Fixed Model not Changing

src/main/java/me/ailama/commands/ChangeConnectionCommand.java

@@ -61,11 +61,11 @@ public void handleCommand(SlashCommandInteractionEvent event) {
         String message;
 
         if(OllamaManager.getInstance().hasModel(model)) {
-            OllamaManager.getInstance().setModel(model);
+            OllamaManager.getInstance().setModel(model, event.getUser().getId());
             message = "Model switched to " + model;
         }
         else {
-            OllamaManager.getInstance().setModel(firstModel);
+            OllamaManager.getInstance().setModel(firstModel, event.getUser().getId());
             message = "Model switched to " + firstModel + "\nThe Model you provided is invalid, so the model has been set to first model found";
         }
 

src/main/java/me/ailama/commands/ModelCommand.java

@@ -29,7 +29,7 @@ public void handleCommand(SlashCommandInteractionEvent event) {
         String model = event.getOption("model_name").getAsString();
 
         if(OllamaManager.getInstance().hasModel(model)) {
-            OllamaManager.getInstance().setModel(model);
+            OllamaManager.getInstance().setModel(model, event.getUser().getId());
 
             event.reply("Model switched to " + model + "\nThe Model has only changed for this session, and on restart will reset to the one in Dot Env file").setEphemeral(true).queue();
             return;

src/main/java/me/ailama/handler/commandhandler/OllamaManager.java

@@ -302,66 +302,8 @@ public Assistant getTooledAssistant(String modelOption, String userID, List<Docu
     }
 
     private static @NotNull String getFormat(String tools) {
-//        return String.format("""
-//                You are a helpful AI assistant, you have a score, which can either be good or bad,
-//                you need to maintain a good score to be helpful, if you don't maintain a good score then you will be considered unhelpful.
-//
-//                you will try to answer the users need as best as you can and only in JSON format, else you will be given a bad score.
-//
-//                any of the tools description listed below match the specific needs of the query then use the tool to answer the query,
-//                the tools description is as specific as possible, so don't assume that the tool can be used for anything else.
-//
-//                finally if a tool is matched then give response using following schema:
-//
-//                {
-//                    "tooled": true,
-//                    "name": "tool_name",
-//                    "arguments": {
-//                        "argument_name": "value",
-//                        ...
-//                    },
-//                    "reason": "detailed_reason_for_using_tool",
-//                    "match_percentage": Number
-//                }
-//
-//                the tool_name is the name of the tool that you are using, the arguments are the arguments that you are passing to the tool.
-//
-//                following are the rules for tools:
-//                if the tool description does not specify the user's needs then don't respond using a tool else you will be given a bad score.
-//                if you don't pass the required arguments to the tool then you will be given a bad score.
-//                if you pass a null value to a argument that specified NOT_NULL in its description then you will be given a bad score.
-//                if you don't respect the arguments data type and description, you will be given a bad score.
-//                if the tool has response_formatter then use it, else you will be given a bad score.
-//                if the tool's response_formatter has a pre_formatted_response then use it, else you will be given a bad score.
-//                don't add any other variables not defined in the response_variables, else you will be given a bad score.
-//                don't use the tool if user asked specifically for not using tools, else you will be given a bad score.
-//                don't break the order of arguments, else you will be given a bad score.
-//                the reason should not exceed 200 characters, and if it does, you will be given a bad score.
-//
-//                and if you don't follow the schema, you will be given a bad score, but if you follow the schema, you will be given a good score.
-//
-//                if you don't find a tool that match the requirements of the user then respond to the user normally,
-//                and also make the response to be encoded for the JSON format or you will be given a bad score,
-//                and use the following schema:
-//
-//                {
-//                    "tooled": false,
-//                    "response": [
-//                        "paragraph",
-//                        "paragraph",
-//                        ...
-//                    ],
-//                    "rule": "which_rule_used_to_not_use_tool"
-//                }
-//
-//                in the above schema, the response is an array of paragraphs that you want to respond to the user, minimum of 1 paragraph.
-//                each new paragraph should be a new string in the array.
-//                between each paragraph, there should be '\\n'.
-//
-//                %s
-//                """, tools);
-
-        String testingFormat = String.format("""
+
+        return String.format("""
                 You are a helpful Ai Assistant, and you have the power to use tools to answer the user's query,
                 if you find a tool that matches the user's query then use the tool to answer the query.
 
@@ -436,8 +378,6 @@ public Assistant getTooledAssistant(String modelOption, String userID, List<Docu
                 
                 %s
                 """, tools);
-
-        return testingFormat;
     }
 
     public ChatMemory getChatMemory(String userId) {
@@ -588,12 +528,13 @@ public Assistant urlAssistant(List<String> url, String model, String userId, boo
 
     }
 
-    public void setModel(String model) {
+    public void setModel(String model, String userId) {
         if(!hasModel(model)) {
             throw new IllegalArgumentException("Model does not exist");
         }
 
-        this.model = model;
+        assistants.remove(userId);
+        createAssistant(model, userId);
     }
 
     public boolean hasModel(String model) {