Added online model.

.gitignore

@@ -0,0 +1 @@
+venv/

py/.idea/misc.xml

@@ -3,5 +3,5 @@
   <component name="Black">
     <option name="sdkName" value="Python 3.12" />
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.12" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.12 (py)" project-jdk-type="Python SDK" />
 </project>

py/.idea/py.iml

@@ -2,7 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
+    <orderEntry type="jdk" jdkName="Python 3.12 (py)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>

py/api.py

@@ -1,10 +1,20 @@
 import requests
 import json
-
+from transformers import AutoTokenizer, LlamaForCausalLM
 
 class API:
     @staticmethod
-    def process_text(prompt, model):
+    def process_text_transformers(prompt, model):
+        model = LlamaForCausalLM.from_pretrained(model)
+        tokenizer = AutoTokenizer.from_pretrained(model)
+
+        inputs = tokenizer(prompt, return_tensors="pt")
+
+        generate_ids = model.generate(inputs.input_ids, max_length=30)
+        return tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+
+    @staticmethod
+    def process_text_local(prompt, model):
         ollama_url = "http://localhost:11434"
 
         response = requests.post(
@@ -26,13 +36,15 @@ class API:
 
     def send_message(self, message, model):
         if model == 1:
-            answer = self.process_text(message, "phi3.5")
+            answer = self.process_text_local(message, "phi3.5")
         elif model == 2:
-            answer = self.process_text(message, "gemma2:2b")
+            answer = self.process_text_local(message, "gemma2:2b")
         elif model == 3:
-            answer = self.process_text(message, "qwen2:0.5b")
+            answer = self.process_text_local(message, "qwen2:0.5b")
         elif model == 4:
-            answer = self.process_text(message, "codegemma:2b")
+            answer = self.process_text_local(message, "codegemma:2b")
+        elif model == 5:
+            answer = self.process_text_transformers(message, "meta-llama/Meta-Llama-3.1-8B")
         else:
             return "Invalid choice"
         return answer

py/venv.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+
+virtualenv venv
+source venv/bin/activate
+pip install transformers