Text reader added

config.yaml

@@ -41,21 +41,29 @@ huggingface:
 
 # --- Data Processing Settings ---
 
-pdf:
+#pdf:
-  # List of paths to PDF files or folders containing PDFs.
+#  # List of paths to PDF files or folders containing PDFs.
-  # Pydantic converts these strings to pathlib.Path objects.
+#  # Pydantic converts these strings to pathlib.Path objects.
-  data:
+#  data:
-    - "C:/path/folder"
+#    - "C:/path/folder"
-  unstructured: false # Use the unstructured PDF loader?
+#  unstructured: false # Use the unstructured PDF loader?
-  chunk_size: 1000
+#  chunk_size: 1000
-  chunk_overlap: 200
+#  chunk_overlap: 200
-  add_start_index: false
+#  add_start_index: false
+#
+#web:
+#  # List of URLs to scrape for data.
+#  data:
+#    - "https://www.example.nl/subdomain"
+#  chunk_size: 200
 
-web:
+text:
-  # List of URLs to scrape for data.
   data:
-    - "https://www.example.nl/subdomain"
+    - "../transcriptions"
-  chunk_size: 200
+  unstructured: true
+  chunk_size: 500
+  chunk_overlap: 100
+  add_start_index: false
 
 chroma_db:
   location: "/app/data/vector_database" # Override default DB path (default: '.chroma_db')

generic_rag/app.py

@@ -13,7 +13,7 @@ from generic_rag.parsers.config import AppSettings, load_settings
 from generic_rag.backend.models import get_chat_model, get_embedding_model, get_compression_model
 from generic_rag.graphs.cond_ret_gen import CondRetGenLangGraph
 from generic_rag.graphs.ret_gen import RetGenLangGraph
-from generic_rag.parsers.parser import add_pdf_files, add_urls
+from generic_rag.parsers.parser import add_pdf_files, add_urls, add_text_files
 
 logger = logging.getLogger("sogeti-rag")
 logger.setLevel(logging.DEBUG)
@@ -139,6 +139,16 @@ if __name__ == "__main__":
         settings.pdf.add_start_index,
         settings.pdf.unstructured,
     )
+
+    add_text_files(
+        vector_store,
+        settings.text.data,
+        settings.text.chunk_size,
+        settings.text.chunk_overlap,
+        settings.text.add_start_index,
+        settings.text.unstructured,
+    )
+
     add_urls(
         vector_store,
         settings.web.data,

generic_rag/parsers/config.py

@@ -92,6 +92,14 @@ class PdfSettings(BaseModel):
     chunk_overlap: int = Field(default=200)
     add_start_index: bool = Field(default=False)
 
+class TextSettings(BaseModel):
+    """Text processing settings."""
+
+    data: List[Path] = Field(default_factory=list)
+    unstructured: bool = Field(default=False)
+    chunk_size: int = Field(default=1000)
+    chunk_overlap: int = Field(default=200)
+    add_start_index: bool = Field(default=False)
 
 class WebSettings(BaseModel):
     """Web data processing settings."""
@@ -131,6 +139,7 @@ class AppSettings(BaseModel):
 
     # --- Data processing settings ---
     pdf: PdfSettings = Field(default_factory=PdfSettings)
+    text: TextSettings = Field(default_factory=TextSettings)
     web: WebSettings = Field(default_factory=WebSettings)
     chroma_db: ChromaDbSettings = Field(default_factory=ChromaDbSettings)
 

generic_rag/parsers/parser.py

@@ -4,14 +4,13 @@ from pathlib import Path
 import requests
 from bs4 import BeautifulSoup, Tag
 from langchain_chroma import Chroma
-from langchain_community.document_loaders import PyMuPDFLoader
+from langchain_community.document_loaders import PyMuPDFLoader, DirectoryLoader
 from langchain_community.vectorstores.utils import filter_complex_metadata
 from langchain_text_splitters import HTMLSemanticPreservingSplitter, RecursiveCharacterTextSplitter
 from langchain_unstructured import UnstructuredLoader
 
 logger = logging.getLogger(__name__)
 
