diff --git a/example/llms/test_apis.py b/example/llms/test_apis.py
new file mode 100644
index 00000000..8eaaaba9
--- /dev/null
+++ b/example/llms/test_apis.py
@@ -0,0 +1,53 @@
+import os
+import sys
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+
+from llm4ad.tools.llm.llm_api_qwen import QwenAPI
+from llm4ad.tools.llm.llm_api_zhipu import ZhipuAPI
+from llm4ad.tools.llm.llm_api_volcengine import VolcengineAPI
+from llm4ad.tools.llm.llm_api_baiduqianfan import BaiduQianfanAPI
+from llm4ad.tools.llm.llm_api_tencentcloud import TencentCloudAPI
+
+
+def main():
+    # Qwen
+    llm = QwenAPI(
+        key='your-api-key',
+        model='qwen-plus',
+        timeout=120
+    )
+
+    # Zhipu AI
+    # llm = ZhipuAPI(
+    #     key='your-api-key',
+    #     model='GLM-5.2',
+    #     timeout=120
+    # )
+
+    # Volcengine Ark
+    # llm = VolcengineAPI(
+    #     key='your-api-key',
+    #     model='doubao-seed-character-260628',
+    #     timeout=120
+    # )
+
+    # Baidu Qianfan
+    # llm = BaiduQianfanAPI(
+    #     key='your-api-key',
+    #     model='ernie-5.1',
+    #     timeout=120
+    # )
+
+    # Tencent Cloud
+    # llm = TencentCloudAPI(
+    #     key='your-api-key',
+    #     model='hy3-preview',
+    #     timeout=120
+    # )
+
+    print(llm.draw_sample('hello'))
+
+
+if __name__ == '__main__':
+    main()
diff --git a/llm4ad/tools/llm/llm_api_baiduqianfan.py b/llm4ad/tools/llm/llm_api_baiduqianfan.py
new file mode 100644
index 00000000..96c81f30
--- /dev/null
+++ b/llm4ad/tools/llm/llm_api_baiduqianfan.py
@@ -0,0 +1,154 @@
+# This file is part of the LLM4AD project (https://github.com/Optima-CityU/llm4ad).
+# Last Revision: 2026/7/5
+#
+# ------------------------------- Copyright --------------------------------
+# Copyright (c) 2025 Optima Group.
+#
+# Permission is granted to use the LLM4AD platform for research purposes.
+# All publications, software, or other works that utilize this platform
+# or any part of its codebase must acknowledge the use of "LLM4AD" and
+# cite the following reference:
+#
+# Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang,
+# Zhichao Lu, and Qingfu Zhang, "LLM4AD: A Platform for Algorithm Design
+# with Large Language Model," arXiv preprint arXiv:2412.17287 (2024).
+#
+# For inquiries regarding commercial use or licensing, please contact
+# http://www.llm4ad.com/contact.html
+# --------------------------------------------------------------------------
+
+from __future__ import annotations
+
+import http.client
+import json
+import time
+from typing import Any
+import traceback
+from ...base import LLM
+
+
+class BaiduQianfanAPI(LLM):
+    def __init__(self, host='qianfan.baidubce.com', key=None, model=None,
+                 path='/v2/chat/completions', timeout=60, **kwargs):
+        """Baidu Qianfan API
+        Args:
+            host   : host name. please note that the host name does not include 'https://'
+            key    : API key.
+            model  : LLM model name.
+            path   : API path for chat completions.
+            timeout: API timeout.
+        """
+        if key is None:
+            raise ValueError('BaiduQianfanAPI requires key.')
+        if model is None:
+            raise ValueError('BaiduQianfanAPI requires model.')
+        super().__init__(**kwargs)
+        self._host = host
+        self._path = path
+        self._key = key
+        self._model = model
+        self._timeout = timeout
+        self._kwargs = kwargs
+        self._cumulative_error = 0
+
+    def draw_sample(self, prompt: str | Any, *args, **kwargs) -> str:
+        """
+        Sends a request to the LLM and retrieves the generated response.
