What data for this category looks like
Core data for urban public transit business processing comes from public transit operation management systems. It includes documents such as card loss reporting, route inquiries, temporary route change notices, and service outlet processing procedures. Data is updated on two schedules: regular route adjustments and service outlet updates are synchronized monthly. Emergency adjustments such as temporary construction-related route changes are pushed in real time. Documents use a fixed five-module structure: processing item description, required materials, processing channels, processing time limits, and consultation methods. Fields include item name, specific location, processing hours, and contact phone number. Units include workdays, yuan, and individual units.
What constraints these characteristics impose on vector models and indexing
Real-time data updates require indexes to support incremental synchronization, to avoid resource consumption caused by full reconstruction. There are many structured fields, and business-specific terms such as station names and route numbers account for a high proportion. Vector indexes must balance semantic recall and structured field filtering. Individual documents have strong continuity in process steps, so chunking must avoid damaging the integrity of business logic. The update frequency of some emergency notices is irregular, so on-demand triggering of index updates must be supported. These characteristics require vector models to adapt to domain-specific vocabulary encoding, and index architectures to balance real-time performance and structured data processing capabilities.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk length | 800–1200 characters | Public transit processing procedure documents are mostly long texts with continuous steps. This length preserves the complete logic of a single process and avoids chunk breakage |
| Overlap length | 100–150 characters | Compensates for semantic gaps at chunk boundaries, and ensures contextual continuity of process steps |
| Similarity threshold | 0.72–0.80 | Keywords for public transit business processing have high recognition. This range filters out irrelevant recall results |
| Single search limit | Top 8 results | The number of optional channels and steps for business processing is limited. Too many recall results will interfere with user judgment |
| Reranking | Enabled | Results with high semantic similarity for public transit services must be sorted by business priority to improve user decision-making efficiency |
maxToken | 4096 | This parameter covers the context length requirements of most public transit business documents under FastGPT v4.17.0 |
Three common errors
- Phenomenon: Embedding model calls through third-party proxy services return connection failures or 400 errors. Cause: API keys and request addresses for the proxy service are not configured correctly, or the input format requirements of the model are not compatible.
- Phenomenon: After enabling reranking configuration, online recall test results do not sort as expected. Cause: Structured fields such as public transit business locations and processing time limits are not included in the weighted dimensions of reranking, leading to semantic sorting that does not match the business scenario.
- Phenomenon: Field missing errors occur during index construction. Cause: Required fields such as "processing time limits" and "consultation phone numbers" in public transit processing documents are not included in the index mapping, leading to loss of key business information during vector storage.
How to confirm the configuration is correct
- Upload a sample document for senior citizen card processing for public transit, run index construction, and check if system logs show prompts for successful chunking and normal vector generation.
- Enter the query "How to inquire about temporarily changed bus routes", and check if the number and similarity of recall results fall within the preset threshold range.
- After enabling the reranking function, compare the sorting logic of recall results, and confirm that it matches the processing priority of public transit outlets.
- Modify a piece of temporary route change information for public transit, trigger incremental index update, and check if the index is synchronized successfully.
The values provided here are common starting points, and should be evaluated against appropriate 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.