diff --git a/.coveragerc b/.coveragerc
index 4b5d00b..c0228fb 100644
--- a/.coveragerc
+++ b/.coveragerc
@@ -1,2 +1,4 @@
 [report]
 exclude_lines = pass
+    pragma: no cover
+    raise NotImplementedError
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
index 93f0713..ddb6f86 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -12,6 +12,7 @@ RUN poetry config virtualenvs.create false && \
 COPY . .
 
 EXPOSE 8000
+EXPOSE 9200
 
 COPY entrypoint.sh /entrypoint.sh
 
diff --git a/app/celery.py b/app/celery.py
new file mode 100644
index 0000000..5766982
--- /dev/null
+++ b/app/celery.py
@@ -0,0 +1,38 @@
+import os
+from celery import Celery
+
+from typing import Dict
+from app.indexer.indexer_file_manager import IndexerFileManager
+from app.downloaders.s3 import S3FileDownloader
+
+from app.handlers.nexus import NexusRESTClient
+from app.text_splitters import TextSplitter, character_text_splitter
+
+
+celery = Celery(__name__)
+celery.conf.broker_url = os.environ.get(
+        "CELERY_BROKER_URL", "redis://localhost:6379"
+    )
+celery.conf.result_backend = os.environ.get(
+        "CELERY_RESULT_BACKEND", "redis://localhost:6379"
+    )
+
+
+@celery.task(name="index_file")
+def index_file_data(content_base: Dict) -> bool:
+    from app.main import main_app
+
+    file_downloader = S3FileDownloader(
+        os.environ.get("AWS_STORAGE_ACCESS_KEY"),
+        os.environ.get("AWS_STORAGE_SECRET_KEY")
+    )
+    text_splitter = TextSplitter(character_text_splitter())
+    manager = IndexerFileManager(file_downloader, main_app.content_base_indexer, text_splitter)
+    index_result: bool = manager.index_file_url(content_base)
+    NexusRESTClient().index_succedded(
+        task_succeded=index_result,
+        nexus_task_uuid=content_base.get("task_uuid"),
+        file_type=content_base.get("extension_file")
+    )
+
+    return index_result
diff --git a/app/config.py b/app/config.py
index e016b5e..bf3f569 100644
--- a/app/config.py
+++ b/app/config.py
@@ -1,4 +1,7 @@
 import os
+from dotenv import load_dotenv
+
+load_dotenv()
 
