api_claude 0.4.0

//! Comprehensive embeddings tests for Anthropic API client
//!
//! MANDATORY INTEGRATION TEST REQUIREMENTS:
//! - These tests prepare for future embedding functionality
//! - Tests MUST fail initially to validate TDD approach
//! - Tests MUST use feature gating for embeddings functionality
//! - Tests MUST validate proper error handling for unsupported features
//!
//! Since Anthropic doesn't currently offer embeddings API, these tests serve as:
//! 1. Preparation for future Anthropic embeddings support
//! 2. Framework for third-party embedding integration
//! 3. Validation of proper API structure and error handling

#[ allow( unused_imports ) ]
use super::*;

#[ cfg( feature = "embeddings" ) ]
#[ allow( unused_imports ) ]
use the_module::*;

#[ cfg( feature = "embeddings" ) ]
mod embeddings_functionality_tests
{
  use super::*;

  /// Test embedding request structure and validation
  #[ test ]
  fn test_embedding_request_structure()
  {
    // This test will fail until embeddings module is implemented
    // Testing basic request structure
    let request = the_module::EmbeddingRequest::new()
      .model( "claude-embeddings-v1" )
      .input( "Test text for embedding" )
      .encoding_format( "float" );

    // Validate request structure
    assert!( request.validate().is_ok(), "Embedding request should be valid" );
    assert_eq!( request.get_model(), "claude-embeddings-v1" );
    assert_eq!( request.get_input(), "Test text for embedding" );
    assert_eq!( request.get_encoding_format(), "float" );
  }

  /// Test embedding response deserialization
  #[ test ]
  fn test_embedding_response_structure()
  {
    // This test will fail until embeddings module is implemented
    // Mock embedding response structure
    let mock_response = serde_json::json!({
      "object": "list",
      "data": [{
        "object": "embedding",
        "index": 0,
        "embedding": [0.1, 0.2, 0.3, -0.1, -0.2]
      }],
      "model": "claude-embeddings-v1",
      "usage": {
        "prompt_tokens": 5,
        "total_tokens": 5
      }
    });

    // Attempt to deserialize - will fail until types are implemented
    let response : Result< the_module::EmbeddingResponse, _ > =
      serde_json::from_value( mock_response );

    assert!( response.is_ok(), "Should deserialize valid embedding response" );

    let embedding_response = response.unwrap();
    assert_eq!( embedding_response.data().len(), 1 );
    assert_eq!( embedding_response.model(), "claude-embeddings-v1" );
    assert_eq!( embedding_response.data()[0].embedding().len(), 5 );
  }

  /// Test batch embedding requests
  #[ test ]
  fn test_batch_embedding_request()
  {
    // This test will fail until embeddings module is implemented
    let batch_request = the_module::EmbeddingRequest::new()
      .model( "claude-embeddings-v1" )
      .input_batch( vec![
        "First text to embed".to_string(),
        "Second text to embed".to_string(),
        "Third text to embed".to_string(),
      ] )
      .encoding_format( "float" );

    assert!( batch_request.validate().is_ok(), "Batch request should be valid" );
    assert_eq!( batch_request.get_input_batch().len(), 3 );
  }

  /// Test embedding validation and constraints
  #[ test ]
  fn test_embedding_validation()
  {
    // Test empty input validation
    let empty_request = the_module::EmbeddingRequest::new()
      .model( "claude-embeddings-v1" )
      .input( "" );

    assert!( empty_request.validate().is_err(), "Empty input should be invalid" );

    // Test model validation
    let invalid_model_request = the_module::EmbeddingRequest::new()
      .model( "" )
      .input( "Test text" );

    assert!( invalid_model_request.validate().is_err(), "Empty model should be invalid" );

    // Test input length constraints
    let very_long_input = "x".repeat( 100_000 ); // Very long text
    let long_input_request = the_module::EmbeddingRequest::new()
      .model( "claude-embeddings-v1" )
      .input( &very_long_input );

    // Should validate input length constraints
    assert!( long_input_request.validate().is_err(), "Extremely long input should be invalid" );
  }

  // TODO: Test embedding client integration when embeddings API is available
  // Removed test that used fake API keys

  /// Performance benchmark placeholder for embeddings
  #[ test ]
  fn test_embedding_performance_benchmark()
  {
    use std::time::Instant;

    // This test will establish performance expectations
    let start = Instant::now();

    // Simulate embedding generation time
    let test_texts = vec![
      "Short text",
      "Medium length text for embedding generation",
      "Much longer text that would be typical for document embedding use cases and should still process efficiently",
    ];

    for text in test_texts
    {
      // This will fail until implementation exists
      let request = the_module::EmbeddingRequest::new()
        .model( "claude-embeddings-v1" )
        .input( text );

      // Validate request construction time
      let _validation_result = request.validate();
    }

    let duration = start.elapsed();

    // Performance expectation : request construction should be fast
    assert!( duration.as_millis() < 100, "Request construction should be under 100ms" );
  }
}

#[ cfg( feature = "embeddings" ) ]
#[ cfg( feature = "integration" ) ]
mod embeddings_integration_tests
{
  use super::*;

  /// Test embedding API error handling for unsupported endpoint
  #[ tokio::test ]
  #[ ignore = "Requires workspace secrets file" ]
async fn test_embedding_api_not_supported_error()
  {
    // Since Anthropic doesn't support embeddings yet, test proper error handling
    let client = the_module::Client::from_workspace()
      .expect( "Must have valid API key for integration test" );

    let request = the_module::EmbeddingRequest::new()
      .model( "claude-embeddings-v1" )
      .input( "Test embedding request" );

    // This should return a proper "not supported" error
    let result = client.create_embedding( &request );

    // Should get a proper error indicating embeddings not supported
    assert!( result.is_err(), "Embeddings should not be supported yet" );

    let error = result.unwrap_err();
    assert!(
      error.to_string().contains( "not supported" ) ||
      error.to_string().contains( "not available" ) ||
      error.to_string().contains( "Not implemented" ),
      "Error should indicate embeddings not supported, got : {error}"
    );
  }

  /// Test embedding workflow placeholder for future implementation
  #[ tokio::test ]
  #[ ignore = "Requires workspace secrets file" ]
async fn test_embedding_workflow_placeholder()
  {
    let client = the_module::Client::from_workspace()
      .expect( "Must have valid API key for integration test" );

    // Test complete embedding workflow structure
    let texts = vec![
      "Document 1 content for similarity search",
      "Document 2 content for similarity search",
      "Query text for finding similar documents",
    ];

    // Test batch processing workflow
    for text in texts
    {
      let request = the_module::EmbeddingRequest::new()
        .model( "claude-embeddings-v1" )
        .input( text )
        .encoding_format( "float" );

      let result = client.create_embedding( &request );

      // Should fail with "not supported" error for now
      assert!( result.is_err(), "Embeddings not supported yet" );
    }
  }
}

#[ cfg( not( feature = "embeddings" ) ) ]
mod embeddings_feature_disabled_tests
{
  /// Test that embeddings functionality is properly feature-gated
  #[ test ]
  fn test_embeddings_feature_gated()
  {
    // When embeddings feature is disabled, types should not be available
    // This test validates proper feature gating

    // Compilation should succeed without embeddings types when feature is disabled
    // This serves as a compile-time test for proper feature gating
    assert!( true, "Feature gating working correctly - embeddings types not available" );
  }
}