FriendliAI Serverless.Chat API

openapi: 3.2.0
info:
  title: Friendli Suite API Reference Container.Audio Serverless.Chat API
  description: This is an OpenAPI reference of Friendli Suite API.
  termsOfService: https://friendli.ai/terms-of-service
  contact:
    name: FriendliAI Support Team
    email: support@friendli.ai
  version: 0.1.0
servers:
- url: https://api.friendli.ai
tags:
- name: Serverless.Chat
paths:
  /serverless/v1/chat/completions:
    post:
      tags:
      - Serverless.Chat
      summary: Chat completions
      description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
      operationId: serverlessChatComplete
      security:
      - token: []
      parameters:
      - name: X-Friendli-Team
        in: header
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          description: ID of team to run requests as (optional parameter).
          title: X-Friendli-Team
        description: ID of team to run requests as (optional parameter).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ServerlessChatCompletionBody'
      responses:
        '200':
          description: Successfully generated a chat response.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ServerlessChatCompleteSuccess'
              examples:
                Example:
                  value:
                    id: chatcmpl-4b71d12c86d94e719c7e3984a7bb7941
                    model: zai-org/GLM-5.2
                    object: chat.completion
                    choices:
                    - index: 0
                      message:
                        role: assistant
                        content: Hello there, how may I assist you today?
                      finish_reason: stop
                    usage:
                      prompt_tokens: 9
                      completion_tokens: 11
                      total_tokens: 20
                    created: 1735722153
        '422':
          description: Unprocessable Entity
      x-speakeasy-name-override: complete
      x-speakeasy-usage-example:
        title: Chat completions
        description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
        position: 1
        tags:
        - usage
        - security
        - retries
        - server
      x-mint:
        metadata:
          title: Model APIs Chat Completions
          sidebarTitle: Chat Completions
          og:title: Model APIs Chat Completions
          description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
          og:description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
        href: /openapi/model-apis/chat-completions
        content: 'Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.


          See available models at [this pricing table](/guides/model-apis/pricing#billing-methods).


          To request successfully, it is mandatory to enter a **Personal API Key** (e.g. flp_XXX) value in the **Bearer Token** field.

          Refer to the [authentication section](/openapi/introduction#authentication) on our introduction page to learn how to acquire this variable and [visit here](https://friendli.ai/suite/~/setting/keys) to generate your API Key.


          When streaming mode is used (i.e., `stream` option is set to `true`), the response is in MIME type `text/event-stream`. Otherwise, the content type is `application/json`.

          You can view the schema of the streamed sequence of chunk objects in streaming mode [here](/openapi/model-apis/chat-completions-chunk-object).


          <Tip>You can explore examples on the [Friendli Model APIs](https://friendli.ai/get-started/model-apis) playground and adjust settings with just a few clicks.</Tip>'
  /serverless/v1/chat/completions#stream:
    post:
      tags:
      - Serverless.Chat
      summary: Stream chat completions
      description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
      operationId: serverlessChatStream
      security:
      - token: []
      parameters:
      - name: X-Friendli-Team
        in: header
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          description: ID of team to run requests as (optional parameter).
          title: X-Friendli-Team
        description: ID of team to run requests as (optional parameter).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ServerlessChatCompletionStreamBody'
      responses:
        '200':
          description: Successfully generated a chat response.
          content:
            text/event-stream:
              x-speakeasy-sse-sentinel: '[DONE]'
              examples:
                Example:
                  value: 'data: {"id":"chatcmpl-4b71d12c86d94e719c7e3984a7bb7941","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"role":"assistant","content":"This"},"finish_reason":null,"logprobs":null}],"usage":null,"created":1726294381}


                    data: {"id":"chatcmpl-4b71d12c86d94e719c7e3984a7bb7941","object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":" is"},"finish_reason":null,"logprobs":null}],"usage":null,"created":1726294381}


                    ...