 
 class AppConfig:
@@ -24,5 +27,18 @@ def __init__(self):
                 "HUGGINGFACE_API_TOKEN", "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"
             ),
         }
+        self.sagemaker_aws ={
+            "endpoint_name": os.environ.get(
+                "SAGEMAKER_ENDPOINT_NAME",
+                "huggingface-pytorch-inference-2023-10-25-14-25-59-713",
+            ),
+            "region_name": os.environ.get("SAGEMAKER_REGION_NAME", "us-east-1"),
+            "aws_key": os.environ.get("SAGE_MAKER_AWS_KEY"),
+            "aws_secret": os.environ.get("SAGE_MAKER_AWS_SECRET"),
+        }
+
+        self.content_base_index_name = os.environ.get(
+            "INDEX_CONTENTBASES_NAME", "content_bases"
+        )
         self.sentry_dsn = os.environ.get("SENTRY_DSN", "")
         self.es_timeout = os.environ.get("ELASTICSEARCH_TIMEOUT", "30")
diff --git a/app/downloaders/__init__.py b/app/downloaders/__init__.py
new file mode 100644
index 0000000..2e0f087
--- /dev/null
+++ b/app/downloaders/__init__.py
@@ -0,0 +1,27 @@
+from abc import ABC, abstractmethod
+from app.downloaders.exceptions import FileDownloaderException
+
+
+class IFileDownloader(ABC):
+    @abstractmethod
+    def authenticate(self):
+        pass
+
+    @abstractmethod
+    def download_file(self):
+        pass
+
+    @abstractmethod
+    def download_file_batch(self):
+        pass
+
+    @abstractmethod
+    def download_file_bulk(self):
+        pass
+
+def download_file(file_downloader, file_name: str) -> None:
+    handler = file_downloader
+    try:
+        handler.download_file(file_name)
+    except Exception as err:
+        raise FileDownloaderException(err)
\ No newline at end of file
diff --git a/app/downloaders/exceptions.py b/app/downloaders/exceptions.py
new file mode 100644
index 0000000..fdcbc3f
--- /dev/null
+++ b/app/downloaders/exceptions.py
@@ -0,0 +1,2 @@
+class FileDownloaderException(BaseException):
+    pass
\ No newline at end of file
diff --git a/app/downloaders/s3/__init__.py b/app/downloaders/s3/__init__.py
new file mode 100644
index 0000000..7adb506
--- /dev/null
+++ b/app/downloaders/s3/__init__.py
@@ -0,0 +1 @@
+from app.downloaders.s3.file_downloader import S3FileDownloader
\ No newline at end of file
diff --git a/app/downloaders/s3/file_downloader.py b/app/downloaders/s3/file_downloader.py
new file mode 100644
index 0000000..8e9f6b9
--- /dev/null
+++ b/app/downloaders/s3/file_downloader.py
@@ -0,0 +1,46 @@
+import os
+import boto3
+from app.downloaders import IFileDownloader
+from fastapi.logger import logger
+from urllib.parse import urlparse
+from typing import Tuple, List
+
+
+class S3FileDownloader(IFileDownloader):
+
+    def __init__(self, 
+                 access_key: str,
+                 secret_key: str,
+                 bucket_name: str = os.environ.get("AWS_STORAGE_BUCKET_NAME"),
+        ) -> None:
+        self.bucket_name = bucket_name
+        self.access_key = access_key
+        self.secret_key = secret_key
+        self.client = self.authenticate()
+
+    def authenticate(self):
+        return boto3.client(
+            "s3",
+            aws_access_key_id=self.access_key,
+            aws_secret_access_key=self.secret_key
+        )
+
+    def download_file(self, file_name):
+        bucket = self.bucket_name
+        key = file_name
+        local_path = f"app/files/{file_name}"
+
+        self.client.download_file(bucket, key, local_path)
+
+    def download_file_batch(self):
+        raise NotImplementedError
+
+    def download_file_bulk(self):
+        raise NotImplementedError
+
+
+def get_s3_bucket_and_file_name(file_url: str)-> Tuple[str, ...]:
+    result = urlparse(file_url)
+    bucket_name = result.netloc.split('.s3')[0]
+    file_name = result.path.strip('/')
+    return bucket_name, file_name
diff --git a/app/embedders/__init__.py b/app/embedders/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/app/embedders/embedders.py b/app/embedders/embedders.py
new file mode 100644
index 0000000..4de451a
--- /dev/null
+++ b/app/embedders/embedders.py
@@ -0,0 +1,79 @@
+from pydantic.v1 import root_validator
+import time
+from langchain.embeddings import SagemakerEndpointEmbeddings
+from typing import Dict, List
+
+
+class SagemakerEndpointEmbeddingsKeys(SagemakerEndpointEmbeddings):
+    aws_key: str = ""
+    aws_secret: str = ""
+
+    @root_validator(skip_on_failure=True)
+    def validate_environment(cls, values: Dict) -> Dict:
+        import boto3
+
+        session = boto3.Session(
+        aws_access_key_id=values["aws_key"],
+        aws_secret_access_key=values["aws_secret"]
+        )
+
+        values["client"] = session.client(
+        "sagemaker-runtime", region_name=values["region_name"]
+        )
+
+        return values
+
+    def embed_documents(
+        self, texts: List[str], chunk_size: int = 32
+    ) -> List[List[float]]:
+        """Compute doc embeddings using a SageMaker Inference Endpoint.
+
+        Args:
+            texts: The list of texts to embed.
+            chunk_size: The chunk size defines how many input texts will
+                be grouped together as request. If None, will use the
+                chunk size specified by the class.
+
+
+        Returns:
+            List of embeddings, one for each text.
+        """
+        results = []
+        _chunk_size = len(texts) if chunk_size > len(texts) else chunk_size
+        for i in range(0, len(texts), _chunk_size):
+            response = self._embedding_func(texts[i:i + _chunk_size])
+            results.extend(response)
+        return results
+
+    def _embedding_func(self, texts: List[str]) -> List[List[float]]:
+        """Call out to SageMaker Inference embedding endpoint."""
+        # replace newlines, which can negatively affect performance.
+        texts = list(map(lambda x: x.replace("\n", " "), texts))
+        _model_kwargs = self.model_kwargs or {}
+        _endpoint_kwargs = self.endpoint_kwargs or {}
+
+        body = self.content_handler.transform_input(texts, _model_kwargs)
+        content_type = self.content_handler.content_type
+        accepts = self.content_handler.accepts
+
+        # send request
+        while True:
+            try:
+                response = self.client.invoke_endpoint(
+                    EndpointName=self.endpoint_name,
+                    Body=body,
+                    ContentType=content_type,
+                    Accept=accepts,
+                    **_endpoint_kwargs,
+                )
+                return self.content_handler.transform_output(response["Body"])
+            except Exception as e:
+                print(
+                    f"Error raised by inference endpoint: {e}\nBody: . Trying again in 5 seconds."
+                )
+                time.sleep(60 * 5)
+
+        raise ValueError(
+            f"Error raised by inference endpoint: {e}. Trying again in 5 seconds."
+        )
+        return self.content_handler.transform_output(response["Body"])
\ No newline at end of file
diff --git a/app/files/__init__.py b/app/files/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/app/handlers/authorizations.py b/app/handlers/authorizations.py
new file mode 100644
index 0000000..b6e5a8c
--- /dev/null
+++ b/app/handlers/authorizations.py
@@ -0,0 +1,8 @@
+import os
+from fastapi import HTTPException
+
+
+def token_verification(token: str):
+    if os.environ.get("SENTENX_TOKEN") == token:
+        return
+    raise HTTPException(status_code=401, detail=[{"msg": str("Unauthorized")}])
diff --git a/app/handlers/content_bases.py b/app/handlers/content_bases.py
new file mode 100644
index 0000000..f9f021c
--- /dev/null
+++ b/app/handlers/content_bases.py
@@ -0,0 +1,95 @@
+from fastapi import APIRouter, Header
+from pydantic import BaseModel
+
+from app.handlers import IDocumentHandler
+from app.indexer import IDocumentIndexer
+
+from app.celery import index_file_data
+from typing import List
+from typing import Annotated
+from app.handlers.authorizations import token_verification
+
+
+class ContentBaseIndexRequest(BaseModel):
+    file: str
+    filename: str
+    file_uuid: str
+    extension_file: str
+    task_uuid: str
+    content_base: str
+
+
+class ContentBaseIndexResponse(BaseModel):
+    file: str
+    filename: str
+    task_uuid: str
+
+
+class ContentBaseSearchRequest(BaseModel):
+    search: str
+    filter: dict[str, str] = None
+    threshold: float = 1.5
+
+
+class ContentBaseSearchResponse(BaseModel):
+    response: List[str]
+
+
+class ContentBaseDeleteRequest(BaseModel):
+    filename: str
+    content_base: str
+    file_uuid: str
+
+
+class ContentBaseDeleteResponse(BaseModel):
+    deleted: bool
+
+
+class ContentBaseHandler(IDocumentHandler):
+    def __init__(self, content_base_indexer: IDocumentIndexer):
+        self.content_base_indexer = content_base_indexer
+        self.router = APIRouter()
+        self.router.add_api_route(
+            "/content_base/index", endpoint=self.index, methods=["PUT"]
+        )
+        self.router.add_api_route(
+            "/content_base/search", endpoint=self.search, methods=["POST"]
+        )
+        self.router.add_api_route(
+            "/content_base/delete", endpoint=self.delete, methods=["DELETE"]
+        )
+
+    def index(self, request: ContentBaseIndexRequest, Authorization: Annotated[str | None, Header()] = None):
+        token_verification(Authorization)
+        content_base = request.__dict__
+        task = index_file_data.delay(content_base)
+
+        return ContentBaseIndexResponse(
+            file=request.file,
+            filename=request.filename,
+            task_uuid=task.id,
+        )
+
+    def batch_index(self):
+        raise NotImplementedError
+
+    def delete(self, request: ContentBaseDeleteRequest, Authorization: Annotated[str | None, Header()] = None):
+        token_verification(Authorization)
+        self.content_base_indexer.delete(
+            request.content_base,
+            request.filename,
+            request.file_uuid,
+        )
+        return ContentBaseDeleteResponse(deleted=True)
+
+    def delete_batch(self):
+        raise NotImplementedError
+
+    def search(self, request: ContentBaseSearchRequest, Authorization: Annotated[str | None, Header()] = None):
+        token_verification(Authorization)
+        response = self.content_base_indexer.search(
+            search=request.search.lower(),
+            threshold=request.threshold,
+            filter=request.filter
+        )
+        return ContentBaseSearchResponse(response=response)
diff --git a/app/handlers/nexus.py b/app/handlers/nexus.py
new file mode 100644
index 0000000..1ea94d8
--- /dev/null
+++ b/app/handlers/nexus.py
@@ -0,0 +1,25 @@
+
+import os
+import json
+import requests
+
+
+class NexusRESTClient:
+    token = os.environ.get("NEXUS_AI_TOKEN")
+    base_url = os.environ.get("NEXUS_AI_URL")
+
+    def __init__(self) -> None:
+        self.headers = {
+            'Authorization': self.token,
+            'Content-Type': "application/json"
+        }
+
+    def index_succedded(self, task_succeded: bool, nexus_task_uuid: str, file_type: str) -> None:
+        endpoint = f'{self.base_url}/api/v1/content-base-file'
+        data = { 
+            "status": int(task_succeded),
+            "task_uuid": nexus_task_uuid,
+            "file_type": "text" if file_type == "txt" else "file",
+        }
+        response = requests.patch(url=endpoint, data=json.dumps(data), headers=self.headers)
+        response.raise_for_status()
diff --git a/app/indexer/content_bases.py b/app/indexer/content_bases.py
new file mode 100644
index 0000000..c14f7bf
--- /dev/null
+++ b/app/indexer/content_bases.py
@@ -0,0 +1,80 @@
+from langchain.docstore.document import Document
+
+from app.handlers.products import Product
+from app.indexer import IDocumentIndexer
+from app.store import IStorage
+from typing import List
+from uuid import UUID
+
+
+class ContentBaseIndexer(IDocumentIndexer):
+    def __init__(self, storage: IStorage):
+        self.storage = storage
+
+    def index_documents(self, docs: List[Document]):
+        file_uuid = docs[0].metadata["file_uuid"]
+        content_base_uuid = docs[0].metadata["content_base_uuid"]
+
+        results = self._search_docs_by_content_base_uuid(
+            content_base_uuid=content_base_uuid,
+            file_uuid=file_uuid,
+        )
+        ids = []
+        if len(results) > 0:
+            ids = [item["_id"] for item in results]
+            self.storage.delete(ids=ids)
+
+        return self.storage.save(docs)
+
+    def index(self, texts: List, metadatas: dict):
+        results = self._search_docs_by_content_base_uuid(
+            content_base_uuid=metadatas.get('content_base_uuid')
+        )
+        ids = []
+        if len(results) > 0:
+            ids = [item["_id"] for item in results]
+            self.storage.delete(ids=ids)
+
+        docs = [
+            Document(page_content=text.lower(), metadata=metadatas)
+            for text in texts
+        ]
+
+        return self.storage.save(docs)
+
+    def index_batch(self):
+        raise NotImplementedError
+
+    def search(self, search, filter=None, threshold=0.1) -> list[Product]:
+        matched_responses = self.storage.search(search, filter, threshold)
+        return set([doc.metadata.get("full_page") for doc in matched_responses])
+
+    def _search_docs_by_content_base_uuid(self, content_base_uuid: UUID, file_uuid: str = None):
+        search_filter = {
+            "metadata.content_base_uuid": content_base_uuid
+        }
+        if file_uuid:
+            search_filter.update({"metadata.file_uuid": file_uuid})
+        return self.storage.query_search(search_filter)
+
+    def delete(self, content_base_uuid: UUID, filename: str, file_uuid: str):
+        search_filter = {
+            "metadata.content_base_uuid": content_base_uuid,
+            "metadata.file_uuid": file_uuid,
+        }
+
+        if filename:
+            search_filter.update({"metadata.source": filename})
+
+        scroll_id, results = self.storage.search_delete(search_filter)
+        ids = []
+
+        while len(results) > 0:
+            ids += [item["_id"] for item in results]
+            scroll_id, results = self.storage.search_delete(search_filter, scroll_id)
+        
+        if ids:
+            self.storage.delete(ids=ids)
+
+    def delete_batch(self):
+        raise NotImplementedError
diff --git a/app/indexer/indexer_file_manager.py b/app/indexer/indexer_file_manager.py
new file mode 100644
index 0000000..c5f093c
--- /dev/null
+++ b/app/indexer/indexer_file_manager.py
@@ -0,0 +1,91 @@
+from app.loaders import load_file_and_get_raw_text, load_file_url_and_get_raw_text, load_file_url_and_get_pages_text, load_file_url_and_split_text
+from app.text_splitters import get_split_text
+from typing import Dict, List
+from fastapi.logger import logger
+from langchain.schema.document import Document
+from app.indexer import IDocumentIndexer
+from app.downloaders import IFileDownloader
+from app.text_splitters import ITextSplitter
+
+
+def get_file_metadata(content_base: Dict) -> Dict[str, str]:
+    return {
+            'source': content_base.get("filename"),
+            "content_base_uuid": str(content_base.get('content_base'))
+        }
+
+def add_file_metadata(document_pages: List[Document], content_base: Dict) -> List[Document]:
+    metadata = {
+        "content_base_uuid": str(content_base.get('content_base')),
+        "filename": content_base.get("filename"),
+        "file_uuid": content_base.get("file_uuid")
+
+    }
+    for page in document_pages:
+        page.metadata.update(metadata)
+    
+    return document_pages
+
+class IndexerFileManager:
+
+    """Business rule to index a file"""
+
+    def __init__(self,
+                 file_downloader: IFileDownloader,
+                 content_base_indexer: IDocumentIndexer,
+                 text_splitter: ITextSplitter
+                 ) -> None:
+        self.file_downloader = file_downloader
+        self.content_base_indexer = content_base_indexer
+        self.text_splitter = text_splitter
+
+    def index_file_url(self, content_base) -> bool:
+        docs: List[Document] = load_file_url_and_split_text(
+            content_base.get("file"),
+            content_base.get('extension_file'),
+            self.text_splitter
+        )
+        document_pages: List[Document] = add_file_metadata(docs, content_base)
+        try:
+            self.content_base_indexer.index_documents(document_pages)
+            return True
+        except Exception as e:  # TODO: handle exceptions
+            logger.exception(e)
+            return False
+
+
+    def index_file_url_raw_text(self, content_base):
+        file_raw_text: str = load_file_url_and_get_raw_text(
+                content_base.get("file"), content_base.get('extension_file')
+            )
+        metadatas: Dict[str, str] = get_file_metadata(content_base)
+        texts: List[str] = get_split_text(file_raw_text)
+
+        try:
+            self.content_base_indexer.index(texts, metadatas)
+            return True
+        except Exception as e:  # TODO: handle exceptions
+            logger.exception(e)
+            return False
+
+    def index_file(self, content_base):
+        filename: str = content_base.get("filename")
+
+        try:
+            self.file_downloader.download_file(filename)
+        except Exception as err:
+            logger.exception(err)
+            return False
+
+        file_raw_text: str = load_file_and_get_raw_text(
+                filename, content_base.get('extension_file')
+            )
+        metadatas: Dict[str, str] = get_file_metadata(content_base)
+        texts: List[str] = get_split_text(file_raw_text)
+
+        try:
+            self.content_base_indexer.index(texts, metadatas)
+            return True
+        except Exception as e:  # TODO: handle exceptions
+            logger.exception(e)
+            return False
diff --git a/app/loaders/__init__.py b/app/loaders/__init__.py
new file mode 100644
index 0000000..a119461
--- /dev/null
+++ b/app/loaders/__init__.py
@@ -0,0 +1,48 @@
+
+import os
+from app.loaders.loaders import (DataLoader, txt_loader, pdf_loader, docx_loader, xlsx_loader, DataLoaderCls, PDFLoader, DocxLoader, TxtLoader, XlsxLoader)
+from langchain.schema.document import Document
+from typing import List
+from app.text_splitters import ITextSplitter
+supported_loaders = {
+    'txt': txt_loader,
+    'pdf': pdf_loader,
+    'doc': docx_loader,
+    'docx': docx_loader,
+    'xls': xlsx_loader,
+    'xlsx': xlsx_loader,
+}
+
+supported_loaders_cls = {
+    'pdf': PDFLoader,
+    'doc': DocxLoader,
+    'docx': DocxLoader,
+    'txt': TxtLoader,
+    'xlsx': XlsxLoader,
+    'xls': XlsxLoader,
+}
+
+
+def load_file_and_get_raw_text(file_name: str, file_type: str) -> str:
+    file_path = f'{os.environ.get("FILE_PATH")}/{file_name}'
+    loader = supported_loaders.get(file_type)
+    data_loader = DataLoader(loader, file_path)
+    return data_loader.raw_text()
+
+
+def load_file_url_and_get_raw_text(file_url: str, file_type: str) -> str:
+    loader = supported_loaders.get(file_type)
+    data_loader = DataLoader(loader, file_url)
+    return data_loader.raw_text()
+
+
+def load_file_url_and_get_pages_text(file_url: str, file_type: str) -> List[Document]:
+    loader = supported_loaders.get(file_type)
+    data_loader = DataLoader(loader, file_url)
+    return data_loader.load()
+
+
+def load_file_url_and_split_text(file_url: str, file_type: str, text_splitter: ITextSplitter) -> List[Document]:
+    loader = supported_loaders_cls.get(file_type)
+    data_loader = DataLoaderCls(loader, file_url)
+    return data_loader.load_and_split_text(text_splitter)
\ No newline at end of file
diff --git a/app/loaders/loaders.py b/app/loaders/loaders.py
index bc53ad8..bffe77a 100644
--- a/app/loaders/loaders.py
+++ b/app/loaders/loaders.py
@@ -1,9 +1,37 @@
+import os
+import uuid
+import requests
+from abc import ABC, abstractmethod
+
 from langchain.document_loaders import (
     TextLoader, PyPDFLoader, UnstructuredExcelLoader,
     UnstructuredWordDocumentLoader, Docx2txtLoader
 )
-from typing import Callable, List
 from langchain.schema.document import Document
+from typing import Callable, List
+from app.text_splitters import ITextSplitter
+
+
+class DocumentLoader(ABC):
+
+    @abstractmethod
+    def load(self):
+        pass
+
+
+class DataLoaderCls:
+    def __init__(self, loader: DocumentLoader, file: str) -> None:
+        self.loader = loader(file)
+        self.file = file
+
+    def load(self) -> List[Document]:
+        return self.loader.load()
+    
+    def load_and_split_text(self, text_splitter: ITextSplitter) -> List[Document]:
+        return self.loader.load_and_split_text(text_splitter)
+
+    def raw_text(self) -> str:
+        return self.loader.raw_text()
 
