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from langchain_community.chat_models import ChatOllama | |
from prompts.prompt import rag_agent_prompt | |
from agents.functions_agent.base import create_functions_agent | |
from langchain.agents import AgentExecutor | |
from langchain.memory import ChatMessageHistory | |
from functions import get_openai_functions, tools, get_openai_tools | |
from config import config | |
llm = ChatOllama(model = config.ollama_model, temperature = 0.55) | |
tools_dict = get_openai_tools() | |
history = ChatMessageHistory() | |
functions_agent = create_functions_agent(llm=llm, prompt=rag_agent_prompt) | |
functions_agent_executor = AgentExecutor(agent=functions_agent, tools=tools, verbose=True, return_intermediate_steps=True) | |
if __name__ == "__main__": | |
while True: | |
try: | |
inp = input("User:") | |
if inp == "/bye": | |
break | |
response = functions_agent_executor.invoke({"input": inp, "chat_history": history, "tools" : tools_dict}) | |
response['output'] = response['output'].replace("<|im_end|>", "") | |
history.add_user_message(inp) | |
history.add_ai_message(response['output']) | |
print(response['output']) | |
except Exception as e: | |
print(e) | |
continue | |