+
+        This method supports multiple input formats for backward compatibility:
+        1. Explicit 'messages' list via kwargs.
+        2. A message list passed directly as the 'prompt'.
+        3. Multimodal inputs (text + base64 images).
+        4. Simple string prompts.
+
+        Args:
+            prompt: The text prompt or a list of message dictionaries.
+            **kwargs: Can include 'image64s' (list of base64 strings) or 'messages'.
+
+        Returns:
+            The string content of the LLM's response.
+        """
+        image64s = kwargs.get('image64s', None)  # List[str]
+        messages_input = kwargs.get('messages', None)
+
+        # --- 1. Priority: Explicit messages list ---
+        if messages_input is not None:
+            if isinstance(messages_input, dict):
+                messages = [messages_input]
+            else:
+                messages = messages_input
+
+        # --- 2. Legacy Support: prompt passed as a pre-constructed list ---
+        elif not isinstance(prompt, str):
+            messages = prompt
+
+        # --- 3. Construction from String + Optional Images ---
+        else:
+            text_content = prompt.strip()
+
+            if image64s:
+                # Construct multimodal content structure
+                content = [{
+                    "type": "text",
+                    "text": text_content
+                }]
+                for image in image64s:
+                    content.append({
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/png;base64,{image}",
+                        }
+                    })
+                messages = [{'role': 'user', 'content': content}]
+
+            else:
+                # Construct standard text-only message
+                messages = [{'role': 'user', 'content': text_content}]
+
+        # Retry loop for handling network or API transient errors
+        while True:
+            try:
+                conn = http.client.HTTPSConnection(self._host, timeout=self._timeout)
+
+                # Prepare standard OpenAI-compatible payload
+                payload = json.dumps({
+                    'max_tokens': self._kwargs.get('max_tokens', 8192),
+                    'top_p': self._kwargs.get('top_p', None),
+                    'temperature': self._kwargs.get('temperature', 1.0),
+                    'model': self._model,
+                    'messages': messages
+                })
+                headers = {
+                    'Authorization': f'Bearer {self._key}',
+                    'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
+                    'Content-Type': 'application/json'
+                }
+                conn.request('POST', self._path, payload, headers)
+                res = conn.getresponse()
+                data = res.read().decode('utf-8')
+                data = json.loads(data)
+
+                # Extract content from the standard response format
+                response = data['choices'][0]['message']['content']
+                # Reset error counter on success
+                if self.debug_mode:
+                    self._cumulative_error = 0
+                return response
+
+            except Exception as e:
+                self._cumulative_error += 1
+
+                # In debug mode, crash after consecutive failures to allow debugging
+                if self.debug_mode:
+                    if self._cumulative_error == 10:
+                        raise RuntimeError(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                                           f'You may check your API host, path, API key, and model.')
+                else:
+                    print(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                          f'You may check your API host, path, API key, and model.')
+                    time.sleep(2)
+                continue
+
+
+class QianfanAPI(BaiduQianfanAPI):
+    """Alias for BaiduQianfanAPI."""
diff --git a/llm4ad/tools/llm/llm_api_qwen.py b/llm4ad/tools/llm/llm_api_qwen.py
new file mode 100644
index 00000000..f66903f6
--- /dev/null
+++ b/llm4ad/tools/llm/llm_api_qwen.py
@@ -0,0 +1,158 @@
+# This file is part of the LLM4AD project (https://github.com/Optima-CityU/llm4ad).
+# Last Revision: 2026/7/5
+#
+# ------------------------------- Copyright --------------------------------
+# Copyright (c) 2025 Optima Group.
+#
+# Permission is granted to use the LLM4AD platform for research purposes.
+# All publications, software, or other works that utilize this platform
+# or any part of its codebase must acknowledge the use of "LLM4AD" and
+# cite the following reference:
+#
+# Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang,
+# Zhichao Lu, and Qingfu Zhang, "LLM4AD: A Platform for Algorithm Design
+# with Large Language Model," arXiv preprint arXiv:2412.17287 (2024).
