Use OpenAI's new Assistant API with your files
Education
Introduction
In this article, we will explore how to leverage OpenAI's Assistant API to create a personalized assistant capable of answering questions based on specific files you provide. The goal is to develop an assistant that speaks in a designated manner and generates responses about your existing content, such as videos. While the process is straightforward, there are some limitations to consider, which we will address as we progress.
Getting Started
To begin, visit platform.openai.com. Log in to your account and navigate to the playground, where you will select the Assistant option. Click on 'Create' and enter a name for your assistant; in this case, we will name it "Key Codes GPT". The next step is to define a system prompt for the assistant, which will guide its responses.
Crafting the System Prompt
The system prompt is crucial in shaping how our assistant interacts with users. Here's an example of a well-thought-out prompt:
You are Key Codes GPT, an assistant with knowledge about the YouTube channel Key Codes.
Rules:
1. Only use the provided context.
2. Always address the user as 'coder'.
3. Encourage likes and subscriptions.
4. End every message with 'Have a lot of fun, coders.'
After setting this up, save your configuration and choose the GPT-4 Turbo model.
Testing the Assistant
Initially, we can test our assistant by asking general questions about the content. For instance, if we query, "What videos does Key Codes have?", the collective knowledge of the assistant will yield a response about general programming tips and tutorials. However, it becomes evident that the assistant lacks real-time access to specific video titles or details.
Utilizing the Whisper API
To enable the assistant to reference specific content, we need to provide it with access to video transcripts. I gathered audio files from my videos and processed them using a Python script that interfaces with the Whisper API. The result is a series of transcription files enriched with metadata, including YouTube URLs and video titles.
Uploading Video Data
Next, I attempted to upload a text format file containing transcript details and ensure that the retrieval function was activated. After uploading, I cleared the context and posed questions to the assistant again. For instance, asking about a specific video title resulted in the assistant failing to access the uploaded files. This led to adjustments in the prompt to emphasize the use of provided links.
Enhancing Performance with JSON Files
I explored the idea of using JSON file formats for data retrieval. I uploaded an unformatted JSON file, but met with limitations. The assistant could reference some video names correctly, but struggled to provide direct links.
After various tests, including trying a beautified JSON version and separate transcript files per video, the assistant still operated suboptimally. Each modification was aimed at reducing context-load issues due to token limits.
Fine-tuning the Prompt
To get better results, I edited the prompt to specify how the assistant should utilize the uploaded data:
You are provided with "Key Code Summaries.txt" which includes titles, URLs, and summaries. Use this primarily and only refer to other files in absence of necessary information.
With this improved directive, the assistant started yielding accurate responses, including linking to relevant videos and summarizing transcripts effectively.
Conclusion
Utilizing OpenAI's Assistant API requires careful attention to detail regarding data management and interaction prompt configurations. Adjusting how files are presented and ensuring the assistant knows where to retrieve information can significantly enhance its performance. Despite encountering several hurdles—primarily related to token limits and structural issues—the journey highlights the power of utilizing APIs to create specialized tools for personal or professional use.
Keywords
- OpenAI
- Assistant API
- Key Codes GPT
- YouTube transcripts
- Whisper API
- JSON format
- Video summaries
- Data retrieval
- Programming tutorials
FAQ
Q1: What is OpenAI's Assistant API?
A1: OpenAI's Assistant API is a powerful tool that allows developers to create personalized AI assistants that can interact with users, answer questions, and retrieve information based on predefined data.
Q2: How can I make my assistant refer to specific content?
A2: You can provide the assistant with files such as transcripts or JSON data that contain relevant information. Ensure to configure the prompt correctly to guide the assistant on how to utilize these files.
Q3: What limitations did you encounter while using the Assistant API?
A3: The main limitations included challenges with token limits and issues related to data retrieval when using various file formats.
Q4: Can I upload different file formats for my assistant?
A4: Yes, you can upload files in multiple formats, such as text or JSON. However, the structure and clarity of the data significantly affect the assistant's performance.
Q5: How do I improve the assistant's ability to provide links to videos?
A5: Adjust the prompt to encourage the assistant to prioritize utilizing the URL information from the provided files first before relying on other data sources.
