What this category of data looks like
Railway and highway investment research data comes primarily from official operation monthly reports, real-time road network scheduling APIs, engineering construction archives, freight rate announcement platforms, and passenger and freight volume statistical reports. Update frequencies cover real-time, daily, monthly, and annual cycles: real-time traffic and scheduling data updates every minute, passenger and freight volume data is aggregated daily, operation costs and infrastructure progress are released monthly, and annual financial reports and long-term planning documents are updated quarterly or annually. Three types of document structures exist: structured operation tables in Excel or CSV format, semi-structured feasibility study reports and operation analysis documents in PDF format, and standardized API response data. Fields and units have clear industry-specific attributes. For example, line mileage uses kilometers as the unit, passenger volume uses passenger trips as the unit, freight volume uses 10,000 tons as the unit, project construction cost uses 10,000 yuan per kilometer as the unit, and station stop duration uses minutes as the unit.
Constraints on model integration and configuration posed by these characteristics
Multi-source heterogeneous data formats require the model integration process to support both structured table parsing and long document chunking. Parsing rules adapted to different formats must be configured. Real-time high-frequency data requires setting reasonable timeout thresholds for model calls. This prevents delayed investment research efficiency caused by excessive waiting time. Industry-specific fields and units require models to strictly match preset fields when generating investment research conclusions. Without targeted configuration, unit confusion or missing fields may occur. The high proportion of long documents requires adjusting chunking parameters to avoid truncating key information. It also requires controlling the number of retrieved entries to prevent irrelevant operational data from interfering with analysis results.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Individual chapters of railway and highway feasibility study reports are typically 5000-10000 characters long. This value avoids truncating core engineering data and operation indicators |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large road network planning PDF documents include multi-chapter drawings and data tables, which take longer to parse. This value covers the complete parsing process |
retrieved entry count | Top 8–12 entries | Railway investment research data is often categorized by line or station. Too many retrieved entries will introduce irrelevant regional operational data. This value balances information density and relevance |
similarity threshold | 0.75–0.85 | Structured field matching requires high precision. This value filters low-match irrelevant reports and avoids interfering with investment research analysis |
model_fallback | Configured via model priority queue | Addresses scenarios where a single model is unstable. It automatically switches to a standby model when the primary model reports an error |
json_schema_enabled | Enabled | Forces the model to output structured data that complies with preset formats. This avoids missing fields or format chaos in generated content |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- A
503 Service Unavailableormodel call timed outerror occurs, and no automatic switch to the standby model is triggered. The cause is that no model fallback policy is configured, and no standby model queue is set up. - It is not possible to add domestic large models as index models, or document indexing fails after configuration. The cause is that no API adaptation rules for the corresponding vendor are added in the model integration configuration, or a compliant proxy address is not used.
- Generated investment research reports have missing fields or do not meet required formats, and only rely on prompt words to constrain output formats. The cause is that the JSON Schema verification switch is not enabled, so the model cannot be forced to follow the preset data structure.
How to verify successful configuration
- Upload a railway line operation report PDF, and check whether the parsed fields match the preset railway investment research data structure, and whether the units comply with industry standards.
- Trigger a model call to simulate a primary model error or timeout, and check whether the system automatically switches to the standby model to complete the request.
- After configuring JSON Schema verification, generate test data, and check whether the output content strictly follows the preset field rules and format requirements.
- Connect a domestic index model, upload a test document, and check whether the slicing and retrieval processes can be completed normally.
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.