9ecc2444aa
- Added `train` function to the Jina client for training classifiers. - Added `ClassificationTrain` struct to define training parameters. - Added `TrainingExample` struct to represent training data. - Added `ClassificationTrainOutput` struct for the training response. - Added a new `classification_api.v` module for classifier training functionalities. - Added a new `classify` function to the Jina client for classification tasks (currently commented out).
146 lines
3.8 KiB
V
146 lines
3.8 KiB
V
module jina
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import json
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// ClassificationAPIInput represents the input for classification requests
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pub struct ClassificationAPIInput {
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pub mut:
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model string @[required]
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input []string @[required]
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labels []string @[required]
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}
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// ClassificationOutput represents the response from classification requests
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pub struct ClassificationOutput {
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pub mut:
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model string
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data []ClassificationData
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usage Usage
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object string
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}
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// ClassificationData represents a single classification result
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pub struct ClassificationData {
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pub mut:
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classifications []Classification
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index int
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}
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// Classification represents a single label classification with score
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pub struct Classification {
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pub mut:
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label string
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score f64
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}
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// BulkEmbeddingJobResponse represents the response from bulk embedding operations
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pub struct BulkEmbeddingJobResponse {
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pub mut:
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job_id string
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status string
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model string
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created_at string
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completed_at string
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error_message string
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}
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// DownloadResultResponse represents the response for downloading bulk embedding results
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pub struct DownloadResultResponse {
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pub mut:
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download_url string
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expires_at string
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}
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// MultiVectorUsage represents token usage information for multi-vector embeddings
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pub struct MultiVectorUsage {
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pub mut:
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total_tokens int
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}
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// MultiVectorEmbeddingData represents a single multi-vector embedding result
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pub struct MultiVectorEmbeddingData {
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pub mut:
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embeddings [][]f64
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index int
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}
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// ColbertModelEmbeddingsOutput represents the response from multi-vector embedding requests
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pub struct ColbertModelEmbeddingsOutput {
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pub mut:
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model string
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object string
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data []MultiVectorEmbeddingData
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usage MultiVectorUsage
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}
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// HTTPValidationError represents a validation error response
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pub struct HTTPValidationError {
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pub mut:
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detail []ValidationError
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}
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// ValidationError represents a single validation error
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pub struct ValidationError {
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pub mut:
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loc []string
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msg string
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type_ string @[json: 'type'] // 'type' is a keyword, so we need to specify the JSON name
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}
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// Serialize and deserialize functions for the main request/response types
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// Serialize TextEmbeddingInput to JSON
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pub fn (input TextEmbeddingInput) to_json() string {
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return json.encode(input)
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}
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// Parse JSON to TextEmbeddingInput
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pub fn parse_text_embedding_input(json_str string) !TextEmbeddingInput {
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return json.decode(TextEmbeddingInput, json_str)
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}
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// Parse JSON to ModelEmbeddingOutput
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pub fn parse_model_embedding_output(json_str string) !ModelEmbeddingOutput {
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return json.decode(ModelEmbeddingOutput, json_str)
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}
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// // Serialize RankAPIInput to JSON
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// pub fn (input RankAPIInput) to_json() string {
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// return json.encode(input)
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// }
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// Parse JSON to RankingOutput
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pub fn parse_ranking_output(json_str string) !RankingOutput {
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return json.decode(RankingOutput, json_str)
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}
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// Serialize ClassificationAPIInput to JSON
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pub fn (input ClassificationAPIInput) to_json() string {
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return json.encode(input)
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}
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// Parse JSON to ClassificationOutput
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pub fn parse_classification_output(json_str string) !ClassificationOutput {
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return json.decode(ClassificationOutput, json_str)
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}
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// Parse JSON to BulkEmbeddingJobResponse
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pub fn parse_bulk_embedding_job_response(json_str string) !BulkEmbeddingJobResponse {
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return json.decode(BulkEmbeddingJobResponse, json_str)
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}
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// Parse JSON to DownloadResultResponse
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pub fn parse_download_result_response(json_str string) !DownloadResultResponse {
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return json.decode(DownloadResultResponse, json_str)
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}
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// Parse JSON to ColbertModelEmbeddingsOutput
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pub fn parse_colbert_model_embeddings_output(json_str string) !ColbertModelEmbeddingsOutput {
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return json.decode(ColbertModelEmbeddingsOutput, json_str)
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}
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// Parse JSON to HTTPValidationError
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pub fn parse_http_validation_error(json_str string) !HTTPValidationError {
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return json.decode(HTTPValidationError, json_str)
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}
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