Brainstorming: File System Watcher and Long Polling for PDF Summarizer

Let's explore how we can combine a File System Watcher with Long Polling in the context of our C# PDF summarizer. The goal here is to create a more reactive and potentially less resource-intensive way to handle new PDF files being added for summarization.

The Core Problem:

A standard File System Watcher can notify us immediately when a new PDF file is created in a monitored directory. However, we might want to decouple the immediate notification from the actual summarization process, perhaps to manage resource usage or to allow a separate service to handle the summarization. Long Polling can play a role in how a client (e.g., a web UI or another application) gets notified that a new summary is available.

Brainstorming Ideas & Approaches:

1. Local File System Watcher with Long Polling for Summary Availability:

  • Workflow:

    1. File System Watcher (C# Service): A background C# service uses FileSystemWatcher to monitor a designated folder for new .pdf files.
    2. New PDF Detected: When a new PDF is detected, the service could:
      • Immediately start the summarization process using the OpenAiHelper.
      • Add the file path (or a unique identifier for the file) to a queue or a temporary storage (e.g., a dictionary or a simple database) indicating that it's being processed.
    3. Long Polling Endpoint (Web API): A separate Web API (could be ASP.NET Core) exposes an endpoint that clients can call to check for new summaries.
    4. Client Request (Long Poll): A client (e.g., a web page) makes an asynchronous HTTP request to this endpoint. The server holds the connection open.
    5. Summary Completion: When the summarization for a newly added PDF is finished, the C# service updates the status of that file (e.g., marks it as "summarized" and stores the summary). It then notifies the long-polling endpoint.
    6. Server Response: The long-polling endpoint, upon notification, checks if there are any new summaries available for the requesting client (potentially based on a unique client ID or a general "new summary" flag). If a new summary exists, the server sends the summary (or a link to it) in the HTTP response and closes the connection.
    7. Client Re-request: The client, upon receiving the response, immediately makes a new long-polling request, starting the cycle again.
    8. Timeout: If no new summaries become available within a defined timeout period, the long-polling endpoint sends an empty or "no new data" response, and the client re-establishes the connection.

  • Pros:

    • Real-time (or near real-time) notification of summary availability to clients without constant polling.
    • Decouples file detection and summarization from client notification.
    • Potentially reduces server load compared to frequent short polling.

  • Cons:

    • More complex to implement due to managing asynchronous operations and connection states.
    • Requires a separate Web API component.
    • Need to handle potential connection interruptions and timeouts gracefully.

2. File System Watcher Triggers Summarization and Updates a Shared State for Polling:

  • Workflow:

    1. File System Watcher (C# Service/Application): Monitors a folder for new PDFs.
    2. New PDF Detected: Triggers the summarization process directly.
    3. Shared State: The summarization service updates a shared state (e.g., a database table, a Redis cache, or even a JSON file) with the status of each PDF (e.g., "processing," "summarized," "failed") and the summary content once complete.
    4. Short Polling Client: A client application (could be the same or different) periodically polls this shared state to check for updates on the PDFs it's interested in.

  • Pros:

    • Simpler to implement than long polling.
    • Doesn't require holding open HTTP connections.

  • Cons:

    • Not as real-time as long polling; the polling interval determines the delay in notification.
    • Can put more load on the shared state if the polling interval is too short or the number of clients is high.

3. File System Watcher with a Message Queue (e.g., RabbitMQ, Kafka) and Separate Summary Service:

  • Workflow:

    1. File System Watcher (C# Service): Detects new PDFs.
    2. Message Queue: When a new PDF is detected, the watcher publishes a message to a message queue containing the file path.
    3. Summary Service (Separate C# Service): A separate service (or multiple instances for scalability) consumes messages from the queue, retrieves the PDF, performs the summarization, and potentially stores the summary in a database or another storage.
    4. Client Notification (Various Options): Clients can be notified of new summaries through:
      • WebSockets: A more persistent and bidirectional communication channel for real-time updates.
      • Server-Sent Events (SSE): A unidirectional channel where the server can push updates to the client.
      • Polling (short or long) of a status endpoint.

  • Pros:

    • Highly scalable and robust due to the message queue.
    • Decouples file detection, summarization, and client notification.
    • Allows for independent scaling of the summarization service.

  • Cons:

    • More complex infrastructure setup with the message queue.

Focusing on File System Watcher + Long Polling (Option 1) in more detail:

  • C# Service (Watcher/Summarizer):

    • Use FileSystemWatcher to listen for Created events with a filter for .pdf files.
    • Maintain a dictionary or similar structure to track the processing status of each file (e.g., ).
    • When a new PDF is detected, start an asynchronous task to:
      • Extract text.
      • Call the OpenAI API.
      • Store the summary.
      • Update the status in the tracking structure to "summarized" along with the summary content.
      • Have a mechanism to signal the long-polling endpoint that a new summary is available. This could be a simple event or updating an in-memory flag.

  • ASP.NET Core Web API (Long Polling Endpoint):

    • Create an API controller with an endpoint like /api/summaries/wait.
    • This endpoint would accept a client identifier (optional, but useful for targeted notifications).
    • When a client makes a request, the server would:
      • Hold the request asynchronously.
      • Wait for a signal from the summarization service that a new summary is available. This could involve using TaskCompletionSource or similar asynchronous primitives.
      • Periodically check if a new summary exists for the requesting client (or generally).
      • If a new summary is found, return the summary (or a reference to it) in the response and complete the request.
      • If a timeout occurs before a new summary is available, return a "no new data" status and close the connection.

  • Client (e.g., Web Browser):

    • Make an asynchronous fetch or XMLHttpRequest to the long-polling endpoint.
    • When a response is received (either with data or a timeout), process the data (if any) and immediately make a new long-polling request.
    • Display the new summary to the user.

Challenges with Long Polling:

  • Scalability: Holding open many connections can be resource-intensive on the server if not handled efficiently (e.g., using asynchronous I/O).
  • Timeouts: Network issues and server load can lead to premature connection closures, requiring careful client-side retry logic.
  • State Management: Managing the state of pending long-polling requests can be complex.

Conclusion:

Combining a File System Watcher with Long Polling offers a way to react to new PDF files in near real-time and notify clients efficiently. However, it introduces complexity in managing asynchronous operations and server-client communication. Depending on the scale and requirements of your application, other approaches like short polling or using a message queue with WebSockets/SSE might be more suitable.

Consider the trade-offs between complexity, real-time requirements, and scalability when choosing your integration strategy.