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import logging
from typing import Optional, Tuple
import typing
from vocode.streaming.agent.chat_gpt_agent import ChatGPTAgent
from vocode.streaming.models.agent import AgentConfig, AgentType, ChatGPTAgentConfig
from vocode.streaming.agent.base_agent import BaseAgent, RespondAgent
from vocode.streaming.agent.factory import AgentFactory
import os
import sys
import typing
from dotenv import load_dotenv
from tools.contacts import get_all_contacts
from tools.vocode import call_phone_number
from tools.email_tool import email_tasks
from tools.summarize import summarize
from langchain.memory import ConversationBufferMemory
from langchain.utilities import SerpAPIWrapper
from langchain.agents import load_tools
from stdout_filterer import RedactPhoneNumbers
load_dotenv()
from langchain.chat_models import ChatOpenAI
from langchain.chat_models import BedrockChat
from langchain.agents import initialize_agent
from langchain.agents import AgentType as LangAgentType
llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo") # type: ignore
#llm = BedrockChat(model_id="anthropic.claude-instant-v1", model_kwargs={"temperature":0}) # type: ignore
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
# Logging of LLMChains
verbose = True
agent = initialize_agent(
tools=[get_all_contacts, call_phone_number, email_tasks, summarize] + load_tools(["serpapi", "human"]),
llm=llm,
agent=LangAgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION,
verbose=verbose,
memory=memory,
)
class SpellerAgentConfig(AgentConfig, type="agent_speller"):
pass
class SpellerAgent(RespondAgent[SpellerAgentConfig]):
def __init__(self, agent_config: SpellerAgentConfig):
super().__init__(agent_config=agent_config)
async def respond(
self,
human_input,
conversation_id: str,
is_interrupt: bool = False,
) -> Tuple[Optional[str], bool]:
print("SpellerAgent: ", human_input)
res = agent.run(human_input)
return res, False
class SpellerAgentFactory(AgentFactory):
def create_agent(
self, agent_config: AgentConfig, logger: Optional[logging.Logger] = None
) -> BaseAgent:
print("Setting up agent", agent_config, agent_config.type)
if agent_config.type == AgentType.CHAT_GPT:
return ChatGPTAgent(
agent_config=typing.cast(ChatGPTAgentConfig, agent_config)
)
elif agent_config.type == "agent_speller":
return SpellerAgent(
agent_config=typing.cast(SpellerAgentConfig, agent_config)
)
raise Exception("Invalid agent config")
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