Fix the double BOS problem in the HF chat template (#888)

python/sglang/srt/openai_api/adapter.py

@@ -594,7 +594,7 @@ async def v1_completions(tokenizer_manager, raw_request: Request):
 
 def v1_chat_generate_request(all_requests, tokenizer_manager):
 
-    texts = []
+    input_ids = []
     sampling_params_list = []
     image_data_list = []
     return_logprobs = []
@@ -608,8 +608,8 @@ def v1_chat_generate_request(all_requests, tokenizer_manager):
         if not isinstance(request.messages, str):
             # Apply chat template and its stop strings.
             if chat_template_name is None:
-                prompt = tokenizer_manager.tokenizer.apply_chat_template(
-                    request.messages, tokenize=False, add_generation_prompt=True
+                prompt_ids = tokenizer_manager.tokenizer.apply_chat_template(
+                    request.messages, tokenize=True, add_generation_prompt=True
                 )
                 stop = request.stop
                 image_data = None
@@ -623,12 +623,13 @@ def v1_chat_generate_request(all_requests, tokenizer_manager):
                         stop.append(request.stop)
                     else:
                         stop.extend(request.stop)
+                prompt_ids = tokenizer_manager.tokenizer.encode(prompt)
         else:
             # Use the raw prompt and stop strings if the messages is already a string.
             prompt = request.messages
             stop = request.stop
             image_data = None
-        texts.append(prompt)
+        input_ids.append(prompt_ids)
         return_logprobs.append(request.logprobs)
         top_logprobs_nums.append(request.top_logprobs)
         sampling_params_list.append(
@@ -645,13 +646,13 @@ def v1_chat_generate_request(all_requests, tokenizer_manager):
         )
         image_data_list.append(image_data)
     if len(all_requests) == 1:
-        texts = texts[0]
+        input_ids = input_ids[0]
         sampling_params_list = sampling_params_list[0]
         image_data = image_data_list[0]
         return_logprobs = return_logprobs[0]
         top_logprobs_nums = top_logprobs_nums[0]
     adapted_request = GenerateReqInput(
-        text=texts,
+        input_ids=input_ids,
         image_data=image_data,
         sampling_params=sampling_params_list,
         return_logprob=return_logprobs,