feat(chat-completions): support n > 1 (multiple completions)

Threads n through ConversationRequest as completion_count, tags each
chunk generator with a choice_index, and merges/accumulates results
by index. Adds a default ProtocolRequest::chunk_generator_for_choice
so the Messages and Responses adapters are unaffected.

Fixes a latent tool-call-id collision across choices as part of the
same change (ids now include choice_index, not just response id and
local tool index).

Signed-off-by: Selby Mashiki <mashikiselby@gmail.com>

README.md

@@ -29,6 +29,11 @@ inference, tool execution, and HTTP transport must be provided externally.
   DeepSeek V4.1 preprocessing with OpenCV.
 - **Tool definitions:** Function tools; the Responses API also supports tool
   namespaces and the `apply_patch` custom tool.
+- **Multiple completions:** Chat Completions `n > 1`. The adapter validates
+  and threads `n` through as `ConversationRequest::completion_count`; the
+  caller runs one inference per completion and builds each completion's
+  events with [`ProtocolRequest::chunk_generator_for_choice`], tagging every
+  chunk with its `choices[].index`.
 
 ## Not yet supported
 
@@ -36,7 +41,6 @@ inference, tool execution, and HTTP transport must be provided externally.
 - Document content, audio/video input, and file retrieval by `file_id`.
 - Server tool execution, such as `web_search`.
 - JSON Schema and regex output constraints, or enforcement of tool `strict` settings.
-- Multiple completions per Chat Completions request (`n > 1`).
 - Responses custom tool definitions other than `apply_patch`.
 - Responses conversation storage and context retrieval through `previous_response_id`.
 - Responses encrypted thinking content (`encrypted_content`).

deepseek-recipe/src/protocol/anthropic/messages/request/convert.rs

@@ -59,6 +59,7 @@ impl ProtocolRequest for MessagesRequest {
             parsing_options,
             model: Some(self.model),
             stream: self.stream.unwrap_or(false),
+            completion_count: 1,
         })
     }
 

deepseek-recipe/src/protocol/openai/chat_completion/request/convert.rs

@@ -28,6 +28,13 @@ use super::schema::{
 /// Maximum number of stop sequences accepted by the adapter.
 const MAX_STOP_SEQUENCES: usize = 16;
 
+/// Maximum number of parallel completions accepted for `n`.
+///
+/// Matches the ceiling OpenAI's own Chat Completions API documents. The
+/// caller is responsible for actually running this many inferences; this
+/// bound only guards against pathological request values.
+const MAX_COMPLETIONS: u8 = 128;
+
 impl ProtocolRequest for ChatCompletionRequest {
     type Response = ChatCompletionResponse;
 
@@ -35,6 +42,7 @@ impl ProtocolRequest for ChatCompletionRequest {
         let (thinking_mode, reasoning_effort) = self.resolve_thinking(options);
         let mut parsing_options = self.parsing_options(thinking_mode);
         let inference_options = self.inference_options()?;
+        let completion_count = validate_completion_count(self.n)?;
         validate_api_params(
             self.stop.as_ref(),
             self.stream,
@@ -60,6 +68,7 @@ impl ProtocolRequest for ChatCompletionRequest {
             parsing_options,
             model: Some(self.model),
             stream: self.stream.unwrap_or(false),
+            completion_count,
         })
     }
 
@@ -67,6 +76,15 @@ impl ProtocolRequest for ChatCompletionRequest {
         request: &ConversationRequest,
         id: String,
         model: String,
+    ) -> ChatCompletionChunkGenerator {
+        Self::chunk_generator_for_choice(request, id, model, 0)
+    }
+
+    fn chunk_generator_for_choice(
+        request: &ConversationRequest,
+        id: String,
+        model: String,
+        choice_index: u32,
     ) -> ChatCompletionChunkGenerator {
         ChatCompletionChunkGenerator::new(
             id,
@@ -74,6 +92,7 @@ impl ProtocolRequest for ChatCompletionRequest {
             !request.stream,
             request.conversation.thinking_mode,
         )
+        .with_choice_index(choice_index)
     }
 }
 
