Build A Transcription API Endpoint

Jan 14, 2026 by Editorial Team 35 views

Hey guys! Let's dive into creating a robust API endpoint for transcriptions, a project that is Issue #721 from Olbrasoft's VirtualAssistant. This guide will walk you through the process, from the initial setup to the technical implementation, ensuring you have a solid understanding of how to fetch recent transcriptions along with their corrections. We're gonna break down everything, so even if you're new to this, you'll be able to follow along. This is all about getting those transcriptions and corrections seamlessly integrated, which is super useful for any application dealing with audio data. The goal is to build an endpoint that provides a DTO (Data Transfer Object) containing the whisper transcription text, creation timestamp, duration, LLM (Large Language Model) correction text (if it exists), and prompt name/ID (if it exists). This comprehensive approach ensures that you have all the necessary information readily available for your application to process and display. Let's get started, shall we?

Understanding the Core Requirements

Alright, first things first. We need to understand the core requirements for this API endpoint. The main objective is to create a way to retrieve recent transcriptions along with their associated corrections. This involves several key components. First, we need to fetch the original transcriptions generated, likely using a service like Whisper. These transcriptions will serve as the baseline data. Second, we must incorporate any corrections made to the transcriptions, possibly through an LLM. These corrections aim to improve the accuracy and quality of the original transcriptions. Third, we need to package this data into a structured format that's easy to consume, which in our case is a DTO. Finally, we must determine the best way to expose this data through an API endpoint. This endpoint will be the gateway through which your application will access and use the transcription data. The DTO will include the Whisper Transcription Text, the CreatedAt timestamp to indicate when the transcription was generated, the Duration of the audio, the LLM Correction Text (if available), and the Prompt Name/ID (if applicable). This detailed approach allows for a complete view of the transcription process, offering all the critical data points in a single, easy-to-use format. Remember, this project is designed to be user-friendly, providing valuable functionality for applications needing accurate and easily accessible transcription data. This way we ensure the endpoint is efficient and provides all the necessary details for each transcription.

The Importance of a Well-Defined DTO

Let's talk about the DTO – the Data Transfer Object. This is super important because it acts as the structure for the data returned by our API endpoint. A well-defined DTO ensures that the data is organized, consistent, and easy to understand. It specifies exactly which data fields will be included in the response, along with their data types. In our case, the DTO will include fields such as: the original Whisper Transcription Text, the CreatedAt timestamp (crucial for time-based queries), Duration (useful for calculating audio length), the LLM Correction Text (if a correction exists), and the Prompt Name/ID (if a prompt was used). By using a DTO, we create a contract between the API and the consuming application. This contract clearly defines what data to expect, minimizing the chances of errors and making it easier to integrate the API into other systems. The DTO helps to encapsulate all relevant information, allowing for efficient data transfer and reducing the amount of processing required on the client side. This design choice contributes to the overall stability and scalability of the API, making it easier to maintain and extend in the future. So, the DTO is your friend; use it wisely.

Technical Implementation: The Nitty-Gritty Details

Now, let's get into the technical stuff. First off, we'll need to create a GetTranscriptionsWithCorrectionsQuery. This is essentially a query handler responsible for fetching the transcriptions and their corresponding corrections. Within this query handler, you'll likely query your database or data storage to retrieve the necessary information. You'll need to consider how your transcriptions and corrections are stored. Are they in the same table, or do you need to join multiple tables? The query handler will be the heart of the data retrieval process. Next, you will need to map the retrieved data into our pre-defined DTO. This involves taking the raw data from the database and transforming it into the structured format specified by the DTO. Pay close attention to data types and ensure that all fields are correctly populated. Now, let's talk about the endpoint itself. You have two main options: create a dedicated endpoint at /api/transcriptions or integrate the query directly into a Razor Page model. The /api/transcriptions approach is a more standard RESTful approach, providing a clear and separate API interface. This is a solid choice if you need to expose this data to multiple applications or want to keep your UI and API separate. On the other hand, integrating the query directly into a Razor Page model can be quicker for simple applications where you only need the data within the Razor Pages context. The choice depends on your project's architecture and requirements. Don't sweat it, both approaches are viable.

