The Graph API returns the prerequisite dependency graph for all courses in the catalog. Each node is enriched with bottleneck and demand scores from the most recent prediction run, allowing you to identify which courses are systemic bottlenecks in the curriculum.Documentation Index
Fetch the complete documentation index at: https://cors-lau.vercel.app/docs/llms.txt
Use this file to discover all available pages before exploring further.
Only courses that participate in at least one prerequisite relationship appear as nodes. Standalone courses with no prerequisites and no dependents are excluded from the graph.
GET /graph/
Returns the full prerequisite graph as a collection of nodes and directed edges.How edges are directed
Each edge represents a prerequisite relationship:source— the prerequisite course (must be completed first)target— the dependent course (requires the source)
source: "CSC201", target: "CSC243".
Scoring fields
Thebottleneck_score and latent_demand fields on each node are pulled from the latest prediction run at the time of the request. If no prediction run exists yet, both fields default to 0.
| Field | Formula / source | Interpretation |
|---|---|---|
latent_demand | Prerequisite completion analysis + influx inputs | Estimated students ready to enroll this term |
bottleneck_score | Count of downstream courses blocked if this course is unavailable | Higher = more curriculum impact if skipped |
| Impact score (derived) | latent_demand + (5.0 × bottleneck_score) | Courses with impact > 150 are systemic bottlenecks |
Responses
Array of course nodes. Only includes courses that appear in at least one prerequisite edge.
Array of directed prerequisite edges.
Identifying systemic bottlenecks
To flag courses that, if skipped, would block the largest number of students across the most downstream courses, compute the impact score client-side:impact_score > 150 are considered systemic bottlenecks and should be prioritized for offering regardless of the ML recommendation.