What the Data for This Category Looks Like
The investment research data for tourist attractions comes from five main sources: official operation reports, passenger flow statistics from cultural and tourism authorities, user reviews on OTA platforms, facility maintenance logs for the attractions, and temporary policy announcements. Data updates follow significantly different schedules: passenger flow data updates daily, temporary policies and facility maintenance records release as needed, and OTA reviews sync in real time. Most documents use structured report formats, with fields including instantaneous carrying capacity (unit: person-times/square meter), daily revenue (unit: yuan), and maintenance cycle (unit: days). They also include unstructured content such as operation summaries and tourist feedback text.
Constraints Imposed on Context and Token Workflows
Multi-source scenic spot data with varying update frequencies causes data redundancy and temporal conflicts during context recall, which increases token consumption. Long operation document paragraphs and multi-field structured reports raise the token usage per context segment. Without restricting the recall range, the large model’s context window limit may be triggered. Real-time passenger flow and review data require context to retain recent valid information. Residual expired data can reduce the accuracy of investment research conclusions. Cumulative context from multi-turn sessions will quickly exhaust token quotas.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
maxContext | Top 8 recall results | Scenic spot investment research data is multi-source and large in volume. Restricting the number of recalled entries avoids context token overflow |
chunkSize | 900–1100 characters | Scenic spot operation documents include long paragraphs of passenger flow analysis and policy text, adapting to single-segment token consumption and semantic integrity |
contextWindowTokens | 16384 token | Matches the basic context window of mainstream large models, supporting the token requirements of multi-turn investment research sessions |
similarityThreshold | 0.72–0.78 | Filters low-relevance OTA reviews or historical operation and maintenance data, reducing invalid token occupancy |
UPLOAD_FILE_MAX_SIZE | 400 MB | Monthly scenic spot operation reports and passenger flow data sets are usually large in size, adapting to batch upload requirements |
WORKFLOW_CONTEXT_STORAGE | Session-level persistence | Investment research workflows need to retain real-time operation data of the current scenic spot across nodes, avoiding context loss |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Errors
- Phenomenon: Tool nodes in workflows return the
Invalid JSON: Bad control charactererror. Cause: Line breaks and special punctuation in scenic spot operation documents were not escaped, leading to illegal JSON control characters in parsed context text. - Phenomenon: AI-generated investment research conclusions have temporal confusion after multi-turn sessions. Cause: Context time ranges were not restricted, and expired passenger flow data was recalled, resulting in conflicting temporal information in the context.
- Phenomenon: Context cannot be restored after a session times out. Cause: Session-level context persistence parameters were not configured, so context caches are cleared when sessions end.
How to Verify Correct Configuration
- Upload a monthly scenic spot operation document. Use the platform’s file parsing preview feature to confirm that parsed segment lengths fall within the configured
chunkSizerange. - Start a multi-turn investment research session, call the tool node repeatedly, and check that the number of returned context entries matches the
maxContextsetting, with no obvious redundant data. - Test scenic spot announcement text with special characters. Confirm that the tool node returns valid JSON with no errors, to verify that escape configurations work correctly.
- Close the session and re-enter the workflow. Check that the previous investment research context is restored, to confirm that persistence configurations are correct.
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.