Swarmauri Tool · Text Length
A Swarmauri-ready helper that measures text length in characters, words, and sentences using NLTK tokenization. Drop it into content pipelines, moderation bots, or editorial agents to monitor message size and cadence.
- Counts characters (excluding spaces) for quick size checks.
- Uses NLTK tokenizers to calculate word and sentence totals accurately.
- Returns a structured dictionary suitable for logging, analytics, or conversational outputs.
Requirements
- Python 3.10 – 3.13.
nltkwith thepunkt_tabresource available (downloaded automatically on import).- Core Swarmauri dependencies (
swarmauri_base,swarmauri_standard,pydantic).
Installation
Pick the packaging tool that fits your workflow; each command installs dependencies.
pip
pip install swarmauri_tool_textlength
Poetry
poetry add swarmauri_tool_textlength
uv
# Add to the current project and update uv.lock
uv add swarmauri_tool_textlength
# or install into the active environment without editing pyproject.toml
uv pip install swarmauri_tool_textlength
Tip: When building containers or offline environments, pre-fetch NLTK data with
python -m nltk.downloader punkt_tabto avoid runtime downloads.
Quick Start
from swarmauri_tool_textlength import TextLengthTool
text = "This is a simple test sentence."
length_tool = TextLengthTool()
result = length_tool(text)
print(result)
# {
# 'num_characters': 26,
# 'num_words': 7,
# 'num_sentences': 1
# }
Usage Scenarios
Enforce Message Length in Moderation Bots
from swarmauri_tool_textlength import TextLengthTool
length_checker = TextLengthTool()
message = """Please keep replies under 50 words so the queue stays manageable."""
metrics = length_checker(message)
if metrics["num_words"] > 50:
raise ValueError("Message too long for moderation queue")
Provide Real-Time Feedback in a Swarmauri Agent
from swarmauri_core.agent.Agent import Agent
from swarmauri_core.messages.HumanMessage import HumanMessage
from swarmauri_standard.tools.registry import ToolRegistry
from swarmauri_tool_textlength import TextLengthTool
registry = ToolRegistry()
registry.register(TextLengthTool())
agent = Agent(tool_registry=registry)
message = HumanMessage(content="Analyze how long this paragraph is compared to our guideline.")
response = agent.run(message)
print(response)
Batch Audit Documentation for Sentence Length
from pathlib import Path
from swarmauri_tool_textlength import TextLengthTool
length_tool = TextLengthTool()
for doc in Path("docs").rglob("*.md"):
metrics = length_tool(doc.read_text(encoding="utf-8"))
print(f"{doc}: {metrics['num_sentences']} sentences, {metrics['num_words']} words")
Scan an entire documentation set to identify sprawling sections or under-documented topics.
Troubleshooting
LookupError: Resource punkt_tab not found– Runpython -m nltk.downloader punkt_tabahead of time, especially in air-gapped deployments.- Unexpected character counts – The tool excludes spaces; adjust the implementation if you need raw length including whitespace.
- Non-English text – NLTK’s default tokenizers target English. Swap in language-specific tokenizers if needed.
License
swarmauri_tool_textlength is released under the Apache 2.0 License. See LICENSE for full details.
1 maintainer
Metadata
1 maintainer
Release files for swarmauri_tool_textlength 0.9.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| swarmauri_tool_textlength-0.9.0.tar.gz | 8.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| swarmauri_tool_textlength-0.9.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.0 kB
Release files / swarmauri_tool_textlength-0.9.0.tar.gz
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Release files / swarmauri_tool_textlength-0.9.0-py3-none-any.whl
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| Size | 9.0 kB |
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