Create load_llms.py

load_llms.py

@@ -0,0 +1,67 @@
+
+
+# populate all models available from GPT4All
+url = "https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/metadata/models3.json"
+response = urlopen(url)
+data_json = json.loads(response.read())
+
+
+def model_choices():
+    model_list = [data_json[i]['filename'] for i in range(len(data_json))]
+    return model_list
+
+    
+# get each models' description
+model_description = {model['filename']: model['description'] for model in data_json}
+
+
+def llm_intro(selected_model):
+    html_string = model_description.get(selected_model, "No description available for this model selection.")
+    formatted_description = html_string.replace("<ul>", "").replace("</ul>", "").replace("</li>", "").replace("<br>", "\n").replace("</br>", "").replace("<li>", "\n➤ ")
+    return formatted_description
+
+
+def remove_endtags(html_string, tags):
+    """Remove rear HTML tags from the input string."""
+    for tag in tags:
+        html_string = re.sub(fr"</{tag}>", "", html_string)
+    return html_string
+
+
+def replace_starttags(html_string, replacements):
+    """Replace starting HTML tags with the corresponding values."""
+    for tag, replacement in replacements.items():
+        html_string = html_string.replace(tag, replacement)
+    return html_string
+
+
+def format_html_string(html_string):
+    """Format the HTML string to a readable text format."""
+    tags_to_remove = ["ul", "li", "br"]
+    html_string = remove_endtags(html_string, tags_to_remove)
+
+    tag_replacements = {
+        "<li>": "\n➤ ",
+        "<br>": "\n",
+        "<strong>": "**",
+        "</strong>": "**"
+    }
+    formatted_string = replace_starttags(html_string, tag_replacements)
+
+    return formatted_string
+
+    
+# cache models for faster reloads
+model_cache = {}  
+
+
+def load_model(model_name):
+    """
+    This function checks the cache before loading a model.
+    If the model is cached, it returns the cached version.
+    Otherwise, it loads the model, caches it, and then returns it.
+    """
+    if model_name not in model_cache:
+        model = GPT4All(model_name)  
+        model_cache[model_name] = model
+    return model_cache[model_name]