Text Completion

Usage

LiteLLM Python SDK

from litellm import text_completion

response = text_completion(
    model="gpt-3.5-turbo-instruct",
    prompt="Say this is a test",
    max_tokens=7
)

LiteLLM Proxy Server

1. Define models on config.yaml

model_list:
  - model_name: gpt-3.5-turbo-instruct
    litellm_params:
      model: text-completion-openai/gpt-3.5-turbo-instruct # The `text-completion-openai/` prefix will call openai.completions.create
      api_key: os.environ/OPENAI_API_KEY
  - model_name: text-davinci-003
    litellm_params:
      model: text-completion-openai/text-davinci-003
      api_key: os.environ/OPENAI_API_KEY

2. Start litellm proxy server

litellm --config config.yaml

OpenAI Python SDK

from openai import OpenAI

# set base_url to your proxy server
# set api_key to send to proxy server
client = OpenAI(api_key="<proxy-api-key>", base_url="http://0.0.0.0:4000")

response = client.completions.create(
    model="gpt-3.5-turbo-instruct",
    prompt="Say this is a test",
    max_tokens=7
)

print(response)

Curl Request

curl --location 'http://0.0.0.0:4000/completions' \
    --header 'Content-Type: application/json' \
    --header 'Authorization: Bearer sk-1234' \
    --data '{
        "model": "gpt-3.5-turbo-instruct",
        "prompt": "Say this is a test",
        "max_tokens": 7
    }'

Input Params

LiteLLM accepts and translates the OpenAI Text Completion params across all supported providers.

Required Fields

• model: string - ID of the model to use
• prompt: string or array - The prompt(s) to generate completions for

Optional Fields

• best_of: integer - Generates best_of completions server-side and returns the "best" one
• echo: boolean - Echo back the prompt in addition to the completion.
• frequency_penalty: number - Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency.
• logit_bias: map - Modify the likelihood of specified tokens appearing in the completion
• logprobs: integer - Include the log probabilities on the logprobs most likely tokens. Max value of 5
• max_tokens: integer - The maximum number of tokens to generate.
• n: integer - How many completions to generate for each prompt.
• presence_penalty: number - Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far.
• seed: integer - If specified, system will attempt to make deterministic samples
• stop: string or array - Up to 4 sequences where the API will stop generating tokens
• stream: boolean - Whether to stream back partial progress. Defaults to false
• suffix: string - The suffix that comes after a completion of inserted text
• temperature: number - What sampling temperature to use, between 0 and 2.
• top_p: number - An alternative to sampling with temperature, called nucleus sampling.
• user: string - A unique identifier representing your end-user

Output Format

Here's the exact JSON output format you can expect from completion calls:

Follows OpenAI's output format

Non-Streaming Response

{
  "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
  "object": "text_completion",
  "created": 1589478378,
  "model": "gpt-3.5-turbo-instruct",
  "system_fingerprint": "fp_44709d6fcb",
  "choices": [
    {
      "text": "\n\nThis is indeed a test",
      "index": 0,
      "logprobs": null,
      "finish_reason": "length"
    }
  ],
  "usage": {
    "prompt_tokens": 5,
    "completion_tokens": 7,
    "total_tokens": 12
  }
}

Streaming Response

{
  "id": "cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe",
  "object": "text_completion",
  "created": 1690759702,
  "choices": [
    {
      "text": "This",
      "index": 0,
      "logprobs": null,
      "finish_reason": null
    }
  ],
  "model": "gpt-3.5-turbo-instruct"
  "system_fingerprint": "fp_44709d6fcb",
}

Supported Providers

Provider	Link to Usage
OpenAI	Usage
Azure OpenAI	Usage