Switch to Mistral Nemo and increase the output length

README.md

@@ -16,7 +16,7 @@ We spend a lot of time on creating the slides and organizing our thoughts for an
 With SlideDeck AI, co-create slide decks on any topic with Generative Artificial Intelligence.
 Describe your topic and let SlideDeck AI generate a PowerPoint slide deck for you—it's as simple as that!
 
-SlideDeck AI is powered by [Mistral 7B Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2).
+SlideDeck AI is powered by [Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407).
 Originally, it was built using the Llama 2 API provided by Clarifai.
 
 *Update (v4.0)*: Legacy SlideDeck AI allowed one-shot generation of a slide deck based on the inputs. 
@@ -28,7 +28,7 @@ where you can create and improve the presentation.
 
 SlideDeck AI works in the following way:
 
-1. Given a topic description, it uses Mistral 7B Instruct to generate the *initial* content of the slides. 
+1. Given a topic description, it uses Mistral Nemo Instruct to generate the *initial* content of the slides. 
 The output is generated as structured JSON data based on a pre-defined schema.
 2. Subsequently, it uses the `python-pptx` library to generate the slides, 
 based on the JSON data from the previous step. 
@@ -52,7 +52,7 @@ number of allowed characters in the textbox, pasting would not work.
 
 # Local Development
 
-SlideDeck AI uses [Mistral 7B Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) 
+SlideDeck AI uses [Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) 
 via the Hugging Face Inference API.
 To run this project by yourself, you need to provide the `HUGGINGFACEHUB_API_TOKEN` API key,
 for example, in a `.env` file. Visit the respective websites to obtain the keys.

global_config.py

@@ -1,3 +1,6 @@
+"""
+A set of configurations used by the app.
+"""
 import logging
 import os
 
@@ -10,10 +13,14 @@ load_dotenv()
 
 @dataclass(frozen=True)
 class GlobalConfig:
-    HF_LLM_MODEL_NAME = 'mistralai/Mistral-7B-Instruct-v0.2'
+    """
+    A data class holding the configurations.
+    """
+
+    HF_LLM_MODEL_NAME = 'mistralai/Mistral-Nemo-Instruct-2407'
     LLM_MODEL_TEMPERATURE: float = 0.2
-    LLM_MODEL_MIN_OUTPUT_LENGTH: int = 50
-    LLM_MODEL_MAX_OUTPUT_LENGTH: int = 4096
+    LLM_MODEL_MIN_OUTPUT_LENGTH: int = 100
+    LLM_MODEL_MAX_OUTPUT_LENGTH: int = 4 * 4096
     LLM_MODEL_MAX_INPUT_LENGTH: int = 750
 
     HUGGINGFACEHUB_API_TOKEN = os.environ.get('HUGGINGFACEHUB_API_TOKEN', '')