Create FIM Completion (Beta)

POST 
/completions

The FIM (Fill-In-the-Middle) Completion API. User must set base_url="https://api.deepseek.com/beta" to use this feature.

Request

application/json

Body

required

model stringrequired

Possible values: [deepseek-chat]

ID of the model to use.

prompt stringrequired

Default value: Once upon a time,

The prompt to generate completions for.

echo booleannullable

Echo back the prompt in addition to the completion

frequency_penalty numbernullable

Possible values: >= -2 and <= 2

Default value: 0

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

logprobs integernullable

Possible values: <= 20

Include the log probabilities on the logprobs most likely output tokens, as well the chosen tokens. For example, if logprobs is 20, the API will return a list of the 20 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response.

The maximum value for logprobs is 20.

max_tokens integernullable

The maximum number of tokens that can be generated in the completion.

presence_penalty numbernullable

Possible values: >= -2 and <= 2

Default value: 0

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

stop

object

nullable

Up to 16 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

oneOf

MOD1

string

MOD2

Array [

string

]

stream booleannullable

Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Example Python code.

stream_options

object

nullable

Options for streaming response. Only set this when you set stream: true.

include_usage boolean

If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array. All other chunks will also include a usage field, but with a null value.

suffix stringnullable

The suffix that comes after a completion of inserted text.

temperature numbernullable

Possible values: <= 2

Default value: 1

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

We generally recommend altering this or top_p but not both.

top_p numbernullable

Possible values: <= 1

Default value: 1

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

We generally recommend altering this or temperature but not both.

Responses

200

OK

application/json

Schema

Schema

id stringrequired

A unique identifier for the completion.

choices

object[]

required

The list of completion choices the model generated for the input prompt.

Array [

finish_reason stringrequired

Possible values: [stop, length, content_filter, insufficient_system_resource]

The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached,
content_filter if content was omitted due to a flag from our content filters, or insufficient_system_resource if the request is interrupted due to insufficient resource of the inference system.

index integerrequired

logprobs

object

nullable

required

text_offset integer[]

token_logprobs number[]

tokens string[]

top_logprobs object[]

text stringrequired

]

created integerrequired

The Unix timestamp (in seconds) of when the completion was created.

model stringrequired

The model used for completion.

system_fingerprint string

This fingerprint represents the backend configuration that the model runs with.

object stringrequired

Possible values: [text_completion]

The object type, which is always "text_completion"

usage

object

Usage statistics for the completion request.

completion_tokens integerrequired

Number of tokens in the generated completion.

prompt_tokens integerrequired

Number of tokens in the prompt. It equals prompt_cache_hit_tokens + prompt_cache_miss_tokens.

prompt_cache_hit_tokens integerrequired

Number of tokens in the prompt that hits the context cache.

prompt_cache_miss_tokens integerrequired

Number of tokens in the prompt that misses the context cache.

total_tokens integerrequired

Total number of tokens used in the request (prompt + completion).

completion_tokens_details

object

Breakdown of tokens used in a completion.

reasoning_tokens integer

Tokens generated by the model for reasoning.

Example (from schema)

{
  "id": "string",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": {
        "text_offset": [
          0
        ],
        "token_logprobs": [
          0
        ],
        "tokens": [
          "string"
        ],
        "top_logprobs": [
          {}
        ]
      },
      "text": "string"
    }
  ],
  "created": 0,
  "model": "string",
  "system_fingerprint": "string",
  "object": "text_completion",
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "prompt_cache_hit_tokens": 0,
    "prompt_cache_miss_tokens": 0,
    "total_tokens": 0,
    "completion_tokens_details": {
      "reasoning_tokens": 0
    }
  }
}

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