Update app.py

app.py

@@ -1,15 +1,41 @@
+# !/usr/bin/python
+# -*- coding: utf-8 -*-
+# @time    : 2021/2/29 21:41
+# @author  : Mo
+# @function: 文本纠错, 使用macro-correct
+
+
+import os
+os.environ["MACRO_CORRECT_FLAG_CSC_TOKEN"] = "1"
+from macro_correct import correct
 import gradio as gr
-from huggingface_hub import InferenceClient
+
+
+### 默认纠错(list输入)
+text_list = ["真麻烦你了。希望你们好好的跳无",
+             "少先队员因该为老人让坐",
+             "机七学习是人工智能领遇最能体现智能的一个分知",
+             "一只小鱼船浮在平净的河面上"
+             ]
+text_csc = correct(text_list)
+print("默认纠错(list输入):")
+for res_i in text_csc:
+    print(res_i)
+print("#" * 128)
 
 """
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+默认纠错(list输入):
+{'index': 0, 'source': '真麻烦你了。希望你们好好的跳无', 'target': '真麻烦你了。希望你们好好地跳舞', 'errors': [['的', '地', 12, 0.6584], ['无', '舞', 14, 1.0]]}
+{'index': 1, 'source': '少先队员因该为老人让坐', 'target': '少先队员应该为老人让坐', 'errors': [['因', '应', 4, 0.995]]}
+{'index': 2, 'source': '机七学习是人工智能领遇最能体现智能的一个分知', 'target': '机器学习是人工智能领域最能体现智能的一个分支', 'errors': [['七', '器', 1, 0.9998], ['遇', '域', 10, 0.9999], ['知', '支', 21, 1.0]]}
+{'index': 3, 'source': '一只小鱼船浮在平净的河面上', 'target': '一只小鱼船浮在平静的河面上', 'errors': [['净', '静', 8, 0.9961]]}
 """
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
 
 
 def respond(
     message,
-    history: list[tuple[str, str]],
+    history,
     system_message,
     max_tokens,
     temperature,
@@ -24,20 +50,27 @@ def respond(
             messages.append({"role": "assistant", "content": val[1]})
 
     messages.append({"role": "user", "content": message})
-
     response = ""
+    message_csc = correct([message])
+    target = message_csc[0].get("target", "")
+    errors = message_csc[0].get("errors", "")
+    response = target + " " + str(errors)
+    for resp in response:
+        yield resp
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
+    # response = ""
+    #
+    # for message in client.chat_completion(
+    #     messages,
+    #     max_tokens=max_tokens,
+    #     stream=True,
+    #     temperature=temperature,
+    #     top_p=top_p,
+    # ):
+    #     token = message.choices[0].delta.content
+    #
+    #     response += token
+    #     yield response
 
 
 """
@@ -46,19 +79,24 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+        gr.Textbox(value="Macro-Correct", label="System message"),
+        # gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        # gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        # gr.Slider(
+        #     minimum=0.1,
+        #     maximum=1.0,
+        #     value=0.95,
+        #     step=0.05,
+        #     label="Top-p (nucleus sampling)",
+        # ),
+],
+    title="Chinese Spelling Correction Model Macropodus/macbert4csc_v2",
+    description="Copy or input error Chinese text. Submit and the machine will correct text.",
+    article="Link to <a href='https://github.com/yongzhuo/macro-correct' style='color:blue;' target='_blank\'>Github REPO: macro-correct</a>",
+
 )
 
 
 if __name__ == "__main__":
     demo.launch()
+    # demo.launch(server_name="0.0.0.0", server_port=8087, share=False, debug=True)