 
 class DataLoader:
@@ -28,6 +56,71 @@ def txt_loader(file: str) -> Callable:
     loader = TextLoader(file)
     return loader.load()
 
+class TxtLoader(DocumentLoader):
+    def _get_file(self, file: str):
+        if os.environ.get("AWS_STORAGE_BUCKET_NAME") in file:
+            response = requests.get(file)
+            if response.status_code == 200:
+                file_path = f"/tmp/{uuid.uuid4()}.txt"
+                text = response.text
+                with open(file_path, "w") as file:
+                    file.write(text)
+                return file_path
+        return file
+
+    def __init__(self, file:str) -> None:
+        self.file = self._get_file(file)
+        self.loader = TextLoader(self.file)
+    
+    def load(self) -> List[Document]:
+        return self.loader.load_and_split()
+    
+    def load_and_split_text(self, text_splitter: ITextSplitter) -> List[Document]:
+        pages = self.load()
+        split_pages = []
+        for page in pages:
+            page_content = page.page_content.lower()
+            metadatas = page.metadata
+            metadatas.update({"full_page": page_content})
+
+            text_chunks = text_splitter.split_text(page_content)
+            for chunk in text_chunks:
+                split_pages.append(Document(page_content=chunk, metadata=metadatas))
+        return split_pages
+
+
+class PDFLoader(DocumentLoader):
+    def __init__(self, file: str) -> None:
+        self.loader = PyPDFLoader(file)
+
+    def load(self) -> List[Document]:
+        pages = self.loader.load_and_split()
+        return pages
+
+    def load_and_split_text(self, text_splitter: ITextSplitter) -> List[Document]:
+        pages = self.load()
+        split_pages = []
+
+        for page in pages:
+            page_content = page.page_content.lower()
+            metadatas = page.metadata
+            metadatas.update({"full_page": page_content})
+
+            text_chunks = text_splitter.split_text(page_content)
+            for chunk in text_chunks:
+                split_pages.append(Document(page_content=chunk, metadata=metadatas))
+
+        return split_pages
+
+    def raw_text(self) -> str:
+        pages = self.load()
+        raw_text = ""
+        for i, page in enumerate(pages):
+            text = page.page_content
+            if text:
+                raw_text += text.lower()
+        return raw_text
+
 
 def pdf_loader(file: str) -> Callable:
     loader = PyPDFLoader(file)
@@ -35,6 +128,27 @@ def pdf_loader(file: str) -> Callable:
     return pages
 
 
+class DocxLoader(DocumentLoader):
+    def __init__(self, file:str) -> None:
+        self.loader = Docx2txtLoader(file)
+
+    def load(self) -> List[Document]:
+        return self.loader.load_and_split()
+    
+    def load_and_split_text(self, text_splitter: ITextSplitter) -> List[Document]:
+        pages = self.load()
+        split_pages = []
+        for page in pages:
+            page_content = page.page_content.lower()
+            metadatas = page.metadata
+            metadatas.update({"full_page": page_content})
+
+            text_chunks = text_splitter.split_text(page_content)
+            for chunk in text_chunks:
+                split_pages.append(Document(page_content=chunk, metadata=metadatas))
+        return split_pages
+
+
 def docx_loader(file: str) -> Callable:
     loader = Docx2txtLoader(file)
     return loader.load()
@@ -50,3 +164,33 @@ def xlsx_loader(file: str) -> Callable:
     """Loads .xlsx and .xls files"""
     loader = UnstructuredExcelLoader(file, mode="elements")
     return loader.load()
+
+from urllib.request import urlretrieve
+from urllib.parse import urlparse
+class XlsxLoader(DocumentLoader):
+    def __init__(self, file:str) -> None:
+        tmp_file, _ = self._get_temp_file(file)
+        self.loader = UnstructuredExcelLoader(tmp_file, mode="single")
+    
+    def _get_temp_file(self, file_url: str):
+        result = urlparse(file_url)
+        filename = result.path.strip("/")
+        file_path, message = urlretrieve(file_url, f"/tmp/{filename}")
+        return file_path, message
+
+
+    def load(self) -> List[Document]:
+        return self.loader.load_and_split()
+    
+    def load_and_split_text(self, text_splitter: ITextSplitter) -> List[Document]:
+        pages = self.load()
+        split_pages = []
+        for page in pages:
+            page_content = page.page_content.lower()
+            metadatas = page.metadata
+            metadatas.update({"full_page": page_content})
+
+            text_chunks = text_splitter.split_text(page_content)
+            for chunk in text_chunks:
+                split_pages.append(Document(page_content=chunk, metadata=metadatas))
+        return split_pages
diff --git a/app/main.py b/app/main.py
index f6599b2..fd50383 100644
--- a/app/main.py
+++ b/app/main.py
@@ -9,11 +9,16 @@
 from app.handlers.products import ProductsHandler
 from app.indexer import IDocumentIndexer
 from app.indexer.products import ProductsIndexer
-from app.store.elasticsearch_vector_store import ElasticsearchVectorStoreIndex
+from app.store.elasticsearch_vector_store import ElasticsearchVectorStoreIndex, ContentBaseElasticsearchVectorStoreIndex
 from app.config import AppConfig
 from app.util import ContentHandler
 
