> ## Documentation Index > Fetch the complete documentation index at: https://docs.fireworks.ai/llms.txt > Use this file to discover all available pages before exploring further. # Create Completion > Create a completion for the provided prompt and parameters. For RL / agent rollouts, Fireworks inference exposes additional rollout-specific features: [`x-session-affinity` and `x-multi-turn-session-id`](https://docs.fireworks.ai/guides/rollout-inference#session-affinity) for multi-turn trajectories, and [MoE Router Replay (R3)](https://docs.fireworks.ai/guides/rollout-inference#moe-router-replay) for MoE expert tracing during rollouts. ## OpenAPI ````yaml post /v1/completions openapi: 3.1.0 info: title: Gateway REST API version: 4.259.0 servers: [] security: [] tags: - name: gateway.openapi_Gateway x-displayName: Gateway - name: gateway-extra.openapi_Gateway x-displayName: Gateway - name: responses.openapi_other x-displayName: other - name: text-completion.openapi_other x-displayName: other - name: anthropic-messages.openapi_other x-displayName: other paths: /v1/completions: servers: - url: https://api.fireworks.ai/inference post: tags: - text-completion.openapi_other summary: Create Completion description: >- Create a completion for the provided prompt and parameters. For RL / agent rollouts, Fireworks inference exposes additional rollout-specific features: [`x-session-affinity` and `x-multi-turn-session-id`](https://docs.fireworks.ai/guides/rollout-inference#session-affinity) for multi-turn trajectories, and [MoE Router Replay (R3)](https://docs.fireworks.ai/guides/rollout-inference#moe-router-replay) for MoE expert tracing during rollouts. operationId: create_completion_v1_completions_post requestBody: content: application/json: schema: $ref: '#/components/schemas/CompletionRequest' required: true responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/CompletionResponse' text/event-stream: schema: $ref: '#/components/schemas/CompletionStreamResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - BearerAuth: [] components: schemas: CompletionRequest: properties: model: type: string title: Model description: |- The name of the model to use. Example: `"accounts/fireworks/models/kimi-k2-instruct-0905"` user: anyOf: - type: string - type: 'null' title: User description: >- A unique identifier representing your end-user, which can help monitor and detect abuse. prompt_cache_key: anyOf: - type: string - type: 'null' title: Prompt Cache Key description: >- A key used for prompt caching session affinity. Requests with the same prompt_cache_key are routed to the same backend to maximize KV cache hit rates. This is the preferred field for session affinity (takes priority over the 'user' field). prompt_cache_isolation_key: anyOf: - type: string - type: 'null' title: Prompt Cache Isolation Key description: Isolation key for prompt caching to separate cache entries. raw_output: anyOf: - type: boolean - type: 'null' title: Raw Output description: Return raw output from the model. default: false perf_metrics_in_response: anyOf: - type: boolean - type: 'null' title: Perf Metrics In Response description: >- Whether to include performance metrics in the response body. **Non-streaming requests:** Performance metrics are always included in response headers (e.g., `fireworks-prompt-tokens`, `fireworks-server-time-to-first-token`). Setting this to `true` additionally includes the same metrics in the response body under the `perf_metrics` field. **Streaming requests:** Performance metrics are only included in the response body under the `perf_metrics` field in the final chunk (when `finish_reason` is set). This is because headers may not be accessible during streaming. The response body `perf_metrics` field contains the following metrics: **Basic Metrics (all deployments):** - `prompt-tokens`: Number of tokens in the prompt - `cached-prompt-tokens`: Number of cached prompt tokens - `server-time-to-first-token`: Time from request start to first token (in seconds) - `server-processing-time`: Total processing time (in seconds, only for completed requests) **Predicted Outputs Metrics:** - `speculation-prompt-tokens`: Number of speculative prompt tokens - `speculation-prompt-matched-tokens`: Number of matched speculative prompt tokens (for completed requests) **Dedicated Deployment Only Metrics:** - `speculation-generated-tokens`: Number of speculative generated tokens (for completed requests) - `speculation-acceptance`: Speculation acceptance rates by position - `backend-host`: Hostname of the backend server - `num-concurrent-requests`: Number of concurrent requests - `deployment`: Deployment name - `tokenizer-queue-duration`: Time spent in tokenizer queue - `tokenizer-duration`: Time spent in tokenizer - `prefill-queue-duration`: Time spent in prefill queue - `prefill-duration`: Time spent in prefill - `generation-queue-duration`: Time spent in generation queue - `generation-duration`: Time spent in generation default: false stream: anyOf: - type: boolean - type: 'null' title: Stream description: >- Whether to stream back partial progress. If set, 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]` message. default: false 'n': type: integer title: 'N' description: >- How many completions to generate for each prompt. **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`. Required range: `1 <= x <= 128` Example: `1` default: 1 service_tier: type: string enum: - auto - default - flex - priority title: Service Tier description: >- The service tier to use for the request. Specifies the processing type used for serving the request. Only "priority" is supported, while all other values will be treated as "default" tier. default: default stop: anyOf: - type: string - type: array items: type: string - type: 'null' title: Stop description: >- Up to 4 sequences where the API will stop generating further tokens. The returned text will NOT contain the stop sequence. max_tokens: anyOf: - type: integer - type: 'null' title: Max Tokens description: >- The maximum number of tokens to generate in the completion. If the token count of your prompt plus max_tokens exceeds the model's context length, the behavior depends on context_length_exceeded_behavior. By default, max_tokens will be lowered to fit in the context window instead of returning an error. max_completion_tokens: anyOf: - type: integer - type: 'null' title: Max Completion Tokens description: Alias for max_tokens. Cannot be specified together with max_tokens. temperature: anyOf: - type: number - type: 'null' title: Temperature description: >- 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. We generally recommend altering this or top_p but not both. Required range: `0 <= x <= 2` Example: `1` top_k: anyOf: - type: integer - type: 'null' title: Top K description: >- Top-k sampling is another sampling method where the k most probable next tokens are filtered and the probability mass is redistributed among only those k next tokens. The value of k controls the number of candidates for the next token at each step during text generation. Must be between 0 and 100. Required range: `0 <= x <= 100` Example: `50` top_p: anyOf: - type: number - type: 'null' title: Top P description: >- 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. Required range: `0 <= x <= 1` Example: `1` min_p: anyOf: - type: number - type: 'null' title: Min P description: >- Minimum probability threshold for token selection. Only tokens with probability >= min_p are considered for selection. This is an alternative to `top_p` and `top_k` sampling. Required range: `0 <= x <= 1` typical_p: anyOf: - type: number - type: 'null' title: Typical P description: >- Typical-p sampling is an alternative to nucleus sampling. It considers the most typical tokens whose cumulative probability is at most typical_p. Required range: `0 <= x <= 1` frequency_penalty: anyOf: - type: number - type: 'null' title: Frequency Penalty description: >- 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. Reasonable value is around 0.1 to 1 if the aim is to just reduce repetitive samples somewhat. If the aim is to strongly suppress repetition, then one can increase the coefficients up to 2, but this can noticeably degrade the quality of samples. Negative values can be used to increase the likelihood of repetition. See also `presence_penalty` for penalizing tokens that have at least one appearance at a fixed rate. OpenAI compatible (follows OpenAI's conventions for handling token frequency and repetition penalties). Required range: `-2 <= x <= 2` presence_penalty: anyOf: - type: number - type: 'null' title: Presence Penalty description: >- 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. Reasonable value is around 0.1 to 1 if the aim is to just reduce repetitive samples somewhat. If the aim is to strongly suppress repetition, then one can increase the coefficients up to 2, but this can noticeably degrade the quality of samples. Negative values can be used to increase the likelihood of repetition. See also `frequency_penalty` for penalizing tokens at an increasing rate depending on how often they appear. OpenAI compatible (follows OpenAI's conventions for handling token frequency and repetition penalties). Required range: `-2 <= x <= 2` repetition_penalty: anyOf: - type: number - type: 'null' title: Repetition Penalty description: >- Applies a penalty to repeated tokens to discourage or encourage repetition. A value of `1.0` means no penalty, allowing free repetition. Values above `1.0` penalize repetition, reducing the likelihood of repeating tokens. Values between `0.0` and `1.0` reward repetition, increasing the chance of repeated tokens. For a good balance, a value of `1.2` is often recommended. Note that the penalty is applied to both the generated output and the prompt in decoder-only models. Required