v0.7

VoiceBlender/voiceblenderv0.7Jan 29, 2026by kaisopos

AI Summary

This release introduces major platform upgrades including Python 3.14 and PyTorch 2.9 support, alongside new inference engines like Fireworks and OpenRouter. It also adds rule-based evaluation judges, improved infrastructure with a one-line installer, and enhanced data format support.

Key Highlights

  • New inference engines: Fireworks and OpenRouter
  • Major platform upgrades: Python 3.14 and PyTorch 2.9 support
  • Rule-based evaluation judges for deterministic assessment
  • Infrastructure improvements: Nebius cloud provider and one-line installer
  • New data formats: XLSX and DOCX support

Breaking Changes

  • Dropped Python 3.9 support, minimum version is now Python 3.10
  • Deprecated alpaca_eval integration
  • Deprecated protobuf conversation definitions

New Features

  • Fireworks inference engine backend
  • OpenRouter inference engine backend
  • Rule-based evaluation judges with CLI integration
  • Metrics logging callback for training
  • Per-reward function configuration support
  • XLSX and DOCX support for synthesis and datasets
  • Few-shot sampling from sources during synthesis
  • Batch AttributeSynthesizer for batch processing
  • Nebius cloud provider as a new option
  • Kubernetes Skypilot support
  • ARM Docker support
  • One-line installer script (install.sh)
  • Optional telemetry via PostHog
  • Pre-trained custom model support
  • Loading spinner for inference operations

Full Release Notes

# Oumi 0.7 Release

## ✨ Highlights

This release brings major platform upgrades (Python 3.14, PyTorch 2.9), new inference engines, rule-based evaluation judges, and significant CLI/documentation improvements.

---



## 🚀 New Features

### Inference

- **Fireworks inference engine** - New backend for Fireworks AI (#2158)


```yaml
# Fireworks example (set FIREWORKS_API_KEY env var)
model:
  model_name: "accounts/fireworks/models/llama4-maverick-instruct-basic"
engine: FIREWORKS
```

```bash
oumi infer -i -c configs/recipes/llama4/inference/maverick_instruct_fireworks_infer.yaml
```
- **OpenRouter inference engine** - New backend for OpenRouter (#2168)

```yaml
# OpenRouter example (set OPENROUTER_API_KEY env var)
model:
  model_name: "anthropic/claude-sonnet-4.5"
engine: OPENROUTER
```
```bash
# Use via cli
oumi infer -i -c configs/apis/openrouter/infer_claude_4_5_sonnet.yaml
```

- **Loading spinner** - Visual feedback during inference operations (#2085)
- **Pre-trained custom model support** - Load your own pre-trained models (#2044)

### Evaluation

- **Rule-based judges** - Deterministic evaluation judges with CLI integration and examples (#2119, #2171)

```yaml
# configs/projects/judges/rule_based/regex_match_phone.yaml
judge_params:
  prompt_template: "{response}"

rule_judge_params:
  rule_type: "regex"
  input_fields:
    - "response"
  rule_config:
    pattern: "\\d{3}-\\d{4}"
    input_field: "response"
    match_mode: "search"
    inverse: false
```

```bash
oumi judge dataset -c regex-match-phone --input data/judge_input.jsonl
```

### Training

- **Metrics logging callback** - Log training metrics to disk (#2140)
- **Per-reward function configuration** - New `reward_function_kwargs` support (#2143)

```yaml
trainer_type: TRL_GRPO

reward_functions:
  - rubric_reward
  - gsm8k

reward_function_kwargs:
  rubric_reward:
    judge_panel_path: "configs/projects/judges/rubric_panel.yaml"
  gsm8k:
    strict: true
```

### Data & Synthesis

- **XLSX and DOCX support** - New formats for synthesis and datasets (#2148)
- **Few-shot sampling** - Sample few-shot examples from sources during synthesis (#2151)
- **Batch AttributeSynthesizer** - Batch processing support (#2181)
- **RaR datasets** - New datasets and base rubric dataset classes (#2144)

### Infrastructure

- **Nebius cloud provider** - New cloud option (#2179)
- **Kubernetes Skypilot support** - Added k8s dependency (#2124)
- **ARM Docker support** - Enabled ARM builds with useful utilities (#2141)
- **One-line installer** - New `install.sh` script (#2155)

```bash
# Basic installation
curl -LsSf https://oumi.ai/install.sh | bash

# With GPU support
curl -LsSf https://oumi.ai/install.sh | bash -s -- --gpu

# With specific Python version
curl -LsSf https://oumi.ai/install.sh | bash -s -- --python 3.12
```

- **Telemetry** - Optional usage analytics via PostHog (#2145)

---

## 📈 Improvements

### Performance

- **Lazy CLI imports** - Faster startup times (#2110)

### CLI

- List aliases, auto-complete, help, and common args improvements (#2122)
- Judge command UX improvements (#2129)
- Version and system info utilities (#2142)

```bash
oumi env  # Show Oumi version, Python version, installed packages, GPU info
```

### Documentation

- Complete docs refresh with new custom theme (#2133, #2167)
- Added CLI reference sections for analyze, tune, and quantize (#2126)
- Updated installation instructions (#2169)

### Configs

- Added Gemma-2-IT chat template and example config (#2159)
- Updated Gemma3-4B-IT SFT training config (#2156)

## ⚠️ Breaking Changes

- **Dropped Python 3.9 support** - Minimum supported version is now Python 3.10 (#2107)
- **Deprecated alpaca_eval integration** (#2108)
- **Deprecated protobuf conversation definitions** (#2127)

---

## 🐛 Bug Fixes

- Fixed synthesis rounding errors (#2104)
- Fixed logging of distributed training CLI commands (#2165)
- Fixed FSDP transformer_wrap_class parsing for fully qualified names (#2164)
- Fixed deprecated torch_dtype usage (#2123)
- Fixed Oumi Tour notebook output (#2157)
- Cleaned up errant print statements (#2121)

---

## 📦 Dependency Updates

- **PyTorch 2.9** and **Python 3.14** support (#2109)
- Updated: peft, uvicorn, bitsandbytes, click, pillow, typer, torchao, pycares, wandb

---

## 👋 New Contributors

Welcome to our new contributors!

- @lrobledo (#2105)
- @RajdeepKushwaha5 (#2085)
- @ritankarsaha (#2044)
- @brian-nguyen (#2157)
- @lefft (#2156)

---

**Full Changelog**: https://github.com/oumi-ai/oumi/compare/v0.6.0...v0.7