Creating the `GetTranscriptionsWithCorrectionsQuery`

Creating the GetTranscriptionsWithCorrectionsQuery is a crucial step. This class will handle the logic of fetching the transcriptions and their corrections. This is where you'll define how the data is retrieved. Inside this query, you'll likely use a data access layer (DAL) or an ORM (Object-Relational Mapper) to interact with your database. Here's a basic breakdown:

Dependencies: Inject any necessary services or dependencies, such as a database context or a repository. These are the tools that will help fetch the data. This will allow for flexibility and maintainability. It helps keep your code clean and manageable.
Query Logic: Implement the core logic to query for recent transcriptions and their corrections. Make sure to retrieve all the required fields: Whisper Transcription Text, CreatedAt, Duration, LLM Correction Text, and Prompt Name/ID. This is where the magic happens and the data is retrieved, and the details must be considered. This will ensure you have a complete picture of each transcription.
Data Mapping: Map the data retrieved from the database to your DTO. This ensures that the data is in the correct format for the API response. Carefully map each field to its corresponding property in the DTO. This part ensures that the output will be consistent and easy to consume. Proper mapping ensures that all the details are ready for the final output.

Implementing the API Endpoint

Implementing the API endpoint is where you decide how your application will access the data. As mentioned earlier, you can go with the /api/transcriptions approach or integrate the logic into a Razor Page model. Let's break down both: If you are going with the first approach, here is what you need to consider:

Dedicated API Endpoint: This involves creating a controller that handles requests to /api/transcriptions. This controller will receive the request, call the GetTranscriptionsWithCorrectionsQuery, and return the results as JSON. This is ideal if you're building a separate API that will be used by multiple clients. This provides a clear separation of concerns, making your application more modular and easier to maintain.
Request Handling: Define the HTTP method (GET, POST, etc.) for the endpoint. In this case, it will likely be a GET request. Handle the incoming request by calling the query handler and retrieving the data.
Response Formatting: Serialize the DTO into a JSON response. Ensure the response format is clean and adheres to common API standards.

If you're going with the second approach, here are some things to think about:

Razor Page Model Integration: Integrate the GetTranscriptionsWithCorrectionsQuery directly into your Razor Page model. This is best if your application is using Razor Pages and only needs this data within the application.
Page Lifecycle: Call the query handler within the Razor Page's lifecycle (e.g., OnGet method). Make sure the data is fetched and populated into a model that can be accessed by the Razor Page. This approach simplifies the architecture, making it faster to set up for some basic needs.

Testing and Validation: Making Sure It Works

Alright, you've built your API endpoint, now what? Testing and validation are super important. You need to make sure everything works as expected. Here are some key steps:

Unit Tests

First, focus on unit tests. Create unit tests for your GetTranscriptionsWithCorrectionsQuery to verify that it correctly retrieves and maps the data. Unit tests are super easy to implement and can check the individual components of your system. You can test edge cases, and that can catch errors before you move on to the next phase of the project. These tests should cover a variety of scenarios, including cases where corrections exist, cases where they don't, and situations with different prompt names or IDs. Make sure to cover the main use cases, and don't forget the edge cases. This makes for a robust and reliable system. This will help you identify any issues within the query logic early on.

Integration Tests

Next, perform integration tests. These tests will make sure that the API endpoint and the query handler work together correctly. These tests will simulate requests to the /api/transcriptions endpoint and verify the returned data against the expected results. This tests the interaction between different parts of your application. Make sure the API returns the correct data, including the Whisper Transcription Text, CreatedAt, Duration, LLM Correction Text (if available), and Prompt Name/ID (if present).

Manual Testing

Lastly, manual testing will allow you to see that your application functions exactly as needed. Try to hit the API endpoint manually using tools like Postman or Insomnia. This is very important. This ensures everything works as expected. Verify that the returned JSON data matches the expected format and contains all the necessary information. It's a great way to spot any unexpected behavior. Verify that you can successfully retrieve the data and that it's correctly formatted. Pay attention to the edge cases. This will ensure that the API endpoint is functioning as intended and that the data is being served correctly.

Conclusion: Ready to Go Live

And there you have it, guys! We've covered the entire process of building an API endpoint for transcriptions. We've gone through the requirements, the technical details, and the testing phases. By following these steps, you should have a solid, working API endpoint that provides the necessary data in a clean, usable format. With a well-defined DTO, robust query handler, and thorough testing, you can ensure that your API is reliable, efficient, and ready to meet your application's needs. Feel free to use this as a guide for your projects! Happy coding!