{ "info": { "name": "DIP Clustering Phase D", "_postman_id": "0c39a7cf-8fde-43f9-8fdb-5d8890ad7676", "description": "Spring clustering API examples with generic algorithm parameters and remote Python backend.", "schema": "https://schema.getpostman.com/json/collection/v2.1.0/collection.json" }, "variable": [ { "key": "baseUrl", "value": "http://localhost:8080" }, { "key": "runId", "value": "" } ], "item": [ { "name": "Create DBSCAN run for TED notices", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "url": { "raw": "{{baseUrl}}/v1/dip/clustering/runs", "host": [ "{{baseUrl}}" ], "path": [ "v1", "dip", "clustering", "runs" ] }, "body": { "mode": "raw", "raw": "{\n \"name\": \"TED notices DBSCAN PCA100\",\n \"algorithm\": \"DBSCAN\",\n \"executionBackend\": \"PYTHON_REMOTE\",\n \"reduction\": {\n \"method\": \"PCA\",\n \"targetDimensions\": 100\n },\n \"selection\": {\n \"documentTypes\": [\n \"TED_NOTICE\"\n ],\n \"representationTypes\": [\n \"SEMANTIC_TEXT\"\n ],\n \"embeddingStatuses\": [\n \"COMPLETED\"\n ],\n \"primaryRepresentationOnly\": true\n },\n \"parameters\": {\n \"eps\": 0.25,\n \"minSamples\": 5,\n \"metric\": \"euclidean\",\n \"normalizeVectors\": true\n }\n}" } } }, { "name": "Create HDBSCAN run for Leitstand TIME", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "url": { "raw": "{{baseUrl}}/v1/dip/clustering/runs", "host": [ "{{baseUrl}}" ], "path": [ "v1", "dip", "clustering", "runs" ] }, "body": { "mode": "raw", "raw": "{\n \"name\": \"Leitstand TIME HDBSCAN PCA50\",\n \"algorithm\": \"HDBSCAN\",\n \"executionBackend\": \"PYTHON_REMOTE\",\n \"reduction\": {\n \"method\": \"PCA\",\n \"targetDimensions\": 50\n },\n \"selection\": {\n \"documentTypes\": [\n \"TIME_ENTRY\"\n ],\n \"builderKeys\": [\n \"time-entry-structured-text\"\n ],\n \"embeddingStatuses\": [\n \"COMPLETED\"\n ],\n \"primaryRepresentationOnly\": true\n },\n \"parameters\": {\n \"minClusterSize\": 15,\n \"minSamples\": 5,\n \"metric\": \"euclidean\",\n \"clusterSelectionMethod\": \"eom\",\n \"normalizeVectors\": true\n }\n}" } } }, { "name": "Create Agglomerative run", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "url": { "raw": "{{baseUrl}}/v1/dip/clustering/runs", "host": [ "{{baseUrl}}" ], "path": [ "v1", "dip", "clustering", "runs" ] }, "body": { "mode": "raw", "raw": "{\n \"name\": \"TED notices Agglomerative\",\n \"algorithm\": \"AGGLOMERATIVE\",\n \"executionBackend\": \"PYTHON_REMOTE\",\n \"reduction\": {\n \"method\": \"PCA\",\n \"targetDimensions\": 100\n },\n \"selection\": {\n \"documentTypes\": [\n \"TED_NOTICE\"\n ],\n \"representationTypes\": [\n \"SEMANTIC_TEXT\"\n ],\n \"embeddingStatuses\": [\n \"COMPLETED\"\n ],\n \"primaryRepresentationOnly\": true\n },\n \"parameters\": {\n \"k\": 25,\n \"linkage\": \"average\",\n \"metric\": \"euclidean\",\n \"normalizeVectors\": true\n }\n}" } } }, { "name": "Start run", "request": { "method": "POST", "url": { "raw": "{{baseUrl}}/v1/dip/clustering/runs/{{runId}}/start", "host": [ "{{baseUrl}}" ], "path": [ "v1", "dip", "clustering", "runs", "{{runId}}", "start" ] } } }, { "name": "Assignments with text", "request": { "method": "GET", "url": { "raw": "{{baseUrl}}/v1/dip/clustering/runs/{{runId}}/assignments?includeText=true", "host": [ "{{baseUrl}}" ], "path": [ "v1", "dip", "clustering", "runs", "{{runId}}", "assignments" ], "query": [ { "key": "includeText", "value": "true" } ] } } } ] }