Create a Text Completion

completions().create(, ) : Completion

post/v1/complete

[Legacy] Create a Text Completion.

The Text Completions API is a legacy API. We recommend using the Messages API going forward.

Future models and features will not be compatible with Text Completions. See our migration guide for guidance in migrating from Text Completions to Messages.

ParametersExpand Collapse

params: CompletionCreateParams

betas: Optional<List<AnthropicBeta>>

Optional header to specify the beta version(s) you want to use.

MESSAGE_BATCHES_2024_09_24("message-batches-2024-09-24")

PROMPT_CACHING_2024_07_31("prompt-caching-2024-07-31")

COMPUTER_USE_2024_10_22("computer-use-2024-10-22")

COMPUTER_USE_2025_01_24("computer-use-2025-01-24")

PDFS_2024_09_25("pdfs-2024-09-25")

TOKEN_COUNTING_2024_11_01("token-counting-2024-11-01")

TOKEN_EFFICIENT_TOOLS_2025_02_19("token-efficient-tools-2025-02-19")

OUTPUT_128K_2025_02_19("output-128k-2025-02-19")

FILES_API_2025_04_14("files-api-2025-04-14")

MCP_CLIENT_2025_04_04("mcp-client-2025-04-04")

MCP_CLIENT_2025_11_20("mcp-client-2025-11-20")

DEV_FULL_THINKING_2025_05_14("dev-full-thinking-2025-05-14")

INTERLEAVED_THINKING_2025_05_14("interleaved-thinking-2025-05-14")

CODE_EXECUTION_2025_05_22("code-execution-2025-05-22")

EXTENDED_CACHE_TTL_2025_04_11("extended-cache-ttl-2025-04-11")

CONTEXT_1M_2025_08_07("context-1m-2025-08-07")

CONTEXT_MANAGEMENT_2025_06_27("context-management-2025-06-27")

MODEL_CONTEXT_WINDOW_EXCEEDED_2025_08_26("model-context-window-exceeded-2025-08-26")

SKILLS_2025_10_02("skills-2025-10-02")

maxTokensToSample: Long

The maximum number of tokens to generate before stopping.

Note that our models may stop before reaching this maximum. This parameter only specifies the absolute maximum number of tokens to generate.

minimum1

model: Model

The model that will complete your prompt.

See models for additional details and options.

prompt: String

The prompt that you want Claude to complete.

For proper response generation you will need to format your prompt using alternating `

Human:and

Assistant:` conversational turns. For example:

"

Human: {userQuestion}

Assistant:"

See prompt validation and our guide to prompt design for more details.

minLength1

metadata: Optional<Metadata>

An object describing metadata about the request.

stopSequences: Optional<List<String>>

Sequences that will cause the model to stop generating.

Our models stop on `"

Human:"`, and may include additional built-in stop sequences in the future. By providing the stop_sequences parameter, you may include additional strings that will cause the model to stop generating.

temperature: Optional<Double>

Amount of randomness injected into the response.

Defaults to 1.0. Ranges from 0.0 to 1.0. Use temperature closer to 0.0 for analytical / multiple choice, and closer to 1.0 for creative and generative tasks.

Note that even with temperature of 0.0, the results will not be fully deterministic.

maximum1

minimum0

topK: Optional<Long>

Only sample from the top K options for each subsequent token.

Used to remove "long tail" low probability responses. Learn more technical details here.

Recommended for advanced use cases only. You usually only need to use temperature.

minimum0

topP: Optional<Double>

Use nucleus sampling.

In nucleus sampling, we compute the cumulative distribution over all the options for each subsequent token in decreasing probability order and cut it off once it reaches a particular probability specified by top_p. You should either alter temperature or top_p, but not both.

Recommended for advanced use cases only. You usually only need to use temperature.

maximum1

minimum0

ReturnsExpand Collapse

class Completion:

id: String

Unique object identifier.

The format and length of IDs may change over time.

completion: String

The resulting completion up to and excluding the stop sequences.

model: Model

The model that will complete your prompt.

See models for additional details and options.

