fix: improve the logic of json_schema and refine the reasoning extraction logic for reasoning model (#1044)

* fix: fix a small bug in response_schema

* feat: support response_format parameter in chat completion

* fix: fix between json_mode and response_format

* Update base.py

* Update deprec.py

* add unittest and refine logic

* fix the reasoning extraction logic and refine prompt for deepseek adaptation

* refactor: introduce workflow_check and streamline task parsing

* refine prompt

---------

Co-authored-by: Young <afe.young@gmail.com>

test/oai/test_completion.py

@@ -1,9 +1,20 @@
 import json
 import unittest
+from typing import Any, Dict, List, Union
+
+from pydantic import BaseModel, Field
 
 from rdagent.oai.llm_utils import APIBackend
 
 
+class TestPersonModel(BaseModel):
+    """This is a test Pydantic model"""
+
+    name: str = Field(description="name")
+    age: int = Field(description="age")
+    skills: List[str] = Field(description="skills")
+
+
 class TestChatCompletion(unittest.TestCase):
     def test_chat_completion(self) -> None:
         system_prompt = "You are a helpful assistant."
@@ -34,6 +45,57 @@ class TestChatCompletion(unittest.TestCase):
         assert token is not None
         assert isinstance(token, int)
 
+    def test_json_mode_with_specific_target_type(self) -> None:
+        """Test json_mode=True with specific json_target_type"""
+        system_prompt = "You are a helpful assistant. Please respond according to requirements."
+        user_prompt = "Generate programmer information including name, age, and skills list"
+
+        response = APIBackend().build_messages_and_create_chat_completion(
+            system_prompt=system_prompt,
+            user_prompt=user_prompt,
+            json_mode=True,
+            json_target_type=Dict[str, Union[str, int, List[str]]],
+        )
+
+        # Verify response format
+        assert response is not None
+        assert isinstance(response, str)
+
+        # Verify JSON format
+        parsed = json.loads(response)
+        assert isinstance(parsed, dict)
+
+    def test_response_format_with_basemodel(self) -> None:
+        """Test response_format with BaseModel (if supported)"""
+        backend = APIBackend()
+
+        system_prompt = "You are a helpful assistant. Please respond according to requirements."
+        user_prompt = "Generate programmer information including name, age, and skills list"
+
+        if backend.supports_response_schema():
+            # Use BaseModel when response_schema is supported
+            response = backend.build_messages_and_create_chat_completion(
+                system_prompt=system_prompt,
+                user_prompt=user_prompt,
+                response_format=TestPersonModel,
+            )
+        else:
+            # Use dict + json_target_type when not supported
+            response = backend.build_messages_and_create_chat_completion(
+                system_prompt=system_prompt,
+                user_prompt=user_prompt,
+                response_format={"type": "json_object"},
+                json_target_type=Dict[str, Union[str, int, List[str]]],
+            )
+
+        # Verify response format
+        assert response is not None
+        assert isinstance(response, str)
+
+        # Verify JSON format
+        parsed = json.loads(response)
+        assert isinstance(parsed, dict)
+
 
 if __name__ == "__main__":
     unittest.main()