> This page is for version 1.10.1 (default). > For other versions, use one of these documentation indexes: > - 1.10.1 (default): https://docs.nvidia.com/nim/llama-3-1-nemoguard-8b-contentsafety/1.10.1/llms.txt > - 1.0.0: https://docs.nvidia.com/nim/llama-3-1-nemoguard-8b-contentsafety/1.0.0/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nim/llama-3-1-nemoguard-8b-contentsafety/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nim/llama-3-1-nemoguard-8b-contentsafety/_mcp/server. # OpenAI-compatible chat endpoint POST /v1/chat/completions Content-Type: application/json Reference: https://docs.nvidia.com/nim/llama-3-1-nemoguard-8b-contentsafety/api-reference/create-chat-completion-v-1-chat-completions-post ## Request ### Body (application/json) This endpoint expects a NIMLLMChatCompletionRequest. - `messages` (list of NIMLLMChatCompletionMessage, required) — A list of messages comprising the conversation so far. - `model` (string, required) — The model to use. - `frequency_penalty` (double, optional, nullable, default: 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. - `logit_bias` (map from string to double, optional, nullable) — Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. - `logprobs` (boolean, optional, nullable, default: false) — Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`. - `top_logprobs` (integer, optional, nullable) — An integer specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used. - `max_tokens` (integer, optional, nullable) — The maximum number of tokens that can be generated. - `n` (integer, optional, nullable, default: 1) — How many completions to generate for each prompt. - `presence_penalty` (double, optional, nullable, default: 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. - `response_format` (ResponseFormat, optional, nullable) — An object specifying the format that the model must output. Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. - `seed` (integer, optional, nullable) — Changing the seed will produce a different response with similar characteristics. Fixing the seed will reproduce the same results if all other parameters are also kept constant. - `stop` (NimllmChatCompletionRequestStop, optional, nullable) — Sequences where the API will stop generating further tokens. - `stream` (boolean, optional, nullable, default: false) — If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` - `stream_options` (StreamOptions, optional, nullable) - `temperature` (double, optional, nullable, default: 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. - `top_p` (double, optional, nullable, default: 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. - `tools` (list of ChatCompletionToolsParam, optional, nullable) - `tool_choice` (NimllmChatCompletionRequestToolChoice, optional, nullable, default: none) — Controls which (if any) tool is called by the model. - `parallel_tool_calls` (boolean, optional, nullable, default: true) - `user` (string, optional, nullable) - `min_p` (double, optional, default: 0) - `prompt_logprobs` (integer, optional, nullable) - `add_special_tokens` (boolean, optional, default: false) — If true, special tokens (e.g. BOS) will be added to the prompt on top of what is added by the chat template. For most models, the chat template takes care of adding the special tokens so this should be set to false (as is the default). - `documents` (list of map from string to string, optional, nullable) — A list of dicts representing documents that will be accessible to the model if it is performing RAG (retrieval-augmented generation). If the template does not support RAG, this argument will have no effect. We recommend that each document should be a dict containing "title" and "text" keys. - `chat_template` (string, optional, nullable) — A Jinja template to use for this conversion. As of transformers v4.44, default chat template is no longer allowed, so you must provide a chat template if the tokenizer does not define one. - `chat_template_kwargs` (NimllmChatCompletionRequestChatTemplateKwargs, optional, nullable) — Additional kwargs to pass to the template renderer. Will be accessible by the chat template. - `guided_whitespace_pattern` (string, optional, nullable) — If specified, will override the default whitespace pattern for guided json decoding. - `nvext` (NVExt, optional, nullable) — Extension dictionary for NIM API. ## Response ### 200 Successful Response - `create_chat_completion_v1_chat_completions_post_Response_200` - ChatCompletionResponse: vllm__entrypoints__openai__protocol__ChatCompletionResponse - ChatCompletionStreamResponse: ChatCompletionStreamResponse ## Errors ### 400 Bad Request Error Received an invalid request possibly containing unsupported or out-of-range parameter values. - `message` (string, required) - `type` (string, required) - `code` (integer, required) - `object` (string, optional, default: error) - `param` (string, optional, nullable) ### 404 Not Found Error The requested model does not exist. - `message` (string, required) - `type` (string, required) - `code` (integer, required) - `object` (string, optional, default: error) - `param` (string, optional, nullable) ### 415 Unsupported Media Type Error Unsupported Media Type - `message` (string, required) - `type` (string, required) - `code` (integer, required) - `object` (string, optional, default: error) - `param` (string, optional, nullable) ### 422 Unprocessable