openai_interface/chat/create/

response.rs

//! This module provides structures for streaming and non-streaming
//! chat completion responses.

pub mod streaming {
    //! Streaming chat completion response.

    use serde::{Deserialize, Serialize};

    use crate::chat::ServiceTier;

    /// Deserializes a possibly-null, possibly-missing list as an empty
    /// `Vec`. Some OpenAI-compatible backends (e.g. vLLM) terminate the
    /// stream with a usage-only chunk whose `choices` is `null`; without
    /// this, the chunk — and with it the only copy of the usage statistics —
    /// would fail to deserialize.
    fn null_to_empty_vec<'de, D, T>(deserializer: D) -> Result<Vec<T>, D::Error>
    where
        D: serde::Deserializer<'de>,
        T: Deserialize<'de>,
    {
        Ok(Option::<Vec<T>>::deserialize(deserializer)?.unwrap_or_default())
    }

    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct ChatCompletionChunk {
        /// A unique identifier for the chat completion.
        pub id: String,
        /// A list of chat completion choices. Can be more than one
        /// if `n` is greater than 1. Empty for the final usage-only chunk
        /// (see `stream_options: {"include_usage": true}`); some backends
        /// send that chunk with `"choices": null` or omit the key entirely,
        /// which deserializes as an empty list too.
        #[serde(default, deserialize_with = "null_to_empty_vec")]
        pub choices: Vec<CompletionChunkChoice>,
        /// The Unix timestamp (in seconds) of when the chat completion was created.
        /// Each chunk has the same timestamp.
        pub created: u64,
        /// The model used for the chat completion.
        pub model: String,
        /// The object type, which is always `chat.completion.chunk`.
        ///
        /// `Some` only when the backend sends a recognized value; some
        /// non-OpenAI gateways omit or repurpose the field.
        pub object: Option<ChatCompletionChunkObject>,
        /// Specifies the processing type used for serving the request.
        ///
        /// When the `service_tier` parameter is set, the response body will include the
        /// `service_tier` value based on the processing mode actually used to serve the
        /// request. This response value may be different from the value set in the
        /// request parameter.
        pub service_tier: Option<ServiceTier>,
        /// This fingerprint represents the backend configuration that the model runs with.
        /// Can be used in conjunction with the `seed` request parameter to understand when
        /// backend changes have been made that might impact determinism.
        pub system_fingerprint: Option<String>,
        /// An optional field that will only be present when you set
        /// `stream_options: {"include_usage": true}` in your request. When present, it
        /// contains a null value **except for the last chunk** which contains the token
        /// usage statistics for the entire request.
        ///
        /// **NOTE:** If the stream is interrupted or cancelled, you may not receive the
        /// final usage chunk which contains the total token usage for the request.
        pub usage: Option<CompletionUsage>,
        /// Moderation results for the request input and generated output.
        ///
        /// Present on the moderation chunk when moderated completions are
        /// requested via the `moderation` request parameter.
        pub moderation: Option<crate::chat::ChatModeration>,

        /// vLLM: the prompt's token IDs after chat-template rendering. Sent
        /// on the first chunk only.
        #[cfg(feature = "vllm")]
        pub prompt_token_ids: Option<Vec<u32>>,
        /// vLLM: the fully rendered prompt text. Only sent on the first
        /// chunk, and only when the request set `vllm_chat.return_prompt_text`.
        #[cfg(feature = "vllm")]
        pub prompt_text: Option<String>,

        /// Z.ai / GLM: the request identifier, echoing the request's
        /// `request_id` or the one GLM generated. Not part of the OpenAI chunk
        /// schema.
        #[cfg(feature = "zai")]
        pub request_id: Option<String>,
    }

    crate::wire_string_enum! {
        /// The object type, which is always `chat.completion.chunk`.
        pub enum ChatCompletionChunkObject {
            ChatCompletionChunk => "chat.completion.chunk",
        }
    }

    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct CompletionChunkChoice {
        /// A chat completion delta generated by streamed model responses.
        pub delta: ChoiceDelta,
        /// The index of the choice in the list of choices.
        pub index: u32,
        /// Log probability information for the choice.
        pub logprobs: Option<ChoiceLogprobs>,
        /// The reason the model stopped generating tokens.
        ///
        /// This will be `stop` if the model hit a natural stop point or a provided stop
        /// sequence, `length` if the maximum number of tokens specified in the request was
        /// reached, `content_filter` if content was omitted due to a flag from our content
        /// filters, `tool_calls` if the model called a tool, or `function_call`
        /// (deprecated) if the model called a function.
        pub finish_reason: Option<FinishReason>,