                    data: {"id":"chatcmpl-4b71d12c86d94e719c7e3984a7bb7941","object":"chat.completion.chunk","choices":[{"index":0,"delta":{},"finish_reason":"stop","logprobs":null}],"usage":null,"created":1726294383}


                    data: {"id":"chatcmpl-4b71d12c86d94e719c7e3984a7bb7941","object":"chat.completion.chunk","choices":[],"usage":{"prompt_tokens":8,"completion_tokens":4,"total_tokens":12},"created":1726294402}


                    data: [DONE]

                    '
              schema:
                $ref: '#/components/schemas/ServerlessChatCompletionStreamSuccess'
        '422':
          description: Unprocessable Entity
      x-speakeasy-name-override: stream
      x-speakeasy-usage-example:
        tags:
        - eventstream
      x-mint:
        metadata:
          title: Model APIs Stream Chat Completions
          sidebarTitle: Stream Chat Completions
          og:title: Model APIs Stream Chat Completions
          description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
          og:description: Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.
        content: 'Generate a model response from a list of messages comprising a conversation. Compatible with the OpenAI Chat Completions API, with support for streaming, tool calls, and structured outputs.


          See available models at [this pricing table](/guides/model-apis/pricing#billing-methods).


          To request successfully, it is mandatory to enter a **Personal API Key** (e.g. flp_XXX) value in the **Bearer Token** field.

          Refer to the [authentication section](/openapi/introduction#authentication) on our introduction page to learn how to acquire this variable and [visit here](https://friendli.ai/suite/~/setting/keys) to generate your API Key.


          When streaming mode is used (i.e., `stream` option is set to `true`), the response is in MIME type `text/event-stream`. Otherwise, the content type is `application/json`.

          You can view the schema of the streamed sequence of chunk objects in streaming mode [here](/openapi/model-apis/chat-completions-chunk-object).


          <Tip>You can explore examples on the [Friendli Model APIs](https://friendli.ai/get-started/model-apis) playground and adjust settings with just a few clicks.</Tip>'
components:
  schemas:
    StreamedChatChoice:
      properties:
        index:
          type: integer
          title: Index
          description: The index of the choice in the list of generated choices.
          examples:
          - 0
        logprobs:
          anyOf:
          - $ref: '#/components/schemas/ChatLogprobs'
          - type: 'null'
        delta:
          $ref: '#/components/schemas/StreamedChatChoiceDelta'
        finish_reason:
          anyOf:
          - type: string
            enum:
            - stop
            - length
            - tool_calls
            - 'null'
          - type: 'null'
          title: Finish Reason
          description: 'Termination condition of the generation. `stop` means the API returned the full chat completions generated by the model without running into any limits.

            `length` means the generation exceeded `max_tokens` or the conversation exceeded the max context length.

            `tool_calls` means the API has generated tool calls.'
      type: object
      required:
      - index
      - delta
      title: StreamedChatChoice
    ChatCompleteBodyToolChoice:
      properties:
        type:
          type: string
          const: function
          title: Type
          description: The type of the tool. Currently, only `function` is supported.
        function:
          $ref: '#/components/schemas/ChatCompleteBodyToolChoiceFunction'
      type: object
      required:
      - type
      - function
      title: ChatCompleteBodyToolChoice
    PromptTokensDetails:
      properties:
        cached_tokens:
          anyOf:
          - type: integer
          - type: 'null'
          title: Cached Tokens
          description: Cached tokens present in the prompt.
      type: object
      title: PromptTokensDetails
    AssistantMessageToolCall:
      properties:
        id:
          type: string
          title: Id
          description: The ID of tool call.
        type:
          type: string
          const: function
          title: Type
          description: The type of tool call.
        function:
          $ref: '#/components/schemas/AssistantMessageToolCallFunction'
          description: The function specification
      type: object
      required:
      - id
      - type
      - function
      title: AssistantMessageToolCall
    AssistantMessage:
      properties:
        role:
          type: string
          const: assistant
          title: Role
          description: The role of the messages author.
        content:
          anyOf:
          - type: string
          - type: 'null'
          title: Content
          description: The content of assistant message. Required unless `tool_calls` is specified.
        reasoning_content:
          anyOf:
          - type: string
          - type: 'null'
          title: Reasoning Content
          description: The intermediate reasoning content of assistant message.
        reasoning:
          anyOf:
          - type: string
          - type: 'null'
          title: Reasoning
          description: The intermediate reasoning content of assistant message. This field is a compatible option for the 'reasoning_content' field.
        name:
          anyOf:
          - type: string
          - type: 'null'
          title: Name
          description: The name for the participant to distinguish between participants with the same role.
        tool_calls:
          anyOf:
          - items:
              $ref: '#/components/schemas/AssistantMessageToolCall'
            type: array
          - type: 'null'
          title: Tool Calls
      type: object
      required:
      - role
      title: AssistantMessage
    ResponseFormat:
      oneOf:
      - $ref: '#/components/schemas/ResponseFormatJsonSchema'
        title: Json Schema
      - $ref: '#/components/schemas/ResponseFormatJsonObject'
        title: Json Object
      - $ref: '#/components/schemas/ResponseFormatRegex'
        title: Regex
      - $ref: '#/components/schemas/ResponseFormatText'
        title: Text
      description: 'The enforced format of the model''s output.