 
+from app.handlers.content_bases import ContentBaseHandler
+from app.indexer.content_bases import ContentBaseIndexer
+from app.embedders.embedders import SagemakerEndpointEmbeddingsKeys
+
+
 class App:
     api: FastAPI
     config: AppConfig
@@ -59,6 +64,23 @@ def __init__(self, config: AppConfig):
         self.products_handler = ProductsHandler(self.products_indexer)
         self.api.include_router(self.products_handler.router)
 
+        content_base_content_handler = ContentHandler()
+        self.content_base_embeddings = SagemakerEndpointEmbeddingsKeys(
+                aws_key=config.sagemaker_aws["aws_key"],
+                aws_secret=config.sagemaker_aws["aws_secret"],
+                endpoint_name=config.sagemaker_aws["endpoint_name"],
+                region_name=config.sagemaker_aws["region_name"],
+                content_handler=content_base_content_handler,
+            )
+        self.content_base_vectorstore = ElasticVectorSearch(
+            elasticsearch_url=config.es_url,
+            index_name=config.content_base_index_name,
+            embedding=self.content_base_embeddings,
+        )
+        self.custom_elasticStore = ContentBaseElasticsearchVectorStoreIndex(self.content_base_vectorstore)
+        self.content_base_indexer = ContentBaseIndexer(self.custom_elasticStore)
+        self.content_base_handler = ContentBaseHandler(self.content_base_indexer)
+        self.api.include_router(self.content_base_handler.router)
 
 config = AppConfig()
 main_app = App(config)
diff --git a/app/store/elasticsearch_vector_store.py b/app/store/elasticsearch_vector_store.py
index c237613..95124f9 100644
--- a/app/store/elasticsearch_vector_store.py
+++ b/app/store/elasticsearch_vector_store.py
@@ -1,9 +1,10 @@
+import os
+
 from langchain.vectorstores import VectorStore
 from langchain.docstore.document import Document
 
 from app.store import IStorage
-
-
+from fastapi.logger import logger
 class ElasticsearchVectorStoreIndex(IStorage):
     def __init__(self, vectorstore: VectorStore, score=1.55):
         self.vectorstore = vectorstore
@@ -50,3 +51,80 @@ def query_search(self, search_filter: dict) -> list[dict]:
 
     def delete(self, ids: list[str] = []) -> bool:
         return self.vectorstore.delete(ids)
+
+
+class ContentBaseElasticsearchVectorStoreIndex(ElasticsearchVectorStoreIndex):
+
+    def save(self, docs: list[Document])-> list[str]:
+        index = os.environ.get("INDEX_CONTENTBASES_NAME", "content_bases")
+        res = self.vectorstore.from_documents(docs, self.vectorstore.embeddings, index_name=index)
+        return res
+
+    def query_search(self, search_filter: dict) -> list[dict]:
+        match_field: str = list(search_filter.keys())[0]
+        match_value: str = search_filter[match_field]
+
+        query_script = {
+            "bool": {
+                "must": [{"match": {match_field: match_value}}],
+            }
+        }
+        try:
+            self.vectorstore.client.indices.get(index=self.vectorstore.index_name)
+        except Exception as e:
+            return []
+
+        source = ["metadata"]
+        response = self.vectorstore.client.search(
+            index=self.vectorstore.index_name, query=query_script, source=source
+        )
+        hits = [hit for hit in response["hits"]["hits"]]
+        return hits
+
+    def search_delete(self, search_filter: dict, scroll_id: str = None) -> tuple[str, dict]:
+
+        if scroll_id:
+            response = self.vectorstore.client.scroll(scroll_id=scroll_id, scroll='2m')
+            scroll_id = response["_scroll_id"]
+            hits = [hit for hit in response["hits"]["hits"]]
+            return scroll_id, hits
+
+        match_field1: str = list(search_filter.keys())[0]
+        match_value1: str = search_filter[match_field1]
+        match_field2 = list(search_filter.keys())[1]
+        match_value2 = search_filter[match_field2]
+
+        query_script = {
+            "bool": {
+                "must": [
+                    {"match": {match_field1: match_value1}},
+                    {"match": {match_field2: match_value2}}
+                ],
+            }
+        }
+
+        try:
+            self.vectorstore.client.indices.get(index=self.vectorstore.index_name)
+        except Exception as e:
+            return []
+
+        source = ["metadata"]
+
+
+        response = self.vectorstore.client.search(
+            index=self.vectorstore.index_name,
+            query=query_script,
+            source=source,
+            scroll="2m",
+            size=100,
+        )
+        scroll_id = response["_scroll_id"]
+        hits = [hit for hit in response["hits"]["hits"]]
+        return scroll_id, hits
+
+    def search(self, search: str, filter=None, threshold=0.1) -> list[Document]:
+        docs = self.vectorstore.similarity_search_with_score(query=search, k=5, filter=filter)
+        return [doc[0] for doc in docs if doc[1] > threshold]
+
+    def delete(self, ids: list[str] = []) -> bool:
+        return self.vectorstore.delete(ids)
diff --git a/app/tests/test_document_loader.py b/app/tests/test_document_loader.py
index 440da47..bc6a96d 100644
--- a/app/tests/test_document_loader.py
+++ b/app/tests/test_document_loader.py
@@ -1,25 +1,43 @@
 import unittest
 from app.loaders.loaders import (
     DataLoader,
+    DataLoaderCls,
+    PDFLoader,
+    DocxLoader,
+    TxtLoader,
     pdf_loader,
     txt_loader,
     docx_loader,
     u_docx_loader,
     xlsx_loader
 )
+from unittest import mock
+from app.loaders import (
+    load_file_url_and_split_text,
+    load_file_url_and_get_pages_text,
+    load_file_and_get_raw_text,
+    load_file_url_and_get_raw_text
+)
 import os
 import pathlib
 import shutil
 import xlsxwriter
 from docx import Document
 from reportlab.pdfgen.canvas import Canvas
+from app.text_splitters import TextSplitter, character_text_splitter
+from typing import List
+
+
+TEST_DIR = pathlib.Path(__file__).parent.resolve()
+TEST_FILE_PATH = os.path.join(TEST_DIR, 'test_files')
 
 
 class TestDocumentLoader(unittest.TestCase):
-    test_dir = pathlib.Path(__file__).parent.resolve()
-    path = os.path.join(test_dir, 'test_files')
+    test_dir = TEST_DIR
+    path = TEST_FILE_PATH
     text_string = 'Hello, World!'
     file_name = 'test_file'
+    text_splitter = TextSplitter(character_text_splitter())
 
     @staticmethod
     def _create_test_dir():
@@ -104,6 +122,67 @@ def test_load_xlsx(self):
         raw_text = data_loader.raw_text()
         self.assertEqual(type(raw_text), str)
 
+    def test_pdf_loader_cls(self):
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        pdf_loader = PDFLoader(file_path)
+        split_pages: List[Document] = pdf_loader.load_and_split_text(self.text_splitter)
+        self.assertEqual(list, type(split_pages))
+
+    def test_docx_loader_cls(self):
+        file_path = f'{self.path}/{self.file_name}.docx'
+        docx_loader = DocxLoader(file_path)
+        split_pages: List[Document] = docx_loader.load_and_split_text(self.text_splitter)
+        self.assertEqual(list, type(split_pages))
+    
+    def test_txt_loader_cls(self):
+        file_path = f'{self.path}/{self.file_name}.txt'
+        docx_loader = TxtLoader(file_path)
+        split_pages: List[Document] = docx_loader.load_and_split_text(self.text_splitter)
+        self.assertEqual(list, type(split_pages))
+
+    def test_load_file_url_and_split_text(self):
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        file_type = "pdf"
+        docs = load_file_url_and_split_text(file_path, file_type, self.text_splitter)
+        self.assertEqual(list, type(docs))
+
+    def test_load_file_url_and_get_pages_text(self):  # this function is deprecated
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        file_type = "pdf"
+        docs = load_file_url_and_get_pages_text(file_path ,file_type)
+        self.assertEqual(list, type(docs))
+
+    @mock.patch.dict(os.environ, {"FILE_PATH": TEST_FILE_PATH})
+    def test_load_file_and_get_raw_text(self):  # this function is deprecated
+        file_type = "pdf"
+        raw_text = load_file_and_get_raw_text(f"{self.file_name}.{file_type}" ,file_type)
+        self.assertEqual(str, type(raw_text))
+
+    def test_file_url_and_get_raw_text(self):  # this function is deprecated
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        file_type = "pdf"
+        raw_text = load_file_url_and_get_raw_text(file_path ,file_type)
+        self.assertEqual(str, type(raw_text))
+
+    def test_pdf_loader_cls_raw_text(self):
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        pdf_loader = PDFLoader(file_path)
+        raw_text = pdf_loader.raw_text()
+        self.assertEqual(str, type(raw_text))
+
+    def test_data_loader_cls(self):
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        data_loader = DataLoaderCls(PDFLoader, file_path)
+        loaded_data: List[Document] = data_loader.load()
+        self.assertEqual(list, type(loaded_data))
+    
+    def test_data_loader_raw_text(self):
+        file_path = f'{self.path}/{self.file_name}.pdf'
+        data_loader = DataLoaderCls(PDFLoader, file_path)
+        loaded_data: str = data_loader.raw_text()
+        self.assertEqual(str, type(loaded_data))
+
+
     @classmethod
     def tearDownClass(cls):
         if os.path.exists(TestDocumentLoader.path):
diff --git a/app/tests/test_elasticsearch_vector_store.py b/app/tests/test_elasticsearch_vector_store.py
index da9f9ce..3efb301 100644
--- a/app/tests/test_elasticsearch_vector_store.py
+++ b/app/tests/test_elasticsearch_vector_store.py
@@ -2,7 +2,7 @@
 
 from langchain.vectorstores import ElasticVectorSearch
 from langchain.docstore.document import Document
-from app.store.elasticsearch_vector_store import ElasticsearchVectorStoreIndex
+from app.store.elasticsearch_vector_store import ElasticsearchVectorStoreIndex, ContentBaseElasticsearchVectorStoreIndex
 from unittest.mock import Mock
 