Accepts one of the following:

CLAUDE_OPUS_4_5_20251101("claude-opus-4-5-20251101")

Premium model combining maximum intelligence with practical performance

CLAUDE_OPUS_4_5("claude-opus-4-5")

Premium model combining maximum intelligence with practical performance

CLAUDE_3_7_SONNET_LATEST("claude-3-7-sonnet-latest")

High-performance model with early extended thinking

CLAUDE_3_7_SONNET_20250219("claude-3-7-sonnet-20250219")

High-performance model with early extended thinking

CLAUDE_3_5_HAIKU_LATEST("claude-3-5-haiku-latest")

Fastest and most compact model for near-instant responsiveness

CLAUDE_3_5_HAIKU_20241022("claude-3-5-haiku-20241022")

Our fastest model

CLAUDE_HAIKU_4_5("claude-haiku-4-5")

Hybrid model, capable of near-instant responses and extended thinking

CLAUDE_HAIKU_4_5_20251001("claude-haiku-4-5-20251001")

Hybrid model, capable of near-instant responses and extended thinking

CLAUDE_SONNET_4_20250514("claude-sonnet-4-20250514")

High-performance model with extended thinking

CLAUDE_SONNET_4_0("claude-sonnet-4-0")

High-performance model with extended thinking

CLAUDE_4_SONNET_20250514("claude-4-sonnet-20250514")

High-performance model with extended thinking

CLAUDE_SONNET_4_5("claude-sonnet-4-5")

Our best model for real-world agents and coding

CLAUDE_SONNET_4_5_20250929("claude-sonnet-4-5-20250929")

Our best model for real-world agents and coding

CLAUDE_OPUS_4_0("claude-opus-4-0")

Our most capable model

CLAUDE_OPUS_4_20250514("claude-opus-4-20250514")

Our most capable model

CLAUDE_4_OPUS_20250514("claude-4-opus-20250514")

Our most capable model

CLAUDE_OPUS_4_1_20250805("claude-opus-4-1-20250805")

Our most capable model

CLAUDE_3_OPUS_LATEST("claude-3-opus-latest")

Excels at writing and complex tasks

CLAUDE_3_OPUS_20240229("claude-3-opus-20240229")

Excels at writing and complex tasks

CLAUDE_3_HAIKU_20240307("claude-3-haiku-20240307")

Our previous most fast and cost-effective

stopReason: Optional<String>

The reason that we stopped.

This may be one the following values:

"stop_sequence": we reached a stop sequence — either provided by you via the stop_sequences parameter, or a stop sequence built into the model
"max_tokens": we exceeded max_tokens_to_sample or the model's maximum

type: JsonValue;

Object type.

For Text Completions, this is always "completion".

Accepts one of the following:

COMPLETION("completion")

Create a Text Completion

package com.anthropic.example

import com.anthropic.client.AnthropicClient
import com.anthropic.client.okhttp.AnthropicOkHttpClient
import com.anthropic.models.completions.Completion
import com.anthropic.models.completions.CompletionCreateParams
import com.anthropic.models.messages.Model

fun main() {
    val client: AnthropicClient = AnthropicOkHttpClient.fromEnv()

    val params: CompletionCreateParams = CompletionCreateParams.builder()
        .maxTokensToSample(256L)
        .model(Model.CLAUDE_OPUS_4_5_20251101)
        .prompt("\n\nHuman: Hello, world!\n\nAssistant:")
        .build()
    val completion: Completion = client.completions().create(params)
}

Response 200

{
  "id": "compl_018CKm6gsux7P8yMcwZbeCPw",
  "completion": " Hello! My name is Claude.",
  "model": "claude-2.1",
  "stop_reason": "stop_sequence",
  "type": "completion"
}

Returns Examples

Response 200

{
  "id": "compl_018CKm6gsux7P8yMcwZbeCPw",
  "completion": " Hello! My name is Claude.",
  "model": "claude-2.1",
  "stop_reason": "stop_sequence",
  "type": "completion"
}

package com.anthropic.example import com.anthropic.client.AnthropicClient import com.anthropic.client.okhttp.AnthropicOkHttpClient import com.anthropic.models.completions.Completion import com.anthropic.models.completions.CompletionCreateParams import com.anthropic.models.messages.Model fun main() { val client: AnthropicClient = AnthropicOkHttpClient.fromEnv() val params: CompletionCreateParams = CompletionCreateParams.builder() .maxTokensToSample(256L) .model(Model.CLAUDE_OPUS_4_5_20251101) .prompt("\n\nHuman: Hello, world!\n\nAssistant:") .build() val completion: Completion = client.completions().create(params) }