@@ -98,11 +117,6 @@ impl ChatCompletionRequest {
     }
 
     fn inference_options(&self) -> Result<InferenceOptions, ConversionError> {
-        if self.n.is_some_and(|value| value != 1) {
-            return Err(ConversionError::bad_request(
-                "Invalid n value (currently only n = 1 is supported)",
-            ));
-        }
         for (name, value) in [
             ("frequency_penalty", self.frequency_penalty),
             ("presence_penalty", self.presence_penalty),
@@ -481,6 +495,20 @@ fn convert_response_format(
     }
 }
 
+/// Validate `n` and resolve it to the number of completions to generate.
+///
+/// Absent `n` defaults to a single completion, matching the OpenAI API.
+fn validate_completion_count(n: Option<u8>) -> Result<u32, ConversionError> {
+    match n {
+        None => Ok(1),
+        Some(0) => Err(ConversionError::bad_request("n must be at least 1")),
+        Some(value) if value > MAX_COMPLETIONS => Err(ConversionError::bad_request(format!(
+            "n must be at most {MAX_COMPLETIONS}"
+        ))),
+        Some(value) => Ok(u32::from(value)),
+    }
+}
+
 /// Validate stop sequences and streaming options.
 fn validate_api_params(
     stop: Option<&ChatCompletionStopSequences>,
@@ -502,3 +530,75 @@ fn validate_api_params(
     }
     Ok(())
 }
+
+#[cfg(test)]
+mod tests {
+    use crate::request::{ConversionOptions, ProtocolRequest};
+
+    use super::ChatCompletionRequest;
+
+    /// A minimal, otherwise-valid request with the given `n`.
+    fn request_with_n(n: Option<u8>) -> ChatCompletionRequest {
+        serde_json::from_value(serde_json::json!({
+            "messages": [{"role": "user", "content": "hi"}],
+            "model": "deepseek-chat",
+            "frequency_penalty": null,
+            "max_tokens": null,
+            "n": n,
+            "presence_penalty": null,
+            "seed": null,
+            "stop": null,
+            "stream": null,
+            "stream_options": null,
+            "temperature": null,
+            "top_p": null,
+            "response_format": null,
+            "tools": null,
+            "tool_choice": null,
+            "reasoning_effort": null,
+            "thinking": null,
+            "parallel_tool_calls": null,
+        }))
+        .expect("fixture request should deserialize")
+    }
+
+    #[test]
+    fn n_absent_defaults_to_one_completion() {
+        let request = request_with_n(None)
+            .convert(ConversionOptions::default())
+            .unwrap();
+        assert_eq!(request.completion_count, 1);
+    }
+
+    #[test]
+    fn n_one_is_accepted_as_before() {
+        let request = request_with_n(Some(1))
+            .convert(ConversionOptions::default())
+            .unwrap();
+        assert_eq!(request.completion_count, 1);
+    }
+
+    #[test]
+    fn n_greater_than_one_is_now_accepted_and_threaded_through() {
+        let request = request_with_n(Some(4))
+            .convert(ConversionOptions::default())
+            .unwrap();
+        assert_eq!(request.completion_count, 4);
+    }
+
+    #[test]
+    fn n_zero_is_rejected() {
+        let error = request_with_n(Some(0))
+            .convert(ConversionOptions::default())
+            .unwrap_err();
+        assert!(error.to_string().contains("at least 1"));
+    }
+
+    #[test]
+    fn n_above_the_bound_is_rejected() {
+        let error = request_with_n(Some(255))
+            .convert(ConversionOptions::default())
+            .unwrap_err();
+        assert!(error.to_string().contains("at most"));
+    }
+}

deepseek-recipe/src/protocol/openai/chat_completion/response/chunk_generator.rs

@@ -20,6 +20,9 @@ pub struct ChatCompletionChunkGenerator {
     created: u64,
     thinking_mode: bool,
     include_usage: bool,
+    /// Which of the request's `n` parallel completions this generator's
+    /// output belongs to. Tagged on every emitted chunk's `choices[].index`.
+    choice_index: u32,
     tool_call_index: u32,
     prompt_usage: PromptUsage,
     system_fingerprint: Option<String>,
@@ -27,7 +30,10 @@ pub struct ChatCompletionChunkGenerator {
 
 impl ChatCompletionChunkGenerator {
     /// The caller supplies a unique response ID and public model name. Tool call
-    /// IDs combine the response ID and per-response tool index.
+    /// IDs combine the response ID, choice index, and per-response tool index.
+    ///
+    /// Defaults to choice index `0`; use [`Self::with_choice_index`] for
+    /// requests with `n > 1`.
     pub fn new(id: String, model: String, include_usage: bool, thinking_mode: bool) -> Self {
         Self {
             id,
@@ -38,6 +44,7 @@ impl ChatCompletionChunkGenerator {
                 .unwrap_or(0),
             thinking_mode,
             include_usage,
+            choice_index: 0,
             tool_call_index: 0,
             prompt_usage: PromptUsage::default(),
             system_fingerprint: None,
@@ -50,6 +57,16 @@ impl ChatCompletionChunkGenerator {
         self
     }
 