 
@@ -84,3 +84,114 @@ def test_query_search_with_exception(self):
             {"doc_generic_id": "123", "metadata.sku": ["SKU-123"]}
         )
         self.assertEqual(result, [])
+
+
+class ContentBaseElasticsearchVectorStoreIndexTest(unittest.TestCase):
+    def setUp(self):
+        self.vectorstore = Mock(spec=ElasticVectorSearch)
+        self.vectorstore.index_name = "index_test"
+        self.vectorstore.client = Mock()
+        self.vectorstore.embeddings = Mock()
+        self.vectorstore.client.indices = Mock()
+        self.storage = ContentBaseElasticsearchVectorStoreIndex(self.vectorstore)
+        self.doc = Document(page_content="test doc", metadata={"full_page": "test document index", "content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977"})
+    def test_save(self):
+        self.vectorstore.from_documents.return_value = [
+            "f40a4707-549e-4847-8f48-19b1987b8149"
+        ]
+        doc = Document(page_content="test doc", metadata={
+            "full_page": "test document index",
+            "content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977"}
+            )
+        result = self.storage.save(doc)
+        self.vectorstore.from_documents(
+            [self.doc], self.vectorstore.embeddings, self.vectorstore.index_name
+        )
+        self.assertEqual(result, ["f40a4707-549e-4847-8f48-19b1987b8149"])
+
+    def test_delete(self):
+        self.vectorstore.delete.return_value = True
+        result = self.storage.delete(ids=["dfff32e7-dce6-40f7-a86e-8f9618887977"])
+        self.assertEqual(True, result)
+
+    def test_search(self):
+        self.vectorstore.similarity_search_with_score.return_value = [
+            (
+                self.doc,
+                1.5,
+            )
+        ]
+        query_filter = {"content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977"}
+        results = self.storage.search(
+            search="test", filter=query_filter
+        )
+        self.vectorstore.similarity_search_with_score.assert_called_once_with(
+            query="test", k=5, filter=query_filter
+        )
+        self.assertEqual(1, len(results))
+        self.assertEqual(results[0].page_content, "test doc")
+
+    def test_query_search(self):
+        self.vectorstore.client.indices.get.return_value = True
+        mock_search_hits = [{"_id": "53899082-cf01-41d1-ba9b-320a90670755"}]
+        self.vectorstore.client.search.return_value = {
+            "hits": {"hits": mock_search_hits}
+        }
+        result = self.storage.query_search(
+            {"metadata.content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977"}
+        )
+        self.assertEqual(result, mock_search_hits)
+    
+    def test_query_search_with_exception(self):
+        query_filter = {"content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977"}
+
+        self.vectorstore.client.indices.get.side_effect = RuntimeError(
+            "Index Not Found"
+        )
+        result = self.storage.query_search(
+            query_filter
+        )
+        self.assertEqual(result, [])
+
+    def test_search_delete(self):
+        search_filter = {
+            "metadata.content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977",
+            "metadata.filename": "filename.pdf"
+        }
+        self.vectorstore.client.indices.get.return_value = True
+        self.vectorstore.client.search.return_value = {
+            "_scroll_id": "dfff32e7",
+            "hits": {
+                "hits": [{"_id": "53899082-cf01-41d1-ba9b-320a90670755"}]
+            }
+        }
+        result = self.storage.search_delete(search_filter)
+        mock_search_tuple = ('dfff32e7', [{'_id': '53899082-cf01-41d1-ba9b-320a90670755'}])
+        self.assertEqual(result, mock_search_tuple)
+    
+    def test_search_delete_scroll_id(self):
+        search_filter = {
+            "metadata.content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977",
+            "metadata.filename": "filename.pdf"
+        }
+        self.vectorstore.client.indices.get.return_value = True
+        self.vectorstore.client.scroll.return_value = {
+            "_scroll_id": "53899082",
+            "hits": {
+                "hits": [{"_id": "43899082-cf01-81d1-ba9b-329a90670755"}]
+            }
+        }
+        result = self.storage.search_delete(search_filter, "dfff32e7")
+        mock_search_tuple = ('53899082', [{'_id': '43899082-cf01-81d1-ba9b-329a90670755'}])
+        self.assertEqual(result, mock_search_tuple)
+
+    def test_search_delete_with_exception(self):
+        search_filter = {
+            "metadata.content_base_uuid": "dfff32e7-dce6-40f7-a86e-8f9618887977",
+            "metadata.filename": "filename.pdf"
+        }
+        self.vectorstore.client.indices.get.side_effect = RuntimeError(
+            "Index Not Found"
+        )
+        result = self.storage.search_delete(search_filter)
+        self.assertEqual(result, [])
\ No newline at end of file
diff --git a/app/tests/test_text_splitter.py b/app/tests/test_text_splitter.py
new file mode 100644
index 0000000..412545c
--- /dev/null
+++ b/app/tests/test_text_splitter.py
@@ -0,0 +1,39 @@
+import unittest
+from app.text_splitters.text_splitters import (
+    TextSplitter, character_text_splitter, get_split_text
+)
+from lorem_text import lorem
+
+from typing import Callable, List, Dict
+from langchain.schema.document import Document
+
+class TestProductsHandler(unittest.TestCase):
+    def setUp(self):
+        self.text = lorem.paragraphs(5)
+
+    def test_character_text_splitter_split_text(self):
+        chunk_size=75
+        splitter = TextSplitter(character_text_splitter(chunk_size=chunk_size))
+        chunks = splitter.split_text(self.text)
+        self.assertEqual(type(chunks), list)
+        [self.assertGreaterEqual(len(chunk), chunk_size) for chunk in chunks]
+
+    def test_character_text_splitter_create_documents(self):
+        chunk_size=75
+        metadatas = [{"text_size": len(self.text)}]
+        text_list = [self.text]
+        splitter = TextSplitter(character_text_splitter(chunk_size=chunk_size))
+        docs = splitter.create_documents(text_list, metadatas)
+        self.assertIs(list, type(docs))
+        self.assertIs(Document, type(docs[0]))
+
+    def test_character_text_splitter_split_documents(self):
+        chunk_size=75
+        splitter = TextSplitter(character_text_splitter(chunk_size=chunk_size))
+        doc = Document(page_content=self.text, metadata={"text_size": len(self.text)})
+        docs = splitter.split_documents([doc])
+        self.assertIs(list, type(docs))
+    
+    def test_get_split_text(self):
+        texts: List[str] = get_split_text(self.text)
+        self.assertIs(list, type(texts))
diff --git a/app/text_splitters/__init__.py b/app/text_splitters/__init__.py
new file mode 100644
index 0000000..f3993a3
--- /dev/null
+++ b/app/text_splitters/__init__.py
@@ -0,0 +1 @@
+from app.text_splitters.text_splitters import get_split_text, ITextSplitter, TextSplitter, character_text_splitter
diff --git a/app/text_splitters/text_splitters.py b/app/text_splitters/text_splitters.py
new file mode 100644
index 0000000..94d78ec
--- /dev/null
+++ b/app/text_splitters/text_splitters.py
@@ -0,0 +1,58 @@
+import os
+from abc import ABC, abstractmethod
+
+from typing import Callable, List, Dict
+from langchain.schema.document import Document
+from langchain.text_splitter import CharacterTextSplitter
+from app.util import count_words
+
+DEFAULT_CHUNK_SIZE = os.environ.get("DEFAULT_CHUNK_SIZE", 75)
+DEFAULT_CHUNK_OVERLAP = os.environ.get("DEFAULT_CHUNK_OVERLAP", 75)
+DEFAULT_SEPARATOR = os.environ.get("DEFAULT_SEPARATOR", "\n")
+
+
+class ITextSplitter(ABC):  #pragma: no cover
+
+    @abstractmethod
+    def split_text(self):
+        raise NotImplementedError
+
+    @abstractmethod
+    def create_documents(self):
+        raise NotImplementedError
+
+
+class TextSplitter(ITextSplitter):
+    def __init__(self, text_splitter: Callable) -> None:
+        self.text_splitter = text_splitter
+
+    def split_text(self, content) -> List[str]:
+        pages = self.text_splitter.split_text(content)
+        return pages
+    
+    def create_documents(self, content: List[str], metadatas: List[Dict]) -> List[Document]:
+        return self.text_splitter.create_documents(content, metadatas=metadatas)
+
+    def split_documents(self, content: Document):
+        return self.text_splitter.split_documents(content)
+
+
+def character_text_splitter(
+        chunk_size: int = DEFAULT_CHUNK_SIZE,
+        chunk_overlap: int = DEFAULT_CHUNK_OVERLAP,
+        length_function: Callable = count_words,
+        separator: str = DEFAULT_SEPARATOR) -> List:
+
+    text_splitter = CharacterTextSplitter(
+        chunk_size=chunk_size,
+        chunk_overlap=chunk_overlap,
+        length_function=length_function,
+        separator=separator,
+    )
+    return text_splitter
+
+
+def get_split_text(raw_data: str):
+    text_splitter = TextSplitter(character_text_splitter())
+    texts = text_splitter.split_text(raw_data)
+    return texts
\ No newline at end of file
diff --git a/app/util.py b/app/util.py
index f4be75f..a4c0aa7 100644
--- a/app/util.py
+++ b/app/util.py
@@ -14,3 +14,7 @@ def transform_input(self, inputs: list[str], model_kwargs: dict) -> bytes:
     def transform_output(self, output: bytes) -> list[list[float]]:
         response_json = json.loads(output.read().decode("utf-8"))
         return response_json["vectors"]
+
+
+def count_words(string: str):
+    return len(string.split())
diff --git a/docker-compose.yml b/docker-compose.yml
index 7c28fca..a691bfb 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -8,12 +8,25 @@ services:
       - "8000:8000"
     depends_on:
       - elasticsearch
+      - redis
     environment:
-      - AWS_SECRET_ACCESS_KEY=<AWS_VALID_SECRET_KEY>
-      - AWS_ACCESS_KEY_ID=<AWS_VALID_ACCESS_KEY>
-      - ELASTICSEARCH_URL=http://elasticsearch:9200
+      - AWS_SECRET_ACCESS_KEY=${AWS_VALID_SECRET_KEY}
+      - AWS_ACCESS_KEY_ID=${AWS_VALID_ACCESS_KEY}
+      - CELERY_BROKER_URL=redis://redis:6379/0
+      - CELERY_RESULT_BACKEND=redis://redis:6379/0
+      - SAGE_MAKER_AWS_KEY=${SAGE_MAKER_AWS_KEY}
+      - SAGE_MAKER_AWS_SECRET=${SAGE_MAKER_AWS_SECRET}
+      - AWS_STORAGE_ACCESS_KEY=${AWS_STORAGE_ACCESS_KEY}
+      - AWS_STORAGE_SECRET_KEY=${AWS_STORAGE_SECRET_KEY}
+      - AWS_STORAGE_BUCKET_NAME=${AWS_STORAGE_BUCKET_NAME}
+      - AWS_STORAGE_REGION_NAME=${AWS_STORAGE_REGION_NAME}
+      - ELASTICSEARCH_URL=${ELASTICSEARCH_URL}
+    networks:
+      - default
+      - sx
+
   elasticsearch:
-    image: docker.elastic.co/elasticsearch/elasticsearch:8.9.1
+    image: docker.elastic.co/elasticsearch/elasticsearch:7.17.16
     ports:
       - "9200:9200"
       - "9300:9300"
@@ -29,3 +42,33 @@ services:
       - http.cors.allow-credentials=true
       - network.publish_host=localhost
       - xpack.security.enabled=false
+    networks:
+      - default
+      - sx
+
+  celery:
+    build: .
+    command: celery -A app worker --loglevel=info
+    environment:
+      - CELERY_BROKER_URL=redis://redis:6379/0
+      - CELERY_RESULT_BACKEND=redis://redis:6379/0
+      - SAGE_MAKER_AWS_KEY=${SAGE_MAKER_AWS_KEY}
+      - SAGE_MAKER_AWS_SECRET=${SAGE_MAKER_AWS_SECRET}
+      - AWS_STORAGE_ACCESS_KEY=${AWS_STORAGE_ACCESS_KEY}
+      - AWS_STORAGE_SECRET_KEY=${AWS_STORAGE_SECRET_KEY}
+      - AWS_STORAGE_BUCKET_NAME=${AWS_STORAGE_BUCKET_NAME}
+      - AWS_STORAGE_REGION_NAME=${AWS_STORAGE_REGION_NAME}
+      - ELASTICSEARCH_URL=${ELASTICSEARCH_URL}
+    networks:
+      - default
+      - sx
+    depends_on:
+      - app
+      - redis
+
+  redis:
+    image: redis:7
+
+networks:
+  sx:
+    external: true
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
index d11de1e..94f424d 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,111 +2,99 @@
 
