Feat: Add support for response_format field in OpenAI Spec

src/litserve/examples/openai_spec_example.py

@@ -45,6 +45,14 @@ def encode_response(self, output):
         )
 
 
+class TestAPIWithStructuredOutput(TestAPI):
+    def encode_response(self, output):
+        yield ChatMessage(
+            role="assistant",
+            content='{"name": "Science Fair", "date": "Friday", "participants": ["Alice", "Bob"]}',
+        )
+
+
 class OpenAIBatchContext(ls.LitAPI):
     def setup(self, device: str) -> None:
         self.model = None

src/litserve/specs/openai.py

@@ -20,7 +20,7 @@
 import uuid
 from collections import deque
 from enum import Enum
-from typing import AsyncGenerator, Dict, Iterator, List, Literal, Optional, Union
+from typing import Annotated, AsyncGenerator, Dict, Iterator, List, Literal, Optional, Union
 
 from fastapi import BackgroundTasks, HTTPException, Request, Response
 from fastapi.responses import StreamingResponse
@@ -105,6 +105,31 @@ class ToolCall(BaseModel):
     function: FunctionCall
 
 
+class ResponseFormatText(BaseModel):
+    type: Literal["text"]
+
+
+class ResponseFormatJSONObject(BaseModel):
+    type: Literal["json_object"]
+
+
+class JSONSchema(BaseModel):
+    name: str
+    description: Optional[str] = None
+    schema: Optional[Dict[str, object]] = None
+    strict: Optional[bool] = False
+
+
+class ResponseFormatJSONSchema(BaseModel):
+    json_schema: JSONSchema
+    type: Literal["json_schema"]
+
+
+ResponseFormat = Annotated[
+    Union[ResponseFormatText, ResponseFormatJSONObject, ResponseFormatJSONSchema], "ResponseFormat"
+]
+
+
 class ChatMessage(BaseModel):
     role: str
     content: Union[str, List[Union[TextContent, ImageContent]]]
@@ -138,6 +163,7 @@ class ChatCompletionRequest(BaseModel):
     user: Optional[str] = None
     tools: Optional[List[Tool]] = None
     tool_choice: Optional[ToolChoice] = ToolChoice.auto
+    response_format: Optional[ResponseFormat] = None
 
 
 class ChatCompletionResponseChoice(BaseModel):

tests/conftest.py

@@ -236,3 +236,43 @@ def openai_request_data_with_tools():
         "frequency_penalty": 0,
         "user": "string",
     }
+
+
+@pytest.fixture()
+def openai_request_data_with_response_format():
+    return {
+        "model": "lit",
+        "messages": [
+            {
+                "role": "system",
+                "content": "Extract the event information.",
+            },
+            {"role": "user", "content": "Alice and Bob are going to a science fair on Friday."},
+        ],
+        "response_format": {
+            "type": "json_schema",
+            "json_schema": {
+                "name": "calendar_event",
+                "schema": {
+                    "type": "object",
+                    "properties": {
+                        "name": {"type": "string"},
+                        "date": {"type": "string"},
+                        "participants": {"type": "array", "items": {"type": "string"}},
+                    },
+                    "required": ["name", "date", "participants"],
+                    "additionalProperties": "false",
+                },
+                "strict": "true",
+            },
+        },
+        "temperature": 0.7,
+        "top_p": 1,
+        "n": 1,
+        "max_tokens": 0,
+        "stop": "string",
+        "stream": False,
+        "presence_penalty": 0,
+        "frequency_penalty": 0,
+        "user": "string",
+    }

tests/e2e/default_openaispec_response_format.py

@@ -0,0 +1,7 @@
+import litserve as ls
+from litserve import OpenAISpec
+from litserve.examples.openai_spec_example import TestAPIWithStructuredOutput
+
+if __name__ == "__main__":
+    server = ls.LitServer(TestAPIWithStructuredOutput(), spec=OpenAISpec())
+    server.run()

