diff --git a/llama_cpp/server/app.py b/llama_cpp/server/app.py
index b6db453b8..e5c741124 100644
--- a/llama_cpp/server/app.py
+++ b/llama_cpp/server/app.py
@@ -267,86 +267,83 @@ async def create_completion(
     request: Request,
     body: CreateCompletionRequest,
 ) -> llama_cpp.Completion:
-    exit_stack = contextlib.AsyncExitStack()
-    llama_proxy = await exit_stack.enter_async_context(contextlib.asynccontextmanager(get_llama_proxy)())
-    if llama_proxy is None:
-        raise HTTPException(
-            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
-            detail="Service is not available",
+    async with contextlib.AsyncExitStack() as exit_stack:
+        llama_proxy = await exit_stack.enter_async_context(contextlib.asynccontextmanager(get_llama_proxy)())
+        if llama_proxy is None:
+            raise HTTPException(
+                status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+                detail="Service is not available",
+            )
+        if isinstance(body.prompt, list):
+            assert len(body.prompt) <= 1
+            body.prompt = body.prompt[0] if len(body.prompt) > 0 else ""
+
+        llama = llama_proxy(
+            body.model
+            if request.url.path != "/v1/engines/copilot-codex/completions"
+            else "copilot-codex"
         )
-    if isinstance(body.prompt, list):
-        assert len(body.prompt) <= 1
-        body.prompt = body.prompt[0] if len(body.prompt) > 0 else ""
-
-    llama = llama_proxy(
-        body.model
-        if request.url.path != "/v1/engines/copilot-codex/completions"
-        else "copilot-codex"
-    )
-
-    exclude = {
-        "n",
-        "best_of",
-        "logit_bias_type",
-        "user",
-        "min_tokens",
-    }
-    kwargs = body.model_dump(exclude=exclude)
 
-    if body.logit_bias is not None:
-        kwargs["logit_bias"] = (
-            _logit_bias_tokens_to_input_ids(llama, body.logit_bias)
-            if body.logit_bias_type == "tokens"
-            else body.logit_bias
-        )
-
-    if body.grammar is not None:
-        kwargs["grammar"] = llama_cpp.LlamaGrammar.from_string(body.grammar)
+        exclude = {
+            "n",
+            "best_of",
+            "logit_bias_type",
+            "user",
+            "min_tokens",
+        }
+        kwargs = body.model_dump(exclude=exclude)
+
+        if body.logit_bias is not None:
+            kwargs["logit_bias"] = (
+                _logit_bias_tokens_to_input_ids(llama, body.logit_bias)
+                if body.logit_bias_type == "tokens"
+                else body.logit_bias
+            )
+
+        if body.grammar is not None:
+            kwargs["grammar"] = llama_cpp.LlamaGrammar.from_string(body.grammar)
+
+        if body.min_tokens > 0:
+            _min_tokens_logits_processor = llama_cpp.LogitsProcessorList(
+                [llama_cpp.MinTokensLogitsProcessor(body.min_tokens, llama.token_eos())]
+            )
+            if "logits_processor" not in kwargs:
+                kwargs["logits_processor"] = _min_tokens_logits_processor
+            else:
+                kwargs["logits_processor"].extend(_min_tokens_logits_processor)
 
-    if body.min_tokens > 0:
-        _min_tokens_logits_processor = llama_cpp.LogitsProcessorList(
-            [llama_cpp.MinTokensLogitsProcessor(body.min_tokens, llama.token_eos())]
-        )
-        if "logits_processor" not in kwargs:
-            kwargs["logits_processor"] = _min_tokens_logits_processor
+        try:
+            iterator_or_completion: Union[
+                llama_cpp.CreateCompletionResponse,
+                Iterator[llama_cpp.CreateCompletionStreamResponse],
+            ] = await run_in_threadpool(llama, **kwargs)
+        except Exception as err:
+            raise err
+
+        if isinstance(iterator_or_completion, Iterator):
+            # EAFP: It's easier to ask for forgiveness than permission
+            first_response = await run_in_threadpool(next, iterator_or_completion)
+
+            # If no exception was raised from first_response, we can assume that
+            # the iterator is valid and we can use it to stream the response.
+            def iterator() -> Iterator[llama_cpp.CreateCompletionStreamResponse]:
+                yield first_response
+                yield from iterator_or_completion
+
+            send_chan, recv_chan = anyio.create_memory_object_stream(10)
+            return EventSourceResponse(
+                recv_chan,
+                data_sender_callable=partial(  # type: ignore
+                    get_event_publisher,
+                    request=request,
+                    inner_send_chan=send_chan,
+                    iterator=iterator(),
+                ),
+                sep="\n",
+                ping_message_factory=_ping_message_factory,
+            )
         else:
-            kwargs["logits_processor"].extend(_min_tokens_logits_processor)
-
-    try:
-        iterator_or_completion: Union[
-            llama_cpp.CreateCompletionResponse,
-            Iterator[llama_cpp.CreateCompletionStreamResponse],
-        ] = await run_in_threadpool(llama, **kwargs)
-    except Exception as err:
-        await exit_stack.aclose()
-        raise err
-
-    if isinstance(iterator_or_completion, Iterator):
-        # EAFP: It's easier to ask for forgiveness than permission
-        first_response = await run_in_threadpool(next, iterator_or_completion)
-
-        # If no exception was raised from first_response, we can assume that
-        # the iterator is valid and we can use it to stream the response.
-        def iterator() -> Iterator[llama_cpp.CreateCompletionStreamResponse]:
-            yield first_response
-            yield from iterator_or_completion
-
-        send_chan, recv_chan = anyio.create_memory_object_stream(10)
-        return EventSourceResponse(
-            recv_chan,
-            data_sender_callable=partial(  # type: ignore
-                get_event_publisher,
-                request=request,
-                inner_send_chan=send_chan,
-                iterator=iterator(),
-                on_complete=exit_stack.aclose,
-            ),
-            sep="\n",
-            ping_message_factory=_ping_message_factory,
-        )
-    else:
-        await exit_stack.aclose()
-        return iterator_or_completion
+            return iterator_or_completion
 