        /// vLLM: which terminator ended generation — the matched stop
        /// string, or the matched token ID. Not part of the OpenAI chunk
        /// schema.
        #[cfg(feature = "vllm")]
        pub stop_reason: Option<crate::vllm::StopReason>,
        /// vLLM: the generated token IDs for this chunk. Only set when the
        /// request set `vllm_chat.return_token_ids`.
        #[cfg(feature = "vllm")]
        pub token_ids: Option<Vec<u32>>,
    }

    pub use crate::chat::FinishReason;

    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct ChoiceDelta {
        /// The contents of the chunk message.
        pub content: Option<String>,
        /// The reasoning contents of the chunk message. Only present for
        /// thinking models (DeepSeek, Qwen3, and other reasoning models
        /// served by OpenAI-compatible backends).
        #[cfg(feature = "reasoning")]
        pub reasoning_content: Option<String>,
        /// vLLM: the reasoning contents of the chunk message, under the key
        /// vLLM actually streams.
        ///
        /// vLLM serializes the chain of thought as `reasoning`, not
        /// `reasoning_content`, so for a vLLM backend the field above stays
        /// `None`. [`ChatCompletionAccumulator`](crate::chat::create::accumulator::ChatCompletionAccumulator)
        /// accumulates both and exposes this one through its `reasoning`
        /// accessor.
        #[cfg(feature = "vllm")]
        pub reasoning: Option<String>,
        /// Deprecated and replaced by `tool_calls`.
        ///
        /// The name and arguments of a function that should be called, as generated by the
        /// model.
        pub function_call: Option<ChoiceDeltaFunctionCall>,
        /// The refusal message generated by the model.
        pub refusal: Option<String>,
        /// The role of the author of this message.
        pub role: Option<CompletionRole>,
        /// A list of tool calls generated by the model, such as function calls.
        pub tool_calls: Option<Vec<ChoiceDeltaToolCall>>,
        /// Annotations for the chunk message, such as URL citations emitted
        /// by search deployments.
        ///
        /// Not part of the official OpenAI chunk schema, but Azure OpenAI
        /// ("on your data" / search deployments) streams `annotations`
        /// inside `delta`, and dropping them silently loses the citations.
        pub annotations: Option<Vec<crate::chat::Annotation>>,
        /// Data about a streamed audio response from the model.
        ///
        /// Not part of the official OpenAI chunk schema, but audio-capable
        /// Azure OpenAI deployments stream `audio` inside `delta`.
        pub audio: Option<crate::chat::ChatCompletionAudio>,
    }

    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct ChoiceDeltaToolCallFunction {
        /// The arguments to call the function with, as generated by the model in JSON
        /// format. Note that the model does not always generate valid JSON, and may
        /// hallucinate parameters not defined by your function schema. Validate the
        /// arguments in your code before calling your function.
        pub arguments: Option<String>,
        /// The name of the function to call.
        pub name: Option<String>,
    }

    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct ChoiceDeltaFunctionCall {
        /// The arguments to call the function with, as generated by the model in JSON
        /// format. Note that the model does not always generate valid JSON, and may
        /// hallucinate parameters not defined by your function schema. Validate the
        /// arguments in your code before calling your function.
        pub arguments: Option<String>,
        /// The name of the function to call.
        pub name: Option<String>,
    }

    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct ChoiceDeltaToolCall {
        /// The index of the tool call in the list of tool calls.
        pub index: u32,
        /// The ID of the tool call.
        pub id: Option<String>,
        /// The function that the model called.
        pub function: Option<ChoiceDeltaToolCallFunction>,
        /// The type of the tool. Currently, only `function` is supported.
        #[serde(rename = "type")]
        pub type_: Option<ChoiceDeltaToolCallType>,
    }

    crate::wire_string_enum! {
        /// The type of a streamed tool call.
        pub enum ChoiceDeltaToolCallType {
            /// The tool call invokes a function.
            Function => "function",
            /// The tool call invokes a custom tool.
            Custom => "custom",
        }
    }

    pub use crate::chat::Role as CompletionRole;

    /// Log probability information for a choice.
    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct ChoiceLogprobs {
        /// A list of message content tokens with log probability information.
        pub content: Option<Vec<LogprobeContent>>,
        /// A list of reasoning content tokens with log probability
        /// information. Only present for thinking models.
        #[cfg(feature = "reasoning")]
        pub reasoning_content: Option<Vec<LogprobeContent>>,
        /// A list of message refusal tokens with log probability information.
        pub refusal: Option<Vec<LogprobeContent>>,
    }

