import sys, os
import traceback
from dotenv import load_dotenv
load_dotenv()
import os
sys.path.insert(0, os.path.abspath('../..'))  # Adds the parent directory to the system path
import pytest
import litellm
from litellm import embedding, completion


litellm.vertex_project = "hardy-device-386718"
litellm.vertex_location = "us-central1"
litellm.set_verbose = True

user_message = "what's the weather in SF "
messages = [{ "content": user_message,"role": "user"}]

# def logger_fn(user_model_dict):
#     print(f"user_model_dict: {user_model_dict}")
# chat-bison
# response = completion(model="chat-bison", messages=messages, temperature=0.5, top_p=0.1)
# print(response)

# text-bison

# response = completion(model="text-bison@001", messages=messages)
# print(response)

# response = completion(model="text-bison@001", messages=messages, temperature=0.1, logger_fn=logger_fn)
# print(response)

# response = completion(model="text-bison@001", messages=messages, temperature=0.4, top_p=0.1, logger_fn=logger_fn)
# print(response)

# response = completion(model="text-bison@001", messages=messages, temperature=0.8, top_p=0.4, top_k=30, logger_fn=logger_fn)
# print(response)

# chat_model = ChatModel.from_pretrained("chat-bison@001")
# parameters = {
#     "temperature": 0.2,
#     "max_output_tokens": 256,
#     "top_p": 0.8,
#     "top_k": 40
# }

# chat = chat_model.start_chat()
# response = chat.send_message("who are u? write a sentence", **parameters)
# print(f"Response from Model: {response.text}")