feat: Add PDF Retrieval and Text Splitter

pyproject.toml

@@ -38,6 +38,9 @@ torchvision = [
 langdetect = ">=1"
 openai = "^1.52.2"
 google-generativeai = "^0.8.3"
+pypdf = ">=5"
+langchain = ">=0.3.7"
+langchain-community = ">=0.3.7"
 
 [tool.poetry.extras]
 cpu = ["torch", "torchvision"]

src/rago/retrieval/__init__.py

@@ -3,8 +3,10 @@
 from __future__ import annotations
 
 from rago.retrieval.base import RetrievalBase, StringRet
+from rago.retrieval.file import PDFPathRet
 
 __all__ = [
     'RetrievalBase',
     'StringRet',
+    'PDFPathRet',
 ]

src/rago/retrieval/base.py

@@ -3,30 +3,60 @@
 from __future__ import annotations
 
 from abc import abstractmethod
-from typing import Any, cast
+from typing import Any, Iterable, cast
 
 from typeguard import typechecked
 
+from rago.retrieval.text_splitter import (
+    LangChainTextSplitter,
+    TextSplitterBase,
+)
+
 
 @typechecked
 class RetrievalBase:
     """Base Retrieval class."""
 
     content: Any
-
-    def __init__(self, sources: Any) -> None:
-        self.sources = sources
+    source: Any
+    splitter: TextSplitterBase
+
+    def __init__(
+        self,
+        source: Any,
+        splitter: TextSplitterBase = LangChainTextSplitter(
+            'RecursiveCharacterTextSplitter'
+        ),
+    ) -> None:
+        """Initialize the Retrieval class."""
+        self.source = source
+        self.splitter = splitter
+        self._validate()
+        self._setup()
+
+    def _validate(self) -> None:
+        """Validate if the source is valid, otherwise raises an exception."""
+        return None
+
+    def _setup(self) -> None:
+        """Set up the object with the giving initial parameters."""
+        return None
 
     @abstractmethod
-    def get(self, query: str = '') -> Any:
-        """Get the data from the sources."""
-        ...
+    def get(self, query: str = '') -> Iterable[str]:
+        """Get the data from the source."""
+        return []
 
 
 @typechecked
 class StringRet(RetrievalBase):
-    """String Retrieval class."""
+    """
+    String Retrieval class.
+
+    This is a very generic class that assumes that the input (source) is
+    already a list of strings.
+    """
 
-    def get(self, query: str = '') -> list[str]:
+    def get(self, query: str = '') -> Iterable[str]:
         """Get the data from the sources."""
-        return cast(list[str], self.sources)
+        return cast(list[str], self.source)

src/rago/retrieval/file.py

@@ -0,0 +1,41 @@
+"""Base classes for retrieval."""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Iterable
+
+from typeguard import typechecked
+
+from rago.retrieval.base import RetrievalBase
+from rago.retrieval.tools.pdf import extract_text_from_pdf, is_pdf
+
+
+@typechecked
+class FilePathRet(RetrievalBase):
+    """File Retrieval class."""
+
+    def _validate(self) -> None:
+        """Validate if the source is valid, otherwise raises an exception."""
+        if not isinstance(self.source, (str, Path)):
+            raise Exception('Argument source should be an string or a Path.')
+
+        source_path = Path(self.source)
+        if not source_path.exists():
+            raise Exception("File doesn't exist.")
+
+
+@typechecked
+class PDFPathRet(FilePathRet):
+    """PDFPathRet Retrieval class."""
+
+    def _validate(self) -> None:
+        """Validate if the source is valid, otherwise raises an exception."""
+        super()._validate()
+        if not is_pdf(self.source):
+            raise Exception('Given file is not a PDF.')
+
+    def get(self, query: str = '') -> Iterable[str]:
+        """Get the data from the source."""
+        text = extract_text_from_pdf(self.source)
+        return self.splitter.split(text)