 [[package]]
 name = "aiohttp"
-version = "3.8.5"
+version = "3.9.1"
 description = "Async http client/server framework (asyncio)"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
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+    {file = "aiohttp-3.9.1-cp39-cp39-win32.whl", hash = "sha256:82eefaf1a996060602f3cc1112d93ba8b201dbf5d8fd9611227de2003dddb3b7"},
+    {file = "aiohttp-3.9.1-cp39-cp39-win_amd64.whl", hash = "sha256:9b05d33ff8e6b269e30a7957bd3244ffbce2a7a35a81b81c382629b80af1a8bf"},
+    {file = "aiohttp-3.9.1.tar.gz", hash = "sha256:8fc49a87ac269d4529da45871e2ffb6874e87779c3d0e2ccd813c0899221239d"},
 ]
 
 [package.dependencies]
 aiosignal = ">=1.1.2"
-async-timeout = ">=4.0.0a3,<5.0"
+async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
-charset-normalizer = ">=2.0,<4.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
 yarl = ">=1.0,<2.0"
 
 [package.extras]
-speedups = ["Brotli", "aiodns", "cchardet"]
+speedups = ["Brotli", "aiodns", "brotlicffi"]
 
 [[package]]
 name = "aiosignal"
@@ -122,15 +110,29 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "amqp"
+version = "5.2.0"
+description = "Low-level AMQP client for Python (fork of amqplib)."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "amqp-5.2.0-py3-none-any.whl", hash = "sha256:827cb12fb0baa892aad844fd95258143bce4027fdac4fccddbc43330fd281637"},
+    {file = "amqp-5.2.0.tar.gz", hash = "sha256:a1ecff425ad063ad42a486c902807d1482311481c8ad95a72694b2975e75f7fd"},
+]
+
+[package.dependencies]
+vine = ">=5.0.0,<6.0.0"
+
 [[package]]
 name = "annotated-types"
-version = "0.5.0"
+version = "0.6.0"
 description = "Reusable constraint types to use with typing.Annotated"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "annotated_types-0.5.0.tar.gz", hash = "sha256:47cdc3490d9ac1506ce92c7aaa76c579dc3509ff11e098fc867e5130ab7be802"},
+    {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
+    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
 ]
 
 [[package]]
@@ -167,21 +169,22 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "23.1.0"
+version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
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+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
 ]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
+dev = ["attrs[tests]", "pre-commit"]
 docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
 tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "backoff"
@@ -212,35 +215,46 @@ soupsieve = ">1.2"
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "billiard"
+version = "4.2.0"
+description = "Python multiprocessing fork with improvements and bugfixes"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "billiard-4.2.0-py3-none-any.whl", hash = "sha256:07aa978b308f334ff8282bd4a746e681b3513db5c9a514cbdd810cbbdc19714d"},
+    {file = "billiard-4.2.0.tar.gz", hash = "sha256:9a3c3184cb275aa17a732f93f65b20c525d3d9f253722d26a82194803ade5a2c"},
+]
+
 [[package]]
 name = "black"
-version = "23.9.1"
+version = "23.12.1"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "black-23.12.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:97e56155c6b737854e60a9ab1c598ff2533d57e7506d97af5481141671abf3ea"},
+    {file = "black-23.12.1-cp39-cp39-win_amd64.whl", hash = "sha256:dd15245c8b68fe2b6bd0f32c1556509d11bb33aec9b5d0866dd8e2ed3dba09c2"},
+    {file = "black-23.12.1-py3-none-any.whl", hash = "sha256:78baad24af0f033958cad29731e27363183e140962595def56423e626f4bee3e"},
+    {file = "black-23.12.1.tar.gz", hash = "sha256:4ce3ef14ebe8d9509188014d96af1c456a910d5b5cbf434a09fef7e024b3d0d5"},
 ]
 
 [package.dependencies]
@@ -254,57 +268,112 @@ typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 colorama = ["colorama (>=0.4.3)"]
-d = ["aiohttp (>=3.7.4)"]
+d = ["aiohttp (>=3.7.4)", "aiohttp (>=3.7.4,!=3.9.0)"]
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "boto3"
-version = "1.28.48"
+version = "1.34.18"
 description = "The AWS SDK for Python"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">= 3.8"
 files = [
-    {file = "boto3-1.28.48-py3-none-any.whl", hash = "sha256:ec7895504e3b2dd35fbdb7397bc3c48daaba8e6f37bc436aa928ff4e745f0f1c"},
-    {file = "boto3-1.28.48.tar.gz", hash = "sha256:fed2d673fce33384697baa0028edfd18b06aa17af5c3ef82da75e9254a8ffb07"},
+    {file = "boto3-1.34.18-py3-none-any.whl", hash = "sha256:ae7cfdf45f4dfd33bd3e84e36afcfbf0517e64a32e647989a068f34d053572b8"},
+    {file = "boto3-1.34.18.tar.gz", hash = "sha256:5e38ca63007e903a7efe0a1751a0374d287b50d7bc148b9d3d495cdf74a0b712"},
 ]
 
 [package.dependencies]
-botocore = ">=1.31.48,<1.32.0"
+botocore = ">=1.34.18,<1.35.0"
 jmespath = ">=0.7.1,<2.0.0"
-s3transfer = ">=0.6.0,<0.7.0"
+s3transfer = ">=0.10.0,<0.11.0"
 
 [package.extras]
 crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.31.48"
+version = "1.34.18"
 description = "Low-level, data-driven core of boto 3."
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">= 3.8"
 files = [
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+    {file = "botocore-1.34.18-py3-none-any.whl", hash = "sha256:2067d8385c11b7cf2d336227d8fa5aea632fe61afbadb3168dc169dcc13d8c3e"},
+    {file = "botocore-1.34.18.tar.gz", hash = "sha256:85a77e72560a45b0dfdad94f92f5e114c82be07a51bb2d19dd310dab8be158cf"},
 ]
 