+#
+# For inquiries regarding commercial use or licensing, please contact
+# http://www.llm4ad.com/contact.html
+# --------------------------------------------------------------------------
+
+from __future__ import annotations
+
+import http.client
+import json
+import time
+from typing import Any
+import traceback
+from ...base import LLM
+
+
+class QwenAPI(LLM):
+    def __init__(self, host='dashscope.aliyuncs.com', key=None, model=None,
+                 path='/compatible-mode/v1/chat/completions', timeout=60, **kwargs):
+        """Qwen API
+        Args:
+            host   : host name. please note that the host name does not include 'https://'
+            key    : API key.
+            model  : LLM model name.
+            path   : API path for chat completions.
+            timeout: API timeout.
+        """
+        if key is None:
+            raise ValueError('QwenAPI requires key.')
+        if model is None:
+            raise ValueError('QwenAPI requires model.')
+        super().__init__(**kwargs)
+        self._host = host
+        self._path = path
+        self._key = key
+        self._model = model
+        self._timeout = timeout
+        self._kwargs = kwargs
+        self._cumulative_error = 0
+
+    def draw_sample(self, prompt: str | Any, *args, **kwargs) -> str:
+        """
+        Sends a request to the LLM and retrieves the generated response.
+
+        This method supports multiple input formats for backward compatibility:
+        1. Explicit 'messages' list via kwargs.
+        2. A message list passed directly as the 'prompt'.
+        3. Multimodal inputs (text + base64 images).
+        4. Simple string prompts.
+
+        Args:
+            prompt: The text prompt or a list of message dictionaries.
+            **kwargs: Can include 'image64s' (list of base64 strings) or 'messages'.
+
+        Returns:
+            The string content of the LLM's response.
+        """
+        image64s = kwargs.get('image64s', None)  # List[str]
+        messages_input = kwargs.get('messages', None)
+
+        # --- 1. Priority: Explicit messages list ---
+        if messages_input is not None:
+            if isinstance(messages_input, dict):
+                messages = [messages_input]
+            else:
+                messages = messages_input
+
+        # --- 2. Legacy Support: prompt passed as a pre-constructed list ---
+        elif not isinstance(prompt, str):
+            messages = prompt
+
+        # --- 3. Construction from String + Optional Images ---
+        else:
+            text_content = prompt.strip()
+
+            if image64s:
+                # Construct multimodal content structure
+                content = [{
+                    "type": "text",
+                    "text": text_content
+                }]
+                for image in image64s:
+                    content.append({
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/png;base64,{image}",
+                        }
+                    })
+                messages = [{'role': 'user', 'content': content}]
+
+            else:
+                # Construct standard text-only message
+                messages = [{'role': 'user', 'content': text_content}]
+
+        # Retry loop for handling network or API transient errors
+        while True:
+            try:
+                conn = http.client.HTTPSConnection(self._host, timeout=self._timeout)
+
+                # Prepare standard OpenAI-compatible payload
+                payload = json.dumps({
+                    'max_tokens': self._kwargs.get('max_tokens', 8192),
+                    'top_p': self._kwargs.get('top_p', None),
+                    'temperature': self._kwargs.get('temperature', 1.0),
+                    'model': self._model,
+                    'messages': messages
+                })
+                headers = {
+                    'Authorization': f'Bearer {self._key}',
+                    'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
+                    'Content-Type': 'application/json'
+                }
+                conn.request('POST', self._path, payload, headers)
+                res = conn.getresponse()
+                data = res.read().decode('utf-8')
+                data = json.loads(data)
+
+                # Extract content from the standard response format
+                response = data['choices'][0]['message']['content']
+                # Reset error counter on success
+                if self.debug_mode:
+                    self._cumulative_error = 0
+                return response
+
+            except Exception as e:
+                self._cumulative_error += 1
+
+                # In debug mode, crash after consecutive failures to allow debugging
+                if self.debug_mode:
+                    if self._cumulative_error == 10:
+                        raise RuntimeError(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                                           f'You may check your API host, path, API key, and model.')
