> ## Documentation Index > Fetch the complete documentation index at: https://docs.gp.scale.com/llms.txt > Use this file to discover all available pages before exploring further. # Generate completion > ### Description Interact with the LLM model using the specified model_deployment_id. The LLM model will generate a text completion based on the provided prompt. ```json { "prompt": "What is the capital of France?" } ``` ## OpenAPI ````yaml https://app.stainlessapi.com/api/spec/documented/sgp/openapi.yml post /v4/models/{model_deployment_id}/completions openapi: 3.1.0 info: title: EGP API V4 description: >- This is the parent API for all EGP APIs. If you are looking for the EGP API, please go to https://api.egp.scale.com/docs. contact: name: Scale Generative AI Platform url: https://scale.com/genai-platform version: 0.1.0 servers: - url: https://api.egp.scale.com security: [] tags: - name: Models description: Model API. paths: /v4/models/{model_deployment_id}/completions: post: tags: - Models summary: Generate completion description: >- ### Description Interact with the LLM model using the specified model_deployment_id. The LLM model will generate a text completion based on the provided prompt. ```json { "prompt": "What is the capital of France?" } ``` operationId: POST-V4-/models/{model_deployment_id}/completions parameters: - name: model_deployment_id in: path required: true schema: title: Model Deployment Id type: string requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CompletionRequestV2' responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/CompletionResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' x-codeSamples: - lang: Python source: |- import os from scale_gp import SGPClient client = SGPClient( api_key=os.environ.get("SGP_API_KEY"), # This is the default and can be omitted ) for completion in client.models.completions.create( model_deployment_id="model_deployment_id", prompt="prompt", ): print(completion) - lang: Go source: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/stainless-sdks/sgp-go\"\n\t\"github.com/stainless-sdks/sgp-go/option\"\n)\n\nfunc main() {\n\tclient := sgp.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tcompletionResponse, err := client.Models.Completions.New(\n\t\tcontext.TODO(),\n\t\t\"model_deployment_id\",\n\t\tsgp.ModelCompletionNewParams{\n\t\t\tPrompt: sgp.F(\"prompt\"),\n\t\t},\n\t)\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", completionResponse.Completions)\n}\n" components: schemas: CompletionRequestV2: properties: model_request_parameters: $ref: '#/components/schemas/ParameterBindings' temperature: title: Temperature description: >- What sampling temperature to use, between [0, 2]. Higher values like 1.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. Setting temperature=0.0 will enable fully deterministic (greedy) sampling.NOTE: The temperature parameter range for some model is limited to [0, 1] if the given value is above the available range, it defaults to the max value. Temperature is ignored for OpenAI reasoning models. default: 0.2 type: number maximum: 2 minimum: 0 stop_sequences: title: Stop Sequences description: >- List of up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. items: type: string type: array maxItems: 4 max_tokens: title: Max Tokens description: > The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. If not, specified, max_tokens will be determined based on the model used: | Model API family | Model API default | EGP applied default | | --- | --- | --- | | OpenAI Completions | [`16`](https://platform.openai.com/docs/api-reference/completions/create#max_tokens) | `context window - prompt size` | | OpenAI Chat Completions | [`context window - prompt size`](https://platform.openai.com/docs/api-reference/chat/create#max_tokens) | `context window - prompt size` | | LLM Engine | [`max_new_tokens`](https://github.com/scaleapi/launch-python-client/blob/207adced1c88c1c2907266fa9dd1f1ff3ec0ea5b/launch/client.py#L2910) parameter is required | `100` | | Anthropic Claude 2 | [`max_tokens_to_sample`](https://docs.anthropic.com/claude/reference/complete_post) parameter is required | `10000` | type: integer top_p: title: Top P description: >- The cumulative probability cutoff for token selection. Lower values mean sampling from a smaller, more top-weighted nucleus. Available for models provided by Google, LLM Engine, and OpenAI. type: number top_k: title: Top K description: >- Sample from the k most likely next tokens at each step. Lower k focuses on higher probability tokens. Available for models provided by Google and LLM Engine. type: number frequency_penalty: title: Frequency Penalty description: >- Penalize tokens based on how much they have already appeared in the text. Positive values encourage the model to generate new tokens and negative values encourage the model to repeat tokens. Available for models provided by LLM Engine and OpenAI. type: number presence_penalty: title: Presence Penalty description: >- Penalize tokens based on if they have already appeared in the text. Positive values encourage the model to generate new tokens and negative values encourage the model to repeat tokens. Available for models provided by LLM Engine and OpenAI. type: number stream: title: Stream description: Flag indicating whether to stream the completion response default: false type: boolean logprobs: title: Logprobs description: >- Whether to return logprobs. Currently only supported for llmengine chat models. type: boolean top_logprobs: title: Top Logprobs description: >- Number of top logprobs to return. Currently only supported for llmengine chat models. type: integer chat_template: title: Chat Template description: >- The chat template to use for the completion. Currently only supported for llmengine chat models. type: string chat_template_kwargs: title: Chat Template Kwargs description: >- Additional keyword arguments for the chat template. Currently only supported for llmengine chat models. additionalProperties: true type: object reasoning_effort: title: Reasoning Effort description: >- The reasoning effort to use for the completion. Currently only supported for openai models. type: string enum: - low - medium - high prompt: type: string title: Prompt additionalProperties: false type: object required: - prompt title: CompletionRequestV2 CompletionResponse: properties: finish_reason: title: Finish Reason type: string prompt_tokens: title: Prompt Tokens default: 0 type: integer response_tokens: title: Response Tokens default: 0 type: integer completions: items: prefixItems: - type: string - items: type: string type: array type: array maxItems: 2 minItems: 2 type: array title: Completions choices: title: Choices items: $ref: >- #/components/schemas/egp_api_backend__server__utils__model_schemas__completions__Choice type: array additionalProperties: false type: object required: - completions title: CompletionResponse HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ParameterBindings: properties: bindings: additionalProperties: anyOf: - type: string - type: integer - type: number - type: boolean type: object title: Bindings additionalProperties: false type: object required: - bindings title: ParameterBindings egp_api_backend__server__utils__model_schemas__completions__Choice: properties: index: type: integer title: Index logprobs: $ref: >- #/components/schemas/egp_api_backend__server__utils__model_schemas__completions__ChoiceLogprobs type: object required: - index title: Choice ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context additionalProperties: true type: object required: - loc - msg - type title: ValidationError egp_api_backend__server__utils__model_schemas__completions__ChoiceLogprobs: properties: content: title: Content items: $ref: >- #/components/schemas/egp_api_backend__server__utils__model_schemas__completions__ChatCompletionTokenLogprob type: array type: object title: ChoiceLogprobs egp_api_backend__server__utils__model_schemas__completions__ChatCompletionTokenLogprob: properties: token: type: string title: Token bytes: title: Bytes items: type: integer type: array logprob: type: number title: Logprob top_logprobs: items: $ref: >- #/components/schemas/egp_api_backend__server__utils__model_schemas__completions__TopLogprob type: array title: Top Logprobs type: object required: - token - logprob - top_logprobs title: ChatCompletionTokenLogprob egp_api_backend__server__utils__model_schemas__completions__TopLogprob: properties: token: type: string title: Token bytes: title: Bytes items: type: integer type: array logprob: type: number title: Logprob type: object required: - token - logprob title: TopLogprob ````