range: `0 <= x <= 2` mirostat_target: anyOf: - type: number - type: 'null' title: Mirostat Target description: >- Defines the target perplexity for the Mirostat algorithm. Perplexity measures the unpredictability of the generated text, with higher values encouraging more diverse and creative outputs, while lower values prioritize predictability and coherence. The algorithm dynamically adjusts the token selection to maintain this target during text generation. If not specified, Mirostat sampling is disabled. mirostat_lr: anyOf: - type: number - type: 'null' title: Mirostat Lr description: >- Specifies the learning rate for the Mirostat sampling algorithm, which controls how quickly the model adjusts its token distribution to maintain the target perplexity. A smaller value slows down the adjustments, leading to more stable but gradual shifts, while higher values speed up corrections at the cost of potential instability. seed: anyOf: - type: integer - type: 'null' title: Seed description: Random seed for deterministic sampling. logprobs: anyOf: - type: integer - type: boolean - type: 'null' title: Logprobs description: >- Include log probabilities in the response. This accepts either a boolean or an integer: If set to `true`, log probabilities are included and the number of alternatives can be controlled via `top_logprobs` (OpenAI-compatible behavior). If set to an integer N (0-5), include log probabilities for up to N most likely tokens per position in the legacy format. The API will always return the logprob of the sampled token, so there may be up to `logprobs+1` elements in the response when an integer is used. The maximum value for the integer form is 5. top_logprobs: anyOf: - type: integer - type: 'null' title: Top Logprobs description: >- An integer between 0 and 5 specifying the number of most likely tokens to return at each token position, each with an associated log probability. The minimum value is 0 and the maximum value is 5. When `logprobs` is set, `top_logprobs` can be used to modify how many top log probabilities are returned. If `top_logprobs` is not set, the API will return up to `logprobs` tokens per position. Required range: `0 <= x <= 5` echo: anyOf: - type: boolean - type: 'null' title: Echo description: Echo back the prompt in addition to the completion. default: false echo_last: anyOf: - type: integer - type: 'null' title: Echo Last description: >- Echo back the last N tokens of the prompt in addition to the completion. This is useful for obtaining logprobs of the prompt suffix but without transferring too much data. Passing `echo_last=len(prompt)` is the same as `echo=True` ignore_eos: type: boolean title: Ignore Eos description: >- This setting controls whether the model should ignore the End of Sequence (EOS) token. When set to `True`, the model will continue generating tokens even after the EOS token is produced. By default, it stops when the EOS token is reached. default: false context_length_exceeded_behavior: type: string enum: - error - truncate title: Context Length Exceeded Behavior description: >- What to do if the token count of prompt plus `max_tokens` exceeds the model's context window. Passing `truncate` limits the `max_tokens` to at most `context_window_length - prompt_length`. This is the default. Passing `error` would trigger a request error. The default of `'truncate'` is selected as it allows to ask for high `max_tokens` value while respecting the context window length without having to do client-side prompt tokenization. Note, that it differs from OpenAI's behavior that matches that of `error`. default: truncate response_format: anyOf: - $ref: '#/components/schemas/ResponseFormat' - type: 'null' description: >- Allows to force the model to produce specific output format. Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. If `"type"` is `"json_schema"`, a JSON schema must be provided. E.g., `response_format = {"type": "json_schema", "json_schema": }`. Important: when using JSON mode, it's crucial to also instruct the model to produce JSON via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length. In this case the return value might not be a valid JSON. logit_bias: anyOf: - additionalProperties: type: number type: object - type: 'null' title: Logit Bias description: >- 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. speculation: anyOf: - type: string - items: type: integer type: array - type: 'null' title: Speculation description: Speculative decoding prompt or token IDs to speed up generation. prediction: anyOf: - $ref: '#/components/schemas/PredictedOutput' - type: string - type: 'null' title: Prediction description: >- OpenAI-compatible predicted output for speculative decoding. Can be a PredictedOutput object or a simple string. Automatically transformed to speculation. metadata: anyOf: - type: object additionalProperties: type: string - type: 'null' title: Metadata description: >- Additional metadata to store with the request for tracing/distillation. reasoning_effort: anyOf: - type: string enum: - low - medium - high - xhigh - max - none - type: integer - type: boolean - type: 'null' title: Reasoning Effort description: >- Controls reasoning behavior for supported models. When enabled, the model's reasoning appears in the `reasoning_content` field of the response, separate from the final answer in `content`. **Accepted values:** - **String** (OpenAI-compatible): `'low'`, `'medium'`, `'high'`, or `'max'` to enable reasoning with varying effort levels; `'none'` to disable reasoning. - **Boolean** (Fireworks extension): `true` to enable reasoning, `false` to disable it. - **Integer** (Fireworks extension): A positive integer to set a hard token limit on reasoning output. Integer values enable the model's normal medium-style thinking behavior and force the model to end its thinking phase after at most that many generated thinking tokens. **Important:** Boolean values are normalized internally: `true` becomes `'medium'`, and `false` becomes `'none'`. This normalization happens before model-specific validation, so if a model doesn't support `'none'`, passing `false` will produce an error referencing `'none'`. **Model-specific behavior:** - **Qwen3 (e.g., Qwen3-8B)**: Grammar-based reasoning. Default reasoning on. Use `'none'` or `false` to disable. Supports integer token limits to cap reasoning output. `'low'`, `'medium'`, and `'high'` keep their model-specific behavior and are not hard budgets. - **MiniMax M2**: Reasoning is required (always on). Defaults to `'medium'` when omitted. Accepts only string `reasoning_effort`: `'low'`, `'medium'`, or `'high'`. `'none'` and boolean values are rejected. - **DeepSeek V3.1**: Binary on/off reasoning. Default reasoning off (matches chat template). Use `true`, `'low'`, `'medium'`, or `'high'` to enable; `'none'` or `false` to disable. - **DeepSeek V3.2**: Binary on/off reasoning. Default reasoning on. Use `'none'` or `false` to disable; effort levels and integers have no additional effect. - **DeepSeek V4**: Accepts `'none'`, `'low'`, `'medium'`, `'high'`, `'xhigh'`, and `'max'`. Default reasoning on (`'high'`). `'xhigh'` is silently promoted to `'max'`. `'max'` prepends a thorough-reasoning preamble; `'high'` enables thinking. `'low'` and `'medium'` are silently promoted to `'high'`. `'none'` or `false` disables thinking. - **GLM 4.5, GLM 4.5 Air, GLM 4.6, GLM 4.7**: Binary on/off reasoning. Default reasoning on. Use `'none'` or `false` to disable; effort levels and integers have no additional effect. - **Harmony (OpenAI GPT-OSS 120B, GPT-OSS 20B)**: Accepts only `'low'`, `'medium'`, or `'high'`. Does not support `'none'`, `false`, or integer values — using these will return an error (e.g., "Invalid reasoning effort: none"). When omitted, defaults to `'medium'`. Lower effort produces faster responses with shorter reasoning. reasoning_history: anyOf: - type: string enum: - disabled - interleaved - preserved - type: 'null' title: Reasoning History description: >- Controls how historical assistant reasoning content is included in the prompt for multi-turn conversations. **Accepted values:** - `null`: Use model/template default behavior (for **GLM-4.7**, the model/template default is `'interleaved'`, i.e. historical reasoning is cleared by default) - `'disabled'`: Strip `reasoning_content` from all messages before prompt construction - `'interleaved'`: Strip `reasoning_content` from messages up to (and including) the last user message - `'preserved'`: Preserve historical `reasoning_content` across the conversation **Model support:** | Model | Default | Supported values | | --- | --- | --- | | Kimi K2.6 | `'interleaved'` | `'disabled'`, `'interleaved'`, `'preserved'` | | Kimi K2 Instruct | `'preserved'` | `'disabled'`, `'interleaved'`, `'preserved'` | | MiniMax M2 | `'interleaved'` | `'disabled'`, `'interleaved'` | | GLM-4.7 | `'interleaved'` | `'disabled'`, `'interleaved'`, `'preserved'` | | GLM-4.6 | `'interleaved'` | `'disabled'`, `'interleaved'` | | Qwen 3.6 | `'preserved'` | `'disabled'`, `'preserved'` | | DeepSeek V4 | `'interleaved'` | `'interleaved'` | For other models, refer to the model provider's documentation. **Note:** This parameter controls prompt formatting only. To disable reasoning computation entirely, use `reasoning_effort='none'`. thinking: anyOf: - $ref: '#/components/schemas/ThinkingConfigEnabled' - $ref: '#/components/schemas/ThinkingConfigDisabled' - type: 'null' title: Thinking description: >- Configuration for enabling extended thinking (Anthropic-compatible format). This is an alternative to `reasoning_effort` for controlling reasoning behavior. **Format:** - `{"type": "enabled"}` - Enable thinking (equivalent to `reasoning_effort: true`) - `{"type": "enabled", "budget_tokens": }` - Enable thinking with a token budget (equivalent to `reasoning_effort: `). Must be >= 1024. - `{"type": "enabled", "keep": "all"}` - Enable thinking and preserve all historical reasoning content in the prompt (equivalent to `reasoning_history: "preserved"`). - `{"type": "disabled"}` - Disable thinking (equivalent to `reasoning_effort: "none"`) **Note:** Cannot be specified together with `reasoning_effort`. If both are provided, a validation error will be raised. return_token_ids: anyOf: - type: boolean - type: 'null' title: Return Token Ids description: Return token IDs alongside text to avoid retokenization drift. default: false prompt: anyOf: - type: string - type: array items: type: string - items: type: integer type: array - items: items: type: integer type: array type: array title: Prompt description: >- The prompt to generate completions for. It can be a single string or an array of strings. It can also be an array of integers or an array of integer arrays, which allows to pass already tokenized prompt. If multiple prompts are specified, several choices with corresponding `index` will be returned in the output. images: anyOf: - type: array items: type: string - items: type: array items: type: string type: array - type: 'null' title: Images description: >- The list of base64 encoded images for visual language completition generation. They should be formatted as MIME_TYPE, eg. data:image/jpeg;base64, Additionally, the number of images provided should match the number of '' special token in the prompt additionalProperties: false type: object required: - prompt - model title: CompletionRequest CompletionResponse: additionalProperties: false description: The response message from a /v1/completions call. properties: id: description: A unique identifier of the response title: Id type: string object: default: text_completion description: The object type, which is always "text_completion" title: Object type: string created: description: The Unix time in seconds when the response was generated title: Created type: integer model: description: The model used for the completion title: Model type: string choices: description: The list of generated completion choices items: $ref: '#/components/schemas/Choice' title: Choices type: array usage: $ref: '#/components/schemas/UsageInfo' description: Usage statistics for the completion perf_metrics: anyOf: - additionalProperties: true type: object - type: 'null' default: null description: >- See parameter [perf_metrics_in_response](#body-perf-metrics-in-response) title: Perf Metrics required: - id - created - model - choices - usage title: CompletionResponse type: object CompletionStreamResponse: additionalProperties: false description: The streamed response message from a /v1/completions call. properties: id: description: A unique identifier of the response title: Id type: string object: default: text_completion description: The object type, which is always "text_completion" title: Object type: string created: description: The Unix time in seconds when the response was generated title: Created type: integer model: description: The model used for the chat completion title: Model type: string choices: description: The list of streamed completion choices items: $ref: '#/components/schemas/CompletionResponseStreamChoice' title: Choices type: array usage: anyOf: - $ref: '#/components/schemas/UsageInfo' - type: 'null' default: null perf_metrics: anyOf: - additionalProperties: true type: object - type: 'null' default: null description: >- See parameter [perf_metrics_in_response](#body-perf-metrics-in-response) title: Perf Metrics required: - id - created - model - choices title: CompletionStreamResponse type: object HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ResponseFormat: properties: type: type: string enum: - json_object - json_schema - grammar - text title: Type schema: anyOf: - type: string - additionalProperties: true type: object - type: 'null' title: Schema grammar: anyOf: - type: string - type: 'null' title: Grammar json_schema: anyOf: - type: string - additionalProperties: true type: object - type: 'null' title: Json Schema additionalProperties: false type: object required: - type title: ResponseFormat PredictedOutput: properties: content: anyOf: - type: string - items: $ref: '#/components/schemas/ChatMessageContent' type: array title: Content type: type: string const: content title: Type default: content additionalProperties: false type: object required: - content title: PredictedOutput description: OpenAI-compatible struct for the "speculation" field. ThinkingConfigEnabled: properties: type: type: string const: enabled title: Type budget_tokens: anyOf: - type: integer - type: 'null' title: Budget Tokens description: >- Determines how many tokens the model can use for its internal reasoning process. Larger budgets can enable more thorough analysis for complex problems, improving response quality. Must be >= 1024 if specified. keep: anyOf: - type: string const: all - type: 'null' title: Keep description: >- Controls whether historical reasoning content is preserved in the prompt. When set to `"all"`, all previous assistant turns' reasoning_content is included in the rendered prompt (equivalent to `reasoning_history: "preserved"`). When omitted (null), the model uses its default history behavior. Only valid when `type` is `"enabled"`. budget_end_str: anyOf: - type: string - type: 'null' title: Budget End Str description: >- Natural-language transition phrase that the model is forced to emit just before the end-thinking token (``) when `budget_tokens` is exhausted. This produces a more natural conclusion than a hard token slam (matches vLLM's `reasoning_end_str` behavior). Defaults to a built-in phrase. Set to "" to disable the bridge and force `` immediately. Only meaningful when `budget_tokens` is set. additionalProperties: false type: object required: - type title: ThinkingConfigEnabled description: >- Configuration for enabling extended thinking (Anthropic-compatible format). ThinkingConfigDisabled: properties: type: type: string const: disabled title: Type additionalProperties: false type: object required: - type title: ThinkingConfigDisabled description: >- Configuration for disabling extended thinking (Anthropic-compatible format). Choice: additionalProperties: false description: A completion choice. properties: index: description: The index of the completion choice title: Index type: integer text: description: The completion response title: Text type: string logprobs: anyOf: - $ref: '#/components/schemas/LogProbs' - $ref: '#/components/schemas/NewLogProbs' - type: 'null' default: null description: The log probabilities of the most likely tokens title: Logprobs finish_reason: anyOf: - enum: - stop - length - error type: string - type: 'null' default: null description: >- The reason the model stopped generating tokens. This will be "stop" if the model hit a natural stop point or a provided stop sequence, or "length" if the maximum number of tokens specified in the request was reached title: Finish Reason raw_output: anyOf: - $ref: '#/components/schemas/RawOutput' - type: 'null' default: null prompt_token_ids: anyOf: - items: type: integer type: array - type: 'null' default: null description: Token IDs for the prompt (when return_token_ids=true) title: Prompt Token Ids token_ids: anyOf: - items: type: integer type: array - type: 'null' default: null description: Token IDs for the generated completion (when return_token_ids=true) title: Token Ids required: - index - text title: Choice type: object UsageInfo: additionalProperties: false description: Usage statistics. properties: prompt_tokens: description: The number of tokens in the prompt title: Prompt Tokens type: integer total_tokens: description: The total number of tokens used in the request (prompt + completion) title: Total Tokens type: integer completion_tokens: anyOf: - type: integer - type: 'null' default: null description: The number of tokens in the generated completion title: Completion Tokens prompt_tokens_details: anyOf: - $ref: '#/components/schemas/PromptTokensDetails' - type: 'null' default: null description: Details about prompt tokens, including cached tokens required: - prompt_tokens - total_tokens title: UsageInfo type: object CompletionResponseStreamChoice: additionalProperties: false description: |- A streamed completion choice. Attributes: index (int): The index of the completion choice. text (str): The completion response. logprobs (float, optional): The log probabilities of the most likely tokens. finish_reason (str): The reason the model stopped generating tokens. This will be "stop" if the model hit a natural stop point or a provided stop sequence, or "length" if the maximum number of tokens specified in the request was reached. prompt_token_ids (Optional[List[int]]): Token IDs for the prompt (when return_token_ids=true, sent in first chunk) token_ids (Optional[List[int]]): Token IDs for this chunk (when return_token_ids=true) properties: index: title: Index type: integer text: title: Text type: string logprobs: anyOf: - $ref: '#/components/schemas/LogProbs' - $ref: '#/components/schemas/NewLogProbs' - type: 'null' default: null title: Logprobs finish_reason: anyOf: - enum: - stop - length - error type: string - type: 'null' default: null title: Finish Reason raw_output: anyOf: - $ref: '#/components/schemas/RawOutput' - type: 'null' default: null prompt_token_ids: anyOf: - items: type: integer type: array - type: 'null' default: null title: Prompt Token Ids token_ids: anyOf: - items: type: integer type: array - type: 'null' default: null title: Token Ids required: - index - text title: CompletionResponseStreamChoice type: object 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 type: object required: - loc - msg - type title: ValidationError ChatMessageContent: properties: type: type: string title: Type text: anyOf: - type: string - type: 'null' title: Text image_url: anyOf: - $ref: '#/components/schemas/ChatMessageContentImageURL' - type: 'null' video_url: anyOf: - $ref: '#/components/schemas/ChatMessageContentVideoURL' - type: 'null' additionalProperties: false type: object required: - type title: ChatMessageContent LogProbs: additionalProperties: false description: Legacy log probabilities format properties: tokens: items: type: string title: Tokens type: array token_logprobs: items: type: number title: Token Logprobs type: array top_logprobs: anyOf: - items: additionalProperties: type: number type: object type: array - type: 'null' title: Top Logprobs text_offset: items: type: integer title: Text Offset type: array token_ids: anyOf: - items: type: integer type: array - type: 'null' default: null title: Token Ids title: LogProbs type: object NewLogProbs: additionalProperties: false description: OpenAI-compatible log probabilities format properties: content: items: $ref: '#/components/schemas/NewLogProbsContent' title: Content type: array title: NewLogProbs type: object RawOutput: additionalProperties: false description: |- Extension of OpenAI that returns low-level interaction of what the model sees, including the formatted prompt and function calls properties: prompt_fragments: description: >- Pieces of the prompt (like individual messages) before truncation and concatenation. Depending on prompt_truncate_len some of the messages might be dropped. Contains a mix of strings to be tokenized and individual tokens (if dictated by the conversation template) items: anyOf: - type: string - type: integer title: Prompt Fragments type: array prompt_token_ids: description: Fully processed prompt as seen by the model items: type: integer title: Prompt Token Ids type: array completion: description: >- Raw completion produced by the model before any tool calls are parsed title: Completion type: string completion_token_ids: anyOf: - items: type: integer type: array - type: 'null' default: null description: Token IDs for the raw completion title: Completion Token Ids completion_logprobs: anyOf: - $ref: '#/components/schemas/NewLogProbs' - type: 'null' default: null description: >- Log probabilities for the completion. Only populated if logprobs is specified in the request images: anyOf: - type: array items: type: string - type: 'null' default: null description: Images in the prompt title: Images videos: anyOf: - type: array items: type: string - type: 'null' default: null description: Videos in the prompt title: Videos grammar: anyOf: - type: string - type: 'null' default: null description: >- Grammar used for constrained decoding, can be either user provided (directly or JSON schema) or inferred by the chat template title: Grammar required: - prompt_fragments - prompt_token_ids - completion title: RawOutput type: object PromptTokensDetails: additionalProperties: false properties: cached_tokens: anyOf: - type: integer - type: 'null' default: null title: Cached Tokens title: PromptTokensDetails type: object ChatMessageContentImageURL: properties: url: type: string title: Url detail: anyOf: - type: string - type: 'null' title: Detail additionalProperties: false type: object required: - url title: ChatMessageContentImageURL ChatMessageContentVideoURL: properties: url: type: string title: Url detail: anyOf: - type: string - type: 'null' title: Detail max_frames: anyOf: - type: integer - type: 'null' title: Max Frames spatial_limit: anyOf: - type: integer - type: 'null' title: Spatial Limit sample_fps: anyOf: - type: number - type: 'null' title: Sample Fps additionalProperties: false type: object required: - url title: ChatMessageContentVideoURL NewLogProbsContent: additionalProperties: false properties: token: title: Token type: string logprob: title: Logprob type: number sampling_logprob: anyOf: - type: number - type: 'null' title: Sampling Logprob bytes: items: type: integer title: Bytes type: array top_logprobs: items: $ref: '#/components/schemas/NewLogProbsContentTopLogProbs' title: Top Logprobs type: array token_id: title: Token Id type: integer text_offset: title: Text Offset type: integer last_activation: anyOf: - type: string - type: 'null' default: null title: Last Activation routing_matrix: anyOf: - type: string - type: 'null' default: null title: Routing Matrix required: - token - logprob - sampling_logprob - bytes - token_id - text_offset title: NewLogProbsContent type: object NewLogProbsContentTopLogProbs: additionalProperties: false properties: token: title: Token type: string logprob: title: Logprob type: number token_id: title: Token Id type: integer bytes: items: type: integer title: Bytes type: array required: - token - logprob - token_id title: NewLogProbsContentTopLogProbs type: object securitySchemes: BearerAuth: type: http scheme: bearer description: >- Bearer authentication using your Fireworks API key. Format: Bearer bearerFormat: API_KEY ````