enable chat for expert, custom inference parameters

backend/src/agents/expert.py

@@ -22,29 +22,55 @@ class ExpertAgent(Agent):
         Agent.__init__(self, app, data)
 
     async def prompt(self, instruction, input=None, **kwargs):
-        # if instruction and input are passed, instruction extends the system prompt
-        # otherwise, use the one passed as the user prompt, with the regular system prompt
-
-        # TODO: if 'history' in kwargs: interpret it as user-agent turns assuming list[str]
+        # Instruction extends system if there's input or messages
+        # Otherwise instruction is the user prompt
+        # Input is always added as a user message at the end, if present
 
+        # Use 'messages' as starting point when passed
+        messages = []
+        if 'messages' in kwargs:
+            messages = [LlamaMessage(msg['role'], msg['content']) for msg in kwargs['messages']]
+        
+        # Construct the default messages
         system = self.config['system_prompt']
-        if instruction != None and input != None:
+        prompt = input
+
+        if input == None and not messages:
+            prompt = instruction
+        elif instruction:
             system += "\n" + instruction
+        
+        # Add default messages to list
+        messages.insert(0, LlamaMessage("system", system))
+        if prompt:
+            messages.append(LlamaMessage("user", prompt))
 
-        prompt = input if input != None else instruction
-        messages = [
-            LlamaMessage("system", system),
-            LlamaMessage("user", prompt)
-        ]
-
-        response = await replicate_llama_completion(self.app, messages, model=Models.llama_70b)
+        response = await replicate_llama_completion(self.app, messages, model=Models.llama_70b, max_tokens=2048)
         return response
 
     async def received_message(self, message):
-        raise Exception("TODO: expert chat support")
+        chat_view = self.app.get_chat_view(message.chat_id)
+        thread = chat_view.get_thread(message.thread_id)
+
+        def msg_role(message):
+            sender = message.sender
+            is_digit = isinstance(sender, (int, str)) and str(sender).isdigit()
+
+            if is_digit and str(sender) == str(self.id):
+                return 'assistant'
+            elif sender == 'user':
+                return 'user'
+            else:
+                raise Exception("Unsupported sender: " + sender)
+        
+        messages = [{'role': msg_role(msg), 'content': msg.content} for msg in thread.messages]
+
+        response = await self.prompt(
+            instruction=None,
+            input=None,
+            messages=messages
+        )
 
-        messages = []
-        response = await replicate_llama_completion(self.app, messages, model=Models.llama_70b)
         self.app.send_chat_message(
             chat_id=message.chat_id,
             sender=self.id,