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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
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