+                else:
+                    print(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                          f'You may check your API host, path, API key, and model.')
+                    time.sleep(2)
+                continue
+
+
+class DashScopeAPI(QwenAPI):
+    """Alias for QwenAPI."""
+
+
+class BailianAPI(QwenAPI):
+    """Alias for QwenAPI."""
diff --git a/llm4ad/tools/llm/llm_api_tencentcloud.py b/llm4ad/tools/llm/llm_api_tencentcloud.py
new file mode 100644
index 00000000..a24a00c4
--- /dev/null
+++ b/llm4ad/tools/llm/llm_api_tencentcloud.py
@@ -0,0 +1,152 @@
+# This file is part of the LLM4AD project (https://github.com/Optima-CityU/llm4ad).
+# Last Revision: 2026/7/5
+#
+# ------------------------------- Copyright --------------------------------
+# Copyright (c) 2025 Optima Group.
+#
+# Permission is granted to use the LLM4AD platform for research purposes.
+# All publications, software, or other works that utilize this platform
+# or any part of its codebase must acknowledge the use of "LLM4AD" and
+# cite the following reference:
+#
+# Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang,
+# Zhichao Lu, and Qingfu Zhang, "LLM4AD: A Platform for Algorithm Design
+# with Large Language Model," arXiv preprint arXiv:2412.17287 (2024).
+#
+# For inquiries regarding commercial use or licensing, please contact
+# http://www.llm4ad.com/contact.html
+# --------------------------------------------------------------------------
+
+from __future__ import annotations
+
+import http.client
+import json
+import time
+from typing import Any
+import traceback
+from ...base import LLM
+
+
+class TencentCloudAPI(LLM):
+    def __init__(self, host='tokenhub.tencentmaas.com', key=None, model=None,
+                 path='/v1/chat/completions', timeout=60, **kwargs):
+        """Tencent Cloud API
+        Args:
+            host   : host name. please note that the host name does not include 'https://'
+            key    : API key.
+            model  : LLM model name.
+            path   : API path for chat completions.
+            timeout: API timeout.
+        """
+        if key is None:
+            raise ValueError('TencentCloudAPI requires key.')
+        if model is None:
+            raise ValueError('TencentCloudAPI requires model.')
+        super().__init__(**kwargs)
+        self._host = host
+        self._path = path
+        self._key = key
+        self._model = model
+        self._timeout = timeout
+        self._kwargs = kwargs
+        self._cumulative_error = 0
+
+    def draw_sample(self, prompt: str | Any, *args, **kwargs) -> str:
+        """
+        Sends a request to the LLM and retrieves the generated response.
+
+        This method supports multiple input formats for backward compatibility:
+        1. Explicit 'messages' list via kwargs.
+        2. A message list passed directly as the 'prompt'.
+        3. Multimodal inputs (text + base64 images).
+        4. Simple string prompts.
+
+        Args:
+            prompt: The text prompt or a list of message dictionaries.
+            **kwargs: Can include 'image64s' (list of base64 strings) or 'messages'.
+
+        Returns:
+            The string content of the LLM's response.
