[FIX&FEAT] 6 fix message initializing bug

[seyeong-han]

Update

• Our system can convey the previous chat histories within contexts in the Message class.
• Now, we have the summarization function. If the Message has an exceeding number of chat histories, automatically summarize the past conversations to shorten our next prompts.

  
  #### src/agent/base_agent.py ####
  # First two messages are system and user personas
  if len(messages) > 2 + NONEVICTION_LENGTH:
  messages = messages[2:-NONEVICTION_LENGTH]
  del self.message.llm_message["messages"][2:-NONEVICTION_LENGTH]
  else:
  messages = messages[2:]
  del self.message.llm_message["messages"][2:]

message_contents = [ message.to_dict()['content'] for message in messages ]

llm_message_chatgpt = { "model": self.model, "messages": [{ "role": "user", "content": "Summarize these previous conversations into 50 words:"

• str(messagecontents) }] } response, = self._get_gpt_response(llm_message_chatgpt) content = "Summarized past conversation:" + response self._add_contexts_to_llm_message("assistant", content, index=2)

To Reviewers

• Check if all the Streamlit flow is working in your system
• Look into the details of the docstring explanation. Let me know if it is hard to understand.
• meMary Chatbot Update Explanation

[kevinl424]

Docstrings are very descriptive nice! Also the video was very helpful. Going to merge this into main and work off of a UI branch.