from litellm import completion
import os

## set ENV variables 
os.environ["OPENAI_API_KEY"] = "your-openai-key" 
os.environ["COHERE_API_KEY"] = "your-cohere-key" 

messages = [{ "content": "Hello, how are you?","role": "user"}]

# openai call
response = completion(model="gpt-3.5-turbo", messages=messages)

# cohere call
response = completion(model="command-nightly", messages=messages)
print(response)

from litellm import acompletion
import asyncio

async def test_get_response():
    user_message = "Hello, how are you?"
    messages = [{"content": user_message, "role": "user"}]
    response = await acompletion(model="gpt-3.5-turbo", messages=messages)
    return response

response = asyncio.run(test_get_response())
print(response)

from litellm import completion
response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
for part in response:
    print(part.choices[0].delta.content or "")

# claude 2
response = completion('claude-2', messages, stream=True)
for part in response:
    print(part.choices[0].delta.content or "")

from litellm import completion

## set env variables for logging tools
os.environ["LANGFUSE_PUBLIC_KEY"] = ""
os.environ["LANGFUSE_SECRET_KEY"] = ""
os.environ["LLMONITOR_APP_ID"] = "your-llmonitor-app-id"

os.environ["OPENAI_API_KEY"]

# set callbacks
litellm.success_callback = ["langfuse", "llmonitor"] # log input/output to langfuse, llmonitor, supabase

#openai call
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])

import openai # openai v1.0.0+
client = openai.OpenAI(api_key="anything",base_url="http://0.0.0.0:8000") # set proxy to base_url
# request sent to model set on litellm proxy, `litellm --model`
response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
    {
        "role": "user",
        "content": "this is a test request, write a short poem"
    }
])

print(response)