+        """
+        image64s = kwargs.get('image64s', None)  # List[str]
+        messages_input = kwargs.get('messages', None)
+
+        # --- 1. Priority: Explicit messages list ---
+        if messages_input is not None:
+            if isinstance(messages_input, dict):
+                messages = [messages_input]
+            else:
+                messages = messages_input
+
+        # --- 2. Legacy Support: prompt passed as a pre-constructed list ---
+        elif not isinstance(prompt, str):
+            messages = prompt
+
+        # --- 3. Construction from String + Optional Images ---
+        else:
+            text_content = prompt.strip()
+
+            if image64s:
+                # Construct multimodal content structure
+                content = [{
+                    "type": "text",
+                    "text": text_content
+                }]
+                for image in image64s:
+                    content.append({
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/png;base64,{image}",
+                        }
+                    })
+                messages = [{'role': 'user', 'content': content}]
+
+            else:
+                # Construct standard text-only message
+                messages = [{'role': 'user', 'content': text_content}]
+
+        # Retry loop for handling network or API transient errors
+        while True:
+            try:
+                conn = http.client.HTTPSConnection(self._host, timeout=self._timeout)
+
+                # Prepare standard OpenAI-compatible payload
+                payload = json.dumps({
+                    'max_tokens': self._kwargs.get('max_tokens', 8192),
+                    'top_p': self._kwargs.get('top_p', None),
+                    'temperature': self._kwargs.get('temperature', 1.0),
+                    'model': self._model,
+                    'messages': messages
+                })
+                headers = {
+                    'Authorization': f'Bearer {self._key}',
+                    'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
+                    'Content-Type': 'application/json'
+                }
+                conn.request('POST', self._path, payload, headers)
+                res = conn.getresponse()
+                data = res.read().decode('utf-8')
+                data = json.loads(data)
+
+                # Extract content from the standard response format
+                response = data['choices'][0]['message']['content']
+                # Reset error counter on success
+                if self.debug_mode:
+                    self._cumulative_error = 0
+                return response
+
+            except Exception as e:
+                self._cumulative_error += 1
+
+                # In debug mode, crash after consecutive failures to allow debugging
+                if self.debug_mode:
+                    if self._cumulative_error == 10:
+                        raise RuntimeError(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                                           f'You may check your API host, path, API key, and model.')
+                else:
+                    print(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                          f'You may check your API host, path, API key, and model.')
+                    time.sleep(2)
+                continue
+
+
diff --git a/llm4ad/tools/llm/llm_api_volcengine.py b/llm4ad/tools/llm/llm_api_volcengine.py
new file mode 100644
index 00000000..2fc42fcb
--- /dev/null
+++ b/llm4ad/tools/llm/llm_api_volcengine.py
@@ -0,0 +1,155 @@
+# This file is part of the LLM4AD project (https://github.com/Optima-CityU/llm4ad).
+# Last Revision: 2026/7/5
+#
+# ------------------------------- Copyright --------------------------------
+# Copyright (c) 2025 Optima Group.
+#
+# Permission is granted to use the LLM4AD platform for research purposes.
+# All publications, software, or other works that utilize this platform
+# or any part of its codebase must acknowledge the use of "LLM4AD" and
+# cite the following reference:
+#
+# Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang,
+# Zhichao Lu, and Qingfu Zhang, "LLM4AD: A Platform for Algorithm Design
+# with Large Language Model," arXiv preprint arXiv:2412.17287 (2024).
+#
+# For inquiries regarding commercial use or licensing, please contact
+# http://www.llm4ad.com/contact.html
+# --------------------------------------------------------------------------
+
+from __future__ import annotations
+
+import http.client
+import json
+import time
+from typing import Any
+import traceback
+from ...base import LLM
+
+
+class VolcengineAPI(LLM):
+    def __init__(self, host='ark.cn-beijing.volces.com', key=None, model=None,
+                 path='/api/v3/chat/completions', timeout=60, **kwargs):
+        """Volcengine API
+        Args:
+            host   : host name. please note that the host name does not include 'https://'
+            key    : API key.
+            model  : LLM model name.
+            path   : API path for chat completions.
+            timeout: API timeout.
+        """
+        if key is None:
+            raise ValueError('VolcengineAPI requires key.')
+        if model is None:
+            raise ValueError('VolcengineAPI requires model.')
+        super().__init__(**kwargs)
+        self._host = host
+        self._path = path
+        self._key = key
+        self._model = model
+        self._timeout = timeout
+        self._kwargs = kwargs
+        self._cumulative_error = 0
+
+    def draw_sample(self, prompt: str | Any, *args, **kwargs) -> str:
+        """
+        Sends a request to the LLM and retrieves the generated response.
+
+        This method supports multiple input formats for backward compatibility:
+        1. Explicit 'messages' list via kwargs.
+        2. A message list passed directly as the 'prompt'.
+        3. Multimodal inputs (text + base64 images).
