---

name: python-pipeline description: "Guides high-level Python LTP pipeline workflows for model loading, sentence splitting, task outputs, custom words, and integration helpers." disable-model-invocation: true metadata: disco-role: operating license: CC BY-NC 4.0

Python Pipeline

Use this sub-skill when the user wants to use from ltp import LTP, StnSplit for Chinese NLP inference, output conversion, or service integration.

Choose this route when

• The task names LTP(...), pipeline, LTPOutput, StnSplit, LTP/tiny, LTP/small, LTP/base, LTP/legacy, or local LTP model directories.
• The user asks for CWS, POS, NER, SRL, dependency parsing, SDP, SDPG, custom words, or GPU movement from Python.
• The user needs to interpret output structures or convert LTP output into a tabular/CoNLL-U-like format.
• The user wants to wrap LTP behind a Python service or batch-processing script.

Route low-level perceptron model/trainer APIs to ../legacy-extension/SKILL.md, deep-training/config tasks to ../training-and-data/SKILL.md, and Rust/C bindings to ../rust-bindings/SKILL.md.

Minimal safe workflow

1. Confirm the package imports and optional CUDA state from the root skill:

   python ../../scripts/check_ltp_install.py --json
   

2. For no-network diagnostics, run the pipeline smoke script without loading a model:

   python scripts/ltp_pipeline_smoke.py --skip-model-load
   

3. If the user has a local or cached model, load it explicitly:

   python scripts/ltp_pipeline_smoke.py --model-path /path/to/ltp-model --local-files-only --tasks cws,pos,ner
   

4. For real application code, use a model id or local path and choose tasks deliberately:

   from ltp import LTP
   
   ltp = LTP("LTP/small")
   output = ltp.pipeline(["他叫汤姆去拿外衣。"], tasks=["cws", "pos", "ner"])
   print(output.cws, output.pos, output.ner)
   

Read these references

• references/api-reference.md for verified signatures, task dependencies, LTPOutput, and method behavior.
• references/workflows.md for common inference, custom-word, pretokenized-input, batch, and CUDA workflows.
• references/model-loading-and-outputs.md for model ids, offline loading, output shapes, labels, and conversion decisions.
• references/service-and-integration.md for CoNLL-U conversion, FastAPI-style wrappers, and production safety notes.
• references/troubleshooting.md when model loading, task selection, CUDA, or optional service dependencies fail.

Bundled helpers

• scripts/ltp_pipeline_smoke.py checks imports/sentence splitting and optionally runs a tiny pipeline against a supplied model path or model id. Defaults avoid network downloads.
• scripts/convert_ltp_output_to_conllu.py converts saved LTP JSON output into CoNLL-U-like rows without loading a model.

Important boundaries

• Do not run remote model downloads unless the user has accepted network/model-cache side effects.
• Do not claim legacy LTP("LTP/legacy") supports SRL/DEP/SDP/SDPG. It supports CWS/POS/NER only.
• Do not pass raw strings when cws is omitted from tasks; pass pretokenized List[List[str]].
• Do not hide private Hugging Face tokens, proxies, or model paths in scripts or committed configs.