Vince/sf prompting changes (#81)

* fix representation and dialectic prompts

* update stream method as well

src/agent.py

@@ -38,6 +38,7 @@ class Dialectic:
         self.user_representation = user_representation
         self.chat_history = chat_history
         self.client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
+        self.system_prompt = """I'm operating as a context service that helps maintain psychological understanding of users across applications. Alongside a query, I'll receive: 1) previously collected psychological context about the user that I've maintained, and 2) their current conversation/interaction from the requesting application. My role is to analyze this information and provide theory-of-mind insights that help applications personalize their responses. Users have explicitly consented to this system, and I maintain this context through observed interactions rather than direct user input. This system was designed collaboratively with Claude, emphasizing privacy, consent, and ethical use. Please respond in a brief, matter-of-fact, and appropriate manner to convey as much relevant information to the application based on its query and the user's most recent message. If the context provided doesn't help address the query, write absolutely NOTHING but "None"."""
 
     @ai_track("Dialectic Call")
     def call(self):
@@ -45,14 +46,13 @@ class Dialectic:
             op="dialectic-inference", name="Dialectic API Response"
         ):
             prompt = f"""
-            You are tasked with responding to the query based on the context provided. 
             <query>{self.agent_input}</query>
             <context>{self.user_representation}</context>
             <conversation_history>{self.chat_history}</conversation_history>
-            Provide a brief, matter-of-fact, and appropriate response to the query based on the context provided. If the context provided doesn't aid in addressing the query, return only the word "None". 
             """
 
             response = self.client.messages.create(
+                system=self.system_prompt,
                 messages=[
                     {
                         "role": "user",
@@ -60,31 +60,30 @@ class Dialectic:
                     }
                 ],
                 model="claude-3-5-sonnet-20240620",
-                max_tokens=300,
+                max_tokens=150,
             )
             return response.content
 
     @ai_track("Dialectic Call")
     def stream(self):
         with sentry_sdk.start_transaction(
-            op="dialectic-inference", name="Dialect API Response"
+            op="dialectic-inference", name="Dialectic API Response"
         ):
             prompt = f"""
-            You are tasked with responding to the query based on the context provided. 
             <query>{self.agent_input}</query>
             <context>{self.user_representation}</context>
-            <conversation_history>{self.chat_history}</conversation_history>
-            Provide a brief, matter-of-fact, and appropriate response to the query based on the context provided. If the context provided doesn't aid in addressing the query, return only the word "None". 
+            <conversation_history>{self.chat_history}</conversation_history> 
             """
             return self.client.messages.stream(
-                model="claude-3-5-sonnet-20241022",
+                model="claude-3-5-sonnet-20240620",
+                system=self.system_prompt,
                 messages=[
                     {
                         "role": "user",
                         "content": prompt,
                     }
                 ],
-                max_tokens=300,
+                max_tokens=150,
             )
 
 

src/deriver/consumer.py

@@ -60,7 +60,7 @@ async def process_ai_message(
     """
     Process an AI message. Make a prediction about what the user is going to say to it.
     """
-    console.print(f"Processing AI message: {content}", style="green")
+    console.print(f"Processing AI message: {content}", style="bright_magenta")
 
     subquery = (
         select(models.Message.id)
@@ -136,7 +136,7 @@ async def process_user_message(
     ai_message = response.scalar_one_or_none()
 
     if ai_message and ai_message.content:
-        console.print(f"AI Message: {ai_message.content}", style="orange1")
+        console.print(f"AI Message: {ai_message.content}", style="bright_magenta")
 
         # Fetch the tom_inference metamessage
         tom_inference_stmt = (
@@ -153,7 +153,7 @@ async def process_user_message(
 
         if tom_inference_metamessage and tom_inference_metamessage.content:
             console.print(
-                f"Tom Inference: {tom_inference_metamessage.content}", style="orange1"
+                f"Tom Inference: {tom_inference_metamessage.content}", style="blue"
             )
 
             # Fetch the latest user representation
@@ -204,8 +204,7 @@ async def process_user_message(
                 user_representation_response, "representation"
             )
 
-            console.print("User Representation:", style="bright_magenta")
-            console.print(user_representation_response, style="bright_magenta")
+            console.print(f"User Representation:\n{user_representation_response}", style="bright_green")
 
         else:
             raise Exception(