Hi there! Thanks for joining me today as I continue my journey with the chatbot platform. In this session, I focused on adding the ability for users to upload files, read from these files, and ultimately provide responses based on their contents. This is an exciting step forward in utilizing OpenAI's APIs extensively. Let's dive in!
Initial Setup and Challenges
To start, I tried using OpenAI's Assistant feature to enhance the bot's capabilities. Initially, I asked Cursor to create a bot that should automatically generate an assistant. However, I encountered an error, and the assistant wasn’t created. Realizing the issue, I decided to switch to the GPT-4o model, as it's better trained with OpenAI's documentation, instead of the Claude 3.5 model. After making this change, I was able to create a new bot, which then appeared under the Assistants feature.
Developing File Search Capability
With the bot successfully created, I wanted to integrate file search functionality within Assistants. The goal was to ensure that when a user uploads a new file, it gets associated with a particular Assistant. In OpenAI's framework, every Assistant can have multiple vector stores, and each vector store can contain multiple files. Thus, I decided to create one vector store for each bot, associating files to the corresponding vector store.
Coding and Configuration
I proceeded to write the code necessary for uploading files. Once the code was in place, I could successfully upload files and see them appear in storage. However, a vector store had not been created. To address this, I modified the code so that a new vector store is created whenever a new bot is set up. Using the GPT-4o model, I inserted code directly from the documentation for a smoother process.
To improve organization, I introduced a "Files" tab that lists all uploaded files, making it easier to manage them. I also corrected a mistake where the system used its own OpenAI key, ensuring it now uses the correct, pre-existing key.
Testing and Troubleshooting
Testing the newly set features, I created a new bot, a gym trainer, and verified its appearance in Assistants. With each Assistant now linked to a vector store, I ensured that user file uploads were stored correctly in the database. This setup allowed me to associate files accurately with their respective vector store IDs, a crucial step for retrieving relevant information during bot interactions.
Finalizing Features
The next step involved adding an association icon next to each file. This function lets me align each file with a specific vector store, ensuring that information retrieval when interacting with the bot is seamless.
Creating new bots, like a gym trainer, further allowed me to test the association process. Upon verification, I could see that the files attached correctly in the vector store and displayed in Assistants, confirming everything was linked as intended.
Conclusion and Future Work
By leveraging these developments, I enabled a feature where users can upload files, connect them with individual bots, and receive tailored responses after retrieving data from these files.
In summary, this session marked a significant advance in building an intelligent file-upload feature for chatbots. I'm excited about the possibilities this opens up and look forward to further enhancements. Thank you for following along with my progress today!
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