diff --git a/.gitignore b/.gitignore
index 7a9c92b..0dd68f8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -146,3 +146,4 @@ debug*
 private*
 crazy_functions/test_project/pdf_and_word
 crazy_functions/test_samples
+request_llm/jittorllms
\ No newline at end of file
diff --git a/request_llm/bridge_jittorllms.py b/request_llm/bridge_jittorllms.py
new file mode 100644
index 0000000..28d0a7a
--- /dev/null
+++ b/request_llm/bridge_jittorllms.py
@@ -0,0 +1,153 @@
+
+from transformers import AutoModel, AutoTokenizer
+import time
+import threading
+import importlib
+from toolbox import update_ui, get_conf
+from multiprocessing import Process, Pipe
+
+load_message = "jittorllms尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，jittorllms消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
+
+#################################################################################
+class GetGLMHandle(Process):
+    def __init__(self):
+        super().__init__(daemon=True)
+        self.parent, self.child = Pipe()
+        self.jittorllms_model = None
+        self.info = ""
+        self.success = True
+        self.check_dependency()
+        self.start()
+        self.threadLock = threading.Lock()
+        
+    def check_dependency(self):
+        try:
+            import jittor
+            from .jittorllms.models import get_model
+            self.info = "依赖检测通过"
+            self.success = True
+        except:
+            self.info = r"缺少jittorllms的依赖，如果要使用jittorllms，除了基础的pip依赖以外，您还需要运行`pip install -r request_llm/requirements_jittorllms.txt`"+\
+                        r"和`git clone https://gitlink.org.cn/jittor/JittorLLMs.git --depth 1 request_llm/jittorllms`两个指令来安装jittorllms的依赖（在项目根目录运行这两个指令）。"
+            self.success = False
+
+    def ready(self):
+        return self.jittorllms_model is not None
+
+    def run(self):
+        # 子进程执行
+        # 第一次运行，加载参数
+        def load_model():
+            import types
+            try:
+                if self.jittorllms_model is None:
+                    device, = get_conf('LOCAL_MODEL_DEVICE')
+                    from .jittorllms.models import get_model
+                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    args_dict = {'model': 'chatglm', 'RUN_DEVICE':'cpu'}
+                    self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
+            except:
+                self.child.send('[Local Message] Call jittorllms fail 不能正常加载jittorllms的参数。')
+                raise RuntimeError("不能正常加载jittorllms的参数！")
+        
+        load_model()
+
+        # 进入任务等待状态
+        while True:
+            # 进入任务等待状态
+            kwargs = self.child.recv()
+            # 收到消息，开始请求
+            try:
+                for response, history in self.jittorllms_model.run_web_demo(kwargs['query'], kwargs['history']):
+                    self.child.send(response)
+            except:
+                self.child.send('[Local Message] Call jittorllms fail.')
+            # 请求处理结束，开始下一个循环
+            self.child.send('[Finish]')
+
+    def stream_chat(self, **kwargs):
+        # 主进程执行
+        self.threadLock.acquire()
+        self.parent.send(kwargs)
+        while True:
+            res = self.parent.recv()
+            if res != '[Finish]':
+                yield res
+            else:
+                break
+        self.threadLock.release()
+    
+global glm_handle
+glm_handle = None
+#################################################################################
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
+    """
+        多线程方法
+        函数的说明请见 request_llm/bridge_all.py
+    """
+    global glm_handle
+    if glm_handle is None:
+        glm_handle = GetGLMHandle()
+        if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + glm_handle.info
+        if not glm_handle.success: 
+            error = glm_handle.info
+            glm_handle = None
+            raise RuntimeError(error)
+
+    # jittorllms 没有 sys_prompt 接口，因此把prompt加入 history
+    history_feedin = []
+    history_feedin.append(["What can I do?", sys_prompt])
+    for i in range(len(history)//2):
+        history_feedin.append([history[2*i], history[2*i+1]] )
+
+    watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
+    response = ""
+    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+        if len(observe_window) >= 1:  observe_window[0] = response
+        if len(observe_window) >= 2:  
+            if (time.time()-observe_window[1]) > watch_dog_patience:
+                raise RuntimeError("程序终止。")
+    return response
+
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+    """
+        单线程方法
+        函数的说明请见 request_llm/bridge_all.py
+    """
+    chatbot.append((inputs, ""))
+
+    global glm_handle
+    if glm_handle is None:
+        glm_handle = GetGLMHandle()
+        chatbot[-1] = (inputs, load_message + "\n\n" + glm_handle.info)
+        yield from update_ui(chatbot=chatbot, history=[])
+        if not glm_handle.success: 
+            glm_handle = None
+            return
+
+    if additional_fn is not None:
+        import core_functional
+        importlib.reload(core_functional)    # 热更新prompt
+        core_functional = core_functional.get_core_functions()
+        if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
+        inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
+
+    # 处理历史信息
+    history_feedin = []
+    history_feedin.append(["What can I do?", system_prompt] )
+    for i in range(len(history)//2):
+        history_feedin.append([history[2*i], history[2*i+1]] )
+
+    # 开始接收jittorllms的回复
+    response = "[Local Message]: 等待jittorllms响应中 ..."
+    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+        chatbot[-1] = (inputs, response)
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    # 总结输出
+    if response == "[Local Message]: 等待jittorllms响应中 ...":
+        response = "[Local Message]: jittorllms响应异常 ..."
+    history.extend([inputs, response])
+    yield from update_ui(chatbot=chatbot, history=history)
diff --git a/request_llm/requirements_jittorllms.txt b/request_llm/requirements_jittorllms.txt
new file mode 100644
index 0000000..3713ce8
--- /dev/null
+++ b/request_llm/requirements_jittorllms.txt
@@ -0,0 +1,4 @@
+jittor >= 1.3.7.9
+jtorch >= 0.1.3
+torch
+torchvision
\ No newline at end of file
diff --git a/request_llm/test_llms.py b/request_llm/test_llms.py
new file mode 100644
index 0000000..d043d62
--- /dev/null
+++ b/request_llm/test_llms.py
@@ -0,0 +1,26 @@
+"""
+对各个llm模型进行单元测试
+"""
+def validate_path():
+    import os, sys
+    dir_name = os.path.dirname(__file__)
+    root_dir_assume = os.path.abspath(os.path.dirname(__file__) +  '/..')
+    os.chdir(root_dir_assume)
+    sys.path.append(root_dir_assume)
+    
+validate_path() # validate path so you can run from base directory
+
+from request_llm.bridge_jittorllms import predict_no_ui_long_connection
+
+llm_kwargs = {
+    'max_length': 512,
+    'top_p': 1,
+    'temperature': 1,
+}
+
+result = predict_no_ui_long_connection(inputs="你好", 
+                                       llm_kwargs=llm_kwargs,
+                                       history=[],
+                                       sys_prompt="")
+
+print('result')
\ No newline at end of file