add tools into TokenizeChatRequest (#18187)

Signed-off-by: yangxia <yangxiast@gmail.com>

tests/entrypoints/openai/test_tokenization.py

@@ -145,6 +145,83 @@ async def test_tokenize_chat(
                 }
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "model_name,tokenizer_name",
+    [(MODEL_NAME, MODEL_NAME), ("zephyr-lora2", "zephyr-lora2")],
+    indirect=["tokenizer_name"],
+)
+async def test_tokenize_chat_with_tools(
+    server: RemoteOpenAIServer,
+    model_name: str,
+    tokenizer_name: str,
+):
+    tokenizer = get_tokenizer(tokenizer_name=tokenizer_name,
+                              tokenizer_mode="fast")
+
+    for add_generation in [False, True]:
+        for add_special in [False, True]:
+            conversation = [{
+                "role":
+                "user",
+                "content":
+                "What's the weather like in Paris today?",
+            }]
+
+            tools = [{
+                "type": "function",
+                "function": {
+                    "name": "get_weather",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string"
+                            }
+                        },
+                    },
+                },
+            }]
+
+            for continue_final in [False, True]:
+                if add_generation and continue_final:
+                    continue
+                if continue_final:
+                    conversation.append({
+                        "role": "assistant",
+                        "content": "Sure,"
+                    })
+
+                prompt = tokenizer.apply_chat_template(
+                    add_generation_prompt=add_generation,
+                    continue_final_message=continue_final,
+                    conversation=conversation,
+                    tools=tools,
+                    tokenize=False,
+                )
+                tokens = tokenizer.encode(prompt,
+                                          add_special_tokens=add_special)
+
+                response = requests.post(
+                    server.url_for("tokenize"),
+                    json={
+                        "add_generation_prompt": add_generation,
+                        "continue_final_message": continue_final,
+                        "add_special_tokens": add_special,
+                        "messages": conversation,
+                        "model": model_name,
+                        "tools": tools,
+                    },
+                )
+                response.raise_for_status()
+
+                assert response.json() == {
+                    "tokens": tokens,
+                    "count": len(tokens),
+                    "max_model_len": 8192,
+                }
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     "model_name,tokenizer_name",

vllm/entrypoints/openai/protocol.py

@@ -1593,6 +1593,10 @@ class TokenizeChatRequest(OpenAIBaseModel):
         default=None,
         description=("Additional kwargs to pass to the HF processor."),
     )
+    tools: Optional[list[ChatCompletionToolsParam]] = Field(
+        default=None,
+        description=("A list of tools the model may call."),
+    )
 
     @model_validator(mode="before")
     @classmethod

vllm/entrypoints/openai/serving_tokenization.py

@@ -65,6 +65,8 @@ class OpenAIServingTokenization(OpenAIServing):
             tokenizer = await self.engine_client.get_tokenizer(lora_request)
 
             if isinstance(request, TokenizeChatRequest):
+                tool_dicts = (None if request.tools is None else
+                              [tool.model_dump() for tool in request.tools])
                 (
                     _,
                     request_prompts,
@@ -73,6 +75,7 @@ class OpenAIServingTokenization(OpenAIServing):
                     request,
                     tokenizer,
                     request.messages,
+                    tool_dicts=tool_dicts,
                     chat_template=request.chat_template or self.chat_template,
                     chat_template_content_format=self.
                     chat_template_content_format,