        Note that the content of the output message may be truncated if it exceeds the `max_tokens`. You can check this by verifying that the `finish_reason` of the output message is `length`.


        For more detailed information, please refer [here](https://friendli.ai/docs/guides/structured-outputs).


        ***Important***

        You must explicitly instruct the model to produce the desired output format using a system prompt or user message (e.g., `You are an API generating a valid JSON as output.`).

        Otherwise, the model may result in an unending stream of whitespace or other characters.


        **When `response_format` is specified, `min_tokens` field is unsupported.**'
      discriminator:
        propertyName: type
        mapping:
          json_object: '#/components/schemas/ResponseFormatJsonObject'
          json_schema: '#/components/schemas/ResponseFormatJsonSchema'
          regex: '#/components/schemas/ResponseFormatRegex'
          text: '#/components/schemas/ResponseFormatText'
    ChatLogprobsContentTopLogprob:
      properties:
        token:
          type: string
          title: Token
          description: The token.
        logprob:
          type: number
          title: Logprob
          description: The log probability of this token.
        bytes:
          anyOf:
          - items:
              type: integer
            type: array
          - type: 'null'
          title: Bytes
          description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
      type: object
      required:
      - token
      - logprob
      title: ChatLogprobsContentTopLogprob
    ResponseFormatJsonObject:
      properties:
        type:
          type: string
          const: json_object
          title: Type
          description: 'The type of the response format: `json_object`'
      type: object
      required:
      - type
      title: ResponseFormatJsonObject
    FunctionResult:
      properties:
        arguments:
          type: string
          title: Arguments
          description: 'The arguments for calling the function, generated by the model in JSON format.

