---
title: "/completions"
url: "/docs/text_completion"
canonical_url: "https://docs.litellm.ai/docs/text_completion"
type: "docs"
last_updated: "2026-10-03"
related:
  - "/docs/response_api"
  - "/docs/image_generation"
---
# /completions

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


## Overview

| Feature | Supported | Notes |
|---------|-----------|-------|
| Cost Tracking | ✅ | Works with all supported models |
| Logging | ✅ | Works across all integrations |
| End-user Tracking | ✅ | |
| Streaming | ✅ | |
| Fallbacks | ✅ | Works between supported models |
| Loadbalancing | ✅ | Works between supported models |
| Guardrails | ✅ | Applies to input prompts and output text (non-streaming only) |
| Supported Providers | All Chat Completion Providers | |

### Usage
**LiteLLM Python SDK**

```python
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

```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**

```python
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**

```shell
curl --location 'http://0.0.0.0:4000/completions' \
    --header 'Content-Type: application/json' \
    --header "Authorization: Bearer $LITELLM_API_KEY" \
    --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](https://platform.openai.com/docs/api-reference/completions) 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**](https://platform.openai.com/docs/api-reference/completions/object)

**Non-Streaming Response**

```python
{
  "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**

```python
{
  "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](../docs/providers/text_completion_openai)                 | 
| Azure OpenAI|   [Usage](../docs/providers/azure)                 |

## Related pages

- [responses()](https://docs.litellm.ai/docs/response_api.md)
- [image_generation()](https://docs.litellm.ai/docs/image_generation.md)