 
 @router.post(
@@ -474,74 +471,71 @@ async def create_chat_completion(
     # where the dependency is cleaned up before a StreamingResponse
     # is complete.
     # https://github.com/tiangolo/fastapi/issues/11143
-    exit_stack = contextlib.AsyncExitStack()
-    llama_proxy = await exit_stack.enter_async_context(contextlib.asynccontextmanager(get_llama_proxy)())
-    if llama_proxy is None:
-        raise HTTPException(
-            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
-            detail="Service is not available",
-        )
-    exclude = {
-        "n",
-        "logit_bias_type",
-        "user",
-        "min_tokens",
-    }
-    kwargs = body.model_dump(exclude=exclude)
-    llama = llama_proxy(body.model)
-    if body.logit_bias is not None:
-        kwargs["logit_bias"] = (
-            _logit_bias_tokens_to_input_ids(llama, body.logit_bias)
-            if body.logit_bias_type == "tokens"
-            else body.logit_bias
-        )
-
-    if body.grammar is not None:
-        kwargs["grammar"] = llama_cpp.LlamaGrammar.from_string(body.grammar)
+    async with contextlib.AsyncExitStack() as exit_stack:
+        llama_proxy = await exit_stack.enter_async_context(contextlib.asynccontextmanager(get_llama_proxy)())
+        if llama_proxy is None:
+            raise HTTPException(
+                status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+                detail="Service is not available",
+            )
+        exclude = {
+            "n",
+            "logit_bias_type",
+            "user",
+            "min_tokens",
+        }
+        kwargs = body.model_dump(exclude=exclude)
+        llama = llama_proxy(body.model)
+        if body.logit_bias is not None:
+            kwargs["logit_bias"] = (
+                _logit_bias_tokens_to_input_ids(llama, body.logit_bias)
+                if body.logit_bias_type == "tokens"
+                else body.logit_bias
+            )
+
+        if body.grammar is not None:
+            kwargs["grammar"] = llama_cpp.LlamaGrammar.from_string(body.grammar)
+
+        if body.min_tokens > 0:
+            _min_tokens_logits_processor = llama_cpp.LogitsProcessorList(
+                [llama_cpp.MinTokensLogitsProcessor(body.min_tokens, llama.token_eos())]
+            )
+            if "logits_processor" not in kwargs:
+                kwargs["logits_processor"] = _min_tokens_logits_processor
+            else:
+                kwargs["logits_processor"].extend(_min_tokens_logits_processor)
 
-    if body.min_tokens > 0:
-        _min_tokens_logits_processor = llama_cpp.LogitsProcessorList(
-            [llama_cpp.MinTokensLogitsProcessor(body.min_tokens, llama.token_eos())]
-        )
-        if "logits_processor" not in kwargs:
-            kwargs["logits_processor"] = _min_tokens_logits_processor
+        try:
+            iterator_or_completion: Union[
+                llama_cpp.ChatCompletion, Iterator[llama_cpp.ChatCompletionChunk]
+            ] = await run_in_threadpool(llama.create_chat_completion, **kwargs)
+        except Exception as err:
+            raise err
+
+        if isinstance(iterator_or_completion, Iterator):
+            # EAFP: It's easier to ask for forgiveness than permission
+            first_response = await run_in_threadpool(next, iterator_or_completion)
+
+            # If no exception was raised from first_response, we can assume that
+            # the iterator is valid and we can use it to stream the response.
+            def iterator() -> Iterator[llama_cpp.ChatCompletionChunk]:
+                yield first_response
+                yield from iterator_or_completion
+
+            send_chan, recv_chan = anyio.create_memory_object_stream(10)
+            return EventSourceResponse(
+                recv_chan,
+                data_sender_callable=partial(  # type: ignore
+                    get_event_publisher,
+                    request=request,
+                    inner_send_chan=send_chan,
+                    iterator=iterator(),
+                ),
+                sep="\n",
+                ping_message_factory=_ping_message_factory,
+            )
         else:
-            kwargs["logits_processor"].extend(_min_tokens_logits_processor)
-
-    try:
-        iterator_or_completion: Union[
-            llama_cpp.ChatCompletion, Iterator[llama_cpp.ChatCompletionChunk]
-        ] = await run_in_threadpool(llama.create_chat_completion, **kwargs)
-    except Exception as err:
-        await exit_stack.aclose()
-        raise err
-
-    if isinstance(iterator_or_completion, Iterator):
-        # EAFP: It's easier to ask for forgiveness than permission
-        first_response = await run_in_threadpool(next, iterator_or_completion)
-
-        # If no exception was raised from first_response, we can assume that
-        # the iterator is valid and we can use it to stream the response.
-        def iterator() -> Iterator[llama_cpp.ChatCompletionChunk]:
-            yield first_response
-            yield from iterator_or_completion
-
-        send_chan, recv_chan = anyio.create_memory_object_stream(10)
-        return EventSourceResponse(
-            recv_chan,
-            data_sender_callable=partial(  # type: ignore
-                get_event_publisher,
-                request=request,
-                inner_send_chan=send_chan,
-                iterator=iterator(),
-                on_complete=exit_stack.aclose,
-            ),
-            sep="\n",
-            ping_message_factory=_ping_message_factory,
-        )
-    else:
-        await exit_stack.aclose()
-        return iterator_or_completion
+            return iterator_or_completion
 
 
 @router.get(