Debugging LangChain chat model AzureChatOpenAI

main.py

import logging
import sys
from dotenv import load_dotenv
from dotenv import dotenv_values

from langchain.chat_models import AzureChatOpenAI
from langchain.agents import initialize_agent

from langchain.chains import LLMChain

from langchain.prompts import PromptTemplate

from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import (
    ChatPromptTemplate,
    HumanMessagePromptTemplate,
)

load_dotenv()
config = dotenv_values(".env")


#human_message_prompt = HumanMessagePromptTemplate(
#        prompt=PromptTemplate(
#            template="What is a good name for a company that makes {product}?",
#            input_variables=["product"],
#        )
#    )
#chat_prompt_template = ChatPromptTemplate.from_messages([human_message_prompt])


#chat = AzureChatOpenAI(
#    deployment_name="gpt-35-turbo",
#    model_kwargs={
#        "api_key": config["OPENAI_API_KEY"],
#        "api_base": config["OPENAI_API_BASE"],
#        "api_type": config["OPENAI_API_TYPE"],
#        "api_version": config["OPENAI_API_VERSION"],
#    },
#)

chat = AzureChatOpenAI(
    deployment_name="gpt-35-turbo",
    openai_api_version="2023-03-15-preview",
    openai_api_key=config["OPENAI_API_KEY"],
    openai_api_base=config["OPENAI_API_BASE"],
    openai_api_type=config["OPENAI_API_TYPE"],
)


prompt=PromptTemplate(
    template="What is a good name for a company that makes {product}?",
    input_variables=["product"],
)

#chain = LLMChain(llm=chat, prompt=chat_prompt_template, verbose=True)
chain = LLMChain(llm=chat, prompt=prompt, verbose=True)
print(chain)
#print(chat)
print(chain.run("colorful socks"))