Query Tools
Template-based queries using self-learning system (20x faster)
Execute queries using learned templates from the Sprint 11 Self-Learning System. Reuses proven query patterns for 20x faster execution compared to cernion_ask. Falls back to LLM generation for new patterns.
Performance:
- Template Match: 50-200ms (20x faster than LLM)
- New Pattern: 2-8 seconds (same as cernion_ask, but learns for future use)
- Confidence Threshold: 0.6 (60%) default - higher = stricter matching
Use Cases:
- Recurring queries (regional capacity, installation counts)
- Performance-critical applications
- Batch processing (analyze multiple regions)
- Real-time dashboards
- API integrations requiring fast responses
When to Use:
- ✅ Recurring query patterns ("PV capacity in {region}")
- ✅ Performance-critical applications
- ✅ Batch processing
- ❌ First-time complex queries → use cernion_ask first
- ❌ Unstructured exploration → use cernion_ask
post/api/query/ask-learned
Request
- Base URL: https://api.cernion.de
- URL: https://api.cernion.de/api/query/ask-learned
- Auth: none declared
Query parameters
tokenstring
Optional Cernion MCP token as URL query parameter. If provided, it overrides CERNION_TOKEN for this request. Prefer Authorization Bearer header in production to reduce token exposure in URLs/logs.
Request body
Example request
{
"query": "PV-Leistung in Hessen",
"confidence": 0.7
}Response
Successful query execution with template information
Example response
{
"success": true,
"templateUsed": true,
"confidence": 0.85,
"executionTimeMs": 45
}Changes
No recorded changes to this operation across all 2 revisions of this API.