---
name: dspy-better-together
version: "1.0.0"
dspy-compatibility: "3.2.1"
tags: ["optimizer"]
requires-extras: []
description: Use for BetterTogether, prompt plus weight optimization, fine-tuning sequences, and strategy chains like p -> w -> p.
allowed-tools:
- Read
- Write
- Glob
- Grep
---
# DSPy BetterTogether
## Goal
Sequence prompt and weight optimizers, evaluate intermediate programs, and return the best candidate.
## Prerequisites
- Use DSPy `3.2.1` or later in the stable `3.2.x` series.
- Assign an LM directly to every predictor with `student.set_lm(lm)`.
- Keep a validation set, or allow `BetterTogether` to hold out part of the trainset.
- Confirm the LM provider supports fine-tuning before including `BootstrapFinetune`.
## Basic Pattern
```python
import dspy
lm = dspy.LM("openai/gpt-4o-mini")
dspy.configure(lm=lm)
student = dspy.ChainOfThought("question -> answer")
student.set_lm(lm)
def metric(example, pred, trace=None):
return float(example.answer.lower() == pred.answer.lower())
optimizer = dspy.BetterTogether(
metric=metric,
p=dspy.GEPA(
metric=lambda gold, pred, trace=None, pred_name=None, pred_trace=None:
dspy.Prediction(score=metric(gold, pred), feedback="Check answer correctness."),
reflection_lm=dspy.LM("openai/gpt-4o"),
auto="light",
),
w=dspy.BootstrapFinetune(metric=metric),
)
compiled = optimizer.compile(
student,
trainset=trainset,
valset=valset,
strategy="p -> w -> p",
)
```
## Strategy Choices
| Strategy | Use it when |
|----------|-------------|
| `"p -> w"` | Start with a simple prompt-then-weight pass |
| `"p -> w -> p"` | Re-optimize prompts after fine-tuning |
| `"w -> p"` | Fine-tuning data is already strong |
| Custom chains | Comparing prompt optimizers or conducting controlled experiments |
Optimizer names come from constructor keyword arguments. For example, `mipro=...` and `gepa=...` make `"mipro -> gepa"` valid.
## Per-Optimizer Compile Arguments
Pass optimizer-specific arguments through `optimizer_compile_args`:
```python
compiled = optimizer.compile(
student,
trainset=trainset,
valset=valset,
strategy="p -> w",
optimizer_compile_args={
"p": {"max_metric_calls": 150},
},
)
```
Do not pass `student` inside `optimizer_compile_args`; `BetterTogether` manages the current program.
## Inspect Results
The returned program exposes:
- `candidate_programs`: evaluated candidates with score and strategy
- `flag_compilation_error_occurred`: whether a step failed before completion
## Related Skills
- Pick optimizers: [dspy-optimizer-selection](../dspy-optimizer-selection/SKILL.md)
- Fine-tune weights: [dspy-finetune-bootstrap](../dspy-finetune-bootstrap/SKILL.md)
- Reflect with GEPA: [dspy-gepa-reflective](../dspy-gepa-reflective/SKILL.md)
## Official Documentation
- **BetterTogether API**: https://dspy.ai/api/optimizers/BetterTogether/
- **Optimizer guide**: https://dspy.ai/learn/optimization/optimizers/