Entity Error Validation Error - `detail` (list of ValidationError, optional) ### 500 Internal Server Error Internal Server Error - `message` (string, required) - `type` (string, required) - `code` (integer, required) - `object` (string, optional, default: error) - `param` (string, optional, nullable) ## Types ### NIMLLMChatCompletionMessage - `role` (enum, required) — The role of the message's author. - Allowed values: `assistant`, `user`, `system`, `tool`, `function` - `content` (string, optional, nullable) — The contents of the message. For a reward model, the predicted attributes, i.e. reward scores, will be returned. - `tool_call_id` (string, optional, nullable) — The id of the tool call. - `name` (string, optional, nullable) — The name of the tool called. - `tool_calls` (list of vllm__entrypoints__openai__protocol__ToolCall, optional, nullable) — The tool(s) called by the model. ### ResponseFormat - `type` (enum, required) — Must be one of `text` or `json_object`. - Allowed values: `text`, `json_object` ### NimllmChatCompletionRequestStop Sequences where the API will stop generating further tokens. - string - list of string ### StreamOptions - `include_usage` (boolean, optional, nullable, default: true) - `continuous_usage_stats` (boolean, optional, nullable, default: true) ### ChatCompletionToolsParam - `function` (FunctionDefinition, required) - `type` (enum, optional, default: function) - Allowed values: `function` ### NimllmChatCompletionRequestToolChoice Controls which (if any) tool is called by the model. - enum - Allowed values: `none`, `auto`, `required` - ChatCompletionNamedToolChoiceParam: ChatCompletionNamedToolChoiceParam ### NimllmChatCompletionRequestChatTemplateKwargs Additional kwargs to pass to the template renderer. Will be accessible by the chat template. ### NVExt - `ignore_eos` (boolean, optional, nullable) — Whether to ignore End of Sequence (EOS) tokens. It is advised to set max_tokens when this is set to avoid overly long response times. - `repetition_penalty` (double, optional, nullable, default: 1) — How much to penalize tokens based on how frequently they occur in the text. A value of 1 means no penalty, while values larger than 1 discourage and values smaller encourage. - `top_k` (integer, optional, default: -1) — How many of the top tokens to sample from. Must be -1 or greater than or equal to 1, and cannot be null. If not set, then the default is -1 which disables top_k sampling (greedy). - `guided_choice` (list of string, optional, nullable) — If specified, the output will be exactly one of the choices. - `guided_json` (NvExtGuidedJson, optional, nullable) — If specified, the output will follow the JSON schema. Can be a string, an object, a reference to a BaseModel, or null. - `guided_regex` (string, optional, nullable) — If specified, the output will follow the regex pattern. Can be a string or null. - `guided_grammar` (string, optional, nullable) — If specified, the output will follow the context-free grammar. Can be a string or null. ### vllm__entrypoints__openai__protocol__ChatCompletionResponse - `model` (string, required) - `choices` (list of ChatCompletionResponseChoice, required) - `usage` (UsageInfo, required) - `id` (string, optional) - `object` (enum, optional, default: chat.completion) - Allowed values: `chat.completion` - `created` (integer, optional) - `prompt_logprobs` (list of map from string to Logprob, optional, nullable) ### ChatCompletionStreamResponse - `model` (string, required) - `choices` (list of ChatCompletionResponseStreamChoice, required) - `id` (string, optional) - `object` (enum, optional, default: chat.completion.chunk) - Allowed values: `chat.completion.chunk` - `created` (integer, optional) - `usage` (UsageInfo, optional, nullable) ### ValidationError - `loc` (list of ValidationErrorLocItems, required) - `msg` (string, required) - `type` (string, required) ### vllm__entrypoints__openai__protocol__ToolCall - `function` (FunctionCall, required) - `index` (integer, optional, nullable) - `id` (string, optional) - `type` (enum, optional, default: function) - Allowed values: `function` ### FunctionDefinition - `name` (string, required) - `description` (string, optional, nullable) - `parameters` (FunctionDefinitionParameters, optional, nullable) ### ChatCompletionNamedToolChoiceParam - `function` (ChatCompletionNamedFunction, required) - `type` (enum, optional, default: function) - Allowed values: `function` ### NvExtGuidedJson If specified, the output will follow the JSON schema. Can be a string, an object, a reference to a BaseModel, or null. - string - map from string to any - BaseModel: BaseModel ### ChatCompletionResponseChoice - `index` (integer, required) - `message` (ChatMessage, required) - `logprobs` (ChatCompletionLogProbs, optional, nullable) - `finish_reason` (enum, optional, nullable, default: stop) - Allowed values: `stop`, `length`, `tool_calls` - `stop_reason` (ChatCompletionResponseChoiceStopReason, optional, nullable) ### UsageInfo - `prompt_tokens` (integer, optional, default: 0) - `total_tokens` (integer, optional, default: 0) - `completion_tokens` (integer, optional, nullable, default: 0) ### Logprob - `logprob` (double, required) - `rank` (integer, optional, nullable) - `decoded_token` (string, optional, nullable) ### ChatCompletionResponseStreamChoice - `index` (integer, required) - `delta` (DeltaMessage, required) - `logprobs` (ChatCompletionLogProbs, optional, nullable) - `finish_reason` (enum, optional, nullable) - Allowed