Genesis commit

app/services/dependencies.py

@@ -0,0 +1,33 @@
+from fastapi import Depends
+from app.config import get_config
+from app.services.file_service import FileService
+from app.services.faiss_service import FAISSService
+
+
+
+def get_file_service(config=Depends(get_config)) -> FileService:
+    """
+    Dependency function to provide a FileService instance.
+
+    :param config: Configuration object obtained via dependency injection.
+    :return: An instance of FileService initialized with the PDF folder path.
+    """
+    if not hasattr(config, "PDF_FOLDER") or not config.PDF_FOLDER:
+        raise ValueError("PDF_FOLDER is not configured in the application settings.")
+    return FileService(folder_path=config.PDF_FOLDER)
+
+
+def get_faiss_service(file_service=Depends(get_file_service)) -> FAISSService:
+    """
+    Dependency function to provide a FAISSService instance.
+
+    :param config: Configuration object obtained via dependency injection.
+    :param file_service: FileService instance for handling PDFs and documents.
+    :return: An instance of FAISSService initialized with vectorstore and embeddings.
+    """
+    config = get_config()
+   
+    return FAISSService(
+        openai_api_key=config.OPENAI_API_KEY,
+        index_path="local_faiss_index",
+    )

app/services/faiss_service.py

@@ -0,0 +1,53 @@
+from langchain_community.vectorstores import FAISS
+from langchain_openai import OpenAIEmbeddings
+from langchain.schema import Document
+
+
+class FAISSService:
+    """
+    A service for creating and loading FAISS indexes for document embeddings.
+    """
+
+    def __init__(self, openai_api_key, index_path="local_faiss_index"):
+        """
+        Initialize the FAISS service.
+
+        :param openai_api_key: OpenAI API key for embeddings.
+        :param index_path: Path to save or load the FAISS index.
+        """
+        self.openai_api_key = openai_api_key
+        self.index_path = index_path
+
+    def create_faiss_index(self, documents):
+        """
+        Create a FAISS index from a list of documents.
+
+        :param documents: List of langchain Document objects.
+        :return: FAISS vectorstore instance.
+        """
+        print("[INFO] Creating FAISS index...")
+        vectorstore = FAISS.from_documents(
+            documents,
+            OpenAIEmbeddings(
+                model="text-embedding-ada-002",
+                openai_api_key=self.openai_api_key
+            )
+        )
+        vectorstore.save_local(self.index_path)
+        print(f"[INFO] FAISS index saved to {self.index_path}.")
+        return vectorstore
+
+    def load_faiss_index(self):
+        """
+        Load an existing FAISS index.
+
+        :return: Loaded FAISS vectorstore instance.
+        """
+        print("[INFO] Loading FAISS index...")
+        vectorstore = FAISS.load_local(
+            self.index_path,
+            OpenAIEmbeddings(openai_api_key=self.openai_api_key),
+            allow_dangerous_deserialization=True  
+        )
+        print(f"[INFO] FAISS index loaded from {self.index_path}.")
+        return vectorstore

app/services/file_service.py

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+# app/services/file_service.py
+
+import os
+import pdfplumber
+
+class FileService:
+    """
+    A service to handle file-related operations, including loading PDFs from a folder.
+    """
+    def __init__(self, folder_path: str):
+        """
+        Initialize the FileService with the folder path to read files from.
+        """
+        self.folder_path = os.path.abspath(folder_path)  
+      #  print(f"[DEBUG] Initialized FileService with folder path: {self.folder_path}")
+
+    def load_pdfs(self):
+        """
+        Reads all PDF files from the folder and returns their paths.
+        
+        :return: List of paths to PDF files in the folder.
+        """
+        if not os.path.exists(self.folder_path):
+            raise FileNotFoundError(f"The folder {self.folder_path} does not exist.")
+
+        pdf_files = [
+            os.path.join(self.folder_path, f)
+            for f in os.listdir(self.folder_path)
+            if f.endswith(".pdf")
+        ]
+
+        if not pdf_files:
+            raise FileNotFoundError(f"No PDF files found in the folder {self.folder_path}.")
+
+        return pdf_files
+
+    def extract_text_from_pdf(self, pdf_path):
+        """
+        Extracts text from the PDF file using pdfplumber.
+        :param pdf_path: Path to the PDF file.
+        :return: Extracted text as a string.
+        """
+        text = ""
+        with pdfplumber.open(pdf_path) as pdf:
+            for page in pdf.pages:
+                page_text = page.extract_text()
+                if page_text:
+                    text += page_text + "\n"
+        return text