters within the document (e.g., "Injection" (injection), "mg/ml"). Verify the model accurately extracts and returns relevant numerical values and units.
- Simulate daily update frequency by batch importing a set of new tender documents. Observe system logs to confirm no backlog in the file processing queue and no significant errors.
- Randomly select specific fields from parsed documents (e.g., "Bid Submission Deadline" (bid submission deadline)). Search for them within the FastGPT interface. Verify the precision and completeness of retrieval results. Adjust
Similarity threshold(Similarity Threshold) based on actual business needs.
The values provided are common starting points. Measure 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.