 [package.dependencies]
 jmespath = ">=0.7.1,<2.0.0"
 python-dateutil = ">=2.1,<3.0.0"
-urllib3 = ">=1.25.4,<1.27"
+urllib3 = {version = ">=1.25.4,<2.1", markers = "python_version >= \"3.10\""}
 
 [package.extras]
-crt = ["awscrt (==0.16.26)"]
+crt = ["awscrt (==0.19.19)"]
+
+[[package]]
+name = "celery"
+version = "5.3.6"
+description = "Distributed Task Queue."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "celery-5.3.6-py3-none-any.whl", hash = "sha256:9da4ea0118d232ce97dff5ed4974587fb1c0ff5c10042eb15278487cdd27d1af"},
+    {file = "celery-5.3.6.tar.gz", hash = "sha256:870cc71d737c0200c397290d730344cc991d13a057534353d124c9380267aab9"},
+]
+
+[package.dependencies]
+billiard = ">=4.2.0,<5.0"
+click = ">=8.1.2,<9.0"
+click-didyoumean = ">=0.3.0"
+click-plugins = ">=1.1.1"
+click-repl = ">=0.2.0"
+kombu = ">=5.3.4,<6.0"
+python-dateutil = ">=2.8.2"
+tzdata = ">=2022.7"
+vine = ">=5.1.0,<6.0"
+
+[package.extras]
+arangodb = ["pyArango (>=2.0.2)"]
+auth = ["cryptography (==41.0.5)"]
+azureblockblob = ["azure-storage-blob (>=12.15.0)"]
+brotli = ["brotli (>=1.0.0)", "brotlipy (>=0.7.0)"]
+cassandra = ["cassandra-driver (>=3.25.0,<4)"]
+consul = ["python-consul2 (==0.1.5)"]
+cosmosdbsql = ["pydocumentdb (==2.3.5)"]
+couchbase = ["couchbase (>=3.0.0)"]
+couchdb = ["pycouchdb (==1.14.2)"]
+django = ["Django (>=2.2.28)"]
+dynamodb = ["boto3 (>=1.26.143)"]
+elasticsearch = ["elastic-transport (<=8.10.0)", "elasticsearch (<=8.11.0)"]
+eventlet = ["eventlet (>=0.32.0)"]
+gevent = ["gevent (>=1.5.0)"]
+librabbitmq = ["librabbitmq (>=2.0.0)"]
+memcache = ["pylibmc (==1.6.3)"]
+mongodb = ["pymongo[srv] (>=4.0.2)"]
+msgpack = ["msgpack (==1.0.7)"]
+pymemcache = ["python-memcached (==1.59)"]
+pyro = ["pyro4 (==4.82)"]
+pytest = ["pytest-celery (==0.0.0)"]
+redis = ["redis (>=4.5.2,!=4.5.5,<6.0.0)"]
+s3 = ["boto3 (>=1.26.143)"]
+slmq = ["softlayer-messaging (>=1.0.3)"]
+solar = ["ephem (==4.1.5)"]
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+tblib = ["tblib (>=1.3.0)", "tblib (>=1.5.0)"]
+yaml = ["PyYAML (>=3.10)"]
+zookeeper = ["kazoo (>=1.3.1)"]
+zstd = ["zstandard (==0.22.0)"]
 
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-version = "2023.7.22"
+version = "2023.11.17"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 [[package]]
@@ -416,6 +500,55 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
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+
+[package.dependencies]
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+
+[[package]]
+name = "click-plugins"
+version = "1.1.1"
+description = "An extension module for click to enable registering CLI commands via setuptools entry-points."
+optional = false
+python-versions = "*"
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+]
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+dev = ["coveralls", "pytest (>=3.6)", "pytest-cov", "wheel"]
+
+[[package]]
+name = "click-repl"
+version = "0.3.0"
+description = "REPL plugin for Click"
+optional = false
+python-versions = ">=3.6"
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 ]
 
 [package.extras]
@@ -493,22 +626,18 @@ toml = ["tomli"]
 
 [[package]]
 name = "dataclasses-json"
-version = "0.5.9"
-description = "Easily serialize dataclasses to and from JSON"
+version = "0.5.14"
+description = "Easily serialize dataclasses to and from JSON."
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7,<3.13"
 files = [
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 [package.dependencies]
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-marshmallow-enum = ">=1.5.1,<2.0.0"
-typing-inspect = ">=0.4.0"
-
-[package.extras]
-dev = ["flake8", "hypothesis", "ipython", "mypy (>=0.710)", "portray", "pytest (>=7.2.0)", "setuptools", "simplejson", "twine", "types-dataclasses", "wheel"]
+marshmallow = ">=3.18.0,<4.0.0"
+typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "docx2txt"
@@ -522,31 +651,31 @@ files = [
 
 [[package]]
 name = "elastic-transport"
-version = "8.4.0"
+version = "8.11.0"
 description = "Transport classes and utilities shared among Python Elastic client libraries"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
 certifi = "*"
-urllib3 = ">=1.26.2,<2"
+urllib3 = ">=1.26.2,<3"
 
 [package.extras]
-develop = ["aiohttp", "mock", "pytest", "pytest-asyncio", "pytest-cov", "pytest-httpserver", "pytest-mock", "requests", "trustme"]
+develop = ["aiohttp", "furo", "mock", "pytest", "pytest-asyncio", "pytest-cov", "pytest-httpserver", "pytest-mock", "requests", "sphinx (>2)", "sphinx-autodoc-typehints", "trustme"]
 
 [[package]]
 name = "elasticsearch"
-version = "8.9.0"
+version = "8.11.1"
 description = "Python client for Elasticsearch"
 optional = false
-python-versions = ">=3.6, <4"
+python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
@@ -558,13 +687,13 @@ requests = ["requests (>=2.4.0,<3.0.0)"]
 
 [[package]]
 name = "emoji"
-version = "2.8.0"
+version = "2.9.0"
 description = "Emoji for Python"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
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 ]
 
 [package.extras]
@@ -583,13 +712,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.3"
+version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
@@ -597,13 +726,13 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "fastapi"
-version = "0.103.1"
+version = "0.103.2"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -617,19 +746,19 @@ all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)"
 
 [[package]]
 name = "filelock"
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+version = "3.13.1"
 description = "A platform independent file lock."
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 python-versions = ">=3.8"
 files = [
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-typing = ["typing-extensions (>=4.7.1)"]
+docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.24)"]
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+typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
 name = "filetype"
@@ -660,83 +789,99 @@ pyflakes = ">=3.1.0,<3.2.0"
 
 [[package]]
 name = "frozenlist"
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 python-versions = ">=3.8"
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 [package.extras]
-docs = ["Sphinx", "docutils (<0.18)"]
+docs = ["Sphinx", "furo"]
 test = ["objgraph", "psutil"]
 
 [[package]]
@@ -885,13 +1024,13 @@ typing = ["pydantic", "types-PyYAML", "types-requests", "types-simplejson", "typ
 
 [[package]]
 name = "idna"
-version = "3.4"
+version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
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 [[package]]
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 ]
 
+[[package]]
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+version = "5.3.5"
+description = "Messaging library for Python."
+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.dependencies]
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+vine = "*"
+
+[package.extras]
+azureservicebus = ["azure-servicebus (>=7.10.0)"]
+azurestoragequeues = ["azure-identity (>=1.12.0)", "azure-storage-queue (>=12.6.0)"]
+confluentkafka = ["confluent-kafka (>=2.2.0)"]
+consul = ["python-consul2"]
+librabbitmq = ["librabbitmq (>=2.0.0)"]
+mongodb = ["pymongo (>=4.1.1)"]
+msgpack = ["msgpack"]
+pyro = ["pyro4"]
+qpid = ["qpid-python (>=0.26)", "qpid-tools (>=0.26)"]
+redis = ["redis (>=4.5.2,!=4.5.5,<6.0.0)"]
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+yaml = ["PyYAML (>=3.10)"]
+zookeeper = ["kazoo (>=2.8.0)"]
+
 [[package]]
 name = "langchain"
 version = "0.0.281"
@@ -970,160 +1141,142 @@ six = "*"
 
 [[package]]
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 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
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 ]
 
 [package.dependencies]
 pydantic = ">=1,<3"
 requests = ">=2,<3"
 
+[[package]]
+name = "lorem-text"
+version = "2.1"
+description = "Dummy lorem ipsum text generator"
+optional = false
+python-versions = ">=3.5"
+files = [
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+
 [[package]]
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+version = "5.1.0"
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 htmlsoup = ["BeautifulSoup4"]
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 [package.dependencies]
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+lint = ["pre-commit (>=2.4,<4.0)"]
 tests = ["pytest", "pytz", "simplejson"]
 
-[[package]]
-name = "marshmallow-enum"
-version = "1.5.1"
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-[package.dependencies]
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-
 [[package]]
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 version = "0.7.0"
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+[[package]]
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+version = "1.1.0"
+description = "shlex for windows"
+optional = false
+python-versions = ">=3.5"
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 [[package]]
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 version = "6.0.4"
@@ -1274,41 +1438,40 @@ twitter = ["twython"]
 
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 [package.dependencies]
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 xml = ["lxml (>=4.8.0)"]
 
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@@ -1702,13 +1929,13 @@ files = [
 
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 [package.extras]
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 typing-extensions = "*"
 
+[[package]]
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 name = "python-magic"
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 [[package]]
 name = "reportlab"
-version = "4.0.7"
+version = "4.0.9"
 description = "The Reportlab Toolkit"
 optional = false
 python-versions = ">=3.7,<4"
 files = [
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 ]
 
