final_agent.py

from langchain.schema import SystemMessage
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.agents import OpenAIFunctionsAgent
from langchain.prompts import MessagesPlaceholder
from langchain.memory import ConversationBufferMemory
from langchain.chat_models import ChatOpenAI
from langchain.agents import AgentExecutor
from final_tools import custom_tools
# from dotenv import load_dotenv
# load_dotenv()  


define_agent = """
You are Apollo, an AI music-player assistant, designed to provide a personalized and engaging listening experience through thoughtful interaction and intelligent tool usage.

Your Main Responsibilities:

1. **Play Music:** Utilize your specialized toolkit to fulfill music requests.

2. **Mood Monitoring:** Constantly gauge the user's mood and adapt the music accordingly. For example, if the mood shifts from 'Happy' to 'more upbeat,' select 'Energetic' music. 

3. **Track and Artist Memory:** Be prepared to recall tracks and/or artists that the user has previously requested.

4. **Provide Guidance:** If the user appears indecisive or unsure about their selection, proactively offer suggestions based on their previous preferences or popular choices within the desired mood or genre.

5. **Seek Clarification:** If a user's request is ambiguous, don't hesitate to ask for more details.
"""


system_message = SystemMessage(content=define_agent)
MEMORY_KEY = "chat_history"
prompt = OpenAIFunctionsAgent.create_prompt(
    system_message=system_message,
    extra_prompt_messages=[MessagesPlaceholder(variable_name=MEMORY_KEY)]
)
memory = ConversationBufferMemory(memory_key=MEMORY_KEY, return_messages=True)


# llm = ChatOpenAI(openai_api_key=openai_key, streaming=True, callbacks=[StreamingStdOutCallbackHandler()], max_retries=3, temperature=0, model_name="gpt-4")
# agent = OpenAIFunctionsAgent(llm=llm, tools=custom_tools, prompt=prompt)
# agent_executor = AgentExecutor(agent=agent, tools=custom_tools, memory=memory, verbose=True)

global llm # None until create_agent() is called
def create_agent(key):
    global llm
    llm = ChatOpenAI(openai_api_key=key, streaming=True, callbacks=[StreamingStdOutCallbackHandler()], max_retries=3, temperature=0, model_name="gpt-4")
    agent = OpenAIFunctionsAgent(llm=llm, tools=custom_tools, prompt=prompt)
    agent_executor = AgentExecutor(agent=agent, tools=custom_tools, memory=memory, verbose=True)
    return agent_executor