# Reverse Proxy HuggingFace TGI endpoint

Generate completions for a HuggingFace TGI endpoint

Endpoint: POST /tgi{name}/v1/chat/completions
Version: 1
Security: 

## Header parameters:

  - `HL-Project-Id` (string)
    The ID or alias for the Project to govern the request processing.
    Example: "internal-search-chatbot"

  - `X-Requester-Id` (string)
    The identifier for the requester to be used if MLDR is enabled

  - `X-LLM-Block-Unsafe` (boolean)
    Whether to block unsafe input and output

  - `X-LLM-Block-Unsafe-Input` (boolean)
    Whether to block unsafe input

  - `X-LLM-Block-Unsafe-Output` (boolean)
    Whether to block unsafe output

  - `X-LLM-Skip-Prompt-Injection-Detection` (boolean)
    Whether to skip prompt injection detection

  - `X-LLM-Block-Prompt-Injection` (boolean)
    Whether to block prompt injection

  - `X-LLM-Prompt-Injection-Scan-Type` (string)
    The type of prompt injection scan to use
    Enum: "quick", "full"

  - `X-LLM-Skip-Input-DOS-Detection` (boolean)
    Whether to skip input denial of service detection

  - `X-LLM-Block-Input-DOS-Detection` (boolean)
    Whether to block input denial of service detection

  - `X-LLM-Input-DOS-Detection-Threshold` (string)
    The threshold for input denial of service detection

  - `X-LLM-Skip-Input-PII-Detection` (boolean)
    Whether to skip input personally identifiable information detection

  - `X-LLM-Skip-Output-PII-Detection` (boolean)
    Whether to skip output personally identifiable information detection

  - `X-LLM-Block-Input-PII` (boolean)
    Whether to block input personally identifiable information detection

  - `X-LLM-Block-Output-PII` (boolean)
    Whether to block output personally identifiable information detection

  - `X-LLM-Redact-Input-PII` (boolean)
    Whether to redact input personally identifiable information

  - `X-LLM-Redact-Output-PII` (boolean)
    Whether to redact output personally identifiable information

  - `X-LLM-Redact-Type` (string)
    The type of redaction to use
    Enum: "entity", "strict"

  - `X-LLM-Entity-Type` (string)
    The type of entity to redact
    Enum: "strict", "all"

  - `X-LLM-Skip-Input-Code-Detection` (boolean)
    Whether to skip input code detection

  - `X-LLM-Skip-Output-Code-Detection` (boolean)
    Whether to skip output code detection

  - `X-LLM-Block-Input-Code-Detection` (boolean)
    Whether to block input code detection

  - `X-LLM-Block-Output-Code-Detection` (boolean)
    Whether to block output code detection

  - `X-LLM-Skip-Guardrail-Detection` (boolean)
    Whether to skip guardrail detection

  - `X-LLM-Block-Guardrail-Detection` (boolean)
    Whether to block guardrail detection

  - `X-LLM-Skip-Input-URL-Detection` (boolean)
    Whether to skip input URL detection

  - `X-LLM-Skip-Output-URL-Detection` (boolean)
    Whether to skip output URL detection

## Path parameters:

  - `name` (string, required)
    The name of the TGI endpoint defined in service settings

## Request fields (application/json):

  - `model` (string)
    The model to use for completions

  - `messages` (array)

  - `messages.role` (string)
    The role of the message

  - `messages.content` (string)
    The content of the message

  - `temperature` (number)
    The temperature to use for completions

  - `max_tokens` (number)
    The maximum number of tokens to generate

  - `top_p` (number)
    The top p value to use for completions

  - `frequency_penalty` (number)
    The frequency penalty to use for completions

  - `presence_penalty` (number)
    The presence penalty to use for completions

## Response 200 fields (application/json):

  - `choices` (array)

  - `choices.finish_reason` (string)
    The reason the completion finished

  - `choices.index` (number)
    The index of the completion

  - `choices.message` (array)

  - `choices.message.role` (string)
    The role of the message

  - `choices.message.content` (string)
    The content of the message

  - `choices.logprobs` (null,string)
    The logprobs of the completion

  - `created` (number)
    The timestamp of the completion

  - `id` (null,string)
    The id of the completion

  - `model` (string)
    The model used for the completion

  - `object` (string)
    The object of the completion

  - `usage` (object)

  - `usage.completion_tokens` (number)
    The number of completion tokens

  - `usage.prompt_tokens` (number)
    The number of prompt tokens

  - `usage.total_tokens` (number)
    The total number of tokens

## Response 502 fields (application/json):

  - `detail` (string)