src/rago/retrieval/text_splitter/__init__.py

@@ -0,0 +1,9 @@
+"""Package for classes about text splitter."""
+
+from rago.retrieval.text_splitter.base import TextSplitterBase
+from rago.retrieval.text_splitter.langchain import LangChainTextSplitter
+
+__all__ = [
+    'TextSplitterBase',
+    'LangChainTextSplitter',
+]

src/rago/retrieval/text_splitter/base.py

@@ -0,0 +1,49 @@
+"""The base classes for text splitter."""
+
+from __future__ import annotations
+
+from abc import abstractmethod
+from typing import Any, Iterable
+
+
+class TextSplitterBase:
+    """The base text splitter class."""
+
+    chunk_size: int = 500
+    chunk_overlap: int = 100
+    splitter_name: str = ''
+    splitter: Any = None
+
+    # defaults
+
+    default_chunk_size: int = 500
+    default_chunk_overlap: int = 100
+    default_splitter_name: str = ''
+    default_splitter: Any = None
+
+    def __init__(
+        self,
+        splitter_name: str = '',
+        chunk_size: int = 500,
+        chunk_overlap: int = 100,
+    ) -> None:
+        """Initialize the text splitter class."""
+        self.chunk_size = chunk_size or self.default_chunk_size
+        self.chunk_overlap = chunk_overlap or self.default_chunk_overlap
+        self.splitter_name = splitter_name or self.default_splitter_name
+
+        self._validate()
+        self._setup()
+
+    def _validate(self) -> None:
+        """Validate if the initial parameters are valid."""
+        return
+
+    def _setup(self) -> None:
+        """Set up the object according to the given parameters."""
+        return
+
+    @abstractmethod
+    def split(self, text: str) -> Iterable[str]:
+        """Split a text into chunks."""
+        return []

src/rago/retrieval/text_splitter/langchain.py

@@ -0,0 +1,40 @@
+"""Support langchain text splitter."""
+
+from __future__ import annotations
+
+from typing import List, cast
+
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+
+from rago.retrieval.text_splitter.base import TextSplitterBase
+
+
+class LangChainTextSplitter(TextSplitterBase):
+    """LangChain Text Splitter class."""
+
+    default_splitter_name: str = 'RecursiveCharacterTextSplitter'
+
+    def _validate(self) -> None:
+        """Validate if the initial parameters are valid."""
+        valid_splitter_names = ['RecursiveCharacterTextSplitter']
+
+        if self.splitter_name not in valid_splitter_names:
+            raise Exception(
+                f'The given splitter_name {self.splitter_name} is not valid. '
+                f'Valid options are {valid_splitter_names}'
+            )
+
+    def _setup(self) -> None:
+        """Set up the object according to the given parameters."""
+        if self.splitter_name == 'RecursiveCharacterTextSplitter':
+            self.splitter = RecursiveCharacterTextSplitter
+
+    def split(self, text: str) -> list[str]:
+        """Split text into smaller chunks for processing."""
+        text_splitter = self.splitter(
+            chunk_size=self.chunk_size,
+            chunk_overlap=self.chunk_overlap,
+            length_function=len,
+            is_separator_regex=True,
+        )
+        return cast(List[str], text_splitter.split_text(text))

src/rago/retrieval/tools/__init__.py

@@ -0,0 +1 @@
+"""Tools for support retrieval classes."""

