In today's tech journey, I'm excited to bring you along as I dive deeper into enhancing my chatbot solution. If you tuned in for the previous episode, you might remember that I laid the foundation by creating a basic chatbot product using OpenAI to answer simple questions by uploading files. Now, I'm taking it a step further by adding an authentication layer and working towards enabling multi-tenancy for the application.
Let's get right into it. First on the agenda is adding a user login and registration feature. I informed the tool I'm using, Cursor, that this is what I want, and it efficiently handled the task. However, it didn't automatically restrict access to the dashboard I built, so I had to prompt it specifically to implement that feature as well.
Once accomplished, a login and registration screen became visible. I opted to sign up first and then attempted to log in using the same credentials. This is where I encountered a roadblock—a persistent error message indicating a mismatch in the expected string pattern. Debugging revealed that the registration input wasn't being recorded in the database, leading to this repetitive error.
I spent some time iterating with Cursor to resolve this. Even when experimenting with different versions of language models like GPT-4o and another variant, I initially couldn't identify the root cause. It finally dawned on me that the registration API endpoint was being protected and requests were rerouted to the login screen, causing the error. It was a testament to the fact that while language models can handle many tasks, there are times when a manual inspection, like reviewing console logs and network responses, is necessary for troubleshooting. Fortunately, once I recognized the issue and communicated it to Cursor, it was quick to correct it.
Having successfully registered an account, I verified its presence in the database and logged in without issues. However, there was a minor hiccup: I wasn't being redirected to the correct pages. After some more prompts to Cursor, I achieved the smooth navigation post-sign-in that I was aiming for.
The next major step was implementing multi-tenancy, where distinct users could have personalized access to their own sets of bots and files. For instance, when user 1 logs in, they should see a different suite compared to user 2. I initiated the process by directing Cursor to ensure logged-in users could only view bots or files they had created.
I went ahead and crafted several test accounts and checked them against the database. In the process, I ran into a 404 error triggered by an endpoint modification—from /bots to just /. Adjusting this was straightforward, and it was addressed promptly. Testing showed that after a minor code change to correctly fetch bots for the logged-in user, different accounts were consistently displaying unique data sets, aligning with the multi-tenancy objective.
With this progress, I'm getting progressively closer to building a fully operational SaaS-based multi-tenant chatbot creator. Soon, it will be robust enough for production use, and I'm thrilled to be expanding its capabilities. Stay tuned for upcoming updates, where I'll continue refining file management and other features, slowly but surely bringing this vision to fruition.
Thank you for joining me on this voyage. Until the next step in our development journey!
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