Repository: vllm-project/vllm
Issue category: Bug Report

Issue:
[Bug]: When apply continue_final_message, encounter: got multiple values for keyword argument
### Your current environment


vLLM Version: 0.6.3.post2.dev256+g4be3a451
<details>
<summary>The output of `python collect_env.py`</summary>

```text
Collecting environment information...                                                                                                                                                                       INFO 11-06 09:39:21 importing.py:15] Triton not installed or not compatible; certain GPU-related functions will not be available.                                                                           PyTorch version: 2.4.0+cpu                                                                                                                                                                                  
Is debug build: False                              
CUDA used to build PyTorch: None                   
ROCM used to build PyTorch: N/A                                                                       
                                                                                                      
OS: Ubuntu 22.04.4 LTS (x86_64)                                                                       
GCC version: (Ubuntu 12.3.0-1ubuntu1~22.04) 12.3.0                                                    
Clang version: Could not collect                   
CMake version: version 3.30.5                      
Libc version: glibc-2.35                           
                                                   
Python version: 3.10.12 (main, Jul 29 2024, 16:56:48) [GCC 11.4.0] (64-bit runtime)                   
Python platform: Linux-5.10.25-nvidia-gpu-x86_64-with-glibc2.35                                       
Is CUDA available: False                                                                              
CUDA runtime version: No CUDA                      
CUDA_MODULE_LOADING set to: N/A                    
GPU models and configuration: No CUDA              
Nvidia driver version: No CUDA                     
cuDNN version: No CUDA                             
HIP runtime version: N/A                           
MIOpen runtime version: N/A

CPU:
Architecture:                    x86_64
CPU op-mode(s):                  32-bit, 64-bit
Address sizes:                   46 bits physical, 57 bits virtual
Byte Order:                      Little Endian
CPU(s):                          17
On-line CPU(s) list:             0-16
Vendor ID:                       GenuineIntel
Model name:                      Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
CPU family:                      6
Model:                           106
Thread(s) per core:              1
Core(s) per socket:              1
Socket(s):                       17
Stepping:                        6
BogoMIPS:                        4000.00
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves wbnoinvd arat avx512vbmi umip pku avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid md_clear arch_capabilities
Hypervisor vendor:               KVM
Virtualization type:             full
L1d cache:                       544 KiB (17 instances)
L1i cache:                       544 KiB (17 instances)
L2 cache:                        68 MiB (17 instances)
L3 cache:                        272 MiB (17 instances)
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:        Mitigation; Enhanced IBRS, IBPB conditional, RSB filling
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected

Versions of relevant libraries:
[pip3] intel_extension_for_pytorch==2.4.0
[pip3] numpy==1.26.4
[pip3] pyzmq==26.2.0
[pip3] torch==2.4.0+cpu
[pip3] torchvision==0.19.0+cpu
[pip3] transformers==4.46.2
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.3.post2.dev256+g4be3a451
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect
```

</details>


### Model Input Dumps

_No response_

### 🐛 Describe the bug

Reproduce using curl
```bash
curl -X POST "http://39.105.21.95:12481/v1/chat/completions" \
     -H "Content-Type: application/json" \
     -d '{
           "model": "meta-llama/Meta-Llama-3-8B-Instruct",
           "messages": [
             {
               "role": "user",
               "content": "tell me a common saying"
             },
             {
               "role": "assistant",
               "content": "Here is a common saying about apple. An apple a day, keeps"
             }
           ],
           "add_generation_prompt": false, "chat_template_kwargs":{"continue_final_message": true}
         }'

Internal Server Error%  
```


Error message on server
```bash
  File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/api_server.py", line 338, in create_chat_completion
    generator = await handler.create_chat_completion(request, raw_request)
  File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/serving_chat.py", line 140, in create_chat_completion
    ) = await self._preprocess_chat(
  File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/serving_engine.py", line 460, in _preprocess_chat
    request_prompt = apply_hf_chat_template(
TypeError: vllm.entrypoints.chat_utils.apply_hf_chat_template() got multiple values for keyword argument 'continue_final_message'
```

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Hints:
You should pass `continue_final_message` directly (like how you did it with `add_generation_prompt`) instead of using separate `chat_template_kwargs`.
Previously, it could only be called in `chat_template_kwargs`, there is already a lot of code to support the “continuation generating” in this way, can vLLM support both options?
I see, feel free to open a PR to support both methods.

Patch:
diff --git a/vllm/entrypoints/openai/serving_engine.py b/vllm/entrypoints/openai/serving_engine.py
index e7aeac8f8c018..e31dc2ced61fb 100644
--- a/vllm/entrypoints/openai/serving_engine.py
+++ b/vllm/entrypoints/openai/serving_engine.py
@@ -443,29 +443,28 @@ async def _preprocess_chat(
             tokenizer,
         )
 
+        _chat_template_kwargs: Dict[str, Any] = dict(
+            chat_template=chat_template,
+            add_generation_prompt=add_generation_prompt,
+            continue_final_message=continue_final_message,
+            tools=tool_dicts,
+            documents=documents,
+        )
+        _chat_template_kwargs.update(chat_template_kwargs or {})
+
         request_prompt: Union[str, List[int]]
         is_mistral_tokenizer = isinstance(tokenizer, MistralTokenizer)
         if is_mistral_tokenizer:
             request_prompt = apply_mistral_chat_template(
                 tokenizer,
                 messages=messages,
-                chat_template=chat_template,
-                add_generation_prompt=add_generation_prompt,
-                continue_final_message=continue_final_message,
-                tools=tool_dicts,
-                documents=documents,
-                **(chat_template_kwargs or {}),
+                **_chat_template_kwargs,
             )
         else:
             request_prompt = apply_hf_chat_template(
                 tokenizer,
                 conversation=conversation,
-                chat_template=chat_template,
-                add_generation_prompt=add_generation_prompt,
-                continue_final_message=continue_final_message,
-                tools=tool_dicts,
-                documents=documents,
-                **(chat_template_kwargs or {}),
+                **_chat_template_kwargs,
             )
 
         mm_data = await mm_data_future


Test patch: