feat: Add gRPC protocol for Unsloth fine-tuning backend (Phase 1)

[localai-bot]

Implementation Progress: Phase 1 Complete

This PR implements Phase 1 of the Unsloth fine-tuning backend feature for LocalAI (Issue #9054).

Changes

• Proto Definition: Added TrainRequest and TrainResponse messages to backend/backend.proto
• gRPC Service: Added TrainStream server-streaming RPC for fine-tuning progress reporting
• Go Interfaces: Updated all gRPC interface files to support the new RPC
• Stub Implementation: Added unimplemented stub in pkg/grpc/base/base.go

Technical Details

The TrainStream RPC follows the existing streaming pattern (PredictStream/TTSStream) with:

• Client sends TrainRequest with hyperparameters, dataset info, and quantization settings
• Server streams TrainProgress messages with real-time training status

Next Phases

• Phase 2: Python backend implementation with Unsloth integration
• Phase 3: Go service layer for job management
• Phase 4: HTTP API endpoints
• Phase 5: React UI components
• Phase 6: GGUF export and model registration
• Phase 7: Build and CI integration

Related

Closes #9054

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[localai-bot]

Fixes Applied

Fixed compilation errors in core/services/training.go:

1. Changed xsync.SyncedMap.Get() calls to use Exists() + Get() pattern
2. Fixed ModelConfig.Model reference to use Name field
3. Replaced ListConfigs/GetConfig with GetModelConfig() API

See commit a034d83 for details.

[localai-bot]

Fix Applied

Updated to use instead of to fix the CI build failure.

The previous torch250 version was not available for the cu121 CUDA 12.8 build. Changed to torch260 which should be compatible.

See commit ae5ed50 for details.

[localai-bot]

CI Fix Applied

Fixed the cublas12 CI build failure by changing the unsloth torch version from to .

Issue: The package was not available on PyPI for the cu121 CUDA 12.8 build.

Solution: Changed to which is the latest available version compatible with cu121.

Commit: 85f3022

[localai-bot]

DCO Fix Applied

Fixed the DCO (Developer Certificate of Origin) check failure by adding proper sign-off to commits.

Additionally, fixed the cublas12 CI build failure by changing the unsloth torch version from to which is available for the cu121 CUDA 12.8 build.

The PR base branch has been updated to include the DCO fixes. Please review the updated branch.

Commit: bfecc4a

[localai-bot]

Fix Applied

Updated cublas13 unsloth torch version from torch250 to torch251 to fix CI build failures.

Issue: The torch250 package may not be available for cu126 CUDA 12.8 build.

Solution: Changed to torch251 which is the latest available version compatible with cu124.

Commit: 85515e5

[localai-bot]

Fix Applied

Fixed the CI build failure by adding a new file with the dependency.

Issue: The package requires the module during its build process, but doesn't declare it as a build dependency. This caused the build to fail with .

Solution: Added to which is installed before the unsloth package requirements, ensuring the module is available during the flash-attn build.

Commit: 79bb441

[localai-bot]

⚠️ BLOCKER: Manual Intervention Required

Date: 2026-03-21T01:40:43Z

Issue

This PR is blocked due to conflicts with upstream changes (PR #9088 merged TRL-based fine-tuning support). The original unsloth implementation has gRPC proto conflicts that require manual resolution.

Current State

• Branch only contains 1 commit (packaging fix)
• Full implementation (78+ commits) exists in backup branch:
• Conflicts in: , , , etc.

Required Action

A maintainer needs to review:

1. The TRL backend implementation in feat: add (experimental) fine-tuning support with TRL #9088
2. The unsloth implementation in the backup branch
3. Determine if both should coexist or be integrated

Recommendation

Consider either:

• Adding unsloth as a separate backend alongside TRL
• Rebasing unsloth implementation on top of TRL infrastructure

Status: PAUSED - Awaiting maintainer decision

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Automated monitoring detected this blocker. Unable to auto-resolve due to complex merge conflicts requiring contextual understanding of both implementations.