-
 headers_to_split_on = [("h1", "Header 1"), ("h2", "Header 2")]
 
 
@@ -74,12 +73,12 @@ def add_urls(vector_store: Chroma, urls: list[str], chunk_size: int) -> None:
 
 
 def add_pdf_files(
-    vector_store: Chroma,
+        vector_store: Chroma,
-    file_paths: list[Path],
+        file_paths: list[Path],
-    chunk_size: int,
+        chunk_size: int,
-    chunk_overlap: int,
+        chunk_overlap: int,
-    add_start_index: bool,
+        add_start_index: bool,
-    unstructerd: bool,
+        unstructerd: bool,
 ) -> None:
     """
     Adds a list of PDF files as vector documents to the provided vector store.
@@ -120,20 +119,72 @@ def add_pdf_files(
     vector_store.add_documents(documents=filter_complex_metadata(pdf_splits))
 
 
-def get_all_local_pdf_files(local_paths: list[Path]) -> list[Path]:
+def add_text_files(
+        vector_store: Chroma,
+        file_paths: list[Path],
+        chunk_size: int,
+        chunk_overlap: int,
+        add_start_index: bool,
+        unstructerd: bool,
+) -> None:
+    """
+    Adds a list of Text files as vector documents to the provided vector store.
+    The Text file will be parsed per page and split into chunks of text with the provided chunk size and overlap.
+    """
+    logger.info("Adding Text files to the vector store.")
+    text_files = get_all_local_text_files(file_paths)
+    new_txts = []
+    for txt_file in text_files:
+        if len(vector_store.get(where={"source": str(txt_file)}, limit=1)["ids"]) == 0:
+            new_txts.append(txt_file)
+        else:
+            logger.info(f"Skipping PDF {txt_file}, as it is already in the database.")
+
+    if len(new_txts) == 0:
+        return
+
+    logger.info(f"{len(new_txts)} Txt(s) to add to the vector store.")
+
+    loaded_documents = []
+    for file in new_txts:
+        loader = UnstructuredLoader(file_path=file, strategy="basic")
+        for document in loader.lazy_load():
+            loaded_documents.append(document)
+
+    text_splitter = RecursiveCharacterTextSplitter(
+        chunk_size=chunk_size, chunk_overlap=chunk_overlap, add_start_index=add_start_index
+    )
+
+    txt_splits = text_splitter.split_documents(loaded_documents)
+
+    logger.info(f"{len(txt_splits)} PDF's split in {len(txt_splits)} vector store documents")
+    logger.info(f"Adding {len(txt_splits)} vector store documents to vector store.")
+
+    vector_store.add_documents(documents=filter_complex_metadata(txt_splits))
+
+
+def get_all_local_files(local_paths: list[Path], extension="pdf") -> list[Path]:
     """
     Function that takes a list of local paths,
     that might contain directories paths and/or direct file paths,
-    and returns a list with all file paths that are a PDF file or any PDF files found in the directory file paths.
+    and returns a list with all file paths that are a file with the matching extension.
-    This fucntion does not scan directories recursively.
+    This function does not scan directories recursively.
     """
     all_pdf_files = []
     for path in local_paths:
         if path.is_dir():
-            all_pdf_files.extend(list(path.glob("*.pdf")))
+            all_pdf_files.extend(list(path.glob(f"*.{extension}")))
-        elif path.suffix == ".pdf":
+        elif path.suffix == f".{extension}":
             all_pdf_files.append(path)
         else:
-            logger.warning(f"Ignoring path {path} as it is not a folder or pdf file.")
+            logger.warning(f"Ignoring path {path} as it is not a folder or {extension} file.")
 
     return all_pdf_files
+
+
+def get_all_local_pdf_files(local_paths: list[Path]) -> list[Path]:
+    return get_all_local_files(local_paths, "pdf")
+
+
+def get_all_local_text_files(local_paths: list[Path]) -> list[Path]:
+    return get_all_local_files(local_paths, "txt")