+        4. Simple string prompts.
+
+        Args:
+            prompt: The text prompt or a list of message dictionaries.
+            **kwargs: Can include 'image64s' (list of base64 strings) or 'messages'.
+
+        Returns:
+            The string content of the LLM's response.
+        """
+        image64s = kwargs.get('image64s', None)  # List[str]
+        messages_input = kwargs.get('messages', None)
+
+        # --- 1. Priority: Explicit messages list ---
+        if messages_input is not None:
+            if isinstance(messages_input, dict):
+                messages = [messages_input]
+            else:
+                messages = messages_input
+
+        # --- 2. Legacy Support: prompt passed as a pre-constructed list ---
+        elif not isinstance(prompt, str):
+            messages = prompt
+
+        # --- 3. Construction from String + Optional Images ---
+        else:
+            text_content = prompt.strip()
+
+            if image64s:
+                # Construct multimodal content structure
+                content = [{
+                    "type": "text",
+                    "text": text_content
+                }]
+                for image in image64s:
+                    content.append({
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/png;base64,{image}",
+                        }
+                    })
+                messages = [{'role': 'user', 'content': content}]
+
+            else:
+                # Construct standard text-only message
+                messages = [{'role': 'user', 'content': text_content}]
+
+        # Retry loop for handling network or API transient errors
+        while True:
+            try:
+                conn = http.client.HTTPSConnection(self._host, timeout=self._timeout)
+
+                # Prepare standard OpenAI-compatible payload
+                payload = json.dumps({
+                    'max_tokens': self._kwargs.get('max_tokens', 8192),
+                    'top_p': self._kwargs.get('top_p', None),
+                    'temperature': self._kwargs.get('temperature', 1.0),
+                    'model': self._model,
+                    'messages': messages
+                })
+                headers = {
+                    'Authorization': f'Bearer {self._key}',
+                    'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
+                    'Content-Type': 'application/json'
+                }
+                conn.request('POST', self._path, payload, headers)
+                res = conn.getresponse()
+                data = res.read().decode('utf-8')
+                data = json.loads(data)
+
+                # Extract content from the standard response format
+                response = data['choices'][0]['message']['content']
+                # Reset error counter on success
+                if self.debug_mode:
+                    self._cumulative_error = 0
+                return response
+
+            except Exception as e:
+                self._cumulative_error += 1
+
+                # In debug mode, crash after consecutive failures to allow debugging
+                if self.debug_mode:
+                    if self._cumulative_error == 10:
+                        raise RuntimeError(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                                           f'You may check your API host, path, API key, and model.')
+                else:
+                    print(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                          f'You may check your API host, path, API key, and model.')
+                    time.sleep(2)
+                continue
+
+
+class DoubaoAPI(VolcengineAPI):
+    """Alias for VolcengineAPI."""
+
diff --git a/llm4ad/tools/llm/llm_api_zhipu.py b/llm4ad/tools/llm/llm_api_zhipu.py
new file mode 100644
index 00000000..bf17437a
--- /dev/null
+++ b/llm4ad/tools/llm/llm_api_zhipu.py
@@ -0,0 +1,150 @@
+# This file is part of the LLM4AD project (https://github.com/Optima-CityU/llm4ad).
+# Last Revision: 2026/7/5
+#
+# ------------------------------- Copyright --------------------------------
+# Copyright (c) 2025 Optima Group.
+#
+# Permission is granted to use the LLM4AD platform for research purposes.
+# All publications, software, or other works that utilize this platform
+# or any part of its codebase must acknowledge the use of "LLM4AD" and
+# cite the following reference:
+#
+# Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang,
+# Zhichao Lu, and Qingfu Zhang, "LLM4AD: A Platform for Algorithm Design
+# with Large Language Model," arXiv preprint arXiv:2412.17287 (2024).
