Update llm/utils/chat.py

llm/utils/chat.py

@@ -1,7 +1,7 @@
 import time
 
 from llm.apimodels.gemini_model import Gemini
-from llm.apimodels.hf_model import HF_Mistaril, HF_TinyLlama, HF_SmolLM135, HF_SmolLM360, HF_SmolLM, HF_Gemma2, HF_Qwen2
+from llm.apimodels.hf_model import HF_Mistaril, HF_TinyLlama, HF_SmolLM135, HF_SmolLM360, HF_SmolLM, HF_Gemma2, HF_Qwen2, FreeThinker3B
 
 from typing import Optional, Any
 
@@ -91,7 +91,19 @@ class Conversation:
         except Exception as e:
             print(f"Error during conversation chain in get_conversation function: {e}")
 
-    def chatting(self, prompt: str) -> str:
+    def _libertarian_conversation(self, prompt) -> Optional[str]:
+        conversation = ConversationChain(llm=FreeThinker3B().execution(), memory=memory, return_final_only=True)
+
+        try:
+            response = conversation.predict(input=prompt)
+            print(f"response: {response}")
+            result = prettify(raw_text=response)
+            return result
+        except Exception as e:
+            print(f"Error during prediction with conversation in has_failed function: {e}")
+            return None
+
+    def chatting(self, prompt: str, is_own_model: bool) -> str:
         """
         Carries out the conversation with the user, handling errors and delays.
 
@@ -99,12 +111,17 @@ class Conversation:
             prompt(str): The prompt to be used for prediction.
 
         Returns:
-            Optional[str]: The final conversation response or None if all models fail.
+            str: The final conversation response or None if all models fail.
         """
 
         if prompt is None or prompt == "":
             raise Exception(f"Prompt must be string not None or empty string: {prompt}")
 
+        if is_own_model:
+            result = _libertarian_conversation(prompt)   
+
+            return result
+
         while self.current_model_index < len(self.model_classes):
             conversation = self._get_conversation()