litellm/cookbook/LiteLLM_batch_completion.ipynb

LiteLLM Batch Completions Example

• This tutorial walks through using batch_completion
• Docs: https://docs.litellm.ai/docs/completion/batching

In [ ]:

!pip install litellm

Import Batch Completion

In [7]:

import os
from litellm import batch_completion

# set your API_KEY
os.environ['ANTHROPIC_API_KEY'] = ""

Calling litellm.batch_completion

In the batch_completion method, you provide a list of messages where each sub-list of messages is passed to litellm.completion(), allowing you to process multiple prompts efficiently in a single API call.

In [11]:

import os

os.environ['ANTHROPIC_API_KEY'] = ""


responses = batch_completion(
    model="claude-2",
    messages = [
        [
            {
                "role": "user",
                "content": "good morning? "
            }
        ],
        [
            {
                "role": "user",
                "content": "what's the time? "
            }
        ]
    ]
)
responses

Out [11]:

[<ModelResponse at 0x7a164eed4450> JSON: {
   "choices": [
     {
       "finish_reason": "stop",
       "index": 0,
       "message": {
         "content": " Good morning!",
         "role": "assistant",
         "logprobs": null
       }
     }
   ],
   "created": 1694030351.309254,
   "model": "claude-2",
   "usage": {
     "prompt_tokens": 11,
     "completion_tokens": 3,
     "total_tokens": 14
   }
 },
 <ModelResponse at 0x7a164eed5800> JSON: {
   "choices": [
     {
       "finish_reason": "stop",
       "index": 0,
       "message": {
         "content": " I'm an AI assistant created by Anthropic. I don't actually have a concept of the current time.",
         "role": "assistant",
         "logprobs": null
       }
     }
   ],
   "created": 1694030352.1215081,
   "model": "claude-2",
   "usage": {
     "prompt_tokens": 13,
     "completion_tokens": 22,
     "total_tokens": 35
   }
 }]