Added persona

neon_llm_core/llm.py

@@ -60,14 +60,14 @@ def llm_model_name(self) -> str:
     def _system_prompt(self) -> str:
         pass
 
-    def ask(self, message: str, chat_history: List[List[str]]) -> str:
+    def ask(self, message: str, chat_history: List[List[str]], persona: dict) -> str:
         """ Generates llm response based on user message and (user, llm) chat history """
-        prompt = self._assemble_prompt(message, chat_history)
+        prompt = self._assemble_prompt(message, chat_history, persona)
         llm_text_output = self._call_model(prompt)
         return llm_text_output
 
     @abstractmethod
-    def get_sorted_answer_indexes(self, question: str, answers: List[str]) -> List[int]:
+    def get_sorted_answer_indexes(self, question: str, answers: List[str], persona: dict) -> List[int]:
         """
             Creates sorted list of answer indexes with respect to order provided in :param answers
             Results should be sorted from best to worst
@@ -87,7 +87,7 @@ def _call_model(self, prompt: str) -> str:
         pass
 
     @abstractmethod
-    def _assemble_prompt(self, message: str, chat_history: List[List[str]]):
+    def _assemble_prompt(self, message: str, chat_history: List[List[str]], persona: dict):
         """
             Assembles prompt engineering logic
 

neon_llm_core/rmq.py

@@ -106,9 +106,10 @@ def handle_request(self, body: dict):
 
         query = body["query"]
         history = body["history"]
+        persona = body.get("persona",{})
 
         try:
-            response = self.model.ask(message=query, chat_history=history)
+            response = self.model.ask(message=query, chat_history=history, persona=persona)
         except ValueError as err:
             LOG.error(f'ValueError={err}')
             response = 'Sorry, but I cannot respond to your message at the moment, please try again later'
@@ -131,12 +132,13 @@ def handle_score_request(self, body: dict):
 
         query = body["query"]
         responses = body["responses"]
+        persona = body.get("persona",{})
 
         if not responses:
             sorted_answer_indexes = []
         else:
             try:
-                sorted_answer_indexes = self.model.get_sorted_answer_indexes(question=query, answers=responses)
+                sorted_answer_indexes = self.model.get_sorted_answer_indexes(question=query, answers=responses, persona=persona)
             except ValueError as err:
                 LOG.error(f'ValueError={err}')
                 sorted_answer_indexes = []
@@ -159,17 +161,19 @@ def handle_opinion_request(self, body: dict):
 
         query = body["query"]
         options = body["options"]
+        persona = body.get("persona",{})
         responses = list(options.values())
 
         if not responses:
             opinion = "Sorry, but I got no options to choose from."
         else:
             try:
-                sorted_answer_indexes = self.model.get_sorted_answer_indexes(question=query, answers=responses)
+                sorted_answer_indexes = self.model.get_sorted_answer_indexes(question=query, answers=responses, persona=persona)
                 best_respondent_nick, best_response = list(options.items())[sorted_answer_indexes[0]]
                 opinion = self._ask_model_for_opinion(respondent_nick=best_respondent_nick,
                                                       question=query,
-                                                      answer=best_response)
+                                                      answer=best_response,
+                                                      persona=persona)
             except ValueError as err:
                 LOG.error(f'ValueError={err}')
                 opinion = "Sorry, but I experienced an issue trying to make up an opinion on this topic"
@@ -183,11 +187,11 @@ def handle_opinion_request(self, body: dict):
                           queue=routing_key)
         LOG.info(f"Handled ask request for message_id={message_id}")
 
-    def _ask_model_for_opinion(self, respondent_nick: str, question: str, answer: str) -> str:
+    def _ask_model_for_opinion(self, respondent_nick: str, question: str, answer: str, persona: dict) -> str:
         prompt = self.compose_opinion_prompt(respondent_nick=respondent_nick,
                                              question=question,
                                              answer=answer)
-        opinion = self.model.ask(message=prompt, chat_history=[])
+        opinion = self.model.ask(message=prompt, chat_history=[], persona=persona)
         LOG.info(f'Received LLM opinion={opinion}, prompt={prompt}')
         return opinion
 

version.py

@@ -26,4 +26,4 @@
 # NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 # SOFTWARE,  EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-__version__ = "0.0.6"
+__version__ = "0.1.0"