diff --git a/python/examples/fit_a_line/local_train.py b/python/examples/fit_a_line/local_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..699ad7b67d5bb2a8f8937418a002e19991058473
--- /dev/null
+++ b/python/examples/fit_a_line/local_train.py
@@ -0,0 +1,36 @@
+import sys
+import paddle
+import paddle.fluid as fluid
+
+train_reader = paddle.batch(paddle.reader.shuffle(
+    paddle.dataset.uci_housing.train(), buf_size=500), batch_size=16)
+
+test_reader = paddle.batch(paddle.reader.shuffle(
+    paddle.dataset.uci_housing.test(), buf_size=500), batch_size=16)
+
+x = fluid.data(name='x', shape=[None, 13], dtype='float32')
+y = fluid.data(name='y', shape=[None, 1], dtype='float32')
+
+y_predict = fluid.layers.fc(input=x, size=1, act=None)
+cost = fluid.layers.square_error_cost(input=y_predict, label=y)
+avg_loss = fluid.layers.mean(cost)
+sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.01)
+sgd_optimizer.minimize(avg_loss)
+
+place = fluid.CPUPlace()
+feeder = fluid.DataFeeder(place=place, feed_list=[x, y])
+exe = fluid.Executor(place)
+exe.run(fluid.default_startup_program())
+
+import paddle_serving_client.io as serving_io
+
+for pass_id in range(30):
+    for data_train in train_reader():
+        avg_loss_value, = exe.run(
+            fluid.default_main_program(),
+            feed=feeder.feed(data_train),
+            fetch_list=[avg_loss])
+
+serving_io.save_model(
+    "serving_server_model", "serving_client_conf",
+    {"x": x}, {"y": y_predict}, fluid.default_main_program())
diff --git a/python/examples/fit_a_line/test_client.py b/python/examples/fit_a_line/test_client.py
new file mode 100644
index 0000000000000000000000000000000000000000..e4aa9cd51b953349b88e8ff707ac7ad2bea168f7
--- /dev/null
+++ b/python/examples/fit_a_line/test_client.py
@@ -0,0 +1,15 @@
+from paddle_serving_client import Client
+import paddle
+import sys
+
+client = Client()
+client.load_client_config(sys.argv[1])
+client.connect(["127.0.0.1:9292"])
+
+test_reader = paddle.batch(paddle.reader.shuffle(
+    paddle.dataset.uci_housing.test(), buf_size=500), batch_size=1)
+
+for data in test_reader():
+    fetch_map = client.predict(feed={"x": data[0][0]}, fetch=["y"])
+    print("{} {}".format(fetch_map["y"][0], data[0][1][0]))
+    
diff --git a/python/examples/fit_a_line/test_server.py b/python/examples/fit_a_line/test_server.py
new file mode 100644
index 0000000000000000000000000000000000000000..e77c5fb6a4842bbc455193c67d8494ee6231c90f
--- /dev/null
+++ b/python/examples/fit_a_line/test_server.py
@@ -0,0 +1,19 @@
+import os
+import sys
+from paddle_serving_server import OpMaker
+from paddle_serving_server import OpSeqMaker
+from paddle_serving_server import Server
+
+op_maker = OpMaker()
+read_op = op_maker.create('general_reader')
+general_infer_op = op_maker.create('general_infer')
+
+op_seq_maker = OpSeqMaker()
+op_seq_maker.add_op(read_op)
+op_seq_maker.add_op(general_infer_op)
+
+server = Server()
+server.set_op_sequence(op_seq_maker.get_op_sequence())
+server.load_model_config(sys.argv[1])
+server.prepare_server(workdir="work_dir1", port=9292, device="cpu")
+server.run_server()
diff --git a/python/paddle_serving_client/io/__init__.py b/python/paddle_serving_client/io/__init__.py
index f3c41d7625d0e444d3ab5b584bb1b2d775700612..8faab294ac33f18d257a5b13ca8e68326c342418 100644
--- a/python/paddle_serving_client/io/__init__.py
+++ b/python/paddle_serving_client/io/__init__.py
@@ -71,6 +71,10 @@ def save_model(server_model_folder,
         fout.write(str(config))
     with open("{}/serving_server_conf.prototxt".format(server_model_folder), "w") as fout:
         fout.write(str(config))
+    with open("{}/serving_client_conf.stream.prototxt".format(client_config_folder), "wb") as fout:
+        fout.write(config.serialize_to_string())
+    with open("{}/serving_server_conf.stream.prototxt".format(server_model_folder), "wb") as fout:
+        fout.write(config.serialize_to_string())