values: `stop`, `length`, `tool_calls` - `stop_reason` (ChatCompletionResponseStreamChoiceStopReason, optional, nullable) ### ValidationErrorLocItems - string - integer ### FunctionCall - `name` (string, optional, nullable, default: ) - `arguments` (string, optional, nullable, default: ) ### FunctionDefinitionParameters ### ChatCompletionNamedFunction - `name` (string, required) ### BaseModel ### ChatMessage - `role` (string, required) - `content` (string, optional, nullable) - `tool_calls` (list of vllm__entrypoints__openai__protocol__ToolCall, optional, nullable) ### ChatCompletionLogProbs - `content` (list of ChatCompletionLogProbsContent, optional, nullable) ### ChatCompletionResponseChoiceStopReason - integer - string ### DeltaMessage - `role` (string, optional, nullable) - `content` (string, optional, nullable) - `tool_calls` (list of vllm__entrypoints__openai__protocol__ToolCall, optional, nullable) ### ChatCompletionResponseStreamChoiceStopReason - integer - string ### ChatCompletionLogProbsContent - `token` (string, required) - `logprob` (double, optional, default: -9999) - `bytes` (list of integer, optional, nullable) - `top_logprobs` (list of ChatCompletionLogProb, optional) ### ChatCompletionLogProb - `token` (string, required) - `logprob` (double, optional, default: -9999) - `bytes` (list of integer, optional, nullable) ## Examples **Request** ```json { "messages": [ { "role": "assistant" } ], "model": "string" } ``` **Response** ```json { "choices": [ { "finish_reason": "stop", "index": 1, "logprobs": { "content": [ { "bytes": [ 1 ], "logprob": -9999, "token": "string", "top_logprobs": [ { "bytes": [ 1 ], "logprob": -9999, "token": "string" } ] } ] }, "message": { "content": "string", "role": "string", "tool_calls": [ { "function": { "arguments": "string", "name": "string" }, "id": "string", "index": 1, "type": "function" } ] }, "stop_reason": 1 } ], "created": 1, "id": "string", "model": "string", "object": "chat.completion", "prompt_logprobs": [ {} ], "usage": { "completion_tokens": 1, "prompt_tokens": 0, "total_tokens": 0 } } ``` **SDK Code** ```python import requests url = "https://api.example.com/v1/chat/completions" payload = { "messages": [{ "role": "assistant" }], "model": "string" } headers = {"Content-Type": "application/json"} response = requests.post(url, json=payload, headers=headers) print(response.json()) ``` ```javascript const url = 'https://api.example.com/v1/chat/completions'; const options = { method: 'POST', headers: {'Content-Type': 'application/json'}, body: '{"messages":[{"role":"assistant"}],"model":"string"}' }; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); } ``` ```go package main import ( "fmt" "strings" "net/http" "io" ) func main() { url := "https://api.example.com/v1/chat/completions" payload := strings.NewReader("{\n \"messages\": [\n {\n \"role\": \"assistant\"\n }\n ],\n \"model\": \"string\"\n}") req, _ := http.NewRequest("POST", url, payload) req.Header.Add("Content-Type", "application/json") res, _ := http.DefaultClient.Do(req) defer res.Body.Close() body, _ := io.ReadAll(res.Body) fmt.Println(res) fmt.Println(string(body)) } ``` ```ruby require 'uri' require 'net/http' url = URI("https://api.example.com/v1/chat/completions") http = Net::HTTP.new(url.host, url.port) http.use_ssl = true request = Net::HTTP::Post.new(url) request["Content-Type"] = 'application/json' request.body = "{\n \"messages\": [\n {\n \"role\": \"assistant\"\n }\n ],\n \"model\": \"string\"\n}" response = http.request(request) puts response.read_body ``` ```java import com.mashape.unirest.http.HttpResponse; import com.mashape.unirest.http.Unirest; HttpResponse response = Unirest.post("https://api.example.com/v1/chat/completions") .header("Content-Type", "application/json") .body("{\n \"messages\": [\n {\n \"role\": \"assistant\"\n }\n ],\n \"model\": \"string\"\n}") .asString(); ``` ```php request('POST', 'https://api.example.com/v1/chat/completions', [ 'body' => '{ "messages": [ { "role": "assistant" } ], "model": "string" }', 'headers' => [ 'Content-Type' => 'application/json', ], ]); echo $response->getBody(); ``` ```csharp using RestSharp; var client = new RestClient("https://api.example.com/v1/chat/completions"); var request = new RestRequest(Method.POST); request.AddHeader("Content-Type", "application/json"); request.AddParameter("application/json", "{\n \"messages\": [\n {\n \"role\": \"assistant\"\n }\n ],\n \"model\": \"string\"\n}", ParameterType.RequestBody); IRestResponse response = client.Execute(request); ``` ```swift import Foundation let headers = ["Content-Type": "application/json"] let parameters = [ "messages": [["role": "assistant"]], "model": "string" ] as [String : Any] let postData = JSONSerialization.data(withJSONObject: parameters, options: []) let request = NSMutableURLRequest(url: NSURL(string: "https://api.example.com/v1/chat/completions")! as URL, cachePolicy: .useProtocolCachePolicy, timeoutInterval: 10.0) request.httpMethod = "POST" request.allHTTPHeaderFields = headers request.httpBody = postData as Data let session = URLSession.shared let dataTask = session.dataTask(with: request as URLRequest, completionHandler: { (data, response, error) -> Void in if (error != nil) { print(error as Any) } else { let httpResponse = response as? HTTPURLResponse print(httpResponse) } }) dataTask.resume() ```