feat: Enhance Jina client with improved classification API

- Update `jina.vsh` example to showcase the new classification API
  with support for both text and image inputs. This improves
  the flexibility and usability of the client.
- Introduce new structs `TextDoc`, `ImageDoc`, `ClassificationInput`,
  `ClassificationOutput`, `ClassificationResult`, and `LabelScore`
  to represent data structures for classification requests and
  responses. This enhances code clarity and maintainability.
- Implement the `classify` function in `jina_client.v` to handle
  classification requests with support for text and image inputs,
  model selection, and label specification. This adds a crucial
  feature to the Jina client.
- Add comprehensive unit tests in `jina_client_test.v` to cover
  the new `classify` function's functionality. This ensures the
  correctness and robustness of the implemented feature.
- Remove redundant code related to old classification API and data
  structures from `model_embed.v`, `model_rank.v`, and
  `jina_client.v`. This streamlines the codebase and removes
  obsolete elements.

examples/clients/jina.vsh

@@ -40,12 +40,18 @@ train_result := jina_client.train(
 
 println('Train result: ${train_result}')
 
-// // Classify
-// classification_result := jina_client.classify(
-// 	model:     .reranker_v2_base_multilingual
-// 	query:     'skincare products'
-// 	documents: ['Product A', 'Product B', 'Product C']
-// 	top_n:     2
-// ) or { panic('Error while classifying: ${err}') }
+// 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: ${classification_result}')
+println('Classification result: ${classify_result}')

lib/clients/jina/classification_api.v

@@ -130,3 +130,133 @@ pub fn (mut j Jina) train(params ClassificationTrain) !ClassificationTrainOutput
 	result := json.decode(ClassificationTrainOutput, response)!
 	return result
 }
+
+// TextDoc represents a text document for classification
+pub struct TextDoc {
+pub mut:
+	text string // The text content
+}
+
+// ImageDoc represents an image document for classification
+pub struct ImageDoc {
+pub mut:
+	image string // The image URL or base64-encoded string
+}
+
+// ClassificationInput represents a single input for classification (text or image)
+pub struct ClassificationInput {
+pub mut:
+	text  ?string // Optional text content
+	image ?string // Optional image content
+}
+
+// ClassificationOutput represents the response from the classify endpoint
+pub struct ClassificationOutput {
+pub mut:
+	data  []ClassificationResult // List of classification results
+	usage ClassificationUsage    // Token usage details
+}
+
+// ClassificationResult represents a single classification result
+pub struct ClassificationResult {
+pub mut:
+	index       int          // Index of the input
+	prediction  string       // Predicted label
+	score       f64          // Confidence score
+	object      string       // Type of object (e.g., "classification")
+	predictions []LabelScore // List of label scores
+}
+
+// LabelScore represents a label and its corresponding score
+pub struct LabelScore {
+pub mut:
+	label string // Label name
+	score f64    // Confidence score
+}
+
+// ClassificationUsage represents token usage for the classification request
+pub struct ClassificationUsage {
+pub mut:
+	total_tokens int // Total tokens consumed
+}
+
+// ClassifyRequest represents the JSON request body for the /v1/classify endpoint
+struct ClassifyRequest {
+mut:
+	model         ?string
+	classifier_id ?string
+	input         []ClassificationInput
+	labels        []string
+}
+
+// ClassifyParams represents parameters for the classification request
+@[params]
+pub struct ClassifyParams {
+pub mut:
+	model         ?JinaModel            // Optional model identifier
+	classifier_id ?string               // Optional classifier ID
+	input         []ClassificationInput // Array of inputs (text or image)
+	labels        []string              // List of labels for classification
+}
+
+// Classify inputs by sending a POST request to /v1/classify
+pub fn (mut j Jina) classify(params ClassifyParams) !ClassificationOutput {
+	// Validate that only one of model or classifier_id is provided
+	mut model_provided := false
+	mut classifier_id_provided := false
+	if _ := params.model {
+		model_provided = true
+	}
+	if _ := params.classifier_id {
+		classifier_id_provided = true
+	}
+	if model_provided && classifier_id_provided {
+		return error('Provide either model or classifier_id, not both')
+	}
+	if !model_provided && !classifier_id_provided {
+		return error('Either model or classifier_id must be provided')
+	}
+
+	// Validate each input has exactly one of text or image
+	for input in params.input {
+		mut text_provided := false
+		mut image_provided := false
+		if _ := input.text {
+			text_provided = true
+		}
+		if _ := input.image {
+			image_provided = true
+		}
+		if text_provided && image_provided {
+			return error('Each input must have either text or image, not both')
+		}
+		if !text_provided && !image_provided {
+			return error('Each input must have either text or image')
+		}
+	}
+
+	// Construct the request body
+	mut request := ClassifyRequest{
+		input:  params.input
+		labels: params.labels
+	}
+	if v := params.model {
+		request.model = v.to_string() // Convert JinaModel enum to string
+	}
+	if v := params.classifier_id {
+		request.classifier_id = v
+	}
+
+	// Create and send the HTTP request
+	req := httpconnection.Request{
+		method:     .post
+		prefix:     'v1/classify'
+		dataformat: .json
+		data:       json.encode(request)
+	}
+
+	mut httpclient := j.httpclient()!
+	response := httpclient.post_json_str(req)!
+	result := json.decode(ClassificationOutput, response)!
+	return result
+}

