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| # !/usr/bin/env python | |
| # -*- coding:utf-8 -*- | |
| # ================================================================== | |
| # [CreatedDate] : Thursday, 1970-01-01 08:00:00 | |
| # [Author] : shixiaofeng | |
| # [Descriptions] : | |
| # ================================================================== | |
| # [ChangeLog]: | |
| # [Date] [Author] [Comments] | |
| # ------------------------------------------------------------------ | |
| import json | |
| import logging | |
| import time | |
| import gradio as gr | |
| import requests | |
| logger = logging.getLogger('gradio') | |
| gr.close_all() | |
| host = "127.0.0.1:9172" | |
| def tableqa(input_question, history=""): | |
| logger.info("run tableqa") | |
| if history == "": | |
| history_sql = None | |
| else: | |
| history_sql = json.loads(history.replace("\'", "\"")) | |
| data = {"raw_data": {'question': input_question, 'history_sql': history_sql}} | |
| ts = time.time() | |
| r = requests.post(f"http://{host}/tableqa", json=data) | |
| response = json.loads(r.text) | |
| print("response", response) | |
| te = time.time() | |
| print("run inference_mask_sam success [{}], time_Cost is [{}]".format(response["code"] == 200, te-ts)) | |
| if response["code"] == 200: | |
| df_value = response["result"]["select_df"] | |
| df = {"data": df_value["rows"], "headers": df_value["header_name"]} | |
| return [df, response["result"]["sql_string"], response["result"]["sql_query"], response["result"]["history"], response["result"]["query_result"]] | |
| else: | |
| return ["1", "2", "3", "4",] | |
| example_iface = [ | |
| ["长江流域的小型水库的库容总量是多少？", ""], | |
| ["那平均值是多少？", "{'agg': [5], 'cond_conn_op': 1, 'conds': [[3, 2, '小型'], [4, 2, '长江']], 'from': ['reservoir'], 'sel': [2]}"], | |
| ["那水库的名称呢？", "{'agg': [1], 'cond_conn_op': 1, 'conds': [[3, 2, '小型'], [4, 2, '长江']], 'from': ['reservoir'], 'sel': [2]}"], | |
| ["汕尾市的水库有吗", "{'agg': [0], 'cond_conn_op': 1, 'conds': [[3, 2, '小型'], [4, 2, '长江']], 'from': ['reservoir'], 'sel': [0]}"], | |
| ["", ""], | |
| ["上个月收益率超过3的有几个基金？", ""], | |
| ["这是哪只基金呢？并且它什么类型的呢？", "{'agg': [4], 'cond_conn_op': 0, 'conds': [[5, 0, '3']], 'from': ['fund'], 'sel': [1]}"], | |
| ["", ""], | |
| ["有哪些型号的SUV油耗高于8？", ""], | |
| ["他们是多大排量的", "{'agg': [0], 'cond_conn_op': 1, 'conds': [[1, 2, 'suv'], [2, 0, '8']], 'from': ['car'], 'sel': [0]}"], | |
| ["", ""], | |
| ["本部博士生中平均身高是多少？", ""], | |
| ["他们是什么专业的?", "{'agg': [1], 'cond_conn_op': 1, 'conds': [[2, 2, '博士'], [7, 2, '本部']], 'from': ['student'], 'sel': [5]}"] | |
| ] | |
| # iface = gr.Interface(fn=greet, inputs="text", outputs=["输出sql语句","输出可执行sql语句","执行结果"]) | |
| iface = gr.Interface(fn=tableqa, inputs=[gr.Textbox(label="input_question", info="请输入想要查询的问题."), | |
| gr.Textbox(label="history sql", info="上下文对话历史信息.")], | |
| outputs=[gr.DataFrame(label="索引到的数据库"), | |
| gr.Textbox(label="输出sql语句"), | |
| gr.Textbox(label="输出可执行sql语句"), | |
| gr.Textbox(label="多轮对话历史sql"), | |
| gr.Textbox(label="SQL执行结果")], | |
| examples=example_iface, | |
| examples_per_page=len(example_iface), | |
| allow_flagging="auto", | |
| cache_examples=True, | |
| description="<p> \ | |
| Choose an example below 🔥 🔥 🔥 \ | |
| Or, give question by yourself: <br>\ | |
| </p>", | |
| ) | |
| title = "TableChat: Chat Model deployment on Table <br>" | |
| demo = gr.TabbedInterface([iface], ['TableChat_V0'], title=title) | |
| # iface.launch(enable_queue=False, server_name="0.0.0.0", server_port=9176, debug=True) | |
| demo.launch(enable_queue=False, server_name="0.0.0.0", server_port=9176, share=True) | |