+    /// Tag this generator's output as belonging to a specific completion.
+    ///
+    /// The caller creates one generator per completion when `n > 1`, each with
+    /// a distinct `choice_index` (`0..n`), and drives each through its own
+    /// [`crate::stream::StreamProcessor`].
+    pub fn with_choice_index(mut self, choice_index: u32) -> Self {
+        self.choice_index = choice_index;
+        self
+    }
+
     fn new_chunk(
         &self,
         delta: ChatCompletionMessageDelta,
@@ -70,7 +87,7 @@ impl ChatCompletionChunkGenerator {
             model: self.model.clone(),
             system_fingerprint: self.system_fingerprint.clone(),
             choices: vec![ChatCompletionChunkChoice {
-                index: 0,
+                index: self.choice_index,
                 delta,
                 logprobs: None,
                 finish_reason,
@@ -130,7 +147,7 @@ impl ChunkGenerator for ChatCompletionChunkGenerator {
                     tool_calls: Some(vec![ChatCompletionToolCallDelta::Start {
                         index,
                         call: ChatCompletionResponseToolCall {
-                            id: format!("call_{}_{index}", self.id),
+                            id: format!("call_{}_{}_{index}", self.id, self.choice_index),
                             r#type: ChatCompletionToolCallType::Function,
                             function: ChatCompletionResponseFunctionCall {
                                 name: tool_name,
@@ -167,3 +184,79 @@ impl ChunkGenerator for ChatCompletionChunkGenerator {
         }
     }
 }
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    /// A generator built for one choice of an `n > 1` request must tag every
+    /// chunk it produces with that choice's index, not the default `0`.
+    #[tokio::test]
+    async fn with_choice_index_tags_every_emitted_chunk() {
+        let mut generator =
+            ChatCompletionChunkGenerator::new("resp_1".into(), "deepseek-chat".into(), true, false)
+                .with_choice_index(2);
+
+        let start_chunks = generator
+            .generate(OutputChunk::Start {
+                system_fingerprint: None,
+                usage: PromptUsage::default(),
+            })
+            .await;
+        let text_chunks = generator
+            .generate(OutputChunk::Raw {
+                content: "hi".into(),
+            })
+            .await;
+
+        for chunk in start_chunks.iter().chain(text_chunks.iter()) {
+            for choice in &chunk.choices {
+                assert_eq!(choice.index, 2);
+            }
+        }
+    }
+
+    /// Two generators for different choices of the same response must not
+    /// mint colliding tool call ids, since both start from the same response
+    /// id and the same per-generator tool call counter.
+    #[tokio::test]
+    async fn tool_call_ids_are_unique_across_choices() {
+        let mut choice0 =
+            ChatCompletionChunkGenerator::new("resp_1".into(), "deepseek-chat".into(), true, false)
+                .with_choice_index(0);
+        let mut choice1 =
+            ChatCompletionChunkGenerator::new("resp_1".into(), "deepseek-chat".into(), true, false)
+                .with_choice_index(1);
+
+        let chunks0 = choice0
+            .generate(OutputChunk::ToolCall {
+                tool_name: "search".into(),
+                arguments: String::new(),
+            })
+            .await;
+        let chunks1 = choice1
+            .generate(OutputChunk::ToolCall {
+                tool_name: "search".into(),
+                arguments: String::new(),
+            })
+            .await;
+
+        assert_ne!(tool_call_id(&chunks0), tool_call_id(&chunks1));
+    }
+
+    fn tool_call_id(chunks: &[ChatCompletionChunk]) -> String {
+        for chunk in chunks {
+            for choice in &chunk.choices {
+                let Some(tool_calls) = &choice.delta.tool_calls else {
+                    continue;
+                };
+                for call in tool_calls {
+                    if let ChatCompletionToolCallDelta::Start { call, .. } = call {
+                        return call.id.clone();
+                    }
+                }
+            }
+        }
+        panic!("no tool call start delta found");
+    }
+}

