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import datetime
from llama_cpp_agent import LlamaCppAgent
from llama_cpp_agent import MessagesFormatterType
from llama_cpp_agent.agent_memory.event_memory import Event
from llama_cpp_agent.chat_history.messages import Roles
from llama_cpp_agent.llm_agent import SystemPromptModule, SystemPromptModulePosition
from llama_cpp_agent.providers import LlamaCppServerProvider
from memory import output_settings, agent_core_memory, agent_retrieval_memory, agent_event_memory, update_memory_section
from prompts import assistant_prompt, memory_prompt, wrap_function_response_in_xml_tags_json_mode, \
generate_write_message, generate_write_message_with_examples, wrap_user_message_in_xml_tags_json_mode
provider = LlamaCppServerProvider("http://localhost:8080")
agent = LlamaCppAgent(
provider,
system_prompt=assistant_prompt,
debug_output=True,
predefined_messages_formatter_type=MessagesFormatterType.CHATML,
)
settings = provider.get_provider_default_settings()
settings.n_predict = 1024
settings.temperature = 0.65
settings.top_k = 40
settings.top_p = 0.85
memory_section = SystemPromptModule("memory",
"The following section shows the count of memories in archival memory and chat history memory and the current content of your core memory:")
date_time_section = SystemPromptModule("current_date_time", "The following section shows the current date and time:")
memory_intro_section = SystemPromptModule(section_name="memory_intro",
prefix="To support you in your task as a AI assistant and to help you remembering things, you have access to 3 different types of memory.",
position=SystemPromptModulePosition.after_system_instructions)
memory_intro_section.set_content(memory_prompt)
output_settings.output_structured_output_and_raw_json_string = True
while True:
user_input = input(">")
if user_input == "exit":
break
update_memory_section(memory_section)
date_time_section.set_content(datetime.datetime.now().strftime("%d.%m.%Y") + "\nFormat: dd.mm.yyyy")
agent_event_memory.add_event(Roles.user, wrap_user_message_in_xml_tags_json_mode(user_input))
agent_output, json_output = agent.get_chat_response(
chat_history=agent_event_memory.get_event_memory_manager().build_chat_history(),
llm_sampling_settings=settings,
system_prompt_modules=[memory_intro_section, memory_section, date_time_section],
structured_output_settings=output_settings)
agent_event_memory.add_event(Roles.assistant, json_output)
while True:
update_memory_section(memory_section)
date_time_section.set_content(datetime.datetime.now().strftime("%d.%m.%Y") + "\nFormat: dd.mm.yyyy")
if agent_output[0]["function"] == "write_message_to_user":
agent_event_memory.add_event(Roles.tool, generate_write_message())
output = agent.get_chat_response(
chat_history=agent_event_memory.get_event_memory_manager().build_chat_history(),
add_message_to_chat_history=False, add_response_to_chat_history=False,
system_prompt_modules=[memory_intro_section, memory_section, date_time_section],
llm_sampling_settings=settings)
agent_event_memory.add_event(Roles.assistant, output)
print(output)
break
agent_event_memory.add_event(Roles.tool, wrap_function_response_in_xml_tags_json_mode(
agent_output[0]["return_value"]))
agent_output, json_output = agent.get_chat_response(
chat_history=agent_event_memory.get_event_memory_manager().build_chat_history(),
llm_sampling_settings=settings,
system_prompt_modules=[memory_intro_section, memory_section,
date_time_section],
structured_output_settings=output_settings)
agent_event_memory.add_event(Roles.assistant, json_output)
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