1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
|
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 lang_prompt_demo import tools
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=tools,
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")
|