deepseek-recipe/src/protocol/openai/chat_completion/response/schema.rs

@@ -307,3 +307,55 @@ impl AppendDelta<ChatCompletionMessageDelta> for ChatCompletionResponseMessage {
         }
     }
 }
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn text_chunk(index: u32, content: &str) -> ChatCompletionChunk {
+        ChatCompletionChunk {
+            id: "resp_1".to_string(),
+            object: CHAT_COMPLETION_CHUNK_OBJECT,
+            created: 0,
+            model: "deepseek-chat".to_string(),
+            system_fingerprint: None,
+            choices: vec![ChatCompletionChunkChoice {
+                index,
+                delta: ChatCompletionMessageDelta {
+                    content: Some(Some(content.to_string())),
+                    ..Default::default()
+                },
+                logprobs: None,
+                finish_reason: None,
+            }],
+            usage: None,
+        }
+    }
+
+    /// Regression test for the `n > 1` non-streaming path: the accumulator
+    /// keys choices by `index`, so interleaved chunks from several
+    /// completions must land in separate, independently-growing choices
+    /// rather than clobbering each other.
+    #[test]
+    fn chunks_with_different_indices_accumulate_into_separate_choices() {
+        let mut response =
+            ChatCompletionResponse::new("resp_1".into(), "deepseek-chat".into(), 0, 0, 0);
+        response.append(text_chunk(0, "Hello"));
+        response.append(text_chunk(1, "Hi"));
+        response.append(text_chunk(0, " world"));
+
+        assert_eq!(response.choices.len(), 2);
+        let choice0 = response
+            .choices
+            .iter()
+            .find(|choice| choice.index == 0)
+            .expect("choice 0 present");
+        let choice1 = response
+            .choices
+            .iter()
+            .find(|choice| choice.index == 1)
+            .expect("choice 1 present");
+        assert_eq!(choice0.message.content.as_deref(), Some("Hello world"));
+        assert_eq!(choice1.message.content.as_deref(), Some("Hi"));
+    }
+}

deepseek-recipe/src/protocol/openai/responses/request/convert.rs

@@ -585,6 +585,7 @@ impl ProtocolRequest for ResponsesRequest {
             parsing_options,
             model: Some(self.model),
             stream: self.stream.unwrap_or(false),
+            completion_count: 1,
         })
     }
 

deepseek-recipe/src/request/mod.rs

@@ -38,6 +38,14 @@ pub struct ConversationRequest {
     /// Original model name, when exposed by the adapter. The caller resolves it.
     pub model: Option<String>,
     pub stream: bool,
+    /// Number of parallel completions the caller should generate for this
+    /// conversation.
+    ///
+    /// Always `1` for protocols that don't expose a multi-completion parameter.
+    /// Chat Completions surfaces this from its `n` request field. The caller
+    /// runs inference once per completion and tags each with a distinct
+    /// `choice_index` via [`ProtocolRequest::chunk_generator_for_choice`].
+    pub completion_count: u32,
 }
 
 impl ConversationRequest {
@@ -49,6 +57,7 @@ impl ConversationRequest {
             parsing_options: ParsingOptions::default(),
             model: None,
             stream: false,
+            completion_count: 1,
         }
     }
 }
@@ -68,11 +77,38 @@ pub trait ProtocolRequest: 'static + Send + Sync {
     fn convert(self, options: ConversionOptions) -> Result<ConversationRequest, ConversionError>;
 
     /// Construct protocol events using the converted request's resolved settings.
+    ///
+    /// Equivalent to [`Self::chunk_generator_for_choice`] with `choice_index`
+    /// `0`. Protocols that never produce more than one completion can keep
+    /// implementing only this method.
     fn chunk_generator(
         request: &ConversationRequest,
         id: String,
         model: String,
     ) -> <Self::Response as ProtocolResponse>::ChunkGenerator;
+
+    /// Construct protocol events for one completion of a `completion_count > 1`
+    /// request.
+    ///
+    /// `choice_index` identifies which of the caller's parallel completions
+    /// this generator's output belongs to; the generator must tag every event
+    /// it produces with that index. The caller runs one inference per
+    /// completion, drives each through its own [`crate::stream::StreamProcessor`]
+    /// built from the generator returned here, and merges (streaming) or
+    /// accumulates (complete response) the results.
+    ///
+    /// The default implementation ignores `choice_index` and delegates to
+    /// [`Self::chunk_generator`], which is correct for every protocol except
+    /// Chat Completions today.
+    fn chunk_generator_for_choice(
+        request: &ConversationRequest,
+        id: String,
+        model: String,
+        choice_index: u32,
+    ) -> <Self::Response as ProtocolResponse>::ChunkGenerator {
+        let _ = choice_index;
+        Self::chunk_generator(request, id, model)
+    }
 }
 