    /// A list of message content tokens with log probability information.
    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct LogprobeContent {
        pub token: String,
        pub logprob: f32,
        pub bytes: Option<Vec<u8>>,
        pub top_logprobs: Vec<TopLogprob>,
    }

    /// List of the most likely tokens and their log probability, at this
    /// token position. In rare cases, there may be fewer than the number of requested top_logprobs returned.
    #[derive(Debug, Deserialize, Serialize, Clone)]
    pub struct TopLogprob {
        pub token: String,
        pub logprob: f32,
        pub bytes: Option<Vec<u8>>,
    }

    pub use crate::chat::{CompletionTokensDetails, CompletionUsage, PromptTokensDetails};

    crate::impl_from_str!(ChatCompletionChunk);

    #[cfg(test)]
    mod test {
        use std::str::FromStr;

        use super::*;

        #[test]
        fn streaming_example_deepseek() {
            let streams = vec![
                r#"{"id": "1f633d8bfc032625086f14113c411638", "choices": [{"index": 0, "delta": {"content": "", "role": "assistant"}, "finish_reason": null, "logprobs": null}], "created": 1718345013, "model": "deepseek-chat", "system_fingerprint": "fp_a49d71b8a1", "object": "chat.completion.chunk", "usage": null}"#,
                r#"{"choices": [{"delta": {"content": "Hello", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": "!", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": " How", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": " can", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": " I", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": " assist", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": " you", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": " today", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": "?", "role": "assistant"}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1"}"#,
                r#"{"choices": [{"delta": {"content": "", "role": null}, "finish_reason": "stop", "index": 0, "logprobs": null}], "created": 1718345013, "id": "1f633d8bfc032625086f14113c411638", "model": "deepseek-chat", "object": "chat.completion.chunk", "system_fingerprint": "fp_a49d71b8a1", "usage": {"completion_tokens": 9, "prompt_tokens": 17, "total_tokens": 26}}"#,
            ];

            for stream in streams {
                let parsed = ChatCompletionChunk::from_str(stream);
                match parsed {
                    Ok(completion) => {
                        println!("Deserialized: {:#?}", completion);
                    }
                    Err(e) => {
                        panic!("Failed to deserialize {}: {}", stream, e);
                    }
                }
            }
        }

        #[test]
        fn streaming_example_qwen() {
            let streams = vec![
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"","function_call":null,"refusal":null,"role":"assistant","tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"我是","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"来自","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"阿里","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"云的超大规模","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"语言","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"模型","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"。","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"问。","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[{"delta":{"content":"","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":"stop","index":0,"logprobs":null}],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}"#,
                r#"{"id":"chatcmpl-e30f5ae7-3063-93c4-90fe-beb5f900bd57","choices":[],"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":{"completion_tokens":17,"prompt_tokens":22,"total_tokens":39,"completion_tokens_details":null,"prompt_tokens_details":{"audio_tokens":null,"cached_tokens":0}}}"#,
            ];

            for stream in streams {
                let parsed = ChatCompletionChunk::from_str(stream);
                match parsed {
                    Ok(completion) => {
                        println!("Deserialized: {:#?}", completion);
                    }
                    Err(e) => {
                        panic!("Failed to deserialize {}: {}", stream, e);
                    }
                }
            }
        }

        /// Azure OpenAI streams `annotations` (URL citations from "on your
        /// data" deployments) and `audio` inside `delta`, outside the
        /// official chunk schema; they must deserialize instead of being
        /// dropped.
        #[test]
        fn streaming_example_azure_annotations_and_audio() {
            let chunk = ChatCompletionChunk::from_str(
                r#"{"id":"chatcmpl-abc","choices":[{"delta":{"content":"According to the doc","annotations":[{"type":"url_citation","url_citation":{"start_index":0,"end_index":20,"title":"Azure Docs","url":"https://learn.microsoft.com/azure"}}],"audio":{"id":"audio_abc","data":"SGVsbG8=","expires_at":1735113344,"transcript":"Hello"}},"finish_reason":null,"index":0,"logprobs":null}],"created":1735113344,"model":"gpt-4o","object":"chat.completion.chunk","system_fingerprint":"fp_abc"}"#,
            )
            .expect("chunk with annotations and audio must deserialize");

            let delta = &chunk.choices[0].delta;
            let annotations = delta.annotations.as_ref().expect("annotations");
            assert_eq!(annotations.len(), 1);
            assert_eq!(annotations[0].url_citation.title, "Azure Docs");
            assert_eq!(
                annotations[0].url_citation.url,
                "https://learn.microsoft.com/azure"
            );

            let audio = delta.audio.as_ref().expect("audio");
            assert_eq!(audio.id, "audio_abc");
            assert_eq!(audio.transcript, "Hello");
        }