 [package.dependencies]
+chardet = "*"
 pillow = ">=9.0.0"
 
 [package.extras]
@@ -2083,20 +2348,20 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "s3transfer"
-version = "0.6.2"
+version = "0.10.0"
 description = "An Amazon S3 Transfer Manager"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">= 3.8"
 files = [
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 ]
 
 [package.dependencies]
-botocore = ">=1.12.36,<2.0a.0"
+botocore = ">=1.33.2,<2.0a.0"
 
 [package.extras]
-crt = ["botocore[crt] (>=1.20.29,<2.0a.0)"]
+crt = ["botocore[crt] (>=1.33.2,<2.0a.0)"]
 
 [[package]]
 name = "sentry-sdk"
@@ -2179,61 +2444,70 @@ files = [
 
 [[package]]
 name = "sqlalchemy"
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+version = "2.0.25"
 description = "Database Abstraction Library"
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
 greenlet = {version = "!=0.4.17", markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\""}
-typing-extensions = ">=4.2.0"
+typing-extensions = ">=4.6.0"
 
 [package.extras]
 aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"]
-aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing-extensions (!=3.10.0.1)"]
+aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
+aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
 asyncio = ["greenlet (!=0.4.17)"]
 asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
 mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
@@ -2243,7 +2517,7 @@ mssql-pyodbc = ["pyodbc"]
 mypy = ["mypy (>=0.910)"]
 mysql = ["mysqlclient (>=1.4.0)"]
 mysql-connector = ["mysql-connector-python"]
-oracle = ["cx-oracle (>=7)"]
+oracle = ["cx_oracle (>=8)"]
 oracle-oracledb = ["oracledb (>=1.0.1)"]
 postgresql = ["psycopg2 (>=2.7)"]
 postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
@@ -2253,7 +2527,7 @@ postgresql-psycopg2binary = ["psycopg2-binary"]
 postgresql-psycopg2cffi = ["psycopg2cffi"]
 postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
 pymysql = ["pymysql"]
-sqlcipher = ["sqlcipher3-binary"]
+sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "starlette"
@@ -2286,6 +2560,23 @@ files = [
 [package.extras]
 widechars = ["wcwidth"]
 
+[[package]]
+name = "taskipy"
+version = "1.12.2"
+description = "tasks runner for python projects"
+optional = false
+python-versions = ">=3.6,<4.0"
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+
+[package.dependencies]
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+mslex = {version = ">=1.1.0,<2.0.0", markers = "sys_platform == \"win32\""}
+psutil = ">=5.7.2,<6.0.0"
+tomli = {version = ">=2.0.1,<3.0.0", markers = "python_version >= \"3.7\" and python_version < \"4.0\""}
+
 [[package]]
 name = "tenacity"
 version = "8.2.3"
@@ -2378,13 +2669,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typing-extensions"
-version = "4.7.1"
-description = "Backported and Experimental Type Hints for Python 3.7+"
+version = "4.9.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
+    {file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
+    {file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
 ]
 
 [[package]]
@@ -2404,24 +2695,24 @@ typing-extensions = ">=3.7.4"
 
 [[package]]
 name = "tzdata"
-version = "2023.3"
+version = "2023.4"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 files = [
-    {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
-    {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
+    {file = "tzdata-2023.4-py2.py3-none-any.whl", hash = "sha256:aa3ace4329eeacda5b7beb7ea08ece826c28d761cda36e747cfbf97996d39bf3"},
+    {file = "tzdata-2023.4.tar.gz", hash = "sha256:dd54c94f294765522c77399649b4fefd95522479a664a0cec87f41bebc6148c9"},
 ]
 
 [[package]]
 name = "unstructured"
-version = "0.10.29"
+version = "0.10.30"
 description = "A library that prepares raw documents for downstream ML tasks."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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+    {file = "unstructured-0.10.30-py3-none-any.whl", hash = "sha256:0615f14daa37450e9c0fcf3c3fd178c3a06b6b8d006a36d1a5e54dbe487aa6b6"},
+    {file = "unstructured-0.10.30.tar.gz", hash = "sha256:a86c3d15c572a28322d83cb5ecf0ac7a24f1c36864fb7c68df096de8a1acc106"},
 ]
 
 [package.dependencies]
@@ -2444,7 +2735,7 @@ typing-extensions = "*"
 
 [package.extras]
 airtable = ["pyairtable"]
-all-docs = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.11)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+all-docs = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.1.0)", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.11)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 azure = ["adlfs", "fsspec (==2023.9.1)"]
 azure-cognitive-search = ["azure-search-documents"]
 bedrock = ["boto3", "langchain"]
@@ -2454,8 +2745,8 @@ confluence = ["atlassian-python-api"]
 csv = ["pandas"]
 delta-table = ["deltalake", "fsspec (==2023.9.1)"]
 discord = ["discord-py"]
-doc = ["python-docx (>=1.0.1)"]
-docx = ["python-docx (>=1.0.1)"]
+doc = ["python-docx (>=1.1.0)"]
+docx = ["python-docx (>=1.1.0)"]
 dropbox = ["dropboxdrivefs", "fsspec (==2023.9.1)"]
 elasticsearch = ["elasticsearch", "jq"]
 embed-huggingface = ["huggingface", "langchain", "sentence-transformers"]
@@ -2467,19 +2758,19 @@ google-drive = ["google-api-python-client"]
 huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"]
 image = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.11)", "unstructured.pytesseract (>=0.3.12)"]
 jira = ["atlassian-python-api"]
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+local-inference = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.1.0)", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.11)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 md = ["markdown"]
 msg = ["msg-parser"]
 notion = ["htmlBuilder", "notion-client"]
-odt = ["pypandoc", "python-docx (>=1.0.1)"]
+odt = ["pypandoc", "python-docx (>=1.1.0)"]
 onedrive = ["Office365-REST-Python-Client (<2.4.3)", "bs4", "msal"]
 openai = ["langchain", "openai", "tiktoken"]
 org = ["pypandoc"]
 outlook = ["Office365-REST-Python-Client (<2.4.3)", "msal"]
 paddleocr = ["unstructured.paddleocr (==2.6.1.3)"]
 pdf = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.11)", "unstructured.pytesseract (>=0.3.12)"]
-ppt = ["python-pptx (<=0.6.21)"]
-pptx = ["python-pptx (<=0.6.21)"]
+ppt = ["python-pptx (<=0.6.23)"]
+pptx = ["python-pptx (<=0.6.23)"]
 reddit = ["praw"]
 rst = ["pypandoc"]
 rtf = ["pypandoc"]
@@ -2493,19 +2784,20 @@ xlsx = ["networkx", "openpyxl", "pandas", "xlrd"]
 
 [[package]]
 name = "urllib3"
-version = "1.26.16"
+version = "2.0.7"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+python-versions = ">=3.7"
 files = [
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+    {file = "urllib3-2.0.7.tar.gz", hash = "sha256:c97dfde1f7bd43a71c8d2a58e369e9b2bf692d1334ea9f9cae55add7d0dd0f84"},
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 [package.extras]
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-secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
-socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
@@ -2526,6 +2818,28 @@ typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
 [package.extras]
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+[[package]]
+name = "vine"
+version = "5.1.0"
+description = "Python promises."
+optional = false
+python-versions = ">=3.6"
+files = [
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+    {file = "vine-5.1.0.tar.gz", hash = "sha256:8b62e981d35c41049211cf62a0a1242d8c1ee9bd15bb196ce38aefd6799e61e0"},
+]
+
+[[package]]
+name = "wcwidth"
+version = "0.2.13"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
+files = [
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+]
+
 [[package]]
 name = "xlsxwriter"
 version = "3.1.9"
@@ -2539,85 +2853,101 @@ files = [
 
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+version = "1.9.4"
 description = "Yet another URL library"
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 python-versions = ">=3.7"
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+    {file = "yarl-1.9.4.tar.gz", hash = "sha256:566db86717cf8080b99b58b083b773a908ae40f06681e87e589a976faf8246bf"},
 ]
 
 [package.dependencies]
@@ -2628,4 +2958,5 @@ multidict = ">=4.0"
 lock-version = "2.0"
 
 python-versions = ">=3.10,<3.13"
-content-hash = "aa2c338bd2145768e8425023ef0e4c40a884927f5b8d3450c7287f08192eb1f7"
\ No newline at end of file
+
+content-hash = "f8d8c0c240311fcb449d2f2b86f21dec403402589d53549276b560ab51578a80"
diff --git a/pyproject.toml b/pyproject.toml
index d086018..389f2ae 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,8 +21,12 @@ docx2txt = "^0.8"
 networkx = "^3.2.1"
 pandas = "^2.1.2"
 openpyxl = "^3.1.2"
-sentry-sdk = {extras = ["fastapi"], version = "^1.35.0"}
 
+python-dotenv = "^1.0.0"
+pydantic = "2.3.0"
+celery = "^5.3.6"
+redis = "^5.0.1"
+sentry-sdk = {extras = ["fastapi"], version = "^1.35.0"}
 
 
 [tool.poetry.group.dev.dependencies]
@@ -31,7 +35,15 @@ black = "^23.9.1"
 reportlab = "^4.0.7"
 xlsxwriter = "^3.1.9"
 flake8 = "^6.1.0"
+lorem-text = "^2.1"
+taskipy = "^1.12.2"
 
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
+
+
+[tool.taskipy.tasks]
+test = 'poetry run coverage run -m unittest discover ./app/tests/'
+post_test = 'coverage html'
+run = 'uvicorn app.main:main_app.api --reload'
\ No newline at end of file