 /// A failure while converting protocol input into a conversation request.

server-rs/src/lib.rs

@@ -11,6 +11,7 @@ use std::time::{SystemTime, UNIX_EPOCH};
 
 use deepseek_recipe::anthropic::MessagesRequest;
 pub use deepseek_recipe::error_response::ErrorResponse;
+use deepseek_recipe::openai::chat_completion::response::ChatCompletionResponse;
 use deepseek_recipe::openai::responses::response::ResponsesResponse;
 use deepseek_recipe::openai::{ChatCompletionRequest, ResponsesRequest};
 pub use deepseek_recipe::request::ConversionError;
@@ -27,7 +28,7 @@ use deepseek_recipe_image::{
     ImageError, ImageQuota, ImageResolver, OpenCvImagePreprocessor, ReqwestImageFetcher,
 };
 use serde::{Serialize, de::DeserializeOwned};
-use tokio_stream::{Stream, StreamExt};
+use tokio_stream::{Stream, StreamExt, StreamMap};
 
 const MOCK_ID: &str = "mock-id";
 const MOCK_MODEL: &str = "deepseek-flash";
@@ -135,6 +136,10 @@ where
 
 /// Prepare Chat Completions SSE using the request's usage inclusion setting.
 ///
+/// When the request's `n` asks for more than one completion, runs one mock
+/// inference per completion and interleaves their chunks as they arrive, each
+/// tagged with its own `choices[].index`.
+///
 /// # Errors
 ///
 /// Returns the protocol conversion error before producing response events, or a
@@ -145,10 +150,131 @@ pub async fn prepare_chat_completion_response(
 ) -> Result<PreparedResponse, ConversionError> {
     let include_usage = req.include_usage();
     let request = req.convert(ConversionOptions::default())?;
-    prepare_converted_response_with::<ChatCompletionRequest>(request, |generator| {
+    if request.completion_count <= 1 {
+        return prepare_converted_response_with::<ChatCompletionRequest>(request, |generator| {
             generator.with_include_usage(include_usage)
         })
+        .await;
+    }
+    prepare_multi_completion_response(request, include_usage).await
+}
+
+/// Prepare Chat Completions SSE for a `n > 1` request.
+///
+/// Each of the `n` completions gets its own mock inference stream and its own
+/// [`StreamProcessor`], built with a distinct `choice_index` so downstream
+/// chunks carry the right `choices[].index`. A [`StreamMap`] merges the `n`
+/// processors so chunks are emitted in true arrival order rather than one
+/// completion at a time, mirroring how a real backend would interleave
+/// parallel generations.
+///
+/// # Errors
+///
+/// Returns a conversion error with status code 400 or 500 when an image cannot
+/// be resolved or preprocessed.
+async fn prepare_multi_completion_response(
+    request: ConversationRequest,
+    include_usage: bool,
+) -> Result<PreparedResponse, ConversionError> {
+    let rendered = DeepseekV41Encoding::new().render_conversation(&request.conversation);
+    let resolver = default_resolver()?;
+    let mut quota = ImageQuota::new();
+    let multi_modal_data = resolver
+        .resolve(&rendered.image_sources, &mut quota)
         .await
+        .map_err(image_error)?;
+    tracing::debug!(
+        prompt = rendered.prompt,
+        image_count = multi_modal_data.images.len(),
+        completion_count = request.completion_count,
+        "rendered prompt for multi-completion request"
+    );
+
+    let mut processors = StreamMap::new();
+    for choice_index in 0..request.completion_count {
+        let generator = ChatCompletionRequest::chunk_generator_for_choice(
+            &request,
+            MOCK_ID.into(),
+            MOCK_MODEL.into(),
+            choice_index,
+        )
+        .with_include_usage(include_usage);
+        let processor = StreamProcessor::new(generator, request.parsing_options.clone());
+        processors.insert(choice_index, Box::pin(processor.process(mock_inference())));
+    }
+
+    let events = processors.map(|(_choice_index, chunk)| {
+        let chunk = chunk.map_err(|error| serde_json::Error::io(std::io::Error::other(error)))?;
+        let data = serde_json::to_string(&chunk)?;
