feat: Upgrade default openai models to gpt-4o-mini which are 3x cheaper

2 files changed, 4 insertions, 4 deletions

diff --git a/docs/docs/03-configuration.md b/docs/docs/03-configuration.md
index 277d182e..60343345 100644
--- a/docs/docs/03-configuration.md
+++ b/docs/docs/03-configuration.md
@@ -32,8 +32,8 @@ Either `OPENAI_API_KEY` or `OLLAMA_BASE_URL` need to be set for automatic taggin
 | OPENAI_API_KEY        | No       | Not set            | The OpenAI key used for automatic tagging. More on that in [here](/openai).                                                                                                                     |
 | OPENAI_BASE_URL       | No       | Not set            | If you just want to use OpenAI you don't need to pass this variable. If, however, you want to use some other openai compatible API (e.g. azure openai service), set this to the url of the API. |
 | OLLAMA_BASE_URL       | No       | Not set            | If you want to use ollama for local inference, set the address of ollama API here.                                                                                                              |
-| INFERENCE_TEXT_MODEL  | No       | gpt-3.5-turbo-0125 | The model to use for text inference. You'll need to change this to some other model if you're using ollama.                                                                                     |
-| INFERENCE_IMAGE_MODEL | No       | gpt-4o-2024-05-13  | The model to use for image inference. You'll need to change this to some other model if you're using ollama and that model needs to support vision APIs (e.g. llava).                           |
+| INFERENCE_TEXT_MODEL  | No       | gpt-4o-mini | The model to use for text inference. You'll need to change this to some other model if you're using ollama.                                                                                     |
+| INFERENCE_IMAGE_MODEL | No       | gpt-4o-mini  | The model to use for image inference. You'll need to change this to some other model if you're using ollama and that model needs to support vision APIs (e.g. llava).                           |
 | INFERENCE_LANG        | No       | english            | The language in which the tags will be generated.                                                                                                                                               |
 
 ## Crawler Configs
diff --git a/docs/docs/06-openai.md b/docs/docs/06-openai.md
index fa2a83ef..6c60a690 100644
--- a/docs/docs/06-openai.md
+++ b/docs/docs/06-openai.md
@@ -4,8 +4,8 @@ This service uses OpenAI for automatic tagging. This means that you'll incur som
 
 ## Text Tagging
 
-For text tagging, we use the `gpt-3.5-turbo-0125` model. This model is [extremely cheap](https://openai.com/pricing). Cost per inference varies depending on the content size per article. Though, roughly, You'll be able to generate tags for almost 1000+ bookmarks for less than $1.
+For text tagging, we use the `gpt-4o-mini` model. This model is [extremely cheap](https://openai.com/pricing). Cost per inference varies depending on the content size per article. Though, roughly, You'll be able to generate tags for almost 3000+ bookmarks for less than $1.
 
 ## Image Tagging
 
-For image uploads, we use the `gpt-4-turbo` model for extracting tags from the image. You can learn more about the costs of using this model [here](https://platform.openai.com/docs/guides/vision/calculating-costs). To lower the costs, we're using the low resolution mode (fixed number of tokens regardless of image size). The gpt-4 model, however, is much more expensive than the `gpt-3.5-turbo`. Currently, we're using around 350 token per image inference which ends up costing around $0.01 per inference. So around 10x more expensive than the text tagging.
+For image uploads, we use the `gpt-4o-mini` model for extracting tags from the image. You can learn more about the costs of using this model [here](https://platform.openai.com/docs/guides/vision/calculating-costs). To lower the costs, we're using the low resolution mode (fixed number of tokens regardless of image size). You'll be able to run inference for 1000+ images for less than a $1.