The video discusses the perceived speed difference between the Ollama API and the CLI, highlighting that the actual processing times are nearly identical, with differences arising from how each handles model loading and output streaming. By demonstrating the use of streaming with the API, the presenter shows that the API can perform as quickly as the CLI, emphasizing the importance of understanding these nuances in user experience.
In the video, the presenter explores the perceived speed difference between the Ollama API and the CLI (Command Line Interface) when answering questions. Using the example of asking “What is a black hole?”, the CLI appears to respond almost instantaneously, while the API seems slower. However, upon closer examination, the actual processing time for both is nearly identical, with only minimal differences. The presenter encourages viewers to like and subscribe for more content on large language models and Ollama.
The presenter explains that the perceived speed difference is largely due to how the CLI and API handle model loading and output streaming. When using the CLI, the model is fully loaded into memory before the user is dropped into the interactive environment. This means that any loading time is not included in the user’s perception of response time. In contrast, when using the API, the user may start timing their question as soon as they press enter, which can lead to an inaccurate assessment of the total time taken.
Another factor contributing to the perceived speed difference is the way output is streamed. In the CLI, the first word of the response appears quickly, allowing users to start reading while the rest of the answer is generated. However, when using the API without streaming, the entire response is returned only after the generation is complete, making it feel slower. The presenter notes that many API clients, like Postman, do not support streaming, which further exacerbates this issue.
To illustrate the difference, the presenter demonstrates how using Curl with the API and enabling streaming can produce results similar to the CLI. By processing each chunk of output as it is generated, users can see the response appear in real-time, just like in the CLI environment. This highlights that the API can perform as quickly as the CLI when streaming is utilized correctly.
In conclusion, the video clarifies that the Ollama API is not inherently slower than the CLI; rather, the differences in user experience stem from how each handles model loading and output streaming. The presenter invites viewers to share their experiences and thoughts in the comments, emphasizing the importance of understanding these nuances when working with APIs and CLIs in the context of large language models.
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00:00 - Start with an example
00:47 - Ollama Serve
01:05 - Why it feels faster
01:15 - The first case
01:31 - Load time
02:11 - Something else
02:37 - Try an API client
03:17 - Try curl
03:29 - The code sample