- Added `with_production_oracle` and `with_oracle` methods to `EconomicsManager` for custom oracle setups.
- Introduced `record_compute_with_gpu` method in `MeteringService` to handle GPU-specific pricing.
- Enhanced `CircuitBreakerManager` to streamline price recording and state checking.
- Expanded `CrossChainOracle` with a builder pattern for easier configuration and added methods for managing pending packets.
- Introduced `PriceOracleBuilder` and `OracleFactory` for creating price oracles with various feeds.
- Added volume discount functionalities in `PricingEngine` for better pricing strategies.
- Improved `ContentResolver` with configuration management and health check features.
- Enhanced `ProverConfig` accessibility in `ProofSubmitter` and `Verifier` for better integration.
- Added utility methods in `SmtContext` for managing SMT-LIB scripts and assertions.
Adds comprehensive model management and training capabilities:
synor-compute (Rust):
- ModelRegistry with pre-registered popular models
- LLMs: Llama 3/3.1, Mistral, Mixtral, Qwen, DeepSeek, Phi, CodeLlama
- Embedding: BGE, E5
- Image: Stable Diffusion XL, FLUX.1
- Speech: Whisper
- Multi-modal: LLaVA
- ModelInfo with parameters, format, precision, context length
- Custom model upload and registration
- Model search by name/category
Flutter SDK:
- Model registry APIs: listModels, getModel, searchModels
- Custom model upload with multipart upload
- Training APIs: train(), fineTune(), trainStream()
- TrainingOptions: framework, epochs, batch_size, learning_rate
- TrainingProgress for real-time updates
- ModelUploadOptions and ModelUploadResult
Example code for:
- Listing available models by category
- Fine-tuning pre-trained models
- Uploading custom Python/ONNX models
- Streaming training progress
This enables users to:
1. Use pre-registered models like 'llama-3-70b'
2. Upload their own custom models
3. Fine-tune models on custom datasets
4. Track training progress in real-time
