In this next video, the presenter illustrates the process of monitoring requests made to a language model (LLM) through the integration of Endr architecture and LM Studio. Initially, a successful request and response are showcased, elucidating details such as the web interface URL and the content, headers, and data of the request. Subsequently, a second request utilizing a different language model is initiated, demonstrating compatibility as both models are depicted in real-time on the LM Studio interface and in the web browser. Additionally, the presenter notes the potential variance in response times among different models. Overall, emphasis is placed on the capability to monitor and seamlessly transition between various language models facilitated by the Endr architecture and LM Studio interface.
In the following video titled “0050 iPhone App Development workflow diagram,” the presenter elucidates the steps involved in establishing communication between an iPhone app and a backend server using Enro interface. This entails utilizing the server’s domain name and interfacing with specific APIs like V1 chat completion. The presenter underscores the importance of a network interface for the iPhone app, which facilitates interaction with the backend API, local API interface of LM Studio, and the LLM chat system. The LLM chat system engages with a trained model, such as Lama 2, to retrieve the prompt reply or answer, subsequently encapsulated within the body of the network response. Overall, the app receives this network response, containing the answer’s content, and integrates it back into the iPhone app’s interface. The presenter encourages viewers to revisit this segment multiple times for better comprehension before advancing to subsequent lectures.
Next, in the video titled “0051 Xcode new project and AIManager Interface creation,” the instructor guides viewers through the initial phase of developing an iPhone app that communicates with the LM Studio backend using Xcode. He underscores the importance of having the latest version of Xcode and proceeds to demonstrate the creation of a new iOS project named “AI manager” within it. Following the project’s creation, the instructor includes a Swift file named “AI manager interface” in the project, which will facilitate interaction with the backend. Concluding this phase of the tutorial, he establishes the “AI manager interface” class and ensures a successful build. Subsequent steps involve further development of the “AI manager interface” to enable communication with the online backend.