            Ensure to validate these arguments in your code before invoking the function since the model may not always produce valid JSON.'
        name:
          type: string
          title: Name
          description: The name of the function to call.
      type: object
      required:
      - arguments
      - name
      title: FunctionResult
    ServerlessChatCompleteSuccess:
      $ref: '#/components/schemas/ChatResult'
      title: ServerlessChatCompleteSuccess
    ChatLogprobsContent:
      properties:
        token:
          type: string
          title: Token
          description: The token.
        logprob:
          type: number
          title: Logprob
          description: The log probability of this token.
        bytes:
          anyOf:
          - items:
              type: integer
            type: array
          - type: 'null'
          title: Bytes
          description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
        top_logprobs:
          items:
            $ref: '#/components/schemas/ChatLogprobsContentTopLogprob'
          type: array
          title: Top Logprobs
          description: List of the most likely tokens and their log probability, at this token position.
      type: object
      required:
      - token
      - logprob
      - top_logprobs
      title: ChatLogprobsContent
    UserMessageContentMultiModal:
      oneOf:
      - $ref: '#/components/schemas/TextContent'
        title: Text
      - $ref: '#/components/schemas/AudioContent'
        title: Audio
      - $ref: '#/components/schemas/ImageContent'
        title: Image
      - $ref: '#/components/schemas/VideoContent'
        title: Video
      discriminator:
        propertyName: type
        mapping:
          audio_url: '#/components/schemas/AudioContent'
          image_url: '#/components/schemas/ImageContent'
          text: '#/components/schemas/TextContent'
          video_url: '#/components/schemas/VideoContent'
    VideoContent:
      properties:
        type:
          type: string
          const: video_url
          title: Type
          description: The type of the message content.
        video_url:
          $ref: '#/components/schemas/VideoData'
          description: The video URL data.
      type: object
      required:
      - type
      - video_url
      title: VideoContent
    ChatUsage:
      properties:
        prompt_tokens:
          type: integer
          title: Prompt Tokens
          description: Number of tokens in the prompt.
          examples:
          - 5
        completion_tokens:
          type: integer
          title: Completion Tokens
          description: Number of tokens in the generated chat completions.
          examples:
          - 7
        total_tokens:
          type: integer
          title: Total Tokens
          description: Total number of tokens used in the request (`prompt_tokens` + `completion_tokens`).
          examples:
          - 12
        prompt_tokens_details:
          anyOf:
          - $ref: '#/components/schemas/PromptTokensDetails'
          - type: 'null'
          description: Breakdown of tokens used in the prompt.
      type: object
      required:
      - prompt_tokens
      - completion_tokens
      - total_tokens
      title: ChatUsage
    AudioContent:
      properties:
        type:
          type: string
          const: audio_url
          title: Type
          description: The type of the message content.
        audio_url:
          $ref: '#/components/schemas/AudioData'
          description: The audio URL data.
      type: object
      required:
      - type
      - audio_url
      title: AudioContent
    TextContent:
      properties:
        type:
          type: string
          const: text
          title: Type
          description: The type of the message content.
        text:
          type: string
          title: Text
          description: The text content of the message.
      type: object
      required:
      - type
      - text
      title: TextContent
    ToolCallResult:
      properties:
        type:
          type: string
          const: function
          title: Type
          description: The type of the tool.
        id:
          type: string
          title: Id
          description: The ID of the tool call.
        function:
          $ref: '#/components/schemas/FunctionResult'
      type: object
      required:
      - type
      - id
      - function
      title: ToolCallResult
    AssistantMessageToolCallFunction:
      properties:
        name:
          type: string
          title: Name
          description: The name of function
        arguments:
          type: string
          title: Arguments
          description: The arguments of function in JSON schema format to call the function.
      type: object
      required:
      - name
      - arguments
      title: AssistantMessageToolCallFunction
    ToolMessage:
      properties:
        role:
          type: string
          const: tool
          title: Role
          description: The role of the messages author.
        content:
          type: string
          title: Content
          description: The content of tool message that contains the result of tool calling.
        tool_call_id:
          type: string
          title: Tool Call Id
          description: The ID of tool call corresponding to this message.
        name:
          anyOf:
          - type: string
          - type: 'null'
          title: Name
          description: An optional name of the tool call corresponding to this message.
      type: object
      required:
      - role
      - content
      - tool_call_id
      title: ToolMessage
    ServerlessChatCompletionStreamSuccess:
      $ref: '#/components/schemas/StreamedChatResult'
      title: ServerlessChatCompletionStreamSuccess
    StreamedToolCallResult:
      properties:
        type:
          type: string
          const: function
          title: Type
          description: The type of the tool.
        id:
          anyOf:
          - type: string
          - type: 'null'
          title: Id
          description: The ID of the tool call.
        index:
          type: integer
          title: Index
          description: The index of the tool call being generated.
        function:
          $ref: '#/components/schemas/StreamedFunctionResult'
      type: object
      required:
      - type
      - index
      - function
      title: StreamedToolCallResult
    ServerlessChatCompletionBody:
      properties:
        model:
          type: string
          title: Model
          description: Code of the model to use. See [available model list](https://friendli.ai/docs/guides/model-apis/pricing#billing-methods).