tests/e2e/test_e2e.py

@@ -244,3 +244,54 @@ def test_e2e_openai_with_batching(openai_request_data):
     assert response.choices[0].message.content == (
         "Hi! It's nice to meet you. Is there something I can " "help you with or would you like to chat? "
     ), f"Server didn't return expected output OpenAI client output: {response}"
+
+
+@e2e_from_file("tests/e2e/default_openaispec_response_format.py")
+def test_openai_parity_with_response_format():
+    client = OpenAI(base_url="http://127.0.0.1:8000/v1", api_key="lit")
+    messages = [
+        {
+            "role": "system",
+            "content": "Extract the event information.",
+        },
+        {"role": "user", "content": "Alice and Bob are going to a science fair on Friday."},
+    ]
+    response_format = {
+        "type": "json_schema",
+        "json_schema": {
+            "name": "calendar_event",
+            "schema": {
+                "type": "object",
+                "properties": {
+                    "name": {"type": "string"},
+                    "date": {"type": "string"},
+                    "participants": {"type": "array", "items": {"type": "string"}},
+                },
+                "required": ["name", "date", "participants"],
+                "additionalProperties": "false",
+            },
+            "strict": "true",
+        },
+    }
+    output = '{"name": "Science Fair", "date": "Friday", "participants": ["Alice", "Bob"]}'
+    response = client.chat.completions.create(
+        model="lit",
+        messages=messages,
+        response_format=response_format,
+    )
+    assert response.choices[0].message.content == output, (
+        f"Server didn't return expected output" f"\nOpenAI client output: {response}"
+    )
+
+    response = client.chat.completions.create(
+        model="lit",
+        messages=messages,
+        response_format=response_format,
+        stream=True,
+    )
+
+    expected_outputs = [output, None]
+    for r, expected_out in zip(response, expected_outputs):
+        assert r.choices[0].delta.content == expected_out, (
+            f"Server didn't return expected output.\n" f"OpenAI client output: {r}"
+        )

tests/test_specs.py

@@ -12,21 +12,23 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import litserve as ls
 import pytest
 from asgi_lifespan import LifespanManager
 from fastapi import HTTPException
 from httpx import AsyncClient
 from litserve.examples.openai_spec_example import (
+    OpenAIBatchingWithUsage,
+    OpenAIWithUsage,
+    OpenAIWithUsageEncodeResponse,
     TestAPI,
     TestAPIWithCustomEncode,
+    TestAPIWithStructuredOutput,
     TestAPIWithToolCalls,
-    OpenAIWithUsage,
-    OpenAIBatchingWithUsage,
-    OpenAIWithUsageEncodeResponse,
 )
+from litserve.specs.openai import ChatMessage, OpenAISpec
+
 from tests.conftest import wrap_litserve_start
-from litserve.specs.openai import OpenAISpec, ChatMessage
-import litserve as ls
 
 
 @pytest.mark.asyncio()
@@ -117,6 +119,20 @@ async def test_openai_spec_with_tools(openai_request_data_with_tools):
             ], "LitAPI predict response should match with the generated output"
 
 
+@pytest.mark.asyncio()
+async def test_openai_spec_with_response_format(openai_request_data_with_response_format):
+    spec = OpenAISpec()
+    server = ls.LitServer(TestAPIWithStructuredOutput(), spec=spec)
+    with wrap_litserve_start(server) as server:
+        async with LifespanManager(server.app) as manager, AsyncClient(app=manager.app, base_url="http://test") as ac:
+            resp = await ac.post("/v1/chat/completions", json=openai_request_data_with_response_format, timeout=10)
+            assert resp.status_code == 200, "Status code should be 200"
+            assert (
+                resp.json()["choices"][0]["message"]["content"]
+                == '{"name": "Science Fair", "date": "Friday", "participants": ["Alice", "Bob"]}'
+            ), "LitAPI predict response should match with the generated output"
+
+
 class IncorrectAPI1(ls.LitAPI):
     def setup(self, device):
         self.model = None