api_ollama 0.2.0

Ollama local LLM runtime API client for HTTP communication.
Documentation 
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//! OllamaClient extension for model tuning operations.
//!
//! Provides model tuning, training data upload, hyperparameter optimization,
//! benchmarking, and version management capabilities.

#[ cfg( feature = "model_tuning" ) ]
mod private
{
  use std::collections::HashMap;
  use crate::client::OllamaClient;
  use crate::tuning::{
    ModelTuningConfig, TrainingData, ModelTuningJob, TuningJobStatus,
    DataUploadResult, ModelBenchmark, BenchmarkResults, ModelVersion, TuningMethod
  };

  /// Extension to OllamaClient for model tuning
  impl OllamaClient
  {
    /// Create a model tuning job
    #[ inline ]
    pub async fn create_tuning_job( &mut self, config : ModelTuningConfig, training_data : TrainingData ) -> crate::OllamaResult< ModelTuningJob >
    {
      // Placeholder implementation
      Ok( ModelTuningJob
      {
        id : format!( "job_{}", fastrand::u64( .. ) ),
        config,
        training_data,
        validation_data : None,
        status : TuningJobStatus::Pending,
        created_at : std::time::SystemTime::now(),
        started_at : None,
        completed_at : None,
        latest_checkpoint_id : None,
        progress : None,
        resource_usage : None,
      } )
    }

    /// Upload training data
    #[ inline ]
    pub async fn upload_training_data( &self, _training_data : &TrainingData ) -> crate::OllamaResult< DataUploadResult >
    {
      // Placeholder implementation
      Ok( DataUploadResult
      {
        data_id : format!( "upload_{}", fastrand::u64( .. ) ),
        size_bytes : 1024,
        sample_count : 100,
        uploaded_at : std::time::SystemTime::now(),
      } )
    }

    /// Create hyperparameter optimization
    #[ inline ]
    pub async fn create_hyperparameter_optimization( &self, _search_space : HashMap<  String, serde_json::Value  > ) -> crate::OllamaResult< HashMap<  String, serde_json::Value  > >
    {
      // Placeholder implementation
      let mut config = HashMap::new();
      config.insert( "optimization_id".to_string(), serde_json::Value::String( format!( "opt_{}", fastrand::u64( .. ) ) ) );
      Ok( config )
    }

    /// Run model benchmark
    #[ inline ]
    pub async fn run_model_benchmark( &self, _model_id : &str, _benchmark : ModelBenchmark ) -> crate::OllamaResult< BenchmarkResults >
    {
      // Placeholder implementation
      Ok( BenchmarkResults
      {
        tasks : HashMap::new(),
        overall_score : 0.85,
        benchmarked_at : std::time::SystemTime::now(),
      } )
    }

    /// List model versions
    #[ inline ]
    pub async fn list_model_versions( &self, _model_name : &str ) -> crate::OllamaResult< Vec< ModelVersion > >
    {
      // Placeholder implementation
      Ok( vec![
        ModelVersion
        {
          id : "v1.0".to_string(),
          name : "llama2".to_string(),
          description : "Base model".to_string(),
          base_model : "llama2".to_string(),
          tuning_method : TuningMethod::FullFineTuning,
          created_at : std::time::SystemTime::now(),
          size_bytes : 4_000_000_000,
          performance_metrics : HashMap::new(),
        }
      ] )
    }
  }
}