          examples:
          - zai-org/GLM-5.2
        messages:
          items:
            $ref: '#/components/schemas/Message'
          type: array
          title: Messages
          description: A list of messages comprising the conversation so far.
          examples:
          - - content: You are a helpful assistant.
              role: system
            - content: Hello!
              role: user
        chat_template_kwargs:
          anyOf:
          - additionalProperties: true
            type: object
          - type: 'null'
          title: Chat Template Kwargs
          description: Additional keyword arguments supplied to the template renderer. These parameters will be available for use within the chat template.
        eos_token:
          anyOf:
          - items:
              type: integer
            type: array
          - type: 'null'
          title: Eos Token
          description: A list of endpoint sentence tokens.
        frequency_penalty:
          anyOf:
          - type: number
          - type: 'null'
          title: Frequency Penalty
          description: Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled, taking into account their frequency in the preceding text. This penalization diminishes the model's tendency to reproduce identical lines verbatim.
        logit_bias:
          anyOf:
          - additionalProperties: true
            type: object
          - type: 'null'
          title: Logit Bias
          description: Accepts a JSON object that maps tokens to an associated bias value. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model.
        logprobs:
          anyOf:
          - type: boolean
          - type: 'null'
          title: Logprobs
          description: Whether to return log probabilities of the output tokens or not.
        max_tokens:
          anyOf:
          - type: integer
          - type: 'null'
          title: Max Tokens
          description: The maximum number of tokens to generate. For decoder-only models like GPT, the length of your input tokens plus `max_tokens` should not exceed the model's maximum length (e.g., 2048 for OpenAI GPT-3). For encoder-decoder models like T5 or BlenderBot, `max_tokens` should not exceed the model's maximum output length. This is similar to Hugging Face's [`max_new_tokens`](https://huggingface.co/docs/transformers/v4.26.0/en/main_classes/text_generation#transformers.GenerationConfig.max_new_tokens) argument.
        min_p:
          anyOf:
          - type: number
          - type: 'null'
          title: Min P
          description: A scaling factor used to determine the minimum token probability threshold. This threshold is calculated as `min_p` multiplied by the probability of the most likely token. Tokens with probabilities below this scaled threshold are excluded from sampling. Values range from 0.0 (inclusive) to 1.0 (inclusive). Higher values result in stricter filtering, while lower values allow for greater diversity. The default value of 0.0 disables filtering, allowing all tokens to be considered for sampling.
        n:
          anyOf:
          - type: integer
          - type: 'null'
          title: N
          description: The number of independently generated results for the prompt. Defaults to 1. This is similar to Hugging Face's [`num_return_sequences`](https://huggingface.co/docs/transformers/v4.26.0/en/main_classes/text_generation#transformers.GenerationConfig.num_return_sequences) argument.
        parallel_tool_calls:
          anyOf:
          - type: boolean
          - type: 'null'
          title: Parallel Tool Calls
          description: Whether to enable parallel function calling.
        presence_penalty:
          anyOf:
          - type: number
          - type: 'null'
          title: Presence Penalty
          description: Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled at least once in the existing text.
        repetition_penalty:
          anyOf:
          - type: number
          - type: 'null'
          title: Repetition Penalty
          description: Penalizes tokens that have already appeared in the generated result (plus the input tokens for decoder-only models). Should be positive value (1.0 means no penalty). See [keskar et al., 2019](https://arxiv.org/abs/1909.05858) for more details. This is similar to Hugging Face's [`repetition_penalty`](https://huggingface.co/docs/transformers/v4.26.0/en/main_classes/text_generation#transformers.generationconfig.repetition_penalty) argument.
        reasoning_effort:
          anyOf:
          - type: string
            enum:
            - minimal
            - low
            - medium
            - high
            - xhigh
            - max
            - ultracode
          - type: 'null'
          title: Reasoning Effort
          description: Sets how much reasoning the model does before answering. Higher values give more thorough responses but take longer. This affects reasoning models only, and the available options depend on the model.
        reasoning_budget:
          anyOf:
          - type: integer
          - type: 'null'
          title: Reasoning Budget
          description: Specifies a positive integer that defines a limit on the number of tokens used for internal reasoning tokens. This parameter is only effective for reasoning models.
        seed:
          anyOf:
          - items:
              type: integer
            type: array
          - type: integer
          - type: 'null'
          title: Seed
          description: Seed to control random procedure. If nothing is given, random seed is used for sampling, and return the seed along with the generated result. When using the `n` argument, you can pass a list of seed values to control all of the independent generations.
        stop:
          anyOf:
          - items:
              type: string
            type: array
          - type: 'null'
          title: Stop
          description: When one of the stop phrases appears in the generation result, the API will stop generation. The stop phrases are excluded from the result. Defaults to empty list.
        stream:
          anyOf:
          - type: boolean
          - type: 'null'
          title: Stream
          description: Whether to stream the generation result. When set to `true`, each token is sent as [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#event_stream_format) once generated.
          default: false
        stream_options:
          anyOf:
          - $ref: '#/components/schemas/StreamOptions'
          - type: 'null'
          description: 'Options related to stream.

