src/agents/Prompt/base_Prompts.py

# SOP========================================================================================================
# "environment_prompt"
# current_state , self(sop)
Get_environment_prompt = "f\"The current scenario is as follows <environment> {self.current_state.environment_prompt} </environment>\""


# sop.transit
#================================================================
Transit_system_prompt = "f\"{environment_prompt};{judge_system_prompt}\""

#  transit chat message 
#  "environment_prompt" is get from "Get_environment_prompt" ; "chat_history_message" if from Memory
Transit_message = "f\"{environment_summary};The chat history is as follows:\\n<chat> {chat_history_message}\\n</chat>;You especially need to pay attention to the last query<query>\\n{query}\\n</query> and the relevant conversation <relevant>\\n{relevant_history} \\n</relevant>\\n\""


Transit_last_prompt = "f\"{judge_last_prompt}\""
#sop.transit================================================================

# sop.call
#================================================================
# help controller to determine the next role to speak.(the {} is agent role)    call_prompt + allocate_component  
Allocate_component = "f\"If it's currently supposed to be speaking for {role}, then output <end>{role}</end>.\\n\""

# environment_prompt is get from "Get_environment_prompt" ; "chat_history_message" if from Memory
Call_system_prompt = "f\"{environment_prompt};{call_system_prompt};{allocate_prompt}\""

#
Call_last_prompt = "f\"You especially need to pay attention to the last query<query>\\n{query}\\n</query> and the relevant conversation <relevant>\\n{relevant_history} \\n</relevant>\\n;Now please choose the person to speak according to the following rules :{allocate_prompt};Note: The person whose turn it is now cannot be the same as the person who spoke last time, so {last_name} cannot be output\\n.\""

Call_message = "f\"The chat history is as follows:\\n<history>\\n{chat_history_message}</history>\\n;The last person to speak is: {last_name}\\n. \""
#sop.call================================================================
# SOP========================================================================================================






# Memory========================================================================================================
Single_message = "f\"{name} said that :{content}\""

Chat_total_message = "f\"{chat_history}\""
# Memory========================================================================================================






# Environment========================================================================================================
Default_environment_summary_system_prompt = "\"\\nYour task is to summarize the historical dialogue records according to the current scene, and summarize the most important information\""

Default_environment_summary_last_prompt = "\"Please make a summary based on the historical chat records, the output format is history summary: \{your summary content\} \""

Environment_summary_memory =  "f\"The information you need to know is as follows:\\n</information>\\n\
            The summary of the previous dialogue history is:<summary>\\n{summary}\\n.</summary>\
            The latest conversation record is as follows:\\n<hisroty> {chat_history}\\n</history>,\
            the relevant chat history you may need is:<relevant>{relevant_history}</relevant>\""
            
Environment_summary_system_prompt = "f\"{environment_prompt};{current_memory};{summary_system_prompt};\""


# observe
Agent_observe_relevant_memory = "f\"The relevant chat history are as follows:\\n<relevant_history>{relevant_memory} </relevant_history>\\n\""


Agent_observe_memory = "f\"Here's what you need to know(Remember, this is just information, Try not to repeat what's inside):\\n<information>\\n{relevant_memory};\
            The previous summary of chat history is as follows :<summary>\\n{agent.short_term_memory}\\n</summary>.\
            The new chat history is as follows:\\n<history> {conversations}\\n</history>\\n\
            </information>\""
# Environment========================================================================================================




# Agent========================================================================================================
Agent_summary_system_prompt = "f\"{summary_prompt};Please summarize past key summary \\n<summary>\\n {self.short_term_memory} </summary>and new chat_history as follows: <history>\\n{conversations}</history>\""          
            
Agent_last_prompt = "f\"{last_prompt};\\nPlease continue the talk based on your known information,Make an effort to make the conversation more coherent and  try to respond differently from your existing knowledge, avoiding repeating what others have said.\""

Agent_system_prompt = "f\"{system_prompt},\""
# Agent========================================================================================================