Output Types

All boileroom models return typed dataclass objects containing prediction results and metadata. Each model’s output type is documented on its own page — this page covers the shared PredictionMetadata type, cross-model comparison, and the include_fields filtering mechanism.

PredictionMetadata

Every output’s metadata field is a PredictionMetadata instance with timing and model information.

str

Name of the model (e.g., "ESMFold", "ESM-2", "Chai-1", "Boltz-2").

str

Version string of the model.

list[int] | None

Number of residues for each input sequence (excluding chain separators).

float | None

Time spent in preprocessing (seconds).

float | None

Time spent in model inference (seconds).

float | None

Time spent in postprocessing (seconds).

Per-model output types

Each model page documents its full output dataclass:

ESMFoldOutput — returned by ESMFold.fold()
ESM2Output — returned by ESM2.embed()
Chai1Output — returned by Chai1.fold()
Boltz2Output — returned by Boltz2.fold()

Cross-model comparison

Field	ESMFold	ESM2	Chai-1	Boltz-2
`metadata`	Yes	Yes	Yes	Yes
`atom_array`	Yes	—	Yes	Yes
`embeddings`	—	Yes	—	—
`plddt`	Yes	—	Yes	Yes
`pae`	Yes	—	Yes	Yes
`pde`	—	—	Yes	Yes
`ptm`	Yes	—	Yes	—
`iptm`	—	—	Yes	—
`confidence`	—	—	—	Yes
`pdb`	Yes	—	—	Yes
`cif`	Yes	—	Yes	Yes
`chain_index`	Yes	Yes	—	—
`residue_index`	Yes	Yes	—	—
`hidden_states`	—	Yes	—	—
`s_s` / `s_z`	Yes	—	—	—

Filtering with `include_fields`

All models support an include_fields configuration key that controls which optional fields are returned. This is useful for reducing memory usage and transfer time when you only need specific outputs.

# Only return pLDDT scores (atom_array is always included for folding models)
result = model.fold("MKTVRQERLKSIVRI", options={"include_fields": ["plddt"]})

# Return everything including PDB/CIF strings
result = model.fold("MKTVRQERLKSIVRI", options={"include_fields": ["*"]})

# Return PDB and PAE
result = model.fold("MKTVRQERLKSIVRI", options={"include_fields": ["pdb", "pae"]})

Fields not listed in include_fields are set to None. The following fields are always included regardless of the filter:

Folding models: metadata, atom_array
Embedding models: metadata, embeddings, chain_index, residue_index

Overview

Folding Models

Embedding Models

Reference

Development

Output Types

PredictionMetadata

Per-model output types

Cross-model comparison

Filtering with `include_fields`

​PredictionMetadata

​Per-model output types

​Cross-model comparison

​Filtering with include_fields

PredictionMetadata

Per-model output types

Cross-model comparison

Filtering with `include_fields`