            It can only be used when `stream: true`.'
        parse_reasoning:
          anyOf:
          - type: boolean
          - type: 'null'
          title: Parse Reasoning
          description: 'Parses model reasoning into `reasoning_content` while keeping the answer in `content`. Default value may vary between endpoints.


            For more detailed information, please refer [here](https://friendli.ai/docs/guides/reasoning#reasoning-parsing-with-friendli).'
        include_reasoning:
          anyOf:
          - type: boolean
          - type: 'null'
          title: Include Reasoning
          description: 'When `parse_reasoning=true`, include parsed reasoning (`reasoning_content`). Defaults to true.


            For more detailed information, please refer [here](https://friendli.ai/docs/guides/reasoning#reasoning-parsing-with-friendli).'
        temperature:
          anyOf:
          - type: number
          - type: 'null'
          title: Temperature
          description: Sampling temperature. Smaller temperature makes the generation result closer to greedy, argmax (i.e., `top_k = 1`) sampling. Defaults to 1.0. This is similar to Hugging Face's [`temperature`](https://huggingface.co/docs/transformers/v4.26.0/en/main_classes/text_generation#transformers.generationconfig.temperature) argument.
        tool_choice:
          anyOf:
          - $ref: '#/components/schemas/ChatCompleteBodyToolChoice'
          - type: string
          title: Tool Choice
          description: 'Determines the tool calling behavior of the model.

            When set to `none`, the model will bypass tool execution and generate a response directly.

            In `auto` mode (the default), the model dynamically decides whether to call a tool or respond with a message.

            Alternatively, setting `required` ensures that the model invokes at least one tool before responding to the user.

            You can also specify a particular tool by `{"type": "function", "function": {"name": "my_function"}}`.

            '
        top_k:
          anyOf:
          - type: integer
          - type: 'null'
          title: Top K
          description: Limits sampling to the top k tokens with the highest probabilities. Values range from 0 (no filtering) to the model's vocabulary size (inclusive). The default value of 0 applies no filtering, allowing all tokens.
        top_logprobs:
          anyOf:
          - type: integer
          - type: 'null'
          title: Top Logprobs
          description: 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.
        top_p:
          anyOf:
          - type: number
          - type: 'null'
          title: Top P
          description: Keeps only the smallest set of tokens whose cumulative probabilities reach `top_p` or higher. Values range from 0.0 (exclusive) to 1.0 (inclusive). The default value of 1.0 includes all tokens, allowing maximum diversity.
        xtc_threshold:
          anyOf:
          - type: number
          - type: 'null'
          title: Xtc Threshold
          description: A probability threshold used to identify “top choice” tokens for exclusion in XTC (Exclude Top Choices) sampling. Tokens with probabilities at or above this threshold are considered viable candidates, and all but the least likely viable token are excluded from sampling. This option reduces the dominance of highly probable tokens while preserving some diversity by keeping the l

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