Merge pull request #1071 from MichaelDecent/comm_pkg9

add Swarmauri Text Length Tool

pkgs/community/swarmauri_tool_communitytextlength/README.md

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+# Swarmauri Example Community Package

pkgs/community/swarmauri_tool_communitytextlength/pyproject.toml

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+[tool.poetry]
+name = "swarmauri_tool_communitytextlength"
+version = "0.6.0.dev1"
+description = "This repository includes an example of a First Class Swarmauri Example."
+authors = ["Jacob Stewart <[email protected]>"]
+license = "Apache-2.0"
+readme = "README.md"
+repository = "http://github.com/swarmauri/swarmauri-sdk"
+classifiers = [
+    "License :: OSI Approved :: Apache Software License",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12"
+]
+
+[tool.poetry.dependencies]
+python = ">=3.10,<3.13"
+
+# Swarmauri
+swarmauri_core = { path = "../../core" }
+swarmauri_base = { path = "../../base" }
+
+# Dependencies
+nltk = "^3.9.1"
+
+
+[tool.poetry.group.dev.dependencies]
+flake8 = "^7.0"
+pytest = "^8.0"
+pytest-asyncio = ">=0.24.0"
+pytest-xdist = "^3.6.1"
+pytest-json-report = "^1.5.0"
+python-dotenv = "*"
+requests = "^2.32.3"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.pytest.ini_options]
+norecursedirs = ["combined", "scripts"]
+
+markers = [
+    "test: standard test",
+    "unit: Unit tests",
+    "integration: Integration tests",
+    "acceptance: Acceptance tests",
+    "experimental: Experimental tests"
+]
+log_cli = true
+log_cli_level = "INFO"
+log_cli_format = "%(asctime)s [%(levelname)s] %(message)s"
+log_cli_date_format = "%Y-%m-%d %H:%M:%S"
+asyncio_default_fixture_loop_scope = "function"
+
+[tool.poetry.plugins."swarmauri.tools"]
+TextLengthTool = "swarmauri_tool_communitytextlength:TextLengthTool"

pkgs/community/swarmauri_tool_communitytextlength/swarmauri_tool_communitytextlength/TextLengthTool.py

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+from swarmauri_core.typing import SubclassUnion
+from typing import List, Literal, Dict
+from pydantic import Field
+from swarmauri._base.tools.ToolBase import ToolBase
+from swarmauri_standard.tools.Parameter import Parameter
+import nltk
+from nltk.tokenize import sent_tokenize, word_tokenize
+
+# Download required NLTK data once during module load
+nltk.download("punkt", quiet=True)
+
+
+class TextLengthTool(ToolBase):
+    version: str = "0.1.dev1"
+    parameters: List[Parameter] = Field(
+        default_factory=lambda: [
+            Parameter(
+                name="text",
+                type="string",
+                description="The text to analyze for length.",
+                required=True,
+            )
+        ]
+    )
+    name: str = "TextLengthTool"
+    description: str = "Calculates the length of the provided text in terms of characters, words, and sentences."
+    type: Literal["TextLengthTool"] = "TextLengthTool"
+
+    def __call__(self, text: str) -> Dict[str, int]:
+        """
+        Calculates the length of the provided text in terms of characters, words, and sentences.
+
+        Parameters:
+            text (str): The text to analyze.
+
+        Returns:
+            dict: A dictionary containing the number of characters, words, and sentences.
+        """
+        return self.calculate_text_length(text)
+
+    def calculate_text_length(self, text: str) -> Dict[str, int]:
+        """
+        Calculate the length of the text in characters, words, and sentences.
+
+        Parameters:
+            text (str): The text to analyze.
+
+        Returns:
+            dict: A dictionary containing:
+                  - 'num_characters': Number of characters in the text.
+                  - 'num_words': Number of words in the text.
+                  - 'num_sentences': Number of sentences in the text.
+        """
+        num_characters = self.count_characters(text)
+        num_words = self.count_words(text)
+        num_sentences = self.count_sentences(text)
+
+        return {
+            "num_characters": num_characters,
+            "num_words": num_words,
+            "num_sentences": num_sentences,
+        }
+
+    def count_characters(self, text: str) -> int:
+        """
+        Count the number of characters in the text, excluding spaces.
+
+        Parameters:
+            text (str): The text to analyze.
+
+        Returns:
+            int: The number of characters in the text.
+        """
+        return len(text.replace(" ", ""))
+
+    def count_words(self, text: str) -> int:
+        """
+        Count the number of words in the text.
+
+        Parameters:
+            text (str): The text to analyze.
+
+        Returns:
+            int: The number of words in the text.
+        """
+        words = word_tokenize(text)
+        return len(words)
+
+    def count_sentences(self, text: str) -> int:
+        """
+        Count the number of sentences in the text.
+
+        Parameters:
+            text (str): The text to analyze.
+
+        Returns:
+            int: The number of sentences in the text.
+        """
+        sentences = sent_tokenize(text)
+        return len(sentences)
+
+
+SubclassUnion.update(
+    baseclass=ToolBase,
+    type_name="TextLengthTool",
+    obj=TextLengthTool,
+)

