---

name: towhee description: "Route Towhee pipeline, operator, data utility, service, Triton, training, and model-zoo tasks to self-contained workflow guidance." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Towhee Repo Skill

Use this skill when the user asks about Towhee, x2vec, Towhee Hub operators, towhee.pipe, towhee.ops, AutoPipes, AutoConfig, DataCollection, towhee server, APIService, Triton packaging for Towhee pipelines, or optional Towhee training/model-zoo workflows.

Towhee 1.1.x is a Python framework for orchestrating unstructured-data pipelines over text, image, audio, video, embeddings, retrieval, service wrapping, and optional Triton deployment. This generated skill is self-contained; do not reopen the original repository checkout for normal operation.

First checks

1. Read installation and compatibility when the task starts with install/import failures, package versions, optional dependency choices, or environment setup.

2. Run the safe root diagnostic when the user wants proof that a Towhee environment is usable:

   python scripts/check_towhee_environment.py --verbose
   

   The helper verifies imports, a local lambda pipeline, batch execution, Entity.combine, APIService, and CLI help. It does not download Hub operators, start web servers, run Docker/Triton, use GPUs, or train models.

3. Read root troubleshooting for cross-cutting import, pkg_resources, Pydantic, Hub/cache, optional dependency, service, Docker, or Triton issues.

4. Read repo provenance before deciding whether this skill is stale for a different Towhee checkout.

Route by task

User task	Read next
Build or debug a custom method-chained pipeline with pipe.input(...).map(...).output(...), flat_map, filter, window, concat, batch, debug, flush, AutoConfig, or AutoPipes	pipeline-programming
Use ops, register local operators, choose Hub operator revisions, validate towhee CLI help, or reason about towhee init side effects	operator-hub-and-cli
Wrap a pipeline/function as an API service, plan towhee server, HTTP/GRPC routes, Triton model repositories, Docker images, build_pipeline_model, or build_docker_image	serving-and-triton
Convert pipeline results with DataCollection, use Entity, DataLoader, media array wrappers, display tables, serialization, visualizer, tracer, or profiler outputs	data-utilities
Configure optional PyTorch training, TrainingConfig, Trainer, NNOperator.train, checkpoints/model cards, or decide whether to install towhee.models	training-and-models

Common safe patterns

Minimal local pipeline

from towhee import AutoConfig, pipe

p = (
    pipe.input('x')
        .map('x', 'y', lambda x: x + 1, config=AutoConfig.LocalCPUConfig())
        .output('y')
)
print(p(2).get())  # [3]

Start with local lambdas/callables to validate schema and graph shape before introducing Hub operators, model downloads, Triton, or training.

Hub/model operators

Hub operators are accessed through ops, for example ops.image_embedding.timm(...) or ops.namespace.operator(...). Treat Hub resolution as potentially networked and dependency-installing. Pin revisions when reproducibility matters and use the operator/CLI sub-skill for local registration or towhee init guidance.

Service and deployment

Construct APIService objects or api_service.build_service(...) before starting live HTTP/GRPC servers. Use object-level smoke checks first; only run towhee server, Docker, Triton, or GPU/CUDA commands after confirming ports, dependencies, artifacts, cleanup, and user approval.

Optional training and model zoo

Towhee's training/model surfaces are optional and PyTorch-centered. Use CPU-safe config templates first. Do not import trainer/model modules in a constrained environment unless optional package installation is acceptable; Towhee dependency helpers can auto-install missing packages.

Known compatibility flags

• Towhee 1.1.x imports pkg_resources; if import fails with No module named 'pkg_resources', install a compatible setuptools such as setuptools<81.
• The repo's own test requirements use pydantic<2; prefer Pydantic v1 for old Towhee service workflows unless the exact Pydantic v2 path has been tested.
• GPU, Docker/Triton, live HTTP/GRPC service, Hub downloads, and real model training are optional workflow checks, not proof from a base Towhee import.