Upload s3 directory path to langflow loaders component

[Preet1234-ux]

I want to use the directory path of Amazon S3 bucket in langflow to load the files . Which loaders sub component shall I use and how ?

[dosubot[bot]]

To load files from an Amazon S3 bucket directory into the langflow loaders component, you should utilize the DirectoryLoaderComponent. Here's a concise guide on setting it up:

from langflow.components.documentloaders.DirectoryLoader import DirectoryLoaderComponent

# Initialize the DirectoryLoaderComponent
directory_loader = DirectoryLoaderComponent()

# Configure the loader with the path to your S3 bucket directory (assumed to be accessible locally)
loaded_documents = directory_loader.build(
    glob="**/*.txt",  # Adjust to match the files you want to load
    path="/mnt/my_s3_bucket_directory",  # Your S3 bucket directory path
    max_concurrency=10,  # Optional: Adjust based on your needs
    load_hidden=False,  # Optional: Whether to load hidden files
    recursive=True,  # Optional: Whether to load files recursively
    silent_errors=False,  # Optional: Whether to silence errors
    use_multithreading=True  # Optional: Whether to use multithreading
)

# `loaded_documents` now contains the documents from your S3 directory

This approach assumes you have access to your S3 bucket as if it were a local directory, possibly through a tool like AWS S3 Fuse. Adjust the DirectoryLoaderComponent configuration as needed, especially the glob pattern to match the specific files you're interested in loading. For more details, refer to the DirectoryLoaderComponent documentation or source code.

Details

Sources

• src/backend/langflow/components/documentloaders/DirectoryLoader.py

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[Preet1234-ux]

@dosu Can you please provide me full code which contains build method also , which I can use in the DirectoryLoader Component ?

[dosubot[bot]]

To load documents from an Amazon S3 bucket directory using the DirectoryLoaderComponent in langflow, here's a full example including the build method. This example assumes your S3 bucket is mounted locally via AWS S3 Fuse:

from langchain.docstore.document import Document
from langflow.components.documentloaders.DirectoryLoader import DirectoryLoaderComponent

def load_documents_from_s3_directory():
    # Path to your mounted S3 bucket directory
    s3_mount_path = "/mnt/s3_bucket/my_directory"
    
    # Initialize DirectoryLoaderComponent with configuration
    directory_loader = DirectoryLoaderComponent()
    
    # Load documents with specified configurations
    documents = directory_loader.build(
        glob="**/*.txt",  # Pattern to match text files
        path=s3_mount_path,  # Mounted S3 bucket path
        max_concurrency=10,  # Adjust as needed
        load_hidden=False,  # Skip hidden files
        recursive=True,  # Load files recursively
        silent_errors=False,  # Show errors
        use_multithreading=True  # Enable multithreading
    )
    
    return documents

# Load the documents
loaded_documents = load_documents_from_s3_directory()

# Example: Print content of loaded documents
for document in loaded_documents:
    print(document.content)

This script will load all .txt files from the specified directory in your S3 bucket, considering the configurations like multithreading and recursion. Adjust the max_concurrency as per your requirements and system capabilities. Ensure AWS S3 Fuse is set up correctly to mount your S3 bucket as a local directory for this to work.

Details

Sources

• src/backend/langflow/components/documentloaders/DirectoryLoader.py
• src/backend/base/langflow/components/data/Directory.py

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[Preet1234-ux]

@dosu I have deployed Langflow on OpenShift . I want to use Directory loader in my flow to load my files . How to achieve it ?

[dosubot[bot]]

To use the DirectoryLoaderComponent in your Langflow application deployed on OpenShift for loading files from an Amazon S3 bucket, you'll need to adapt the component to work with S3 directly, especially since you're operating in a cloud environment where direct filesystem access to S3 might not be feasible or optimal. Here's how you can achieve this by leveraging Langflow's S3StorageService:

1. Integrate S3StorageService: First, ensure that Langflow's S3StorageService is accessible within your application. This service is designed to simplify interactions with S3, allowing you to list, retrieve, and manage files directly in your S3 bucket.

2. Configure AWS Credentials: Make sure your AWS credentials are correctly configured in your OpenShift environment. These credentials should have the necessary permissions to access your S3 bucket and should be securely stored, possibly using OpenShift's secrets management features.

3. Adapt DirectoryLoaderComponent for S3 Usage:
   You'll need to modify the DirectoryLoaderComponent to use the S3StorageService for fetching files from S3. This involves listing the files in a directory and retrieving each file's content asynchronously. Here's a basic example of how you might adapt the component:

   from langflow.services.storage.s3 import S3StorageService
   from langchain.docstore.document import Document
   
   class DirectoryLoaderComponent:
       def __init__(self, s3_storage_service: S3StorageService):
           self.s3_storage_service = s3_storage_service
   
       async def load_from_s3(self, folder: str):
           file_names = await self.s3_storage_service.list_files(folder)
           documents = []
           for file_name in file_names:
               data = await self.s3_storage_service.get_file(folder, file_name)
               documents.append(Document(content=data.decode('utf-8'), name=file_name))
           return documents

   This code snippet demonstrates how to initialize the component with an instance of S3StorageService, list files in a specific folder, and load each file as a Document object. Remember to handle asynchronous operations correctly, especially if your Langflow application is designed to operate synchronously.

4. Ensure Proper Permissions: Double-check that the AWS credentials used by S3StorageService have the necessary permissions to list and retrieve files from your S3 bucket. This might involve configuring IAM roles and policies in AWS to grant access to the specific resources needed by your application.

By following these steps, you can effectively use the DirectoryLoaderComponent within your Langflow application on OpenShift to load files from an S3 bucket, leveraging cloud-native services and practices for optimal performance and scalability.

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[Preet1234-ux]

@dosu If I upload my directory on openshift , then can I access the directory directly in DirectoryLoader component ?

[dosubot[bot]]

Yes, after uploading your directory to OpenShift, you can directly access it in the DirectoryLoaderComponent to load your files. Here's how you can do it:

from your_module import DirectoryComponent  # Adjust the import path as necessary

# Initialize the DirectoryComponent
directory_component = DirectoryComponent()

# Configure and load files from the directory
loaded_records = directory_component.build(
    path="/path/to/your/directory",  # Replace with the actual path to your directory in OpenShift
    depth=0,  # Optional: Adjust based on how deep you want to search
    max_concurrency=10,  # Optional: Adjust based on your concurrency needs
    load_hidden=False,  # Optional: Set to True if you need to load hidden files
    recursive=True,  # Optional: Set to False if you do not want to search directories recursively
    silent_errors=False,  # Optional: Set to True if you prefer to ignore errors silently
    use_multithreading=True  # Optional: Set to False if you prefer not to use multithreading
)

Make sure to replace "/path/to/your/directory" with the actual path where your files are located in the OpenShift environment. This setup allows you to load files from the specified directory with configurations such as concurrency, recursion, and error handling according to your needs.

Details

Sources

• src/backend/langflow/components/documentloaders/DirectoryLoader.py
• src/backend/base/langflow/components/data/Directory.py
• tests/test_data_components.py
• src/backend/langflow/components/documentloaders/FileLoader.py

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.