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)