update assistant script

core/demorrha.py

@@ -19,9 +19,8 @@ from dotenv import load_dotenv
 class DemorrhaAssistant(object):
     def __init__(self):
         load_dotenv()
-        self.client = self.initialize_client() # OpenAI(api_key = getenv("OPENAI_API_KEY"))
+        self.client = self.initialize_client()
         self.vector_store = None
-        self.load_assistant()
         self.list_vector_store_ids = []
 
     def initialize_client(self):
@@ -112,14 +111,15 @@ class DemorrhaAssistant(object):
         )
 
     def load_assistant(self, assistant_name="Demorrha"):
-        system_prompt = GlobalSystemPrompts.linguascribe()
+        self.set_system_prompt(GlobalSystemPrompts.linguascribe())
+        # system_prompt = GlobalSystemPrompts.linguascribe()
         assistant_id = self.search_assistant(assistant_name)
         if assistant_id is None:
             self.assistant = self.client.beta.assistants.create(
                 model="gpt-4o-mini",
                 name="Demorrha",
                 description="Traite les messages des utilisateurs et génère une traduction.",
-                instructions=f"{system_prompt}",
+                instructions=f"{self.system_prompt}",
                 temperature=0.1,
                 tools=[{"type": "file_search"}]
             )
@@ -169,32 +169,24 @@ class DemorrhaAssistant(object):
         )
 
     def use_assistant(self):
-        self.set_system_prompt(GlobalSystemPrompts.linguascribe())
         # Utiliser l'assistant ici
+        full_response = ""
         with self.client.beta.threads.create_and_run(
             assistant_id=self.assistant.id,
             thread={
                 "messages": [
-                    {"role": "system", "content": f"{self.system_prompt}"},
                     {"role": "user", "content": self.payload_content}
                 ]
             },
             stream=True
         ) as stream:
             for event in stream:
-                # Print the text from text delta events
-                if event.type == "thread.message.delta" and event.data.delta.content:
-                    print(event.data.delta.content[0].text)
-    
-"""
-
-            file_paths = ["style.txt"]
-            file_streams = [open(path, "rb") for path in file_paths]
-
-            file_batch = client.beta.vector_stores.file_batches.upload_and_poll(
-            vector_store_id=vector_store.id, files=file_streams
-            )
-"""
+                if event.event == "thread.message.delta":
+                    full_response += event.data.delta.content[0].text.value
+                    yield full_response + "▌"
+                elif event.event == "thread.message.completed":
+                    yield event.data.content[0].text.value
+                    return 
 
 if __name__ == "__main__":
     demorrha = DemorrhaAssistant()
@@ -215,7 +207,10 @@ if __name__ == "__main__":
     # Exemple d'utilsation de l'assistant
     demorrha.load_assistant("Demorrha")
     demorrha.update_vector_store_ids()
-    demorrha.set_payload("Bonjour, comment ça va ?", "Traduit le texte en Anglais")
-    demorrha.use_assistant()
-    #print("Réponse de l'assistant:", response)
-
+    demorrha.set_payload("Tu dois faire preuve de courage pour trouver la force.", "Traduit le texte en Anglais. Et applique les instructions du fichier \'style.txt\'")
+    response_generator = demorrha.use_assistant()
+    final_response = ""
+    for response in response_generator:
+        print(response, end="\r")
+        final_response = response
+    print(f"\nRéponse finale de l'assistant: {final_response}")