pkgs/community/swarmauri_tool_communitytextlength/swarmauri_tool_communitytextlength/__init__.py

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+from .TextLengthTool import TextLengthTool
+
+__version__ = "0.6.0.dev26"
+__long_desc__ = """
+
+# Swarmauri Example Plugin
+
+This repository includes an example of a Swarmauri Plugin.
+
+Visit us at: https://swarmauri.com
+Follow us at: https://github.com/swarmauri
+Star us at: https://github.com/swarmauri/swarmauri-sdk
+
+"""

pkgs/community/swarmauri_tool_communitytextlength/tests/unit/TextLength_unit_test.py

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+import pytest
+from swarmauri_tool_communitytextlength.TextLengthTool import TextLengthTool as Tool
+
+
+@pytest.mark.unit
+def test_ubc_resource():
+    tool = Tool()
+    assert tool.resource == "Tool"
+
+
+@pytest.mark.unit
+def test_ubc_type():
+    assert Tool().type == "TextLengthTool"
+
+
+@pytest.mark.unit
+def test_initialization():
+    tool = Tool()
+    assert type(tool.id) == str
+
+
+@pytest.mark.unit
+def test_serialization():
+    tool = Tool()
+    assert tool.id == Tool.model_validate_json(tool.model_dump_json()).id
+
+
+@pytest.mark.unit
+def test_call():
+    tool = Tool()
+    text = "This is a simple test sentence."
+
+    num_characters = 26
+    num_words = 7
+    num_sentences = 1
+
+    expected_keys = {"num_characters", "num_words", "num_sentences"}
+
+    result = tool(text)
+
+    assert isinstance(result, dict), f"Expected dict, but got {type(result).__name__}"
+    assert expected_keys.issubset(
+        result.keys()
+    ), f"Expected keys {expected_keys} but got {result.keys()}"
+    assert isinstance(
+        result.get("num_characters"), int
+    ), f"Expected int, but got {type(result.get('num_characters')).__name__}"
+    assert isinstance(
+        result.get("num_words"), int
+    ), f"Expected int, but got {type(result.get('num_words')).__name__}"
+    assert isinstance(
+        result.get("num_sentences"), int
+    ), f"Expected int, but got {type(result.get('num_sentences')).__name__}"
+
+    assert (
+        result.get("num_characters") == num_characters
+    ), f"Expected Number of Characters is {num_characters}, but got {result.get('num_characters')}"
+    assert (
+        result.get("num_words") == num_words
+    ), f"Expected Number of Words is {num_words}, but got {result.get('num_words')}"
+    assert (
+        result.get("num_sentences") == num_sentences
+    ), f"Expected Number of Sentence is {num_sentences}, but got {result.get('num_sentences')}"