What this category of data looks like
Port shipping policy and regulatory basis data primarily originates from officially published documents of the Ministry of Transport, directly affiliated maritime administrations, and local port management authorities. It also includes operational specifications and management rules formulated internally by port enterprises. Data updates follow no fixed schedule. New shipping supervision policies or port operation regulations trigger synchronous additions, while internal systems are updated irregularly alongside adjustments to business processes. Each document typically includes fields such as document number, issuing authority, effective date, applicable scope, and clause content. Document numbers follow the format “Jiao Shui Fa [Year] XX Number”. Date format uses YYYY-MM-DD. Clause content consists of continuous text paragraphs with no fixed segment length.
Constraints Imposed on Vector Models and Indexes by These Data Characteristics
The authoritative nature of official documents requires vector indexes to ensure full matching of metadata with the original text. Retain metadata such as document number and effective date during chunking to avoid loss of critical identifiers after splitting. No fixed update cycle requires indexes to support incremental updates and on-demand triggering, to avoid resource consumption from full reconstruction. Fixed document fields with clear applicable scopes require support for filtering by fields such as port type and issuing authority during retrieval. Vector indexes must therefore be associated with metadata fields. Significant variation in single-document length requires adjusting chunking strategies based on clause length, to avoid splitting complete clauses into multiple fragments that harm retrieval accuracy.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the typical length of single clauses in port shipping policy documents, to avoid splitting complete clauses |
| Overlap Length | 100–200 characters | Ensures semantic coherence between adjacent chunks, to avoid semantic breaks across clause chunks |
| Similarity Threshold | 0.75–0.85 | Filters low-match irrelevant policy content, to ensure relevance between retrieval results and queries |
| Single Search Limit | Top 20 results | Covers common retrieval scopes for port shipping policies, to avoid returning excessive redundant results |
maxToken | 4096 | Adapts to the maximum input length of external vector models, matching the text length of port policy document chunks |
defaultToken | Configured according to the actual settings of the external model | Unifies token counting standards within the system, to avoid differences in length calculations across models |
Three Common Misconfigurations
- Phenomenon: A vector model API call returns a 404 status code, and the console displays prompts such as “API does not exist” or “Resource not found”. Cause: The configured embedding model API address does not correctly point to the target service, access permissions for the corresponding model are not configured in the system, or the configuration does not adapt to long-text vector calculation requirements in port shipping scenarios.
- Phenomenon: After deploying a vector model without a GPU environment, the system displays “Insufficient memory” or “Model loading failed”. Cause: A lightweight embedding model adapted for CPU or ARM architectures was not selected, and a model package dependent on GPU acceleration was used directly, leading to insufficient runtime resources.
- Phenomenon: Exported knowledge base data can only be packaged as a whole knowledge base, and cannot be split by business category. Cause: Separate indexing of metadata fields was not enabled in the index configuration, so the export granularity can only be performed at the overall knowledge base level, which does not match the need to classify port shipping policies by business type.
How to Verify Successful Configuration
- Upload a single port policy document that includes a complete document number and effective date, and check that all metadata fields are retained in the chunked text with no omissions or truncation.
- Call the vector model API, input a segment of port policy clause text, and confirm that the returned vector data length matches the token count of the input text with no abnormal truncation.
- Set the similarity threshold to 0.8, retrieve for queries such as “port operation safety management specifications”, and confirm that the matching degree of returned results falls within the expected threshold range.
- Trigger an incremental update task, upload a new port policy document, and confirm that the system automatically indexes it into the knowledge base and it can be retrieved normally.
The values provided are common starting points and should be measured against the reader's 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 2026-09-28.