lib/clients/jina/jina_client.v

@@ -85,14 +85,6 @@ pub fn (mut j Jina) rerank(params RerankParams) !RankingOutput {
 	return json.decode(RankingOutput, response)!
 }
 
-@[params]
-pub struct ClassifyParams {
-pub mut:
-	model  string   @[required] // The classification model
-	input  []string @[required] // Input texts or image URLs
-	labels []string @[required] // Classification labels
-}
-
 // // Create embeddings with a TextDoc input
 // pub fn (mut j Jina) create_embeddings_with_docs(args TextEmbeddingInput) !ModelEmbeddingOutput {
 

lib/clients/jina/jina_client_test.v

@@ -55,3 +55,26 @@ fn test_train() {
 	assert train_result.classifier_id.len > 0
 	assert train_result.num_samples == 2
 }
+
+fn test_classify() {
+	time.sleep(1 * time.second)
+	mut client := setup_client()!
+	classify_result := client.classify(
+		model:  .jina_clip_v1
+		input:  [
+			ClassificationInput{
+				text: 'A photo of a cat'
+			},
+			ClassificationInput{
+				image: 'https://letsenhance.io/static/73136da51c245e80edc6ccfe44888a99/1015f/MainBefore.jpg'
+			},
+		]
+		labels: ['cat', 'dog']
+	) or { panic('Error while classifying: ${err}') }
+
+	assert classify_result.data.len == 2
+	assert classify_result.data[0].prediction in ['cat', 'dog']
+	assert classify_result.data[1].prediction in ['cat', 'dog']
+	assert classify_result.data[0].object == 'classification'
+	assert classify_result.data[1].object == 'classification'
+}

lib/clients/jina/model_embed.v

@@ -207,13 +207,6 @@ pub fn (t TextEmbeddingInput) dumps() !string {
 // 	return text_embedding_input_from_raw(raw)
 // }
 
-// TextDoc represents a document with ID and text for embedding
-pub struct TextDoc {
-pub mut:
-	id   string
-	text string
-}
-
 // ModelEmbeddingOutput represents the response from embedding requests
 pub struct ModelEmbeddingOutput {
 pub mut:

lib/clients/jina/model_rank.v

@@ -2,37 +2,6 @@ module jina
 
 import json
 
-// ClassificationAPIInput represents the input for classification requests
-pub struct ClassificationAPIInput {
-pub mut:
-	model  string   @[required]
-	input  []string @[required]
-	labels []string @[required]
-}
-
-// ClassificationOutput represents the response from classification requests
-pub struct ClassificationOutput {
-pub mut:
-	model  string
-	data   []ClassificationData
-	usage  Usage
-	object string
-}
-
-// ClassificationData represents a single classification result
-pub struct ClassificationData {
-pub mut:
-	classifications []Classification
-	index           int
-}
-
-// Classification represents a single label classification with score
-pub struct Classification {
-pub mut:
-	label string
-	score f64
-}
-
 // BulkEmbeddingJobResponse represents the response from bulk embedding operations
 pub struct BulkEmbeddingJobResponse {
 pub mut:
@@ -114,16 +83,6 @@ pub fn parse_ranking_output(json_str string) !RankingOutput {
 	return json.decode(RankingOutput, json_str)
 }
 
-// Serialize ClassificationAPIInput to JSON
-pub fn (input ClassificationAPIInput) to_json() string {
-	return json.encode(input)
-}
-
-// Parse JSON to ClassificationOutput
-pub fn parse_classification_output(json_str string) !ClassificationOutput {
-	return json.decode(ClassificationOutput, json_str)
-}
-
 // Parse JSON to BulkEmbeddingJobResponse
 pub fn parse_bulk_embedding_job_response(json_str string) !BulkEmbeddingJobResponse {
 	return json.decode(BulkEmbeddingJobResponse, json_str)