+#
+# For inquiries regarding commercial use or licensing, please contact
+# http://www.llm4ad.com/contact.html
+# --------------------------------------------------------------------------
+
+from __future__ import annotations
+
+import http.client
+import json
+import time
+from typing import Any
+import traceback
+from ...base import LLM
+
+
+class ZhipuAPI(LLM):
+    def __init__(self, host='open.bigmodel.cn', key=None, model=None,
+                 path='/api/paas/v4/chat/completions', timeout=60, **kwargs):
+        """Zhipu AI API
+        Args:
+            host   : host name. please note that the host name does not include 'https://'
+            key    : API key.
+            model  : LLM model name.
+            path   : API path for chat completions.
+            timeout: API timeout.
+        """
+        if key is None:
+            raise ValueError('ZhipuAPI requires key.')
+        if model is None:
+            raise ValueError('ZhipuAPI requires model.')
+        super().__init__(**kwargs)
+        self._host = host
+        self._path = path
+        self._key = key
+        self._model = model
+        self._timeout = timeout
+        self._kwargs = kwargs
+        self._cumulative_error = 0
+
+    def draw_sample(self, prompt: str | Any, *args, **kwargs) -> str:
+        """
+        Sends a request to the LLM and retrieves the generated response.
+
+        This method supports multiple input formats for backward compatibility:
+        1. Explicit 'messages' list via kwargs.
+        2. A message list passed directly as the 'prompt'.
+        3. Multimodal inputs (text + base64 images).
+        4. Simple string prompts.
+
+        Args:
+            prompt: The text prompt or a list of message dictionaries.
+            **kwargs: Can include 'image64s' (list of base64 strings) or 'messages'.
+
+        Returns:
+            The string content of the LLM's response.
+        """
+        image64s = kwargs.get('image64s', None)  # List[str]
+        messages_input = kwargs.get('messages', None)
+
+        # --- 1. Priority: Explicit messages list ---
+        if messages_input is not None:
+            if isinstance(messages_input, dict):
+                messages = [messages_input]
+            else:
+                messages = messages_input
+
+        # --- 2. Legacy Support: prompt passed as a pre-constructed list ---
+        elif not isinstance(prompt, str):
+            messages = prompt
+
+        # --- 3. Construction from String + Optional Images ---
+        else:
+            text_content = prompt.strip()
+
+            if image64s:
+                # Construct multimodal content structure
+                content = [{
+                    "type": "text",
+                    "text": text_content
+                }]
+                for image in image64s:
+                    content.append({
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/png;base64,{image}",
+                        }
+                    })
+                messages = [{'role': 'user', 'content': content}]
+
+            else:
+                # Construct standard text-only message
+                messages = [{'role': 'user', 'content': text_content}]
+
+        # Retry loop for handling network or API transient errors
+        while True:
+            try:
+                conn = http.client.HTTPSConnection(self._host, timeout=self._timeout)
+
+                # Prepare standard OpenAI-compatible payload
+                payload = json.dumps({
+                    'max_tokens': self._kwargs.get('max_tokens', 8192),
+                    'top_p': self._kwargs.get('top_p', None),
+                    'temperature': self._kwargs.get('temperature', 1.0),
+                    'model': self._model,
+                    'messages': messages
+                })
+                headers = {
+                    'Authorization': f'Bearer {self._key}',
+                    'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
+                    'Content-Type': 'application/json'
+                }
+                conn.request('POST', self._path, payload, headers)
+                res = conn.getresponse()
+                data = res.read().decode('utf-8')
+                data = json.loads(data)
+
+                # Extract content from the standard response format
+                response = data['choices'][0]['message']['content']
+                # Reset error counter on success
+                if self.debug_mode:
+                    self._cumulative_error = 0
+                return response
+
+            except Exception as e:
+                self._cumulative_error += 1
+
+                # In debug mode, crash after consecutive failures to allow debugging
+                if self.debug_mode:
+                    if self._cumulative_error == 10:
+                        raise RuntimeError(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                                           f'You may check your API host, path, API key, and model.')
+                else:
+                    print(f'{self.__class__.__name__} error: {traceback.format_exc()}.'
+                          f'You may check your API host, path, API key, and model.')
+                    time.sleep(2)
+                continue