...

examples/aiexamples/jina.vsh

@@ -0,0 +1,86 @@
+#!/usr/bin/env -S v -n -w -gc none  -cc tcc -d use_openssl -enable-globals run
+
+import freeflowuniverse.herolib.clients.jina
+
+mut jina_client := jina.get()!
+health := jina_client.health()!
+println('Server health: ${health}')
+
+// Create embeddings
+embeddings := jina_client.create_embeddings(
+	input: ['Hello', 'World']
+	model: .jina_embeddings_v3
+	task:  'separation'
+) or { panic('Error while creating embeddings: ${err}') }
+
+println('Created embeddings: ${embeddings}')
+
+// Rerank
+rerank_result := jina_client.rerank(
+	model:     .reranker_v2_base_multilingual
+	query:     'skincare products'
+	documents: ['Product A', 'Product B', 'Product C']
+	top_n:     2
+) or { panic('Error while reranking: ${err}') }
+
+println('Rerank result: ${rerank_result}')
+
+// Train
+train_result := jina_client.train(
+	model: .jina_clip_v1
+	input: [
+		jina.TrainingExample{
+			text:  'Sample text'
+			label: 'positive'
+		},
+		jina.TrainingExample{
+			image: 'https://letsenhance.io/static/73136da51c245e80edc6ccfe44888a99/1015f/MainBefore.jpg'
+			label: 'negative'
+		},
+	]
+) or { panic('Error while training: ${err}') }
+
+println('Train result: ${train_result}')
+
+// Classify
+classify_result := jina_client.classify(
+	model:  .jina_clip_v1
+	input:  [
+		jina.ClassificationInput{
+			text: 'A photo of a cat'
+		},
+		jina.ClassificationInput{
+			image: 'https://letsenhance.io/static/73136da51c245e80edc6ccfe44888a99/1015f/MainBefore.jpg'
+		},
+	]
+	labels: ['cat', 'dog']
+) or { panic('Error while classifying: ${err}') }
+
+println('Classification result: ${classify_result}')
+
+// List classifiers
+classifiers := jina_client.list_classifiers() or { panic('Error fetching classifiers: ${err}') }
+println('Classifiers: ${classifiers}')
+
+// Delete classifier
+delete_result := jina_client.delete_classifier(classifier_id: classifiers[0].classifier_id) or {
+	panic('Error deleting classifier: ${err}')
+}
+println('Delete result: ${delete_result}')
+
+// Create multi vector
+multi_vector := jina_client.create_multi_vector(
+	input:          [
+		jina.MultiVectorTextDoc{
+			text:       'Hello world'
+			input_type: .document
+		},
+		jina.MultiVectorTextDoc{
+			text:       "What's up?"
+			input_type: .query
+		},
+	]
+	embedding_type: ['float']
+	// dimensions:     96
+)!
+println('Multi vector: ${multi_vector}')