        /// vLLM-style backends terminate the stream with a usage-only chunk
        /// whose `choices` is `null`. The chunk must parse, yield no
        /// choices, and keep the usage statistics.
        #[test]
        fn usage_chunk_with_null_choices_parses() {
            let parsed = ChatCompletionChunk::from_str(
                r#"{"id":"chatcmpl-1","choices":null,"created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","usage":{"completion_tokens":17,"prompt_tokens":22,"total_tokens":39}}"#,
            )
            .expect("usage chunk with null choices must deserialize");
            assert!(parsed.choices.is_empty());
            assert_eq!(parsed.usage.expect("usage").total_tokens, 39);
        }

        #[test]
        fn usage_chunk_with_missing_choices_parses() {
            let parsed = ChatCompletionChunk::from_str(
                r#"{"id":"chatcmpl-1","created":1735113344,"model":"qwen-plus","object":"chat.completion.chunk","usage":{"completion_tokens":1,"prompt_tokens":2,"total_tokens":3}}"#,
            )
            .expect("usage chunk without a choices key must deserialize");
            assert!(parsed.choices.is_empty());
        }

        /// Gateways invent finish reasons (`eos`, provider-specific codes).
        /// They must not kill the chunk, and must round-trip unchanged.
        #[test]
        fn unknown_finish_reason_is_preserved() {
            let parsed = ChatCompletionChunk::from_str(
                r#"{"id":"1","choices":[{"index":0,"delta":{},"finish_reason":"eos"}],"created":1,"model":"m","object":"chat.completion.chunk"}"#,
            )
            .expect("chunk with unknown finish_reason must deserialize");

            let finish_reason = parsed.choices[0]
                .finish_reason
                .as_ref()
                .expect("finish_reason");
            assert_eq!(finish_reason.as_str(), "eos");
            assert_eq!(finish_reason.to_string(), "eos");
            assert_eq!(
                serde_json::to_value(finish_reason).unwrap(),
                serde_json::json!("eos")
            );
        }

        #[test]
        fn unknown_role_is_preserved() {
            let parsed = ChatCompletionChunk::from_str(
                r#"{"id":"1","choices":[{"index":0,"delta":{"role":"model","content":"hi"},"finish_reason":null}],"created":1,"model":"m","object":"chat.completion.chunk"}"#,
            )
            .expect("chunk with unknown role must deserialize");
            let role = parsed.choices[0].delta.role.as_ref().expect("role");
            assert_eq!(role.as_str(), "model");
        }

        #[test]
        fn missing_or_unknown_object_field_parses() {
            let missing =
                ChatCompletionChunk::from_str(r#"{"id":"1","choices":[],"created":1,"model":"m"}"#)
                    .expect("chunk without object must deserialize");
            assert!(missing.object.is_none());

            let weird = ChatCompletionChunk::from_str(
                r#"{"id":"1","choices":[],"created":1,"model":"m","object":"vendor.custom.chunk"}"#,
            )
            .expect("chunk with unknown object must deserialize");
            assert_eq!(
                weird.object.expect("object").as_str(),
                "vendor.custom.chunk"
            );
        }

        /// Responses must serialize back out for proxying/logging.
        #[test]
        fn chunk_round_trips_through_json() {
            let parsed = ChatCompletionChunk::from_str(
                r#"{"id":"1","choices":[{"index":0,"delta":{"role":"assistant","content":"Hi"},"finish_reason":null}],"created":1,"model":"m","object":"chat.completion.chunk"}"#,
            )
            .expect("chunk must deserialize");

            let json = serde_json::to_value(&parsed).unwrap();
            assert_eq!(json["object"], "chat.completion.chunk");
            assert_eq!(json["choices"][0]["delta"]["content"], "Hi");

            let reparsed = serde_json::from_value::<ChatCompletionChunk>(json).unwrap();
            assert_eq!(reparsed.id, parsed.id);
            assert_eq!(
                reparsed.choices[0].delta.content,
                parsed.choices[0].delta.content
            );
        }
    }
}

pub mod no_streaming {
    //! Non-streaming chat completion response.

    /// Alias for `crate::chat::ChatCompletion`, which is shared
    /// by many other modules. This alias is for compatibility.
    pub type ChatCompletion = crate::chat::ChatCompletion;
}