src/rago/retrieval/tools/pdf.py

@@ -0,0 +1,44 @@
+"""PDF tools."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from pypdf import PdfReader
+
+
+def is_pdf(file_path: str | Path) -> bool:
+    """
+    Check if a file is a PDF by reading its header.
+
+    Parameters
+    ----------
+    file_path : str
+        Path to the file to be checked.
+
+    Returns
+    -------
+    bool
+        True if the file is a PDF, False otherwise.
+    """
+    try:
+        with open(file_path, 'rb') as file:
+            header = file.read(4)
+            return header == b'%PDF'
+    except IOError:
+        return False
+
+
+def extract_text_from_pdf(file_path: str) -> str:
+    """
+    Extract text from a PDF file using pypdf.
+
+    The result is the same as the one returned by PyPDFLoader.
+    """
+    reader = PdfReader(file_path)
+    pages = []
+    for page in reader.pages:
+        text = page.extract_text()
+        if text:
+            pages.append(text)
+    return ' '.join(pages)

tests/conftest.py

@@ -15,3 +15,12 @@ def env() -> dict[str, str]:
     dotenv_file = Path(__file__).parent / '.env'
     load_dotenv(dotenv_file)
     return dotenv_values(dotenv_file)
+
+
+@pytest.fixture
+def animals_data() -> list[str]:
+    """Fixture for loading the animals dataset."""
+    data_path = Path(__file__).parent / 'data' / 'animals.txt'
+    with open(data_path) as f:
+        data = [line.strip() for line in f.readlines() if line.strip()]
+        return data

tests/test_gemini.py

@@ -2,8 +2,6 @@
 
 import os
 
-from pathlib import Path
-
 import pytest
 
 from rago import Rago
@@ -12,15 +10,6 @@
 from rago.retrieval import StringRet
 
 
-@pytest.fixture
-def animals_data() -> list[str]:
-    """Fixture for loading the animals dataset."""
-    data_path = Path(__file__).parent / 'data' / 'animals.txt'
-    with open(data_path) as f:
-        data = [line.strip() for line in f.readlines() if line.strip()]
-    return data
-
-
 @pytest.fixture
 def api_key(env) -> str:
     """Fixture for Gemini API key from environment."""

tests/test_hugging_face.py

@@ -1,24 +1,11 @@
 """Tests for rago package."""
 
-from pathlib import Path
-
-import pytest
-
 from rago import Rago
 from rago.augmented import SentenceTransformerAug
 from rago.generation import HuggingFaceGen
 from rago.retrieval import StringRet
 
 
-@pytest.fixture
-def animals_data() -> list[str]:
-    """Create a fixture with animals dataset."""
-    data_path = Path(__file__).parent / 'data' / 'animals.txt'
-    with open(data_path) as f:
-        data = [line.strip() for line in f.readlines() if line.strip()]
-        return data
-
-
 def test_aug_sentence_transformer(animals_data: list[str]) -> None:
     """Test RAG with hugging face."""
     query = 'Is there any animals larger than a dinosaur?'

tests/test_llama.py

@@ -2,8 +2,6 @@
 
 import os
 
-from pathlib import Path
-
 import pytest
 
 from rago import Rago
@@ -12,15 +10,6 @@
 from rago.retrieval import StringRet
 
 
-@pytest.fixture
-def animals_data() -> list[str]:
-    """Create a fixture with animals dataset."""
-    data_path = Path(__file__).parent / 'data' / 'animals.txt'
-    with open(data_path) as f:
-        data = [line.strip() for line in f.readlines() if line.strip()]
-        return data
-
-
 @pytest.mark.skip_on_ci
 def test_llama(env, animals_data: list[str], device: str = 'auto') -> None:
     """Test RAG with hugging face."""

tests/test_openai.py

@@ -2,8 +2,6 @@
 
 import os
 
-from pathlib import Path
-
 import pytest
 
 from rago import Rago
@@ -12,15 +10,6 @@
 from rago.retrieval import StringRet
 
 
-@pytest.fixture
-def animals_data() -> list[str]:
-    """Fixture for loading the animals dataset."""
-    data_path = Path(__file__).parent / 'data' / 'animals.txt'
-    with open(data_path) as f:
-        data = [line.strip() for line in f.readlines() if line.strip()]
-        return data
-
-
 @pytest.fixture
 def api_key(env) -> str:
     """Fixture for OpenAI API key from environment."""