+        Ok(
+            match <ChatCompletionResponse as ProtocolResponse>::chunk_event_type(&chunk) {
+                Some(event_type) => format!("event: {event_type}\ndata: {data}\n\n"),
+                None => format!("data: {data}\n\n"),
+            },
+        )
+    });
+    let done = <ChatCompletionResponse as ProtocolResponse>::done_message()
+        .map(|message| Ok(format!("data: {message}\n\n")));
+
+    Ok(PreparedResponse {
+        prompt: rendered.prompt,
+        multi_modal_data,
+        events: Box::pin(events.chain(tokio_stream::iter(done))),
+    })
+}
+
+/// Aggregate a `n > 1` Chat Completions request into a single JSON response.
+///
+/// Every completion's chunks append into the same [`ChatCompletionResponse`];
+/// its accumulator already keys choices by `index`, so no merge logic is
+/// needed beyond running each completion's chunks through `.append()`.
+///
+/// # Errors
+///
+/// Returns a conversion error with status code 400 or 500 when an image cannot
+/// be resolved or preprocessed, or if a completion's output fails to process.
+pub async fn complete_chat_completion_response(
+    req: ChatCompletionRequest,
+) -> Result<ChatCompletionResponse, ConversionError> {
+    let include_usage = req.include_usage();
+    let request = req.convert(ConversionOptions::default())?;
+    if request.completion_count <= 1 {
+        return complete_response_with::<ChatCompletionRequest>(request, |generator| {
+            generator.with_include_usage(include_usage)
+        })
+        .await;
+    }
+
+    let rendered = DeepseekV41Encoding::new().render_conversation(&request.conversation);
+    let resolver = default_resolver()?;
+    let mut quota = ImageQuota::new();
+    resolver
+        .resolve(&rendered.image_sources, &mut quota)
+        .await
+        .map_err(image_error)?;
+
+    let created = SystemTime::now()
+        .duration_since(UNIX_EPOCH)
+        .map(|elapsed| elapsed.as_secs())
+        .unwrap_or(0);
+    let mut response =
+        ChatCompletionResponse::new(MOCK_ID.into(), MOCK_MODEL.into(), created, 0, 0);
+    for choice_index in 0..request.completion_count {
+        let generator = ChatCompletionRequest::chunk_generator_for_choice(
+            &request,
+            MOCK_ID.into(),
+            MOCK_MODEL.into(),
+            choice_index,
+        )
+        .with_include_usage(include_usage);
+        let processor = StreamProcessor::new(generator, request.parsing_options.clone());
+        let mut chunks = pin!(processor.process(mock_inference()));
+        while let Some(chunk) = chunks.next().await {
+            let chunk = chunk.map_err(|error| ConversionError::internal(error.to_string()))?;
+            response.append(chunk);
+        }
+    }
+    Ok(response)
 }
 
 /// Prepare Responses SSE using the request's custom tool declarations.

server-rs/src/main.rs

@@ -13,9 +13,9 @@ use deepseek_recipe::response::ProtocolResponse;
 use deepseek_recipe::stream::ChunkGenerator;
 use serde::{Serialize, de::DeserializeOwned};
 use server_rs::{
-    ConversionError, ErrorResponse, PreparedResponse, complete_response,
+    ConversionError, ErrorResponse, PreparedResponse, complete_chat_completion_response,
-    complete_responses_response, prepare_chat_completion_response, prepare_converted_response,
+    complete_response, complete_responses_response, prepare_chat_completion_response,
-    prepare_responses_response,
+    prepare_converted_response, prepare_responses_response,
 };
 
 type ApiError = (StatusCode, Json<ErrorResponse>);
@@ -47,7 +47,10 @@ async fn chat_completion_handler(
             .map(sse_response)
             .map_err(http_error);
     }
-    api_handler(Json(request)).await
+    complete_chat_completion_response(request)
+        .await
+        .map(|response| Json(response).into_response())
+        .map_err(http_error)
 }
 
 async fn responses_handler(Json(request): Json<ResponsesRequest>) -> Result<Response, ApiError> {