diff --git a/configs/models/my_api/my_api.py b/configs/models/my_api/my_api.py
new file mode 100644
index 000000000..eedc427ab
--- /dev/null
+++ b/configs/models/my_api/my_api.py
@@ -0,0 +1,21 @@
+from opencompass.models.my_api import MyAPIModel
+api_meta_template = dict(
+    round=[
+            dict(role='HUMAN', api_role='HUMAN'),
+            dict(role='BOT', api_role='BOT', generate=True),
+    ],
+)
+models = [
+    dict(
+        type=MyAPIModel,
+        abbr='my_api',
+        path='my_api',
+        url='https://api-opencompass.jd.com/testing',
+        api_key = 'w8QA7LSXQG1q9Tc1A0X3P8PWXMkmyuPSCPtRSCg9NtM95dBlpO',
+        meta_template=api_meta_template,
+        max_out_len=100,
+        max_seq_len=2048,
+        batch_size=8,
+        run_cfg=dict(num_gpus=1, num_procs=1),
+    )
+]
\ No newline at end of file
diff --git a/opencompass/models/my_api.py b/opencompass/models/my_api.py
new file mode 100644
index 000000000..01a7cdf99
--- /dev/null
+++ b/opencompass/models/my_api.py
@@ -0,0 +1,162 @@
+import time
+from concurrent.futures import ThreadPoolExecutor
+from typing import Dict, List, Optional, Union
+
+import requests
+
+from opencompass.utils.prompt import PromptList
+
+from .base_api import BaseAPIModel
+
+PromptType = Union[PromptList, str]
+
+
+class MyAPIModel(BaseAPIModel):
+    """Model wrapper around Baichuan.
+
+    Documentation: https://platform.baichuan-ai.com/docs/api
+
+    Args:
+        path (str): The name of Baichuan model.
+            e.g. `Baichuan2-53B`
+        api_key (str): Provided api key
+        url (str): Provide url
+        query_per_second (int): The maximum queries allowed per second
+            between two consecutive calls of the API. Defaults to 1.
+        max_seq_len (int): Unused here.
+        meta_template (Dict, optional): The model's meta prompt
+            template if needed, in case the requirement of injecting or
+            wrapping of any meta instructions.
+        retry (int): Number of retires if the API call fails. Defaults to 2.
+    """
+
+    def __init__(
+        self,
+        path: str,
+        api_key: str,
+        url: str,
+        query_per_second: int = 2,
+        max_seq_len: int = 2048,
+        meta_template: Optional[Dict] = None,
+        retry: int = 2,
+        generation_kwargs: Dict = {
+            'temperature': 0.3,
+            'top_p': 0.85,
+            'top_k': 5,
+            'with_search_enhance': False,
+            'stream': False,
+            'do_sample':False,
+        }):  # noqa E125
+        super().__init__(path=path,
+                         max_seq_len=max_seq_len,
+                         query_per_second=query_per_second,
+                         meta_template=meta_template,
+                         retry=retry,
+                         generation_kwargs=generation_kwargs)
+        
+        self.api_key = api_key
+        self.url = url
+        self.model = path
+        
+    def generate(
+        self,
+        inputs: List[str or PromptList],
+        max_out_len: int = 512,
+    ) -> List[str]:
+        """Generate results given a list of inputs.
+
+        Args:
+            inputs (List[str or PromptList]): A list of strings or PromptDicts.
+                The PromptDict should be organized in OpenCompass'
+                API format.
+            max_out_len (int): The maximum length of the output.
+
+        Returns:
+            List[str]: A list of generated strings.
+        """
+
+        with ThreadPoolExecutor() as executor:
+            results = list(
+                executor.map(self._generate, inputs,
+                             [max_out_len] * len(inputs)))
+        self.flush()
+        return results
+
+    def _generate(
+        self,
+        input: str or PromptList,
+        max_out_len: int = 512,
+    ) -> str:
+        """Generate results given an input.
+
+        Args:
+            inputs (str or PromptList): A string or PromptDict.
+                The PromptDict should be organized in OpenCompass'
+                API format.
+            max_out_len (int): The maximum length of the output.
+
+        Returns:
+            str: The generated string.
+        """
+
+        assert isinstance(input, (str, PromptList))
+
+        if isinstance(input, str):
+            messages = [{'role': 'user', 'content': input}]
+        else:
+            messages = []
+            for item in input:
+                msg = {'content': item['prompt']}
+                if item['role'] == 'HUMAN':
+                    msg['role'] = 'user'
+                elif item['role'] == 'BOT':
+                    msg['role'] = 'assistant'
+
+                messages.append(msg)
+
+        data = {'model': self.model, 'messages': messages}
+        data.update(self.generation_kwargs)
+        
+        headers = {
+            'Content-Type': 'application/json',
+            'api-key': self.api_key,
+        }
+
+        max_num_retries = 0
+        while max_num_retries < self.retry:
+            self.acquire()
+            try:
+                raw_response = requests.request('POST',
+                                                url=self.url,
+                                                headers=headers,
+                                                json=data)
+                response = raw_response.json()
+            except Exception as err:
+                print('Request Error:{}'.format(err))
+                time.sleep(3)
+                continue
+
+            self.release()
+            # print(response.keys())
+            # print(response['choices'][0]['message']['content'])
+            if response is None:
+                print('Connection error, reconnect.')
+                # if connect error, frequent requests will casuse
+                # continuous unstable network, therefore wait here
+                # to slow down the request
+                self.wait()
+                continue
+            if raw_response.status_code == 200:
+
+                # msg = response['choices'][0]['message']['content']
+                msg = response
+                return msg
+
+            if raw_response.status_code != 200:
+                print(raw_response.json())
+                time.sleep(1)
+                continue
+            print(response)
+            max_num_retries += 1
+
+        raise RuntimeError(response)